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A comparison of fishing activities between two coastal communities within a biosphere reserve in the Upper Gulf of California

Brad Erisman, Ismael Mascareñas‐Osorio, Catalina López‐Sagástegui, Marcia Moreno‐Báez, Victoria Jiménez‐Esquivel, Octavio Aburto‐Oropeza, This electronic reprint is provided by the author(s) to be consulted by fellow scientists. It is not to be used for any purpose other than private study, scholarship, or research. Further reproduction or distribution of this reprint is restricted by copyright laws. If in doubt about fair use of reprints for research purposes, the user should review the copyright notice contained in the original journal from which this electronic reprint was made.


Fisheries Research 164 (2015) 254–265

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Fisheries Research journal homepage: www.elsevier.com/locate/fishres

A comparison of fishing activities between two coastal communities within a biosphere reserve in the Upper Gulf of California b ˜ Brad Erisman a,∗ , Ismael Mascarenas-Osorio , Catalina López-Sagástegui c , d Marcia Moreno-Báez , Victoria Jiménez-Esquivel b , Octavio Aburto-Oropeza d a

University of Texas at Austin, Marine Science Institute, Port Aransas, TX 78373-1015, USA Centro para la Biodiversidad Marina y la Conservación A.C., La Paz, BCS 23090, México c UC MEXUS, University of California Riverside, CA 92521, USA d Marine Biology Research Division, Scripps Institution of Oceanography, University of California at San Diego, La Jolla, CA 92093-0202, USA b

a r t i c l e

i n f o

Article history: Received 31 July 2014 Received in revised form 19 December 2014 Accepted 20 December 2014 Handling Editor A.E. Punt Keywords: Small-scale fisheries Collaborative fisheries research Upper Gulf of California Colorado River Delta Marine protected areas

a b s t r a c t We engaged in collaborative research with two small-scale fishing communities inside the Upper Gulf of California Biosphere Reserve in Mexico, San Felipe (SF) and El Golfo de Santa Clara (GSC), to test how well the geographic heterogeneity of fishing activities within the reserve coincided with current regulations. We compared the two communities in terms of catch composition, fishing effort, ex-vessel prices and revenues, seasonal patterns in fishing activities in relation to the reproductive seasons of target species, and spatial patterns of fishing in relation to managed zones within the reserve. The top four species (Cynoscion othonopterus, Micropogonias megalops, Scomberomorus concolor, Litopenaeus stylirostris) in terms of relative effort, catch, and revenues were the same for both communities but overall fisheries production, effort, and revenues were higher in GSC than SF for these species. Fishing activities in GSC followed a predictable annual cycle that began with L. stylirostris and were followed sequentially by the harvesting of C. othonopterus, M. megalops, and S. concolor during their respective spawning seasons, which were associated with seasonal variations in ex-vessel prices. Conversely, catch and revenues in SF were more diversified, less dependent on those four species, less seasonal, and did not show seasonal variations in prices. Interactions between fisheries and managed zones also differed such that SF interacted mainly with the southwest portion of the vaquita (Phocoena sinus) refuge, whereas GSC fished over a larger area and interacted mainly with the northeast portion of the vaquita refuge and the no-take zone. Our results indicate the two communities differ markedly in their socio-economic dependence on fisheries, their spatio-temporal patterns of fishing, their use of and impacts on species, coastal ecosystems and managed areas, and how different regulations may affect livelihoods. Regional management and conservation efforts should account for these differences to ensure the protection of endangered species and to sustain ecosystem services that maintain livelihoods and healthy coastal ecosystems. This study provides further evidence of the ability of collaborative research between scientists and fishers to produce robust and fine-scale fisheries and biological information that improves the collective knowledge and management of small-scale fisheries within marine protected areas. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Commercial fisheries are essential to the livelihood, welfare, and food security of coastal communities, and more than 90% of the

∗ Corresponding author. Tel.: +1 361 749 6833; fax: +1 361 749 6777. E-mail addresses: berisman@utexas.edu (B. Erisman), ˜ ismael.mascarenas@gocmarineprogram.org (I. Mascarenas-Osorio), catalina@ucr.edu (C. López-Sagástegui), mmorenobaez@ucsd.edu (M. Moreno-Báez), victoria.jimenez@gocmarineprogram.org (V. Jiménez-Esquivel), maburto@ucsd.edu (O. Aburto-Oropeza). http://dx.doi.org/10.1016/j.fishres.2014.12.011 0165-7836/© 2014 Elsevier B.V. All rights reserved.

world’s fishers are employed in small-scale fisheries (Chuenpagdee et al., 2006; FAO, 2012; Teh and Sumaila, 2013). However, smallscale fisheries can be more difficult to manage than industrial (large-scale) fisheries, because they often lack sufficient or reliable data related to effort, catch, discard rates, the biology of target species, and other information necessary to assess stocks and set regulations (Johannes, 1998; Salas et al., 2007). Moreover, fisheries information is usually available only on coarse spatial and temporal scales that do not always correspond to the demographics or life history characteristics of fish stocks or the dynamics of smallscale fisheries that target them (Tzanatos et al., 2005; Erisman et al., 2011; Wilson et al., 2012). Understanding spatial and temporal


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Fig. 1. Map of the Upper Gulf of California and Colorado River Delta Biosphere Reserve, managed areas within the reserve, the locations of the coastal fishing communities of El Golfo de Santa Clara and San Felipe, and the location of the Biosphere Reserve within the Gulf of California (inset).

patterns of small-scale fisheries and how they align with fisheries and conservation regulations is particularly important for the management of marine protected areas. Such information is crucial to assess possible impacts of fishing on endangered or protected species, coastal ecosystems, and managed areas as well as to identify and mitigate socio-economic impacts of regulations on fishing communities (Gunderson et al., 2008; Abbott and Haynie, 2012; Erisman et al., 2012; Horta e Costa et al., 2013). Likewise, incorporating spatio-temporal interactions within and among ecosystem components and human activities into management decisions is an essential component of ecosystem-based fisheries management (Leslie and McLeod, 2007), which aims to simultaneously protect the structure and function of marine ecosystems and the services they provide to mankind (FAO, 2005). The Gulf of California is the most important fishing region in Mexico, as it contributes more than half of the country’s total annual fisheries production, and small-scale fisheries generate the majority of this production (Cisneros-Mata, 2010; Erisman et al., 2011). The Upper Gulf of California (Fig. 1) is arguably the most important region in Mexico in terms of small-scale fisheries production, where nearly 1000 small boats use gill nets to harvest blue shrimp (Litopenaeus stylirostris), Gulf corvina (Cynoscion othonopterus), bigeye croaker (Micropogonias megalops), Spanish mackerel (Scomberomorus concolor), and small volumes of other groups such as sharks, rays, crustaceans, and bivalves (Cudney and Turk, 1998; RodríguezQuiroz et al., 2010). Fishing activities in this region have long

