Changes in fishing production in the northern BrazilAbstract
This study analyzed temporal changes in fishery production along the northern coast of Brazil to assess evidence of fishing down marine food webs. Landings data from Pará State between 1997 and 2007 were used to evaluate variations in catch composition and mean trophic levels (MTL). Mean annual landings (t) by combined taxa peaked around 1998 and 2002, followed by a steady decline in later years. High-trophic groups, including large pelagic, demersal fish, and elasmobranchs, showed marked reductions in mean annual landings. Although no significant annual differences in MTL were detected, linear regression revealed a significant negative temporal trend, indicating a gradual shift toward species of lower trophic levels. These results suggest that fisheries in northern Brazil are undergoing a process of fishing down where high-value, top-predator species such as Cynoscion acoupa and Scomberomorus brasiliensis are being replaced by smaller, faster-growing taxa. This scenario is reinforced by decreases in catch volumes of the main target fishery resources. Despite limitations in data reliability, the consistent decline in trophic level underscores the need for improved monitoring systems, accurate species identification, and the implementation of ecosystem-based management strategies.
Key words
Brazilian Amazon; Ecosystem-based management; Fishery production; Overfishing; Trophic level
INTRODUCTION
The dynamics of the fisheries operating off the northern coast of Brazil are linked directly to local climatic and hydrological conditions (Isaac & Braga 1999, Trindade et. al. 2023, Moura et al. 2024). The fishery production of the state of Pará is one of the country’s largest, and this state plays a prominent role in the sector in northern Brazil (Isaac et al. 2008, MPA 2025).
Fisheries often focus on the species present at the top of the food web, that is, the species that consume most energy or have the highest energetic cost (España et al. 2006). However, a general consensus exists that the process of “fishing down marine food webs” is reflected in processes such as overfishing, loss of sustainability and other ecological changes that decrease the density of organisms at the highest high trophic levels (Pauly et al. 1998, Essington et al. 2006).
Several studies have demonstrated the occurrence of fishing down. Christensen (1996) and Pauly et al. (1998) were among the first to document a global decline in the average trophic levels of catches. Subsequent research, including that of Pauly et al. (2002), Arancibia & Neira (2005), Essington et al. (2006), and Schiller et al. (2014), have expanded our understanding by quantifying the mechanisms and ecological implications of this process across several large marine ecosystems worldwide. In Brazil, Freire & Pauly (2010) provided evidence of decreasing trophic levels in the Greater Eastern Brazilian Marine Ecosystem, while Lecheta et al. (2017) examined the impacts of downward fishing and its sustainability implications in southern Brazilian fisheries. Collectively, these studies underscore the utility of trophic indicators in monitoring fishing impacts and supporting the development of management strategies for marine ecosystems.
The marine trophic index (MTI) and the mean trophic level (MTL) can be used together to describe the complex interactions between fisheries and the marine ecosystem, and if there is any replacement of organisms occurring as a result of fishing pressure. The analysis of these two parameters provides important insights for the development of management strategies (Pauly & Watson 2005), although these indicators are not based on a simple analysis of the decrease in productivity at a given point in time, but rather, on a holistic assessment of the changes occurring along the food chain, resulting either from the exclusion of a given trophic level through fishing-induced mortality or system-level shifts caused by other human activities (Walther et al. 2002).
Climate change is one factor that may affect capture potential. Cheung et al. (2010) concluded that the capture potential of most Exclusive Economic Zones (EEZs) is decreasing, especially in tropical and subtropical regions. Under the CMIP5 RCP8.5 high-emission scenario, projected to mid-century (2050), catch potential in Brazil is expected to decline by approximately 6-13% (Cheung et al. 2010). Primary production rates, which are critical to the maintenance of both biodiversity and fishery stocks, are being altered by climate change throughout the world’s oceans, but reliable predictions of the response of populations to these changes are hampered by interspecific interactions, such as predation and competition (Brown et al. 2010).
In the cases of fisheries, any anthropogenic interference, whether direct or indirect, can lead to changes in productivity, with knock-on effects for specific economic activities that were previously highly lucrative. In the specific case of the typical artisanal fisheries of the northern Brazilian coast that target multiple species, obtaining reliable estimates of losses can be a considerable challenge, but if the mean trophic level continues to decrease in multispecies fisheries, it can be safely assumed that the activity is unsustainable over the long term (Pauly & Watson 2005). España et al. (2006) emphasized the need for further research on ecosystem structure and function, especially for the understanding of the consequences of the replacement of an overexploited species by a new one at the same trophic level.
