Spatial Patterns of Distribution and the Influence of Seasonal and Abiotic Factors on Demersal Ichthyofauna in an Estuarine Tropical Bay

Journal of Fish Biology (2016) 89, 821–846 doi:10.1111/jfb.13033, available online at wileyonlinelibrary.com

Spatial patterns of distribution and the influence of seasonal and abiotic factors on demersal ichthyofauna in an estuarine tropical bay

D. R. da Silva Jr.*†, R. Paranhos‡ and M. Vianna*

*Federal University of Rio de Janeiro, Institute of Biology, Department of Marine Biology, Laboratory of Fisheries Biology and Technology, CCS, Bl. A, 21949-900, Cidade Universitária, Ilha do Fundão, Rio de Janeiro, Brazil and ‡Federal University of Rio de Janeiro, Institute of Biology, Department of Marine Biology, Laboratory of Hydrobiology, CCS, Bl. A, 21949-900, Cidade Universitária, Ilha do Fundão, Rio de Janeiro, Brazil

This study focused on the influence of local-scale environmental factors on key metrics offish community structure and function at Guanabara Bay, an estuarine system that differs from all other south-western Atlantic estuaries due to the influence of an annual low-intensity upwelling event during late spring and summer, between November and March, when a warm rainy climate prevails. The spatial patterns of the bottom temperature and salinity were more heterogeneous during the rainy season than the dry season, being linked to total precipitation and seasonal oceanographic events. The study identified 130 species and 45 families, placing Guanabara Bay as one of the most species-rich tropical estuarine ecosystems, far exceeding 22 other Brazilian estuaries. These results, in addition to characteristics such as a relatively well-preserved mangrove forest, high productivity and favourable conditions for the growth and reproduction of estuarine species, indicate that Guanabara Bay plays a central role in supporting large populations of fishes, including commercially important species. © 2016 The Fisheries Society of the British Isles

Key words: environmental drivers; estuarine functional groups; estuary; fish faunal richness.

INTRODUCTION Estuaries comprise almost 13% of all marine coastal environments and given their particular attributes, including high primary and secondary productivity, warm shallow waters and key ecological resources including shelter and protection and food avail- ability, these highly dynamic ecosystems sustain large numbers of fish species, (Thiel et al., 2003; McLusky & Elliott, 2004; Elliott et al., 2007). These characteristics give estuaries a fundamental role in regional ichthyofauna dynamics, functioning as growth sites for many marine species and reproduction areas for estuarine species. Since estuaries experience major shifts in environmental conditions over short periods, one of the classical hypotheses is that water variables are the principal drivers that shape the patterns of species distribution and composition (Maes et al., 2004). Therefore, determining how the ichthyofauna responds to these factors is among the

†Author to whom correspondence should be addressed. Tel.: +55 21 2562 6332; email: demarques- [email protected] 821

central goals of estuarine fish ecology. Studies on many of these systems have identified temperature, freshwater input, salinity, dissolved oxygen and transparency asthe main environmental drivers (Thiel et al., 2003; Maes et al., 2004; Akin et al., 2005). As estuaries are highly dynamic ecosystems, however, the relative weight of these factors differs to some degree, even among neighbouring estuaries, which creates the need for local case-by-case studies of the roles of abiotic factors (Blaber, 2013). The available information on the ecology and dynamics of ichthyofaunal assemblages in South American estuaries and marine ecosystems is concentrated in relatively few coastal areas [e.g. Caeté, Goiana and Sepetiba Bay, tropical estuaries from the northern, north-east and south-east coasts of Brazil; Patos Lagoon, Guaratuba and Paranaguá, subtropical estuaries from the southern coast of Brazil; La Plata, a subtropical estuary from the south-west Atlantic coast of Argentina; Barletta et al. (2010)], and a few studies have been conducted recently in Guanabara Bay. Together, they cover the following topics: ichthyoplankton composition and variability (Kraus & Bonecker, 1994; Castro et al., 2005), fisheries (Jablonski et al., 2006) and ichthyofauna spatial and temporal dynamics (Rodrigues et al., 2007; Silva et al., 2007; Vasconcellos et al., 2007, 2010, 2011; Andrade-Tubino et al., 2009; Silva et al., 2013). There is, however, considerable lack of information about the fish fauna, including basic information such as species occurrence, patterns of occupancy, and estuarine use. Guanabara Bay is of immense ecological, social and economical importance for the south-eastern region of Brazil, strategically located adjacent to one of the most industrialized regions of the country and under the influence of numerous fishing and commercial port facilities, in addition to ship yards and oil refineries. Regardless of its history of environmental depletion as a result of diverse anthropogenic activities, the bay still exhibits characteristics of a typical tropical estuary, including a relatively well-preserved mangrove forest, high productivity and favourable conditions for growth and reproduction of estuarine species (Blaber, 2000). Therefore, it continues to sustain important fisheries and a large number of fishers (Jablonski et al., 2006). To improve the knowledge of the ichthyofaunal dynamics in Guanabara Bay, the present study adopted a narrow approach, focusing on the influence of local-scale environmental factors on key metrics of community structure and function, such as estuarine use. The objectives were to (1) describe the spatial distribution of local fishes in the bay, particularly the demersal ichthyofauna, based on important community metrics and ecological features such as feeding-mode, habitat and estuarine-use functional group and (2) elucidate the influence of seasonal factors on the fish community of Guanabara Bay.

MATERIALS AND METHODS

STUDY AREA Guanabara Bay is a semi-enclosed tropical bay located on the south-eastern coast of Brazil, in the centre of a densely urbanized and industrialized area of the metropolitan region of Rio de Janeiro (Baptista-Neto et al., 2006) (22∘ 41′ –22∘ 03′ S; 043∘ 16′ –043∘ 01′ W) (Fig. 1). It is one of the largest estuarine systems on the Brazilian coast (381 km2), surrounded by 16 cities, and the drainage basin (4081 km2) contains a total of 91 rivers and canals. Regional climate is humid tropical, with two main seasons: warm rainy (December to March) and cold dry (July to August) (Paranhos & Mayr, 1993). The semi-diurnal tide fluctuates· 0 7 m on average. The

(a) (b) 680 000 685 000 690 000 695 000 700 000 680 000 685 000 690 000 695 000 700 000

MagéMagé Duque de Caxias BG-24 Duque de Caxias 7 490 000 7 490 000 BG-20 BG-22

Paquetá Island BG-31 BG-26 Paquetá Island 3 000 3 000 BG-29 8 8 BG-28 BG-17 Duque de Caxias Upper bay 7 4 7 4 BG-16

Central Channel BG-15 Governador IslandBG-13 Governador Island BG-12 BG-10 BG-11 São Gonçalo São Gonçalo Gradim

BG-34 7 476 000 7 476 000

BG-09 Governador Island BG-07

Lower bay C.P. Rio de Janeiro - Praça Mauá C.P. Rio de Janeiro - Praça Mauá 7 469 000 7 469 000