interacted with the conservation of two endangered species of national and international concern: the vaquita porpoise (Phocoena sinus) and the totoaba (Totoaba macdonaldi) (Aragón-Noriega et al., 2010; Bobadilla et al., 2011; Ávila-Forcada et al., 2012). Consequently, the region has a storied history of management and conservation efforts that are now most visible through the implementation of the Upper Gulf of California and Colorado River Delta Biosphere Reserve, which includes a no-take zone in the estuary of the Colorado River to protect the spawning grounds of totoaba and Gulf corvina and another no-take zone that serves as a refuge for vaquita (Fig. 1). Successful management of small-scale fisheries in the Biosphere Reserve is hindered by a paucity of fisheries information and ongoing conflicts between fishing communities that operate inside the reserve and the region’s conservation agenda (Bobadilla et al., 2011). The coastal fishing communities of San Felipe, Baja California, and El Golfo de Santa Clara, Sonora, (henceforth referred to as “Santa Clara” and “San Felipe”) lie within the boundaries of the reserve, utilize the buffer zones within the reserve as their principal fishing grounds, and thus are effected greatly by strict regulations implemented within the reserve for conservation purposes (Bobadilla et al., 2011; Pérez Valencia et al., 2011; Ávila-Forcada et al., 2012). Small-scale fisheries are central socioeconomic components in both communities. However, they differ in terms of capacity and fisheries production. There are 457 boats in Santa Clara that collectively operate a total of 925 fishing permits for 20


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Table 1 Number of fishing trips monitored with GPS data loggers from February 2012 to October 2013 in San Felipe and Golfo de Santa Clara organized by community, species, and year. Community

C. othonopterus (Gulf corvina)

M. megalops (Bigeye croaker)

S. concolor (Spanish mackerel)

L. stylirostris (Blue shrimp)

2012

2013

2012

2013

2012

2013

2012

2013

GSC SF

50 22

86 –

198 265

5 79

55 40

– 31

611 63

197 16

1202 485

Total

72

86

463

84

95

31

674

213

1687

fisheries, and San Felipe has a fleet of 204 boats with 547 fishing permits covering 27 fisheries. Only about 15% of the workforce in San Felipe is involved in primary production (i.e. fishing), whereas 50% to 80% of the people in Santa Clara actively fish seasonally or year round (Ávila-Forcada et al., 2012; Vázquez León et al., 2012). The tourism industry supports 64% of San Felipe’s workforce compared to only 30% in Santa Clara. Fisheries regulations in the Upper Gulf primarily focus on limiting the total capture on commercial species and the restriction of fishing inside specific zones, seasonal restrictions, or gear restrictions (Bobadilla et al., 2011; Pérez Valencia et al., 2011) but do not consider the possibility that communities may differ markedly in their fishing activities with respect to catch composition, spatio-temporal patterns in effort, catch, and revenues, and the overall contribution of fisheries production. Investigations of potential variations among communities are warranted, since they may coincide with differential effects on marine fish populations, ecosystems, and managed areas, or how regulations impact fishing activities and production. Moreover, adjusting management regulations to account for spatio-temporal heterogeneity among communities would match current support by scientists, nongovernment agencies, and government agencies for the adoption of ecosystem-based fisheries management approaches for marine protected areas in the region (OECD, 2006; Cudney-Bueno and Basurto, 2009; Ezcurra et al., 2009). The goal of this research was to test the hypothesis that small-scale fisheries in the Biosphere Reserve exhibit geographic heterogeneity at a finer scale than accounted by current management regulations. To accomplish this goal, we engaged in collaborative fisheries research with commercial fishers and stakeholders from Santa Clara and San Felipe to compare their fisheries in terms of catch composition, fishing effort, revenues, seasonal patterns in fishing activities and ex-vessel prices in relation to the reproductive seasons of target species, and spatial patterns of fishing in relation to managed zones within the Biosphere Reserve. Results of this study provide a baseline of fisheries information related to the Upper Gulf of California and the Biosphere Reserve, offer practical insights for the management of small-scale fisheries within marine protected areas, and demonstrate the benefits of collaborative fisheries research for the management of small-scale fisheries. 2. Materials and methods 2.1. Species composition of catch; annual effort, landings, and revenues We acquired commercial fisheries data from the Mexican National Commission for Fisheries and Aquaculture (CONAPESCA) in Mazatlan, México, for Santa Clara and San Felipe for the period January 2001 to December 2011. These data included 35,902 catch reports from Santa Clara and 31,861 catch reports from San Felipe. Data were organized into a fisheries database comprised of monthly records of landings (kg) and ex-vessel prices (pesos/kg) arranged by the common name of the species or species group (e.g. snappers, sharks) for all months and years. Ex-vessel revenues were

Total

calculated by multiplying landings by ex-vessel prices, and the resulting values in Mexican pesos were then converted to US dollars using published monetary exchange rates. Next, we calculated mean annual landings (tons) and revenues (USD) for each species by community using absolute and relative measures (%). Direct calculations of fishing effort or CPUE were not possible using the fisheries database, because commercial fishers are not required to submit detailed daily logs of fishing activities. Therefore, we calculated mean annual CPUE for each species by community from the fisheries database by dividing the mean annual landings by the number of fishing permits distributed. This methodology has its limitations, as illegal fishing, misreported catch, and unreported catch and effort are pervasive in Mexico (Cisneros-Montemayor et al., 2013). However, these represent the only available data on fisheries effort for the region. We also compared CPUE patterns (qualitatively) from the fisheries database with CPUE estimated from our collaborative research with fishers (see below) to determine whether the results were similar, and as a means of assessing the reliability of official fisheries statistics in this regard. A one-way ANOVA was used to test for significant differences in mean annual landings, ex-vessel prices, and ex-vessel revenues between the two communities for the four most important fisheries: L. stylirostris, C. othonopterus, M. megalops, and S. concolor. Where significant differences were found, post hoc multiple comparisons were performed using a Tukey test. We engaged in collaborative fisheries research with commercial fishers of Santa Clara and San Felipe from January 2012 through December 2013 to acquire fine-scale information on catch composition, revenues, and spatial patterns (see Section 2.3) of fishing for L. stylirostris, C. othonopterus, M. megalops, and S. concolor. Fishers recorded the landings (kg) for each species by trip. We also interviewed several fishers (n = 35 for Santa Clara; n = 31 for San Felipe) to estimate the average number of days each year they fished for each of these four fishes to obtain a semi-quantitative estimate of mean annual fishing effort by species. In Santa Clara, we obtained information for 1202 fishing trips (Table 1) from 74 different pangas and representing 14 cooperatives. In San Felipe, we obtained information for 485 fishing trips from 53 pangas, representing both fishing federations (i.e. organizations comprised of numerous fishing cooperatives) that operate in the community. Sampling was opportunistic, such that we worked with all fishers and fishing cooperatives willing to participate in the study. Considerable effort was made to engage and involve as many fishers as possible in both communities throughout the study to minimize sampling bias. Fisher participation was lower in 2013 due to conflicts between fishers, local NGOs, and management agencies that arose after several fisheries regulations were implemented in the region related to the Gulf corvina and shrimp fisheries. We used these data to calculate a second estimate of mean annual CPUE for each species by community by dividing landings per fishing trip by the number of fishing trips. 2.2. Reproductive seasonality We conducted biological surveys on a monthly basis at Santa Clara and San Felipe from January to December 2012 to determine


