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Biological attributes and major threats as predictors of the vulnerability of species: a case study with Brazilian reef fishes

Published online by Cambridge University Press:  16 April 2013

M.G. Bender*
Affiliation:
Programa de Pós-graduação em Ecologia e Conservação, Universidade Federal de Paraná, Setor de Ciências Biológicas, Curitiba, PR 81531-980, Brazil
S.R. Floeter
Affiliation:
Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Brazil
F.P. Mayer
Affiliation:
Programa de Pós-graduação em Ecologia, Universidade Federal de Santa Catarina, Florianópolis, Brazil
D.A. Vila-Nova
Affiliation:
Programa de Pós-graduação em Ecologia e Conservação, Universidade Federal de Paraná, Setor de Ciências Biológicas, Curitiba, PR 81531-980, Brazil
G.O. Longo
Affiliation:
Programa de Pós-graduação em Ecologia, Universidade Federal de Santa Catarina, Florianópolis, Brazil
N. Hanazaki
Affiliation:
Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, Brazil
A. Carvalho-Filho
Affiliation:
Fish Bizz Ltda., São Paulo, Brazil
C.E.L. Ferreira
Affiliation:
Departamento de Biologia Marinha, Universidade Federal Fluminense, Niteroi, Brazil
*
(Corresponding author) E-mail maribender@yahoo.com.br
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Abstract

Global biodiversity declines and increasing rates of extinction necessitate the assessment and prediction of the vulnerability of species to extinction. Here, we examine the relationships between conservation status and ecological traits of reef fish species of the Brazilian biogeographical province. We used binomial tests and a logistic regression to address two questions. Do biological attributes differ between threatened and non-threatened fishes? Which combination of traits and impacts exerts greater influence on species threat status? Of the 559 species, 36 are categorized as threatened (compiled from global, national and local Red Lists). Three species are categorized as Critically Endangered, seven as Endangered and 26 as Vulnerable. Our analyses revealed that Elasmobranchii, sex-changing bony fishes and endemic species are the most vulnerable reef fishes in Brazilian waters. Body size and trophic category were identified as good predictors of the vulnerability of a species to extinction. Small-bodied species that are exploited by the ornamental trade and have complex reproductive strategies are also of concern. Such combinations of attributes could be of value in predicting which reef fish species elsewhere have a high risk of extinction.

Type
Papers
Copyright
Copyright © Fauna & Flora International 2013

This paper contains supplementary material that can be found online at http://journals.cambridge.org/orx

Introduction

The ongoing threats to ecosystems are increasing contemporary extinction rates (Soulé, Reference Soulé1991; Purvis et al., Reference Purvis, Gittleman, Cowlishaw and Mace2000). In marine ecosystems anthropogenic pressure, predominantly overexploitation, has led to marked reductions in ranges and population sizes (Dulvy et al., Reference Dulvy, Sadovy and Reynolds2003, 2004; Myers & Worm, Reference Myers and Worm2005; Jackson Reference Jackson2008; Worm & Tittensor, Reference Worm and Tittensor2011), and to the extinction of species (Casey & Myers, Reference Casey and Myers1998; Roberts & Hawkins, Reference Roberts and Hawkins1999; Dulvy et al., Reference Dulvy, Sadovy and Reynolds2003, Reference Dulvy, Ellis, Goodwin, Grant, Reynolds and Jennings2004; del Monte-Luna et al., Reference del Monte-Luna, Lluch-Belda, Serviere-Zaragoza, Carmona, Reyes-Bonilla and Aurioles-Gamboa2007). For reef ecosystems the key drivers of decline are pollution, disease and climate change (Bellwood et al., Reference Bellwood, Hughes, Folke and Nystrom2004; Jackson, Reference Jackson2008). Evaluation of the effect of multiple stressors on the risk of species extinction is essential for conservation planning and prioritization (Mace & Lande, Reference Mace and Lande1991; IUCN, 2001). IUCN provides an objective evaluation system under which species must meet quantitative criteria to be assigned to Red List categories (IUCN, 2001). The IUCN Red List and the categories and criteria used to assess species have become an important tool for management, monitoring and decision making (Rodrigues et al., Reference Rodrigues, Pilgrim, Lamoreux, Hoffmann and Brooks2006). However, evaluations of extinction risk using such methods require population data, which are not available for the majority of species, including reef fishes.

The scarcity of population data combined with the threats to marine ecosystems highlight the urgent need to assess and predict the vulnerability of fishes to multiple stressors (Dulvy et al., Reference Dulvy, Sadovy and Reynolds2003; Cheung et al., Reference Cheung, Pitcher and Pauly2005; Graham et al., Reference Graham, Chabanet, Evans, Jennings, Letourneur and MacNeil2011). Attempts to predict vulnerability to extinction include factors such as species' geographical range, area occupancy and rarity (Hawkins et al., Reference Hawkins, Roberts and Clark2000), ecological specialization (Graham et al., Reference Graham, Chabanet, Evans, Jennings, Letourneur and MacNeil2011), and body size and other life-history traits (Cheung et al. Reference Cheung, Pitcher and Pauly2005). For fish species biological attributes such as slow growth, late maturity and low reproductive output can be correlated to body size, which can thus be used as a predictor of the threat of extinction (Roberts & Hawkins, Reference Roberts and Hawkins1999; Dulvy et al., Reference Dulvy, Sadovy and Reynolds2003; Reynolds et al., Reference Reynolds, Dulvy, Goodwin and Hutchings2005; Olden et al., Reference Olden, Hogan and Zanden2007). Biological traits can help determine the probabilities of local declines, and factors such as range size, occupancy and rarity can indicate declines that could potentially lead to global extinction (Graham et al., Reference Graham, Chabanet, Evans, Jennings, Letourneur and MacNeil2011).Therefore, identifying the attributes and the interactions between traits and extrinsic threats to species at risk can provide information on the vulnerability of species to extinction.

