Building a baseline: a survey of the composition and distribution of the ichthyofauna of Guanabara Bay, a deeply impacted estuary

Clara V. Teixeira-Leite¹ and Marcelo Vianna¹

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Abstract​

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Introduction​

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Estuaries are highly dynamic coastal environments that exhibit a wide range of salinity, nutrient, and temperature variations, providing habitats, resources, and shelter to a variety of species at different life cycle stages (Silva-Junior et al., 2016; Wolanski, Elliott, 2016). Estuaries function as important nursery and feeding areas (Corrêa, Vianna, 2015; Santos et al., 2015; Andrade et al., 2016; Mérigot et al., 2017; Gonçalves-Silva, Vianna, 2018b), which are essential for the maintenance of several marine fish stocks (Santos et al., 2020). Even though these environments are known to contain few strictly resident species (Andrade-Tubino et al., 2008; Vianna et al., 2012; Silva-Junior et al., 2016; Gonçalves-Silva, Vianna, 2018a), their ichthyofaunal diversity displays a rich taxonomic composition, including many species of economic interest and others at serious risk of extinction.

The Guanabara Bay is the second largest Brazilian estuary, located in the metropolitan region of the state of Rio de Janeiro, presenting significant historical, environmental, touristic, and scenic importance. The bay also comprises an essential part of Rio de Janeiro’s economy, since it harbors a major port area and supports the most productive estuarine fisheries in the region (Prestrelo, Vianna, 2016). Guanabara Bay has historically suffered from a series of human impacts associated to huge solid waste, untreated domestic sewage, and persistent pollutant inputs, such as metals and hydrocarbons (Pereira et al., 2007; Rosenfelder et al., 2012; Silva-Junior et al., 2012, 2016; Hauser-Davis et al., 2019a; Paiva et al., 2021). Despite several impacts, this estuary is still ecologically relevant and is considered an area with the potential to become a priority for Brazilian conservation according to guidelines of the Brazilian National Biodiversity Commission (Teixeira-Leite et al., 2018).

Guanabara bay’s ichthyofauna is historically a common target of scientific studies (e.g., Gomes et al., 1974; Toledo et al., 1983; Brum et al., 1995; Brum, 2000; Baêta et al., 2006; Vasconcellos et al., 2010; Mulato et al., 2015) as many research centers are located around the bay (e.g., Universidade Federal do Rio de Janeiro, Universidade Federal do Estado do Rio de Janeiro, Universidade Federal Fluminense, Universidade do Estado do Rio de Janeiro). However, knowledge on several aspects of the bay’s biodiversity was dispersed over the years in different literature, hindering a more comprehensive understanding of the bay’s fish diversity. Reliable and informative inventories are important to promote the conservation and adequate management of natural areas (Reis-Filho et al.,2010; Silveira et al., 2010; Sreekanth et al., 2020), in addition to providing a baseline to assess how environmental changes and human impacts affect temporal community variations (Sheaves, 2006). Vianna et al. (2012) made a first attempt to gather past knowledge of the bay’s ichthyofauna by developing a list of local species, but most of the information they recovered was not based on published articles that went through proper critical peer-review. In addition, since 2012 new research initiatives that monitor experimental collections and fishing landings carried out by research groups (e.g., Laboratório de Biologia e Tecnologia Pesqueira – BioTecPesca/UFRJ, Universidade Federal do Rio de Janeiro) have promoted a considerable increase in knowledge concerning the ichthyofauna of the bay.

The aim of this study is therefore to develop a baseline of Guanabara Bay’s ichthyofauna, to achieve a better understanding of the composition, distribution, and richness of fish species in the bay. The use of reliable past data (e.g., articles published in indexed journals, voucher specimens deposited in ichthyological collections, biological samplings and fishing landings monitored by BioTecPesca/UFRJ) make this inventory a basis for comparison for future studies. It also potentially reveals changes in species composition that have already taken place throughout history.

Material and methods

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Study area. TheGuanabara Bay (22°59’02.20’’S – 22°40’23.66’’S; 43°01’26.53’’W – 43°17’26.08”W) is a semi-enclosed tropical estuary located on the southeastern coast of Brazil, in the state of Rio de Janeiro, covering 384 km², with an average volume of 1.87 x 10⁹ m³ of water, and a 4,080 km² drainage basin with maximum depth of 50 m in the central channel (Meniconi et al., 2012; Silva-Junior et al., 2016). It is characterized by seasonal salinity variations influenced by a connection with oceanic waters, the local rainfall regime, and tides. During the low rainfall period (June to August), the water column is more homogeneous, with little temperature and salinity variations, becoming vertically stratified during the rainy season (December to March), with the appearance of upwelling areas due to the penetration of the South Atlantic Central Water (SACW) that enters the estuary through its saline wedge (Valentin et al., 1999; Silva-Junior et al., 2016).

