Spatial patterns of distribution and the influence of ... - Semantic Scholar

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 of fish 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 availability, 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: [email protected]

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D . R . D A S I LVA E T A L.

central goals of estuarine fish ecology. Studies on many of these systems have identified temperature, freshwater input, salinity, dissolved oxygen and transparency as the 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 S T U DY A R E A 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

© 2016 The Fisheries Society of the British Isles, Journal of Fish Biology 2016, 89, 821–846

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I C H T H Y O FAU N A O F E S T U A R I N E T R O P I C A L B AY

Magé

Duque de Caxias

700 000

BG-24 BG-20

BG-31 BG-29 BG-28

685 000

690 000

695 000

700 000

Magé

Duque de Caxias

BG-22

Paquetá Island

BG-26

680 000

BG-17 Upper bay

Paquetá Island

7 483 000

695 000

7 483 000

690 000

7 490 000

(b) 685 000

680 000

7 490 000

(a)

Duque de Caxias

São Gonçalo

BG-34

Governador Island

Central Channel Gradim

São Gonçalo

7 476 000

BG-15

BG-12 BG-11

BG-10

7 476 000

BG-16

Governador Island BG-13

BG-09

BG-01 Seaward end

Niterói Rio de Janeiro

2·5

Entrance Seaward end

N

0

7 469 000

C.P. Rio de Janeiro - Praça Mauá

Niterói

7 462 000

BG-02

Rio de Janeiro

BG-03

7 462 000

Lower bay C.P. Rio de Janeiro - Praça Mauá BG-04

Governador Island

7 469 000

BG-07

N

5 km

10

SAD 1969 UTM Zone 23S

0

2·5

5

10

SAD 1969 UTM Zone 23S

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 1·6 m s−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 20∘ C and salinity > 36; Matsuura, 1986) are driven by the Brazil current during the rest of the year (Brandini, 1990).


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E N V I R O N M E N TA L D R I V E R S 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 [2·8–3·7 km h−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 0·1 g. No sub-sampling method was employed. The catch per unit effort (CPUE) was used to estimate abundance (number of individuals = 0·5 h−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). D ATA A N A LY S I S 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 (I RI ) (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 I RI . 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)


30

60 No data available

80

20

40

2005

2006

May

June

April

March

February

January

December

October

November

September

July

August

May

June

April

March

January

February

December

October

0

November

0

September

20

July

10

August

Temperature (° C)

40

Total precipitation (mm)

825


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, where x 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 C H A R A C T E R I Z AT I O N O F E N V I R O N M E N TA L PAT T E R N S

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 indicates 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


Dissolved oxygen (mg l−1 )

Ammonium (𝜇M)

Total phosphorus (𝜇M)

Salinity

Temperature (∘ C)

Season

Area

Dissolved oxygen (mg l−1 )

Ammonium (𝜇M)

Total phosphorus (𝜇M)

Salinity

Temperature (∘ C)

Season

Area

Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum

Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum Mean ± s.d. Minimum–maximum

21·5 ± 2·3 17·0–25·0 34·6 ± 0·5 33·4–35·8 2·2 ± 1·7 0·9–11·2 8·1 ± 7·4 0·2–41·5 3·3 ± 0·6 1·1–4·3

Rainy (17)

23·4 ± 1·7 20·0–27·0 33·6 ± 0·9 32·2–35·6 3·9 ± 0·6 3·0–4·9 24·9 ± 12·7 5·2–51·4 2·1 ± 1·2 0·7–3·9

Dry (7) 23·0 ± 2·2 17·0–28·0 32·4 ± 1·4 29·1–34·4 3·7 ± 1·2 1·3–6·8 29·3 ± 19·9 1·7–102·6 2·5 ± 1·4 0·7–7·0

Rainy (17)

Governador Island

21·9 ± 2·0 18·0–25·0 34·8 ± 0·6 33·8–35·7 2·1 ± 0·6 1·3–3·6 9·9 ± 6·2 0·3–20·2 3·4 ± 0·8 2·1–4·9

Dry (7)

Central Channel

23·6 ± 2·2 20·0–27·0 32·1 ± 1·3 29·7–33·7 3·2 ± 0·8 1·5–4·6 7·8 ± 8·0 0·2–21·4 3·1 ± 2·2 0·2–8·0

Dry (7)

23·5 ± 1·5 21·0–27·0 31·1 ± 1·6 27·5–33·4 4·6 ± 1·3 2·7–9·5 31·3 ± 16·4 2·2–82·4 2·0 ± 1·5 0·0–6·2

Rainy (17)

24·2 ± 2·2 20·0–29·0 29·3 ± 3·1 18·8–33·6 3·8 ± 2·4 1·1–16·2 9·1 ± 9·0 0·2–33·0 2·7 ± 1·4 0·5–5·6