Studies of species decline are commonly used to identify which attributes predispose species to particular threats (Pimm, Reference Pimm1991; Purvis et al., Reference Purvis, Gittleman, Cowlishaw and Mace2000). Such studies can be used as a benchmark to identify vulnerability patterns that could exist among species not yet threatened (Gustafsson, Reference Gustafsson1994; Hero et al., Reference Hero, Williams and Magnusson2005; Kotiaho et al., Reference Kotiaho, Kaitala, Komonen and Paivinen2005). However, such an approach has not previously been used to assess the vulnerability of reef fishes to extinction.

Here we analyse quantitatively the species-specific biological traits and the main anthropogenic threats to threatened and non-threatened reef fishes in the Brazilian biogeographical province (sensu Floeter et al., Reference Floeter, Rocha, Robertson, Joyeux, Smith-Vaniz and Wirtz2008). We address two questions. Do biological attributes differ between threatened and non-threatened fishes? Which combination of traits and impacts exerts greater influence on species threat status?

Methods

Reef fish database

A list of 559 species (509 Teleostei, 50 Elasmobranchii) from the Brazilian province was compiled by A. Carvalho-Filho & S.R. Floeter (unpubl. data). Species distributions are based on Carvalho-Filho (Reference Carvalho-Filho1999) and Floeter et al. (Reference Floeter, Rocha, Robertson, Joyeux, Smith-Vaniz and Wirtz2008). We define reef fishes as any shallow-living (< 100 m) tropical/subtropical benthic or benthopelagic fishes that constantly associate with hard substrates of coral, algal or rocky reefs, or that occupy adjacent sandy substrate (i.e. use reef structures or the surrounding area for reproduction, feeding and/or protection; Floeter et al., Reference Floeter, Rocha, Robertson, Joyeux, Smith-Vaniz and Wirtz2008). Species biological traits (maximum body size: < 10, 10–25, 25–50, > 50 cm; trophic category, after Ferreira et al., Reference Ferreira, Floeter, Gasparini, Joyeux and Ferreira2004: macrocarnivore, herbivore, planktivore, omnivore, mobile benthic invertivore/cleaner, coral/colonial sessile invertivore; reproductive traits: monogamy, nest guarding, mouth brooding, spawning aggregation, sex change; mutualisms) were determined from the available literature (Böhlke & Chaplin, Reference Böhlke and Chaplin1993; Randall, Reference Randall1996; Smith, Reference Smith1997; Carvalho-Filho, Reference Carvalho-Filho1999; Halpern & Floeter, Reference Halpern and Floeter2008) and Fishbase (Froese & Pauly, Reference Froese and Pauly2009). If the maximum length of a species could not be found we assigned the mean value for the genus or family, as appropriate. Potential threats to species (artisanal fishing, game fishing, ornamental trade, bycatch, restricted range/endemism) were based on literature searches of peer-reviewed reports (Haimovici & Klippel, Reference Haimovici and Klippel1999; Gasparini et al., Reference Gasparini, Floeter, Ferreira and Sazima2005; Floeter et al., Reference Floeter, Halpern and Ferreira2006) and were assessed as: 0, no impact; 1, low impact; 2, high impact.

We compiled information on the conservation status of reef fish species from global (IUCN, 2008), national (MMA, 2004, 2005) and local (Brazilian state) Red List inventories. At the regional level we also included information from the 2008 IUCN Workshop for Brazilian Epinephelinae and Lutjanidae Assessment (Subirá et al., Reference Purvis, Gittleman, Cowlishaw and Mace2012). The local inventories (Espírito Santo, Paraná, Rio de Janeiro and Rio Grande do Sul states) are based on IUCN criteria and categories (IUCN, 2001). We considered species to be threatened if they are categorized as Critically Endangered, Endangered or Vulnerable, and non-threatened if categorized as Near Threatened, Least Concern or Data Deficient.

With the exception of endemic species, global conservation status is often not representative of conservation status at the regional scale (Rodríguez et al., Reference Rodríguez, Ashenfelter, Rojas-Suárez, García-Fernández, Suárez and Dobson2000; Gärdenfors, Reference Gärdenfors2001). The transfer of information from global to national assessments could decrease the credibility of national Red Lists and the efficiency of conservation at this level, where actions are most likely to have an impact (Rodríguez et al., Reference Rodríguez, Ashenfelter, Rojas-Suárez, García-Fernández, Suárez and Dobson2000). However, we included data from the global IUCN Red List because only a small number of reef fishes have been evaluated and listed in the national inventory. As we want to provide insights into species that could become threatened, those Brazilian reef fishes that have not been assessed with the IUCN Red List criteria were termed non-threatened, and were compared with threatened species.

