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What Are the Main Local Drivers Determining Richness and Fishery ZOOLOGIA 35: e12898 ISSN 1984-4689 (online) zoologia.pensoft.net RESEARCH ARTICLE What are the main local drivers determining richness and fishery yields in tropical coastal fish assemblages? Cynthia D. Souza1, Vandick S. Batista1, Nidia N. Fabré1 1Instituto de Ciências Biológicas e da Saúde, Universidade Federal de Alagoas. Avenida Lourival Melo Mota, Tabuleiro do Martins, 57072-900 Maceió, AL, Brazil. Corresponding author: Vandick S. Batista ([email protected]) http://zoobank.org/BA1F702C-377F-4E25-BC1E-D060DC79504A ABSTRACT. Seasonal ecological effects caused by temperature and photoperiod are typically considered minimal in the tropics. Nevertheless, annual climate cycles may still influence the distribution and abundance of tropical species. Here, we investigate whether seasonal patterns of precipitation and wind speed influence the structure of coastal fish assemblages and fishing yields in northeast Brazil. Research trips were conducted during the rainy and dry seasons using commercial boats and gear to sample the fish community. Diversity was analyzed using abundance Whittaker curves, diversity profiles and the Shannon index. Principal Component Analysis (PCA) was used to analyze associations between the abundance of species and various environmental variables related to seasonality. A total of 2,373 fish were collected, representing 73 species from 34 families – 20 of which were classified as both frequent and abundant. Species richness was greater and more equitable during the rainy season than the dry season – driven by changes in the precipitation rather than to wind speed. Species diversity profiles were slightly greater during the rainy season than the dry season, but this difference was not statistically significant. Using PCA was identified three groups of species: the first associated with wind speed, the second with precipitation, and the third with a wide range of sampling environments. This latter group was the largest and most ecologically heterogeneous. We conclude that tropical coastal fish assemblages are largely influenced by local variables, and seasonally mediated by annual changes related to precipitation intensity and wind speed, which in turn influences fishery yields. KEY WORDS. artisanal fishing, fishes, wind, precipitation, seasonality, gillnet. INTRODUCTION 2010, Schroeder and Castello 2010). Even so, the generalization of these findings is not possible as climate and local landscape Water quality and nutrient availability in coastal waters characteristics may drive communities to different profiles. are influenced by environmental factors such as the spatial and In the tropics, where annual changes in temperature and temporal patterns of precipitation, land drainage, and wind photoperiod are minimal, seasonality is heavily determined by patterns (Kennedy et al. 2002). Seasonal changes in biophysical precipitation (Lowe-McConnell 1987), which generates dry and factors can modify the composition of communities, affecting rainy seasons (Figueroa and Nobre 1990). Such seasonal varia- the occurrence and distribution of species within and between tion, though less apparent than that observed in temperate areas, trophic levels (Blaber et al. 1995, Brown et al. 1997, Walther et al. has the capacity to influence fish behavior (Wootton 1990) and, 2002). In coastal ecosystems, these effects are usually mediated consequently, may influence the distribution and abundance through temporal changes in temperature profile, the extent and of species within a given area (Laevastu and Hayes 1981) with magnitude of precipitation and continental runoff, wind patterns a knock-on effect on fishery yields (Hilborn and Walters 1992). and storm frequency (Bernal-Ramírez et al. 2003, Jury 2011, Ken- The consequences of these variability includes the estuarization nedy et al. 2002). Studies on the effects of changes in climate and process, when coastal waters resembles estuarine conditions biological productivity in the eastern Atlantic have documented (Longhurst and Pauly 1987b), even affecting the functional a range of seasonal effects on trophic levels, coral reefs, juvenile diversity of fish assemblages (Passos et al. 2016). dispersal, fishery yields and fish species abundance (e.g. Muehe Even facing those large-scale patterns, local effects are and Garcez 2005, Ciotti et al. 2010, Costa et al. 2010, Leão et al. detectable after higher scale effects being known and considered. ZOOLOGIA 35: e12898 | DOI: 10.3897/zoologia.35.e12898 | March 9, 2018 1 / 12 C.D. Souza et al. In this study, the objectives were to determine how seasonal da Pedra” (Fig. 1). The first set was approximately 11 km from patterns of precipitation and wind influence the temporal struc- Jaraguá Harbor at a depth of approximately 12 m; the second was ture of tropical fish assemblages and the yields of the coastal located approximately 14 km from the port of Jaraguá in a depth gillnet fishery. of approximately 20 m. The distance between the centroids of the sites was approximately 6.5 km. MATERIAL AND METHODS A commercial gillnet 1,330 m long