Rainy (17)

Gradim

23·8 ± 2·5 20·0–28·0 32·8 ± 0·9 30·8–33·9 3·9 ± 1·4 2·0–7·6 42·1 ± 50·2 7·4–198·1 3·0 ± 2·8 1·3–12·3

Dry (7)

Duque de Caxias

21·1 ± 2·5 16·0–26·0 34·9 ± 0·6 33·4–36·1 1·4 ± 0·7 0·5–4·6 4·2 ± 5·3 0·1–29·2 4·3 ± 0·6 2·4–5·2

Rainy (17)

23·9 ± 2·3 20·0–28·0 32·8 ± 0·9 31·1–34·1 3·3 ± 0·8 2·0–4·7 16·9 ± 14·0 0·4–51·5 3·2 ± 1·3 1·3–5·1

Dry (7)

24·1 ± 1·7 21·0–28·0 30·4 ± 2·4 22·6–33·5 3·7 ± 1·0 2·1–6·2 21·7 ± 12·3 0·6–45·7 2·4 ± 1·3 0·2–6·7

Rainy (17)

Paquetá Island

21·6 ± 1·8 18·0–24·0 35·1 ± 0·5 34·2–35·8 1·4 ± 0·5 0·6–2·5 3·8 ± 4·4 0·3–16·9 4·4 ± 0·6 3·2–5·4

Dry (7)

Entrance

Table I. Environmental variables of each area sampled in the dry and rainy periods (number of months given in parentheses) in Guanabara Bay, including temperature, salinity, total phosphorus, ammonium and dissolved oxygen, from July 2005 to June 2007

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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 distinction 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 0·2 mg l−1 ) and at Paquetá Island during rainy period (0·2 mg l−1 ). Coincidentally, Duque de Caxias and Gradim had higher concentrations, attaining 12·3 and 8·0 mg l−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, comprising 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 drivers was 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.


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

Richness

Diversity

Equitability

Area Season Area v. season Error Area Season Area v. season Error Area Season Area v. season Error Area Season Area v. season Error

Sum of squares

d.f.

Mean square

F

P

310 672 61 764 58 497 2 030 757 1355·64 0·01 163·75 2412·07 9·1130 1·5998 1·2460 24·3028 0·60160 0·23562 0·09526 2·44643

5 1 5 132 5 1 5 132 5 1 5 132 5 1 5 132

62 134 61 764 11 699 15 385 271·13 0·01 32·75 18·27 1·8226 1·5998 0·2492 0·1841 0·12032 0·23562 0·01905 0·01853

4·0388 4·0147 0·7605 – 14·837 0·001 1·792 – 9·899 8·689 1·354 – 6·492 12·713 1·028 –

0·05 – 0·05. , species; , location/season lines; dashes and circle, data groups.


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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 dissimilarities 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 Environmental 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 Meriti, 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 draining 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). R I C H N E S S V. R E G I O N A L I M P O RTA N C E

In addition to the typical environmental characteristics of a tropical estuary, Guanabara 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 productive 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



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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 overexploitation 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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APPENDIX I. Spatial pattern of temperature (∘ 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



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 (b) dry months.



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APPENDIX III. Spatial pattern of total phosphorous (𝜇M) 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 IV. Spatial pattern of total dissolved oxygen (mg l−1 ) 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.



841

APPENDIX V. Spatial pattern of ammonium (𝜇M) 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.



843


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 Absolute mode abundance Constancy functional (n) % (monthly) group

Estuarine use functional Habitat group

Species

Family

Chilomycterus spinosus spinosus Genidens genidens Micropogonias furnieri Cetengraulis edentulus Cynoscion jamaicensis Eucinostomus argenteus Orthopristis ruber Prionotus punctatus Ctenosciaena gracilicirrhus Genidens barbus Chloroscombrus chrysurus Dactylopterus volitans Etropus crossotus Selene setapinnis Eucinostomus gula Trichiurus lepturus Sphoeroides greeleyi Diapterus rhombeus Diplectrum radiale Lagocephalus laevigatus Symphurus tessellatus Brevoortia aurea Stephanolepis hispidus Harengula clupeola Synodus foetens Cynoscion leiarchus Chirocentrodon bleekerianus Peprilus paru Diplectrum formosum Citharichthys macrops Syacium papillosum Larimus breviceps Anchoa lyolepis Gobionellus oceanicus Stellifer rastrifer Dules auriga Chaetodipterus faber Cathorops spixii Anchoa tricolor Trachinotus falcatus Anchoa januaria

Diodontidae

14 842

100

Zoobenthivore

SB

MEO

Ariidae Sciaenidae Engraulidae Sciaenidae Gerreidae Haemulidae Triglidae Sciaenidae

