Habitat characteristics affecting use of lowland agricultural grassland by birds in winter

Biological Conservation 95 (2000) 279±294

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Habitat characteristics a ecting use of lowland agricultural grassland by birds in winter Allan J. Perkins a,*, Mark J. Whittingham a, Richard B. Bradbury a, Jeremy D. Wilson a,b, Antony J. Morris a, Philip R. Barnett a a

Ecology and Behaviour Group, Edward Grey Institute of Field Ornithology, Department of Zoology, South Parks Road, Oxford OX1 3PS, UK b RSPB, The Lodge, Sandy, Bedfordshire SG19 2DL, UK Received 25 August 1999; received in revised form 2 February 2000; accepted 3 March 2000

Abstract Almost a third of the bird species designated as Species of European Conservation Concern exploit agricultural grasslands, yet few studies have focused on their use as foraging habitats for birds. This study investigated the in¯uence of variation in sward structure, grassland management and landscape variables on the use of 77 grass ®elds by 14 ®eld-feeding bird species wintering on lowland mixed farmland in southern England. Multiple logistic regression was used to model the proportion of bird-count visits in which each species was encountered as a function of the recorded habitat variables for each ®eld. Variation in sward height and density were associated with frequency of occurrence for 12 bird species and larger areas of bare earth and occurrence of winter grazing by stock animals were correlated with greater frequency of occurrence by 11 bird species. Two rapidly declining species, skylark (Alauda arvensis) and yellowhammer (Emberiza citrinella), were recorded more frequently on ®elds with higher numbers of seeding grasses. We suggest that mosaics of ®elds managed as short-term leys and permanent pastures with low-intensity cattle grazing over the autumn and winter would provide the combination of heterogeneous sward structure, areas of bare earth and presence of some seeding plants necessary to maximise the range of bird species able to use a given area of agriculturally improved grassland throughout the winter. # 2000 Elsevier Science Ltd. All rights reserved.

Keywords: Grassland; Agricultural intensi®cation; Conservation; Farmland birds; Sward structure

1. Introduction Agricultural practice in the British Isles and throughout Europe has changed considerably over the last 50 years, with an emphasis on intensi®cation and polarisation of land use (O'Connor and Shrubb, 1986; Lack, 1992; Pain and Pienkowski, 1997). Intensi®cation of grassland management (`improvement') to provide better grazing and higher yield of forage grasses comprises increased fertiliser application, drainage, and regular ploughing and re-seeding with a limited range of competitive, nitrogen-responsive grass species, especially rye-grasses (Lolium spp) (Fuller, 1987; Vickery et al., 1999; Wilson et al., 1999). Agricultural grassland habitats cover >20% of the land area in 11 out of 35 European * Corresponding author. Tel.: +44-1865-271156; fax: +44-1865271221.

E-mail addresses: allan.perkins@Zoology.ox.ac.uk (A.J. Perkins), richard.bradbury@zoology.ox.ac.uk (R.B. Bradbury).

countries for which data are available (Tucker and Evans, 1997) and, within Britain, enclosed grasslands now occupy >50% of the agricultural land, the extent varying from around 60% of all enclosed agricultural land in the west of the country to <15% in the east (MAFF, 1997; Vickery et al., 1999). Agricultural improvement of >90% of British grassland has taken place during the 20th century, mostly since the Second World War (Fuller, 1987; Hopkins and Hopkins, 1994).

As a result stocking densities have increased and silage leys, which receive multiple cuts throughout the summer and high fertiliser and herbicide inputs, have replaced hay meadows (Fuller, 1987; Hopkins and Hopkins, 1994). Arable and agriculturally improved grassland habitats are of importance to 81 of the 278 bird species designated as being Species of European Conservation Concern (SPECs), and 79 of these are species recognised as having permanent grassland as a preferred habitat (Tucker and Evans, 1997). It is, therefore, important to consider how the grassland component of these agricultural

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habitats can best be managed to maximise their value as habitats for birds and other wildlife within the constraints of management that focuses on production of forage grasses and pasture.

Most such studies have focused on the nesting habitat requirements of ground-nesting species (e.g. Baines, 1989; Shrubb, 1990; O'Brien and Smith, 1992; Green et al., 1997; Wakeham-Dawson et al., 1998) or on the impact of grazing wildfowl (e.g. Summers and Critchley, 1990; Percival, 1993). Few studies have examined the e ects of management on the value of agricultural grassland as a winter foraging habitat for the wide range of species which exploit farmland for invertebrate and seed foods. Such studies as there are (Tucker, 1992; Wilson et al., 1996b; Buckingham et al., 1999) have considered grassland as only one component of a wider range of habitat types (e.g. arable crops, set-aside). This study investigated in detail how the winter use of lowland agricultural grassland by foraging birds varied in relation to habitat structure and ®eld management.

counted. Because it was not possible to know which ®elds were being used by birds resting within or upon boundary features such as hedgerows, fencelines or isolated trees within ®elds, these birds were excluded from later analyses. Counts were made with binoculars and the observer walked a predetermined number of transects across each ®eld (walked along the longest axis), based on 50 m separation measured from 1:10,000 Ordnance Survey maps, in order to ¯ush all birds in the ®eld. This method achieved complete counts of birds except where the vegetation within a ®eld was particularly tall and dense. In these cases, closer transects (20 m separation) were used. Some species tend to use only the ®eld edge (Spencer, 1982) so the two outer transects were within 10 m of the ®eld boundary. Double-counting of birds was minimised by observers taking into consideration birds which were ¯ushed to other ®elds or to other parts of the ®eld being surveyed. Surveys were carried out at least 1 h after sunrise and completed by at least 1 h before sunset to avoid missing birds travelling to or from roost sites.

2. Methods

2.3. Habitat recording

2.1. Study sites

During October and November (`autumn'), and again in March (`spring'), quadrate surveys were carried out on each of the 77 ®elds to obtain data on sward structure. Given the large number of ®elds to be surveyed, data on most ®elds were collected from 15 1 1 m quadrates, subdivided into 100 10 cm squares. This was the maximum number of quadrates achievable with the logistical constraints of the study. However, only 10 quadrates were sampled on the seven ®elds of <1 ha.

Each corner quadrate was placed within 1 m of the boundary and quadrates were placed approximately equidistantly from corner to corner across each ®eld, avoiding any areas which were devoid of vegetation.

Such areas of bare earth were measured separately (see below). Sward height was measured using a ruler placed vertically in each corner square of the quadrate and one in the centre to give ®ve measures per quadrate of the tallest live vegetation stem. The mean of these ®ve measures was calculated for each quadrate. A measure of sward density was taken as the number of 10 cm squares with <50% of the surface area visible as exposed soil. Mean and standard deviation (SD) values over all quadrates were used to de®ne the sward characteristics of each ®eld.