Statistical analysis

To identify which trophic groups and body size categories are disproportionately threatened we applied binomial tests (P < 0.05; Zar, Reference Zar2008) to compare threatened and non-threatened species. We also explored the differences in the percentages of threatened and non-threatened Elasmobranchii and endemic species because of concern about the vulnerability of these groups. Sharks and rays appear to be particularly vulnerable to overexploitation because of life-history traits such as slow growth, late sexual maturity, long life spans and low fecundity (Stevens et al., Reference Stevens, Bonfill, Dulvy and Walker2000). The majority (74%) of the species endemic to the Brazilian Province are benthic demersal spawners, with a short planktonic stage and consequently restricted dispersal (Floeter & Gasparini, Reference Floeter and Gasparini2000). Restricted-range species are thought to face a greater risk of extinction than widespread species because local threats and impacts could cause the extinction of such restricted-range species at a global scale (Hawkins et al., Reference Hawkins, Roberts and Clark2000).

We assessed which factors have more influence on the threatened status of species (response variable: threatened, 1; non-threatened, 0) using a logistic regression, which is a special case of Generalized Linear Models (Nelder & Wedderburn, Reference Nelder and Wedderburn1972). Explanatory variables were type (Teleostei, Elasmobranchii), size category (small, medium, large), trophic category (planktivore, herbivore, macrocarnivore, invertebrate feeder), game fishing, artisanal fishing, ornamental trade, bycatch, monogamy, nest guarding, mouth brooding, spawning aggregation, sex change and endemism.

Variables were selected with forward and backward stepwise procedures, using both the Akaike information criterion (AIC; Akaike, Reference Akaike1974) and deviance (D) reduction. We used likelihood ratio tests to identify terms that would significantly reduce the deviance, and could be included in the model. We used a likelihood ratio χ2 statistic as a goodness-of-fit measure. To check the model assumptions we analysed the normal probability plots and the Cook's distance of studentized residuals. The odds ratio (odds of a positive and a negative response) was applied to facilitate interpretation. The probability of Brazilian reef fish species being threatened with extinction were calculated based on predictions from the final model, which were obtained from the estimated parameters. More details can be found in Supplementary Information 1. Analyses were performed using R v. 2.7.2 (R Development Core Team, 2008).

Results

Of the 559 species, 36 Brazilian reef fishes are at risk of extinction at the global, national or regional level (Supplementary Table S1, Fig. 1). From the six Red Lists compiled, four species are considered Critically Endangered, seven Endangered and 25 Vulnerable (Fig. 1). Extinction risk is not distributed evenly, or randomly, across Brazilian reef fish groups: 12 of 106 families contain > 25% of the species at risk of extinction (Supplementary Table S1). The families Epinephelidae and Lutjanidae have 27.7% of the threatened fishes (eight and three species, respectively). Of the threatened species 13 (36.1%) are sharks and rays (26% of the Brazilian Elasmobranchii reef fauna). The percentage of the Elasmobranchii (n = 10) threatened is significantly greater than that of the Teleostei (n = 26; binomial test: p1 > p2, P < 0.0001). Of 21 Near Threatened reef fishes, 16 are in the Elasmobranchii, of which eight are in the Carcharhinidae.

Fig. 1 Number of reef fishes of Brazilian waters in each Red List category on the global IUCN Red List (IUCN, 2008), regional MMA list (MMA 2004, 2005), local lists (Bender et al., Reference Bender, Floeter, Ferreira and Hanazaki2012, and references therein) and the total number of species categorized as threatened (black). Note that the total number does not correspond to the sum of species within the global, regional and local lists because some species have been assessed for several lists. CR, Critically Endangered; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern; DD, Data Deficient.

Fig. 2 Percentage of non-threatened and threatened reef fish species in Brazilian waters in (a) trophic categories and (b) maximum body-size class (large, > 50 cm; medium, 25–50 cm; small–medium, 10–25 cm; small, < 10 cm; *Significant difference at P < 0.05 with the Binomial test).

The macrocarnivores comprise the most threatened trophic group: 21 (58.3%) of the 36 threatened reef fishes (binomial test: p1 > p2 , P < 0.001; Fig. 2a). In addition to top predators, 11 species of mobile invertebrate feeders (30.5%) are amongst the species at risk of extinction (Table 1). Reef fishes that attain large-body sizes are also disproportionately threatened in relation to other length categories (Fig. 2b). The binomial tests also indicated that the percentage of medium (p1 < p2, P < 0.001) and small–medium (p1 < p2, P = 0.04) threatened species is lower than expected.

Table 1 Deviance analysis of the logistic regression model.

1 Likelihood ratio χ2 test applied to the initial model and this model plus each following candidate interaction. Variable interaction that significantly reduces the deviance has P < 0.05.

***P < 0.001; **P < 0.01; *P < 0.05

Of the potential threats the ornamental trade and endemism seem to have the greatest influence on threatened status. The residual deviance (D = 77.82, df = 134) of the logistic regression indicated that the model properly fitted the data (P ∼ 0.99; Table 1). Residual analysis for the final model showed no evidence of any failures in the assumptions. Parameter estimates and odds ratios are given in Supplementary Table S2.

Of the biological traits, type, ability to change sex and body length significantly affected the probability of a species being threatened (Table 1). The model predicted that species most likely to face threats are sharks and rays, sex-changing bony fishes and endemic species (90, 20 and > 6,000 times greater, respectively; Supplementary Table S2). Six reef fish species endemic to the Brazilian Province are at risk of extinction (Supplementary Table S1).