B. Erisman et al. / Fisheries Research 164 (2015) 254–265

the reproductive seasons of the three most common fishes captured by commercial fisheries in the region (C. othonopterus, n = 281 females; M. megalops, n = 253 females; S. concolor, n = 198 females). Fish were obtained opportunistically at either local fishing markets or directly from fishers upon their return from fishing trips. For each fish collected, we recorded information on total length to the nearest mm, total body weight to the nearest g, and gonad weight to the nearest 0.1 g. The sex and reproductive condition of each fish sampled was first determined by macroscopic inspections of gonads and later verified by microscopic evaluations of gonad tissue sections prepared using standard histological procedures (Erisman et al., 2012). Classification of gonadal development stages followed BrownPeterson et al. (2011). Emphasis was placed on identifying females in the actively spawning stage with ovaries containing batches of hydrated or ovulated oocytes to specify months in which spawning had occurred (Erisman et al., 2012). However, the monthly proportion of females with ovaries containing batches of oocytes in advanced stages of vitellogenesis (spawning capable) was also recorded to provide additional information on seasonal reproductive activity. The mean monthly gonadosomatic index (GSI) of females was calculated as follows: GSI = 100 × (gonad weight/total body weight). Mean monthly GSI of females was plotted to identify seasonal peaks that correspond with spawning activity. Monthly patterns in the percentage of actively spawning and spawning capable females were combined with GSI data to define the spawning season for each species. Our estimates of reproductive seasonality for each species were then compared to published and unpublished technical reports to corroborate our conclusions. 2.3. Seasonal patterns in effort, landings, revenues, and prices We compared the monthly patterns in catch for C. othonopterus, M. megalops, and S. concolor from the fisheries database with their reproductive seasons to estimate the contribution of the reproductive season to fisheries production in each community. First, catch reports (Santa Clara = 33,029 reports; San Felipe = 13,422 reports) for each species from each community were pooled by month and year. Next, we calculated mean monthly landings by species for each community to determine whether seasonal peaks in catch coincided with the reproductive season. We then estimated the relative importance of the reproductive season to fisheries for each of the four species by summing the landings recorded during months and dividing these values by the total annual landings (Erisman et al., 2010). We multiplied landings recorded during reproductive months by monthly ex-vessel prices to estimate ex-vessel revenues from reproductive seasons. A one-way ANOVA tested for significant differences in landings, ex-vessel prices, and ex-vessel revenues by community and by month separately for both communities. Where significant differences were found, post hoc multiple comparisons were performed using a Tukey test to identify peak months in catch, price, and revenue. We used the same method to test for differences between the communities with respect to the relative contribution of the reproductive season to total annual landings of each species. Spearman’s rank correlation was used to test for a relationship between monthly landings and ex-vessel price for each species within each community.

257

fishers as they departed the beach to embark on a fishing trip and were retrieved upon their return to shore. We implemented a simple protocol that minimized requirements for fishers to operate the data loggers to avoid disrupting their normal fishing activities and maximize incentives and willingness of fishers to use data loggers. Briefly, fishers were only requested to turn the loggers on and off at the beginning and end of fishing trips, respectively, and were not asked to mark any points during trips. Sampling was opportunistic, such that we worked with all fishers willing to participate, which usually included a large number of fishers representing a large fraction of the fishing cooperatives operating in both communities (see Section 2.1). We uploaded the data from each fishing trip to a computer and displayed it using GPSBabel (see http://www.gpsbabel.org) to ensure files with aberrant data were excluded from the analysis. GPS data were then transformed to ASCII code outputs, imported into a Geographic Information System (GIS) format using ArcGISTM 10.2 software. Spatial data from each fishing trip were analyzed to identify the fishing grounds using the object oriented model builder tools in ArcGISTM 10.2 and visual techniques. The fishing ground was represented as a point, identified as the centroid of a line that represented the spatial pattern of the deployment and retrieval of a net (i.e. the distance over which the net drifted between deployment and retrieval). Fine-scale patterns of movement and boat speed facilitated the identification of locations where nets were deployed and retrieved (Erisman et al., 2012). We validated our method on several occasions by working with fishers after fishing trips to confirm our estimations were consistent with their knowledge of where fishing occurred. We estimated the fishing area used by each community for each fishery by simultaneously plotting all marked points on a regional map and using the directional distribution tool in ArcGISTM 10.2 to create an elliptical polygon centered on the mean for all fishing observations. We utilized two standard deviations in order to cover a 95% confidence interval for each fishery, and we created a polygon around the outer boundaries using the aggregate points tool to calculate the area of the polygon for each fishery. We calculated the percentage of marked points located within these areas to estimate the general distribution of fishing grounds in relation to the two restricted zones within the Biosphere Reserve (the vaquita refuge and the no-take zone) for each fishery and each community. For each of the four fisheries within each community, we calculated the average distance traveled per boat trip as a simple metric for estimating fishing costs. All four fisheries use gill nets as the principal method of capture (Rodríguez-Quiroz et al., 2010), and three of these fisheries (those for M. megalops, S. concolor, L. stylirostris) capture their targets species by deploying gill nets and allowing them to soak and drift in strong currents for 30 min to several hours at a time. These nets vary considerably in length from 290 to 1485 m (RodríguezQuiroz et al., 2010; Erisman et al., 2012), and some nets may capture fish at locations up to 1–2 km away from the site of deployment. Consequently, these points provide only a general idea of where fishing activities occur and should not be used to calculate exact locations of fishing or capture in relation to restricted zones (see Section 4).