Two other sward variables were only measured in autumn. For dicotyledonous plant species, we calculated the total number of species (herb richness) in a ®eld by aggregating data from all quadrates in that ®eld.

Grasses were not speci®cally identi®ed, but we did record the proportion of sampling squares in each quadrate occupied by any seeding grasses. The mean was then calculated for each ®eld (grass in seed).

Fieldwork took place between October 1997 and March 1998 on 77 grass ®elds covering 432 ha (ranging in area from 0.4 to 22.2 ha, with a mean of 5.61 ha), distributed across eight study sites in mixed lowland farmland in Oxfordshire, Wiltshire and Warwickshire, UK. All study sites were mixed farms, with pastoral and arable components varying in proportions between sites. Field boundaries varied considerably between and within the eight study sites, from mature tree lines to open ditches and fences. Combined, the sites covered an area of c. 1020 ha of which, at the start of the study, 46% was grass, 30% winter-sown cereal [wheat (Triticum) or barley (Hordeum)], 13% stubble, 5% winter-sown broadleaved crops [oilseed rape (Brassica napus ssp oleifera) and beans (Phaseolus)], 5% bare till and 1% non-cropped habitats. Between and within the eight study sites, grassland management varied from intensively managed silage leys and improved, grazed pastures to extensively managed rough grazing. No grass ®elds were ploughed during the study.

2.2. Bird counts Two visits per month were made to each ®eld from November 1997 to March 1998 inclusive. Six ®elds received only nine visits. All bird species using a ®eld were counted. These included all birds recorded on the ground and birds hunting over ®elds such as sparrowhawks (Accipiter nisus) or kestrels (Falco tinnunculus).

Other birds simply seen ¯ying over ®elds were not

A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

Other habitat characteristics were recorded on each bird-count visit. These were: presence and species of grazing stock (cattle, horses or sheep), number of stock, presence of human-provided feed for livestock/game, and an estimate of the amount of exposed bare earth (m2). The majority of ®elds had at least one small area, usually next to gateways or livestock feeders and water troughs, where the ground had been trampled or poached by livestock or vehicles. All areas of bare earth 1 m2 or larger were summed per ®eld on each bird-count visit.

Mean values of bare earth over all visits were calculated for each ®eld. Presence/absence of an adjacent building or stubble was recorded on the ®rst bird-count visit.

Most ®elds were grazed either infrequently or not at all, through the winter, so there were insu cient data to test for e ects of livestock densities on bird distributions.

Instead, a two-level categorical variable simply describing whether a ®eld was being grazed or not on any visit during the winter was used in the modelling analyses. A similar approach was taken to analyse the e ects of the presence within ®elds of animal feed. Physical enclosure of ®elds may a ect their use by certain bird species. To investigate the e ects of ®eld enclosure we divided ®elds into four categories, according to whether more or less than 50% of the ®eld boundary consisted of hedgerow/ tree line (rather than a fence or no vertical structure), and whether that hedgerow/tree line was greater or less than 3 m in height (disregarding any isolated trees of >3 m within the hedgerow; Table 1).

Data relating to individual ®eld management, including sowing date, were supplied by farmers prior to the study. Field area was measured from 1:10,000 Ordnance

281

Survey maps using the AutoCAD software package (AutoCAD Release 13, Autodesk, San Rafael, California) and an A3 digitising slate (CalcComp, Reading, UK).

Fields were grouped into four management categories: grass leys, mixed grass-clover leys, permanent pastures and rough grass. The distinction between leys and permanent pastures was based on age of the sward. All ®elds <10 years old were classi®ed as leys (85% were <5 years old and 30% were <2 years old). Most leys were cut during the spring and summer for silage and many were grazed after the last cut. All permanent pastures were at least 10 years old, often considerably older. They were not cut but were grazed at various times of the year. The full list of habitat variables used in the analyses is summarised in Table 1.

2.4. Statistical analysis To ®nd which habitat characteristics explained a signi®cant proportion of variation in ®eld use for each bird species, we used multiple logistic regression to model the proportion of bird-count visits in which each species was encountered as a function of the recorded habitat variables (Table 1) over all 77 ®elds. The number of visits to a ®eld on which the species was recorded was speci®ed as the response variable and total number of visits to that ®eld as the binomial denominator (specifying a binomial error structure and a logit link function: Crawley, 1993). All modelling was undertaken in GLIM release 4 (NAG, 1993). Using this approach, models were built for 14 species which were recorded on at least 14 ®elds (see Table 2). One exception was pheasant

Table 1 Environmental variables describing habitat characteristics of the 77 ®elds Variable

Type

Sward height and standard deviation in autumn Sward height and standard deviation in spring Sward density and standard deviation Bare earth Field area Grass in seed Herb richness Stubble Building Grazed Animal feed Field enclosure

Continuous variables Continuous variables Continuous variables Continuous variable Continuous variable Continuous variable Continuous variable 2-Level factor 2-Level factor 2-Level factor 2-Level factor 4-Level factor

Farm Management category

8-Level factor 4-Level factor

a

n=Number of ®elds relating to given factor level.

Factor levels

na

Adjacent or not Adjacent or not Grazed or not on at least one bird-count visit Present or not on at least one bird-count visit Boundary <50% hedgerow/treeline, max. height <3m Boundary <50% hedgerow/treeline, max. height >3m Boundary >50% hedgerow/treeline, max. height <3m Boundary >50% hedgerow/treeline, max. height >3m

24 31 46 12 5 14 8 50

Grass ley Mixed grass-clover ley Permanent pasture Rough grass

17 18 38 4

Adjacent Adjacent Grazed Present

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Table 2 Total counts of farmland bird species on the four ®eld management categories across all study sites Species

Grass ley

Grass-clover ley

Pasture

Rough grass

Kestrel Falco tinnunculus Red-legged partridge Alectoris rufa Grey partridge Perdix perdix Pheasant Phasianus colchicus Golden plover Pluvialis apricaria Lapwing Vanellus vanellus Common snipe Gallinago gallinago Black-headed gull Larus ridibundus Stock dove Columba oenas Woodpigeon Columba palumbusb Skylark Alauda arvensisb Meadow pipit Anthus pratensisb Pied wagtail Motacilla albab Dunnock Prunella modularis Robin Erithacus rubecula Blackbird Turdus merulab Fieldfare Turdus pilarisb Song thrush Turdus philomelos Redwing Turdus iliacusb Mistle thrush Turdus viscivorus Magpie Pica picab Jackdaw Corvus monedulab Rook Corvus frugilegusb Carrion crow Corvus coroneb Starling Sturnus vulgarisb House sparrow Passer domesticus Tree sparrow Passer montanus Cha nch Fringilla coelebsb Green®nch Carduelis chloris Gold®nch Carduelis carduelis Linnet Carduelis cannabina Yellowhammer Emberiza citrinellab Reed bunting Emberiza schoeniclus Corn bunting Miliaria calandra