and 1.5 m high was used, with a mesh size of 40 mm between opposite knots and a nylon Samples were collected in the central coastal zone of the thread size of 50 mm. Gillnets were set near the surface parallel to state of Alagoas, north-eastern Brazil, near the main regional the seabed and was fixed at both ends with anchors. The mean ± fisheries harbor (Fig. 1). standard deviation of the duration of each set was 3.51 ± 1.01 hours. The seasonal patterns are typically tropical and consist For each launch, the set position and duration were of a rainy season from March to August and a dry season from recorded, wind direction and intensity, the type and number September to February (Macêdo et al. 2004). Precipitation is of each species caught and the total length (cm) of each fish high on the coastal plain; with an annual average of 1,800 caught. All fishes were physically anesthetized by hypothermia mm. Coastal currents are conditioned by winds and tides and, on board and killed freezing on ice. in the rainy season, trade winds. During the rainy season, the Additional data on precipitation, wind speed and direction southeast quadrant (SE) experiences more frequent and intense were obtained from INMET/SEMARH, Brazilian government. To winds, while during the dry season, such winds flow from the facilitate the communication of our results to environmental northeast quadrant (NE) (Araújo et al. 2006). managers and members of local communities, a scale of wind Trips were made on crescent moon days in an 8 m intensity was created based on the reports of the fishermen on wooden boat with an ice capacity of 500 kg and a one-cylinder, board and the daily wind speed recorded by INMET/SEMARH as diesel-powered B18 engine. Six sampling trips were conducted follows: null = 0.0 m/s; weak ≤ 3.0 m/s; strong > 3.0 m/s. Simi- between October 2010 to August 2011, with three occurring larly, the precipitation values recorded by INMET/SEMARH were during the rainy season (June/July/August) and three during the categorized as very low = 0–31 mm; low = 32–84 mm; moderate dry season (October/December/February). Each trip lasted three = 85–137 mm; moderate-high = 138–196 mm; high = 197–200 days, totaling 30 launches of effective fishing. mm and very high ≥ 201 mm. Sets were established between two fishing areas with mud From these data, there was calculated: the number of and gravel substrates, known locally as “Lama Grande” and “Tira species and specimens per set, the mean length per species per Figure 1. Location of the sampled area within the Alagoas coast. Jaraguá fishing harbor and the fishery sites were indicated. 2 / 12 ZOOLOGIA 35: e12898 | DOI: 10.3897/zoologia.35.e12898 | March 9, 2018 What are the main local drivers determining richness and fishery yields? set, the catch per set (kg), the CPUE (catch per unit effort) with occasional species, and 51 and 20 as abundant and common standardized effort (1,330 m gillnet * set hours), the mean wind species, respectively (the same species can belong to more speed in m/s (mean of 6 hours per day: 3 hours before + 2 hours than one category depending on the weather station) (Suppl. during the set + 1 hour after) and the total monthly precipitation material 1). The frequent and abundant species, from most (mm). All data were compared between the dry and rainy seasons. to least abundant, were as follows: Carangidae: Caranx crysos (Mitchill, 1815) (blue runner) (N = 360); Sciaenidae: Larimus Data analysis breviceps Cuvier, 1830 (shorthead drum) (N = 321); Scombridae: Euthynnus alletteratus (Rafinesque, 1810) (little tunny) (N = Samples of all species were taken to the laboratory (SISBIO 301); Scombridae: Scomberomorus brasiliensis Collette Russo & 1837810) after each fishing trip and identified using a variety of Zavala-Camin, 1978 (serra spanish mackerel) (N = 254); Hae- keys (Lessa and Nóbrega 2000, Menezes and Figueiredo 1980). mulidae: Conodon nobilis (Linnaeus, 1758) (barred grunt) (N = One or two type specimens of each species were placed in a 168); Clupeidae: Opisthonema oglinum (Lesueur, 1818) (Atlantic standard collection as reference material (see Suppl. material 1). thread herring) (N = 108); Carangidae: Chloroscombrus chry- Analyses of diversity were conducted using three different surus (Linnaeus, 1766) (Atlantic bumper) (N = 98), Sciaenidae: methods: Whittaker abundance curves (Whittaker 1960, Whittaker Menticirrhus littoralis (Holbrook, 1847) (gulf kingcroaker) (N = et al. 2001), diversity profiles (Melo 2008) using Rényi series – Eq. 72); Ariidae: Bagre bagre (Linnaeus, 1766) (coconut sea catfish) (B.1) (Magurran 2004) and the Shannon-Wiener diversity index (H’) (N = 57); Lutjanidae: Lutjanus synagris (Linnaeus, 1758) (lane – Eq. (B.2), including a bias correction term (Hammer et al. 2001). A snapper) (N = 56); Ariidae: Cathorops spixii (Agassiz, 1829) modified t-test was used to analyze the Shannon index, estimating (madamango sea catfish) (N = 51); Carangidae:Caranx hippos the variance by Eq. (B.3) (Magurran 2004). Diversity analyses were (Linnaeus, 1766) (jack crevalle) (N = 50); Sciaenidae: Macrodon conducted using the program PAST (Hammer et al.
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