BG-04 BG-03 Niterói BG-02 Niterói Rio de Janeiro BG-01 Rio de Janeiro Entrance

Seaward end Seaward end 7 462 000 7 462 000 N N

0 2·5 5 10 SAD 1969 UTM Zone 23S 02·55 10 SAD 1969 UTM Zone 23S km km

Fig. 1. (a) Environmental sampling points and (b) ichthyofauna sampling sites in Guanabara Bay, Rio de Janeiro. Bottom water variables were sampled every 15 days for 24 months (July 2005 to June 2007). seaward end (lower bay, euryhaline) is narrow (1·6 km) and has the strongest tidal currents, reaching 1·6ms−1 (SEMADS, 2001). In this section of the bay, the influence of coastal waters is maximum and the effects (higher salinity and lower temperatures) extend through the long central channel (18 km; maximum depth of 50 m) towards the upper bay. In the middle and upper bays (except the central channel), areas depths are <10 m and extensive shallow mud banks exist. In these sections, specifically those close to Governador Island and the cities of Duque de Caxias, Magé and São Gonçalo, the influence of continental drainage is greater, imposing mesohaline to polyhaline characteristics during the rainy season and euryhaline ones in the dry season. In addition to the natural gradient from oceanic to continental waters, Guanabara Bay exhibits a water quality gradient, as pollution loads undergo different degrees of dilution (Paranhos et al., 1998). This condition is essentially attributed to high sedimentation rates associated with landfills, which have led to severe restriction of water circulation and increasing water turnover time (Amador, 1980) in the middle and upper bays (except central channel). On the other hand, bathymetric profiles of the central channel show it contributes to a high water renewal promoted by tidal cycles. The inner parts of the bay exhibit the poorest water quality, especially the north-western side, given the highly urbanized and industrialized drainage basin composed of the São João de Meriti River and the Sarapuí River (Baptista-Neto et al., 2006; Kalas et al., 2009). On the opposite shore, the north-eastern portion is better preserved because of the integrity of the drainage basin of the Guapimirim Environmental Protection Area (Ribeiro & Kjerfve, 2002). In the rainy season, Guanabara Bay is influenced by an annual low-intensity upwelling event during late spring and summer (November to March). This period is characterized by an increase of north-east winds that bring South Atlantic Central Water (SACW) to the surface 100 km north of the bay entrance, establishing subtropical and temperate characteristics for the Rio de Janeiro coast, with temperatures between 10∘ and 20∘ C (Matsuura, 1986; Barletta et al., 2010). Oceano- graphic characteristics that oppose the typical influence of tropical waters (temperature > 20∘ C and salinity > 36; Matsuura, 1986) are driven by the Brazil current during the rest of the year (Brandini, 1990).

ENVIRONMENTAL DRIVERS Precipitation and water variables were assessed in order to investigate the spatial and temporal patterns of the demersal ichthyofauna. Precipitation was evaluated for each month, based on two categories defined by Walter & Lieth (1967) indicating dry and rainy months based on mean temperature and total precipitation. Data for both factors were obtained from the C. P. Rio de Janeiro, Praça Mauá weather station. Bottom water variables were sampled every 15 days during a 24 month period, from July 2005 to June 2007, at 21 points across Guanabara Bay [Fig. 1(a)] and analysed by standard oceanographic methods (Grasshoff et al., 1999). Water temperature was measured with a graduated thermometer (∘ C). Salinity and dissolved oxygen (DO; mg l−1) were evaluated, respectively, by the chlorinity and Winkler-azide methods. Inorganic nutrients were also analysed: ammonium nitrogen by indophenol (𝜇M), and total phosphorus by acid digestion to phosphate (𝜇M).

FISH SAMPLING Fish surveys were conducted under the authorisation of SISBio (Sistema de Autorização e Informação em Biodiversidade, ‘Authorization and Information System on Biodiversity’) No. 055, 5 December 2005. The same periodicity of every 15 days was adopted for fish sampling during a 24 month period (July 2005 to June 2007) in six areas [Fig. 1(b)]. Each sampling area was evaluated by means of two to four hauls made during the day, at a constant speed [2·8–3·7kmh−1 (1·5–2·0 knots)], for 30 min, using a typical boat of the local artisanal fleet, and the GPS co-ordinates of the beginning and the end of sampling were recorded. The trawl net was 7 m long, with a 14 m ground rope and a 18 mm mesh codend. All fishes were counted, identified, measured to the nearest· 0 1 cm (total length, LT) and weighed to the nearest 0·1g. No sub-sampling method was employed. The catch per unit effort (CPUE) was used to esti- mate abundance (number of individuals = 0·5h−1) for all analyses, given the consistency of the sampling gear and field methods. Three other univariate measurements regarding community structure were determined: species richness (total number of species, S); Shannon diversity index (H′) and Pielou equitability (J) (Margalef, 1974). Complementary biological features of the feeding-mode functional group, habitat and estuarine-use functional group were assessed for each species through specialized references (Cervigón & Fischer, 1979; Menezes & Figueiredo, 1980; Randall, 1983; Marceniuk, 2005). The classification followed the definitions of Elliott et al. (2007).

DATA ANALYSIS Environmental data were analysed as means ± s.d., minimum and maximum values for each site. A t-test was used to verify the difference of mean precipitation between seasons. Fish measurements (each haul was treated as a sample) were tested for normality (Kolmogorov–Smirnov test) and homoscedasticity (Levene’s test) and then evaluated by two-way ANOVA without data transformation. A Tukey post hoc test was used to assess the variability of these measurements (Zar, 1999), considering the spatial (areas: six levels, fixed) and seasonal patterns (precipitation: two levels, random). Next, fish patterns were explored using a correspondence analysis (CA), followed by a canonical correspondence analysis (CCA) in order to screen for the environmental variables that best explained the ichthyofauna distribution and seasonality. Not all species captured were employed in the analyses. Because of the type of sampling gear used in this study, those species that were considered as being pelagic or strictly associated with hard bottoms were removed from the analysis, focusing the investigation on the soft-bottom fish community. Another criterion specifically employed in the CA and CCA was the total index of relative importance (IRI) (Selleslagh & Amara, 2008). This analysis was carried out only for the dominant species during the study period, i.e. those that individually contributed >0·1% of the IRI. This approach removes rare species that increase noise, and affects only the total variation expressed by the eigenvalues without altering the interpretation of results. Analyses were performed using the programmes Statistica 7.1 (StatSoft; www.statsoft.com) and PC-ORD 4 (McCune & Mefford, 1999). A significance level of 0·05 was used in all tests. Additionally, Kriging and Co-Kriging geostatistical techniques (Matheron, 1971) were employed to explore the spatial organization of fish metrics (abundance, richness and diversity)

40 80

30 60 ) mm ailable re (° C) v u 20 40 perat m e No data a T otal precipitation (

10 20 T

0 0 t t y y y y y y y y l l ne ne ar ar ar ar ber ber ber ber ber ber u u u u J J u u u u Ma Ma J J m m m m m m April April ugus ugus March March e e A A v v Jan Jan October October Febr Febr Dece Dece No No Septe Septe 2005 2006 2007

Fig. 2. Climate diagram [temperature ( ) and total precipitation ( )] based on the methodology of Walter & Lieth (1967). Data obtained from the C. P. Rio de Janeiro – PraçaMauá weather station during the study period (July 2005 to June 2007). Due to technical problems, it was not possible to obtain rainfall data for December 2006 and January 2007. across Guanabara Bay. Each area was evaluated by a set of 28–64 data points for each fish metric calculated for a location x,wherex is defined by latitude and longitude in a two-dimensional space. All interpolation models were submitted to validation by the method of leave-one-out (Isaaks & Srivastava, 1989). Models were generated by the programme ArcMap 10.0 (ESRI, 2010).