Variable interactions that exert influence on the probability of a species being threatened are the following pairs: sex change–game fishing; type Elasmobranchii/Teleostei–artisanal fishing; and nest guarding–ornamental trade (Table 1). According to the model predictions reef fish species with the highest probabilities of being threatened have the trait combination of invertebrate feeder trophic category, small body size and endemism. Species with lower probabilities of extinction risk are medium-sized planktivores. However, there are several trait combinations that can generate similar threat probabilities for different species (Supplementary Table S3). For example, the Brazilian endemic ray Dasyatis marianae (a medium-sized, invertebrate feeder) and the grouper Dermatolepis inermis (a large-bodied macrocarnivore and sex-changing species) both have c. 75% probability of being threatened).

Discussion

The risk of extinction for the reef fishes of Brazilian waters is a result of a combination of fishing pressure and species' traits that enhance their vulnerability to harvesting and habitat loss. Our analysis reveals that biological attributes capable of predicting species susceptibilities are consistent with previous studies (Jennings et al., Reference Jennings, Reynolds and Polunin1999; Musick, Reference Musick1999; Roberts & Hawkins, Reference Roberts and Hawkins1999; Reynolds et al., Reference Reynolds, Dulvy, Goodwin and Hutchings2005; Pinsky et al., Reference Pinsky, Jense, Ricard and Palumbi2011). Despite the small number of threatened species identified in our database these species share many attributes with the non-threatened species, making the former suitable for predicting extinction risks for those not yet threatened (Supplementary Table S3). Species' biological attributes and their interaction with fishing pressure are discussed separately below.

Biological attributes

Of the traits believed to enhance vulnerability to extinction the most widely cited is body size (Jennings et al., Reference Jennings, Reynolds and Polunin1999). This biological feature has been examined in a variety of mammals, birds and fishes, and large-bodied species are consistently more prone to declines or extinctions (Bennet & Owens, Reference Bennett and Owens1997; Jennings et al., Reference Jennings, Reynolds and Polunin1999; Reed & Shine, Reference Reed and Shine2002; Cardillo et al., Reference Cardillo, Mace, Gittleman and Purvis2006). Large-bodied Brazilian reef fishes are disproportionately threatened in relation to other body size categories. Larger fishes are heavily targeted in fisheries and tend to suffer greater declines than smaller fishes (Jennings et al., Reference Jennings, Reynolds and Polunin1999; Dulvy et al., Reference Dulvy, Metcalfe, Glanville, Pawson and Reynolds2000; Stevens et al., Reference Stevens, Bonfill, Dulvy and Walker2000) given the correlated life-history traits that render populations less resilient to exploitation (Coleman et al., Reference Coleman, Koenig, Huntsman, Musick, Eklund and McGovern2000; Reynolds et al., Reference Reynolds, Jennings, Dulvy, Reynolds, Mace, Redford and Robinson2001). However, small-bodied, low trophic level fish species are highly vulnerable to overexploitation (Pinsky et al., Reference Pinsky, Jense, Ricard and Palumbi2011) and climate change disturbances (Graham et al., Reference Graham, Chabanet, Evans, Jennings, Letourneur and MacNeil2011).

Trophic category is another biological attribute that could predict those species with greater vulnerabilities. For mammalian carnivores and birds large-bodied species with sizeable home ranges, low densities and of high trophic level are the most prone to extinction (Gaston & Blackburn, Reference Gaston and Blackburn1995; Cardillo et al., Reference Cardillo, Mace, Gittleman and Purvis2006). This also seems to be the case for many marine fishes (Morris et al., Reference Morris, Roberts and Hawkins2000; Myers et al., Reference Myers, Baum, Shepherd, Powers and Peterson2007; Baum & Worm, Reference Baum and Worm2009), including Brazilian macrocarnivores, which is the most threatened trophic group, many of them being large bodied (Supplementary Table S1). Other high trophic level fishes of Brazilian waters are on the path to extinction risk: 38% of Near Threatened fishes are species of Carcharhinidae. These top predators exert a fundamental influence on marine communities (Heithaus et al., Reference Heithaus, Frid, Wirsing and Worm2008), and changes in abundance modify ecosystem structure, functioning and resilience (Duffy, Reference Duffy2002; Jackson, Reference Jackson2010).

It has been proposed that sex-changing species are more vulnerable to overexploitation because selective fishing pressure affects sex ratios (Hawkins & Roberts, Reference Hawkins and Roberts2003). We found that 33.3% of threatened species were sex changing (of the 12 sex-changing species, eight are groupers) and this trait was identified as an important driver of threat in reef fishes. Many grouper species exhibit protogynous hermaphrodite life histories (Shapiro, Reference Shapiro, Polovina and Ralston1987). Additionally, several groupers spawn in aggregations, and this reproductive strategy is known to increase the vulnerability of a species to overfishing (Cheung et al., Reference Cheung, Pitcher and Pauly2005). However, spawning aggregation was not significant in our model results but this could be because only a small number of species in our study exhibit this behaviour.

Potential threats and their interactions with biological attributes

Our results suggest that species exhibiting nest-guarding behaviour and that are harvested for the ornamental trade are highly vulnerable. Aquarium fisheries have a significant impact on reef fisheries elsewhere (Wood, Reference Wood2001; Sadovy & Vincent, Reference Sadovy, Vincent and Sale2002), and are active along the Brazilian coast (Gasparini et al., Reference Gasparini, Floeter, Ferreira and Sazima2005). Furthermore, many traded species exhibit complex reproductive strategies (Gasparini et al., Reference Gasparini, Floeter, Ferreira and Sazima2005), which are usually associated with their low recruitment rates, possibly leading to population declines.

