CambridgeBiologyforNSWSampleChapter

Evan Roberts

Tammy Heath

Sherine Metira

Cambridge

Biology

for NSW Stage 6

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Chapter

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How to use this resource

Syllabus coverage

Syllabus content dot points at the start of each section outline what you can expect to learn. They are numbered by section, for clear mapping and reference, and are linked to the success criteria checklist at the end of each chapter.

Learning tools

Practical colour-coding makes it easy for you to find different types of activities and learning support.

Glossary definitions appear in the margin where the key term first appears in the chapter.

SKILLS

Skills boxes reinforce key biological skills, such as analysing data or interpreting phylogenetic trees.

ACTIVITY

Activities can include secondary-source investigations, modelling, data analysis, classroom activities and more.

PRACTICAL

Practicals focus on developing Working scientifically skills. Every practical is also included in the digital workbook as a worksheet that can be completed online or downloaded.

Links to the Interactive Textbook

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CambridgeBiologyforNSW

Chapterreview

How to use this resource

Exam practice and revision tools

Reviseandconsolidateyourlearningwiththeseonlinetools:

• Chaptersummaries(download)

• Depthstudysupport(download)

• Reviewquestions:answeronlineordownload

• Successcriteriachecklist:viewonlineordownload

ManagementSystemfeatures:

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EXAM PRACTICE

• Assigntasksandtrackresults

• Individualandwholeclassreports

TeacherscanaccesstheseadditionaldownloadableresourcesandLearning

• Create(andprint)custompracticeexams

• Chaptertests(download)

Success

Describethestructureandfunctionofthecapsule,cellwall,cell pilimembrane,cytoplasm,nucleoid,plasmid,ribosomes,flagellaand inprokaryoticcells

Exam practice boxes at the end of every section include an exam-style question, a breakdown of what the question is asking, marking criteria and a sample response to help you become familiar with how to approach exam questions.

You will also find a video walkthrough for every exam practice box in the Interactive Textbook.

CHAPTER REVIEW

Describethestructureandfunctionofthecellwall,cellmembrane, cytoplasm,nucleus,mitochondria,chloroplast,endoplasmic reticulum,Golgibody,ribosomes,lysosomesandvacuolein

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Exam-style chapter reviews include multiple choice questions and exam-style written response questions. These questions can be answered in workspaces or downloaded in the Interactive Textbook.

The chapter review questions are linked to syllabus content dot points in the success criteria checklist, allowing students to monitor their progress.

A downloadable version is available in the Interactive Textbook.

SECTION REVIEW

A set of review questions provide opportunities for revision at the end of every section and are also available in the Interactive Textbook.

Auto-marked quizzes provide instant feedback on your progress.

Questions can be completed online in workspaces, which include selfassessment functionality.

Using the Interactive Textbook

• Prior knowledge quiz: Complete an automarked quiz on Stage 4 and 5 Science prior knowledge before starting a chapter. Depending on your score, you may be provided with content from earlier years for revision.

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• Workspaces: You can answer questions online by typing, inserting mathematical symbols, drawing or uploading. Self-assessment tools enable you to check your answers and mark your own work (if your teacher has provided access to suggested solutions).

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Using the Online Teaching Suite

For your teacher

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Using the digital workbook

A complete digital workbook is included in your Interactive Textbook.

Download the workbook as a whole resource from the Interactive Textbook OR download individual worksheets from within each chapter.

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• all practicals from the print book with plenty of space for recording your results and answers

• at least one worksheet per section that can be completed digitally or printed for in-class and homework use.

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Assessment tools

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Access in-platform support from the bottom right of your screen.

About the authors

Evan Roberts

Evan Roberts is a Science and HSC Biology teacher with more than 15 years’ experience teaching secondary students in public and independent schools. He lectures in education at the University of Sydney. Evan is an experienced author of several science education resources, including Cambridge Science for the NSW Syllabus 4 and the award-winning Cambridge Science for the Victorian Curriculum Years 7 and 8 first editions. His work focuses on evidence-informed practice and the design of accessible resources that cultivate curiosity, student agency and deep learning in science.

Tammy Heath

With extensive experience in the NSW Catholic and Independent sectors, Tammy Heath has taught Senior Biology, Chemistry and Physics in both rural and Sydney settings, and has over 10 years’ experience as an HSC Biology exam marker. Drawing on a professional background in microbiology and environmental science, she integrates real-world expertise into the HSC and IB curricula, and is dedicated to inspiring a genuine passion for Biology in her students.

Sherine Metira

Sherine Metira is a science educator and academic leader with nearly two decades of teaching experience, including HSC Biology and Chemistry. She has taught across several schools in New South Wales and is driven by a deep belief in the transformative power of education. Sherine is committed to inspiring curiosity, critical thinking and a love of scientific discovery in young people. She enjoys empowering students to see science as a tool for understanding and shaping the world around them.

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The publisher would like to thank Christine Charlton, Luke Colella, Dr Gemma Dale, Dr Simon Crook, Steph McDougall and Ashley Suter for reviewing and contributing to this resource. Special thanks to Alison Quin for her review of Indigenous inclusions.

AREA

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Working scientifically

SYLLABUS OUTCOMES

A student:

• develops and evaluates questions and hypotheses for scientific investigations

• designs and evaluates scientific investigations

• conducts scientific investigations to collect data and information

• selects and processes qualitative and quantitative data and information

• analyses and evaluates primary and secondary data and information

• uses scientific processes to solve scientific problems

• communicates scientific arguments using evidence, scientific language and terminology for a specific audience

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CHAPTERS

1. Working scientifically

Enhance your learning with these integrated online resources:

Students

Digital workbook

• Prior knowledge quiz

• Suggested responses

• Download or answer questions online

Videos

Teachers

• Chapter tests

• Exam generator tool

• Planning documents

SYLLABUS

CONTENT DOT POINTS: WORKING SCIENTIFICALLY

At the end of this chapter, I will be able to:

1A.1 Use observations and scientific knowledge and understanding to propose questions and hypotheses for scientific investigations involving primary and secondary data

1A.2 Evaluate questions and hypotheses based on scientific knowledge

1A.3 Modify questions and hypotheses to reflect new evidence

1B.1 Justify the use of independent, dependent and controlled variables, and experimental controls in a valid scientific investigation

1B.2 Explain how reliable primary data is obtained

1B.3 Assess the reliability of secondary data and information when planning

1B.4 Assess potential hazards and their associated risks to develop a risk assessment

1B.5 Select appropriate materials and technologies to design a scientific investigation

1B.6 Discuss ethical issues in the development and use of scientific knowledge

1C.1 Apply safe work practices and manage risks while conducting a scientific investigation

1C.2 Construct and manipulate identified materials and technologies to perform scientific investigations

1C.3 Use equipment appropriately and systematically to collect and record data, information, evidence and findings

1C.4 Gather data and information from a range of secondary sources

1D.1 Select qualitative and quantitative information from texts, diagrams, flow charts, tables, databases, graphs and multimedia resources

1D.2 Apply quantitative processes to data, including unit conversions

1D.3 Select and use a range of representations to organise data and information, including graphs, keys, models, diagrams, tables and spreadsheets

SECTION

1A Questioning and predicting

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1B Planning scientific investigations

1D.4 Extract data and information from a wide range of sources and acknowledge these sources using an accepted referencing style

1D.5 Describe the Cultural Knowledges and observations of Aboriginal and Torres Strait Islander Peoples and examine how these contribute to the development of scientific knowledge

1E.1 Describe qualitative and quantitative relationships between variables

1E.2 Explain patterns and trends, including inconsistencies in data and information

1E.3 Assess error, uncertainty and limitations in data and include calculations of percentage error, range, mean and standard deviation

1E.4 Assess the validity, reliability, accuracy and precision of data and information

1E.5 Interpret data and information to identify outliers, make predictions, explain results and draw conclusions

1C Conducting scientific investigations

1D Processing data and information

1E.6 Evaluate data and information to suggest improvements or further investigations

1E Analysing data and information

CONTENT DOT POINTS: WORKING SCIENTIFICALLY

At the end of this chapter, I will be able to:

1F.1 Apply scientific principles to address real-world applications and problems

1F.2 Use modelling and cause-and-effect relationships, including mathematical examples, to make predictions, explain phenomena and solve problems

1F.3 Evaluate and modify a scientific investigation in response to new evidence

1F.4 Explain why current scientific knowledge is both contestable and testable by further inquiry

1G.1 Construct evidence-based arguments and recognise the role of peer review in the evaluation of scientific practices, solutions or conclusions

1G.2 Select and use appropriate digital, visual, written and oral media to convey scientific arguments

1G.3 Apply appropriate scientific notations, language and nomenclature

1G.4 Use evidence and correct scientific language and terminology to address a specific audience and purpose in a variety of contexts

SECTION

1F Problem-solving in Biology

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1G Communicating in Biology

GLOSSARY TERMS

Aboriginal and Torres Strait Islander Peoples absolute uncertainty accuracy binomial nomenclature calibration cause-and-effect contestable controlled variable correlation Country cultural humility Cultural Knowledge data dependent variable dichotomous key ethical evidence evidence-based argument extrapolate hazard hypothesis independent variable Indigenous Cultural and Intellectual Property

Indigenous Data Sovereignty interpolate investigable question model outlier

parallax error peer review precision primary data qualitative data quantitative data random error reading error reflexivity relative uncertainty reliability repeatability replicability reproducibility sample size scientific investigation scientific notation scientific principle secondary data sensitivity

SI units (International System of Units) spontaneous generation standard deviation systematic error testable uncertainty validity

zero calibration error

Concept map

1A Questioning and predicting

Develop and evaluate questions and hypotheses for scientific investigations

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1G Communicating in Biology

Communicate scientific arguments using evidence, scientific language and terminology for a specific audience

1B Planning scientific investigations

Design and evaluate scientific investigations

1F Problem-solving in Biology

Use scientific processes to solve scientific problems

1C Conducting scientific investigations

Conduct scientific investigations to collect data and information

1E Analysing data and information

Analyse and evaluate primary and secondary data and information

1D Processing data and information

Select and process qualitative and quantitative data and information

Worksheet 1A.1

1A Questioning and predicting

SYLLABUS

At the end of this section, I will be able to:

Questioning and predicting questions download word download pdf

1A.1 Use observations and scientific knowledge and understanding to propose questions and hypotheses for scientific investigations involving primary and secondary data

1A.2 Evaluate questions and hypotheses based on scientific knowledge

1A.3 Modify questions and hypotheses to reflect new evidence

scientific investigation

a scientific process of answering a question, exploring an idea or solving a problem, which requires activities such as planning a course of action, collecting data, reaching a conclusion and communicating these activities; can include practical and/or secondary-source data or information

data information gathered through observations, measurements, study or analysis

hypothesis a suggested explanation or prediction of a scientific problem that can be tested with an investigation evidence data or information that supports or refutes a hypothesis investigable question a question that can be answered by conducting a scientific investigation

testable able to be investigated and verified through experimentation

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A scientific investigation always begins with a question. The kind of question a scientist asks shapes the design of their experiment, the data they collect and the conclusions they draw. A good question is not random; it is based on careful observations and existing scientific knowledge. From this question, a hypothesis is developed and tested, leading to new evidence and discoveries.

This section will guide you through the process of developing and evaluating questions and hypotheses so you can work scientifically with confidence.

Investigable and non-investigable questions

Not all questions can be answered through scientific investigation. Some are too broad, subjective or abstract. Investigable questions are those that can be answered through experimentation. They are specific, measurable and testable

Example of an investigable question:

How does light intensity affect the growth of plants?

• Independent variable – light intensity (can be manipulated)

• Dependent variable – plant growth (can be measured)

Non-investigable questions cannot be directly tested through experiments. Examples of a non-investigable question are: Why are plants important? and What is the best type of music?

To decide whether a question is suitable for investigation, apply the criteria outlined in Table 1A.1.

Table 1A.1 Criteria used to determine whether a question is investigable

CriteriaDescription

SpecificThe question must be clear and unambiguous, allowing systematic investigation.

TestableIt must be possible to collect measurable data to answer the question.

RelevantThe question should address an important issue or problem in science.

FeasibleThe investigation must be possible with the available resources, time and budget.

Novel Ideally, the question offers a new approach or perspective.

From observations to questions

Scientific questions often arise from observations: noticing patterns, anomalies or changes in the natural world. These observations are combined with existing scientific knowledge to propose clear, investigable questions.

• Primary data is information you collect yourself through experiments or fieldwork.

• Secondary data is information from existing sources, such as research papers, textbooks or reliable databases.

Developing hypotheses

A hypothesis is a tentative explanation or prediction that can be tested. It links the independent variable and the dependent variable in a way that can be measured.

Structure of a hypothesis

If [independent variable] is changed, then [dependent variable] will change, because [scientific reasoning].

WORKED EXAMPLE 1A.1

Developing a hypothesis

Observation: Plants near windows grow taller than those in darker corners.

From this observation, formulate a hypothesis that links the dependent and independent variables.

Solution

Question: Does the amount of light affect plant height?

Scientific reasoning: Plants require exposure to light energy to grow, because light is required for photosynthesis.

Dependent variable: growth rate of plants

Independent variable: amount of light

Hypothesis: If the amount of light increases, then the growth rate of plants will increase, because light provides the energy needed for photosynthesis.

Explanation

Pose a question based on your observations.

Identify the scientific reasoning behind the observation, based on your prior knowledge or research.

Identify the dependent and independent variables.

State the hypothesis, including links the dependent and independent variables.

primary data information you collect yourself through experiments or fieldwork secondary data information from existing sources; for example, research papers, textbooks and reliable databases

independent variable the variable that is deliberately changed, often through a series of pre-set values dependent variable the factor in an experiment that changes in response to changes to the independent variable

Evaluating questions and hypotheses

Once a question or hypothesis is proposed, it needs to be evaluated. Consider the following:

• Is the question testable with the available equipment and time?

• Is it relevant to the learning goal or scientific problem?

• Does it align with current scientific knowledge?

• Is it specific and measurable, avoiding vague or subjective terms?

Example evaluation:

• Question: Does temperature affect enzyme activity?

• Testable: yes, temperature can be changed and enzyme activity measured.

• Relevant: yes, enzymes are central to biology.

• Feasible: yes, with lab equipment such as test-tubes, stopwatch and living tissue containing the relevant enzyme.

• Scientific knowledge: consistent with known enzyme properties.

ACTIVITY 1A.1

Proposing a testable hypothesis

Known information about factors affecting enzyme activity allows a question to be turned into a testable hypothesis.

Substrate concentration: as an enzyme becomes saturated with substrate, the rate of reaction becomes constant.

Substrate concentration

Enzyme concentration Figure 1A.1 Known information about factors affecting enzyme activity What testable hypotheses can be derived from this information on enzymes?

Modifying questions and hypotheses

Science is not static. As new evidence emerges, questions and hypotheses may need to be refined. This ensures that investigations remain accurate and aligned with the most current understanding.

For example:

• Initial hypothesis: If fertiliser is added to soil, plants will always grow taller.

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• New evidence: Some plants showed stunted growth when too much fertiliser was added.

• Modified hypothesis: If fertiliser is added in moderate amounts, then plants will grow taller, because nutrients support growth, but excessive fertiliser may harm roots.

How can secondary data refine a hypothesis?

In addition to conducting first-hand investigations, scientists also analyse secondary data information produced by other researchers through previously completed scientific studies. Secondary sources, such as peer-reviewed journal articles, textbooks, scientific databases and government reports, provide established findings that help scientists refine existing hypotheses or generate new ones. By reviewing this broader evidence base, scientists can identify patterns, inconsistencies, limitations or additional variables they may not have originally considered.

Extensive reading of relevant scientific literature helps ensure that any developing hypothesis is accurate, relevant and scientifically defensible. Because secondary data is produced by external researchers, it must be acknowledged appropriately using a formal referencing style, such as Harvard or APA. This maintains academic integrity and allows other scientists to trace the origin of the information.

To extract and apply secondary data effectively, scientists follow four key steps.

1. Read to ensure the source relates directly to the investigation or research question. Scientists critically assess whether the secondary study explores similar variables, methodologies or biological principles. Only relevant sources should be used in developing a hypothesis.

2. Summar ise the data using structured scientific writing (e.g. write a TEEL paragraph – this method is explained in Skills 1A.1).

Summar ising allows scientists to condense complex data into clear, meaningful statements that support or challenge their current thinking. TEEL ensures clarity, logic and appropriate use of evidence.

3. Check the discussion and conclusion to ensure that any errors or limitations identified in the secondary investigation are accounted for in your own experimental design.

Discussions and conclusions often reveal biases, methodological weaknesses, sampling limitations or uncontrolled variables in the original study. By analysing these limitations, scientists can avoid repeating the same errors, and design a more reliable and valid investigation.

4. Construct and record a complete reference acknowledging the source. All secondary data must be referenced using an accepted format. For example, Harvard style includes the following information:

Author, Year, Title, Publisher/Website, Access date

Correct referencing credits the original researcher and ensures transparency within the scientific community.

SKILLS 1A.1

Writing a TEEL paragraph

TEEL is a framework that helps structure scientific writing so it is clear, logical and supported by evidence.

Letter

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Meaning

T – Topic sentenceIntroduces the main idea

Purpose

States what the paragraph will discuss

E – EvidenceData from primary or secondary sourcesDemonstrates credibility

E – ExplanationInterprets the evidence Shows how the evidence supports the argument

L – Link Connects back to the question or hypothesis Ensures coherence

Summary of questioning and predicting

• Good scientific investigations start with clear, specific and testable questions.

• Questions are informed by both observations and existing knowledge.

• Hypotheses predict outcomes and are evaluated for feasibility and scientific relevance.

• As evidence changes, so too must our questions and hypotheses. By mastering questioning and predicting, you lay the foundation for strong and meaningful scientific investigations.

SECTION 1A REVIEW

1. What is the difference between an investigable question and a non-investigable question? Provide one example of each.

2. Write a hypothesis for the question: Does temperature affect the rate of yeast fermentation?

3. How can secondary data help refine a scientific question?

4. Give an example of how new evidence might lead to modification of a hypothesis.

5. Why is it important to analyse data from secondary sources for limitations?

1B Planning scientific investigations

SYLLABUS

At the end of this section, I will be able to:

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1B.1 Justify the use of independent, dependent and controlled variables, and experimental controls in a valid scientific investigation

1B.2 Explain how reliable primary data is obtained

1B.3 Assess the reliability of secondary data and information when planning

1B.4 Assess potential hazards and their associated risks to develop a risk assessment

1B.5 Select appropriate materials and technologies to design a scientific investigation

1B.6 Discuss ethical issues in the development and use of scientific knowledge

Scientific investigations are the foundation of evidence-based knowledge. A welldesigned investigation allows scientists to collect reliable data, evaluate evidence and form valid conclusions. This section explores how to plan, justify and assess a scientific investigation to ensure it is reliable, ethical and safe.

Variables and experimental controls

Understanding variables

In any investigation, the variables must be clearly identified and controlled to ensure the results are valid.

• The independent variable is the factor that is deliberately changed by the experimenter.

• The dependent variable is the factor that is measured or observed as it changes in response to changes in the independent variable.

• Controlled variables are factors that are kept constant to ensure that the effect on the dependent variable is due to changes in the independent variable alone (i.e. in order to run a fair test).

Example of investigation variables

For example, in an investigation examining the effect of light intensity on plant growth:

• independent variable = light intensity

• dependent variable = plant growth (e.g. height, number of leaves)

• controlled variables = type of plant, soil, amount of water, temperature.

Experimental controls

An experimental control is a set-up in which the independent variable is not applied – this provides a baseline for comparison against all other experimental conditions. The control allows the scientist to determine whether any observed changes in the dependent variable are truly caused by the manipulated factor.

In some investigations, scientists also use positive and negative controls to strengthen the reliability of their results. A positive control is a condition where a known response is expected; for example, plants grown in normal light should show healthy growth, confirming that the experimental set-up is functioning correctly. In contrast, a negative control is a condition where no response is expected – for example, plants grown in no light should not grow or should show minimal growth.

that

By comparing experimental groups (e.g. plants in high or low light) against both positive and negative controls, you will gain a clearer understanding of how light intensity influences plant growth and will be better able to identify whether your results are valid and biologically meaningful.

ACTIVITY 1B.1

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Designing an experiment

Design an investigation to test the effect of temperature on yeast fermentation. Identify your independent, dependent and controlled variables, and describe the control set-up.

Capillary tube

Limewater

Obtaining reliable primary data

Primary data is data you collect directly through observation, measurement or experimentation. When planning an investigation, the experimenter must consider what type of data is being collected, and what tools will be used to collect this data. The data you collect may be qualitative or quantitative

To ensure that your data is recorded accurately, consider the following points:

• A results table has been designed to accurately record findings with regards to the independent and dependent variables.

• The data being recorded is exactly as measured.

• The scientific equipment used to gather the data is precise to ensure accuracy.

Identifying types of data to collect

Different investigations require different types of data. Qualitative data is descriptive, such as noting the colour or texture of plant leaves. Quantitative data is numerical, such as measuring the height of a plant or counting the number of leaves.

Choosing the right method to collect reliable data is also important. Fieldwork, such as observing animals in their natural habitat, can provide real-world data, whereas laboratory experimentation, such as testing chemical reactions under controlled conditions, gives tighter control and more consistency. For instance, if a scientist is studying the effect of fertiliser on plant growth, laboratory experiments can control environmental factors better than field studies.

Collecting valid and reliable data in investigations

When planning an investigation and analysing the results, it is important to consider the validity and reliability of your data.

Validity

Validity is the answer to the question, “Is this a fair test?” In other words, “Are all other variables controlled?” and “Is this experiment addressing the question posed?”

The experiment should manipulate only the independent variable and measure only the dependent variable, with all other variables kept constant. Validity refers to how appropriate the method is to investigate the phenomenon it is intended to measure. By evaluating the validity of methods and the data collected, researchers can make informed decisions about the quality of the data and ensure that their conclusions and recommendations are based on correct methodology.

For an investigation to be valid, the scientist must:

• control all other variables except the independent variable

• use a method that directly tests the hypothesis

• ensure the equipment and procedures match the purpose of the investigation.

qualitative data information that uses descriptive explanations involving features, characteristics or properties to identify important components; not numerical in nature quantitative data information that is expressed or measured numerically

validity the extent to which an experiment is a fair test, with all relevant variables controlled, and appropriately addresses the research question

reliability how repeatable, replicable and reproducible the results are

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If uncontrolled factors influence the dependent variable, the experiment is invalid, because the results cannot be confidently linked to the independent variable.

sample size the number of test subjects that are tested or observed in an experiment

WORKED EXAMPLE 1B.1

Validity

Imagine you are investigating how light intensity affects the rate of photosynthesis in aquatic plants. Your hypothesis predicts that increasing light intensity will increase the rate of photosynthesis.

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To ensure the validity of your investigation:

1. The variables must be controlled. In this case:

• independent variable = light intensity

• dependent variable = rate of photosynthesis (measured by oxygen bubbles per minute)

• controlled variables =

> temperature

> carbon dioxide concentration

> water volume

> distance between light source and plant (except when changing intensity)

> species and size of plant.