RESULTS

CHARACTERIZATION OF ENVIRONMENTAL PATTERNS Based on the climate diagram of Walter & Lieth (1967), only seven of the 24 months were considered as dry periods: August 2005, March 2006, July 2006, August 2006, March 2007, April 2007 and June 2007 (Fig. 2). It was not possible to obtain rainfall data for December 2006 and January 2007 due to technical problems, but those months were considered as rainy periods (Paranhos & Mayr, 1993; Kjerfve et al., 1997). During these months, the mean precipitation was 30·1 ± 19·1 mm, a value statistically different (P < 0·05) from the rainy period, which had a mean precipitation of 112·4 ± 44·1 mm. Below, the rainy and dry periods are together termed ‘seasons’, although they did not correspond exactly to the normal annual cycle. The environmental characterization of sampling sites is shown in Table I and indi- cates the spatial and seasonal heterogeneity of bottom water variables in Guanabara Bay. The spatial patterns of temperature and salinity were more heterogeneous during rainy months, periods when s.d. was consistently higher. The same period revealed greater amplitudes of minimum and maximum temperature (16–29∘ C) than in dry months (18–28∘ C; Table I and Appendix I). Lowest temperatures were observed during rainy periods at Entrance (16∘ C), Central Channel (17∘ C) and Governador Island (17∘ C). On the other hand, the highest temperature was measured at Gradim during

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 826 D. R. DA SILVA ET AL. 3 0 1 5 0 5 6 7 4 · · · 2 7 · · · · 6 3 7 3 · · 0 2 · 6 7 · 2 · · · · · · · · · 2 0 1 2 0 5 0 1 1 12 ± ± ± ± ± ± ± ± ± ± 1 9 1 4 0–26 4–5 4–36 5–4 2–6 1–6 6–33 0–28 3 · · 2 4 · · 4 7 7 · · 1–29 · · · · · · 6–45 · · · · · · · · 016 833 821 534 021 · 90 · 122 021 64 · · 44 51 · 324 930 42 · 50 · · 50 · · · 32 · 83 · · · 10 72 · 1 0 · · · · 0 4 0 2 0 1 0 14 ± ± ± ± ± ± ± ± ± ± 6 1 0–24 2–5 2–35 6–2 · · 4 8 4 9 8 · · · 3–16 · 3–5 0–4 1–34 0–28 · · · 2 · 3 · 9 · · · · · 4–51 · · · · 43 018 434 521 635 · 631 020 · 40 · 223 132 54 · · 31 · · 22 00 23 · 50 · · 43 016 43 · · · · 61 · · · · · 1 1 · 2 3 1 16 1 1 9 2 ± ± ± ± ± ± ± ± ± ± 5 1 0–27 0–6 5–33 7–9 2 3 · · 0 3 6 5–5 8–33 0–29 · · · · 2–82 7 · 1 8 · · · · · 1–16 · · 2–33 · · · · · · 231 718 020 224 329 021 12 927 82 523 · 931 44 · · 40 22 · 09 83 · · 30 · · · · · · 00 61 · · · · · 62 · · 2 1 · 2 2 0 1 2 8 0 50 ± ± ± ± ± ± ± ± ± ± 6 1 2–8 5–4 7–33 0–27 0 8 8 9 0–28 8–33 0–7 · 1 · 8 2 · · · · 2–21 · · · · 1 · · · 3–12 · · · · · · 4–198 · 97 429 020 60 223 432 · 020 830 · · · 63 323 442 532 73 · 43 · 23 · · 57 22 00 81 · · · · · · · · · 31 · · 2 1 · 0 2 7 0 1 1 19 1 ± ± ± ± ± ± ± ± ± ± 0 4 7–7 3–6 1–34 0–28 3 5 1 6 2 · · 5 3 7 0–25 1–4 4–35 · · · · · · · · · · · · · · 2–41 · 9–11 7–102 · · · 729 629 017 017 733 · 723 932 021 83 28 634 62 · · 41 · · 20 · 22 · 63 · · · · · · 90 91 · 91 60 · · · · · · 1 0 2 0 6 0 0 1 12 0 ± ± ± ± ± ± ± ± ± ± 4 6 9 4 9 8 1 7–3 0–4 2–35 0–27 0–25 1–4 8–35 3–3 · 1 9 · 9 · · · · · · · · · 2–51 · · 3–20 · · · · · · · s.d. 21 s.d. 3 s.d. 34 s.d. 2 s.d. 9 s.d. 23 s.d. 2 s.d. 33 s.d. 3 s.d. 24 ± ± ± ± ± ± ± ± ± ± Minimum–maximum 18 Minimum–maximum 2 Minimum–maximum 0 Minimum–maximum 33 Minimum–maximum 1 Minimum–maximum 0 Minimum–maximum 3 Minimum–maximum 32 Minimum–maximum 20 Minimum–maximum 5 ) Mean ) Mean 1 1 − − M) Mean M) Mean including temperature, salinity, total phosphorus, ammonium and dissolved oxygen, from July 2005 to June 2007 𝜇 𝜇 C) Mean C) Mean M) Mean M) Mean ∘ ∘ 𝜇 𝜇 Table I. Environmental variables of each area sampled inArea the dry and rainy periodsSeason (number of months given in parentheses)Temperature ( in Guanabara Bay, AreaSeasonTemperature ( Dry (7) Central Channel Rainy (17) Dry (7) Duque de Caxias Rainy (17) Dry (7) Rainy Entrance (17) Dry Governador (7) Island Rainy (17) Dry (7) Gradim Rainy (17) Dry (7) Rainy (17) Paquetá Island Salinity Mean Total phosphorus ( Salinity Mean Dissolved oxygen (mg l Total phosphorus ( Dissolved oxygen (mg l Ammonium ( Ammonium (