3. Results 2.4. Spatial patterns of fishing activities Fishing areas for L. stylirostris, C. othonopterus, M. megalops, and S. concolor were identified for both communities using GPS data loggers (AMOD AGL 3080) that use a Global Positioning System (GPS) to record a boat’s position at regular intervals of 1–30 s depending on the fishery (Erisman et al., 2012). Data loggers were given to

3.1. Species composition of catch; annual patterns of effort, landings, and revenues Mean total landings and revenues were higher in Santa Clara than San Felipe (Table 2). Fisheries in Santa Clara recorded landings for 20 species, with four species representing more than 90%


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Table 2 Catch composition of small-scale fisheries from El Golfo de Santa Clara (GSC) and San Felipe (SF) from 2001 to 2011 organized by species, landings, and ex vessel revenues. GSC

SF

Species

Mean Mean annual Mean annual landings (tons) annual revenue (USD) landings (%)

pcMean Species annual revenue (%)

Gulf corvina Bigeye croaker Spanish mackerel Blue shrimp Other shrimp Smoothhound sharks Rays Clams Guitarfishes Crabs Other sharks Other corvinas Mullets Flounders Mojarras King croaker Gulf coney Angel shark Triggerfish Snappers Total

2566.2 1249.8 1129.8 501.2 47.8 28.2 24.6 24.6 19.4 15.1 11 10.7 10 2.2 2.1 0.7 0.2 0.2 0.1 0.01 5643.91

21.1 8.6 11.1 53.4 3.7 0.4 0.8 0.2 0.1 0.1 0.1 0.05 0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05 <0.05

44.5 21.7 19.6 8.8 0.8 0.5 0.4 0.4 0.3 0.2 0.2 0.1 0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1

2,189,047 889,329 1,157,461 5,553,193 381,974 44,615 83,292 17,956 20,254 18,925 15,780 6215 9096 4141 1088 1484 524 217 54 27 10,394,672

Mean annual landings (tons)

Bigeye croaker 1055.1 Spanish mackerel 687.3 Blue shrimp 437.1 Gulf corvina 195 Geoduck 174.7 Rays 145.9 Guitarfishes 105.4 Crabs 87.4 Angel shark 85.4 Other sharks 69.1 Other shrimp 45.4 Flounders 42.3 Gulf coney 31.8 Ballusa 26.5 Smoothhound sharks 12.4 Goldspotted bass 12.3 Groupers 6.7 Triggerfish 5.9 Mullets 5.4 Snails 4.3 Pampano 3.9 3.7 Other corvinas 3.3 Octopus 2.4 Mojarras Gulf scallop 1.3 1.2 Snappers White seabass 0.9 0.7 Jacks 0.05 Huachinango Total 3252.85

Mean Mean annual annual revenue (USD) landings (%) 32.4 21.1 13.4 6 5.4 4.5 3.2 2.7 2.6 2.1 1.4 1.3 1 0.8 0.4 0.4 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 <0.1 <0.1 <0.1 <0.1 <0.1

670,055 711,346 4,153,042 170,290 304,386 144,240 100,930 76,511 109,543 96,116 308,139 73,927 115,578 13,081 17,096 14,005 8430 5050 3471 1210 1927 7822 9334 1240 4884 1770 2643 602 89 7,126,757

Mean annual revenue (%) 9.4 10 58.3 2.4 4.3 2 1.4 1.1 1.5 1.3 4.3 1 1.6 0.2 0.2 0.2 0.1 0.1 <0.1 <0.1 <0.1 0.1 0.1 <0.1 0.1 <0.1 <0.1 <0.1 <0.1

Source: CONAPESCA Mazatlan, Mexico. Dotted line indicates 90% of total commercial landings and ex-vessel revenues.

of total landings. Conversely, San Felipe recorded landings of 29 species, and nine species represented more than 90% of total landings. In both communities, four species (blue shrimp, Gulf corvina, bigeye croaker, and Spanish mackerel) ranked highest with respect to annual landings and revenues, but their relative importance to overall fisheries production differed between Santa Clara and San Felipe. Blue shrimp was the most important fishery resource in terms of revenue in both communities, and it ranked 4th in Santa Clara and 3rd in San Felipe in terms of mean annual landings. In Santa Clara, the Gulf corvina, Spanish mackerel, and bigeye croaker comprised an average of 94.6% of total landings and 94.2% of exvessel revenues. The relative contribution of these fisheries was lower in San Felipe, representing an average 72.9% of total commercial landings and 80.1% of ex vessel revenues. Mean Annual landings and ex-vessel revenues for Gulf corvina in Santa Clara were

approximately 13 times greater than those in San Felipe (Table 2). The same pattern was found for Spanish mackerel, for which revenues were nearly 40% higher in Santa Clara than in San Felipe. In contrast, landings and revenues for L. stylirostris and M. megalops were similar between the two communities. Overall, fishing effort was comparable for both communities: Santa Clara issued more fishing permits but was similar to San Felipe in terms of the number of trips per boat per year for the four fisheries (Table 3). In both communities, effort was highest for blue shrimp (L. stylirostris) with more than 100 trips per boat per season, followed by bigeye croaker (M. megalops), Spanish mackerel (S. concolor), and Gulf corvina (C. othonopterus). The relative CPUE for each of the four fisheries calculated from the fisheries database and the CPUE calculated from our GPS trackers program were comparable for Santa Clara and San Felipe, such that CPUE was highest

Table 3 Comparison of annual values in effort, landings, catch-per unit effort, distance traveled by fishers, and ex-vessel revenues of the four most important small-scale fisheries data in El Golfo de Santa Clara (GSC) and San Felipe (SF) from the official fisheries database (2001–2011. Community

Species

CONAPESCA data No. Permits

Mean annual landings (tons)

GPS data Mean annual revenue (USD)

Mean CPUE (tons/permits/year)

Mean effort (trips/season/boat)

Mean Distance (km)

Mean CPUE (kg/trip)

GSC

C. othonopterus (Gulf corvina) M. megalops (Bigeye croaker) S. concolor (spanish mackerel) L. stylirostris (Blue shrimp)

405 405 405 423

2566.2 1249.8 1129.8 501.2

2,189,047 889,329 1,157,461 5,553,193

6.33 3.08 2.78 1.1

23 45 30 100

90.8 91.5 97.7 99.6

749.26 300.67 275.33 27.35

SF

C. othonopterus (Gulf corvina) M. megalops (Bigeye croaker) S. concolor (spanish mackerel) L. stylirostris (Blue shrimp)

239 239 239 220

195.0 1055.1 687.3 437.1

170,290 670,055 711,346 4,153,042

0.81 3 2.8 1.9

30 50 40 110

70.6 67.2 72.3 71.9

437.83 328.94 254.81 24.09

Source: CONAPESCA Mazatlan, Mexico) and our GPS trackers program (this study; February 2012 – October 2013).