The size of the geographic range of a species also influences vulnerability and threat status (Purvis et al., Reference Purvis, Gittleman, Cowlishaw and Mace2000), and may be a useful tool in predicting which species are likely to have a higher risk of extinction elsewhere (Hero et al., Reference Hero, Williams and Magnusson2005). Hawkins et al. (Reference Hawkins, Roberts and Clark2000) investigated restricted-range coral reef fishes and found that > 50% of species qualified as threatened. Even though a small range does not necessarily predispose a species to being rare (Hawkins et al., Reference Hawkins, Roberts and Clark2000; 25.1% of the total abundance of South-western Atlantic reef fishes are endemic species) many endemics are highly threatened (Gasparini et al., Reference Gasparini, Floeter, Ferreira and Sazima2005; Floeter et al., Reference Floeter, Halpern and Ferreira2006). This is the case for large parrot-fishes endemic to Brazil, such as Scarus trispinosus, which is heavily targeted by fisheries (Ferreira & Gonçalves, Reference Ferreira and Gonçalves2006; Francini-Filho et al., Reference Francini-Filho, Moura, Ferreira and Coni2008). We found that endemic species have a high probability of being threatened, especially if this attribute is combined with others such as small body size.

The reef fishes of Brazilian waters are as threatened as fishes elsewhere (Floeter et al., Reference Floeter, Halpern and Ferreira2006), and this is a consequence of similar sources of threat. In addition, the biological attributes that are predictive of the vulnerability of a species to extinction are in accordance with those previously identified for marine fishes (Jennings et al., Reference Jennings, Reynolds and Polunin1999; Musick, Reference Musick1999; Roberts & Hawkins, Reference Roberts and Hawkins1999; Reynolds et al., Reference Reynolds, Dulvy, Goodwin and Hutchings2005). These results strengthen the importance of including species' biological traits into conservation planning analyses, as has been done for Neotropical anurans and mammals (Loyola et al., Reference Loyola, Becker, Kubota, Haddad, Fonseca and Lewinsohn2008a, Reference Loyola, Oliveira, Diniz-Filho and Lewinsohnb).

Making predictions, and thus informing conservation priorities, is one of the goals of trait-based analyses (Fisher & Owens, Reference Fisher and Owens2004; Vila-Nova et al., Reference Vila-Nova, Bender, Carvalho-Filho, Ferreira and Floeter2011). Our results suggest that body size, trophic category, ability to change sex and taxonomic group are good predictors of species vulnerabilities. Special attention needs to be given to small-bodied (Pinsky et al., Reference Pinsky, Jense, Ricard and Palumbi2011), restricted-range species, which have a high probability of being threatened. Such traits can be used as guidelines for global inferences of the extinction risk of fish species.

Acknowledgements

We thank the anonymous reviewers whose critiques helped improve this article.

Biographical sketches

Mariana Bender is interested in the macroecology and conservation of reef fishes. Sergio Floeter’s research focuses on marine biogeography and macroecology, especially that of reef fishes. Fernando Mayer’s interests are statistical models applied to ecology. Daniele Vila-Nova focuses on geographical information system analysis of major impacts adjacent to Brazilian marine protected areas. Guilherme Longo is studying the ecological roles of reef fishes and the effects of biodiversity on ecosystem functioning. Natalia Hanazaki’s main research subjects are human ecology and ethnobotany. Alfredo Carvalho-Filho focuses on the systematics and taxonomy of marine fishes. Carlos Eduardo Ferreira leads investigations on the functioning and conservation of reef ecosystems.