14 425 13 604 3954 3501 3248 3217 2947 2776

100 100 100 100 100 100 100 100

Opportunist Zoobenthivore Zooplanktivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore

SB SB P SB SB SB SB SB

MED MED MM MEO MED MEO MEO MEO

Ariidae Carangidae

1552 1052

100 91·7

Opportunist Zooplanktivore

SB P

MED MS

Dactylopteridae Paralichthyidae Carangidae Gerreidae Trichiuridae Tetraodontidae Gerreidae Serranidae Tetraodontidae

836 731 651 587 528 525 490 419 353

100 100 95·8 100 100 100 100 100 95·8

Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Piscivore Zoobenthivore Omnivore Zoobenthivore Zoobenthivore

SB SB SB SB P SB SB SB SB

MEO MED MS MEO MEO ER MED MEO MM

Cynoglossidae Clupeidae Monacanthidae Clupeidae Synodontidae Sciaenidae Pristigasteridae

348 339 247 243 236 201 174

100 62·5 100 70·8 95·8 54·2 62·5

Zoobenthivore Zooplanktivore Omnivore Zooplanktivore Zoobenthivore Zoobenthivore Planktivore

SB P SB P SB SB P

MED MED MEO MM MEO MEO MM

Stromateidae Serranidae Paralichthyidae Paralichthyidae Sciaenidae Engraulidae Gobiidae Sciaenidae Serranidae Ephippidae Ariidae Engraulidae Carangidae Engraulidae

158 117 112 112 107 80 80 80 79 77 72 68 63 62

45·8 87·5 83·3 79·2 37·5 25 70·8 62·5 70·8 79·2 37·5 62·5 12·5 54·2

Zooplanktivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zooplanktivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zooplanktivore Zoobenthivore Zooplanktivore

P SB SB SB SB P SB SB SB SB SB P SB P

MEO MEO MEO MEO MED MM ER MED MEO MEO MED MM MEO MM


844


APPENDIX VI. Continued Feeding Absolute mode abundance Constancy functional (n) % (monthly) group


Species

Family

Sphoeroides tyleri Citharichthys spilopterus Cynoscion striatus Sphoeroides testudineus Upeneus parvus Bothus robinsi Gymnura altavela Mullus argentinae Menticirrhus americanus Pellona harroweri Selene vomer Sardinella brasiliensis Porichthys porosissimus Sphyraena guachancho Syacium micrurum Zapteryx brevirostris Priacanthus arenatus Elops saurus Cynoscion acoupa Achirus lineatus Gymnothorax ocellatus Paralonchurus brasiliensis Pogonias cromis Bothus ocellatus Menticirrhus littoralis Anchoa marinii Stellifer stellifer Calamus penna Dasyatis hypostigma Umbrina coroides Scorpaena isthmensis Trinectes paulistanus Boridia grossidens Hyporthodus niveatus Mugil liza Odontognathus mucronatus Opisthonema oglinum Paralichthys patagonicus Symphurus diomedeanus Trachurus lathami Bathygobius soporator

Tetraodontidae Paralichthyidae

61 59

83·3 66·7

Zoobenthivore Zoobenthivore

SB SB

MEO MEO

Sciaenidae Tetraodontidae Mullidae Bothidae Gymnuridae Mullidae Sciaenidae

56 49 41 40 38 37 36

29·2 75 33·3 62·5 83·3 20·8 66·7

Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore

SB SB SB SB SB SB SB

MEO MEO MEO MS MM MEO MEO

Pristigasteridae Carangidae Clupeidae Batrachoididae Sphyraenidae Paralichthyidae Rhinobatidae Priacanthidae Elopidae Sciaenidae Achiridae Muraenidae Sciaenidae

35 33 32 28 21 19 17 16 13 12 11 11 11

29·2 45·8 41·7 41·7 33·3 29·2 37·5 33·3 29·2 20·8 29·2 45·8 29·2

Zooplanktivore Zoobenthivore Zooplanktivore Zoobenthivore Piscivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore

P SB P SB P SB SB HB SB SB SB SB SB

MM MED MM MEO MS MS MS MEO MED MEO MEO MEO MEO

Sciaenidae Bothidae Sciaenidae Engraulidae Sciaenidae Sparidae Dasyatidae Sciaenidae Scorpaenidae Achiridae Haemulidae Serranidae Mugilidae Pristigasteridae