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Fig. 3. Spawning seasons of Gulf corvina (Cynoscion othonopterus; top), bigeye croaker (Micropogonias megalops; middle), and Spanish mackerel (Scomberomorus concolor; bottom) in the Upper Gulf of California from changes in the monthly percentage of spawning capable females (%SC) and actively spawning females (%AS), and the mean gonadosomatic index (%GSI) of adult females. Lines represent 95% confidence intervals.

3.2. Reproductive seasonality

Fig. 2. Annual trends in landings for the four most important fisheries in El Golfo de Santa Clara (solid line) and San Felipe (dashed line) from 2001 to 2011. Source: CONAPESCA Mazatlan, Mexico.

for Gulf corvina and followed by bigeye croaker, Spanish mackerel, and blue shrimp (Table 3). CPUE for blue shrimp, bigeye croaker, and Spanish mackerel were similar in Santa Clara and San Felipe, but the CPUE for Gulf corvina was 781% and 171% higher for the fisheries database and the GPS trackers program collectively, in Santa Clara Santa. Variation in annual landings of blue shrimp in both communities were not significant (F264,1 = 0.64, p > 0.05). Annual landings of Gulf corvina were relatively constant in Santa Clara over the entire time period but were higher in San Felipe during the period of 2008–2011 than the period of 2001–2007 (F132,1 = 34.5, p < 0.0001). Since 2007, mean annual landings of bigeye croaker (F132,1 = 11.8, p < 0.001) and Spanish mackerel (F132,1 = 7.05, p < 0.01) in Santa Clara were significantly higher during the period of 2008–2011 than during the period of 2001–2007. Annual landings for bigeye croaker (F132,1 = 8.9, p < 0.01) and Spanish mackerel (F132,1 = 60.3, p < 0.0001) in San Felipe were also higher after 2007 than before (Fig. 2).

While all three fish species were best categorized as spring spawners, the onset and duration of the reproductive season differed among Gulf corvina, bigeye croaker, and Spanish mackerel (Fig. 3). Female Gulf corvina classified as spawning capable, with ovaries in advanced stages of vitellogenesis were collected from late February through September. Mean female GSI in Gulf corvina increased from February through April and then steadily declined from May through September. Female corvina classified as actively spawning, with clear macroscopic and microscopic evidence of imminent spawning (via hydrated or ovulated oocytes within ovaries), were collected from February to September. These data suggested that Gulf corvina reproduce from late February through early June, with a peak in activity during March and April. Bigeye croaker females in the spawning capable phase were collected from February through early November, during which time GSI levels were elevated above basal levels. However, actively spawning female croaker were only collected from March through July. These patterns indicated a protracted reproductive season for bigeye croaker starting in March and running through early October, with a peak in spawning activity from March through July. Female Spanish mackerel in the Spawning Capable phase were collected from April through October, and mean female GSI peaked from April through June. Actively Spawning female mackerel were collected from April through July. Collectively, these results indicated that reproductive season for Spanish mackerel began in April, peaked from April through July, and ceased by September.


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Fig. 4. Mean monthly landings (bars) and ex-vessel prices (lines) of the four most important species from El Golfo de Santa Clara (right column) and San Felipe (left column) from 2001 to 2011 in relation to their spawning season (hatched box). Source: CONAPESCA Mazatlan, Mexico. Dark gray bars indicate months of peak landings identified by Tukey post hoc tests. Lines indicate 95% confidence intervals.

3.3. Seasonal interactions between fishing and spawning Seasonal interactions between fishing activities and the reproductive seasons of three of the four main target species differed between Santa Clara and San Felipe (Fig. 4). In both communities, peaks in landings and revenues for blue shrimp were not associated with the reproductive season since fishing is closed during that period. Fishing in Santa Clara began each year with the blue shrimp season from September through March, and showed a peak in landings (F11,132 = 19.1, p < 0.0001) and revenues (F11,132 = 16.4, p < 0.0001) during October and November. The shrimp season was followed sequentially by fishing seasons for Gulf corvina, bigeye croaker, and Spanish mackerel in coincidence with their respective reproductive seasons (Fig. 4). Monthly landings and revenues for Gulf corvina in Santa Clara were significantly higher during March and April than other months (landings: F11,132 = 45.9, p < 0.0001; revenues: F11,132 = 41.1, p < 0.0001). Both landings and revenues for bigeye croaker in Santa Clara were highest in April and May (landings: F11,132 = 10.2, p < 0.0001; revenues: F11,132 = 3.9, p < 0.0001). Spanish mackerel revenues and landings peaked in May and June in Santa Clara (landings: F11,132 = 15.8, p < 0.0001; revenues: F11,132 = 12.4, p < 0.0001). Seasonal patterns of fishing looked different in San Felipe (Fig. 4). Similar to Santa Clara, fishing in San Felipe for blue shrimp season took place after the closed spawning season: from September through March with peaks in landings (F11,132 = 37.1, p < 0.0001) and revenues (F11,132 = 39.4, p < 0.0001) during October and November. However, landings and revenues for Gulf corvina

showed no strong seasonal pattern and were relatively consistent across all months of the year. Both landings (F11,132 = 9.9, p < 0.0001) and revenues (F11,132 = 6.1, p < 0.0001) for bigeye croaker in San Felipe were highest at the start of their spawning season in April and May. Spanish mackerel were harvested steadily throughout the year in San Felipe but showed a small yet significant peak in landings (F11,132 = 3.2, p < 0.001) and revenues (F11,132 = 2.9, p < 0.01) during the peak reproductive month of May. Overall, the contribution of the reproductive season to total landings and revenues was significantly higher for all three species of fish in Santa Clara than for San Felipe (Table 4), comprising 94–99% of total annual landings and revenues in Santa Clara compared to 48–92% in San Felipe (Table 5). In Santa Clara, Gulf corvina and Spanish mackerel were harvested in large volumes exclusively during their spawning season, whereas San Felipe harvested these species consistently, but in lower monthly volumes, throughout the year. Both communities targeted bigeye croaker during their peak spawning season in April and May. Seasonal and overall patterns in ex-vessel prices for all four species also differed between Santa Clara and San Felipe. Mean ex-vessel price for Gulf corvina was slightly higher in San Felipe ($0.88 kg−1 ) than Santa Clara ($0.71 kg−1 ) (F212,214 = 18.86, p < 0.01). Prices for corvina did not vary significantly by month in San Felipe (F117,112 = 1.4, p = 0.17), but did vary by month in Santa Clara (F85,73 = 2.9, p < 0.01), such that prices were highest in February and March at the start of the spawning season and declined steadily afterwards. There was a positive relationship between landings and price of Gulf corvina in Santa Clara (rs = 0.58; p = 0.04). Mean