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 ICHTHYOFAUNA OF ESTUARINE TROPICAL BAY 827 the rainy period (29∘ C), followed by Paquetá Island (both periods), Governador Island (rainy period) and Duque de Caxias (dry period), all exhibited the maximum of 28∘ C (Table I and Appendix I). Areas close to the seaward end (Entrance) and those under the direct influence of tidal currents (Central Channel) showed the highest salinity values, attaining a maximum of 36·1 at Entrance and 35·8 at Central Channel, both during rainy periods (Table I and Appendix II). Gradim and Paquetá Island showed the lowest salinity values (18·8 and 22·6) during rainy months. The pattern observed for total phosphorous was similar to salinity and temperature, with values more homogeneous along the bay during dry periods (range = 0·6–7·6). Lowest mean values were obtained at Entrance and Central Channel with no clear dis- tinction between seasons (Table I and Appendix III). Dissolved oxygen and ammonium revealed an inverse pattern and had more heterogeneous values during the dry months. The lowest concentrations of dissolved oxygen were observed at Duque de Caxias and Gradim during the dry period (0·0 and 0·2mgl−1) and at Paquetá Island during rainy period (0·2mgl−1). Coincidentally, Duque de Caxias and Gradim had higher concentrations, attaining 12·3 and 8·0mgl−1 (Table I and Appendix IV). Lastly, the highest concentrations of ammonium were associated with the western portion of the Bay, including Duque de Caxias during the dry period (198·1 𝜇M) and Governador Island during the rainy period (102·6 𝜇M; Table I and Appendix V).

COMMUNITY DESCRIPTORS A total of 74 186 specimens were caught during the 2 years of sampling, compris- ing 130 species and 45 families. The three most numerous species [Chilomycterus spinosus spinosus (L. 1758), Genidens genidens (Cuvier 1829) and Micropogonias furnieri (Desmarest 1823)] accounted for 57·8% of the absolute abundance. Sciaenidae was the most numerous family, contributing 27·5% of the total catch (Appendix VI). ANOVA indicated no interaction between environmental drivers (areas v. season) for any fish metric (Table II). Therefore, the influence of each of these driverswas examined individually. Changes in abundance, diversity and equitability were statistically explained by the two drivers independently, and the shifts in richness values were associated only with spatial variability (P < 0·05). Abundance changed markedly during the study period, as evidenced by the large s.d. Sampling was most effective in the Duque de Caxias area, with c. 250 individuals per haul (0·5 h) during dry months. Regardless of the season, the mean catch at Duque de Caxias was statistically dissimilar from those at the Entrance and Paquetá Island sites. Generally, larger mean catches were obtained during dry months for all sampling locations except Duque de Caxias. Only the catches from Gradim diverged statistically between seasons [Table II and Fig. 3(a)]. Higher richness values were obtained at areas close to the seaward end. At the Entrance, a total of 87 species were collected, while 69 species were recorded from the Central Channel. The catches at Entrance showed the highest mean richness, in contrast to Paquetá Island, which showed the lowest values. Richness in both areas was statistically different from the others [Table II and Fig. 3(b)]. Rainy months usually showed higher levels, with the exception of Paquetá Island and Central Channel.

Table II. Results of two-way ANOVA on fish metrics using area and season as orthogonal factors

Sum of Mean Sources of variation squares d.f. square FP CPUE Area 310 672 5 62 134 4·0388 <0·01 Season 61 764 1 61 764 4·0147 <0·05 Area v. season 58 497 5 11 699 0·7605 >0·05 Error 2 030 757 132 15 385 – – Richness Area 1355·64 5 271·13 14·837 <0·001 Season 0·01 1 0·01 0·001 >0·05 Area v. season 163·75 5 32·75 1·792 >0·05 Error 2412·07 132 18·27 – – Diversity Area 9·1130 5 1·8226 9·899 <0·001 Season 1·5998 1 1·5998 8·689 <0·01 Area v. season 1·2460 5 0·2492 1·354 >0·05 Error 24·3028 132 0·1841 – – Equitability Area 0·60160 5 0·12032 6·492 <0·001 Season 0·23562 1 0·23562 12·713 <0·001 Area v. season 0·09526 5 0·01905 1·028 >0·05 Error 2·44643 132 0·01853 – –

Bold values indicate alpha = 0.05.

Diversity was higher during rainy months at all locations, with the exception of Duque de Caxias, where it was almost equal between seasons. Similar to richness, diversity showed higher values at Entrance [Table II and Fig. 3(c)]. In addition, equitability suggested that dry months showed higher dominances of one or more species [Table II and Fig. 3(d)]. The lowest values were observed at Duque de Caxias, Gradim and Governador Island during dry months. Geostatistical results visually demonstrated the same patterns as the ichthyofauna metrics, but gave more emphasis to the differences between seasons. The higher spatial heterogeneity of the CPUE at Guanabara Bay during rainy months, with an amplitude of c. 800 individuals 0·5h−1 while during dry periods, the CPUE was less spatially concentrated (amplitude of c. 200 individuals 0·5h−1) (Fig. 3). Latitudinal differences in capture can also be observed in the model (Fig. 4). Richness (Fig. 5) and diversity (Fig. 6) models agree with the higher spatial heterogeneity associated with rainy months. Both gradients displayed higher values in areas close to the seaward end, cor- roborating the results from ANOVA. The CA and CCA revealed that the longitudinal spatial gradient within Guanabara Bay is stronger than the seasonal gradient with respect to the patterns of occupancy of the demersal ichthyofauna (Figs 7 and 8). The results demonstrated that marine estuarine-opportunists [e.g. Orthopristis ruber (Cuvier 1830), Diplectrum formosum (L. 1766), Cynoscion jamaicensis (Vaillant & Bocourt 1883) and Ctenosciaena gracilicirrhus (Metzelaar 1919)] were associated with lower-bay locations, where the higher dissolved oxygen content and salinity may be responsible for the similarity of the fish assemblage between the Entrance and Central Channel during both seasons. In contrast, marine estuarine-dependent species, such as the catfishes G. genidens and Genidens barbus (Lacépède 1803), were associated with the upper bay. The assemblage at Duque

(a)450 (b) 30 400 )

–1 350 25 0.5h

s 300

al 20 u ss id 250 v 200 15 Richne 150 10 ndance (indi

u 100

Ab 5 50 a; b a b ** 0 0 (c)3·0 (d) 0·80 0·75 2·5 ) ) J'

H' 0·70 2·0 0·65 index u 0·60 1·5 (pielo hannon index 0·55 s y ( y

it 1·0 0·50 s itabilit er u v 0·45 Eq Di 0·5 0·40 aa a; ba; c; d c; e; f e b; f d * 0 0·35 Central Channel Entrance Gradim Central Channel Entrance Gradim Duque de Caxias Governador Island Paquetá Island Duque de Caxias Governador Island Paquetá Island

Fig. 3. Spatial mean ± s.e. variation in both seasons( ,dry; , rainy) of (a) abundance, (b) richness, (c) diversity and (d) equitability (d) of soft-bottom demersal ichthyofauna in Guanabara Bay, Rio de Janeiro, sampled from July 2005 to June 2007. Letters from ‘a’ to ‘f’ indicate the pairs of areas which are statistically different based on Tukey post-test (P < 0·01); , the area differs statistically from all other areas (P < 0·05); ,the pairs of seasons which are statistically different based on Tukey post-test (P < 0·01). de Caxias was associated with higher levels of ammonium and total phosphorus, as well as higher temperatures.