The bay is categorized into three compartments (sensu Silva-Junior et al., 2016; Souza, Vianna, 2022): (i) the lower estuary, corresponding to the central channel and its banks, comprising the area suffering the greatest influence of the oceanic waters that enter the bay; (ii) the middle estuary, consisting of an intermediate transition area between the more saline waters of the lower estuary and the more brackish waters of the upper estuary, and (iii) the upper estuary, the innermost bay region under greater influence of continental waters from the local hydrographic basin.

The Guanabara Bay entrance was defined as the shortest distance between the east and west coasts (limit line, from the point of Forte São José, 22°56’24.41”S 43° 09’06.66”W to the point of Fortaleza de Santa Cruz da Barra, 22°56’16.97”S 43°08’06.30”W). Therefore, all records external to this line were considered as outside the estuarine region and were not included in our inventory. The bay was also divided into quadrants using the Quantum GIS (QGIS) software version 3.16.5 according to the same grid applied by the fishing landing monitoring efforts in Guanabara Bay (Prestelo, Vianna, 2016) (Fig. 1).

FIGURE 1| Guanabara Bay map, Rio de Janeiro, divided into five km x five km quadrants. Different shades of blue indicate which estuary compartment (upper, middle or lower) the quadrant belongs to.

Data compilation. Different strategies were employed to gather ichthyofaunal records in the Guanabara Bay. First, we made a compilation of scientific literature concerning the bay’s ichthyofauna. A scientometric analysis was carried out at the Web of Science, SciELO and Scopus portals, covering articles from all available years, i.e., from 1921 to March 23, 2021. The search method applied two keyword fields linked by the connectors “AND” and “OR”, the first referring to the study location (Guanabara Bay) and the second to the study group (ichthyofauna) (Tab. 1). We added to the scientometric analysis results other published articles that were previously known by the authors. Then, data from two sets of fish samplings carried out by BioTecPesca/UFRJ were added to the database. These bottom trawl samplings were carried out from 2005 to 2007 at quadrants C3, C5, D5, D7, E3, E5 and E7; and from 2013 to 2015 at quadrants C5 and D5. In addition, the records of species identified in two artisanal fishing landing monitoring programs at Guanabara Bay based on different commercial fishing gear (also carried out by BioTecPesca/UFRJ) were considered, the first in 2009 and 2010, and the second in 2013 and 2014.

TABLE 1 | Keywords used in the scientometric search on fish at Guanabara Bay, Rio de Janeiro.

Historical records were obtained from the online databases of the fish collections of Museu de Zoologia da Universidade de São Paulo, São Paulo (MZUSP) (records available online at https://mz.usp.br/pt/laboratorios/ictiologia/ accessed on July 30, 2020) and the Museu Nacional, Universidade Federal do Rio de Janeiro, Rio de Janeiro (MNRJ) (records available online at https://ipt.sibbr.gov.br/mnrj/resource?r= mnrj_ictiologia, accessed on July 30, 2020). In addition, we included to our data compilation the listings made by the BioTecPesca/UFRJ research group deposited at the Coleção de Peixes do Instituto de Biodiversidade e Sustentabilidade, Universidade Federal do Rio de Janeiro (NPM). The SpeciesLink Network (http://www.specieslink.net/) was used as another tool to compile records from several scientific collections. “Guanabara” was employed as keyword and the records were filtered by taxon to include only fishes, considering all reports until July 21, 2020. All lot numbers of species included in our database are available in Tab. S1.

Regardless of the strategy employed, records were considered only at the species level, with species without previous confirmed records in the state of Rio de Janeiro considered as doubtful records and not included in the baseline. Records at genus or family level were also not considered. Taxonomic classification (at species level and above) and species known distribution followed the Eschmeyer’s Catalog of Fishes (Fricke et al., 2023). As this study comprised only the Guanabara Bay, records obtained from local watershed rivers were not considered. Records from ichthyoplankton studies were also not included in our compilation. The historical baseline was built on data available until 2020, therefore we did not include records made after this year. However, we added the information of a few records made after this time-period in the Results section due to their ecological relevance. These include the first record of Galeocerdo cuvier (Perón & Lesueur, 1822) in Guanabara Bay and records of species that had not been recorded in the last decade (Bagre bagre (Linnaeus, 1766)) and Rhizoprionodon lalandii (Valenciennes, 1839)).