If the temperature fluctuates or different plants are used, these factors could change the photosynthesis rate, making the experiment less valid.

2. The method must match the question and hypothesis.

• If the hypothesis is about light intensity, but the method accidentally changes light colour, then the investigation does not correctly test the hypothesis and is less valid.

3. Appropriate equipment must be used.

• A faulty light meter, a leaking test tube or inconsistent measurement intervals reduce validity because they introduce additional variables.

If all variables except light intensity are controlled, then observed changes in oxygen output can confidently be attributed to light intensity, because no other factor is influencing the results. Providing appropriate equipment was used, the investigation can be considered valid.

Reliability

Reliable experimental results are those that we consider repeatable, replicable and reproducible. A method with a large sample size, large range of data and many repetitions reduces the effect of random variation and ensures that the results are more representative of the broader population. Reliable results are similar or consistent across repeated trials. When multiple trials produce similar outcomes, the reliability is said to be high, because the results are unlikely to be due to chance.

To understand why sample size matters, imagine trying to decide whether doctors should prescribe a new painkiller by asking only one person if it reduced their pain. It would be unreasonable and scientifically invalid to make decisions about the healthcare of all Australians based on the experience of a single individual. The more participants or repeated measurements used, and the more consistent the results, the more reliable the findings.

Repeatability, replicability and reproducibility

Results from a single experiment may not be reliable as evidence for the research question. For example, it is difficult to perfectly control all controlled variables in an experiment, so a single experiment may be influenced by some unknown variation. Therefore, scientists should ensure that they repeat their experiment under exactly the same conditions multiple times – this is often called conducting multiple trials. If the results match well, the experiment is said to have high repeatability . An average calculated from many repeats is more reliable than a single measurement or an average of fewer repeats. Also, if the results obtained from a first-hand investigation align closely with published scientific research, then this secondary-source information further confirms the reliability of the results obtained.

The results should also be replicable, which occurs when another scientist can repeat the investigation using the same method and equipment as the original experiment and obtain similar results. Replicability is important because it shows that the findings are not dependent on a single researcher, location or set of trials. Therefore, when multiple independent investigations produce consistent outcomes, the reliability of the results is further confirmed, demonstrating that the findings are stable, reproducible and not due to chance or bias.

Finally, the results should be reproducible (have high reproducibility) – this means if another scientist carries out an experiment investigating the same question, using a method and equipment that are different from the original experiment, they will still get similar results.

Table 1B.1 The difference between repeatability, replicability and reproducibility

Consistent results from:same person and lab, same method different person and lab, same method different person and lab, different method

If experimental results are repeatable, replicable and reproducible, scientists can be confident that these results are reliable.

Accuracy

Even if an experiment is valid and reliable, it may still lack accuracy if the equipment or procedure introduces random error and/or systematic error (error is discussed further in Section 1E). Accuracy refers to how close a measurement is to the true or accepted value. When a quantity has a known published value, such as the boiling point of water, we can compare our measured value to this standard to judge accuracy. However, when something is being measured for the first time, scientists do not know the true value until multiple independent investigations produce similar results, gradually establishing what is accepted as accurate.

Precision

In addition to accuracy, scientists must also consider precision . Precision refers to how close repeated measurements are to each other, regardless of whether they are close to the true value. For example, three mass readings of 5.02 g, 5.01 g and 5.03 g show high precision because the measurements are very similar. However, they may still be inaccurate if the true mass is actually 6.00 g. Precision is influenced by the quality of the measuring instrument and the consistency of the measuring technique.

repeatability how well the results match up when the same scientist repeats the experiment under the same conditions as the original experiment, including the same equipment and laboratory or field site

replicability how well the results match up when a different scientist repeats the experiment under the same conditions as the original experiment, including the same equipment and laboratory or field site

reproducibility how well the results match up when a different scientist repeats the experiment under different conditions than the original experiment, including different equipment and laboratory or field site accuracy in an experiment, how close a measurement is to the true value

precision the extent to which repeated measurements of the same item are close to each other

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widget reporting note taking scorcher

High-quality scientific investigations aim for both accuracy and precision. Accuracy ensures measurements are correct, while precision ensures results are consistent. When an experiment achieves both high accuracy and high precision, its results are more likely to be trusted, reproduced by other scientists and used as reliable evidence for further research and decision-making.

PRACTICAL 1B.1

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A qualitative experiment collecting primary data

Aim

To investigate the effect of temperature on enzyme activity, using gelatin and fresh pineapple juice.

Method

1. Prepare several small beakers or test tubes with gelatin that has been allowed to set.

2. Add fresh pineapple juice (which contains the enzyme bromelain) to some of the gelatin samples.

3. Place samples at different temperatures (e.g. fridge, room temperature, warm water bath).

4. Leave for a set period and observe changes.

Results

Observe the consistency of the gelatin and record your findings.

Discussion

Explain why your observations are qualitative observations.

Ensuring reliability

Reliability means the data is consistent and reproducible. To ensure reliability:

• repeat trials and take averages

• use calibrated and accurate equipment

• ensure consistent procedures are followed by all experimenters

• record data systematically, and as measured, in a results table.

For example, in Practical 1B.1, the reliability of the results could be increased by repeating the enzyme reaction three times at each temperature and calculating the mean reaction time.

Table 1B.2 Example of reliable results: measuring the amount of carbon dioxide produced per minute in the fermentation of sugar at different temperatures

Secondary data and information

Secondary data comes from sources such as scientific journals, textbooks, reputable websites and databases.

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Assessing the reliability of secondary sources

When planning an investigation, evaluate secondary data carefully by applying the CRAAP test.

• Cur rency – Is the information up to date?

> Check the date of publication and whether more recent data is available, especially in fast-changing fields such as medicine or climate science.

• Relevance – Does the source relate directly to your research question or hypothesis?

> Make sure the data, context and species studied are appropriate for your investigation.

• Authority – Who produced the information?

> Give preference to peer-reviewed journals, recognised scientific institutions, universities or government agencies over anonymous or non-expert sources.

• Accuracy – Is the information trustworthy and supported by evidence?

> Look for clear methods, referenced data, logical reasoning and results that are consistent with other reputable sources.

• Pur pose – Why was the information created?

> Identify whether the purpose is to inform, persuade, sell or entertain. Be wary of sources with obvious bias or commercial interests.

Using the CRAAP method will help ensure that any secondary data you include in your investigation is reliable, credible and suitable for refining your hypothesis and supporting your scientific argument.

For example, when designing a microbiology experiment, checking World Health Organization (WHO) guidelines will provide more reliable data than consulting an anonymous online blog.

To extract data from a secondary source:

1. Cr itically review the information and ensure it relates to your investigation/research.

2. Summar ise the data from the secondary-source material.

3. Link the secondary-source information to your own investigation.

4. Acknowledge the source, using correct referencing.

Figure 1B.1 A scientist researching secondary data

Modifying an investigation in response to new evidence Investigations often need to be modified in response to new evidence. If the initial results suggest an unexpected trend, the hypothesis or experimental design might need to be adjusted. For example, if you are testing how different fertilisers affect plant growth and discover that one fertiliser unexpectedly stunts growth, you might need to investigate the chemical composition of that fertiliser and its effect on the plants.

Using reliable secondary sources

When evaluating secondary sources, especially online content, you should develop and apply criteria to determine the validity and reliability of the content, such as the author’s qualifications, the accuracy of the information and the presence of supporting evidence. Reliable information is usually written by experts, such as scientists or scholars, and is published in reputable journals, books or websites. Look at the date of publication to ensure the information is current, because outdated data might no longer be accurate. Consider the purpose of the source: is it meant to inform, persuade or sell something? Be wary of bias, which can distort the facts. Cross-referencing information with other credible sources can help verify its accuracy.

The principles for evaluating the validity and reliability of secondary-source data are the same as for primary data, which is the kind of data that you and your class have collected.

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When using secondary sources, be sure to record the correct referencing details, because you will need to state your sources in any reports or science communications where they are acknowledged. Referencing secondary sources is covered further in Section 1D.

Peer review

Scientific knowledge is verified through rigorous processes such as hypothesis testing and peer review . Hypothesis testing involves proposing a testable explanation and conducting experiments to gather data that supports or refutes the hypothesis. In peer review, other experts critically assess the research methods and findings before publication of the results.

Scientific publishing crisis

However, these verification processes are being undermined by a growing global crisis in scientific publishing. In 2023, over 10,000 sham research papers were retracted (compared to just 1000 in 2013), exposing the widespread issue of fraudulent studies, driven largely by “shadow” organisations known as “paper mills”. These paper mills produce fake research to advance the careers of young scientists, often by bribing journal editors or infiltrating editorial boards. This scandalous practice undermines scientific progress and threatens credible research, making it difficult for scientists to base their work on trustworthy findings.

Figure 1B.2 Nature is one of the most cited scientific journals, making it a globally respected academic journal.

peer review evaluation of scientific work by others in the same field to ensure accuracy and reliability

Identifying hazards and risks

A hazard is a potential source of harm, such as chemicals, heat, glassware or biological materials. When planning a scientific investigation, hazards and risks must be described. This information can be structured in a risk assessment table, such as Table 1B.3. This format makes it easy to identify what you need to do in the investigation to reduce the risk of injury. By complying with the relevant control measures, you are implementing the required safe practices for everyone involved.

Table 1B.3 Example of a risk assessment

Heating solutionsBurns to the skin

Sharp instrumentsCuts/injuries to the skin

Bacterial culturesContamination/ infection by bacteria

• Use heatproof mats.

• Wear safety glasses and gloves.

• Handle hot equipment with care.

• Handle sharp instruments with care.

• Store sharp equipment safely (e.g. when storing scalpels, make the handle the most accessible component rather than the blade)

• Wear PPE while handling cultures.

• Sterilise all equipment used.

• Follow aseptic technique (e.g. hand washing)

Following safe practices involves wearing appropriate personal protective equipment (PPE) such as gloves, safety glasses and lab coat when handling hazardous materials, and following safety protocols to minimise the risk of accidents.

Managing risks includes having emergency procedures in place, such as knowing the location of safety showers and eye wash stations. Addressing potential risks and following safety guidelines will reduce the likelihood of accident or injury.

Developing a risk assessment

When developing a formal risk assessment, follow these steps:

1. Identify the hazards.

2. Identify the potential risk associated with the hazard.

3. Implement control measures.

4. Review and update if necessary.

hazard something that poses a potential risk of harm or injury

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NOTE

Risk assessments are mandatory for all school-based investigations.

Figure 1B.3 It is important to wear PPE when handling bacterial cultures.

Selecting materials and technologies

The choice of materials and technologies affects the accuracy, reliability and safety of an investigation. Choosing high-quality and appropriate tools, such as a pH meter for accurate acidity measurements, ensures reliable and valid results.

• Materials – these must be appropriate for the procedure and compatible with the variables being tested.

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• Technologies – these include both traditional tools (e.g. thermometers, balances, rulers) and modern technologies (e.g. data loggers, spectrophotometers, digital sensors).

Accurately assembling, constructing and manipulating equipment is essential in any investigation. Experimental apparatus must be set up according to detailed instructions and all components checked to ensure that they function correctly. For example, when assembling a circuit for an electrical experiment, the wires must be connected properly, and the power supply must be compatible with the components used.

Figure 1B.4 (a.) Using a digital pH probe provides more precise data than (b.) using universal indicator paper.

Figure 1B.5 Proper set-up and handling of equipment in scientific experiments, even in challenging environments like the Snowy Mountains, is crucial for obtaining accurate results.

Manipulating equipment with care, such as calibrating an electronic balance, will ensure that the experimental conditions are consistent and results are more accurate. Calibration is the process of adjusting equipment to ensure its measurements are accurate and consistent. It involves comparing the measurements from the equipment with known standards or reference values and making adjustments as necessary to correct any discrepancies. An example of this is making sure an electronic balance is “tared” (zeroed) when a container is placed on it.

Ensuring that all equipment is correctly calibrated will allow better replicability and reproducibility by other scientists. Using a large sample size will improve reliability because it reduces the effect of random errors by averaging them out. Proper use and maintenance of equipment can also enhance the accuracy of results and prolong the lifespan of the tools and materials used.

Ethical issues in scientific investigations

In addition to safety considerations, scientific investigations must be carried out within an ethical framework to protect humans, animals and the environment. The data should be collected with a high level of accuracy and recorded with honesty.

For an investigation to be both safe and ethical, it must meet the following requirements.

• An appropriate risk assessment has been developed and will be adhered to.

• The equipment to be used is the most precise available to ensure the data being collected is accurate, with minimal errors.

calibration the process of adjusting a piece of measuring equipment against a known standard value to ensure its accuracy

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• The data is recorded exactly as it is measured, and any sources of information are acknowledged.

• Informed consent from human participants has been obtained where necessary. For example, in medical research, participants must understand the potential risks before agreeing to be involved.

• Animal welfare has been considered, with minimal harm and distress to animals.

• The environment has been protected, with safe disposal of waste products.

ethical (in science) conforming to accepted moral principles and standards of conduct that guide researchers in their professional activities, ensuring the integrity of the process and the wellbeing of participants

Figure 1B.6 Equipment used to calibrate volumetric glassware

ACTIVITY 1B.2

Evaluating ethical issues

Evaluate the ethical implications of using genetically modified organisms (GMOs) in agricultural research. In your response:

1. outline the potential benefits of the research (e.g. food security, disease resistance, economic outcomes)

2. identify possible ethical concerns (e.g. environmental impact, biodiversity loss, corporate control, consumer choice)

3. present a balanced argument that considers both scientific evidence and ethical principles.

Summary of planning scientific investigations

Scientific investigations must be carefully planned to produce valid, reliable, accurate and ethical results.

Variables and controls

• Independent, dependent and controlled variables must be clearly identified.

• Controlled variables must remain constant to ensure a fair test.

• Experimental controls provide a baseline for comparison.

• Positive controls show the experiment is working; negative controls show what happens with no expected response.

Obtaining reliable primary data

• Data can be qualitative (descriptive) or quantitative (numerical).

• Reliable data requires:

> appropriate results tables

> consistent measurement techniques

> correct use of precise and calibrated equipment

> repeated trials and adequate sample sizes.

Repeatability, replicability and reproducibility

• Repeatability – same scientist, same conditions → similar results.

• Replicability – different scientist, same method → similar results.

• Reproducibility – different scientist, different method → similar results.

• High repeatability, replicability and reproducibility increase reliability.

Accuracy and precision

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• Accuracy – how close a measurement is to the true value.

• Precision – how close repeated measurements are to each other.

• Experiments should aim for high accuracy and high precision.

Validity

• An investigation is valid when:

> only the independent variable is changed

> the method directly tests the question and hypothesis

> the equipment and procedures suit the purpose.

• Uncontrolled variables reduce validity.

Using secondary data

• Secondary sources include journal articles, textbooks and reputable websites.

• To assess a source, use the CRAAP test.

>Currency: Is it up to date?

>Relevance: Does it relate to your question?

>Authority: Is it from experts?

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>Accuracy: Is it supported by evidence?

>Purpose: Why was it written?

• Extract, summarise and reference secondary data correctly.

Risk assessment and safety

• All investigations require identification of:

> hazards

> associated risks

> control measures.

• Follow PPE guidelines, safe handling procedures and emergency protocols.

Materials and technologies

• Select equipment that is appropriate, precise and safe.

• Technologies such as pH meters, data loggers and sensors improve accuracy.

• Correct calibration and careful manipulation of equipment improves data quality.

Ethical considerations

• Data must be recorded honestly and without fabrication.

• Human participants require informed consent.

• Animal welfare must be protected.

• Environmental impacts must be minimised.

• All sources must be properly acknowledged.

SECTION 1B REVIEW

Review questions

1. Explain why controlling variables is important for validity.

2. Describe two ways of increasing the reliability of primary data.

3. Outline three criteria for assessing secondary data.

4. Complete a risk assessment for heating solutions in a laboratory.

5. Suggest a technology that improves the precision of temperature measurement, and explain why.

6. Discuss one ethical issue that may arise in human medical trials.

Quiz

Review questions

Reporting (student and teacher)

Worksheet 1C.1

1C Conducting scientific investigations

SYLLABUS

At the end of this section, I will be able to:

Evaluating and interpreting secondary sources questions download word download pdf

1C.1 Apply safe work practices and manage risks while conducting a scientific investigation

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1C.2 Construct and manipulate identified materials and technologies to perform scientific investigations

1C.3 Use equipment appropriately and systematically to collect and record data, information, evidence and findings

1C.4 Gather data and information from a range of secondary sources

Conducting a scientific investigation involves more than simply carrying out an experiment. It requires planning for safety, choosing and using appropriate equipment, handling materials responsibly, and gathering accurate data from both primary and secondary sources. In Stage 6 Biology, you will develop these skills so that you can confidently investigate scientific questions and communicate reliable findings.

Applying safe work practices and managing risks

As discussed in the previous section, before starting any practical investigation, scientists must identify and manage potential hazards. A risk assessment allows researchers to evaluate the likelihood and consequences of hazards and put control measures in place.

Key safety practices:

• Wear appropriate personal protective equipment (PPE) such as goggles, gloves and lab coat.

• Know the location of safety equipment (fire extinguisher, eyewash station, first aid kit).

• Never eat or drink in the laboratory.

• Dispose of chemicals and biological material safely.

• Follow teacher and laboratory instructions at all times.

Figure 1C.1 Using safety gear minimises the chances of injury during an investigation. Heating solutions in a lab requires wearing safety goggles, using heatproof mats and handling hot glassware with tongs to prevent burns.

Figure 1C.2 The steps for developing a risk assessment

Constructing and manipulating materials and technologies

Scientists often need to build or adapt apparatus to suit their investigation. For example, this might involve:

• setting up a microscope slide for cell observation

• constructing a respirometer to measure gas exchange

• using technologies such as data loggers, pH probes or spectrophotometers to improve accuracy.

This may encourage creativity, as scientists may need to adapt or manipulate available equipment to achieve reliable results.

Using equipment appropriately and systematically

Accurate results depend on correct use of equipment and systematic methods.

Principles of good practice:

• Calibrate instruments before use (e.g. zero a digital balance).

• Use correct measuring technique (e.g. read from the bottom of the meniscus when measuring liquids).

• Record results systematically in a table, logbook or digital format.

• Repeat measurements and average to improve reliability.

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Data and information from secondary sources

Not all data is collected first-hand. Secondary sources provide additional information that supports or compares with primary data. Examples of secondary sources are:

• scientific journals and textbooks

• reputable websites (e.g. CSIRO, government health departments)

• databases (e.g. PubMed, ScienceDirect).

Figure 1C.3 Measuring the same amount of water in different types of glassware, with increasing sensitivity and accuracy, from left to right: (a.) beaker, (b.) measuring cylinder and (c.) burette

Go online to access the Interactive Textbook

Evaluating secondary data – the CRAAP method

As discussed in the previous section, when planning an investigation, evaluate secondary data carefully by applying the CRAAP test:

• C – Currency

• R – Relevance

• A – Authority

• A – Accuracy

• P – Purpose.

Using the CRAAP method will help ensure that the secondary data you use is reliable, credible and suitable, and will support your scientific argument.

SECTION 1C REVIEW

Review questions

1. Explain why conducting a risk assessment is essential before an investigation.

2. Describe two examples of how scientists manipulate materials or technologies in an investigation.

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3. Why is it important to calibrate equipment before taking measurements?

4. Outline three criteria used to evaluate secondary sources of scientific information.

5. Suggest one technology that improves the precision of temperature measurement, and explain why. Quiz Review

Figure 1C.4 Throughout your studies in Stage 6 Biology, you will research a wide range of secondary sources.

1D Processing data and information

SYLLABUS

At the end of this section, I will be able to:

1D.1 Select qualitative and quantitative information from texts, diagrams, flow charts, tables, databases, graphs and multimedia resources

1D.2 Apply quantitative processes to data, including unit conversions

1D.3 Select and use a range of representations to organise data and information, including graphs, keys, models, diagrams, tables and spreadsheets

1D.4 Extract data and information from a wide range of sources and acknowledge these sources using an accepted referencing style

1D.5 Describe the Cultural Knowledges and observations of Aboriginal and Torres Strait Islander Peoples and examine how these contribute to the development of scientific knowledge

Biology relies not only on gathering data, but also on processing and interpreting it in meaningful ways. Data must be selected, transformed and presented in formats that highlight patterns, relationships and trends. This section focuses on the selection, processing and representation of data from primary and secondary sources, and recognises that Aboriginal and Torres Strait Islander Cultural Knowledge is scientific and that Western science can learn from and through Indigenous approaches.

Selecting and extracting information from a variety of sources

Scientists must be able to interpret information presented in many forms. When processing data, the first step is to recognise and select the information that is already available. Data is often presented in tables, graphs or diagrams, and before any analysis can occur, you must carefully read and understand what is being shown.

1. Read the title.

> The title provides an overview of what the data represents.

> Ask yourself: What is the focus of this table or graph?

2. Check headings and labels.

> In tables, look at the column and row headings.

> In graphs, examine the axis labels.

> Always note the units (e.g. °C, mL, years), because these show how the data was measured.

Worksheet 1D.1

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3. Identify the type of information.

> Decide whether the data is qualitative (descriptive categories such as colour, species or type) or quantitative (numerical values such as mass, temperature or time).

> This will guide how you interpret the data in later steps.

4. Recognise what the data shows.

> Before analysing trends or patterns, ensure you can describe the data accurately.

> At this stage, the goal is to select and recognise the information, not to explain it.

Example: extracting information from tables

Table 1D.1 shows the average height of bean plants grown at different temperatures. The title tells us that the focus is on plant growth in relation to temperature. The headings identify the variables: temperature (°C) is the independent variable, and average plant height (cm) is the dependent variable. Because the data is measured with numbers, it is quantitative. By carefully reading the table, you can see how plant growth changes as the temperature increases.

Table 1D.1 Average growth of bean plants at different temperatures

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SKILLS 1D.1

Guidelines for creating a results table

When you conduct a scientific investigation, a results table will help you organise and display your data clearly. To create a results table, follow these steps.

1. Write a clear title.

The title should describe what your table shows (e.g. see Table 1D.2 “The effect of light on photosynthesis by aquatic plants [e.g. Elodea]”)

2. Decide on your variables.

Place the independent variable (the one you change) in the first column. Place the dependent variable (the one you measure) in the second column.

3. Include units.

Always write the unit of measurement in brackets after the variable name in the column heading (e.g. Temperature [°C], Time [s])

4. Use neat columns and rows.

Each trial or observation should be recorded in its own row.

If you repeat trials, include extra rows or columns to record each one.

5. Add a column for averages.

If you repeat measurements, add a column to calculate and record the average.

6. Keep it organised.

Use ruled lines (if hand-drawn) or a simple table tool (if typed).

Make sure your table is easy to read and interpret.

Table 1D.2 The effect of light on photosynthesis by aquatic plants (e.g. Elodea)

Graphs

Graphs are useful for displaying quantitative data, because graphs often make it easier to interpret and identify visible tends. In Stage 6 science, we tend to use column and line graphs the most. Examples of column, bar and line graphs and a pie chart are shown in Figures 1D.1, 1D.2 and 1D.3. Column graphs and bar graphs are similar; often one is chosen over the other simply because of how the type of information is more effectively displayed. In column graphs, the categories are listed along the x-axis and numbers along the y-axis, while in bar graphs it is the other way around.