2 0 4 18 0 0 7 1676 7 384 207 32 6 0 1 8 523 0 50 1 1 747 1181 164 1293 6 0 161 0 0 0 3 3 0

2 8 16 5 1 6 3 1007 0 2498 205 325 5 0 1 22 1552 0 90 5 6 231 993 89 1137 0 0 78 0 1 1 78 0 0

2 9 2 24 0 0 12 90 4 518 6 72 107 7 11 126 1207 4 55 8 18 403 1587 66 555 40 5 622 35 18 5 61 0 0

0 0 0 14 0 0 39 0 0 16 30 21 1 1 1 0 2 9 0 0 8 66 209 23 0 0 0 37 0 2 0 6 9 0

Totalc Area (ha) Field visitsd

7841 107.0 170

9792 179.2 179

5726 127.7 377

612 18.1 38

Total birdsa 6 17 22 61 1 6 61 2773 11 3416 448 450 119 8 14 156 3284 13 195 14 33 1447 3970 342 2986 46 5 898 35 21 6 148 12 0

(6) (6) (4) (18) (1) (1) (9) (10) (3) (30) (21) (26) (20) (7) (11) (39) (23) (6) (16) (7) (15) (26) (48) (39) (29) (3) (1) (24) (3) (8) (2) (17) (3) (0)

23597 (76) 432 764

a `Total birds' shows the total number of birds recorded on grass ®elds, with the number of ®elds in which these birds were recorded in parentheses. b Indicates species included in multivariate analyses. c Total counts are of all species recorded, including those not in the table. d Number of ®eld visits over the whole winter, by management category. Note that six ®elds were visited only nine times.

(Phasianus colchicus), which was excluded from analyses due the likelihood of distributions being biased by local releases. Nine of these 14 species are Species of European Conservation Concern (Tucker and Heath, 1994). This method of analysing ®eld occupancy was chosen for three reasons. First, it allowed some weighting of preference within those ®elds selected (unlike binary used/ unused models which only di erentiate between ®elds which were or were not used at any point during the winter). Secondly, although some total counts for the whole winter were very high (Table 2), birds were highly aggregated within ®elds, resulting in many zero counts and only small numbers of high counts on individual ®eld visits. Attempts to model these data using both Poisson and negative binomial error structures provided

poor model ®ts with very high levels of overdispersion.

Such poor ®t of the models can be due either to failure to include important environmental variables in the model or, more likely in this case, failure to meet the assumptions of the speci®ed error distribution (Collett, 1991; Crawley, 1993). Thirdly, the relationship between the proportion of visits on which the species was observed and the total number of individuals recorded on that ®eld during the winter was found to be positive for all 14 species, and signi®cantly so for 11 of these (Fig. 1).

One potential pitfall of using this approach is the unaccounted error caused by di ering numbers of birds being present on each visit. For example, if the total count across all ®elds on a visit `A' was very large, birds

A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

would, if distributed randomly, occur on ®elds of all sizes whereas if the total count on visit `B' was very low there would be a bias towards birds using big ®elds. Big ®elds may, therefore, be over-represented in the frequency counts. To test for this we used Spearman-rank correlation to compare mean ®eld area from each visit with (a) number of ®elds occupied by a species on that visit and (b) total count of a species across all ®elds on that visit. There were no associations found in 13 out of 14 species (P<0.05). The exception was meadow pipit (Anthus pratensis) which tended to be found on larger ®elds when fewer ®elds were used (Spearman-rank r=ÿ0.70, d.f.=9, P=0.025), but no relationship was found when more birds were present (r=ÿ0.32, d.f.=9, P=0.37). Models for this species should, therefore, be interpreted cautiously.

In model-building, backwards deletion was used to simplify models (Crawley, 1993). Initially, all habitat variables (including quadratic terms for continuous variables) were entered into a full model. Each variable was then excluded and re-®tted to the model in turn.

The signi®cance of exclusion of each variable was assessed by comparing the change in deviance in the model with the w2 distribution with the appropriate number of degrees of freedom. The variable whose exclusion resulted in the smallest change in deviance was removed from the model, unless that change was signi®cant at P=0.05. Linear terms for continuous variables could only be removed from the model if the quadratic term had already been removed. The Minimum Adequate Model (MAM) was reached when no variables could be added or deleted from the model without causing a signi®cant change in deviance. Once the MAM was attained, further post-hoc contrasting tests were undertaken to identify signi®cant di erences between the four levels of the factor ®eld enclosure. This was achieved by grouping factor levels together and then re-®tting the factor to the model.

Two potential problems needed to be addressed in the analysis. First, the order in which variables were deleted from stepwise models could lead to di erent MAMs being selected, especially when variables were highly intercorrelated (James and McCulloch, 1990). Table 3 presents the associations between variables used in this study. Farm was signi®cantly associated with a number of other variables. Secondly, the ®elds in our study were not independent because they were clustered within farms. To account for both the non-independence of ®elds within farms and the association of farm with other variables the null model was taken to include farm (whether or not it was statistically signi®cant). This technique helps to exclude variables which may otherwise be retained in MAMs but which are acting as surrogates for other, unmeasured habitat characteristics acting at the farm level (e.g. Green et al., 1994; Wilson et al., 1997). Conversely, retention of farm in the MAMs could mask genuine in¯uences of variables that happen to vary

283

strongly between study sites. To reveal any such masked e ects, a second set of MAMs were constructed, with farm excluded from the models. However, the results of these models should be interpreted with caution as it was not possible to di erentiate between independent and spatially autocorrelated in¯uences of variables when they were retained only in MAMs which excluded farm.

When other variables were signi®cantly associated with each other and one `A', but not the other `B', remained in the MAM, then `B' was substituted for `A' and its signi®cance was assessed by deletion from the remaining model. If `B' was signi®cant then both `A' and `B' could have had a signi®cant impact on frequency of that species occurrence.