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261

Table 4 Summary of the contribution of the spawning season of the three most commercially important fish species in the Upper Gulf of California to landings (tons) and ex-vessel revenues in El Golfo de Santa Clara (GSC) and San Felipe (SF) from 2001 to 2011. Community

Species

References

Spawning season

Avg annual landings from aggregations (tons)

% of annual landings from aggregations

C. othonopterus (Gulf corvina)

Erisman et al. (2012); this study Román-Rodríguez (2000); Castro-González (2004); this study Valdovinos-Jacobo (2006); this study

Feb–Jun

2546.9

99.2

2,178,466

99.5

Mar–Oct

1190.9

95.2

845,469

95.1

Apr–Sep

1066.7

94.4

1,095,301

94.6

Feb–Jun

94.3

48.3

82,535

48.5

Mar–Oct

953.2

90.3

616,082

91.9

Apr–Sep

354.6

51.5

358,743

50.4

GSC M. megalops (Bigeye croaker)

S. concolor (spanish mackerel) C. othonopterus (Gulf corvina) SF M. megalops (Bigeye croaker)

S. concolor (spanish mackerel)

Erisman et al. (2012); this study Román-Rodríguez (2000); Castro-González (2004); this study Valdovinos-Jacobo (2006); this study

Avg annual revenue from aggregations (USD)

% of annual revenue from aggregations

Source: CONAPESCA Mazatlan, Mexico. Table 5 Results of a 1-way ANOVA comparing the percent contribution of the spawning season to annual landings and ex-vessel revenues for the three most commercially important fish species in El Golfo de Santa Clara and San Felipe during the period of 2001 to 2011. All pairwise comparisons were significant and indicated a higher contribution of the spawning season to fisheries in El Golfo de Santa Clara. Scientific name

Effects

F

p-value

C. othonopterus (Gulf corvina)

% Landings % Revenues

78.06 88.1

<0.0001 <0.0001

M. megalops (Bigeyecroaker)

% Landings % Revenues

11.83 13.61

0.002 <0.001

S. concolor (Spanish mackerel)

% Landings % Revenues

30.35 30.94

<0.0001 <0.0001

ex-vessel price for blue shrimp was higher in Santa Clara ($12.07 kg−1 ) than San Felipe ($10.60 kg−1 ) (F153,151 = 12.9, p < 0.01). In both Santa Clara (F76,69 = 4.81, p < 0.01) and San Felipe (F77,70 = 6.85, p < 0.01), monthly ex-vessel prices were lowest at the start of the fishing season in September and increased to peak at the end of the season in February and March. Mean ex-vessel price for bigeye croaker was similar in Santa Clara ($0.57 kg−1 ) and San Felipe ($0.52 kg−1 ) and did not vary significantly by month in either community. Mean ex-vessel price for Spanish mackerel was also similar in Santa Clara ($0.93 kg−1 ) and San Felipe ($0.90 kg−1 ), was relatively consistent in San Felipe throughout the year, but varied significantly in Santa Clara (F100,88 = 2.7, p < 0.01), such that prices were elevated during the spawning season and showed a positive relationship with landings (rs = 0.03; p = 0.03). 3.4. Spatial patterns of fishing We found noticeable differences in spatial patterns of fishing between Santa Clara and San Felipe with respect to the total area fished, the average distance traveled, and the use of the Biosphere Reserve (Fig. 5). Fishers from Santa Clara used an area of 2307.8 km2 for blue shrimp; 1291.1 km2 for Gulf corvina; 1452.4 km2 for bigeye croaker; and 1809.7 km2 for Spanish mackerel. Fishing activities from Santa Clara occurred primarily in the northeast portion of the Biosphere Reserve, with fishing taking place in the buffer zone, the no-take zone, and the vaquita refuge. Fishing grounds for blue shrimp, bigeye croaker and Spanish mackerel were located between the northeast boundary of the vaquita refuge and the coastline of Sonora, reaching the boundaries of the no-take zone

to the north and the buffer zone to the south (Fig. 5a, c and d). However, Gulf corvina were fished from the northeast boundary of the vaquita refuge to the coastline and within the no-take zone of the estuary, inside the two channels surrounding Montague Island (Fig. 5b). For all four species, the average distance fishers from Santa Clara traveled during a fishing trip was greater than fishers from San Felipe (Table 3). Fishing areas were must smaller for San Felipe compared to Santa Clara fishers for all species except bigeye croaker, such that San Felipe fishers covered an area of 597.9 km2 for blue shrimp; 938 km2 for Gulf corvina; 1682.4 km2 for bigeye croaker; and 1094.8 km2 for Spanish mackerel (Fig. 5a–h). In contrast with Santa Clara, fishers from San Felipe focused their effort primarily along the southwestern portion of the Biosphere Reserve and to the south along the coast of Baja California. Their most important fishing areas were located adjacent to San Felipe, in the corridor between the Baja California coastline and the western boundary of the vaquita refuge. Fishing activities of both communities interacted partially with the vaquita refuge and the no-take zone. For Santa Clara, the percentages of observations that occurred inside the no-take zone were low for Spanish mackerel (1.5%), blue shrimp (3.4%) and bigeye croaker (2.9%). However, for Gulf corvina this percentage was considerably higher (61.1%). The percentage of fishing points by fishers of Santa Clara inside the vaquita refuge was highest for the Spanish mackerel fishery (15.5%), followed by blue shrimp (11.9%), bigeye croaker (3.2%) and Gulf corvina (0.4%). For San Felipe, the percentages recorded inside the vaquita refuge were higher (Gulf corvina = 39%; blue shrimp = 30.3%; bigeye croaker = 16.5% and Spanish mackerel = 5.7%) when compared to the no-take zone (Gulf corvina = 2.8%; bigeye croaker = 0.07%; blue shrimp and Spanish mackerel = not registered).