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Bar graph showing heart rates of different types of animals

Column graph showing heart rates of different types of animals

1D.1 (a.) Column and (b.) bar graphs are a way of displaying how a quantitative,

) changes in response to a qualitative independent variable (e.g. species)

Figure 1D.2 Line graphs are ideal for displaying changes over time, or changes in the dependent variable (plotted on the vertical y-axis) as the independent variable changes (plotted on the horizontal x-axis). This graph shows population changes over time for red kangaroos (prey) and dingoes (predator). In this example, two dependent variables are plotted on the same graph, as red and blue lines. Plotting them together shows the relationship between predator and prey.

Figure 1D.3 A pie graph is useful for presenting the proportional relationship of a variable in relation to other variables – in this example, the number of animals inhabiting particular ecosystems.

Figure

SKILLS 1D.2

Guidelines for drawing graphs

1. Always use a sharp, dark pencil.

2. Usually, the independent variable goes on the horizontal axis (x-axis) and the dependent variable on the vertical axis (y-axis). However, sometimes you may be asked to disregard this rule.

3. Axes should be labelled with the quantity being measured and the units. The units should be in brackets after the quantity name – for example, time (s) or volume (L)

4. Use the full width of the graph paper (if drawing on paper) and choose a scale that spreads the data points out over most of the grid. If you are measuring quantities where zero does not mean “no quantity” (e.g. temperature), then you do not have to start the axes at zero. If the range of values does not go to zero (e.g. 85–115), then don’t start the axes at zero. In this example, you could start the axis at 80 and continue the numbers to 120. If the quantities on both axes go to zero, then the point where the axes meet, (0, 0), is called the origin.

5. The scale should increase evenly, preferably with each grid square used to represent multiples of 1, 2, 5 or 10. Do not have breaks in the scale – for example, you can’t show 0 to 20 in intervals of five and then skip straight to 60.

6. Data points are typically represented with a dot or a cross. If you are plotting multiple sets of data on the same graph, use different-coloured points for each data set and add a legend.

7. Circle any outlier results and label them as “outlier”. These data points are those that are clearly different and are probably due to an error or a mistake in recording that data point. Note: Do not simply remove the point! Scientists must communicate all data, including outlier results.

8. Write a clear and concise title for the graph, incorporating the independent variable and the dependent variable. When the data comes from a secondary source, this should be referenced. Add labels and keys where necessary.

Applying quantitative processes to data

Quantitative data involves numerical values that can be measured and analysed using mathematical processes. Scientists use calculations, ratios, averages and unit conversions to make data consistent and comparable across investigations.

Unit conversions

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Biological data is often collected using different measurement units. To analyse data correctly, you must ensure that all values are expressed in the same unit system, usually SI units (International System of Units) . Table 1D.3 outlines some units you will commonly use in the laboratory.

WORKED EXAMPLE 1D.1

Converting units

A student measures a plant’s growth rate as 2.5 mm per day. Express this in centimetres per week.

Solution

2.5 mm/day 10 = 0.25 cm/day

0.25 cm/day × 7 = 1.75 cm/week

Explanation

Step 1. Convert the rate from millimetres to centimetres. To do this, divide the value by 10, because there are 10 millimetres in a centimetre.

Step 2. Convert the rate into weeks. To do this, multiply the value by 7, because there are 7 days in a week.

Selecting and using a range of representations

Presenting data visually helps reveal trends and relationships that are not always obvious from raw numbers. Scientists use tables, graphs, spreadsheets, diagrams, models and keys to organise and communicate their findings.

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model a mathematical, conceptual or physical representation that describes, simplifies, clarifies or explains the structure, workings or relationships within an object, system or idea; can provide a means of testing and predicting behaviour within limited conditions

Tables

As mentioned earlier in this section, tables are a way of organising data systematically. A table must include:

• a clear title

• headings with units

• consistent decimal places.

Graphs

Graphs visually show relationships between variables.

• Line graphs – show continuous change (e.g. enzyme activity versus temperature).

• Bar graphs – compare discrete categories (e.g. number of plant species in habitats).

• Scatter plots – show correlation between variables.

Label both axes, include units, and draw a line of best fit if appropriate.

Spreadsheets

Spreadsheets (such as Excel or Google Sheets) allow you to:

• enter data and do automatic calculations

• create graphs

• analyse errors using formulas.

Figure 1D.4 There are many ways of analysing data.

Video: Worked example 1D.1

dichotomous key a classification tool that uses paired statements to identify organisms

Diagrams and models

Biological diagrams represent complex structures (e.g. cells, ecosystems) in a simplified way. Models can be physical (DNA models), mathematical or computer simulations used to explain biological processes.

1D.5 This is a physical model representing the structure of DNA.

Keys

Keys help identify organisms using observable features. An example is the dichotomous key in Figure 1D.6.

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Figure

Reptile

Figure 1D.6 A simple dichotomous key for classifying animals

Extracting and acknowledging data from sources

Biologists rely on primary data (from their own experiments) and secondary data (from other sources, such as scientific journals, databases and reports). To maintain academic integrity, it is essential to acknowledge all sources properly.

Table 1D.4 Primary versus secondary data

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Primary Collected first-hand by the investigatorMeasuring plant growth in class

Obtained from others’ work Using data from CSIRO or NESA reports

Evaluating sources

When using external data, assess its:

• authority – who produced it? (e.g. a reputable scientific institution)

• accuracy – has the data been verified and peer reviewed?

• cur rency – is the information recent and relevant?

• bias – is there evidence of selective interpretation by the authors?

Referencing styles

When listing and citing your sources, use an accepted academic style, such as Harvard.

Harvard-style reference format

Author, Year, Title of Source, Publisher or Website, Accessed date.

Example: CSIRO. (2024). Australian Climate Data Summary. Retrieved from www.csiro.au, accessed 12 May 2025.

Cultural Knowledge is science

Aboriginal and Torres Strait Islander sciences are independent and enduring and have sustained life for tens of thousands of years. Deeply grounded in custodianship of Country , Cultural Knowledge has been developed through careful observation, experimentation, abstraction and deduction.

NOTE

Aboriginal and Torres Strait Islander knowledge systems are holistic and relational; science knowledge is interwoven with knowledge from all other fields and is connected to people and place. This is why the phrase “Cultural Knowledge” is used instead. It better reflects the extent of knowledge covered, the responsibilities that come with knowing, and the social protocols involved in learning and sharing knowledge.

Aboriginal and Torres Strait Islander people use their Cultural Knowledge to fulfill their responsibilities and aspirations for Country and community. One example of this is Aboriginal and Torres Strait Islander scientists working with cutting edge technologies to, for example, clean polluted water, replenish river systems and develop renewable energy grids.

Aboriginal and Torres Strait Islander Peoples

Aboriginal Peoples are the first peoples of Australia and identify themselves as belonging to more than 250 language groups, each associated with a particular Country. Torres Strait Islander Peoples are associated with islands to the north of Cape York.

An Aboriginal and/or Torres Strait Islander person:

• is of Aboriginal and/or Torres Strait Islander descent

• identifies as an Aboriginal person and/ or Torres Strait Islander person, and

• is accepted as such by the Aboriginal and/or Torres Strait Islander community(ies) in which they live.

Country a living entity, created by the Ancestors, that Aboriginal and Torres Strait Islander people interact with spiritually and culturally

Cultural Knowledge the cumulative, placebased understandings developed by Aboriginal and Torres Strait Islander Peoples through long-term interaction with Country, transmitted across generations through Indigenous ways of knowing and doing

Indigenous Cultural and Intellectual Property collective ownership and authority of Indigenous Peoples over their Cultural Knowledge, expressions and heritage

Indigenous Data Sovereignty collective control by Indigenous Peoples over how their data is created, accessed, used and governed

cultural humility recognition of one’s own biases and assumptions, and a commitment to addressing structural inequalities

reflexivity ongoing reflection on how your position shapes what you see, know and do

Indigenous knowledge holders and custodians also work with non-Indigenous scientists in order to:

• re-introduce and scale up cultural burning practices that help Country replenish and heal;

• enable non-Indigenous scientists to learn sustainable principles of ecological governance for local contexts;

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• make traditional medicines and foods accessible to more people;

• determine the health and range of animal and plant populations, to implement caring for Country strategies.

Increasingly, Western-trained scientists are developing the skills to be able to work collaboratively and respectfully with Aboriginal and Torres Strait Islander scientists, knowledge holders and knowledges. This allows for innovative ways of knowing and working with Country to be developed.

Aboriginal and Torres Strait Islander peoples’ Cultural Knowledge belongs to Aboriginal and Torres Strait Islander people, as do their scientific processes for generating new understandings. There has been a history of non-Indigenous scientists using Indigenous peoples’ knowledge without their permission. Scientists who work with Aboriginal and Torres Strait Islander people and knowledge need to be familiar with Indigenous Cultural and Intellectual Property and Indigenous Data Sovereignty principles, to ensure respectful and relational practices. It is recommended that non-Indigenous scientists develop their cultural humility and reflexivity .

or

practice that Aboriginal and Torres Strait Islander people have used for tens of thousands of years to maintain the health of Country. By applying the right fire at the right time, low intensity white smoke fires keep landscapes clean, encourage new growth and prevent bushfires. This method creates a mosaic of burnt and unburnt areas, protects culturally significant sites, and is based on deep, longstanding knowledge of local ecosystems.

Summary of processing data and information

This section has shown how to:

• apply quantitative skills and unit conversions to process data

• represent information effectively, using tables, graphs, models and spreadsheets

• ex tract, evaluate and reference information from various sources

• begin developing respectful practices to work with Aboriginal and Torres Strait Islander Cultural Knowledge.

Figure 1D.7 Cultural burning, also known as firestick farming

fire management, is an ongoing

SECTION 1D REVIEW

Quiz

Review questions Reporting (student and teacher)

Go online to access the Interactive Textbook Review questions

1. How does Aboriginal and Torres Strait Islander Cultural Knowledge differ to Western science practices?

2. In what ways might conventional Western science practices disrespect Aboriginal and Torres Strait Islander Cultural Knowledge protocols?

3. What are recommended strategies and capabilities for scientists working with Aboriginal and Torres Strait Islander Cultural Knowledge?

4. A student measures the mass of a sample that has a true value of 10.0 g. Their four readings are: 9.8 g, 9.9 g, 9.8 g, 9.9 g.

a. Comment on the precision of these results.

b. Comment on the accuracy of these results.

c. Explain how it is possible for a set of measurements to be precise but not accurate.

5. A student investigates the effect of soil pH on the germination rate of bean seeds. They set up four trays with different pH values (4, 5, 6, 7). In each tray they place 20 seeds and water them daily. The trays are kept on different windowsills that receive different amounts of sunlight.

a. Identify the independent and dependent variables.

b. Name two controlled variables that should be kept constant in this experiment.

c. Explain why the use of different windowsills reduces the validity of the experiment.

6. Two groups of students investigate the effect of caffeine on heart rate.

GroupA tests 2 volunteers and repeats the reading once for each person.

Group B tests 20 volunteers and repeats the reading three times per person.

a. Which group produces more reliable results? Explain your reasoning.

b. State one additional step that either group could take to further increase the reliability of their investigation.

7. A student measures the rate of an enzyme-catalysed reaction at different temperatures and records the following data.

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a. On graph paper, draw a line graph of this data, with axes labelled:

• Temperature (°C) on the x-axis

• Rate of reaction on the y-axis.

b. Describe the trend shown in the graph.

c. Estimate the optimum temperature for this enzyme and justify your answer.

8. In an osmosis experiment, the true salt concentration of a solution is 0.30 mol L ¹.

A student’s titration result gives a value of 0.26 mol L ¹.

a. Calculate the percentage error of the student’s result. Show your working.

b. Suggest one reason for this inaccuracy and one way to improve accuracy in future trials.

Worksheet 1E.1

Analysing

1E Analysing data and information

SYLLABUS

At the end of this section, I will be able to:

1E.1 Describe qualitative and quantitative relationships between variables

1E.2 Explain patterns and trends, including inconsistencies in data and information

1E.3 Assess error, uncertainty and limitations in data and include calculations of percentage error, range, mean and standard deviation

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Worksheet 1E.2

1E.4 Assess the validity, reliability, accuracy and precision of data and information

1E.5 Interpret data and information to identify outliers, make predictions, explain results and draw conclusions

1E.6 Evaluate data and information to suggest improvements or further investigations

Once data has been collected and processed, the next step in scientific investigation is analysis, as well as identifying what the data reveals and how it supports or challenges your hypothesis. In this section, you will learn how to interpret, evaluate and communicate scientific data accurately and meaningfully.

Describing qualitative and quantitative relationships between variables

Scientific investigations often explore relationships between independent and dependent variables.

Quantitative relationships involve quantitative data. Quantitative data is data in the form of measurements or numerical values, which can be compared. In a quantitative relationship, one variable changes in response to another in a way that can be expressed using numbers, graphs or mathematical patterns.

For example:

• “A s temperature increases from 20°C to 40°C, enzyme activity increases from 10 units/min to 24 units/min before decreasing at higher temperatures.”

• “A s substrate concentration increases from 0.1 mol L ¹ to 0.5 mol L ¹, the reaction rate increases from 5 bubbles/min to 22 bubbles/min, until saturation occurs.”

These numerical examples show the strength and direction of the relationship between variables and allow scientists to analyse trends, calculate rates and make predictions.

The patterns or trends in qualitative relationships are described using words (e.g. “Enzyme activity slows down as the temperature becomes too high”).

Table 1E.1 Summary of relationships between variables

Example of a direct linear relationship

An experiment measures plant growth at different nitrate concentrations. When nitrate concentration doubles, plant height roughly doubles. This indicates a direct linear relationship (Figure 1E.1).

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Explaining patterns, trends and inconsistencies

When analysing data, scientists look for patterns (repeated observations), trends (directional changes), and anomalies or inconsistencies (data points that don’t fit expected patterns).

To identify patterns in your data, follow these steps.

1. Plot the data – use an appropriate graph or table.

2. Describe the trend – is it increasing, decreasing or constant?

3. Identify anomalies – points that differ significantly.

4. Sug gest explanations – experimental error, environmental variation or biological limits.

In a scientific investigation, identifying patterns and trends in the data is necessary in order to understand the underlying phenomena. A pattern is a regularity or repeated sequence in the data. A trend is a general direction in which the data points move as a variable changes. Often, patterns and trends describe the same thing. This discussion applies to data when the dependent variable is plotted against the independent variable. A graph allows scientists to visualise relationships (or the lack of relationship) between variables, so graphs are generally the best representation of data to use. However, other kinds of diagrams and tables can also be used effectively.

Identifying data that supports or refutes a hypothesis

An investigation should be a valid test of a prediction from a hypothesis. The prediction is usually in the form of “If the independent variable is changed, the dependent variable will change in a specified way”. If it does change in the predicted way, then the data supports the hypothesis. If it does not, the data refutes the hypothesis. Sometimes the results are not clear, such as when your prediction was for an increase in the dependent variable, but the increase you observed is so small it could have arisen by chance. Scientists have ways to calculate whether a change in the dependent variable is significant, but these calculations are not part of this course. If the hypothesis is supported or refuted, then questions or solutions to problems that are based on that hypothesis are also supported or refuted.

Figure 1E.1 Graph showing a direct linear relationship

correlation when two or more variables change at the same time, but one does not necessarily cause the other to change; it is possible that another (possibly unknown) variable is the cause

Relationships between variables

The relationships between variables should be identified and described by examining how changes in one variable affect another. For instance, in a study examining the effect of fertiliser on plant growth, the amount of fertiliser used (independent variable, plotted on the horizontal x-axis) and the height of the plants (dependent variable, plotted on the vertical y-axis) are the key variables. A positive relationship might be observed if increased fertiliser led to taller plants, while a negative relationship would be indicated if the fertiliser harmed the plants. No correlation may be observed with some plants if the added fertiliser had no effect. Recall the meaning of correlation from Stages 4 and 5 Science.

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Figure 1E.2 Two variables may be related to each other positively or negatively, or they may have no correlation. The latter can be shown by a flat plotline or line of best fit, where the dependent variable was not changed by changes to the independent variable, or it can be shown by data to which a line can’t be fitted. This may suggest that the dependent variable changed due to a confounding variable.

Example:

A student records enzyme activity at different pH levels: the rate increases from pH 4 to pH 7, then drops sharply at pH 9.

• Pattern observed: Enzyme activity rises, then falls.

• Explanation: Enzymes have specific environmental conditions, such as temperature and pH, under which they work most efficiently. This is known as their optimum. The pattern of increasing activity up to the optimum, followed by decreasing activity outside that range, can be explained by the shape and energy requirements of the enzyme and its active site (Figure 1E.3).

Figure 1E.3 Graph showing the effect of changing pH on enzyme activity

Assessing error, uncertainty and limitations

Systematically and accurately collecting and recording data involves using appropriate methods and tools to gather data, and ensuring all measurements are carefully taken and recorded, and are consistent. For example, when measuring the growth rate of plants, it is important to use a consistent method, such as measuring from the base to the highest point of the plant at regular intervals. With fieldwork, documenting the conditions under which the data was collected, such as the date, time and environmental factors, could also provide valuable information when later interpreting the results.

and omissions.

Identifying and responding to errors and uncertainty

Measurements are rarely perfect. The accuracy of any measurement will always be limited by the apparatus being used, the skills of the person collecting the data, the method being used and the environment in which the experiment is carried out. Whenever we do an experiment, we are attempting to determine the “most true” data, but we will normally find variation in the results.

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What are the possible reasons for the different values seen in our data? Mistakes are avoidable problems made by the person collecting the data, such as selecting the wrong piece of equipment or writing down results incorrectly. Although mistakes like these are possible, a careful scientist should not make mistakes and would not include them in any report.

Error is the difference between the results of experimental measurements and the true or reference values involved. Error is not the same as mistakes.

Figure 1E.4 Recording data promptly and accurately in a structured format, such as a lab notebook or digital spreadsheet, helps prevent errors

systematic error

an error that causes measurements to differ from the true result by a consistent amount, often due to faulty or uncalibrated equipment

zero calibration error

a measuring instrument giving a non-zero reading when the true value should be zero

parallax error a measurement taken that is not the true value due to the position of the object along various lines of sight

Systematic error

Systematic error arises from measured values that are either consistently larger or smaller than the true value of your data if equipment is used in the same way.

Systematic error can be minimised by careful experimental design, including calibrating measuring instruments correctly. Some examples are given below.

• Instrument effects are caused when a measuring instrument is faulty or has not been calibrated correctly. For example, if a scale used to measure a mass was not properly calibrated, so all the readings were 3.00 g greater than they should be, then all the measurements of mass would be consistently overestimated by 3.00 g. This is a systematic error because the data is all wrong by the same amount each time a measurement is taken. A zero calibration error occurs when the initial value shown by a measuring instrument is not zero when it should be zero. For example, a scale may show 0.001 g, even when nothing is being weighed.

• Environmental effects are caused by external factors such as temperature or humidity. For example, the measurements taken using a metal ruler will differ depending on the temperature. In low temperatures the ruler will contract, whereas in warmer temperatures it will expand. This means that all the measurements taken under those particular conditions would always be lower or higher than the correct value.

• Observation errors are caused by making the wrong observations or reading instruments incorrectly. For example, parallax error may occur when the observer’s eye is positioned at an angle to the measurement markings instead of level (Figure 1E.5), causing the recorded data to be either larger or smaller than the correct value.

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Figure 1E.5 The position where there is no parallax is the correct eye level for reading the measurement.

Choosing the best equipment and using a method that avoids systematic errors will improve the accuracy of the experiment. For example, you could use an electronic timer system to record measurements at given time intervals rather than rely on a human to use a hand-operated stopwatch.

Random errors

Even if careful experimental design removes systematic errors, random errors will affect the accuracy of a measurement. Random errors are caused by limitations of the measurement device and the observer, and are equally likely to be positive or negative because they do not follow a regular pattern. They can be caused by the experimenter’s inability to obtain the same measurement in the same way to get the same result. For example, you might measure the mass of a piece of magnesium ribbon three times using the same balance and get three results that vary slightly: 1.36 g, 1.38 g and 1.39 g.

Reading errors

Reading errors can occur when a measurement falls between two measurement markers. In this case, you would have to estimate the value, and this would differ between observers. It is likely that half of the results obtained would be estimates that are too large and half would be too small. These effects are an unavoidable part of doing experiments and can affect the precision of results, but the error can be reduced by repeating the experiment many times and taking average values.

Uncertainty

Due to random and systematic effects in the experimental process, there will always be a margin of doubt about any of your results – this is known as the uncertainty of the measurements. But how big is this margin? We have looked at how errors can arise, but we need to be able to quantify them. The uncertainty of any measurement can be estimated in one of two ways: absolute or relative.

Absolute uncertainty

The first way to estimate uncertainty is to state a range or interval around a measured value that quantifies the likelihood that a repetition of the experiment would produce a new result that would lie within this interval.

The notation for a measurement and its uncertainty should take the following format (remember to add the appropriate units):

measured value ± uncertainty

where ± means “give or take”. This tells us the absolute uncertainty

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The following rules are often used to determine the absolute uncertainty for a single measurement when using either an analogue scale or a digital measuring instrument.

• The uncertainty in an analogue-scale measuring instrument is equal to the smallest increment of the instrument divided by two.

• The uncertainty in a digital measuring instrument is equal to the smallest increment of the instrument.

random error an error caused by limitations of the measurement device or the observer; it does not follow a regular pattern reading error a reading or measurement that is not the true value

uncertainty the doubt that a measured value is the true value

absolute uncertainty the size of the range of values within which the actual “true value” of a measurement probably lies

Video: Worked example 1E.1

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Figure 1E.6 There are different rules for estimating uncertainty for single measurements using (a. and c.) analogue or (b. and d.) digital instruments. Remember to include units!

However, if we take multiple measurements to calculate a mean, we can estimate the absolute uncertainty by calculating half the range, as shown in Worked example 1E.1.

WORKED EXAMPLE 1E.1

Calculating absolute uncertainty

A student measured the mass of a piece of magnesium ribbon three times and recorded the following values: 1.36 g, 1.38 g and 1.39 g. Calculate the absolute uncertainty.

Calculating the mean 1.36 + 1.38 + 1.39 3 = 1.38 g To calculate the mean, add the values collected. Then divide this by the number of values collected. In this case, there are three values.

Calculating the range 1.39 1.36 = 0.03 gTo calculate the range, subtract the minimum value from the maximum value.

Calculating the uncertainty 0.5 × 0.03 = 0.015 gTo calculate the uncertainty, take half the range. This can be rounded up to 0.02 g because this is the same number of decimal places as the measurements.