This study investigates the fisheries of the northern Brazilian coast for evidence of the possible “fishing down marine food webs” (Pauly et al. 1998), and potential impacts to the commercial fish stocks found in the region. By applying trophic indicators such as the landings (commercial catches by group) and mean trophic level, this research aims to provide insights for ecosystem-based management and to support the development of continuous monitoring programs for sustainable fisheries in the region.
MATERIALS AND METHODS
Study area
Northern Brazil is characterized by high rainfall, with annual precipitation of up to 3000 mm. The rainy season coincides with the first half of the year, peaking in March and April, while the second half of the year is dry, with September typically being the hottest and driest month (Isaac & Braga 1999). The coast of the Brazilian state of Pará (Figure 1) is a region of high productivity, due to the large amount of suspended matter of terrestrial origin, derived from the enormous volumes of freshwater discharged by the Amazon River (Wolff et al. 2000). The primary fishing grounds for various fishing systems (e.g., gillnets, longlines, and trawls) are strategically located across the coastal region and the adjacent continental shelf, directly off the mouth of the Amazon River (Isaac et al. 2009).
The main fishing ports of Pará, Brazil. P1 = Soure, P2 = Belém, P3 = Vigia, P4 = São Caetano de Odivelas, P5 = Curuça, P6 = Marapanim, P7 = Salinópolis, P8 = São João de Pirabas, P9 = Quatipuru, P10 = Bragança, P11 = Augusto Corrêa. The dotted line indicates the area of operation of the main fishing systems in this region. Environmental data such as reef and bathymetry were obtained from Moura et al. (2016).
Data collection and analysis
The article is based on landings data. Therefore, no declaration or license for animal studies was required. The data analyzed in this study refer to marine and estuarine fishery landings in the state of Pará between 1997 and 2007, obtained from the project ESTATPESCA, conducted by the Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) / (Centro de Pesquisa e Conservação da Biodiversidade Marinha do Norte - CEPNOR (IBAMA 2007). The dataset includes: (i) the year, (ii) the common and scientific names of the species, (iii) the zoological category (mollusk, crustacean, large pelagic, medium pelagic, small pelagic, demersal and elasmobranch), (iv) trophic guild (defined as herbivores, detritivores, planktivores, omnivores, and carnivores, following Cortéz (1999)), and (v) the mean annual catch per year (t).
The total average annual production was calculated for all taxa combined and by functional group. In addition, the annual production of the ten most landed species was verified. Therefore, different production metrics were applied depending on the scale of analysis. For the assessments by combined taxa and functional group, the average annual production (t) was calculated for all taxa, representing the arithmetic mean of the landings of all taxa within those specific categories for each year. For combined taxa, the value represents the arithmetic mean of the annual landings across all recorded taxa, not the total biomass landed in the year. In contrast, for the analysis of the ten most representative species, the sum of annual landings (t) was used, representing the total biomass recorded for each specific taxon. The use of total biomass summed at the species level is necessary to illustrate the real economic importance and pressure exerted on the main fishery resources of the region, which would be masked if the average were calculated together with less frequent taxa. It is important to note that this 1997-2007 period represents the last continuous and systematic time series of fishery statistics detailed by species for Northern Brazil, as the comprehensive data collection was discontinued shortly thereafter.
The scientific name and trophic guild of the different species were obtained from the specialized literature, and the MTL and ecological category of each organism were extracted from FISHBASE (http://www.fishbase.org) and Cortéz (1999). As elasmobranchs were recorded in general categories such as “sharks” and “rays”, their trophic level was calculated as the average of the species commonly caught on the northern coast of Brazil (Marceniuk et al. 2019). Although some reference studies focus on industrial fisheries, the dominant species analyzed here (e.g., Cynoscion acoupa and Scomberomorus brasiliensis) are exploited by both artisanal and industrial sectors, justifying the comparison.
To evaluate differences in the distribution of individual trophic levels among years, the assumptions of normality (Shapiro-Wilk test) and homogeneity of variances (Levene’s test) were verified. As these assumptions were violated (p < 0.05), the non-parametric Kruskal-Wallis test was applied to assess overall interannual differences, followed by pairwise Wilcoxon tests with Bonferroni correction for multiple comparisons.