Logistic or log-linear regression prohibits the calculation of meaningful R2 values, as the variance is proportional to the mean in these models. There is no ®rm theory which predicts the power of the MAM in explaining the variance, i.e. as R2 does in normal regression (Collett, 1991; Crawley, 1993). Instead, the ®t of the model to the data can be approximately assessed by the ratio of the residual deviance divided by the residual degrees of freedom.

Ratios close to one suggest that the model provides a good ®t to the data (Crawley, 1993). Ratios of over two suggest that the data are overdispersed (either through lack of binomial error in the data or failure to include important explanatory predictors in the MAM) and that the power of the model in explaining the data is weak.

To ®nd di erences in habitat characteristics between di erent management categories, variations in all the continuous habitat variables were modelled as a function of management category. Variation in each of these variables was highly skewed and was, therefore, best modelled using a Poisson error distribution and a log link. When the ratio of residual deviance to residual degrees of freedom exceeded 2, standard error values p were multiplied by (residual deviance/residual degrees of freedom) to correct for overdispersion in the model (Crawley, 1993). In this study, overdispersion was caused by the highly skewed frequency distributions of the habitat characteristics measured. Post-hoc tests were carried out (as described above) to identify signi®cant di erences between factor levels. The degree of association between management and each of the factorial parameters (stubble, building, grazed, animal feed, ®eld enclosure, and farm) were determined using the Cramer coe cient (Siegel and Castellan, 1988).

3. Results 3.1. Bird counts Sixty species, with a total count of >23,000 birds, were recorded from 764 bird-count visits to the 77 grass ®elds

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A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

(Table 2). Of the 14 species analysed, only blackbird (Turdus merula), rook (Corvus frugilegus) and carrion crow (Corvus corone) occurred in >50% of the ®elds surveyed. A further four species, woodpigeon (Columba palumbus), meadow pipit, jackdaw (Corvus monedula) and starling (Sturnus vulgaris) occurred in more than a third of the ®elds. Ten of the 14 species are primarily insectivorous and only cha nch and yellowhammer are predominantly granivorous in winter. During the winter,

woodpigeon and skylark (Alauda arvensis) consume both green plant material and seeds. As shown by other studies (e.g. Wilson et al., 1996b), many other seed-eating species were found on very few grass ®elds, and in very low numbers.

Few ®elds registered multiple observations throughout the winter, suggesting that most species had a high degree of mobility or were scarce (Fig. 1). Six species [pied wagtail (Motacilla alba), redwing (Turdus iliacus),

A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

285

Fig. 1. Plots for the 14 bird species analysed showing number of visits (frequency) on which the species was recorded on a ®eld against total number (count) of individuals recorded on that ®eld during the winter. These were signi®cantly positively correlated for 11 species. Plot labels give sample sizes in cases where >1 ®eld had the same frequency/count combination. Spearman-rank correlation coe cients are shown. n=number of ®elds used by that species. * P<0.05 ; **P<0.01 ; ***P<0.001.

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A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

Table 3 P-values of correlations between all pairwise combinations of the 16 variables used in multivariate analyses of bird distributions across di erent ®eldsa Sward Sward Sward height height height (spring) st. dev. (autumn) (spring) Sward height (spr.)b Height st. dev. (spr.)b +*** Sward height (aut.)b Height st. dev. (aut.)b Sward densityb Sward density st. devb Bare earthb Field areab Grass in seedb Herb richnessb Stubblec Buildingc Grazedc ±* Animal feedc Field enclosured Farmd

+*

+*** +* ±*** +*** ±**

Sward Sward Sward Bare Field Grass in Herb Stubble Building Grazed Animal Field height density density earth area seed richness feed enclosure st. dev. st. dev. (autumn)

+** ±*** +*** ±*

±*** ±*

+** +** ±* +* +**

***

***

***

***

***

**

***

***

a Correlations were tested using Mann±Whitney (2 level factor vs continuous variable), Kruskal±Wallis (>2 level factor vs continuous variable), Spearman Rank or Pearson (continuous variable vs continuouus variable) and Cramer's V or t- (>2 level factor vs >2 level factor) tests. Signi®cant correlations are asterisked. Directions of relationships are given for continuous variables only. * P<0.05 ; ** P<0.01 ; *** P<0.001. b Indicates continuous variable. c Indicates 2-level factor. d Indicates >2-level factor.

®eldfare (Turdus pilaris), magpie (Pica pica), cha nch (Fringilla coelebs) and yellowhammer (Emberiza citrinella)] were never recorded more than three times in any one ®eld. Skylark, meadow pipit, rook and carrion crow were the only species for which 25% or more of the ®elds used contained birds on four or more visits.

3.2. Summary of ®eld habitat characteristics Data summarising the habitat characteristics of the 77 ®elds surveyed are presented in Table 4. Of the measured Table 4 Summary of sward structure characteristics and ®eld size Habitat characteristic

Mean 1 standard error

Range

Sward height in spring (cm) Sward height standard deviation in spring Sward height in autumn (cm) Sward height standard deviation in autumn Sward densitya Sward density standard deviationa Bare earth (m2) Grass in seedb Herb richness (# species) Field area (ha)

9.7 0.4 2.1 0.1 11.5 0.7 5.0 0.50 95.4 0.7 6.6 0.7 108.1 17.1 3.1 0.6 10.0 0.3 5.61 0.5

5.0±20.6 0.6±7.3 4.9±39.7 1.5±27.3 59.5±100 0±27.8 0±734 0±31.8 4±17 0.4±22.18

a Units are based on the mean percentage of surface area covered by vegetation per quadrate. b Units are based on the mean percentage cover of seeding grasses per quadrate.

sward parameters, only sward height and standard deviation di ered signi®cantly between the ®rst and second sampling occasions and so only these variables are broken down by season in Table 4. Sward structures were similar for a large number of ®elds with, for example, mean sward height of 85% of the 77 ®elds within the range 5±15 cm. Sward densities also varied little between the majority of ®elds, with scores of >90% for 88% of the 77 ®elds surveyed. The mean area of bare earth within di erent ®elds was more variable than other characteristics. A quarter of the ®elds had a mean area of bare earth of <10 m2 and 38% had >100 m2.

Livestock were present on at least one bird-count visit in 60% of the ®elds surveyed. Animal feed was present in 12 ®elds and tended to be located close to ®eld boundaries. Twenty-four grass ®elds were adjacent to stubbles. These were all wheat or barley stubbles with the exception of one maize (Zea mays) stubble. Of the 31 ®elds which were next to a building, 19 were next to farmyards, with the remainder adjacent to either houses or barns.