DISCUSSION Estuaries exhibit both horizontal and vertical gradients in their water variables. Since this study focused on demersal soft-bottom species, interest was in the horizontal gradient of Guanabara Bay, which is typically structured by the balance between continental drainage, influenced by rainy and dry periods, and coastal currents (Mayr et al., 1989; Valentin, 1993, 1999; Ribeiro & Kjerfve, 2002). Continental drainage is an important factor, with more influence on the inner bay areas and during the rainy season, apattern that in Guanabara Bay is especially pronounced due to its extensive drainage basin. The proximity of the Serra do Mar mountain range (c. 20 km) contributes to a much larger freshwater input, predominantly from December to March, compared to other important Brazilian estuarine ecosystems such as the Patos Lagoon (Garcia et al., 2012). At the opposite end of the bay, the influence of coastal waters was another driver forthe horizontal gradient, as the Central Channel as well as the bay mouth (Entrance) are strongly influenced by tidal currents (Mayr et al., 1989). Corresponding with the continental drainage, the influence of coastal waters on the spatial organization and composition of the ichthyofauna is seasonally structured

(a) (b)

Magé Magé Duque de Caxias Duque de Caxias 7 490 000 7 490 000

Paquetá Island Paquetá Island 3 000 3 000 8 8 7 4 7 4

Governador Island Governador Island São Gonçalo São Gonçalo 7 476 000 7 476 000 7 469 000 Rio de Janeiro Rio de Janeiro 7 469 000 Niterói Niterói 7 462 000 N N 7 462 000

680 000 687 000 694 000 701 000 680 000 687 000 694 000 701 000 SAD 1969 UTM Zone 23S 0 2·5 5 10 km

85 – 152 218 – 285 352 – 418 485 – 552 618 – 685 752 – 818 152 – 218 285 – 352 418 – 485 552 – 618 685 – 752 818 – 885

Fig. 4. Spatial pattern of catch per unit of effort (CPUE; number of individuals 0·5h−1) of the soft-bottom demersal ichthyofauna sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) dry months. in Guanabara Bay. One of the principal oceanographic features of the south-eastern Brazilian coast is the prevalence of tropical waters carried by the Brazil Current during most of the year (Brandini, 1990). During late spring and summer, however, the South Atlantic Central Water (SACW) surfaces 100 km north of the bay entrance, establishing subtropical and temperate characteristics for the Rio de Janeiro coast, with temperatures between 10 and 20∘ C (Matsuura, 1986; Barletta et al., 2010). This oceanographic phenomenon distinguishes Guanabara Bay from all other south-western Atlantic estuaries, as the only one under the influence of an annual low-intensity upwelling event. Due to the correspondence between rainy periods and the proximity of the SACW to the shore, the effects of both environmental processes were clearly observed in the geostatistical models. The results for rainy months showed higher heterogeneity than those for dry months, due to the concomitantly higher freshwater input of Duque de Caxias, Paquetá Island, Governador Island and Gradim and the effects of cold and saline intrusion of SACW along the bottom, creating a density-dependent vertical gradient, and imposing mesohaline to polyhaline characteristics to upper-bay areas during the rainy months (Valentin, 1993). Considering all the limitations of an estuarine environmental quality assessment, combined with the intrinsically high variability and the adaptation of the ichthyofauna to these conditions, known as the ‘estuarine quality paradox’ (Elliott & Quintino, 2007), the results presented here support some inferences about the influence of

(a) (b)

Magé Magé Duque de Caxias Duque de Caxias 7 490 000 7 490 000

Paquetá Island Paquetá Island 3 000 3 000 8 8 7 4 7 4

Governador Island Governador Island São Gonçalo São Gonçalo 7 476 000 7 476 000 7 469 000 7 469 000 Rio de Janeiro Rio de Janeiro Niterói Niterói 7 462 000 7 462 000 NN

680 000 687 000 694 000 701 000 680 000 687 000 694 000 701 000 SAD 1969 UTM Zone 23S 0 2·5 5 10 km 10 – 11·2 12·4 – 13·6 14·8 – 16 17·2 – 18·4 19·6 – 20·8 11·2 – 12·4 13·6 – 14·8 16 – 17·2 18·4 – 19·6 20·8 – 22

Fig. 5. Spatial pattern of richness total (number of species) of the soft-bottom demersal ichthyofauna sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) dry months. human activities on Guanabara Bay. This bay is known for long-term degradation of environmental indicators, and the present observations corroborate the pollution gradient pattern of the system (Mayr et al., 1989; Kjerfve et al., 1997). Environmental variables such as oxygen content, total phosphorus and ammonium suggest that the inner part of the bay, especially the north-western side, is in a state of advanced dete- rioration, mainly because of its generally shallow depths that limit water circulation, and the highly urbanized and industrialized sub-basin composed of the São João de Meriti River and the Sarapuí River (Baptista-Neto et al., 2006; Kalas et al., 2009). On the opposite shore, the north-eastern portion is better preserved, due to the integrity of the sub-basin of the Guapimirim Environmental Protection Area (Ribeiro & Kjerfve, 2002). The central channel and the mouth of the estuary have the best environmental integrity, due to tidal currents that regularly renew the water (Villac et al., 1991).

SEASONAL VARIABILITY AND SPATIAL DISTRIBUTION OF DEMERSAL ICHTHYOFAUNA As with many other estuaries, the spatial dynamics of the demersal ichthyofauna are controlled by the balance between land drainage and coastal currents, creating a longitudinal gradient of water variables in the system (Vilar et al., 2013). There- fore, typical patterns of ichthyofauna metrics were observed, such as the highest values of richness, diversity and equitability in areas closer to the seaward end. This

(a) (b)

Magé Magé Duque de Caxias Duque de Caxias 7 490 000 7 490 000

Paquetá Island Paquetá Island 3 000 3 000 8 8 7 4 7 4

Governador Island Governador Island São Gonçalo São Gonçalo 7 476 000 7 476 000 7 469 000 7 469 000 Rio de Janeiro Rio de Janeiro Niterói Niterói

7 462 000 N N 7 462 000

680 000 687 000 694 000 701 000 680 000 687 000 694 000 701 000

SAD 1969 UTM Zone 23S 0 2·5 5 10 km 1·05 – 1·3 1·46 – 1·59 1·69 – 1·78 1·84 – 1·92 2·03 – 2·16 1·3 – 1·46 1·59 – 1·69 1·78 – 1·84 1·92 – 2·03 2·16 – 2·33