Mass = 1.38 ± 0.02 gYou can then include this uncertainty when communicating the results. The mass of the magnesium can therefore be expected to be between 1.36 g and 1.40 g. Uncertainty = 1 V 2 =

Relative uncertainty

The uncertainty of any measured value can also be expressed as a percentage or as a ratio. This is relative uncertainty . It is calculated by dividing the absolute uncertainty of the result by the result itself. The relative uncertainty can be more useful than the absolute uncertainty because it puts your experimental data into perspective. For example, if you made an error in measuring the length of your eraser, it would be more noticeable than if you made the same error when measuring the table. Relative uncertainty does not have units, unless the uncertainty is multiplied by 100, where it is reported as a percentage.

WORKED EXAMPLE 1E.2

Calculating relative uncertainty

You measured the length of your table (80.0 cm) and your eraser (5.0 cm) using a metre rule.

Length of table = 80.0 cm ± 0.05 cm

Length of eraser = 5.0 cm ± 0.05 cm

The absolute uncertainty of both measurements is ±0.05 cm. Calculate the relative uncertainty of both measurements.

Solution

Calculating the relative uncertainty

Relative uncertainty of table length 0.05 80.0 = 0.000625

Relative uncertainty of eraser length 0.05 5.0 = 0.01

Calculating the percentage uncertainty

Percentage uncertainty of table length 0.000625 × 100 = 0.0625%

Percentage uncertainty of eraser length

0.01 × 100 = 1%

Explanation

To calculate the relative uncertainty, divide the absolute uncertainty of a value by the value.

relative uncertainty the ratio of the absolute uncertainty to the reported value, often expressed as a percentage

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This can then be reported as a percentage by multiplying by 100. We can now see that the relative uncertainty of the eraser measurement is much higher than that of the table measurement.

Worked example 1E.2 illustrates the importance of considering both absolute and relative uncertainty when reporting measurement results. While the absolute uncertainty is the same for both the table and the eraser measurements, the relative uncertainty is significantly higher for the eraser due to the eraser’s smaller size.

Uncertainty when measuring length

When we measure length, we normally use a ruler or a tape measure. These are scale-measuring instruments, so the uncertainty should be equal to half the smallest increment of the instrument. The smallest division of a ruler you probably have is one millimetre, producing an uncertainty of 0.5 mm or 0.05 cm.

If you were measuring the length of an eraser, you would place the eraser so it was aligned at zero on your ruler, so there is an additional ±0.05 cm error at that end. Therefore, the total error for a centimetre ruler is 0.05 cm + 0.05 cm = ±0.1 cm.

Video: Worked example 1E.2

Which uncertainty should be recorded?

Often, you will be completing an experiment that uses equipment and involves recording multiple measurements. The accuracy of your investigation should consider the unit in which you are measuring the dependent and independent variables, as well as the precision of the instruments you are using (Figure 1E.7). You should always record the largest source of uncertainty.

Figure 1E.7 Measurement tools vary in their precision.

Experimental precision

Experimental precision refers to how closely repeated measurements agree with each other. For example, let’s say you record the mass of a product of a chemical reaction in grams (g) and you repeat the experiment four times, getting results of 1.54 g, 1.55 g, 1.55 g and 1.54 g. The data shows low variation from the mean (it is clustered tightly) and can be said to be precise. Note that, even though this data is precise, it is not necessarily accurate. Precision does not give us an indication of how ‘true’ the data is –that is, how accurately it matches the actual values. The reading of values on glassware such as burettes and measuring cylinders can sometimes affect precision, particularly when the experimenter needs to estimate a value between graduated markings.

In science, we distinguish the sensitivity of a measuring instrument from precision. Sensitivity refers to the smallest change in a value that the instrument can detect or measure, whereas precision refers to the consistency of the readings.

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but not accurate

Precise and accurate Accurate but not precise

Figure 1E.8 Precision is not the same as accuracy. A faulty piece of measuring equipment might consistently give wrong values, like the target on the left. This measurement would be precise, but the results are inaccurate and do not measure what they claim to measure; therefore, they have low validity. Note that there are some diagrams that use this dartboard analogy for the broader term “reliability”, but it is best restricted to showing the more specific term “precision”.

Precise

Standard deviation

Standard deviation is a measure of how spread out the values in a data set are from the mean (average). A low standard deviation means most results are close to the mean, indicating consistent data with little variation. A high standard deviation means the results vary widely from the mean, showing greater inconsistency (Figure 1E.9). In scientific investigations, standard deviation is used to judge the reliability of data; smaller deviations suggest more reliable and repeatable results, while larger deviations indicate greater uncertainty.

WORKED EXAMPLE 1E.3

Calculating standard deviation

Narrow curve

Low standard deviation

Spread out curve

High standard deviation

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Figure 1E.9 A comparison of high and low standard deviation, indicating how spread out the data is

standard deviation a measure of how spread out values are around the mean

The oxygen output (mL/min) from five trials of photosynthesis was recorded as follows.

4.8, 5.0, 5.2, 5.0, 4.9

Calculate the standard deviation of the results.

Solution

4.8 + 5.0 + 5.2 + 5.0 + 4.9 5 = 4.98 mL/min

4.8 4.98 = 0.18

5.0 4.98 = 0.02

5.2 4.98 = 0.22

5.0 4.98 = 0.02

4.9 4.98 = 0.08

0.182 + 0.022 + 0.222 + 0.022 + 0.082 5 = 0.018

0.018 = 0.13

Statistical significance

Explanation

Step 1. Calculate the mean by adding all the values together and dividing by the total number of values.

Step 2. Calculate each value’s difference from the mean, by subtracting the mean from the value. Note that values that are lower than the mean have a negative difference.

Step 3. Calculate the variance by squaring each difference and dividing by the total number of values.

Step 4. Calculate the standard deviation by taking the square root of the variance. A low standard deviation indicates that the results are consistent.

Statistical significance is a further method of analysing data. It is a statistical test for working out the likelihood of a hypothesis not being true. This involves determining a p-value, which is a measure of whether the relationship between variables is caused by something other than chance (i.e. the hypothesis).

A small p-value indicates that it is unlikely that the data would result if it weren’t for the variables interacting. This therefore indicates that there is significant evidence to support the experimental hypothesis. Typically a p-value under 0.05, which roughly corresponds to two standard deviations from the mean, is deemed to be statistically significant.

NOTE

While statistical significance is commonly used as an important measure in scientific studies, students are not expected to use this at Stage 6 level.

Worked example 1E.3

Video:

outlier a data value that appears to stand out from the other members of the data set by being unusually high or low

Assessing validity, reliability, accuracy and precision

Table 1E.2 summarises the four experimental factors that will affect the quality of the data you collect.

Table 1E.2 Validity, reliability, accuracy and precision

TermDefinition

ValidityWhether the investigation tests what it intends to test

ReliabilityConsistency of the results across repeated trials

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Example

Measuring enzyme activity with correct variables controlled

Three trials give similar data

AccuracyHow close a measurement is to the true valueA correctly calibrated thermometer reads 25°C for a 25°C sample

PrecisionHow close repeated measurements are to each other Readings of 5.00, 5.01 and 5.02 mL show high precision.

Each of the factors listed in Table 1E.2 can be further improved. Below are suggested ways to enhance each experimental factor.

• Validity – control variables and ensure the method matches the hypothesis.

• Reliability – increase repetition and sample size.

• Accuracy – calibrate equipment and reduce human error.

• Precision – use fine-scale instruments and consistent measuring techniques.

Interpreting data to identify outliers, make predictions and draw conclusions

Identifying outliers

An outlier is a result that lies well outside the pattern of the rest of the data. Outliers may indicate:

• experimental error (e.g. faulty equipment)

• data entry errors (human miscalculation)

• natural biological variation.

Always check whether an outlier should be included or excluded, and give justification.

Investigating outliers

It is important that outliers are investigated and accounted for in the discussion of your results. Sometimes, repeating the experiment eliminates the outlier, but you need to mention that this has occurred. Outliers can easily be spotted when data is graphed. There will often be a large gap between an extremely high or low value and the other observations, indicating that it differs greatly.

Figure 1E.10 Outliers are often easily spotted in graph form.

Outlier

Making predictions

When data shows a clear trend, you can use it to extrapolate (predict beyond the measured values) or interpolate (predict within the measured values).

Predictions should always be logical and supported by evidence.

Extrapolation

Outside of known values

Interpolation

Between two known values

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extrapolate to predict values outside the range of known data points based on the existing trend interpolate to estimate unknown values within the range of known data points

For example, if a graph shows a linear increase in enzyme activity with increasing temperature up to 40°C, interpolation can estimate enzyme activity at 35°C, and extrapolation can predict activity at 45°C. These techniques are valuable for making informed predictions and understanding trends beyond the collected data. They can be used in the discussion of your results and in your conclusions. Predictions from interpolation and extrapolation can also be used in further research.

Evaluating evidence and drawing conclusions

To draw valid conclusions, you need to apply scientific concepts to interpret the data accurately. For instance, understanding the principles of photosynthesis can help you explain why increased light exposure enhances plant growth. Your conclusions should be directly supported by the evidence you collected during the investigation, and you should also state whether your results support or refute your hypothesis. This involves comparing the observed results with the expected outcomes based on the hypothesis.

A conclusion:

• directly answers the hypothesis

• summarises key findings

• refers to specific data values

• acknowledges limitations and suggests further research.

For example, if the data shows that increasing light intensity raises photosynthetic rate until it levels off, the conclusion might state:

“Light intensity is directly proportional to photosynthetic rate up to 500 μmol m−2 s−1, after which the rate plateaus, suggesting another limiting factor, such as CO2 availability.”

1E.12 If a hypothesis states that increased sunlight will enhance plant growth, data showing higher growth rates in plants exposed to more sunlight would support the hypothesis. Conversely, if the data showed no significant difference or a decrease in growth, it would refute the hypothesis.

Figure

Figure 1E.11 Extrapolation and interpolation

Go online to access the

Evaluating data to suggest improvements or further investigations

Evaluation involves reflecting on the quality of the data and considering how the investigation could be improved, or asking “What next?” for further investigations.

Possible improvements:

• increase the number of trials for greater reliability

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• use digital instruments for greater precision

• control the environmental variables more tightly

• collect a larger sample size

• repeat under different conditions.

Further investigations:

• test a different variable (e.g. light wavelength instead of intensity)

• extend the range of data collected

• conduct long-term observations

• compare results with other species or conditions.

For example, if soil pH was shown to affect seed germination, a further investigation to refine understanding might test how pH interacts with soil moisture.

Summary of analysing data and information

In this section, you learned how to:

• describe relationships between variables

• explain patterns, trends and inconsistencies

• calculate error, uncertainty, mean, range and standard deviation

• evaluate validity, reliability, accuracy and precision

• interpret data to identify outliers, make predictions and draw conclusions

• suggest improvements and further investigations to refine scientific understanding.

SECTION 1E REVIEW

Review questions

1. Why is a result that is both valid and reliable stronger than one that is only reliable?

2. How can a result be precise but inaccurate?

3. Define “outlier”.

4. Why should conclusions always refer back to the hypothesis?

5. Give two ways to improve the reliability of an investigation.

6. Suggest one possible follow-up investigation after finding that temperature affects enzyme rate.

1F Problem-solving in Biology

SYLLABUS

At the end of this section, I will be able to:

1F.1 Apply scientific principles to address real-world applications and problems

Worksheet 1F.1

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quiz questions download word download

1F.2 Use modelling and cause-and-effect relationships, including mathematical examples, to make predictions, explain phenomena and solve problems

1F.3 Evaluate and modify a scientific investigation in response to new evidence

1F.4 Explain why current scientific knowledge is both contestable and testable by further inquiry

Applying scientific principles to real-world problems

Scientific principles form a foundation for addressing issues that affect living organisms and their environments. These principles include biological studies such as cell theory, evolution, genetics, ecology, homeostasis and energy transfer. Look at Table 1F.1 to understand how to determine a biological application from a real-world problem.

Table 1F.1 Applying scientific principles to real-world problems

Real-world problemScientific principle Biological application

Disease outbreaksGerm theory of disease

Understanding pathogen transmission to control pandemics

Coral bleachingPhotosynthesis and symbiosisManaging temperature stress in coral ecosystems

Antibiotic resistanceNatural selection

Loss of biodiversityEcology and conservation

ACTIVITY 1F.1

Case study: managing eutrophication

Excess nutrients in waterways cause algal blooms, which reduce oxygen and kill aquatic life. The presence of excess nutrients in waterways is known as eutrophication, and is a growing environmental challenge affecting aquatic biodiversity, fisheries and water quality. By applying ecological principles, such as energy flow and nutrient cycling, scientists can recommend reducing fertiliser run-off and restoring wetland filters to absorb excess nutrients.

Developing new drugs and promoting responsible antibiotic use

Designing wildlife corridors and breeding programs

Declining pollinator populations

In this research task, you will investigate the causes, impacts and possible management strategies of eutrophication in Australian freshwater or coastal ecosystems. You will apply biological principles, model cause-and-effect relationships, and propose an evidence-based solution.

You are to:

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contestable open to challenge or reinterpretation

1. Select an Australian case study of eutrophication (e.g. Lake Macquarie, Murray–Darling Basin, Gippsland Lakes, Tuggerah Lakes).

2. Describe the biological processes involved, including:

• nutrient cycling (nitrogen and phosphorus)

• photosynthesis and respiration in aquatic systems

• energy flow and population interactions.

3. Analyse data (graphs, tables or government data sets) that shows evidence of eutrophication, such as changes in dissolved oxygen, algal biomass or species diversity.

4. Develop a scientific model (diagram, flow chart or mathematical representation) showing cause-and-effect relationships between human activity and ecological change.

5. Evaluate management strategies already implemented to address eutrophication, identifying their effectiveness, limitations and scientific basis.

6. Propose a new or modified solution, supported by evidence and sound biological reasoning.

7. Reflect on scientific knowledge as contestable and testable, discussing how new monitoring technologies (e.g. satellite imaging, biosensors or genetic testing) could influence current understanding or management approaches.

Using modelling and cause-and-effect relationships

Models in science

Models help scientists visualise, predict and explain biological processes. A model can be:

• physical (e.g. three-dimensional models of cells)

• conceptual (e.g. flow diagrams showing nutrient cycles)

• mathematical (e.g. equations predicting population growth).

Figure 1F.1 This three-dimensional model of a cell is an example of a physical model.

Nitrogen fixation by lightning

Nitrogen fixation by free-living bacteria in soil

Ammonia (NH3) and ammonium (NH4 + )

Free nitrogen (N2)

Nitrogen fixation by nitrogen-fixing bacteria in root nodules

Assimilated by animals

Urea, egested material and the bodies of dead organisms are broken down by decomposers (ammonification )

Nitrification by nitrifying bacteria

Denitrification by denitrifying bacteria (often in waterlogged soils)

Assimilated by plants

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Ammonia (NH3) and ammonium (NH4 + )

Nitrification by nitrifying bacteria

Nitrification by nitrifying bacteria

Figure 1F.2 A flow diagram of the nitrogen cycle is an example of a conceptual model.

Growth rate (r ) = (final population – initial population ) initial population × time

If r > 0, the population is increasing; if r < 0, it is declining.

Figure 1F.3 An equation predicting population growth is an example of a mathematical model. In biology, events rarely occur in isolation. A cause produces an effect, which can often be described mathematically or symbolically.

Evaluating and modifying investigations in response to new evidence

Science is dynamic: as new data is collected, it can challenge existing conclusions. When new evidence emerges, scientists must re-evaluate, revise or extend their investigations. An example of revising a hypothesis is as follows.

Initial hypothesis: “Plant growth is unaffected by salt.”

New evidence: Growth decreases as salt concentration increases.

Next step: Modify the investigation to test how salt affects water uptake and enzyme activity.

Steps for evaluation and modification.

1. Review the results and compare them with previous studies.

2. Identify inconsistencies or new findings.

3. Revise the method – adjust controlled variables, instruments or sample size.

4. Formulate a refined hypothesis.

5. Repeat the experiment to confirm the new predictions.

ACTIVITY 1F.2

Applied case study: re-evaluating climate models that predict coral bleaching events

Background

Coral reefs are highly sensitive to ocean temperature changes. Early computer models predicted that significant coral bleaching would occur only when sea surface temperatures (SST) exceeded +2°C above average. However, recent satellite and field data from the Great Barrier Reef (GBR) show widespread bleaching at only +1°C, prompting scientists to review and modify existing climate and ecological models.

Research context

A team of marine biologists and climate scientists at the Australian Institute of Marine Science (AIMS) set out to refine their model.

Step 1. Review the results

The team compared the 2024 bleaching data with earlier predictions.

• They observed that bleaching intensity and spatial spread were double the predicted value for the same temperature anomaly.

Step 2. Identify inconsistencies

The existing model did not account for:

• cumulative heat stress (repeated exposure to smaller temperature rises)

• solar radiation intensity

• reduced water flow from changes in ocean currents.

Step 3. Revise the method

The researchers incorporated new variables:

• average number of heatwave days per season

• local water movement rates

• cloud cover and radiation data.

Step 4. Formulate a refined hypothesis

“Coral bleaching intensity is determined not only by temperature but also by the combined effect of thermal stress duration and solar exposure.”

Step 5. Repeat and validate

The scientists tested the new model using data from three separate reef regions and found that bleaching events could now be predicted with 91% accuracy, compared to only 65% in the previous version.

Scientific principle applied

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This case demonstrates how new evidence can require existing scientific models to be modified, improving their predictive power and guiding conservation action. Revised models now help identify priority reef protection zones and inform early-warning systems for coral bleaching.

Data snapshot

Applied questions

1. What inconsistency prompted scientists to modify the original climate model?

2. Identify two new variables that were added to the revised model.

3. State the refined hypothesis produced by the researchers.

Science as contestable and testable knowledge

Contestable knowledge

Scientific ideas are contestable because they are open to questioning, debate and re-evaluation. Competing interpretations often drive discovery. For example:

• Early cell theory excluded viruses. This has been re-examined because of advances in virology.

• The theory of continental drift was contested until evidence from seafloor spreading confirmed plate tectonics.

Testable knowledge

Scientific knowledge is testable when it can be supported or disproved by experimentation or observation. An example is Pasteur’s swan-neck flask experiment. Pasteur tested the hypothesis that microorganisms arose spontaneously. His experiment refuted the theory of spontaneous generation , confirming that microbes come from other living organisms, demonstrating testability and falsifiability.

The role of peer review

Scientific claims are tested by:

• replication of the experiment by other scientists

• peer review of the results before publication

• debate and refinement of theories within the scientific community.

spontaneous generation the discredited belief that living things develop spontaneously from non-living matter

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Figure 1F.4 Advances in virology (the study of viruses) has advanced and changed our understanding of how viruses relate to cells and cell theory.

Figure 1F.5 An artist's impression of Louis Pasteur working in his laboratory

scientific principle a general rule or law explaining how aspects of the natural world behave cause and effect the principle that one event (cause) leads to another (effect)

Summary of problem-solving

In this section, you learned how biologists:

• apply scientific principles to real-world problems

• use models and cause-and-effect reasoning to make predictions

• evaluate and adapt investigations when new evidence arises

• understand that scientific knowledge is contestable, testable and self-correcting.

SECTION 1F REVIEW

Quiz

Go online to access the Interactive Textbook

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Review questions

Review questions

Reporting (student and teacher)

1. Do online research to answer the question: How does scientific knowledge about photosynthesis help solve environmental issues such as deforestation?

2. Do online research to answer the question: What scientific principle underpins vaccination programs?

3. Give one advantage of using mathematical models in biology.

4. What is meant by a cause-and-effect relationship? Provide a biological example.

5. Identify one limitation of using a physical model in scientific research.

6. A student records the rate of photosynthesis (O₂ produced per minute) at different light intensities and obtains the following data.

a. Plot this data as a graph and describe the trend.

b. Identify the cause and the effect in this relationship.

c. Suggest a reason why O₂ production stops increasing beyond 400 μmol m−2 s−1.

7. What does it mean for scientific knowledge to be contestable?

8. Why must scientific knowledge always be testable?

reporting

1G Communicating in Biology

SYLLABUS

At the end of this section, I will be able to:

1G.1 Construct evidence-based arguments and recognise the role of peer review in the evaluation of scientific practices, solutions or conclusions

Worksheet 1G.1

Antibiotic resistance

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1G.2 Select and use appropriate digital, visual, written and oral media to convey scientific arguments

1G.3 Apply appropriate scientific notations, language and nomenclature

1G.4 Use evidence and correct scientific language and terminology to address a specific audience and purpose in a variety of contexts

Science depends on clear communication. Biologists must present evidence, justify conclusions and engage specific audiences – teachers, peers, government or the general public. This section will help develop your ability to construct evidencebased arguments , use appropriate scientific language, and communicate using written, oral and digital media.

Constructing evidence-based arguments and peer review

What is an evidence-based argument?

An evidence-based argument uses reliable data and logical reasoning to support or challenge a scientific claim. It includes:

• a claim – a statement or conclusion

• evidence – data, observations or research that supports the claim

• reasoning – the logical link explaining how the evidence supports the claim.

Evidence-based argument example

Claim: Increased CO2 concentration raises global temperatures.

Evidence: Satellite data shows a 1.1°C increase in global temperatures since 1900, correlating with a 50% rise in atmospheric CO2.

Reasoning: CO2 traps infrared radiation, enhancing the greenhouse effect.

The role of peer review

Peer review is the process in which scientists critically evaluate each other’s research before the results of that research are published. Peer review ensures that:

• the evidence is credible and verifiable

• the method used is valid and reproducible

• any conclusions reached are logical and unbiased.

The benefits of peer review are that it:

• maintains scientific accuracy

• builds public trust in scientific findings

• identifies methodological flaws or bias.

evidence-based argument a scientific claim supported by reliable data and logical reasoning

Using appropriate media to communicate in science

Biologists communicate through a range of media, depending on the purpose and the audience. Some examples are outlined in Table 1G.1.

Table 1G.1 Examples of communication media and their purpose

Communication medium Purpose

Examples

Written Record findings, report resultsScientific reports, journal articles, lab summaries

Visual

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Illustrate patterns and trendsGraphs, diagrams, infographics

Oral Present or persuade Presentations, debates, interviews

Digital Share and collaborate widelySlideshows, blogs, videos, podcasts, animations

When deciding which format is the most appropriate form of communication, scientists ask the following questions.

• Who is my audience (students, experts, public)?

• What is my purpose (inform, persuade, evaluate)?

• Which media type will best represent my data and my argument?

For example, a scientist who wants to explain coral bleaching data might:

• use a line graph to show temperature trends

• add photographic evidence of reef changes

• record a short video summary for public awareness.

ACTIVITY 1G.1

Presenting on a scientific

issue

Design a two-minute digital presentation explaining one current biological issue (e.g. microplastics, invasive species). Your presentation must:

• include one visual aid (graph or image)

• use correct scientific terminology

• conclude with one evidence-based recommendation.

Figure 1G.1 Bleached coral in the Great Barrier Reef

Scientific notation, language and nomenclature

Clear communication relies on accuracy and consistency. Scientists follow strict conventions for naming, measuring and writing results.

Scientific notation

Scientific notation is a way of writing very large or very small numbers. For example:

6,000,000 = 6.0 × 106

0.00042 = 4.2 × 10 4

Units and symbols

• Use SI units (m, g, L, mol).