3.3. Logistic regression models The results of the 14 species models are presented in Table 5. Farm had a signi®cant in¯uence on the distribution of 12 of the 14 species and was the strongest predictor in seven MAMs. Table 6 shows the additional variables which were retained when farm was not included

A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

287

Table 5 Results of multivariate analyses for 14 bird speciesa Model Sward goodness height of ®t (res dev/res df) Woodpigeon Skylark Meadow pipit Pied wagtail Blackbird Fieldfare Redwing Magpie Jackdaw Rook Carrion crow Starling Cha nch Yellowhammer

1.287 0.853 1.111 0.547 1.128 0.967 0.69 0.496 0.995 1.600 1.220 1.153 0.873 0.83

Sward Sward Sward Bare height density density earth standard standard deviation deviation ±*

±ns(s)/b +*** ±* (a) ±*** (a)±*(s)

±*

Grass in Herb Stubble Building Grazed Field Field seed richness enclosure area

±ns/b+** +*** +*** +** +*/b±*

±* +**

+* +***

±ns(a)/b+*** ±*(s)

+** +* (a)

+*** +*

+* +*

±***

+*

+*** +*** +*** +**

+*** +*** +***

** *

Farm

*** *** *** *** +*/b±* *** +** **

+*** +***

ns

* *

+** +*** +*** +*

*** * *** *** * * ns

a Signi®cance levels and, where relevant, direction of association (+ or ÿ) between predictor variables and frequency of occurrence of the bird species are given for each Minimum Adequate Model. For sward height measures, (a)=autumn; (s)=spring. *P<0.05; **P<0.01; ***P<0.001. b Denotes a quadratic relationship and is given by+/ bÿ, with the sign and signi®cance of the linear term to the left of the slash.

in the modelling process. The importance of these variables, however, cannot be disentangled from the e ect of farm, and they may be acting as surrogates for unmeasured habitat characteristics acting at the farm level. Fig. 2 presents plots which illustrate quantitatively the predicted e ect of varying speci®c habitat characteristics on the probability of ®eld use by bird species. For all models, the ratios of the residual deviance to the residual degrees of freedom varied between 0.50 and 1.60, indicating that all models provided a good ®t to the data.

3.3.1. Vegetation structure Of the vegetation structure variables included in the models, sward height, sward density, and bare earth, the last was the strongest predictor of bird distributions.

Nine of the 14 species were associated with bare earth.

These were woodpigeon, skylark, meadow pipit, pied wagtail, blackbird, redwing, ®eldfare, jackdaw and carrion crow (Tables 5 and 6). All except woodpigeon were found more frequently as the area of bare earth increased, although quadratic relationships were found for skylark and blackbird. Greater sward height was a signi®cant predictor for eight species; pied wagtail, blackbird, carrion crow and starling (negative relationships), magpie (positive relationship), and meadow pipit, rook and cha nch (quadratic relationships; Tables 5 and 6). Increasing sward height standard deviation in autumn was associated with higher frequency of occurrence by yellowhammer, implying that this species selected ®elds with structurally heterogeneous swards. Quadratic relationships with increased sward height standard deviation were found for woodpigeon, skylark, rook and carrion crow (Tables 5 and 6). Sward density was signi®cant for three species; pied wagtail selected ®elds with sparser swards, rooks selected denser swards, and

®eldfare showed a quadratic relationship (Tables 5 and 6). Increasing sward density standard deviation was a signi®cant predictor for skylark (negative relationship) and rook (quadratic relationship). Autumn sward height and sward density were weakly correlated (Table 3), with tall swards being more dense. Replacement of autumn sward height with sward density, and vice-versa, in the MAMs in which one or the other predictor was present did not result in the replacement variable being signi®cant in any of these models. Thus, sward height and sward density could be considered as independent in¯uences on distributions of those species when they were present in the MAMs. In addition, both variables were present in the MAM for pied wagtails which selected shorter, sparser swards (Table 5). Bare earth was correlated with building and sward density standard deviation (Table 3). The evidence that bare earth was the real explanatory variable, and not building, was tested by replacing bare earth with either sward density standard deviation or building in MAMs which retained bare earth but not either of the other two variables. In no cases did the inclusion of the alternative predictor variable lead to a signi®cant change in deviance, supporting the idea that bare earth was an important determinant of bird distribution for these species. Furthermore, bare earth was signi®cantly positively associated with ®eld occupancy by both rook (w2=4.33, d.f.=1, P<0.04) and cha nch (w2=8.16, d.f.=1, P<0.005), when it was included in their MAMs instead of building.

3.3.2. Grass in seed and herb richness Four species, skylark, rook, starling and yellowhammer were found more frequently on ®elds which supported more grass in seed (including volunteer cereals from crops of previous years) (Tables 5 and 6, see

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Table 6 Summary of results of multivariate analyses for 14 species which exclude the variable farma Variable

Species model

w2 Value and trend

Sward height (autumn)

Meadow pipit Magpie Carrion crow Starling Cha nch

+*** +* ±* ±** ±/+**

Sward height standard dev. (autumn)

Woodpigeon Skylark Rook Carrion crow

±/+* +/±* ±/+** ±/+**

Sward density

Fieldfare Rook

+/±* +*

Sward density standard dev.

Rook

±/+***

Bare earth

Woodpigeon Fieldfare

±* +*

Grass in seed

Blackbird Magpie Yellowhammer

±*** ±* +*

Stubble

Skylark Cha nch

±*** ±*

Building

Woodpigeon

+***

Grazed

Jackdaw

+*

Field enclosure

Woodpigeon Skylark Fieldfare Rook Carrion crow Yellowhammer

** *** * ** *** *

Field area

Woodpigeon Starling

+*** +**

a Signi®cant species/variable relationships additional to those found when farm was included in the analyses are presented. Signi®cance levels and, where relevant, the direction of association between habitat variable and bird species are presented. *P<0.05; **P<0.01; ***P<0.001.

below for yellowhammer). Blackbird and magpie showed the reverse relationship, but only when farm was excluded from the modelling process (Table 6).

Starlings occurred less frequently on ®elds with high herb richness, but this variable in¯uenced the occurrence of no other species.

Sward height and standard deviation and grass in seed were strongly positively correlated (Table 3). Sward height and sward height standard deviation were each forced into all three MAMs in Table 5 (skylark, rook and starling) in place of grass in seed and were not signi®cant in any model (P>0.09 in all cases), thus con®rming an independent e ect of grass in seed for all three species.

Conversely, grass in seed was substituted in place of either sward height or sward height standard deviation in

Fig. 2. The e ect on probability of ®eld use by birds of increased bare earth (a) and (b); increased grass in seed (c); grazing (d). Species plotted are those which showed a signi®cant association with the variable and are currently of conservation concern within Britain or Europe.