Fig. 6. Spatial pattern of Shannon diversity index (H′) of the soft-bottom demersal ichthyofauna sampled from July 2005 through June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) dry months. is a regular configuration of ichthyofauna in estuaries worldwide, as the predomi- nant functional group is composed of marine species, either estuarine-dependent or estuarine-opportunist species (Elliott et al., 2007; Selleslagh & Amara, 2008). This observation reinforces the idea that estuaries are mostly used as a temporary habitat by fishes, attracted by the shelter, high densities of prey and food and shallow turbid waters that provide protection. On the other hand, the abundance metric revealed a unique pattern of spatial distribution, with the largest catch in the north-western portion (Duque de Caxias), essentially comprised of G. genidens. The most impressive aspect is the preference of this species for an area that has the worst water conditions in the entire bay (Baptista-Neto et al., 2006; Kalas et al., 2009). As the catfishes are among the few species that can tolerate these conditions, it is likely that the decrease in competition from less-tolerant species is favouring the dominance of G. genidens (Silva et al., 2013). As previously seen, Guanabara Bay is under the influence of an annual low-intensity upwelling process, which seasonally establishes subtropical and temperate characteristics along the Rio de Janeiro coast, and has the potential to change the composition and distribution of marine organisms during this period (Barletta et al., 2010). It was expected that the establishment of subtropical and temperate characteristics along the Rio de Janeiro coast (10 and 20∘ C) would favour the occasional presence of less-abundant species that are more associated with temperatures between 10 and 20∘ C, such as Dules auriga Cuvier 1829. This was clearly evidenced by the generally

0·5 MM MS

Gradim Governador Island Duque de Caxias Central Channel 0·0 MED Paquetá Island MEO

Entrance

–0·5

–1·0

ER –1·5

–1·0 –0·50·00·51·0

Fig. 7. Correspondence analysis (CA) plot of site and estuarine functional user group. MEO, marine-estuarine-opportunist; MED, marine-estuarine-dependent; MM, marine migrants; MS, marine stragglers; ER, estuarine resident (definitions according to Elliott et al., 2007). higher diversity of the fish assemblage in rainy months (late spring and summer, the upwelling period) at all locations, except for some locations in the upper bay (Duque de Caxias and Paquetá Island). In view of the well-known history of degeneration of environmental quality in the bay, the present results corroborate the common-sense impression that water quality is

3·5 Diplectrum formosum 3·0 Orthopristis ruber Syacium papillosum 2·5 Citharichthys macrops PI-Dry; PI-Rainy; GR-Rainy ariance) v 2·0 Synodus foetens Etropus crossotus 1·5 Sphoeroides greeleyi Stephanolepis hispidus Genidens genidens 1·0 Cynoscion leiarchus EN-Dry; EN-Rainy DC-Dry; DC-Rainy Dactylopterus volitans Dissolved oxygen Genidens barbus 0·5 Ctenosciaena gracilicirrhus

e = 0·2637; 30·4% of Salinity Micropogonias furnieri u

al 0·0 Ammonium v CC-Rainy Diplectrum radiale

en Symphurus tesselatus Total phosphorus g –0·5 CC-Dry Temperature Prionotus punctatus GI-Dry; GI-Rainy; GR-Dry II (ei Cynoscion jamaicensis s –1·0 Chilomycterus spinosus Eucinostomus argenteus Axi E. gula –1·5 Lagocephalus laevigatus Selene setapinnis Diapterus rhombeus –2·0 –2·5 –2·0 –1·5 –1·0 –0·5 0·0 0·5 1·0 1·5 2·0 Axis I (eigenvalue = 0·4839; 55·79% of variance)

Fig. 8. Canonical correspondence analysis (CCA) ordination representing the influence of water variables on soft-bottom demersal ichthyofauna in Guanabara Bay, Rio de Janeiro, from July 2005 to June 2007. Only the most numerous species are shown. axis I: 55·79%; P < 0·01. axis II: 30·4%; P > 0·05. , species; , location/season lines; dashes and circle, data groups.

poorest towards the upper bay, while the entrance has the best water quality (Castro et al., 2005). An additional east–west gradient exists that highlights the dissimilari- ties between shores, especially when comparing Duque de Caxias v. Paquetá Island (both upper-bay locations; western and eastern shores, respectively) and Governador Island v. Gradim (both mid-bay locations; western and eastern shores, respectively). The principal hypothesis is that the drainage sub-basin of the Guapimirim Environ- mental Protection Area (north-eastern portion of the bay), which directly influences the Paquetá Island sampling location and to a lesser extent Gradim, is better preserved than the western drainage basin, which contains the highly impacted São João de Mer- iti, Iguaçu and Sarapuí Rivers (Ribeiro & Kjerfve, 2002). This assumption was not verified statistically, as CCA axis II was not significant, but two main biological results support the hypothesis. One is the concentration of the tolerant catfish G. genidens at the Duque de Caxias location, together with the poor water conditions in this area. The other is the similarity, during rainy periods, of the fish assemblages of Gradim and Paquetá Island, both located near the eastern shore. This association is presumed to be a result of the better water conditions provided by the larger volume of water drain- ing from the Guapimirim Environmental Protection Area. A similar tendency was not observed between the Duque de Caxias and Governador Island locations, mainly due to the presence of the island itself, which functions as a natural barrier, in addition to the reduction of water circulation in the north-western region, a result of landfills (Coelho, 2007).

RICHNESS V. REGIONAL IMPORTANCE In addition to the typical environmental characteristics of a tropical estuary, Gua- nabara Bay is distinguished from other estuarine ecosystems of the south-western Atlantic Ocean by its large size and geomorphology, which allows a free connection to coastal waters. These characteristics create a situation where it is expected that the bay is essential for the maintenance of ecological processes on a regional scale (Vilar et al., 2013), a function that is far underestimated. One of the lines of evidence that support this hypothesis is the sustainability of high richness. Regardless of the differences in sampling techniques and CPUE between this study and the available literature, Guanabara Bay exhibits the highest richness among 22 of the largest and most important estuarine systems on the Brazilian coast, such as Ribeira, Sepetiba and Paranaguá Bays and Patos Lagoon (Andrade-Tubino et al., 2008). On a global scale, considering only tropical climates, the richness of the ichthyofauna in Guanabara Bay is lower than only 11 of 38 estuaries examined by Blaber (2000), encompassing systems of different sizes and types, including the well-known Embley (Australia), Orinoco (Venezuela), Terminós Lagoon (Mexico) and Mississippi Delta (U.S.A.). It is widely accepted that a community with a wider range of available resources will contain more species. From this perspective, Guanabara Bay is one of the most pro- ductive systems on the Brazilian coast (Valentin, 1999), and if higher productivity is correlated with a higher rate of supply and variety of resources offered (Begon et al., 2006), then it is reasonable to assume that this attribute is one of the pillars of the high species richness in this ecosystem. Besides primary and secondary production, another prominent characteristic of Guanabara Bay is its large size, which encompasses a wide spatial heterogeneity containing various microhabitats and shelter options for juveniles, extending the resource spectrum and favouring growth and reproduction of estuarine

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 ICHTHYOFAUNA OF ESTUARINE TROPICAL BAY 835 species (Blaber, 2000). The high species richness in Guanabara Bay is an indication of its capability to sustain numerous and abundant fish populations, including commercially important species, playing a role as a source of individuals for particular populations (estuarine-dependent) from the source-sink meta-community perspective (Leibold et al., 2004). Richness is directly associated with diversity, which can increase the stability of the whole system, and apparently enhances robustness to overexploita- tion of fisheries resources (Worm et al., 2006).