The selected records were used to build a baseline containing the currently valid name of the species, the year of the record, and the quadrant or quadrants where the species was recorded, if the information was available. When the exact year of collection was not indicated, the year of publication of the reference was considered as the date of the record. To generate a more complete inventory, the FishBase platform (https://www.fishbase.se) and specific literature on each species were used to obtain information on (i) feeding and functional guilds in the estuary (standardized according to Elliott et al., 2007) and (ii) habitat (standardized according to Silva-Junior et al., 2016). Finally, information on the extinction risk of each species was considered at both the global and Brazilian level, according to the IUCN Red List of Threatened Species (http://www.iucnredlist.org) and the Livro vermelho da fauna brasileira ameaçada de extinção (Subirá et al., 2018), respectively.

Data analysis. One of the main difficulties of studies that aim to assess the species richness of a given locality is to determine whether the employed sampling effort was sufficient to accurately estimate the richness (Schilling et al., 2012). As our study consisted on building a reference database using previously generated data, the number of sources consulted was considered as a unit of sampling effort. Thus, four absolute richness accumulation (S) curves by effort were constructed using the R software version 3.6.0, considering one for the bay as a whole and one for each of the three compartments of its estuary (low, medium and upper). In all cases, the random sample-based rarefaction method was used (Gotelli, Colwell, 2001) employing 100,000 permutations. In order to further understand the results of the curves, the non-parametric estimator for incidence data Chao2 was applied to each curve (Chao et al., 2009) which, in addition to allowing the verification of curve stabilization (reaching an asymptote), also provides a series of other information (Tab. 2). One of the advantages of using this estimator is the possibility to obtain “mg” values, since “g” values can be converted into percentages. In this context, if for a given “g” value extra collections are not necessary (null mg), then it is confirmed that the study in question was able to record the “g” of the percentage of total richness. A graph was also constructed for each rarefaction curve, where the x axis corresponds to “g” values and the y axis, to “mg” values.

TABLE 2 | Variables related to the non-parametric Chao2 estimator. The t, T, S obs, Q1 and Q2 values are used to calculate S est, q0, m and mg.

Concerning the spatial richness distribution, accumulation of absolute richness (S) values of each water quadrant was plotted on the bay map employing the QGIS software version 3.16.5. As each quadrant has its own water surface area (discounting portions of land, such as islands and coastlines), species density (S/water surface area) was also calculated in each one of them to obtain comparable results.

Finally, considering the bay’s history of environmental degradation and fishing exploitation, we expected the ichthyofaunal composition to change over the years. In this context, the temporal range of our baseline (1889 to 2020) was divided into decades to identify species that no longer occur in the bay, or that are at least rare now. We considered recent all records made from 2010 to 2020, because since 2010 there were no one-off impact events (e.g., oil spills) that may have affected the ichthyofaunal composition. Therefore, for this study purposes, the 10 years period between 2010 and 2020 (last decade) represent the recent state of the bay.

Results​

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Ichthyofauna richness and composition. The scientometric analysis resulted in a total of 176 published articles, 70 of which fitted the criteria described in Data compilation and were included in this study. Assembling all data compilation strategies, we considered a total of 84 different data sources. A total of 220 species (203 teleosts and 17 elasmobranchs) were recorded, distributed in 149 genera (136 teleosts and 13 elasmobranchs) and 72 families (61 teleosts and 11 elasmobranchs) (Tab. 3). Regarding the Teleostei, a very asymmetrical richness distribution was noted among families given that 14 families make up about 50% of the total recorded richness. Among these, the Sciaenidae included the highest number of species (23), followed by Carangidae (14) and Haemulidae (8). Concerning elasmobranchs, the numerical variation of species between families was lower, with the Dasyatidae and Carcharhinidae including three species each, followed by Sphyrnidae and Rhinobatidae with two species. Other families of the Elasmobranchii are represented by just one species each.

TABLE 3 | Species reported at Guanabara Bay and the sources, record dates and quadrants (column Q) in which these records occurred. Taxonomic classification (at species level and above) followed the Eschmeyer’s Catalog of Fishes (Fricke et al., 2023). New records made after 2020 (*), first published in our study, are not included in the data analysis. Column “FD” corresponds to feeding guilds, where DV = detritivore, HV = herbivore, OV = omnivore, OP = opportunist, PV = piscivore, ZB = zoobenthivore, ZP = zooplanktivore. Column “H” corresponds to habitat, where P = pelagic, SB = non-consolidated substrate (soft bottom) and HB = consolidated substrate (hard bottom). The column “EG” corresponds to the estuarine guild, where AM = amphidromous, ER = estuarine resident, MED = marine estuarine-dependent, MEO = marine estuarine-opportunistic, MM = marine migrant, MS = marine straggler and AS = semi-anadromous. IUCN = IUCN Red List of Threatened Species, and ICMBio = Livro vermelho da fauna brasileira ameaçada de extinção (Subirá et al., 2018). Source numbering available at Tab. S2.