The annual MTL was calculated as the arithmetic mean of the trophic levels of all species recorded in the landings during a given year k. This approach assumes equal representation in the estimation of the trophic position when detailed, continuous catch weight data for all specific taxa are unavailable or unreliable, focusing on the diversity and replacement of functional groups. The formula used for the simple arithmetic mean MTL is:
Where:
TLi is the trophic level of species i;
m is the total number of distinct taxa/groups recorded in year k.
To assess the temporal trend consistent with the “fishing down marine food webs” hypothesis, the calculated annual MTL values were fitted to a linear regression model. The regression slope (β) and its significance (p-value) were interpreted as indicators of the direction and strength of the trend.
All analyses were performed using R 4.4.1 software (R Core Team 2024), and the graphs were generated with the ggplot2 package (Wickham et al. 2024).
RESULTS
The mean annual landings of combined taxa peaked at approximately 2,400 t in 1998 and 2002, subsequently decreasing in subsequent years (Figure 2). The species diversity in the region includes a variety of elasmobranchs, bony fishes, crustaceans, and mollusks (Table I), some of which are classified as endangered or critically endangered by the IUCN (http://www.iucnredlist.org).
Species composition and historical landing metrics (1997–2007) by commercial fisheries in the ports of Pará. *=Calculated as the arithmetic mean of the annual landings for each specific taxon during the 11-year study period.
Crustaceans showed a mean annual production of 2,700 t in 1997, followed by a decline to approximately 800 t in 2006 and 2007. Demersal fish exhibited the highest mean annual values in 1997 (2,587 t) and 2002 (3,428 t), followed by a gradual decrease until 2007.
Among large pelagics, production ranged from 1,727 t in 1997 to 815.6 t in 2007. Medium pelagics showed a production peak in 1999 (1,287 t) and a minimum in 2004 (340 t). Small pelagics exhibited more moderate fluctuations, starting with an initial production of 430.85 t, a peak in 2005 (642.75 t), followed by a decrease in 2006 and 2007.
Elasmobranchs showed high production levels at the beginning of the period (4,262 t in 1997), followed by fluctuations, with a peak in 2000 (4,083 t) and a significant drop in 2006 (2,063 t). Mollusk production started extremely low (0.04 t in 1997) and gradually increased from 2000 onward, reaching a peak of 430.5 t in 2004, followed by a decline in subsequent years (Figure 3).
The mean trophic levels did not show significant differences among years (p-value = 1.0), ranging from 3.65 to 3.58. Despite the absence of interannual differences, the linear regression revealed a significant temporal trend of decline in the MTL. The linear regression model showed a significantly negative slope coefficient (β = -0.0054; p = 0.0108), indicating an average decline of approximately 0.0054 trophic level units per year (Figure 4).
Temporal dynamics of the mean trophic level (MTL) of species landed in Pará between 1997 and 2007. a = Annual distribution of trophic levels; boxplots represent annual variation (median and quartiles), gray points indicate individual observations (jitter), and the black line connects the annual means. b = Temporal trend of the MTL based on linear regression. The shaded area represents the 95% confidence interval.
Among the most landed species, Cynoscion acoupa reached a summed annual landing of 22,028 t in 2000. Its catch remained consistently high throughout the period. S. brasiliensis exhibited markedly oscillating production patterns, with a peak in 1998 (12,255 t) and a subsequent decline to 4,684 t in 2007. Sciades parkeri peaked in 2000 at 12,212 t, followed by a progressive decline until 2006 (Figure 5).
Summed annual landings of the 10 most landed species from 1997 to 2007 in the ports of Pará. The values in parentheses indicate the trophic level of each species.
DISCUSSION
Several factors hinder a more detailed analysis of long-term patterns in the fisheries of the Brazilian North Coast. Most of the studies and reports available from this region refer to the catches by their vernacular or common names, which may often obscure impacts on threatened species. This is one of the principal limitations of the statistical data on the fishery catches landed in Brazil (Isaac et al. 2008).