This study is part of the programme ‘Environmental Assessment of Guanabara Bay’ co-ordinated and funded by CENPES – PETROBRAS, which has given permission for the publication of the results. The study was undertaken in conjunction with the Laboratory of Fisheries Biology and Technology, Federal University of Rio de Janeiro, which was responsible for the biological monitoring framework.

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© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 838 D. R. DA SILVA ET AL. APPENDIX C) from the bottom water sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) dry months. ∘ APPENDIX I. Spatial pattern of temperature (

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 ICHTHYOFAUNA OF ESTUARINE TROPICAL BAY 839 b) dry months. APPENDIX II. Spatial pattern of salinity from the bottom water sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 840 D. R. DA SILVA ET AL. M) from the bottom water sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) 𝜇 dry months. APPENDIX III. Spatial pattern of total phosphorous (

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 ICHTHYOFAUNA OF ESTUARINE TROPICAL BAY 841 ) from the bottom water sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy 1 − and (b) dry months. APPENDIX IV. Spatial pattern of total dissolved oxygen (mg l

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846 842 D. R. DA SILVA ET AL. M) from the bottom water sampled from July 2005 to June 2007 in Guanabara Bay, Rio de Janeiro, in the (a) rainy and (b) dry 𝜇 months. APPENDIX V. Spatial pattern of ammonium (

APPENDIX VI. Absolute abundance, constancy (% monthly) and preferential habitat of all fish species caught in Guanabara Bay, Rio de Janeiro, from July 2005 to June 2007

Feeding Estuarine Absolute mode use abundance Constancy functional functional Species Family (n) % (monthly) group Habitat group

Chilomycterus spinosus Diodontidae 14 842 100 Zoobenthivore SB MEO spinosus Genidens genidens Ariidae 14 425 100 Opportunist SB MED Micropogonias furnieri Sciaenidae 13 604 100 Zoobenthivore SB MED Cetengraulis edentulus Engraulidae 3954 100 Zooplanktivore P MM Cynoscion jamaicensis Sciaenidae 3501 100 Zoobenthivore SB MEO Eucinostomus argenteus Gerreidae 3248 100 Zoobenthivore SB MED Orthopristis ruber Haemulidae 3217 100 Zoobenthivore SB MEO Prionotus punctatus Triglidae 2947 100 Zoobenthivore SB MEO Ctenosciaena Sciaenidae 2776 100 Zoobenthivore SB MEO gracilicirrhus Genidens barbus Ariidae 1552 100 Opportunist SB MED Chloroscombrus Carangidae 1052 91·7 Zooplanktivore P MS chrysurus Dactylopterus volitans Dactylopteridae 836 100 Zoobenthivore SB MEO Etropus crossotus Paralichthyidae 731 100 Zoobenthivore SB MED Selene setapinnis Carangidae 651 95·8 Zoobenthivore SB MS Eucinostomus gula Gerreidae 587 100 Zoobenthivore SB MEO Trichiurus lepturus Trichiuridae 528 100 Piscivore P MEO Sphoeroides greeleyi Tetraodontidae 525 100 Zoobenthivore SB ER Diapterus rhombeus Gerreidae 490 100 Omnivore SB MED Diplectrum radiale Serranidae 419 100 Zoobenthivore SB MEO Lagocephalus Tetraodontidae 353 95·8 Zoobenthivore SB MM laevigatus Symphurus tessellatus Cynoglossidae 348 100 Zoobenthivore SB MED Brevoortia aurea Clupeidae 339 62·5 Zooplanktivore P MED Stephanolepis hispidus Monacanthidae 247 100 Omnivore SB MEO Harengula clupeola Clupeidae 243 70·8 Zooplanktivore P MM Synodus foetens Synodontidae 236 95·8 Zoobenthivore SB MEO Cynoscion leiarchus Sciaenidae 201 54·2 Zoobenthivore SB MEO Chirocentrodon Pristigasteridae 174 62·5 Planktivore P MM bleekerianus Peprilus paru Stromateidae 158 45·8 Zooplanktivore P MEO Diplectrum formosum Serranidae 117 87·5 Zoobenthivore SB MEO Citharichthys macrops Paralichthyidae 112 83·3 Zoobenthivore SB MEO Syacium papillosum Paralichthyidae 112 79·2 Zoobenthivore SB MEO Larimus breviceps Sciaenidae 107 37·5 Zoobenthivore SB MED Anchoa lyolepis Engraulidae 80 25 Zooplanktivore P MM Gobionellus oceanicus Gobiidae 80 70·8 Zoobenthivore SB ER Stellifer rastrifer Sciaenidae 80 62·5 Zoobenthivore SB MED Dules auriga Serranidae 79 70·8 Zoobenthivore SB MEO Chaetodipterus faber Ephippidae 77 79·2 Zoobenthivore SB MEO Cathorops spixii Ariidae 72 37·5 Zoobenthivore SB MED Anchoa tricolor Engraulidae 68 62·5 Zooplanktivore P MM Trachinotus falcatus Carangidae 63 12·5 Zoobenthivore SB MEO Anchoa januaria Engraulidae 62 54·2 Zooplanktivore P MM

APPENDIX VI. Continued

Feeding Estuarine Absolute mode use abundance Constancy functional functional Species Family (n) % (monthly) group Habitat group