4. Discussion Collectively, our results show that blue shrimp, Gulf corvina, bigeye croaker, and Spanish mackerel represent the most important fisheries in terms of production and revenue for both Santa Clara and San Felipe within the Biosphere Reserve in the Upper Gulf of California. Similar findings were reported in previous studies that examined small-scale fisheries in this region (Cudney and Turk, 1998; Aragón-Noriega et al., 2010; Rodríguez-Quiroz et al., 2010). Likewise, our results support previous technical reports


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that the Biosphere Reserve encompasses the breeding grounds for the most important commercial fish species in the Upper Gulf of California (Arvizu-Martínez, 1987; Román-Rodríguez, 2000; Castro-González, 2004; Valdovinos-Jacobo, 2006; Aragón-Noriega, 2007). However, by engaging in collaborative fisheries research with commercial fishers to collect novel, fine-scale spatial and temporal data on effort, catch, revenues, the location of fishing activities, and the timing of reproduction in these four species, we have identified important differences between the fisheries of Santa Clara and San Felipe that have direct, meaningful implications for the management of small-scale fisheries inside and adjacent to the Biosphere Reserve. Small-scale fisheries in Santa Clara are best characterized by sequential changes in catch composition that coincide with seasonal regulations (shrimp) and seasonal reproductive migrations of target species into the nearby area, which in turn, drive fluctuations in market demands and ex-vessel prices. The fishing cycle starts with the opening of the shrimp fishing season in September, and nearly all fishers focus their efforts on this species until it closes the following March due to the high prices this fishery provides to fishers. The end of the shrimp season marks the start of the massive spring spawning migration of the Gulf corvina, which coincides with a high domestic demand for fish in Mexico during Easter (Erisman et al., 2012), and an initial increase in ex-vessel

prices. However, after Easter the supply of corvina greatly exceeds demand (i.e. a market glut), and prices drop abruptly. Fishing activities for Gulf corvina are quickly replaced by the targeted harvesting of bigeye croaker that start to form spawning aggregations in April and the Spanish mackerel aggregations that start to form in May. Fishing effort for croaker and mackerel decrease during the summer months as the availability of these species declines, and the landings become more diversified with low volumes of other bony fishes, sharks, rays, and sea jellies until the cycle start again with the onset of the next season for blue shrimp in the Fall. This seasonal fishing cycle is critical to the economic livelihood of Santa Clara, as it supports a large fleet of 457 boats that incorporate up to 80% of the available workforce of the community (Ávila-Forcada et al., 2012; Vázquez León et al., 2012). In contrast, the small-scale fisheries of San Felipe tend to be less seasonal and less dependent on the reproductive periods of fishes. Fisheries are also more diversified in terms of catch composition, such that they tend to catch lower volumes per species but across a wider range of species, and many species are caught year round. Related to this, market demands and ex-vessel prices remain relatively constant throughout the year. The fishing sector employs a much smaller proportion of the workforce in San Felipe, where the tourism industry offers a viable alternative source of employment (Ávila-Forcada et al., 2012; Vázquez León et al., 2012).

Fig. 5. Fishing zones of the most important species to small-scale fisheries in El Golfo de Santa Clara (a–d) and San Felipe (e–h) from 2012 to 2013. (a and b) L. stylirostris; (c and d) C. othonopterus; (e and f) M. megalops; (g and h) S. concolor.


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263

Fig. 5. (Continued)

Consequently, the fishing fleet is smaller than Santa Clara, and total fisheries production and revenues are lower. Fishers from Santa Clara and San Felipe also show differences in their spatial patterns of fishing, such that fishing activities occur in close proximity to their respective communities but differ in the size of the area that is fished and the average distance traveled. The large fishing fleet from Santa Clara fishes over a large expanse and operates mainly in the areas between the north and northeast boundaries of vaquita refuge and the coastline of Sonora, including the two channels surrounding Montague Island. The large size of the fishing fleet in Santa Clara, all of which utilize gill nets, means that fishers tend to travel farther to avoid net entanglements. In contrast, the smaller fleet from San Felipe focus their activities further southwest, in a small area in the corridor between Baja California coastline and western boundary of vaquita refuge, and along the northern boundary of no-take zone and well to the south beyond the boundary of the reserve. For San Felipe, fishing grounds for three of the top four species (Gulf corvina, blue shrimp and bigeye croaker) overlap with the vaquita refuge. Santa Clara shows only a weak interaction with the vaquita refuge for Spanish mackerel and blue shrimp, but a strong interaction with the no-take zone for the Gulf corvina fishery. The smaller size of the fishing fleet in San Felipe and the large distance of the community from Santa Clara mean that fishers do not have to travel as far to avoid entanglement with nets of other fishers.

Differences in catch composition between Santa Clara and San Felipe, including the diversity of catch and the relative volumes landed per species reflect differences in the spatial patterns of their fishing activities and the coastal habitats that occur adjacent to each community. Similar to most small-scale fishers in the Gulf of California, fishers here use small boats (pangas) to fish the coastal habitats adjacent to their community (Erisman et al., 2011; Moreno-Báez et al., 2012). Whereas the nearshore habitats off Santa Clara are primarily sandy or mud bottoms, San Felipe also houses rocky reefs along the coastline and nearby islands, which tend to hold a higher diversity of fishes due to increased habitat complexity (Hastings and Findley, 2010; Robago Quiroz et al., 2011). Also, Santa Clara’s proximity to the Colorado Delta where several species such as shrimp reproduce and several species of sciaenid fishes (e.g. Gulf corvina, bigeye croaker) form spawning aggregations has made this community an important commercial fishing port (Flanagan and Hendrickson, 1976; Pérez Valencia et al., 2011). These clear differences in size, use and location of the fishing grounds are strongly related with the seasonal distributions of species (AragónNoriega et al., 2010; Erisman et al., 2012) and the distance of fishing grounds from the community. Both factors have an important effect on the total costs and the total revenues for the fleet (AragónNoriega et al., 2010). In this case, the longer average distance traveled by fishers from Santa Clara should equate to higher fishing costs.