References

Agresti, A. (2002) Categorical Data Analysis. 2nd editionJohn Wiley & Sons, New York, USA.CrossRefGoogle Scholar
Akaike, H. (1974) A new look at the statistical model identification. The IEEE Transactions on Automatic Control, 19, 716723.CrossRefGoogle Scholar
Baum, J. & Worm, B. (2009) Cascading top-down effects of changing oceanic predator abundances. Journal of Animal Ecology, 78, 699714.CrossRefGoogle ScholarPubMed
Bellwood, D.R., Hughes, T.P., Folke, C. & Nystrom, M. (2004) Confronting the coral reef crisis. Nature, 429, 827833.CrossRefGoogle ScholarPubMed
Bender, M.G., Floeter, S.R., Ferreira, C.E.L. & Hanazaki, N. (2012) Mismatches between global, national and local Red Lists and their consequences for Brazilian reef fish conservation. Endangered Species Research, 18, 247254.CrossRefGoogle Scholar
Bennett, P.M. & Owens, I.P.F. (1997) Variation in extinction risk among birds: chance or evolutionary predisposition? Proceedings of the Royal Society B, 264, 401408.CrossRefGoogle Scholar
Böhlke, J.E. & Chaplin, C.C.G. (1993) Fishes of the Bahamas and Adjacent Tropical Waters. University of Texas Press, Austin, USA.Google Scholar
Cardillo, M., Mace, G.M., Gittleman, J.L. & Purvis, A. (2006) Latent extinction risk and the future battlegrounds of mammal conservation. Proceedings of the National Academy of Sciences of the United States of America, 103, 41574161.CrossRefGoogle ScholarPubMed
Carvalho-Filho, A. (1999) Peixes: Costa Brasileira. Melro, São Paulo, Brazil.Google Scholar
Casey, J.M. & Myers, R.A. (1998) Near extinction of a large, widely distributed fish. Science, 281, 690692.CrossRefGoogle ScholarPubMed
Cheung, W.W.L., Pitcher, T.J. & Pauly, D. (2005) A fuzzy logic expert system to estimate extinction vulnerabilities of marine fishes to fishing. Biological Conservation, 124, 97111.CrossRefGoogle Scholar
Coleman, F.C., Koenig, C.C., Huntsman, G.R., Musick, J.A., Eklund, A.M., McGovern, J.C. et al. (2000) Long-lived reef fishes: the grouper-snapper complex. Fisheries, 25, 1420.2.0.CO;2>CrossRefGoogle Scholar
del Monte-Luna, P., Lluch-Belda, D., Serviere-Zaragoza, E., Carmona, R., Reyes-Bonilla, H., Aurioles-Gamboa, D. et al. (2007) Marine extinctions revisited. Fish and Fisheries, 8, 107122.CrossRefGoogle Scholar
Dobson, A.J. (2002) An Introduction to Generalized Linear Models. 2nd edition. Chapman & Hall, London, UK.Google Scholar
Duffy, J.E. (2002) Biodiversity and ecosystem function: the consumer connection. Oikos, 99, 201219.CrossRefGoogle Scholar
Dulvy, N.K., Ellis, J.R., Goodwin, N.B., Grant, A., Reynolds, J.D. & Jennings, S. (2004) Methods of assessing extinction risk in marine fishes. Fish and Fisheries, 5, 255276.CrossRefGoogle Scholar
Dulvy, N.K., Metcalfe, J.D., Glanville, J., Pawson, M.K. & Reynolds, J.D. (2000) Fishery stability, local extinctions, and shifts in community structure in skates. Conservation Biology, 14, 283293.CrossRefGoogle Scholar
Dulvy, N.K., Sadovy, I. & Reynolds, J.D. (2003) Extinction vulnerability in marine populations. Fish and Fisheries, 4, 2564.CrossRefGoogle Scholar
Ferreira, C.E.L., Floeter, S.R., Gasparini, J.L., Joyeux, J.C. & Ferreira, B.P. (2004) Trophic structure patterns of Brazilian reef fishes: a latitudinal comparison. Journal of Biogeography, 31, 10931106.CrossRefGoogle Scholar
Ferreira, C.E.L. & Gonçalves, J.E.A. (2006) Community structure and diet of roving herbivorous reef fishes in the Abrolhos Archipelago, south-western Atlantic. Journal of Fish Biology, 69, 119.CrossRefGoogle Scholar
Fisher, D.O. & Owens, I.P.F. (2004) The comparative method in conservation biology. Trends in Ecology & Evolution, 19, 391398.CrossRefGoogle ScholarPubMed
Floeter, S.R. & Gasparini, J.L. (2000) The south-western Atlantic reef fish fauna: composition and zoogeographic patterns. Journal of Fish Biology 56, 10991114.CrossRefGoogle Scholar
Floeter, S.R., Halpern, B.S. & Ferreira, C.E.L. (2006) Effects of fishing and protection on Brazilian reef fishes. Biological Conservation, 128, 391402.CrossRefGoogle Scholar
Floeter, S.R., Rocha, L.A., Robertson, D.R., Joyeux, J.C., Smith-Vaniz, W.F., Wirtz, P. et al. (2008) Atlantic reef fish biogeography and evolution. Journal of Biogeography, 35, 2247.CrossRefGoogle Scholar
Francini-Filho, R.B., Moura, R.L., Ferreira, C.M. & Coni, E. (2008) Live coral predation by parrot-fishes (Perciformes: Scaridae) in the Abrolhos Bank, eastern Brazil, with comments on the classification of species into functional groups. Neotropical Ichthyology, 6, 191200.CrossRefGoogle Scholar
Froese, R. & Pauly, D. (eds) (2009) Fishbase. Http://www.fishbase.org [accessed 20 June 2011].Google Scholar
Gärdenfors, U. (2001) Classifying threatened species at national versus global levels. Trends in Ecology & Evolution, 16, 511516.CrossRefGoogle Scholar
Gasparini, J.L., Floeter, S.R., Ferreira, C.E.L. & Sazima, I. (2005) Marine ornamental trade in Brazil. Biodiversity and Conservation, 14, 28832899.CrossRefGoogle Scholar
Gaston, K.J. & Blackburn, T.M. (1995) Birds, body size and the threat of extinction. Philosophical Transactions of the Royal Society B, 347, 205212.Google Scholar