Given this, the compilation of catch data per species (by its scientific name) is hampered by the lack of experience of the data collectors who, in many cases, are persons of limited education that live in the fishing communities. Adequate training of these individuals for the reliable identification of species may conflict with the more practical needs of the fishery sector, not to mention the difficulties of identifying rare species or those with doubtful taxonomic status, such as many ariids and mugilids. There are additional potential sources of error. The frequency of docking of each vessel and sampling procedures for the selection of catches may also affect results (Isaac et al. 2008). In the case of the fisheries of the Brazilian North Coast, which are almost all (90%) artisanal, the collection of census-type data should be considered, to compensate for possible sources of bias resulting from unrealistic extrapolations (Isaac et al. 2008). These potential sources of error imply that the available statistics, in particular from northern Brazil, may not be totally reliable, but even so, they are the only data existing on the production of specific ethnospecies. Given this, the development of more accurate methods for the measurement of catches should be of the utmost priority for fishery management. In addition to production, data on fishery effort and the size of the fleets, as well as the socioeconomic status of the actors involved in these operations should also be collected.
Despite potential inaccuracies in the dataset, the presented results indicate an initial trend consistent with the fishing down effect. The observed decline in MTL and the reduction in production of higher-trophic species suggest growing pressure on the upper levels of the food chain. Although the Kruskal–Wallis test revealed no significant differences in MTL among individual years, the linear regression analysis showed a significant negative temporal trend (β = -0.0054; p = 0.011), evidencing a gradual decrease in the trophic position of landed species between 1997 and 2007.
Fisheries statistical data from the states, detailed by species, were only published up to 2007, which prevented the analysis of MTL patterns in subsequent years. However, given that a decreasing trend was already observed by the end of the period analyzed in this study, it reinforces the need to reestablish comprehensive fisheries statistics. This is essential to enable the analysis and confirmation of whether the decline in MTL over the past 18 years has been significant.
Although the total decline in MTL observed in this study (0.07 units between 1997 and 2007) is below the 0.15 threshold suggested by Essington et al. (2006) as indicative of pronounced fishing down processes, it represents a consistent negative trend over a relatively short 11-year period. The estimated regression slope (β = −0.0054 year⁻¹; p = 0.0108) indicates a cumulative reduction of approximately 0.059 trophic level units across the study window. When considered in the context of the limited temporal scale and the absence of large-scale industrial expansion during this period, this rate of decline suggests a measurable restructuring of the trophic composition of landings. Moreover, the decline was not driven by the sequential addition of new low-trophic fisheries, but rather by the progressive reduction in catches of high-trophic species such as elasmobranchs and large demersals. Therefore, while the magnitude of change does not reach the threshold proposed for long-term global assessments, the observed directional shift provides regional-scale evidence consistent with an incipient fishing down process.
In the case of C. acoupa, the production peak occurred after the implementation of financing programs initiated in the mid-1990s. Between 1997 and 2002, a significant expansion of the fishing fleet was recorded in municipalities traditionally engaged in fishing in the state of Pará, particularly among small and medium-sized vessels (Mourão et al. 2009). Fishing targeting this species takes place year-round (Matos & Lucena 2006), and over time, fishing effort has increased, driven by investments aimed at enhancing vessel autonomy, such as the installation of onboard refrigeration chambers (Moura et al. 2025). These factors have contributed to the decline in the landing volumes of this species in Pará.
Globally, similar trends have been documented, with average trophic levels in marine catches declining from 3.3 in the 1950s to below 3.1 in the 1990s (Pauly et al. 1998, Essington et al. 2006). In India, for instance, catches increased from 0.6 to 3.3 million tons between 1950 and 2000, driven primarily by sardines (low-trophic species) that replaced overexploited stocks (Bhathal & Pauly 2008). In Brazil, Freire & Pauly (2010) observed an apparent increase in the national MTI between 1978 and 2000, a trend largely influenced by the collapse of sardine stocks and the expansion of tuna fisheries. However, such large-scale analyses can obscure regional declines like those identified here for northern Brazil.
As noted by Caddy et al. (1998), fishing pressure is a key driver of the “fishing down” phenomenon. In our study area, the period analyzed (1997-2007) coincides with documented increases in fishing effort, fleet expansion, and technological improvements (Mourão et al. 2009, Moura et al. 2025). While our analysis is based on landing data and does not include independent fishing effort metrics, the concurrent decline in high-trophic species and MTL provides circumstantial but coherent evidence that fishing pressure contributed to the observed patterns. Future studies incorporating direct effort data (e.g., number of vessels or fishing days) would be valuable to quantitatively link pressure to trophic changes.