Probability of ®eld use was derived by solving the equations of the MAMs for each species. The value of the plotted predictor was varied and substituted into the MAM equation whilst holding constant the values of other predictors. For continuous variables, these were set to the mean value of the 77 ®elds whilst factors were set to level 1 (e.g. not grazed; not next to stubble; farm 1), with the exception of boundary structure which was set to level 4, the most frequent boundary type of the 77 ®elds. Note that the intercept of a plot will vary according to the values at which the variables held constant in the MAM are set, dependant on the species relationship with these variables, but the gradient of the slope (change in probability of ®eld use with change in value of test variable) will remain the same.

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289

Table 7 Field habitat characteristics of the four ®eld management categories; grass ley, grass-clover ley, permanent pasture and rough grassa

Sward height in spring (cm)b Sward height standard dev. (spring)b Sward height in autumn (cm)b Sward height standard dev.(autumn)b Sward densityb,e Sward density standard deviationb,e Bare earth (m2)b Field area (ha)b Grass in seedb,f Herb richness (# species)b Stubblec Buildingc Grazedc Animal feedc Field enclosured Farmd

w2

df

4.98 25.76 123.7 121.1 8.34 5.82 25.11 41.76 37.55 2.28

1 1 1 1 2 1 2 3 3 3

Cramer coe cient

0.237 0.306 0.094 0.143 0.270 0.520

P value

Grass ley

Grass-clover ley

Permanent pasture

Rough grass

*0.026 ***0.000 ***0.000 ***0.000 *0.015 *0.016 ***0.000 ***0.000 ***0.000 0.510 0.230 0.065 0.877 0.667 0.052 ***0.000

11.2 0.9 2.0 0.2 10.2 0.6 3.8 0.3 93.2 2.4 7.8 2.1 88.5 28.6 6.30 0.9 6.5 2.0 9.2 0.5

9.4 0.6 2.0 0.2 10.6 0.6 4.4 0.4 95.2 1.0 6.6 1.1 97.9 30.4 9.9 1.3 1.7 0.6 10.5 0.4

8.7 0.5 1.9 0.1 10.2 0.6 4.2 0.4 96.0 0.7 6.7 1.0 131.5 28.5 3.4 0.4 1.4 0.4 10.2 0.5

13.2 2.4 4.6 1.0 33.9 3.2 20.7 3.6 99.8 0.2 1.0 0.9 14.0 8.3 4.54 2.3 10.9 4.4 8.7 0.7

a Presented are: for categorical variables, Cramer coe cient values for the correlations between the variable in question and management category (4-level factor); for continuous variables, results of log-linear regression analysis of management category on each habitat variable. Mean values ( 1 standard error) are shown for the continuous variables. * P<0.05; **P<0.01; ***P<0.001. b Indicates continuous variable. c Indicates 2-level factor. d Indicates >2-level factor. e Units are based on the mean percentage of surface area covered by vegetation per quadrate. f Units are based on the mean percentage cover of seeding grasses per quadrat.

the MAMs concerned, and was signi®cant for blackbird (w2=5.94, d.f.=1, P<0.015; negative relationship) and yellowhammer (w2=5.041, d.f.=1, P<0.025; positive relationship). Consequently, for both of these species it was not possible to distinguish between the e ects of grass in seed and sward height.

3.3.3. Presence of livestock and animal feed Grazed ®elds were occupied signi®cantly more frequently than ungrazed ®elds by ®ve species; ®eldfare, jackdaw, rook, carrion crow and starling (Tables 5 and 6).

No species showed the reverse relationship. Sheep-grazed ®elds were used more frequently than cattle-grazed ®elds, but separating livestock type did not improve the model ®t. None of the 14 species showed signi®cant association with the presence of animal feed within ®elds.

3.3.4. Landscape variables Field boundary characteristics were the most important of the measured external in¯uences on ®eld use by birds.

Distributions of 10 of the 14 species were associated with ®eld enclosure (Tables 5 and 6). Post-hoc contrasting tests revealed associations with particular boundary types for two species. Magpie (w2=4.99, d.f.=1, P<0.026) and blackbird (w2=7.737, d.f.=1, P<0.006) both occupied `enclosed' ®elds (>50% of boundary comprising hedgerow/tree line) signi®cantly more frequently than `open' ®elds which were bounded predominantly

by ditches or fences (<50% of boundary comprising hedgerow/tree line).

Proximity of a ®eld to buildings was a strong predictor for some species. Woodpigeon, jackdaw, rook, cha nch and yellowhammer all showed signi®cantly more frequent occupation of ®elds next to buildings (Tables 5 and 6). Six species showed a signi®cant association with ®elds bordering stubbles, with three positive (magpie, jackdaw and carrion crow) and three negative (skylark, pied wagtail, and cha nch) relationships.

3.3.5. Field area As ®eld area increased, so did the frequency of encountering most species. This study could not di erentiate between increased frequency of occurrence because larger ®elds were actively selected and the increasing probability of occurrence on larger ®elds that would result if birds were distributed randomly. Only when ®eld area was not retained in a species' MAM could it be said that it was not important in ®eld selection by a species. This was the case for four species; pied wagtail, redwing, magpie, and cha nch. Only blackbirds showed an association with smaller ®elds (quadratic relationship).

Field area was signi®cantly correlated with sward density and sward density standard deviation (Table 3).

Hence, in cases in which ®eld area but not sward density or sward density standard deviation were included within MAMs, we replaced ®eld area with, respectively, sward

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density and sward density standard deviation. In the models for skylark (w2=8.96, d.f.=1, P<0.004) and carrion crow (w2=4.58, d.f.=1, P<0.03), sward density did have a signi®cant e ect when ®eld area was excluded from the MAM. In both species, ®eld occupancy increased as sward density decreased, which suggests that both variables were important in ®eld selection by these species.

3.4. Associations of ®eld habitat characteristics with management category Field management category was correlated with several habitat variables. Table 7 presents these correlations and the results of post-hoc tests carried out to determine whether individual ®eld management categories were associated with particular environmental characteristics.

Rough grass ®elds (de®ned by their signi®cantly taller swards) also had higher sward density and lower sward density standard deviation, or heterogeneity in density, than all other management categories. There was very little di erence in sward height between leys and permanent pastures, but leys had signi®cantly lower sward density than permanent pastures. Mean area of bare earth was signi®cantly greater in permanent pastures than in leys, whilst in rough grass ®elds it was signi®cantly smaller than in all other management categories. Grass-clover leys had the largest ®eld areas and permanent pastures were smaller than all other management categories. Rough grass had the most grass in seed and grass leys had signi®cantly more grass in seed than either mixed leys or permanent pasture. Management category and farm were strongly correlated, indicating that certain farms specialised in particular types of grassland management.