• Always include uncertainty or error margins when appropriate (e.g. 25.0 ± 0.5°C).

Biological nomenclature

Scientific names are written using a system known as binomial nomenclature

Each name consists of two words: the genus and the species (e.g. Escherichia coli).

• The genus name is capitalised.

• The species name is all lowercase.

• The full name is in italics (or underlined if handwritten).

• The genus name can be abbreviated to an initial after the full name has been already mentioned (e.g. E. coli).

Scientific language

Genus name is capitalised species name is lowercase

Homo sapiens

Written in italics

Figure 1G.2 The scientific name for humans, written using the binomial system

• Use objective, precise terms (e.g. “hypothesis”, “variable”, “anomaly”).

• Avoid subjective or emotive words (e.g. “good”, “bad”, “proves”).

Communicating to a specific audience for a specific purpose

Adapting communication

Scientific communication varies depending on the audience’s knowledge and the purpose of the communication. Table 1G.2 outlines some examples.

Table 1G.2 Different approaches to scientific communication, depending on the audience

Scientific peers Present findings Use precise language, data tables and references Students/general public Explain concepts Use clear analogies, visuals and simple terms

scientific notation a way of expressing numbers using powers of ten

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binomial nomenclature a system of naming organisms scientifically, using two words (genus and species)

Example 1 – For scientists

“The data indicates a statistically significant (p < 0.05) increase in mean chlorophyll concentration correlating with nitrogen load.”

Example 2 – For the public

“Higher fertiliser run-off causes more algae to grow in rivers, reducing oxygen for fish.”

Both statements describe the same result, but the language and tone differ for the target audience.

Summary of communicating in science

In this section, you learned to:

• construct evidence-based scientific arguments

• recognise the importance of peer review

• select suitable media and communication formats

• apply correct scientific notation and nomenclature

• adapt your communication for different audiences and purposes.

ACTIVITY 1G.2

Translating science

Rewrite the following scientific statement for a non-specialist audience.

“Anthropogenic CO2 emissions have accelerated ocean acidification, reducing calcification rates in marine organisms such as molluscs and corals.”

SECTION 1G REVIEW

Go online to access the Interactive

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Review questions

1. Define “evidence-based argument”.

2. What are two purposes of peer review in science?

3. Convert 0.00053 L to scientific notation.

4. Write the correct scientific name for a human being.

5. Why is it important to use SI units and consistent notation?

6. Suggest two ways to make complex data accessible to a general audience.

Chapter review

Revise and consolidate your learning with these online tools:

• Success criteria checklist (view online or download)

• Review questions (answer online or download)

• Suggested responses (view online with teacher enabled access)

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• Depth study support (download)

Teachers can access these additional downloadable resources and Learning Management System features:

• Individual and whole class reports

• Assign tasks and track results

• Create (and print) custom practice exams

• Chapter tests (download)

• Chapter summaries (download)

Success criteria checklist

Check your understanding of the Working scientifically skills using the linked questions below. Throughout this course, you will be expected to apply these skills in context. The remaining chapters in this resource will provide you with opportunities to do so.

I am now able to:

1A.1 Use observations and scientific knowledge and understanding to propose questions and hypotheses for scientific investigations involving primary and secondary data 18

1A.2 Evaluate questions and hypotheses based on scientific knowledge1, 2 (1A review)

1A.3 Modify questions and hypotheses to reflect new evidence 3, 4 (1A review)

1B.1 Justify the use of independent, dependent and controlled variables, and experimental controls in a valid scientific investigation 6

1B.2 Explain how reliable primary data is obtained 18

1B.3 Assess the reliability of secondary data and information when planning7, 18

1B.4 Assess potential hazards and their associated risks to develop a risk assessment 4 (1B review)

1B.5 Select appropriate materials and technologies to design a scientific investigation 5 (1B review)

1B.6 Discuss ethical issues in the development and use of scientific knowledge 6 (1B review)

1C.1 Apply safe work practices and manage risks while conducting a scientific investigation 1 (1C review)

1C.2 Construct and manipulate identified materials and technologies to perform scientific investigations 2, 3 (1C review)

1C.3 Use equipment appropriately and systematically to collect and record data, information, evidence and findings 4 (1C review)

I am now able to:

1C.4 Gather data and information from a range of secondary sources 5 (1C review)

1D.1 Select qualitative and quantitative information from texts, diagrams, flow charts, tables, databases, graphs and multimedia resources 16

1D.2 Apply quantitative processes to data, including unit conversions 1, 2

1D.3 Select and use a range of representations to organise data and information, including graphs, keys, models, diagrams, tables and spreadsheets 13, 14

1D.4 Extract data and information from a wide range of sources and acknowledge these sources using an accepted referencing style 19

1D.5 Describe the Cultural Knowledges and observations of Aboriginal and Torres Strait Islander Peoples and examine how these contribute to the development of scientific knowledge 1, 2, 3 (1D review)

1E.1 Describe qualitative and quantitative relationships between variables 21

1E.2 Explain patterns and trends, including inconsistencies in data and information 16, 22

1E.3 Assess error, uncertainty and limitations in data and include calculations of percentage error, range, mean and standard deviation 9, 23, 24

1E.4 Assess the validity, reliability, accuracy and precision of data and information 3, 4, 5, 12

1E.5 Interpret data and information to identify outliers, make predictions, explain results and draw conclusions 10

1E.6 Evaluate data and information to suggest improvements or further investigations 17

1F.1 Apply scientific principles to address real-world applications and problems 1, 6 (1F review)

1F.2 Use modelling and cause-and-effect relationships, including mathematical examples, to make predictions, explain phenomena and solve problems 8

1F.3 Evaluate and modify a scientific investigation in response to new evidence 17

1F.4 Explain why current scientific knowledge is both contestable and testable by further inquiry 11

1G.1 Construct evidence-based arguments and recognise the role of peer review in the evaluation of scientific practices, solutions or conclusions 11

1G.2 Select and use appropriate digital, visual, written and oral media to convey scientific arguments 15

1G.3 Apply appropriate scientific notations, language and nomenclature 20

1G.4 Use evidence and correct scientific language and terminology to address a specific audience and purpose in a variety of contexts 15, 20

Multiple-choice questions

1. Convert 0.035 kg to grams.

A. 0.35 g

B. 3.5 g

C. 35 g

D. 350 g

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2. A bacterial culture increases from 200 cells to 600 cells in 3 hours. What is the approximate rate of growth (cells per hour)?

A. 133

B. 100

C. 400

D. 33

3. Which of the following best describes validity in a scientific investigation?

A. the closeness of measurements to the true value

B. the consistency of repeated results

C. how well the investigation tests the intended hypothesis

D. the spread of results around the mean

4. A student repeats an experiment five times and obtains very similar results each time. What does this indicate?

A. high validity

B. high reliability

C. high accuracy

D. high precision

5. Which scenario shows high precision but low accuracy?

A. Values are close to the true value but inconsistent.

B. Values are clustered closely together but far from the true value.

C. Values are spread out but all slightly below the true value.

D. Values match the published value exactly.

6. What is the purpose of a negative control in an experiment?

A. to test the full effect of the independent variable

B. to show a condition where a known response should occur

C. to show a condition where no response should occur

D. to replace the independent variable entirely

7. Which of the following is an example of using secondary data?

A. measuring the mass of a sample in the lab

B. conducting your own titration

C. reading a peer-reviewed study and using its data

D. observing results from your assigned group

8. When the temperature exceeds an enzyme’s optimum, why does the reaction rate decrease sharply?

A. The substrate concentration becomes zero.

B. The active site denatures and no longer binds the substrate.

C. More enzyme–substrate complexes form.

D. The enzyme becomes more efficient at high temperatures.

9. A low standard deviation indicates that the data

A. is usually inaccurate.

B. has large variation between trials.

C. is tightly clustered around the mean.

D. is probably invalid.

10. A student’s graph shows enzyme activity increasing from 5 units to 24 units as temperature rises from 10°C to 40°C. At 50°C, activity drops to 8 units. Which conclusion is most valid?

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A. Enzyme activity increases endlessly with temperature.

B. Enzyme activity is unaffected by temperature.

C. The enzyme works best at 50°C.

D. The enzyme has an optimum around 40°C, after which it denatures.

Exam-style questions

11. Explain why evidence must always be accompanied by reasoning. (2 marks)

12. Discuss why conducting an experiment only once is not enough to ensure reliability. (2 marks)

13. Identify one advantage of using a line graph over a bar graph. (1 mark)

14. Recall why every table should include units in its headings. (1 mark)

15. Discuss why audience awareness is important when communicating in science. (3 marks)

16. Explain what it means if data shows a non-linear trend. (1 mark)

17. Identify what could cause an inconsistent result in an experiment. (1 mark)

18. Describe the difference between primary and secondary data. (2 marks)

19. Identify a reason for referencing being important in scientific communication. (1 mark)

20. Compare the tone of a scientific report with that of a science news article. (3 marks)

21. Outline what the differences are between qualitative information and quantitative information. (3 marks)

22. Demonstrate an example of an inverse relationship in biology. (1 mark)

23. Summarise what a large standard deviation indicates. (1 mark)

24. Calculate the percentage error if a mass was measured as 9.7 g when the true mass was 10.0 g. (2 marks)

Cells as the basis of life

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SYLLABUS OUTCOMES

A student:

• explains how cell structures enable biological processes needed for life

CHAPTERS

2. Cell structures and functions

3. Cells and their environments

4. Biochemical processes

5. Cell division

Cell structures and functions 2

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Enhance your learning with these integrated online resources:

Students

Digital workbook

• Prior knowledge quiz

• Suggested responses

• Download or answer questions online

Videos

Teachers

• Chapter tests

• Exam generator tool

• Planning documents

SYLLABUS

CONTENT DOT POINTS: CELL STRUCTURES AND FUNCTIONS

At the end of this chapter, I will be able to:

2A.1 Use a variety of sources to compare the cellular structures of eukaryotic and prokaryotic cells

2A.2 Conduct a practical investigation to prepare a wet mount slide and identify the cytoplasm, cell wall and nucleus under a light microscope

2A.3 Describe the structure and function of the capsule, cell wall, cell membrane, cytoplasm, nucleoid, plasmid, ribosomes, flagella and pili in prokaryotic cells

2B.1 Contrast the cell structure and organelles of plant and animal cells based on the function of the cell

2B.2 Describe the structure and function of the cell wall, cell membrane, cytoplasm, nucleus, mitochondria, chloroplast, endoplasmic reticulum, Golgi body, ribosomes, lysosomes and vacuole in eukaryotic cells

2B.3 Conduct a practical investigation to calculate the size of a variety of specialised cells under the microscope using a mini-grid and the equation

Cell size = diameter of field of view number of cells across the field of view

2C.1 Assess the impact of technological developments in microscopy on scientific understanding of cell structure and function

GLOSSARY TERMS

archaea bacteria capsule cell membrane cell wall chloroplast cytoplasm endoplasmic reticulum (ER) endosymbiosis eukaryote flagella Golgi body

SECTION

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2C Microscopes

lysosome mitochondria nucleoid nucleus organelle pili plasmid prokaryote ribosome turgor pressure vacuole

2A Types of cells

2B Eukaryotic cells

Concept map

2A Types of cells

Common features of all cells

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Prokaryotic

Eukaryotic

2C Microscopes

How microscopes have impacted our understanding of cells

Plasma

Rough

2B Eukaryotic cells

Contrasting the structure and function of organelles in plant and animal cells

Vesicle

Cell

Plasma

Rough endoplasmic

Smooth endoplasmic reticulum

Chloroplast

2A Types of cells

SYLLABUS

At the end of this section, I will be able to:

2A.1 Use a variety of sources to compare the cellular structures of eukaryotic and prokaryotic cells

Worksheet 2A.1 Types of cells

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2A.2 Conduct a practical investigation to prepare a wet mount slide and identify the cytoplasm, cell wall and nucleus under a light microscope

2A.3 Describe the structure and function of the capsule, cell wall, cell membrane, cytoplasm, nucleoid, plasmid, ribosomes, flagella and pili in prokaryotic cells

Imagine tracing your family tree back not just for hundreds of years but for billions. At the very beginning, you wouldn’t find a human, a fish or even algae. Instead, you’d find something much simpler: a tiny, single-celled ancient ancestor. Scientists call this ancestor LUCA, the Last Universal Common Ancestor.

LUCA lived around 3.8 billion years ago in Earth’s ancient oceans. It wasn’t the first life form, but it carried a blueprint that would shape everything alive today: a cell membrane to separate inside from outside, genetic material (DNA or RNA) to store instructions, and tiny ribosomes to build proteins.

Over time, LUCA’s descendants split into two great lineages: bacteria and archaea . These are the simplest cells we find on Earth today, and we refer to them as prokaryotes . From within the archaeal lineage, some cells formed partnerships with bacteria, engulfing them rather than destroying them. This symbiotic relationship is known as endosymbiosis and is the most common theory used to explain the rise in eukaryotes , cells with complex internal structures such as nuclei and mitochondria. These eukaryotic cells would eventually diversify into plants, animals, fungi and countless multicellular life forms.

In this section, you’ll explore the differences between prokaryotic and eukaryotic cells.

Prokaryote versus eukaryote

Prokaryotes are unicellular and do not contain membrane-bound organelles . They are very small and contain genetic material, a cell membrane , cytoplasm and ribosomes . Some have other structures such as a cell wall or a capsule . Examples of prokaryotic organisms are bacteria and archaea. Table 2A.1 summarises the key structures found in all types of cells.

Table 2A.1 Structures found in all types of cells

Genetic materialContains hereditary information in the form of genes that code for proteins

Cytosol The liquid inside cells, consisting of 80% water, salts and organic molecules; the site of many cellular reactions

Ribosome The site of protein synthesis

Plasma (cell) membraneSeparates the interior and exterior environments, selecting what enters and leaves the cell

Video: Cell types and their common structures

bacteria unicellular, prokaryotic organisms that lack membrane-bound organelles

archaea an ancient type of prokaryotic cell, similar to bacteria

prokaryote a single-celled organism that does not have membrane-bound organelles; includes bacteria and archaea

endosymbiosis a close relationship in which one organism lives inside the cells of another and both may benefit; thought to be important in the evolution of eukaryotic cells

eukaryote a single-celled or multicellular organism whose cells include membrane-bound organelles; includes protists, fungi, plants and animals

organelle a compartment within a cell that performs specific functions

cell membrane a flexible structure made up of phospholipids and other materials that surrounds the cell, separating the interior of the cell from the exterior environment and selecting what enters or leaves the cell; sometimes called a plasma membrane

cytoplasm all the contents inside the membrane of a cell, except the nucleus; includes cytosol and organelles

ribosome an organelle involved in synthesis of proteins; not membrane-bound

Eukaryotes can be single-celled or multicellular organisms, and are much bigger and more complex than prokaryotes. Eukaryotic cells contain membrane-bound organelles. Examples of eukaryotic organisms are protists, fungi, plants and animals.

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cell wall a rigid structure that surrounds some types of cells (such as prokaryotes and plant cells) and provides shape and support; made of different materials depending on the cell type

Prokaryotic cell

• Lacks membrane-bound organelles

• Contains ribosomes

• Genetic material is usually one circular DNA chromosome located in an area known as a nucleoid

• Many contain small rings of double-stranded DNA called plasmids

• Plasma membrane is surrounded by a cell wall

• Some bacteria also have flagella (singular: flagellum) for movement and pili (singular: pilus) for attaching to surfaces

questions download word download pdf

capsule a protective outer layer that encloses some types of bacterial cells

nucleoid an irregularly shaped area in a prokaryotic cell where genetic material is located

plasmid a small, circular DNA fragment in prokaryotic cells that is separate to the nucleoid

flagella a long, whip-like appendage on the outside of some prokaryotic cells that is used for movement; singular: flagellum

pili small hair-like structures on the outside of some prokaryotic cells

nucleus an organelle in eukaryotic cells that contains the cell’s genetic material

Eukaryotic cell

Worksheet 2A.2

Key word revision

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• Contains ribosomes

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• Contains membrane-bound organelles

• Genetic material is linear DNA chromosomes contained within a nucleus

• Plasma membrane encloses the cytoplasm

• Cell wall is present in fungi, plants and some protists

• Many cell types (not fungi) have flagella or cilia for movement

questions download word download pdf

Nucleoid

PRACTICAL 2A.1

Observing onion cells under the microscope

Aim

To prepare a wet mount slide of onion epidermal cells and observe the cell wall, cytoplasm and nucleus under a light microscope using methylene blue stain.

Materials

• Light microscope (4×, 10×, 40× objectives)

• Clean glass slide and coverslip

• Forceps and scalpel (or scissors)

• Dropper/pipette

• Onion (brown or white), small piece

• Distilled water

• Methylene blue (0.1–1% aqueous solution)

• Paper towels

• Lens tissue or soft cloth

• Waste beaker

• Gloves, lab coat, safety glasses

Method

Prepare onion epidermis

1. Cut the onion in half along the stem, peel it and then cut into 2 cm thick slices.

2. Separate out the onion layers and cut them again to make 2 cm squares.

Be careful

• Wear eye protection and gloves. Methylene blue can stain skin and clothing.

• Handle scalpel/razor carefully; cut away from your body.

• Wipe spills immediately; dispose of stained waste to the designated beaker.

• Wash hands after the practical.

3. Peel a thin, translucent layer, one cell thick, from the inner surface of the onion square.

Mount the sample

4. Place the thin layer of onion onto the glass slide, making sure it is flat and not overlapping.

5. Add one small drop of methylene blue to the tissue, wait 30–60 seconds, and wick away the excess using the edge of a paper towel.

6. Lower a coverslip at a 45° angle, using a probe or toothpick to avoid bubbles.

Focus and observe

7. Start at 40× magnification (i.e. using the 4× objective), then move to 100 × and 400× magnification (using the 10× and 40× objectives respectively)

Results

Sketch a field of view at 100 × and 400× magnification. Remember that the total magnification includes the eyepiece lens, which is an additional 10× magnification. Always include the total magnification when labelling your drawings. Label cell wall, cytoplasm and nucleus.

NOTE

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If no nucleus is visible – use fresh tissue. Reduce stain (over-staining can obscure detail). If everything is too dark – wick away the stain with the edge of a paper towel. Add a drop of water to the side of the coverslip. Increase brightness.

If you can’t find any cells – start at low power (40× magnification). Focus on the edge of the tissue, then centre and increase magnification. If there are air bubbles – lower the coverslip slowly at an angle. Re-mount if bubbles cover the field. What you should see:

• cell wall – thick rectangular boundary (stains pale to mid-blue)

• cytoplasm – lighter blue/clear area inside the wall

• nucleus – darker round/oval body within the cytoplasm.

Discussion

1. Explain how methylene blue improves the visibility of cellular structures.

2. Differentiate between the function of the cell wall and the cell membrane in onion cells.

3. Estimate the average size of the cells.

4. Estimate the average size of the nucleus.

Prokaryote structure

Cell wall

Cytoplasm

Nucleus

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Although prokaryotic cells are very small compared to eukaryotic cells, and they lack membrane-bound organelles, they still perform all the essential functions of life. To achieve this, they rely on a range of specialised structures – these structures are listed in Table 2A.2.

Table 2A.2 Structures found in prokaryotic cells and their functions

Structure Function

Capsule Protective outer layer that prevents desiccation (drying out); helps bacteria adhere (stick) to surfaces; in pathogenic bacteria it also protects against phagocytosis by immune cells

Cell wall Rigid structure made mainly of peptidoglycan (sugar and amino acids); provides shape, support and protection from osmotic lysis

Plasma membrane (cell membrane)

Semi-permeable boundary controlling the movement of substances into and out of the cell

CytoplasmGel-like substance where metabolic reactions occur; contains enzymes, nutrients and genetic material

Nucleoid Region containing a single circular DNA chromosome; controls cell activities and stores genetic instructions; not membrane-bound

Plasmid Small, circular DNA fragment independent of chromosomal DNA; often thousands of times shorter than animal DNA

RibosomesSites of protein synthesis; smaller than eukaryotic ribosomes but have the same basic role

Flagella Long, whip-like appendages used for movement

Pili (fimbriae) Hair-like structures used for attachment to surfaces or other cells

Ribosomes

Cytosol

Cell wall

Plasma membrane

Nucleoid

Plasmid

Flagellum

Capule

Pili

Figure 2A.1 The structure of a prokaryotic cell

EXAM PRACTICE 2A

Example question

Compare prokaryotic and eukaryotic cells. (3 marks)

What is the question asking?

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The key verb in this question is compare, which means you need to show the relationship between things, or cause and effect. To compare, you need to include:

• at least one similarity and one difference; the number of each depends on the mark

• direct, point-to-point comparison using the same criteria for each item

• clear, explicit linking words.

Typical structure

1. State the similarities.

(“Both…”, “Similarly…”, “Each…”)

2. State the differences.

(“However…”, “In contrast…”, “Whereas…”)

You can also draw a table to help with comparing, as shown in the sample response below.

Marking criteria

Criteria

• Provides differences and similarities between prokaryotic and eukaryotic cells 3

• Provides a difference and a similarity OR

• Provides differences 2

• Provides relevant information 1

Sample response

Both prokaryotic and eukaryotic cells contain ribosomes, genetic material (DNA) and cytoplasm. However, only eukaryotic cells contain membrane-bound organelles. Prokaryotic

No membrane-bound organellesContain ribosomes, DNA and cytoplasm

SECTION 2A REVIEW

Contains membrane-bound organelles (e.g. nucleus, mitochondria, chloroplasts)

Review questions

1. Identify one specialised structure in prokaryotic cells that helps them avoid being destroyed by the immune system.

2. Describe the role of the cell wall in prokaryotic cells.

3. Explain how prokaryotic chromosomes differ from eukaryotic chromosomes.

4. Analyse how the presence of flagella and pili can increase the chances of survival for bacteria.

5. Identify what comprises cytosol.

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2B Eukaryotic cells

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SYLLABUS

Worksheet 2B.1

Eukaryotic cells

At the end of this section, I will be able to:

questions download word download pdf

2B.1 Contrast the cell structure and organelles of plant and animal cells based on the function of the cell

Worksheet 2B.2

Key word revision

2B.2 Describe the structure and function of the cell wall, cell membrane, cytoplasm, nucleus, mitochondria, chloroplast, endoplasmic reticulum, Golgi body, ribosomes, lysosomes and vacuole in eukaryotic cells

questions download word download pdf

2B.3 Conduct a practical investigation to calculate the size of a variety of specialised cells under the microscope using a mini-grid and the equation

Cell size = diameter of field of view number of cells across the field of view

Benefits of specialised organelles

A eukaryotic cell can be thought of as a highly organised and busy kitchen, where countless ingredients (reactants) must move, collide and transform into new products. For these reactions to occur efficiently, molecules need to be present at the right time and the right place. Eukaryotic cells are relatively large compared to prokaryotes, and so it would be inefficient for all reactions to occur in a single, open space.