Graham, N.A.J., Chabanet, P., Evans, R.D., Jennings, S., Letourneur, Y., MacNeil, M.A. et al. (2011) Extinction vulnerability in coral reef fishes. Ecology Letters, 14, 341348.CrossRefGoogle ScholarPubMed
Gustafsson, L. (1994) A comparison of biological characteristics and distribution between Swedish threatened and non-threatened forest vascular plants. Ecography, 17, 3949.CrossRefGoogle Scholar
Haimovici, M. & Klippel, S. (1999) Diagnóstico da biodiversidade dos peixes teleósteos demersais marinhos e estuarinos do Brasil. Programa Nacional de Diversidade Biológica, Avaliação e Ações Prioritárias para a Zona Costeira Marinha, Brazil.Google Scholar
Halpern, B.S. & Floeter, S.R. (2008) Functional diversity responses to changing species richness in reef fish communities. Marine Ecology Progress Series, 364, 147156.CrossRefGoogle Scholar
Hawkins, J.P. & Roberts, C.M. (2003) Effects of fishing on sex-changing Caribbean parrot-fishes. Biological Conservation, 115, 213226.CrossRefGoogle Scholar
Hawkins, J.P., Roberts, C.M. & Clark, V. (2000) The threatened status of restricted-range coral reef fish species. Animal Conservation, 3, 8188.Google Scholar
Heithaus, M.R., Frid, A., Wirsing, A.J. & Worm, B. (2008) Predicting ecological consequences of marine top predator declines. Trends in Ecology & Evolution, 23, 202210.CrossRefGoogle ScholarPubMed
Hero, J.M., Williams, S.E. & Magnusson, W.E. (2005) Ecological traits of declining amphibians in upland areas of eastern Australia. Journal of Zoology, London, 267, 221232.CrossRefGoogle Scholar
IUCN (2001) IUCN Categories and Criteria Version 3.1. IUCN Species Survival Commission, Gland, Switzerland and Cambridge, UK. Http://www.iucnredlist.org/technical-documents/categories-and-criteria/2001-categories-criteria [accessed 26 October 2012].Google Scholar
IUCN (2008) IUCN Red List of Threatened Species. IUCN, Gland, Switzerland. Http://www.iucnredlist.org [accessed 24 July 2008].Google Scholar
Jackson, J.B.C. (2008) Ecological extinction and evolution in the brave new ocean. Proceedings of the National Academy of Sciences of the United States of America, 105, 1145811465.CrossRefGoogle ScholarPubMed
Jackson, J.B.C. (2010) The future of the oceans past. Philosophical Transactions of the Royal Society B, 365, 37653778.CrossRefGoogle ScholarPubMed
Jennings, S., Reynolds, J.D. & Polunin, N.V.C. (1999) Predicting the vulnerability of tropical reef fisheries to exploitation with phylogenies and life histories. Conservation Biology, 13, 14661475.CrossRefGoogle Scholar
Kotiaho, J.S., Kaitala, V., Komonen, A. & Paivinen, J. (2005) Predicting the risk of extinction from shared ecological characteristics. Proceedings of the National Academy of Sciences of the United States of America, 102, 19631967.CrossRefGoogle ScholarPubMed
Loyola, R.D., Becker, C.G., Kubota, U., Haddad, C.F.B., Fonseca, C.R. & Lewinsohn, T.M. (2008a) Hung out to dry: choice of priority ecoregions for conserving threatened Neotropical anurans depends on life-history traits. PLoS ONE, 5, e2120.CrossRefGoogle Scholar
Loyola, R.D., Oliveira, G., Diniz-Filho, J.A.F. & Lewinsohn, T.M. (2008b) Conservation of Neotropical carnivores under different prioritization scenarios: mapping species traits to minimize conservation conflicts. Diversity and Distributions 14, 949960.CrossRefGoogle Scholar
Mace, G.M. & Lande, R. (1991) Assessing extinction threats: toward a re-evaluation of IUCN threatened species categories. Conservation Biology, 5, 148157.CrossRefGoogle Scholar
McCullagh, P. & Nelder, J.A. (1989) Generalized Linear Models. 2nd ed.Chapman & Hall, London, UK.CrossRefGoogle Scholar
MMA (Ministério do Meio Ambiente) (2004) Lista Nacional das Espécies de Invertebrados Aquáticos e Peixes ameaçados de extinção com categorias da IUCN. Instrução Normativa no. 5, de 21 de maio de 2004. Diário Oficial da União, Brasília, Brazil.Google Scholar
MMA (Ministério do Meio Ambiente) (2005) Alteração da Instrução Normativa no. 5, de 21 de omaio de 2004. Instrução Normativa no. 52, 9 de novembro de 2005. Publisher, Diário Oficial da União, Brasília, Brazil.Google Scholar
Morris, A.V., Roberts, C.M. & Hawkins, J.P. (2000) The threatened status of groupers. Biodiversity and Conservation, 9, 919942.CrossRefGoogle Scholar
Musick, J.A. (1999) Criteria to define extinction risk in marine fishes. Fisheries, 24, 614.2.0.CO;2>CrossRefGoogle Scholar
Myers, R.A., Baum, J., Shepherd, T.D., Powers, S.P. & Peterson, C.H. (2007) Cascading effects of the loss of apex predatory sharks from a coastal ocean. Science, 315, 18461850.CrossRefGoogle ScholarPubMed
Myers, R.A. & Worm, B. (2005) Extinction, survival or recovery of large predatory fishes. Philosophical Transactions of the Royal Society B, 360, 1320.CrossRefGoogle ScholarPubMed
Nelder, J.A. & Wedderburn, R.W.M. (1972) Generalized Linear Models. Journal of the Royal Statistical Society A, 135, 370384.CrossRefGoogle Scholar