Sphoeroides tyleri Tetraodontidae 61 83·3 Zoobenthivore SB MEO Citharichthys Paralichthyidae 59 66·7 Zoobenthivore SB MEO spilopterus Cynoscion striatus Sciaenidae 56 29·2 Zoobenthivore SB MEO Sphoeroides testudineus Tetraodontidae 49 75 Zoobenthivore SB MEO Upeneus parvus Mullidae 41 33·3 Zoobenthivore SB MEO Bothus robinsi Bothidae 40 62·5 Zoobenthivore SB MS Gymnura altavela Gymnuridae 38 83·3 Zoobenthivore SB MM Mullus argentinae Mullidae 37 20·8 Zoobenthivore SB MEO Menticirrhus Sciaenidae 36 66·7 Zoobenthivore SB MEO americanus Pellona harroweri Pristigasteridae 35 29·2 Zooplanktivore P MM Selene vomer Carangidae 33 45·8 Zoobenthivore SB MED Sardinella brasiliensis Clupeidae 32 41·7 Zooplanktivore P MM Porichthys porosissimus Batrachoididae 28 41·7 Zoobenthivore SB MEO Sphyraena guachancho Sphyraenidae 21 33·3Piscivore P MS Syacium micrurum Paralichthyidae 19 29·2 Zoobenthivore SB MS Zapteryx brevirostris Rhinobatidae 17 37·5 Zoobenthivore SB MS Priacanthus arenatus Priacanthidae 16 33·3 Zoobenthivore HB MEO Elops saurus Elopidae 13 29·2 Zoobenthivore SB MED Cynoscion acoupa Sciaenidae 12 20·8 Zoobenthivore SB MEO Achirus lineatus Achiridae 11 29·2 Zoobenthivore SB MEO Gymnothorax ocellatus Muraenidae 11 45·8 Zoobenthivore SB MEO Paralonchurus Sciaenidae 11 29·2 Zoobenthivore SB MEO brasiliensis Pogonias cromis Sciaenidae 11 20·8 Zoobenthivore SB MEO Bothus ocellatus Bothidae 10 33·3 Zoobenthivore SB MED Menticirrhus littoralis Sciaenidae 9 25 Zoobenthivore SB MEO Anchoa marinii Engraulidae 8 12·5 Zooplanktivore P MM Stellifer stellifer Sciaenidae 8 4·2 Zoobenthivore SB MED Calamus penna Sparidae 7 20·8 Zoobenthivore SB + HB MS Dasyatis hypostigma Dasyatidae 7 16·7 Zoobenthivore SB MM Umbrina coroides Sciaenidae 7 16·7 Zoobenthivore SB MEO Scorpaena isthmensis Scorpaenidae 6 25 Zoobenthivore HB MEO Trinectes paulistanus Achiridae 6 25 Zoobenthivore SB MED Boridia grossidens Haemulidae 5 12·5 Zoobenthivore SB MEO Hyporthodus niveatus Serranidae 5 8·3 Zoobenthivore HB MEO Mugil liza Mugilidae 5 16·7DetritivoreSBMEO Odontognathus Pristigasteridae 5 16·7 Planktivore P MM mucronatus Opisthonema oglinum Clupeidae 5 12·5 Zooplanktivore P MM Paralichthys Paralichthyidae 5 12·5 Zoobenthivore SB MS patagonicus Symphurus Cynoglossidae 5 16·7 Zoobenthivore SB MEO diomedeanus Trachurus lathami Carangidae 5 16·7 Zoobenthivore SB MS Bathygobius soporator Gobiidae 4 8·3 Omnivore SB ER

APPENDIX VI. Continued

Feeding Estuarine Absolute mode use abundance Constancy functional functional Species Family (n) % (monthly) group Habitat group

Etropus longimanus Paralichthyidae 4 12·5 Zoobenthivore SB MED Hippocampus reidi Syngnathidae 4 12·5 Zooplanktivore HB MEO Isopisthus parvipinnis Sciaenidae 4 8·3 Zoobenthivore SB MED Rhinobatos horkelii Rhinobatidae 4 16·7 Zoobenthivore SB MS Trachinotus carolinus Carangidae 4 8·3 Zoobenthivore SB MS Umbrina canosai Sciaenidae 4 8·3 Zoobenthivore SB MEO Achirus declivis Achiridae 3 12·5 Zoobenthivore SB MEO Aluterus schoepfi Monacanthidae 3 8·3 Herbivore SB MS Archosargus Sparidae 3 8·3OmnivoreSBMEO rhomboidalis Conodon nobilis Haemulidae 3 12·5 Zoobenthivore SB MEO Cyclopsetta chittendeni Paralichthyidae 3 12·5 Zoobenthivore SB MS Hyporthodus nigritus Serranidae 3 8·3 Zoobenthivore HB MEO Mugil curema Mugilidae 3 12·5 Detritivore SB DM Paralichthys Paralichthyidae 3 12·5 Zoobenthivore SB MS orbignyanus Aluterush eudelotii Monacanthidae 2 8·3 Herbivore SB MS Bairdiella ronchus Sciaenidae 2 8·3 Zoobenthivore SB MED Caranx latus Carangidae 2 8·3PiscivoreSBMS Centropomus parallelus Centropomidae 2 8·3 Zoobenthivore SB DM Cynoscion Sciaenidae 2 4·2 Zoobenthivore SB MEO microlepidotus Echeneis naucrates Echeneidae 2 8·3PiscivoreP MS Engraulis anchoita Engraulidae 2 8·3 Planktivore P MM Notarius grandicassis Ariidae 2 4·2 Opportunist SB MED Ophichthus gomesii Ophichthidae 2 8·3 Zoobenthivore SB MEO Polydactylus virginicus Polynemidae 2 8·3 Zoobenthivore SB MED Rhinobatos percellens Rhinobatidae 2 8·3 Zoobenthivore SB MS Stellifer brasiliensis Sciaenidae 2 8·3 Zoobenthivore SB MED Acanthostracion sp. Ostraciidae 1 4·2 Zoobenthivore P MS Anisotremus virginicus Haemulidae 1 4·2 Zoobenthivore HB MS Antennarius striatus Antennariidae 1 4·2PiscivoreSBMS Aspistor luniscutis Ariidae 1 4·2 Zoobenthivore SB MEO Atherinella brasiliensis Atherinopsidae 1 4·2 Zooplanktivore P ER Centropomus Centropomidae 1 4·2 Piscivore SB DM undecimalis Chilomycterus Diodontidae 1 4·2 Zoobenthivore P MS reticulatus Dasyatis guttata Dasyatidae 1 4·2 Zoobenthivore SB MM Diplodus argenteus Sparidae 1 4·2 Herbivore HB MEO argenteus Fistularia petimba Fistulariidae 1 4·2PiscivoreHBMEO Fistularia tabacaria Fistulariidae 1 4·2PiscivoreHBMEO Haemulon steindachneri Haemulidae 1 4·2 Zoobenthivore HB MEO

APPENDIX VI. Continued

Feeding Estuarine Absolute mode use abundance Constancy functional functional Species Family (n) % (monthly) group Habitat group

Mycteroperca Serranidae 1 4·2 Zoobenthivore HB MEO microlepis Nebris microps Sciaenidae 1 4·2 Zoobenthivore SB MED Oligoplites saurus Carangidae 1 4·2PiscivoreP MS Pomadasys Haemulidae 1 4·2 Zoobenthivore SB MEO corvinaeformis Scorpaena brasiliensis Scorpaenidae 1 4·2 Zoobenthivore SB MEO Scorpaena plumieri Scorpaenidae 1 4·2 Zoobenthivore HB MEO Sphyraena tome Sphyraenidae 1 4·2PiscivoreP MS Strongylura marina Belonidae 1 4·2 Zooplanktivore P MEO Syngnathus folletti Syngnathidae 1 4·2 Zooplanktivore SB MED Synodus myops Synodontidae 1 4·2 Zoobenthivore SB MS

Habitat: SB, soft bottom; HB, hard bottom; P, pelagic. Estuarine use functional group: MM, marine migrants; MEO, marine estuarine-opportunists; MED, marine estuarine-dependents; ER, estuarine residents; DM, diadromous migrants; MS, marine straggler.