This challenge is overcome through compartmentalisation. Eukaryotic cells contain specialised membrane-bound organelles, each dedicated to a specific function. The membrane of each membrane-bound organelle helps maintain optimal concentrations of reactants, creating ideal conditions for particular reactions to take place – for example, enzymes in lysosomes breaking down waste materials. By confining processes to specific organelles, multiple chemical reactions can take place simultaneously without interfering with one another. This not only increases the overall efficiency of the cell but also enables eukaryotic cells to sustain the complex activities required to grow to a larger size.

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Reactant molecules spread out in a large compartment.

If the reactant molecules are restricted to a smaller space by being enclosed in an organelle, they are more likely to bump into each other and react.

Figure 2B.1 The benefits of compartmentalisation within a cell

More organelles allow other specialised reactions to take place without being affected by the presence of other reactants.

Organelles

Eukaryotic cells contain many specialised organelles. Think of these organelles as mini organs, each with a specific role that contributes to the overall health of the cell. Depending on the specialised nature of the cell, the number of each organelle may change. For example, the muscle cells in your heart need a lot of energy constantly, and so they contain 30% more mitochondria, the energy-producing organelles, compared to a skin cell. The main organelles in eukaryotic cells are outlined below.

Plasma membrane

The plasma membrane (also known as the cell membrane) acts as a boundary between the internal and external environments of a cell. It is semi-permeable, meaning it can control what enters and leaves the cell. It contains a double layer of a phospholipid molecule known as a phospholipid bilayer, which is covered in more detail in Chapter 3. The cell membrane also plays a role in recognising and communicating with other cells using surface proteins. All cells have a plasma membrane.

Cytoplasm

The cytoplasm is all the contents inside the plasma membrane, except the nucleus. It includes cytosol (the liquid part where many cellular reactions occur) and organelles.

Cell wall

The cell wall surrounds plant cells and lies outside the plasma membrane. It contains cellulose, which is a strong rigid material, and provides structural support and protection in plants. Fungi have a cell wall made of chitin, which is softer and more flexible. Think about what would happen if you bent a stick of celery in half, compared to a mushroom – the mushroom would bend, whereas the celery would snap. Animal cells do not have a cell wall. Video: Organelles in plant and animal cells

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Phospholipid

Protein

Figure 2B.2 Structure of the plasma membrane

mitochondria

organelles in eukaryotic cells that produce ATP via cellular respiration; singular: mitochondrion

Matrix Genetic material

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Fungal cell

Proteins

Cell wall

Chitin

Cell membrane

Figure 2B.4 The structure of the cell wall and cell membrane in fungal cells

Figure 2B.6 Electron micrograph of mitochondria

Outer membrane Inner membrane

Ribosomes

Cristae

Figure 2B.5 Cross-section of a mitochondrion

Cells

Cell wall

Figure 2B.3 In plant cells, the cell wall is a rigid layer of cellulose.

Chloroplasts

Chloroplasts are the site of photosynthesis and are found in plant cells but not animal cells. They use light energy to convert carbon dioxide and water into glucose and oxygen. A chloroplast contains chlorophyll and has a double membrane, with internal structures called grana and stroma. The function of the chloroplast is covered in more detail in Chapter 3.

chloroplast an organelle where photosynthesis occurs; contains chlorophyll

Nucleus

The nucleus is a double-membrane-bound organelle containing the cell’s genetic material (DNA and RNA). It stores and protects the DNA, and directs the cell’s activities by using RNA to send messages throughout the cell. Nuclear pores allow selected materials to move into or out of the nucleus.

Thylakoid

Granum

Genetic material

Stroma

Ribosomes

Figure 2B.7 Cross-section of a chloroplast

Figure 2B.8 Electron micrograph of a chloroplast

Nuclear envelope

Nuclear pore

Figure 2B.9 The structure of a nucleus

Figure 2B.10 Electron micrograph of a nucleus

endoplasmic reticulum ( ER ) a long, folded membrane that connects to the nucleus and consists of rough and smooth components, which have different functions

Golgi body a series of stacked membranes that prepares proteins for transport to other parts of the cell or outside the cell

Endoplasmic reticulum

Rough ER

The endoplasmic reticulum (ER) is a long, folded membrane. The first part of the ER is known as “rough ER”. It is connected to the nucleus and is studded with ribosomes. It transports proteins in vesicles to the Golgi body .

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Smooth ER

Towards the end furthest from the nucleus, the ER lacks ribosomes and so is called “smooth ER”. Smooth ER is involved in the synthesis and transport of lipids. The diagrams in Figures 2B.11 and 2B.12 represent cross-sections of the ER and therefore may appear to have several separated components. However, note that in its entirety, the ER is one continuous membrane.

Ribosomes

Ribosomes are non-membrane-bound organelles and are found in both eukaryotic and prokaryotic cells. They convert RNA (messages from the nucleus) into protein. Proteins are a major component of all organisms – examples of proteins are antibodies in the immune system, haemoglobin in the blood, enzymes in the digestive system and even the pigment in your iris. Ribosomes in the cytosol produce proteins for internal use, while those on the rough ER produce proteins for export or membrane insertion.

Figure 2B.11 Rough endoplasmic reticulum

Figure 2B.12 Smooth endoplasmic reticulum

Golgi body (Golgi apparatus)

The Golgi body consists of stacked membranes that modify and package proteins into vesicles for secretion or use within the cell.

Figure 2B.13 A ribosome, with large subunit and small subunit

Ribosomes

Figure 2B.14 Electron micrograph of ribosomes on the endoplasmic reticulum

Vesicles Golgi body

Figure 2B.16 Electron micrograph of a Golgi body

Figure 2B.15 A Golgi body, with proteins being packaged off in vesicles

lysosome a membranebound sac in animal cells that contains digestive enzymes for breaking down waste materials

vacuole a membranebound sac that stores water and ions

turgor pressure the pressure that pushes the cell membrane against the cell wall in plant cells, due to the flow of water into the vacuole; provides structural support

Lysosomes

Found in animal cells, lysosomes are membrane-bound sacs containing digestive enzymes. They break down foreign matter and materials no longer needed by the cell.

Rough endoplasmic reticulum

Nucleus

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Nuclear envelope

Nuclear pore

Ribosomes

Smooth endoplasmic reticulum

Secretory vesicles

Lysosome

Plasma membrane

Vacuoles

Vacuoles are membrane-bound sacs that store substances such as water and ions.

In plant cells, vacuoles are large and play an important role in maintaining structural support through turgor pressure. Where vacuoles are present in some animal and protist cells, they are smaller and temporary.

Figure 2B.19 Vacuoles (indicated by black lines) in a Paramecium under a light microscope

Vacuole

Figure 2B.18 A large vacuole in a plant cell

Golgi body

Figure 2B.17 The relationship between the nucleus, endoplasmic reticulum, Golgi body and lysosomes

Plant cells versus animal cells

Although plant and animal cells are both eukaryotic and share many common organelles, they also have key structural differences that reflect the specialised functions of the whole organism (Figure 2B.20). Table 2B.1 highlights these differences and explains how each structure supports the way the cell operates.

Animal cell

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Plasma membrane

Rough endoplasmic reticulum

Smooth endoplasmic reticulum

Lysosome

Golgi body

Vesicle

Mitochondrion

Table 2B.1 Comparison of plant and animal cells

Feature / organellePlant cells

Cell wall

Animal cells

Present (cellulose) Absent

Plant cell

Vesicle

Cell wall

Plasma membrane

Rough endoplasmic reticulum

Mitochondrion

Smooth endoplasmic reticulum

Functional significance

Provides rigidity, structural support and protection; prevents bursting in hypotonic environments

Plasma membrane Present (inside cell wall) Present (outer boundary) Controls the movement of substances into and out of the cell

Chloroplasts Present (in photosynthetic tissues) Absent Carry out photosynthesis, converting light energy into glucose

Large central vacuole Very large, often occupies most of the cell Small and temporary, if present Stores water and nutrients, maintains turgor pressure for rigidity and growth

Shape of cell Regular, rectangular due to rigid cell wall

Irregular, rounded or varied Plant structure supports upright growth; animals benefit from flexible shapes for movement

Centrioles Absent in vascular plantsPresent in centrosomesHelp organise spindle fibres during cell division

Lysosomes Rare; vacuole often performs similar roles Common

Break down waste and recycle materials

Carbohydrate storage Starch in plastidsGlycogen in cytoplasmDifferent storage forms reflect how each kingdom manages energy reserves

Chloroplast

Nucleus

Vacuole

Figure 2B.20 Similarities and differences between an animal cell and a plant cell

PRACTICAL 2B.1

Calculating cell size

Aim

To calculate the field of view of a microscope using a mini-grid, measure the actual size of specialised cells, and draw accurate scaled biological diagrams using the magnification formula.

Materials

• Compound light microscope

• Mini-grid slide

• Prepared slides of specialised cells (e.g. onion epidermal cells, cheek cells, amoeba, root hair cells)

• Drawing paper and pencils

• Calculator

• Ruler

Method

Part A: Calibrating the microscope field of view

1. Place the mini-grid on the microscope stage and view it at low power (usually 4× objective lens, which gives 40× magnification)

2. Focus the lens on the mini-grid using the adjusting knobs.

3. Count how many divisions of the mini-grid fit across the diameter of the field of view (FOV). The FOV is the circular visible area that can be observed through the microscope.

4. Calculate the diameter of the FOV. Each division on the mini-grid is typically 0.01 mm or 10 µm.

5. Repeat for the medium (10×) and high power (40×) objectives if desired (100× and 400× magnification respectively).

Part B: Measuring actual cell size

6. View a prepared slide (e.g. onion epidermis) under medium or high power.

7. Estimate how many cells will fit across the diameter of the FOV if placed next to each other.

8. Calculate cell size using the following equation:

Celll size = diameter of FOV number of cells across the FOV

Part C: Constructing scaled diagrams

9. Measure the size of the image (drawn cell) in millimetres, using a ruler.

10. Use the magnification formula:

Actual size = image size magnification or rearrange the formula to find the magnification if needed.

11. Construct biological diagrams to scale, using a scale bar and including correct annotations. questions download word download pdf

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Example calculation

FOV at 40× magnification = 4.5 mm

Cell occupies 1 5 of FOV

Estimated actual size:

= 4.5 mm ÷ 5 = 0.9 mm

If image of cell is drawn at 90 mm:

Magnification = image size actual size

= 90 mm 0.9 mm = 100

Magnification × 100

Results

Give your table an appropriate heading.

Onion epidermis

Cheek cell

Muscle tissue

Measurement conversions

Table 2B.2 Reference table of common prefixes for length

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NOTE

1 metre (m) = 100 centimetres (cm) = 1000 millimetres (mm)

= 1,000,000 micrometres (µm) = 1,000,000,000 nanometres (nm)

To convert between millimetres and micrometres:

millimetres to micrometresmm to

micrometres to millimetresµm to

Examples:

1. Convert 5

2. Convert

×

Discussion

Convert each of the following into micrometres.

1. 3 millimetres

2. 67 centimetres

3. 1500 millimetres

4. 0.24 metres

EXAM PRACTICE 2B

Example question

Explain why muscle cells are likely to contain more mitochondria compared to skin cells. (3 marks)

What is the question asking?

The key verb in this question is explain. To explain, you need to include:

• a logical link between ideas (don’t just list facts)

• a sequence showing process, reason or mechanism

• enough detail that the reader understands why the outcome occurs.

Typical structure

1. Identify the concept material, a cellular membrane, cytoplasm or process.

2. Describe the relevant steps/features.

3. Connect them using “because”, “therefore”, “this leads to”, “as a result”.

4. Conclude the effect or outcome.

Marking criteria

SAMPLEPAGES

• Explains the role of mitochondria in the production of ATP

• Links the number of mitochondria to cell function

• Explains the role of mitochondria OR

• Identifies the role of mitochondria and links it to cell function

• Provides relevant information

Sample response

Identify: Mitochondria use cellular respiration to produce ATP.

Describe: ATP is the energy storage molecule that all cells need for functioning.

Connect: Muscle cells facilitate movement and are likely to need more energy/ATP.

Conclude: Therefore, they would likely have more mitochondria than skin cells.

SECTION 2B REVIEW

Review questions

1. Describe the structural differences between the cell walls of plant cells and fungi, and how these differences relate to their functions.

2. Outline the role of the endoplasmic reticulum (smooth ER and rough ER) in the synthesis and transport of proteins and lipids.

3. Discuss how the specialisation of organelles within eukaryotic cells contributes to the efficiency of cellular processes in these cells. Use at least two examples in your response.

4. Describe the relationship between the nucleus, ribosomes and Golgi body in the production and export of proteins from a cell.

5. Construct a Venn diagram to compare and contrast organelles commonly found in plant and animal cells.

2C Microscopes

SYLLABUS

At the end of this section, I will be able to: 2C.1 Assess the impact of technological developments in microscopy on scientific understanding of cell structure and function

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How light microscopes work

Light microscopes use visible light to illuminate a specimen, and have glass lenses to bend (refract) the light, producing a magnified image.

1. Light passes from a lamp or a mirror through a condenser lens, which focuses the light onto the specimen.

2. The light travels through the specimen and enters the objective lens, which creates a magnified, inverted image.

3. This image is further magnified by the eyepiece (ocular lens), so the viewer sees an enlarged image.

4. Stains or dyes are often applied to specimens to improve contrast, because many cells are transparent.

Figure 2C.1 A light microscope

Figure 2C.2 Volvox, a green alga that forms spherical colonies, as seen here under a light microscope

How electron microscopes work

Electron microscopes don’t use light, like traditional microscopes; instead, they fire a beam of electrons at a specimen to create an image. Because electrons have a much shorter wavelength than visible light, they can reveal details at the nanometre scale, which is much higher resolution than light microscopes. Magnetic coils (acting like lenses) bend and focus the electron beam, which interacts with the specimen to produce either a highly detailed 2D image (in a transmission electron microscope; TEM) or a 3D surface image (in a scanning electron microscope; SEM).

Steps for electron microscopy:

1. An electron gun emits electrons, which are focused into a beam using electromagnetic coils.

2. The beam interacts with the specimen.

• TEM: electrons pass through the ultra-thin specimen to produce a detailed 2D image.

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• SEM: electrons bounce off the surface of the specimen to create a detailed 3D image.

3. Detectors capture the electrons and convert them into a digital image on a screen.

Figure 2C.3 An electron microscope

Figure 2C.4 Blood cells as seen under a scanning electron microscope

Table 2C.1 Comparison of light microscopes and electron microscopes

Feature Light microscope

MagnificationUp to ~1500×

Resolution ~200 nm (lower resolution; limited by wavelength of visible light)

Specimen preparation

Simple preparation: specimens can be living or dead, may be stained for contrast

Image producedColour image (natural or stained); shows overall structure

Cost and sizeRelatively cheap and portable (~$1000–$10,000); fits on a laboratory bench

ApplicationsViewing cells, tissues and small organisms (e.g. bacteria, plant cells)

Electron microscope

Up to ~1,000,000×

~0.1 nm (much higher resolution; uses electron beams with shorter wavelengths)

Complex preparation: specimens must be dead, fixed, dehydrated and placed in a vacuum

Black and white image; can show surface (SEM) or internal ultrastructure (TEM)

Very expensive (~$1 M+); large and requires special laboratory conditions (vacuum, anti-vibration)

Viewing organelles, viruses, macromolecules and detailed ultrastructure

Timeline of microscopes and cell knowledge

Table 2C.2 outlines the main developments in the timeline of microscopy, and our knowledge of cells.

Table 2C.2 Main developments in the evolution of microscopes

Date/era and main scientist

Technological development

1665 – Robert HookeFirst use of a compound light microscope to describe “cells” in cork

1674 – Antonie van Leeuwenhoek

Improved lenses 200× allowing clearer images

1830s – Introduction to cell theory (Matthias Schleiden and Theodor Schwann)

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Impact on our understanding of cells

Hooke used the term “cell” because he thought the structures he saw resembled the cells that monks lived in.

Leeuwenhoek was the first to observe living cells, such as protozoa, sperm and bacteria, which he called “animalcules”. This led to recognition that life is cellular.

Advances in lenses Schleiden and Schwann proposed that all organisms are made of cells, and that the cell is the basic unit of life, forming the basis of cell theory.

1850s – Rudolf VirchowRefinements in stainingWith better microscopes and improved dyes to make cell structures more visible, Virchow showed that new cells are formed only by the division of existing cells. This discovery completed the classical cell theory, which now included three main ideas.

• All living things are made up of cells.

• The cell is the basic unit of life.

• All cells come from pre-existing cells.

1931 – Ernst Ruska and Max Knoll

Electron microscope (TEM) invented

This invention was a huge leap forward because the TEM could magnify up to 1000 times more than light microscopes. For the first time, scientists could see fine details inside cells that had been invisible before. Using the TEM, researchers discovered and studied organelles such as mitochondria, endoplasmic reticulum (ER), Golgi bodies and ribosomes.

Date/era and main scientist Technological development Impact on our understanding of cells

1930s–1940s Scanning electron microscope (SEM) developed

This new type of electron microscope used a beam of electrons to scan the surface of a specimen. Instead of thin internal slices (as in TEM), the SEM produced detailed 3D images of cell surfaces. This gave scientists a much clearer view of the shapes, textures and external features of cells, including how they interact with their environment and with each other. SEM images helped researchers understand cell structure.

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Video: Exam practice 2C

1950s–1960s Advances in cell fractionation and electron microscopy

1970s–1980s Fluorescence microscopy using antibodies tagged with fluorescent markers

1990s–2000s Confocal microscopy and digital imaging

2000s–present Super-resolution microscopy (e.g. STED, PALM, STORM)

Scientists developed methods to break open cells and separate their parts (cell fractionation) and then study those organelles under an electron microscope. This allowed them to work out the jobs of different organelles. For example, mitochondria were shown to be the sites of cellular respiration and energy (ATP) production.

This let scientists make certain proteins or parts of the cell light up, so they could see exactly where things were inside the cell and connect structures to what they do.

This enabled 3D reconstruction of cells, which led to better understanding of dynamic processes in living cells.

These new techniques let scientists see things that are smaller than the normal limits of light microscopes (down to about 20 nm). They revealed the tiny structures inside cells, such as parts of the cytoskeleton and protein groups, and allowed scientists to watch some processes happen in real time.

EXAM PRACTICE 2C

Example question

Discuss the strengths and limitations of using a light microscope to observe plant cells. (3 marks)

What is the question asking?

The key verb in the question is discuss, which means to present different sides, viewpoints or factors, and show how they relate. It does not mean “write everything you know”. It means consider the issue from multiple angles before reaching a reasoned conclusion. You need to include:

• more than one perspective (e.g. advantages and disadvantages, causes and effects, evidence for and against)

• logical linking between ideas, not a list.

Typical structure

1. Introduce the topic.

(“There are several factors that contribute to…”)

2. Present multiple sides:

• first viewpoint – with explanation

• alternative viewpoint – with explanation

• additional factors, if relevant.

3. Link ideas.

(Use “however”, “on the other hand”, “additionally”, “this means that…”.)

Marking criteria

Criteria

• Provides strengths and limitations of light microscopes AND

• Links points to the observation of plant cells

• Provides a strength and a limitation of light microscopes AND

• Provides a link to the observation of plant cells OR

• Provides strengths of using light microscopes to observe plant cells

• Provides relevant information

Sample response

Marks

3

2

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1

Introduction: Light microscopes are commonly used in science laboratories and can magnify objects up to 400×.

First viewpoint (positive): 400× magnification is powerful enough to see individual plant cells clearly and identify the cell wall, nucleus and vacuoles. It also allows cell size to be estimated.

Alternative viewpoint (negative): However, smaller organelles such as mitochondria or chloroplasts can be difficult to distinguish using a light microscope, and can only be clearly seen using an electron microscope with a higher magnification/resolution.

SECTION 2C REVIEW

Quiz

Review questions

Review questions

Reporting (student and teacher)

1. Identify which type of microscope requires specimens to be dead and placed in a vacuum-sealed chamber before viewing.

2. Summarise the advantages of using a light microscope over an electron microscope.

3. Identify the development in microscopy that occurred in the 1970s and 1980s, and explain how this contributed to our understanding of cells.

4. Explain why stains are applied to specimens in microscope slides.

5. Propose why the development of super-resolution microscopy has been important for the future of the scientific field.

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Success criteria checklist

I am now able to: Linked

2A.1 Use a variety of sources to compare the cellular structures of eukaryotic and prokaryotic cells 1, 2, 6

2A.2 Conduct a practical investigation to prepare a wet mount slide and identify the cytoplasm, cell wall and nucleus under a light microscope

2A.3 Describe the structure and function of the capsule, cell wall, cell membrane, cytoplasm, nucleoid, plasmid, ribosomes, flagella and pili in prokaryotic cells

Practical 2A.1

7, 8, 9

2B.1 Contrast the cell structure and organelles of plant and animal cells based on the function of the cell 3, 4

2B.2 Describe the structure and function of the cell wall, cell membrane, cytoplasm, nucleus, mitochondria, chloroplast, endoplasmic reticulum, Golgi body, ribosomes, lysosomes and vacuole in eukaryotic cells

2B.3 Conduct a practical investigation to calculate the size of a variety of specialised cells under the microscope using a mini-grid and the equation

Cell size = diameter of field of view number of cells across the field of view

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3, 4, 10, 11, 12, 13

Practical 2B.1

2C.1 Assess the impact of technological developments in microscopy on scientific understanding of cell structure and function 5, 14, 15

Multiple-choice questions

1. Which feature is found in all cells?

A. mitochondria

B. nucleus

C. plasma membrane

D. chloroplast

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2. What distinguishes prokaryotic DNA from eukaryotic DNA?