4. Discussion 4.1. Associations with sward structure Ten of the 14 bird species were associated with ®elds with more bare earth (7 in Table 5, 1 in Table 6, 2 dependent on swapping two correlated predictors). Only woodpigeon (a species which grazes on green plant material) showed the reverse relationship, and then only when farm was excluded from the modelling process.

Eight of the 10 species are primarily invertebrate-feeders, and all have an invertebrate component to the diet.

Areas of bare earth may provide, for smaller bird species in particular, opportunities to forage at the soil surface which may otherwise prove di cult in dense swards.

Swards are often wet with dew or frost during the winter and this may also act as a stimulus for birds to select open, less vegetated areas of ®elds. Studies of other farmland habitats have also shown that some species forage on areas of bare earth. Cracknell (1986) found

that several species, including blackbird, cha nch and yellowhammer, signi®cantly selected bare strips around the edges of arable ®elds as foraging sites. Jackdaw and carrion crow, which were both associated with ®elds with larger areas of bare earth, also forage predominantly at the soil surface (Waite, 1984). Wilson et al. (1996b) recorded preferential use of recently ploughed ®elds by several species and it is recognised that ®elds of bare fallow are a good source of seed and invertebrate food for a variety of species, particularly ®nches, buntings and skylarks (e.g. Buckingham et al., 1999). Wakeham-Dawson and Aebischer (1998) found that manipulations of arable-reversion grassland to physically opened-up swards resulted in greater use of ®elds by skylarks, presumably because the management provided better access to food resources (e.g. Odderskaer et al., 1997; Milsom et al., 1998).

In this study, there were varying responses to ®ner-scale measures of sward height. Taller swards were selected by some species (magpie and meadow pipit) and shorter swards by others (pied wagtail, blackbird, carrion crow and starling). There was some evidence of a response to sward density and heterogeneity in sward structure across the ®eld as measured by sward height standard deviation and sward density standard deviation. Overall, the clearest pattern is that species which forage by probing for soil-dwelling invertebrates (corvids, thrushes) require access to areas of bare earth that are provided by relatively large patches at the ®eld scale, as measured by bare earth, while it seems that mosaics of vegetation height at the between-®eld scale are likely to maximise the variety of bird species able to exploit agricultural grassland as a foraging habitat in winter.

4.2. Associations with grazing Five species occurred more frequently on grazed ®elds. None showed the reverse relationship. These results are consistent with those of previous studies that have examined di erences between the use of grazed and ungrazed grass by a wide range of farmland bird species (Waite, 1984; Tucker, 1992; Wilson et al., 1996b). Four species (jackdaw, rook, carrion crow and starling) occurred more frequently on sheep-grazed ®elds than on cattle-grazed ®elds. Fieldfare was the only species which showed the opposite trend, favouring cattle-grazed ®elds. All ®ve species feed on surface and soil-dwelling invertebrates, in particular earthworms and beetle larvae and adults (Waite, 1984; Wilson et al., 1996a). Grazing, especially by cattle, promotes the creation of structurally diverse, species-rich vegetation which can increase both invertebrate abundance and species diversity (e.g. Gibson et al., 1992; Ausden and Treweek, 1995). In addition, dung may make soil invertebrates more accessible by bringing them closer to the surface, and promoting their concentration in small

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291

areas, thus making foraging more e cient (Scullion and Ramshaw, 1987; Tucker, 1992). There may also be a more direct, short-term response to livestock grazing by foraging birds. Animals disturb the soil substrate through trampling and grazing and this may result in more activity near the surface by ground-dwelling invertebrates (Lack, 1992), thus providing birds with more productive foraging.

Disturbance of the soil surface and creation of bare earth patches by grazing activity may also bene®t seedeaters by bringing buried seeds to the surface which would not otherwise be accessible to them (Robinson, 1997). The cha nch, which is predominantly granivorous and ground-feeding outside the breeding season, showed a positive relationship with larger areas of bare earth.

Yellowhammers were frequently observed feeding on areas of bare earth although, perhaps because of the small numbers recorded, no signi®cant relationship was found between their distribution and ®elds that had more bare earth. Other seed-eating species observed using areas of bare earth but not seen in su cient enough numbers to analyse included ®nches such as linnet (Carduelis cannabina), gold®nch (C. carduelis) and lesser redpoll (C. ¯ammea).

recorded in hedgerows near to farmyards than in those further away.

Other landscape in¯uences on bird distributions included proximity to stubble ®elds and ®eld enclosure.

Three corvid species, magpie, jackdaw and carrion crow, were recorded more frequently in grass ®elds that were next to stubbles than in those not next to stubbles.

All three feed primarily on invertebrates but also take substantial quantities of grain (Cramp and Perrins, 1994; Wilson et al., 1996a), so their greater use of grass ®elds which were next to stubbles may re¯ect birds moving short distances to and from neighbouring grass and stubble ®elds to take advantage of invertebrate and grain resources respectively.

Field enclosure appeared to have in¯uenced the distributions of most species, although the nature of the relationships were not always clear. Blackbird and magpie both selected `enclosed' ®elds whose ®eld enclosure was predominantly hedgerow or woodland edge. Blackbirds tend to feed close to cover and feed extensively on berries of various shrubs found commonly within hedgerows (Wilson et al., 1996a). Tucker (1992) also found that blackbirds and other thrushes occurred more frequently in ®elds enclosed by hedgerows.

4.3. Associations with seeding grass

4.5. Conservation implications

Skylark, rook, starling and yellowhammer were positively associated with the abundance of seeding grass. All four species take grain during the winter months, whilst other grass seeds feature in the diet of skylark, starling and yellowhammer (Cramp and Perrins, 1994; Wilson et al., 1996a). Blackbird and magpie, which feed mainly on invertebrates, were negatively associated with the abundance of grass in seed. High availability of seeding grass is likely to be promoted by low intensity or intermittent grazing (Wakeham-Dawson et al., 1998), especially in late summer and autumn, after the ®nal cut of forage grasses, but before the end of the growing season. Fastgrowing species such as meadow grasses (Poa spp) are likely to set seed all year round.