Olden, J.D., Hogan, Z.S. & Zanden, M.J.V. (2007) Small fish, big fish, red fish, blue fish: size-biased extinction risk of the world's freshwater and marine fishes. Global Ecology and Biogeography, 16, 694701.CrossRefGoogle Scholar
Pimm, S.L. (1991) The Balance of Nature? University of Chicago Press, Chicago, USA.Google Scholar
Pinsky, M.L., Jense, O.P., Ricard, D. & Palumbi, S.R. (2011) Unexpected patterns of fisheries collapse in the world's oceans. Proceedings of the National Academy of Sciences of the United States of America, 108, 83178322.CrossRefGoogle ScholarPubMed
Purvis, A., Gittleman, J.L., Cowlishaw, G. & Mace, G.M. (2000) Predicting extinction risk in declining species. Proceedings of the Royal Society B, 267, 19471952.CrossRefGoogle ScholarPubMed
R Development Core Team (2008) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Randall, J.E. (1996) Caribbean Reef Fishes. 3rd ed.TFH, Neptune City, New Jersey, USA.Google Scholar
Reed, R.N. & Shine, R. (2002) Lying in wait for extinction: ecological correlates of conservation status among Australian elapid snakes. Conservation Biology, 16, 451461.CrossRefGoogle Scholar
Reynolds, J.D., Dulvy, N.K., Goodwin, N.B. & Hutchings, J.A. (2005) Biology of extinction in marine fishes. Proceedings of the Royal Society B, 272, 23372344.CrossRefGoogle ScholarPubMed
Reynolds, J.D., Jennings, S. & Dulvy, N.K. (2001) Life histories of fishes and population responses to exploitation. In Conservation of Exploited Species (eds Reynolds, J.D., Mace, G.M., Redford, K.H. & Robinson, J.G.), pp. 147168. Cambridge University Press, Cambridge, UK.Google Scholar
Roberts, C.M. & Hawkins, J.P. (1999) Extinction risk in the sea. Trends in Ecology & Evolution, 14, 241246.CrossRefGoogle ScholarPubMed
Rodrigues, A.S.L., Pilgrim, J.D., Lamoreux, J.F., Hoffmann, M. & Brooks, T.M. (2006) The value of the IUCN Red List for conservation. Trends in Ecology & Evolution, 21, 7176.CrossRefGoogle ScholarPubMed
Rodríguez, J.P., Ashenfelter, G., Rojas-Suárez, F., García-Fernández, J.J., Suárez, L. & Dobson, A.P. (2000) Local data are vital to worldwide conservation. Nature 403, 241.CrossRefGoogle ScholarPubMed
Sadovy, Y.J. & Vincent, A.C.J. (2002) Ecological issues and the trades in live reef fishes. In: Coral Reef Fishes: Dynamics and Diversity in a Complex Ecosystem (ed. Sale, P.F.), pp. 391420. Academic Press, San Diego, USA.CrossRefGoogle Scholar
Shapiro, D.Y. (1987). Reproduction in groupers. In Tropical Snappers and Groupers: Biology and Fisheries Management (eds Polovina, J.J. & Ralston, S.), pp. 295327. Westview Press, Boulder, Colorado, USA.Google Scholar
Smith, C.L. (1997) Tropical Marine Fishes of the Caribbean, the Gulf of Mexico, Florida, the Bahamas, and Bermuda. Alfred A. Knopf, New York, USA.Google Scholar
Soulé, M.E. (1991) Conservation: tactics for a constant crisis. Science, 253, 744–75.CrossRefGoogle ScholarPubMed
Stevens, J.D., Bonfill, R., Dulvy, N.K. & Walker, P.A. (2000) The effects of fishing on sharks, rays, and chimaeras (chondrichthyans), and the implications for marine ecosystems. ICES Journal of Marine Science, 57, 476494.CrossRefGoogle Scholar
Subirá, R.J., Souza, E.C.F., Guidorizzi, C.E., Almeida, M.P., Almeida, J.B. & Martins, D.S. (2012) Avaliação cientifica do risco de extinção da fauna brasileira: resultados alcançados em 2012. Biodiversidade Brasileira, 2, 124130.Google Scholar
Venables, W.N. & Ripley, B.D. (2002) Modern Applied Statistics with S. 4th edition. Springer, New York, USA.CrossRefGoogle Scholar
Vila-Nova, D.A., Bender, M.G., Carvalho-Filho, A., Ferreira, C.E L. & Floeter, S.R. (2011) The use of non-reef habitats by Brazilian reef fish species: considerations for the design of marine protected areas. Natureza & Conservação, 9, 7986.CrossRefGoogle Scholar
Wood, E.M. (2001) Global advances in conservation and management of marine ornamental resources. Aquarium Sciences and Conservation, 3, 6577.CrossRefGoogle Scholar
Worm, B. & Tittensor, D.P. (2011) Range contraction in large pelagic predators. Proceedings of the National Academy of Sciences of the United States of America, 108, 1194211947.CrossRefGoogle ScholarPubMed
Zar, J.H. (2008) Bioestatistical Analysis. 5th edition. Pearson Prentice Hall, New Jersey, USA.Google Scholar
Figure 0

Fig. 1 Number of reef fishes of Brazilian waters in each Red List category on the global IUCN Red List (IUCN, 2008), regional MMA list (MMA 2004, 2005), local lists (Bender et al., 2012, and references therein) and the total number of species categorized as threatened (black). Note that the total number does not correspond to the sum of species within the global, regional and local lists because some species have been assessed for several lists. CR, Critically Endangered; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern; DD, Data Deficient.

Figure 1

Fig. 2 Percentage of non-threatened and threatened reef fish species in Brazilian waters in (a) trophic categories and (b) maximum body-size class (large, > 50 cm; medium, 25–50 cm; small–medium, 10–25 cm; small, < 10 cm; *Significant difference at P < 0.05 with the Binomial test).

Figure 2

Table 1 Deviance analysis of the logistic regression model.