11 10 9 8 8 7 7 7 6 6 5 5 5 5

20·8 33·3 25 12·5 4·2 20·8 16·7 16·7 25 25 12·5 8·3 16·7 16·7

Zoobenthivore SB Zoobenthivore SB Zoobenthivore SB Zooplanktivore P Zoobenthivore SB Zoobenthivore SB + HB Zoobenthivore SB Zoobenthivore SB Zoobenthivore HB Zoobenthivore SB Zoobenthivore SB Zoobenthivore HB Detritivore SB Planktivore P

MEO MED MEO MM MED MS MM MEO MEO MED MEO MEO MEO MM

Clupeidae Paralichthyidae

5 5

12·5 12·5

Zooplanktivore Zoobenthivore

P SB

MM MS

Cynoglossidae

5

16·7

Zoobenthivore

SB

MEO

Carangidae Gobiidae

5 4

16·7 8·3

Zoobenthivore Omnivore

SB SB

MS ER


845




Species

Family

Etropus longimanus Hippocampus reidi Isopisthus parvipinnis Rhinobatos horkelii Trachinotus carolinus Umbrina canosai Achirus declivis Aluterus schoepfi Archosargus rhomboidalis Conodon nobilis Cyclopsetta chittendeni Hyporthodus nigritus Mugil curema Paralichthys orbignyanus Aluterush eudelotii Bairdiella ronchus Caranx latus Centropomus parallelus Cynoscion microlepidotus Echeneis naucrates Engraulis anchoita Notarius grandicassis Ophichthus gomesii Polydactylus virginicus Rhinobatos percellens Stellifer brasiliensis Acanthostracion sp. Anisotremus virginicus Antennarius striatus Aspistor luniscutis Atherinella brasiliensis Centropomus undecimalis Chilomycterus reticulatus Dasyatis guttata Diplodus argenteus argenteus Fistularia petimba Fistularia tabacaria Haemulon steindachneri

Paralichthyidae Syngnathidae Sciaenidae Rhinobatidae Carangidae Sciaenidae Achiridae Monacanthidae Sparidae

4 4 4 4 4 4 3 3 3

12·5 12·5 8·3 16·7 8·3 8·3 12·5 8·3 8·3

Zoobenthivore Zooplanktivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Herbivore Omnivore

SB HB SB SB SB SB SB SB SB

MED MEO MED MS MS MEO MEO MS MEO

Haemulidae Paralichthyidae Serranidae Mugilidae Paralichthyidae

3 3 3 3 3

12·5 12·5 8·3 12·5 12·5

Zoobenthivore Zoobenthivore Zoobenthivore Detritivore Zoobenthivore

SB SB HB SB SB

MEO MS MEO DM MS

Monacanthidae Sciaenidae Carangidae Centropomidae Sciaenidae

2 2 2 2 2

8·3 8·3 8·3 8·3 4·2

Herbivore Zoobenthivore Piscivore Zoobenthivore Zoobenthivore

SB SB SB SB SB

MS MED MS DM MEO

Echeneidae Engraulidae Ariidae Ophichthidae Polynemidae Rhinobatidae Sciaenidae Ostraciidae Haemulidae Antennariidae Ariidae Atherinopsidae Centropomidae

2 2 2 2 2 2 2 1 1 1 1 1 1

8·3 8·3 4·2 8·3 8·3 8·3 8·3 4·2 4·2 4·2 4·2 4·2 4·2

Piscivore Planktivore Opportunist Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Zoobenthivore Piscivore Zoobenthivore Zooplanktivore Piscivore

P P SB SB SB SB SB P HB SB SB P SB

MS MM MED MEO MED MS MED MS MS MS MEO ER DM

Diodontidae

1

4·2

Zoobenthivore

P

MS

Dasyatidae Sparidae

1 1

4·2 4·2

Zoobenthivore Herbivore

SB HB

MM MEO

Fistulariidae Fistulariidae Haemulidae

1 1 1

4·2 4·2 4·2

Piscivore Piscivore Zoobenthivore

HB HB HB

MEO MEO MEO


846




Species

Family

Mycteroperca microlepis Nebris microps Oligoplites saurus Pomadasys corvinaeformis Scorpaena brasiliensis Scorpaena plumieri Sphyraena tome Strongylura marina Syngnathus folletti Synodus myops

Serranidae

1

4·2

Zoobenthivore

HB

MEO

Sciaenidae Carangidae Haemulidae

1 1 1

4·2 4·2 4·2

Zoobenthivore Piscivore Zoobenthivore

SB P SB

MED MS MEO

Scorpaenidae Scorpaenidae Sphyraenidae Belonidae Syngnathidae Synodontidae

1 1 1 1 1 1

4·2 4·2 4·2 4·2 4·2 4·2

Zoobenthivore Zoobenthivore Piscivore Zooplanktivore Zooplanktivore Zoobenthivore

SB HB P P SB SB

MEO MEO MS MEO MED 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.