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A previous study by Rodríguez-Quiroz et al. (2010) used fisher interviews to construct maps that described the size and location of fishing grounds in relation to various areas and habitats within the Biosphere Reserve, and they estimated that nearly 77% of the no-take zone and the 100% vaquita refuge were heavily fished. Conversely, by working directly with fishers from Santa Clara and San Felipe to deploy GPS data loggers on hundreds of fishing trips, we produced the first fine-scale map showing the spatial distribution of fishing activities in this region. Using this approach, we found that the fishing activities inside the two restricted areas were much lower for Santa Clara and San Felipe in comparison with the results of the previous study. Differences in the results of these two studies likely reflect the methodologies applied to generate maps of fishing activities and their associated biases. Methodologies that utilize qualitative methods such as interviews, printed maps to localize delineate or estimate fishing grounds to provide coarse approximations of the use of different areas, including protected areas in constant conflict (between fisheries and conservation strategies), can potentially lead to the overestimation of size, use and interactions between fishing and no-take zones, due to the “selective memory retention” or the decline of the reliability of fishers memories over time (Close and Hall, 2006; Moreno-Báez et al., 2010; Taylor et al., 2011). Conversely, the use of GPS data loggers provides spatial data that are more reasonable for estimating interactions and use between fishing, coastal ecosystems, and managed areas and identifying differences in fishing activities among communities. However, this methodology also has its limitations, which requires GPS data be used properly and responsibly when extrapolating information for management purposes. In this case, it is important to note that gill nets used by fishers in the Upper Gulf vary in length, soak times, and spatial orientation depending on the target species and the strength of surface currents at time of deployment. Also, the locations of gear deployment and retrieval do not specifically reflect the exact locations where fish were captured. Finally, fishers traveling with GPS data loggers may preferentially avoid protected areas out of concern for penalties (Erisman et al., 2012). Despite these limitations, it is clear the two communities differ in their interactions with managed areas of the Biosphere Reserve, critical habitats for endangered and protected species, and reproductive periods of commercially important species. These differences are important to consider within the context of the management of regional fisheries and the reserve, particularly within the framework of Ecosystem Based Management. For example, San Felipe has a stronger interaction with the vaquita refuge due to its close proximity and because that area historically represented one of the most productive and important fishing grounds for shrimp by fishers from that community (Moreno-Báez et al., 2010, 2012). Therefore, the survival and recovery of the vaquita is likely to be more impacted by fishing activities from San Felipe, and enforcement and monitoring should be focused accordingly. Similarly, fishers from Santa Clara have a much stronger interaction with the no-take zone, which lies adjacent to the community and was associated with the most productive fishing grounds for blue shrimp and Gulf corvina prior to the establishment and enforcement of the reserve. Given that the no-take zone represents the critical breeding habitat for blue shrimp and Gulf corvina, the monitoring and enforcement of the no-take zone should necessarily focus more on Santa Clara to protect the reproductive activity of both species and maintain a level of reproductive output necessary to maintain the fisheries. The successful management of the vaquita refuge and the no-take zone will also require government agencies to properly account for the losses in fishing revenues incurred to each community as a consequence of losing their most productive fishing grounds when devising strategies to incentivize compliance with reserve restrictions and reduce illegal fishing activities inside their boundaries.

The synchronization between fishing activities in Santa Clara and the timing and locations of the seasonal spawning aggregations of Gulf corvina, bigeye croaker, and Spanish mackerel should be a focal point for managing fisheries in this community. Countless studies have demonstrated that intense fishing pressure on spawning aggregations, which are predictable in time and space are highly vulnerable to overfishing, and can result in rapid declines (or collapses) if not well-managed (reviewed by Sadovy de Mitcheson and Erisman, 2012). This scenario characterizes the history of the totoaba fishery in the Upper Gulf, in which relentless harvesting of thousands of tons fish at their spawning aggregation sites in the estuaries of the Colorado River Delta resulted in a sudden fishery collapse by the 1950s (Cisneros-Mata et al., 1995). Current fishing activities for the Gulf corvina mimic those observed in the totoaba fishery several decades ago, with up to five thousand tons of fish harvested from the only known spawning aggregation site for the species, and indeed a suite of regulations have been implemented to avoid the same disastrous result (Erisman et al., 2012, 2014). These include gear restrictions, a seasonal quota of total harvest, and attempts to enforce the no-take zone. However, such regulations should also extend to the management of spawning aggregations of bigeye croaker, which is currently harvested in larger volumes than Gulf corvina, garners a higher market value, utilizes gill nets that exceed 1 km in length, and may have a much greater impact on protected species (e.g. vaquita), but is completely unregulated in terms of harvest or gear restrictions. Likewise, the fishery for the Spanish mackerel, which is listed by the IUCN as vulnerable to extinction due to its small geographic range in the Upper Gulf of California and its propensity to form spawning aggregations that are heavily exploited (Collette et al., 2011), would benefit from seasonal regulations or catch limits in Santa Clara that protect spawning for the benefit of a sustainable fishery. Differences in the ecological impact of fishing between the two communities may necessitate specific management regulations for each community, but it is equally important to consider the social and economic impacts of such actions. For example, regulations that reduce and restrict harvest levels of blue shrimp, Gulf corvina, bigeye croaker, Spanish mackerel may have a disproportionately larger negative impact on Santa Clara than San Felipe given its dependence on these four fisheries, the lower diversity of alternative species in the area to exploit commercially, the overall dependence of fisheries production as the main source of employment, and the general lack of economic alternatives (e.g. tourism) currently available to recoup lost fisheries revenues. Such impacts are particularly important to consider in relation to the dependence of Santa Clara’s fisheries production on the seasonal availability and harvest of the four principle species, which are already highly sensitive to fluctuations in ex-vessel prices, and thus will need to be countered by policies that help stabilize or increase market values, develop other sources of revenue (e.g. sportfishing) that will help maintain the livelihoods of the communities, and provide incentives to comply with fisheries and conservation regulations. Of course, harvest restrictions on the four principal fisheries will also have a serious effect on the fishing industry in San Felipe, and these same principles must therefore be applied. However, the diversity of species exploited and the existence of a tourist industry may help mitigate the impacts of such regulations on the overall livelihood of the community.

Acknowledgements We thank fishers of San Felipe and El Golfo Santa de Clara, ˜ L. Pérez, V. Corrales, H. Ruiz, Y. Flores, J. Vázquez, J. Montanez, A. Domínguez, R. Carrillo, C. Tirado, R. Franco, A. García, J. CotaNieto, G. Hinojosa, and Alto Golfo Sustentable for their partnership


B. Erisman et al. / Fisheries Research 164 (2015) 254–265

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