A. Prokaryotic DNA is linear.

B. Eukaryotic DNA is circular.

C. Prokaryotic DNA is found in a nucleoid.

D. Eukaryotic DNA is found in plasmids.

3. Which organelle is responsible for packaging and modifying proteins?

A. rough ER

B. Golgi apparatus

C. ribosomes

D. lysosomes

4. What is the main function of chloroplasts?

A. cellular respiration

B. protein synthesis

C. photosynthesis

D. lipid transport

5. Which microscope allows cell ultrastructure to be viewed at the highest resolution?

A. light microscope

B. compound microscope

C. scanning electron microscope

D. transmission electron microscope

Exam-style questions

6. Identify one feature that distinguishes prokaryotic cells from eukaryotic cells. (1 mark)

7. Describe the function of ribosomes in both prokaryotes and eukaryotes. (2 marks)

8. Outline why cell membranes are described as selectively permeable. (2 marks)

9. Explain how the presence of a capsule can help bacteria survive in the human body. (3 marks)

10. Distinguish between the storage products of plant and animal cells. (3 marks)

11. Compare the roles of the Golgi body and the endoplasmic reticulum in a cell. (3 marks)

12. Explain why chloroplasts and mitochondria are often described as energy organelles. (4 marks)

13. Discuss the advantages of having organelles with membranes in eukaryotic cells. (4 marks)

14. Evaluate how improvements in staining techniques helped scientists identify different cell structures. (4 marks)

15. Propose how being able to see living cells in ever finer detail in the future might change our understanding of how cells function. (5 marks)

Cell division 5 CHAPTER

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SYLLABUS

CONTENT DOT POINTS: CELL DIVISION

At the end of this chapter, I will be able to:

5A.1 Use the deoxyribonucleic acid (DNA) double helix model to demonstrate the structure of DNA, including nucleotide composition, complementary base pairing and hydrogen bonding

5A.2 Conduct a practical investigation to model the process of DNA replication, demonstrating the role of complementary bases, the replication fork with leading and lagging strands, and the enzymes of helicase, primase, DNA polymerases and ligase

5A.3 Assess the use of models to demonstrate DNA replication

5A.4 Construct diagrams to compare the forms in which DNA exists in prokaryotic and eukaryotic cells

5B.1 Compare the structures and roles of somatic and gametic cells

5B.2 Account for the phases of gap 1 (G1), synthesis, gap 2 (G2) and mitosis in the cell cycle

5B.3 Conduct a practical investigation to model the named phases of mitosis and cytokinesis

5C.1 Describe the processes of crossing over, independent assortment and random segregation during meiosis

5C.2 Conduct a practical investigation to model the named phases of meiosis and cytokinesis

5C.3 Evaluate the importance of DNA replication, mitosis, meiosis and cytokinesis in cell division

SECTION

5A The structure of DNA

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5B The cell cycle and mitosis

Meiosis

GLOSSARY TERMS

anaphase

C (cytokinesis) phase centromere centrosome chiasma chromatid complementary base pairing crossing over cytokinesis

deoxyribonucleic acid (DNA)

diploid (2n) double chromosome

G0 phase

G1 (first gap) phase

G2 (second gap) phase gamete haploid (n)

homologous chromosomes independent assortment interphase

M (mitosis) phase metaphase monomer nucleotide Okazaki fragments polymer primer prophase purine pyrimidine

S (synthesis) phase single chromosome somatic cell telophase

5C

Concept map

5A The structure of DNA

Nucleotides are the building blocks of DNA

Purines Pyrimidines

Adenine A GC T Guanine

CytosineThymine

Deoxyribose sugar Nitrogenous base

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5B The cell cycle and mitosis

The cell cycle regulates growth and cell division

DNA must be replicated for cells to reproduce

5C Meiosis

Meiosis produces gametes for sexual reproduction

Prophase I

Metaphase I

Anaphase I

Synapsis and crossing over

Phosphate group line up at pl

Mitosis produces

Prophase

Metaphase

Anaphase

Telophase

Cytokinesis

Telophase I

Cytokinesis

Prophase II

Metaphase II

Anaphase II

Telophase II

Cytokinesis

Homologous chromosomes metaphase plate

at metaphase plate

Four

cells

5A The structure of DNA

SYLLABUS

At the end of this section, I will be able to:

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5A.1 Use the deoxyribonucleic acid (DNA) double helix model to demonstrate the structure of DNA, including nucleotide composition, complementary base pairing and hydrogen bonding

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5A.2 Conduct a practical investigation to model the process of DNA replication, demonstrating the role of complementary bases, the replication fork with leading and lagging strands, and the enzymes of helicase, primase, DNA polymerases and ligase

5A.3 Assess the use of models to demonstrate DNA replication

Instructions for life

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Worksheet 5A.1

DNA structure and function

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Worksheet 5A.2

Key word revision

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5A.4 Construct diagrams to compare the forms in which DNA exists in prokaryotic and eukaryotic cells

DNA (deoxyribonucleic acid) is a universal molecule that links every organism on Earth, from the simplest bacteria to humans. Within its helical structure lies a shared language of life. DNA is copied, transcribed and repaired billions of times each day inside every individual, yet even the smallest change in this code can have profound consequences, driving evolution, causing disease or sparking entirely new traits.

Our growing understanding of DNA has transformed medicine, agriculture and forensics. It has opened new opportunities once believed to be impossible, from gene therapies to treating chronic illnesses such as cystic fibrosis, to personalised medicine, synthetic biology and even the potential to edit entire species. As we continue to unlock its secrets, DNA challenges us with both extraordinary opportunities and profound responsibilities for the future of life itself. This chapter explores the fundamentals of DNA structure and function.

DNA structure

DNA is a polymer , meaning it is built from many repeating subunits called monomers . In DNA, the monomers are nucleotides that differ only in which nitrogenous base they contain. There are four bases: adenine (A), cytosine (C), guanine (G) and thymine (T).

DNA forms a double-stranded molecule in which each base always pairs with its complementary partner: A with T, and C with G. A simple way to remember this is:

“Apples in Trees, Cars in Garages”.

Video: Structure of DNA

deoxyribonucleic acid ( DNA ) a type of nucleic acid that carries the organism’s genetic information polymer a molecule made up of a large number of smaller, repeating units monomer a molecule that forms bonds with other identical molecules as the repeating units that make up a polymer nucleotide the monomer (building block) of nucleic acids that are joined together to form DNA or RNA (polymers); consists of a phosphate group, a sugar and a nitrogenous base

Each strand of a DNA molecule is made up of many repeating nucleotides. Each nucleotide has three main components:

• a phosphate group

• a deoxyribose sugar

• one of four nitrogenous bases – adenine (A), cytosine (C), guanine (G) or thymine (T).

Phosphate group

purine a nucleotide with a two-ring structure (adenine and guanine)

pyrimidine a nucleotide with a single-ring structure (cytosine and thymine) complementary base pairing the pairing of nitrogenous bases in DNA; adenine and thymine always pair, and cytosine and guanine always pair

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Nitrogenous base –variable (A, T, C or G )

Deoxyribose sugar

Nitrogenous bases can be classified as purines or pyrimidines, according to their chemical structure. Adenine and guanine have a two-ring structure, which makes them purines , while thymine and cytosine have a single-ring structure, making them pyrimidines (Figure 5A.3). Complementary base pairing in DNA means that a purine (larger in structure) will always pair with a pyrimidine (smaller in structure), which helps to strengthen and stabilise the DNA helix. Therefore, adenine and thymine always pair together, and guanine and cytosine always pair together.

Figure 5A.2 The structure of a typical nucleotide; the monomer of a DNA molecule

Figure 5A.1 The double helix shape of DNA. A DNA molecule consists of two antiparallel strands of nucleic acids that wrap around each other, giving rise to its “twisted ladder” form.

base

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Phosphate group

Figure 5A.3 The four nucleotides in DNA, showing the purines (double rings) and pyrimidines (single rings) that form the nitrogenous base component and give each nucleotide its identity

The sides of the DNA “ladder” (the strands) are formed by the alternating phosphate and deoxyribose sugar groups of the nucleotides, giving rise to the sugar–phosphate backbone (Figure 5A.4). The nitrogenous bases form the “rungs” of the ladder by orientating themselves towards the centre of the molecule. Hydrogen bonds form between complementary nitrogenous bases of the two opposing strands, and these bonds hold the molecule in its double helix form.

Figure 5A.4 (a.) How the nitrogenous bases A, T, G and C link the two sugar–phosphate backbones into a ladder structure. Note the difference in the number of hydrogen bonds between complementary bases, which explains why A and T only and always bond together, and G and C only and always bond together. (b.) A simplified version of the ladder structure of DNA, showing how it is twisted into a double helix.

primer a single-stranded piece of DNA (or RNA) complementary to a specific sequence of nucleotides

Okazaki fragments short segments of DNA that are added to the lagging strand during DNA replication

Steps in DNA replication

Before a cell can undergo mitosis, it must first copy its DNA. It does this through a process called DNA replication.

The double helix is unwound by the enzyme helicase, which separates the complementary strands and creates a replication fork (Figure 5A.5). Each exposed strand then acts as a template for building a new complementary strand.

Primase lays down a short RNA primer to mark the starting point. DNA polymerase attaches to the primer and moves along the template strand, adding free nucleotides one by one in the 5´ to 3´ direction.

On the leading strand, replication proceeds smoothly and continuously, following the movement of the replication fork. On the lagging strand, however, replication occurs in short sections because the template runs in the opposite direction. Here, primase repeatedly adds primers, and DNA polymerase builds short fragments of DNA, called Okazaki fragments , because DNA polymerase can only add bases in the 5´ to 3´ direction, moving away from the replication fork.

Finally, the RNA primers are replaced with DNA nucleotides, and the enzyme DNA ligase seals the sugar–phosphate backbone, joining the fragments into a continuous strand. This ensures that both new DNA molecules are complete and identical to the original.

Because each new strand consists of an original strand and a new strand, the process is referred to as semi-conservative replication.

Figure 5A.5 The DNA replication process, showing the action of DNA polymerase, ligase, primase and helicase

SKILLS 5A.1

Assessing models

In Chapter 1 you learned about the use of models in biology and what makes a good model. When assessing models, it is important to already have a detailed understanding of the process being modelled. In an exam, any questions related to assessing models are an opportunity to show the marker your level of understanding, by using subject-specific terminology.

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Table 5A.1 shows two models of DNA replication and a sample assessment.

Table 5A.1 Assessing the effectiveness of two DNA replication models

Model of DNA replication

Assessment of the model DNA replication fork

Positives

• This model clearly shows the leading and lagging strand of DNA with the 3′ and 5′ ends labelled.

• It shows the direction in which the new strand is being built.

Negatives

• This model does not contain any of the enzymes, such as helicase, DNA polymerase or ligase.

• This model does not show the structure of DNA with complementary nitrogenous bases.

Judgement

• Overall, this model lacks the level of detail needed to accurately represent DNA replication.

Positives

• This model clearly shows the leading and lagging strand of DNA with the 3′ and 5′ ends labelled.

• It shows the direction in which the new strand is being built.

• It indicates the RNA primer with a different-coloured backbone, effectively differentiating it from DNA.

• It includes the enzymes DNA polymerase, helicase and primase.

Negatives

• The model lacks ligase.

• The model shows all the original strand’s nucleotides as the same colour, which may be misleading because they should represent all four bases.

Judgement

• Although the model lacks ligase and differentiation between the four nitrogenous bases, it shows the general process of DNA replication at a sufficient level to assist in understanding.

PRACTICAL 5A.1

Modelling DNA replication

Aim

To create a poster-based model of DNA replication for a Year 11 Biology audience that explains the sequence of events and the role of key enzymes involved in DNA replication.

Activity overview

Work in small groups to design and construct a poster that models DNA replication. The poster must visually represent the step-by-step process of replication, with enzymes and strand directions clearly labelled.

Materials

• Poster paper or butcher’s paper

• Coloured paper or card

• Scissors

• Glue or tape

• Coloured pens or markers

Method

• Ruler

• Sticky notes or labels

• String or wool (to represent strands)

• Optional: printed base letters (A, T, C, G)

1. Begin with a short section showing the DNA double helix before replication.

2. Show helicase unwinding the DNA and forming a replication fork.

3. Represent complementary base pairing on each template strand.

4. Clearly show the leading strand being built continuously in the 5′ to 3′ direction.

5. Show the lagging strand forming Okazaki fragments.

6. Include primase adding RNA primers.

7. Show DNA polymerase extending new DNA strands.

8. Include ligase joining Okazaki fragments.

9. Indicate that replication is semi-conservative.

10. Ensure all enzymes, strands and directions are clearly labelled.

Assessment rubric

Scientific accuracyAll steps and enzymes correctly represented and labelled

Sequence and clarityClear, logical sequence from start to finish

Use of biological terminology

Communication and explanation

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Discussion

Correct and consistent use of scientific terms

Student clearly explains the model using correct biology concepts

Most steps and enzymes correct, with minor errors

Mostly logical sequence, with minor gaps

Mostly correct terminology used

Explanation is mostly clear

Some correct features but major inaccuracies

Sequence is unclear or partially incorrect

Limited use of correct terms

Explanation lacks clarity or detail

1. Why are models used in science to explain processes such as DNA replication?

2. What are the limitations of a poster model of DNA replication?

3. How could you assess the validity of the DNA replication models produced in class?

4. Provide one example of warm feedback you could give another group about their model.

Model shows little understanding of DNA replication

Sequence is missing or incorrect

Incorrect or no scientific terminology

Unable to explain the model

Organisation of DNA in prokaryotic and eukaryotic cells

While the structure of DNA and the process of DNA replication are conserved across living organisms, the way DNA is organised within cells differs between prokaryotes and eukaryotes. Table 5A.2 and Figure 5A.6 compare key features of prokaryotic and eukaryotic DNA, including their location, structure and packaging.

Table 5A.2 Comparison of prokaryotic and eukaryotic DNA

Feature

LocationNot bound by a membrane; present in the centre of the cell; called “nucleoid”

Main formSingle circular chromosome; may also contain plasmids, which are non-chromosomal DNA

PackagingNo histones

SizeSmall, usually around 4–5 Mbp (million base pairs)

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Prokaryotic cellEukaryotic cell DNA in nucleoid DNA in nucleus Ribosomes

RNA

Cytoplasm Cell membrane

Figure 5A.6 Comparison of DNA in a prokaryotic cell and a eukaryotic cell

EXAM PRACTICE 5A

Example question

Eukaryote DNA

Bound by a membrane; contained in the nucleus

Multiple linear chromosomes

Tightly wound around histone proteins (Figure 5A.7)

Large, around 3.2 Gbp (billion base pairs) in humans; up to 150 Gbp in some plant species

Chromatin fibre

Chromosome

Histones

“Beads on a string” DNA wound on nucleosomes

Double helix

Figure 5A.7 The histone packaging of DNA in a eukaryotic chromosome

Video: Exam practice 5A

Outline the role of enzymes in DNA replication. (4 marks)

What is the question asking?

The key verb in this question is outline, which means to give the main features or general principles of a topic. This is broader than “identify” but far less detailed than “explain”. You should include:

• a brief summary of the key ideas

• only the essential points – no deep detail or cause–effect is needed

• clear, concise statements.

Typical structure

1. Name the idea, process or feature.

2. Give a short description.

3. Numbered steps or sentence dot points are suitable.

Marking criteria

Criteria Marks

Names and describes the roles of at least 4 enzymes in the process of DNA replication4

Names and describes the roles of at least 3 enzymes in the process of DNA replication3

Names and describes the roles of at least 2 enzymes in the process of DNA replication2

Names and describes the roles of an enzyme in the process of DNA replication 1

Sample response

Many enzymes are involved in the process of DNA replication.

1. Helicase begins the process by unwinding the DNA and creating the replication fork.

2. Primase lays an RNA primer to start the replication process.

3. DNA polymerase attaches to the RNA primer and begins to build the new strand in a 5 prime to 3 prime direction.

4. Ligase seals the bonds between nucleotides at the end of the process.

SECTION 5A REVIEW

Go online to access the Interactive Textbook

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Review questions

1. Which of the following correctly lists the components of a DNA nucleotide?

A. ribose sugar, phosphate group, nitrogenous base

B. deoxyribose sugar, phosphate group, nitrogenous base

C. glucose molecule, phosphate group, nitrogenous base

D. deoxyribose sugar, amino acid, phosphate group

2. Explain why, in DNA, adenine can only pair with thymine and guanine only with cytosine.

3. Explain why DNA is referred to as a polymer.

4. Identify and describe the function of the five key enzymes in DNA replication.

5. Assess the model of DNA replication shown here. Quiz Review questions

Reporting (student and teacher)

5B The cell cycle and mitosis

SYLLABUS

At the end of this section, I will be able to:

5B.1 Compare the structures and roles of somatic and gametic cells

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Worksheet 5B.1

Mitosis

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5B.2 Account for the phases of gap 1 (G1), synthesis, gap 2 (G2) and mitosis in the cell cycle

5B.3 Conduct a practical investigation to model the named phases of mitosis and cytokinesis

Somatic cells versus gametes

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Multicellular organisms contain two main types of cells: somatic cells , which make up over 99.9% of the cells in the body; and gametes , also known as germline or sex cells.

Somatic cells make up the tissues and organs of an organism, such as muscle, nerve and skin cells. They are diploid (2 n ) , meaning they contain two complete sets of chromosomes, one from each parent. In humans, this is 23 pairs and therefore 46 chromosomes in total. Somatic cells divide by mitosis, producing genetically identical daughter cells. This process enables growth, repair and the maintenance of the organism throughout its life.

Figure 5B.1 Types of somatic and gamete cells in a human

Gametic cells, or gametes, are the sex cells involved in reproduction: sperm in males and ova in females. They are haploid ( n ) , meaning they contain only one set of chromosomes. Gametes are produced through meiosis, which introduces genetic variation through crossing over and independent assortment. During fertilisation, a sperm and an ovum fuse, which restores the diploid chromosome number, forming a genetically unique zygote that is diploid.

Worksheet 5B.2

Key word revision

somatic cell a diploid body cell that divides by mitosis for growth, repair and maintenance

gamete a haploid sex cell (sperm or ovum) produced by meiosis for sexual reproduction

diploid ( 2 n ) containing two complete sets of chromosomes, one from each parent

haploid ( n ) containing a single set of chromosomes (in gametes)

Muscle cell

Table 5B.1 summarises the differences between somatic and gametic cells.

Table 5B.1 Contrasting somatic and gametic cells

Chromosome numberDiploid (2n) – two sets of chromosomes

Division processMitosis

Genetic compositionGenetically identical to the parent cell

Function Growth, repair and maintenance of the organism

Haploid (n) – one set of chromosomes

Meiosis

Genetically unique due to crossing over and independent assortment

Sexual reproduction and creation of genetic diversity

Examples Muscle, nerve and skin cellsSperm and ova (egg cells)

Cell division in eukaryotes

The presence of membrane-bound organelles in eukaryotic cells makes the division of these cells more complex than that of prokaryotic cells.

The cell cycle

The cell cycle is the process that most eukaryotic cells undergo in order to multiply. Recall from earlier in this section that eukaryotic cells divide for the purpose of growth and repair. The cell cycle consists of distinct stages that cells progress through in an orderly manner in preparation for division. The parent cell gives rise to two genetically identical daughter cells, and these daughter cells immediately commence their own pathway through the stages – hence the term “cycle”. On average, a typical human cell takes approximately 24 hours to progress through the cycle, although this can vary depending on the type of cell. The stages of the cell cycle are shown in Figure 5B.2, and outlined through the rest of this section.

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Figure 5B.2 Phases of the eukaryotic cell cycle. “M phase” means “mitotic phase”, “C phase” means “cytokinetic phase” and “S phase” means “synthetic phase”. G1 and G2 are the first and second gap phases, while G0 is a resting phase.

Interphase

Interphase is the portion of the cell cycle in which a typical cell spends most of its time. It consists of the G1, S, G2 and, in some cells, G0 phases of the cell cycle. During interphase, the cell undergoes several important changes in preparation for division: it grows, replicates its DNA to produce two sets of chromosomes, and multiplies organelles so it is ready to move out of interphase and into the division portion of the cycle, which consists of M phase and C phase. Note that, in interphase, chromosomes are not visible and the nucleus appears as a dark mass of chromatin. The key features of each interphase stage are described in detail below.

G1 phase

In the G1 phase (or first gap phase ), the cell grows larger and almost doubles in size. This growth is important because it enables the conservation of cell size once division has occurred. It is also the point in the cycle where organelles are copied so that daughter cells will be equipped with the necessary “machinery” to sustain their own survival. This is the longest phase of the cell cycle, and therefore most cells are seen in this stage when viewed under a microscope.

G0 phase

Not all cells progress through the whole cell cycle. Some cells exit the cycle in G1 and enter a resting state, called the G0 phase . For some cells, this resting state is not permanent and they eventually re-enter the cycle and divide normally. For other cells, such as neurons, this state of rest is permanent, which explains why damage to the nervous system is difficult to treat.

S phase

interphase the period of the cell cycle that consists of the G1, S and G2 phases

G1 ( first gap ) phase the first period of cell growth in the cell cycle

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Following G1 is the S phase (or synthesis phase ). It is during this phase that the DNA in the nucleus of a cell is replicated, creating two identical copies of DNA. Even though chromosomes are not present in this stage of the cycle, it is easier to explain by imagining that they are. During DNA replication, single chromosomes become double chromosomes consisting of two sister chromatids joined by a centromere (Figure 5B.4). The two sister chromatids contain identical genetic information that is passed to the two daughter cells when cell division occurs at the end of M phase.

G0 phase the resting phase of the cell cycle that some cells may enter

S ( synthesis ) phase the DNA replication phase of the cell cycle

single chromosome a highly condensed, single molecule of DNA

double chromosome

a highly condensed, replicated molecule of DNA consisting of two identical chromatids joined by a centromere

chromatid one of two strands of a double chromosome formed when a single chromosome is replicated prior to mitosis or meiosis; when two chromatids are joined at a centromere, they are called sister chromatids and are identical

centromere the structure in a chromosome where the two chromatids are held together; also the point of attachment of the kinetochore, which the spindle microtubules attach to during cell division

Figure 5B.3 Whitefish embryo cell with a nucleus in the centre, filled with chromatin. In interphase, chromosomes are not visible.

In a typical human cell, before the replication of DNA in S phase, there are 46 single chromosomes in the nucleus. At the end of S phase, the replication of DNA means that the nucleus now consists of 46 double chromosomes.

Double chromosome

Single chromosome

Nucleus

Before DNA replication (in S phase)

Sister chromatids (genetically identical)

After DNA replication (in S phase)

Parent cell

After cell division (M phase)

Figure 5B.4 The replication of DNA in S phase results in genetically identical daughter cells.

G2 phase

G2 ( second gap ) phase the second period of cell growth in the cell cycle

M ( mitosis ) phase the portion of the cell cycle that includes mitosis homologous chromosomes chromosomes that have matching structural features (size, banding pattern, centromere location) and gene loci, one from each parent

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Identical daughter cells

Video: Cell division – mitosis

The G2 phase (or second gap phase ) is the final stage of interphase. In the G2 phase, the cell once again enters a period of growth, as well as increasing its energy store in preparation for division. Metabolic activity also increases as proteins needed for division are synthesised.

M phase

Following the G2 portion of interphase, the cell progresses to M (mitosis) phase . Mitosis is the stage of the cell cycle in which in the nucleus of the parent cell splits into two. It is responsible for the growth and development of an organism as well as the repair or replacement of damaged and worn-out cells. Prior to division, the parent cell contains a diploid number (2n) of chromosomes. This means the cell contains two sets of chromosomes, one set from each parent, and the chromosomes in the pair are called homologous chromosomes (Figure 5B.5). This number is conserved through the division process, with each of the two daughter cells also containing a diploid number of chromosomes.

Chromosome Centromere

Chromatid

Chromatid

Figure 5B.5 Homologous chromosomes

Mitosis consists of four subphases (Figure 5B.6), each with its own unique characteristics. It can be easy to confuse the order of the subphases, so the acronym PMAT is used:

• P – prophase

• M – metaphase

• A – anaphase

• T – telophase.

cell growth G2 cell growth Anaphase Telophase ProphaseMetaphase

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Figure 5B.6 The mitosis component of M phase consists of four subphases.

Table 5B.2 outlines the key characteristics of each subphase of mitosis.

Table 5B.2 The stage before mitosis followed by the subphases of mitosis

Stage/subphase of mitosis

Before mitosis

Interphase (G1, S and G2)

Key characteristics Diagram

Over a 24-hour cell cycle:

• G1 = 11 hours

• S = 8 hours

• G2 = 4 hours

Mitosis ( 1 hour )

Prophase

Early prophase:

• Chromatin condenses into individual chromosomes, which now appear as discrete shapes and are visible under a microscope.