To maximise the range of bird species able to exploit improved lowland agricultural grassland as a winter foraging habitat, some ®elds should be grazed to provide patches of bare earth and varying vegetation height between ®elds, coupled with the opportunity for some grasses (and broad-leaved species) to set seed and provide a food resource for granivorous species. Similar management recommendations were made by PaÈrt and SoÈderstroÈm (1999) in their breeding season study of associations between botanical diversity and breeding bird assemblages in pastures in Sweden. In winter, this combination of attributes is most likely to be achieved by low stocking densities, and the continuation of grazing through the autumn and winter on some ®elds. At low stocking densities, cattle are more likely to produce these conditions than sheep since cattle are more selective in the areas of vegetation they choose to graze which, together with their trampling, leads to uneven swards of patches of tall and short vegetation, interspersed with bare, disturbed areas (Ausden and Treweek, 1995). Mosaics of short-term leys and permanent pastures at the farm scale may also be bene®cial since long-term pastures are most likely to have patches of bare earth created by grazing stock, and will be richer in soil-dwelling invertebrates such as earthworms and coleopteran and dipteran larvae (e.g. Tucker, 1992) than regularly cultivated ®elds. In contrast, regularly re-seeded leys, if harvested as hay or silage, may have a higher abundance of seeding grasses, especially if the ®eld is not grazed after the last cut.

4.4. Associations with landscape variables Several landscape in¯uences on bird distributions were evident. Woodpigeon, jackdaw, rook, cha nch and yellowhammer were all recorded signi®cantly more frequently in ®elds which were next to buildings, although the e ect for rook and cha nch was confounded with that for bare earth. Grain and cattle feed found in farmyards would be an attractive source of food for all these species. Yellowhammers in particular are often associated with farmyards where cattle are fed during the winter (O'Connor and Shrubb, 1986), and Spencer (1982) found that many more small birds were

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Historically, the type of grassland management outlined above has declined as a consequence of the widespread improvement of lowland agricultural grassland since the 1950s. Summer stocking densities have increased, multiple-cut silage production has replaced late-cut hay, and an increasing proportion of grazing stock have been wintered inside buildings, especially on heavy soils where excessive loss of grass cover and soil structure by poaching can occur (Carter and Stans®eld, 1994). This has promoted shorter, more uniformly grazed swards during the summer months with fewer seeding grasses, and fewer ®elds in which winter grazing re-establishes heterogeneity in sward structure and creates patches of bare earth. In situations where extensi®cation of grazing management along the lines described above is not feasible, the arti®cial creation and maintenance of exposed soil surfaces by mechanical means may be an alternative approach to improving foraging opportunities for wintering bird species in pasture (e.g. Wakeham-Dawson and Aebischer, 1998).

The agricultural improvement of grassland and intensi®cation of its management is well known as the direct cause of decline of a wide range of ground-nesting bird species through the removal of suitable nest sites (e.g. Baines, 1989; O'Brien and Smith, 1992; Green, 1995). Its in¯uence on the population trends of species using agricultural grasslands simply as foraging habitats is less clear, although a notable exception is the well documented but complex relationship between grazing management, abundance and availability of tipulid larvae and carabid beetles, and chough (Pyrrhocorax pyrrhocorax) foraging behaviour (e.g. McCracken and Bignal, 1998). In the present study, 9 of the 14 species analysed (woodpigeon, skylark, meadow pipit, blackbird, ®eldfare, redwing, jackdaw, cha nch and yellowhammer) have been designated as Species of European Conservation Concern (SPECs) by virtue of recent population or range contractions, or a high proportion of their world population being concentrated in Europe (Tucker and Heath, 1994). At a more local level, skylark, blackbird and starling are considered of conservation concern because of UK population declines >25% in the last 25 years (>50% in the case of skylark), and redwing and ®eldfare because the UK holds >20% of the European non-breeding population (RSPB, 1996). A rapid range contraction and population decline of yellowhammers in recent years would also now add this species to the list (Crick et al., 1998).

Thrushes use grassland to forage for soil-dwelling invertebrates, especially later in the winter when supplies of hedgerow fruit have been depleted (Tucker, 1992). In this study, blackbirds and ®eldfares were found more frequently on grazed ®elds or others with short swards, and all three thrush species analysed were found more frequently on ®elds with larger areas of bare earth. For thrushes, therefore, ®elds managed as pastures with

some over-winter grazing to open up the sward and keep it short are likely to provide better foraging opportunities than ungrazed ®elds managed as shortterm leys. Starlings similarly selected short, grazed swards, although the primary cause of decline of this species both in the UK and elsewhere has probably been caused by the drainage, re-seeding and loss of pastures and the concomitant loss of breeding season supplies of tipulid larvae and earthworms as nestling foods in arable areas (e.g. Tiainen et al., 1989).

The two granivorous species of current conservation concern, skylark and yellowhammer, were found more frequently on ®elds that were richer in seeding grasses, and ®elds managed least intensively (`rough grass' management category) tended to have the most seeding grasses. Sixty years ago, Wild (1938) found that meadows and pastures were preferred foraging habitats for yellowhammers seeking food for nestlings, but Bradbury and Stoate (in press) found that such ®elds are now avoided.

Similarly, Wilson (in press) found that skylarks avoided intensively managed silage ®elds and pastures but selected organically managed silage meadows and grass-sown set-aside. It is therefore possible that grassland improvement may have contributed to the decline of these species by reducing food availability in the breeding season and over winter. This possibility is worthy of more detailed research investigation as a possible basis for restoring populations of granivorous species such as skylark, yellowhammer and corn bunting in pastoral farming areas. For example, do the drastic losses of yellowhammer and corn bunting from Ireland and Wales (Gibbons et al., 1993) re¯ect the absolute dependence of these species on grain and weed seed associated with tilled farmland, or could they recolonise if grass production was modi®ed to o er more standing seed?

Overall, the indirect e ects of changing grassland management on the abundance and accessibility of food for birds are in need of more detailed research as a potential contribution to reversing population declines and range contractions in areas dominated by intensive pastoral agriculture. This study has shown that intensively managed agricultural grasslands do vary in their use as winter foraging habitats by birds, and that this variation correlates strongly with di erences in grazing management and sward structure that are open to manipulation.

Acknowledgements We thank Helen Browning, Phil Douthwaite, Richard Green, Richard Manors, Pat and Daphne Saunders, David Sharpe, Adam Twine, Alastair Welford, The National Trust and the University of Oxford for access to land owned or managed by them. This work was

A.J. Perkins et al. / Biological Conservation 95 (2000) 279±294

also made possible by the great assistance in the ®eld of Deryk Shaw, SteÂphanie Clark, Darren Moorcroft and Karl Evans. Statistical advice was received from Dr Mario Cortina Borja and earlier drafts of the manuscript were improved by comments from Paul Donald. The work was supported by a research grant from the Biotechnology & Biological Sciences Research Council.

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