• In the cytoplasm, centrosomes (duplicated in S phase) begin moving to opposite poles (ends) of the cell.

Late prophase:

• Nuclear membrane of the cell has completely broken down.

• Centrosomes are now at opposite ends of the cell.

• Spindle microtubules produced by the centrosomes enter the nuclear area and make contact with the chromosomes.

prophase the first mitotic phase; involves the breakdown of the nuclear membrane and the appearance of distinct chromosomes

DNA (chromatin

Nuclear membrane breaking down

Centrosomes

Spindle microtubules Chromosomes

Stage/subphase of mitosis

Metaphase

M = middle (chromosomes are visible when viewed under a microscope)

Key characteristics Diagram

• Chromosomes are forced into the centre of the cell by the attachment of spindle microtubules to each chromosome’s centromere.

• Chromosomes line up along the metaphase plate in the middle of the cell.

• Chromosomes appear stationary but they are being tugged towards opposite poles of the cell by the microtubules.

Microscope view

Anaphase

A = apart (chromosomes move away from each other)

Telophase

T = two (there are two nuclei in the cell)

• The centromere holding the sister chromatids of each double chromosome is split apart by the opposing microtubule forces.

• The two sister chromatids (each now a single chromosome) begin moving to opposite poles of the cell, centromere first.

• Microtubules from each centrosome retract and get smaller (like a fishing line being reeled in), resulting in chromosomes being pulled further apart.

• The now single chromosomes arrive at opposite poles of the cell.

• The chromosomes revert to chromatin.

• The spindle microtubules disassemble.

• Nuclear membranes re-form around the two groups of chromosomes on opposite sides of the cell.

metaphase the second mitotic phase; involves the lining up of chromosomes along the middle (equator) of the cell

anaphase a mitotic phase in which double chromosomes separate and the sister chromatids are pulled apart to opposite sides of the cell

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centrosome an organelle from which spindle microtubules develop during cell division; contains the centrioles

telophase the final mitotic phase, in which two nuclei are formed and the cell prepares to divide

Nuclear membrane re-forming

Chromatids (now referred to as chromosomes)

Figure 5B.7 Mitosis in a plant cell

C phase

The final stage of the cell cycle is C (cytokinesis) phase , which occurs after telophase in mitosis. During cytokinesis , the cytoplasm splits. Cytokinesis is important because it restores the original size of the cell, maintaining the allimportant SA:V ratio. It also divides organelles between the two daughter cells, ensuring that these cells will be able to survive once they are separated. At the end of cytokinesis, the parent cell will have completed its passage through the cell cycle, which is marked by the presence of two genetically identical daughter cells.

The cell cycle: summary

A summary of the cell cycle is shown in Figure 5B.8.

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C ( cytokinesis ) phase the portion of the cell cycle that includes cytokinesis cytokinesis the final stage of the cell cycle, in which the cytoplasm splits, giving rise to two genetically identical daughter cells

Interphase

Mitosis

Prophase

Chromosomes condense and nuclear membrane disappears

2n = 46

Metaphase

Chromosomes line up along the middle of the cell

Anaphase

Double chromosome separates and sister chromatids are pulled apart to opposite poles of the cell

Telophase

Nuclear membrane reforms and cell prepares to divide (two nuclei )

Cytokinesis

Parent cell splits into two genetically identical daughter cells

Interphase

Each daughter cell restarts cell cycle

2n = 46

2n = 46

Figure 5B.8 Stages of the cell cycle in an animal cell

PRACTICAL 5B.1

Modelling mitosis using a physical model

Aim

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To create a physical model of mitosis that explains to a Year 11 Biology student the sequence of events and key structures involved in cell division.

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Curriculum links

• This activity aligns with syllabus requirements to model the named phases of mitosis and cytokinesis and to assess the use of models in representing biological processes.

Activity overview

• Students work in small groups to create a physical or sequential model of mitosis, using modelling clay or a flip book. The model must clearly represent prophase, metaphase, anaphase, telophase and cytokinesis, showing chromosome behaviour and spindle involvement. Students use the model to explain mitosis to peers.

Suggested time

One lesson for construction and one lesson for presentation and discussion.

Materials

Option A: Modelling clay model

• Modelling clay or playdough (multiple colours)

• Cardboard base or paper plates

• String or wool (to represent spindle fibres)

• Toothpicks or skewers (to represent spindle poles or centromeres)

• Sticky labels or paper

• Markers

Option B: Flip book model

• Small notebook or stack of index cards

• Pencils or pens

• Coloured pencils

• Ruler

Instructions for students

1. Review the stages of mitosis: prophase, metaphase, anaphase, telophase and cytokinesis.

2. Choose either a modelling clay model or a flip book.

3. Represent chromosome structure and position for each stage.

4. Show chromosomes condensing during prophase.

5. Show chromosomes aligned at the metaphase plate.

6. Show sister chromatids separating during anaphase.

7. Show nuclear membranes re-forming during telophase.

8. Show cytoplasmic division during cytokinesis.

9. Clearly label each stage and key structures, such as chromosomes, chromatids, centromeres and spindle fibres.

10. Prepare a short oral explanation describing how your model represents mitosis.

Student product

A completed physical model or flip book that can be used to explain mitosis to another Year 11 Biology student.

Assessment rubric

CriteriaHigh Sound

Scientific accuracy

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All stages of mitosis correctly represented and labelled, including chromosome behaviour

Sequence and clarity Clear, logical sequence from prophase to cytokinesis

Use of biological terminology Correct and consistent use of terms such as prophase, metaphase, anaphase, telophase and cytokinesis

Communication and explanation

Discussion

Most stages correct, with minor errors

Some correct features but major inaccuracies

Model shows little understanding of mitosis

Mostly logical sequence, with minor gaps

Mostly correct terminology used

Sequence is unclear or partially incorrect

Limited use of correct terms

Sequence is missing or incorrect

Incorrect or no scientific terminology

Student clearly explains the model using correct biology concepts

Explanation is mostly clear

Explanation lacks clarity or detail

Unable to explain the model

1. Explain why physical models are useful for understanding mitosis.

2. Discuss the limitations of using a clay model or a flip book to represent mitosis.

3. Assess whether the mitosis model is scientifically valid.

4. Provide one example of warm feedback you could give another group about their mitosis model.

EXAM PRACTICE 5B

Example question

Compare meiosis and mitosis. (4 marks)

What is the question asking?

The key verb in this question is compare, which means you need to show the relationship between things, or cause and effect. You need to include:

• at least one similarity and one difference (the number of each depends on the mark)

• a direct, point-to-point comparison using the same criteria for each item

• clear, explicit linking words.

Video: Exam practice 5B

Go online to access the Interactive Textbook

Typical structure

1. State the similarity: (“Both…”, “Similarly…”, “Each…”.)

2. State the difference: (“However…”, “In contrast…”, “Whereas…”.)

You can also draw up a table to help with comparing, as shown in the sample response.

Marking criteria

Criteria

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Marks

Gives at least 4 specific similarities and differences 4

Gives at least 3 specific similarities and differences3

Gives at least 2 specific similarities or differences 2

Gives one similarity or difference 1

Sample response

Meiosis only

Similarities

Four daughter cells producedBoth involve doubling the DNA in the cell before the first division

Haploid daughter cells produced

Two splitting phases

Creates gametes

Produces genetically unique cells

SECTION 5B REVIEW

Quiz

Review questions

Review questions

Mitosis only

Two daughter cells produced

Diploid daughter cells

One splitting phase

Creates somatic cells

Produces genetically identical cells

Reporting (student and teacher)

1. Describe the main structural difference between prokaryotic DNA and eukaryotic DNA.

2. Explain how the presence or absence of histone proteins affects DNA packaging.

3. Compare the relative sizes of prokaryotic and eukaryotic genomes and discuss the biological implications.

4. Distinguish between the chromosome number of somatic and gametic cells.

5. Briefly summarise the key events that occur in each phase of the cell cycle.

6. Explain the difference between a single chromosome and a double chromosome, referring to S phase in your answer.

7. Draw a labelled diagram of the cell cycle.

5C Meiosis

SYLLABUS

At the end of this section, I will be able to:

5C.1 Describe the processes of crossing over, independent assortment and random segregation during meiosis

5C.2 Conduct a practical investigation to model the named phases of meiosis and cytokinesis

5C.3 Evaluate the importance of DNA replication, mitosis, meiosis and cytokinesis in cell division

Meiosis is the process by which animals and plants produce gametes for sexual reproduction. This process occurs in the gonads of sexually reproducing organisms (in humans, the testes and the ovaries). The process begins with a parent cell, which is diploid, and results in four “daughter” cells (the gametes), which are haploid. Remember, the gametes must contain only half the chromosomes of a somatic cell, so that when fertilisation occurs, the resulting zygote has the full set of chromosomes or a diploid number of chromosomes.

In order to produce haploid gametes, meiosis involves two divisions of the nucleus, known as meiosis I and meiosis II.

• In meiosis I, the chromosomes in the homologous pair separate and are pulled to opposite poles of the cell.

• In meiosis II, the chromatids in the double chromosome are pulled apart, forming a single chromosome, and the haploid gametes are produced.

These steps are further subdivided into several stages: interphase, prophase, metaphase, anaphase, telophase and cytokinesis (not a stage of meiosis). The events that occur during these stages are very similar to mitosis, especially meiosis II, which you will see clarified later in this section.

The stages of meiosis

The stages of meiosis are summarised in Table 5C.1.

Worksheet 5C.1

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• DNA winds up, chromosomes condense (two chromatids joined at a centromere).

• Spindle microtubules form.

• Homologous chromosomes position themselves side by side (called synapsis)

• Nuclear membrane dissolves by the end of prophase I.

• Crossing over may occur late in prophase I: chromosomes may become so close that there is an exchange of genetic material between them at the chiasmata (covered in greater detail in the subsection titled "Crossing over")

Meiosis

Table 5C.1 Stages of meiosis

Meiosis I, cont

Metaphase I

Anaphase I

Telophase I

Cytokinesis

Meiosis II

Prophase II

Metaphase II

Anaphase II

• Spindle microtubules attach to the centromere of homologous chromosomes and pull them into a line at the equator of the cell.

• Independent assortment: the homologous chromosomes take random positions along the equator of the cell.

• Random segregation of homologous chromosomes occurs during this stage.

• Spindle microtubules split the homologous chromosomes into single chromosomes, which move to opposite poles of the cell.

• The centromeres do not divide.

• Independent assortment: the bivalents move randomly to either pole.

• Spindle microtubules disappear.

• The cell membrane pinches in and two separate nuclei form, with the nuclear membrane re-forming around each.

• The cell cytoplasm divides, forming two haploid daughter cells.

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Telophase II

Cytokinesis

4 × n

• The nuclear membrane dissolves.

• Spindle microtubules re-form.

• Chromosomes move into the equator of the cell.

• Spindle microtubules attach to each chromatid via the centromere.

• Random segregation of sister chromatids occurs during this phase.

• Sister chromatids are pulled to opposite poles of the cell.

• The centromere is divided.

• The nuclear membrane re-forms and the spindle microtubules disappear.

• At the end of telophase II, the chromosomes de-condense and are no longer visible.

• Both cells pinch in half to produce four haploid cells, each containing half the genetic information of the parent cell.

• One member of a chromosome pair is present in each gamete.

Mitosis versus meiosis

A summary and comparison of the processes of mitosis (making copies of somatic cells) and meiosis (making gametes) is given in Table 5C.2.

Table 5C.2 Mitosis versus meiosis. (See the Interactive Textbook, where you can zoom in to see chromosome detail.)

Mitosis

Prophase

Meiosis

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Metaphase

Anaphase

Telophase

Cytokinesis

Synapsis and crossing over

Homologous chromosomes line up at metaphase plate

Sister chromosomes line line up at metaphase plate

Two diploid cells

Four haploid cells

Prophase I

Prophase II

Metaphase I

Metaphase II

Anaphase I

Anaphase II

Telophase I

Cytokinesis

Telophase II

Cytokinesis

crossing over the exchange of genetic material between non-sister chromatids in a homologous pair of chromosomes during prophase I of meiosis; occurs at the chiasmata and results in recombinant chromosomes, increasing variation between gametes chiasma the point of contact between non-sister chromatids in a homologous pair of chromosomes; the point at which crossing over may occur; plural: chiasmata independent assortment the random arrangement of pairs of homologous chromosomes during meiosis, resulting in the random combination of alleles into gametes

The importance of genetic diversity

The advantage of sexual reproduction and meiosis is that they create genetic variation or diversity in the offspring. Variation is necessary for populations of organisms, so some individuals are better adapted to survive changes in the environment, including selection pressures such as disease or climate change, allowing evolution to occur.

There are four main sources of genetic variation:

• crossing over (in prophase I)

• independent assortment (in metaphase I)

• random segregation of chromosomes into gametes (in anaphase II)

• random fusion of gametes from two parents (fertilisation).

Crossing over

Recall that, in prophase I, homologous chromosomes position themselves side by side. The non-sister chromatids of the homologous chromosomes are in contact with each other at points called chiasmata (singular: chiasma ). This is the physical point at which crossing over may occur. The non-sister chromatids of a homologous pair of chromosomes get so close that some of the genetic material from the maternal chromosome swaps with some of the genetic material from the paternal chromosome. This results in the chromosomes being recombined in a new combination of genetic material, leading to more variation between the gametes.

Duplicated paternal chromosome Duplicated maternal chromosome

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Recombinant chromosomes

Non-sister chromatids

Homologous chromosomes exchange genetic material

Non-recombinant chromosomes

Figure 5C.1 Crossing over during prophase I results in the formation of recombinant chromosomes with a new combination of genetic material. The black circle indicates the position of the chiasma.

Independent assortment

In metaphase I, homologous chromosomes line up in the centre of the cell. The arrangement of the homologous pairs is random: the maternal chromosome may be on the left and the paternal chromosome on the right, or vice versa. This random orientation of the homologous pairs during metaphase I is called independent assortment . Because this random assortment occurs for each homologous pair independently of the other pairs, the number of possible gamete combinations depends on the number of homologous pairs that the species has. In humans, the number of possible gamete combinations can be represented by 2n (where n represents one complete set of chromosomes in that organism) or 223 (8,388,608) possible combinations in humans.

Possibility 1

Possibility 2

Combination 1

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Combination 2

Random segregation

Combination 4

Figure 5C.2 Independent assortment during metaphase I results in many possible gamete combinations.

Random segregation is the random separation of homologous chromosome pairs during meiosis I, where one chromosome from each pair is allocated to each gamete. As a result, each gamete receives one chromosome from each of the 23 pairs.

Fertilisation

Fertilisation, or the fusion of gametes from two parent organisms, is another way in which variation is increased in species that reproduce sexually. As you know, the fusion of haploid gametes forms a diploid zygote, and crossing over and independent assortment lead to greater variation between gametes, so it makes sense that random fertilisation can produce a large number of unique genetic combinations in the zygotes.

Summary of important processes in cell division

Table 5C.3 Key processes in cell division

DNA replication Occurs during the S phase of interphase. The entire DNA in a cell is copied to produce two identical copies.

MitosisDivision of the cell producing two genetically identical diploid daughter cells.

Meiosis Two rounds of nuclear division producing four haploid gametes. Involves random segregation, crossing over and independent assortment, which increase genetic variation in daughter cells.

CytokinesisDivision of the cytoplasm following mitosis or meiosis, forming separate daughter cells.

Ensures each daughter cell receives an exact copy of genetic information, maintaining genetic stability.

Enables growth, repair and replacement of damaged cells.

Generates genetic variation in gametes and ensures the correct halving of chromosome number for sexual reproduction.

Restores the normal surface area-tovolume ratio and ensures each cell has organelles and sufficient cytoplasm to survive.

Essential for the survival of the new daughter cell.

Can cause genetic disorders if errors occur.

Faulty mitosis can lead to uncontrolled cell division (tumour formation)

Errors (e.g. nondisjunction) can cause chromosomal abnormalities such as Down syndrome.

Incomplete cytokinesis may produce multinucleate or non-viable cells, disrupting tissue function.

PRACTICAL 5C.1

Stop-motion storyboard: modelling the phases of meiosis and cytokinesis

Aim

questions download word download pdf

To conduct a hands-on practical investigation to model and visualise the stages of meiosis and cytokinesis using craft materials, documenting each phase in a storyboard that can be transformed into a stop-motion animation.

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Materials

• Coloured clay or modelling dough (for chromosomes and spindle fibres)

• String or wool (for spindle fibres)

• Paper plates or cardboard circles (for cell membranes)

• Markers or coloured pencils

• Scissors and glue

• Smartphone or tablet (for photographing or creating stop-motion video)

• Worksheet or storyboard template (provided)

Method

1. Review the key stages of meiosis (prophase I, metaphase I, anaphase I, telophase I, cytokinesis I, prophase II, metaphase II, anaphase II, telophase II and cytokinesis II).

2. Sketch a storyboard outlining how you will represent each phase, showing homologous chromosomes, crossing over, spindle formation and chromosome separation.

3. Using materials, build a 3D model of the cell and chromosomes using different colours to distinguish maternal and paternal chromosomes.

4. Take a photo of each phase in sequence, showing chromosomal behaviour and cytokinesis clearly.

5. Optional extension: use a stop-motion app to compile the images into a short animation of meiosis.

6. Label each image in your storyboard with the name of the phase and key events.

Storyboard template

Give your table an appropriate heading.

Phase Description of key events Sketch

Prophase I

Metaphase I

Anaphase I

Telophase I

Cytokinesis I

Prophase II

Metaphase II

Anaphase II

Telophase II

Cytokinesis II

Labels/materials needed

Discussion

1. Which phase of meiosis was the most challenging to represent accurately, and why?

2. How does your model show the difference between meiosis I and meiosis II?

3. What evidence in your model demonstrates crossing over and independent assortment?

4. What are the strengths and limitations of using a craft model to represent meiosis, compared to a digital simulation or microscope observation?

EXAM PRACTICE 5C

Example question

Discuss the impact of mutations occurring in somatic and germline cells. (4 marks)

What is the question asking?

The key verb used in the question is discuss, which means you need to include points for and/or against the statement. This means if there are opposing points they need to be included. You need to highlight how much a change in DNA will affect an individual if it occurs in a somatic cell or in a germline cell.

Marking criteria

Criteria

• Gives 2 points related to the impact of mutations in germline cells

• Gives 2 points related to the impact of mutation on somatic cells 4

• Gives 3 points total for the impact of mutation on germline and somatic cells

• Gives 1 point related to the impact of mutations on germline cells

• Gives 1 point related to the impact of mutation on somatic cells 2

• Makes 1 relevant comment related to the impact of mutation 1

Sample response

Somatic mutation: In a somatic cell, the mutation will result in only the single cell being affected. Somatic mutations are not passed on between generations.

Germline mutation: This does not affect the organism that the gamete is in; rather, it affects the next generation. Germline mutations affect every cell in the body of the offspring.

Review questions

1. Outline the purpose of meiosis.

2. Distinguish between meiosis I and meiosis II.

3. Summarise the processes in meiosis I and II by listing two key aspects of each stage. Try to select features of each stage that distinguish it from the other stages.

4. Describe how variation arises through meiosis and fertilisation.

5. Explain why genetic variation, or diversity, among offspring is advantageous to the continuity of a species.

Chapter review

Revise and consolidate your learning with these online tools:

• Success criteria checklist (view online or download)

• Review questions (answer online or download)

• Suggested responses (view online with teacher enabled access)

• Depth study support (download)

Teachers can access these additional downloadable resources and Learning Management System features:

• Individual and whole class reports

• Assign tasks and track results

• Create (and print) custom practice exams

• Chapter tests (download)

• Chapter summaries (download)

Success criteria checklist

I am now able to:

5A.1 Use the deoxyribonucleic acid (DNA) double helix model to demonstrate the structure of DNA, including nucleotide composition, complementary base pairing and hydrogen bonding 1, 2

5A.2 Conduct a practical investigation to model the process of DNA replication, demonstrating the role of complementary bases, the replication fork with leading and lagging strands, and the enzymes of helicase, primase, DNA polymerases and ligase

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Practical 5A.1

5A.3 Assess the use of models to demonstrate DNA replication 6

5A.4 Construct diagrams to compare the forms in which DNA exists in prokaryotic and eukaryotic cells 7

5B.1 Compare the structures and roles of somatic and gametic cells 3

5B.2 Account for the phases of gap 1 (G1), synthesis, gap 2 (G2) and mitosis in the cell cycle 5, 8, 9

5B.3 Conduct a practical investigation to model the named phases of mitosis and cytokinesis

Practical 5B.1

5C.1 Describe the processes of crossing over, independent assortment and random segregation during meiosis 4, 13

5C.2 Conduct a practical investigation to model the named phases of meiosis and cytokinesis

Practical 5C.1

5C.3 Evaluate the importance of DNA replication, mitosis, meiosis and cytokinesis in cell division 10, 11, 12, 14

Multiple-choice questions

1. DNA replication is described as semi‑conservative because

A. both original strands are degraded and replaced.

B. each daughter molecule contains one old and one new strand.

C. only the lagging strand is copied accurately.

D. each new molecule contains two newly made strands.

2. Which enzyme is responsible for unwinding the DNA double helix during replication?

A. ligase

B. DNA polymerase

C. helicase

D. primase

3. Which statement correctly compares somatic cells and gametes?

A. Somatic cells are haploid; gametes are diploid.

B. Somatic cells and gametes both form through mitosis.

C. Gametes are genetically identical to the parent cell.

D. Somatic cells are diploid; gametes are haploid.

4. During meiosis I, genetic variation is increased by

A. cytokinesis.

B. crossing over and independent assortment.

C. DNA polymerase proofreading.

D. chromosome condensation.

5. Which phase of the cell cycle involves DNA synthesis?

A. G1

B. S phase

C. G2

D. M phase

Exam-style questions

6. Explain why DNA replication is described as semi conservative. (2 marks)

7. Compare the structure of DNA in prokaryotes and eukaryotes, referring to location and packaging. (4 marks)

8. Outline the roles of spindle fibres and centromeres during anaphase. (2 marks)

9. Describe the significance of the G2 phase in the eukaryotic cell cycle. (2 marks)

10. The table shows the relative time a typical cell spends in each stage of the cell cycle.

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Analyse the data to explain what it suggests about the importance of interphase in maintaining normal cell function. (4 marks)

11. Explain how the process of meiosis contributes to the continuity of a species. (4 marks)

12. Assess the importance of mitosis and meiosis in maintaining genetic stability and promoting variation in sexually reproducing organisms. (5 marks)

13. Evaluate the significance of the three key sources of genetic variation – crossing over, independent assortment and random fertilisation – in ensuring the survival of species in changing environments. (6 marks)

14. Discuss the consequences for an organism if errors occur during DNA replication or chromosome segregation. In your answer, refer to named examples or disorders. (5 marks)

15. You are provided with onion root tip cells. Design an investigation to determine the proportion of cells undergoing mitosis at any given time. In your plan, include a hypothesis, variables, a brief method and data presentation. (8 marks)