The observed decrease in MTL in Pará indicates potential overfishing and ecological changes associated with the loss of higher trophic species. These results reinforce that fishing in the region has gradually shifted toward smaller, faster-growing species, consistent with the fishing down hypothesis. The changes in catch composition may also result from natural fluctuations, environmental variability, and technological advances, but the consistent negative trend found here suggests that fishing pressure has been a key driver (Caddy et al. 1998).
While the consistent negative trend suggests fishing pressure is a key driver (Caddy et al. 1998), the temporal scope of the available official data remains a principal limitation. The lack of recent, standardized landing statistics impedes the assessment of whether the declining MTL trend has continued, stabilized, or reversed. The reinstitution of systematic, species-level monitoring is critical for understanding current fishery dynamics and validating long-term ecological changes.
In summary, the decline in mean trophic level and the fluctuations in fishery production in Pará reflect a trajectory toward unsustainable exploitation of marine resources. Although the available data present some limitations, they provide evidence that fisheries in northern Brazil are undergoing structural changes typical of overfished ecosystems. To ensure the long-term sustainability of these fisheries, it is crucial to strengthen monitoring systems, standardize taxonomic identification in landings, and implement management measures based on ecosystem indicators.
References
-
ARANCIBIA H & NEIRA S. 2005. Long-term changes in the mean trophic level of Central Chile fishery landings. Sci Mar 69: 295-300. https://doi.org/10.3989/scimar.2005.69n2295.
» https://doi.org/10.3989/scimar.2005.69n2295 -
BHATHAL B & PAULY D. 2008. ‘Fishing down marine food webs’ and spatial expansión of coastal fisheries in India, 1950-2000. Fish Res 91: 26-34. https://doi.org/10.1016/j.fishres.2007.10.022.
» https://doi.org/10.1016/j.fishres.2007.10.022 -
BROWN CJ ET AL. 2010. Effects of climate-driven primary production change on marine food webs: implications for fisheries and conservation. Glob Chang Biol 16: 1194-1212. DOI: 10.1111/j.1365-2486.2009.02046.x.
» https://doi.org/10.1111/j.1365-2486.2009.02046.x -
CADDY JF, CSIRKE J, GARCIA SM & GRAINGER RJR. 1998. How pervasive is ‘Fishing down marine food webs’? Science 282: 1383-1384. https://doi.org/10.1126/science.282.5393.1383a.
» https://doi.org/10.1126/science.282.5393.1383a -
CHEUNG WWL, LAM VWY, SARMIENTO JL, KEARNEY K, WATSON R, ZELLER D & PAULY D. 2010. Large-scale redistribuition of máximum fisheries catch potential in the global ocean under climate change. Glob Chang Biol 16: 24-35. https://doi.org/10.1111/j.1365-2486.2009.01995.x.
» https://doi.org/10.1111/j.1365-2486.2009.01995.x -
CHRISTENSEN V. 1996. Managing fisheries involving predator and prey species. Rev Fish Biol Fish 6: 417-442. https://doi.org/10.1007/BF00164324.
» https://doi.org/10.1007/BF00164324 -
CORTÉZ E. 1999. Standardized diet compositions and trophic levels of sharks. ICES J Mar Sc 56: 707-717. https://doi.org/10.1006/jmsc.1999.0489.
» https://doi.org/10.1006/jmsc.1999.0489 - ESPAÑA HP, ARENAS LGA & BADILLO MLJ. 2006. Is fishing-down trophic web a generalized phenomenon? The case of Mexican fisheries. Fish Res 79: 349-352.
-
ESSINGTON TE, BEAUDREAU AH & WIEDENMANN J. 2006. Fishing through marine food webs. Proc Nal Acad Sci 103: 3171-3175. https://doi.org/10.1073/pnas.0510964103.
» https://doi.org/10.1073/pnas.0510964103 -
FREIRE KMF & PAULY D. 2010. Fishing down Brazilian marine food webs, with emphasis on the east Brazil large marine ecosystem. Fish Res 105: 57-62. https://doi.org/10.1016/j.fishres.2010.02.008.
» https://doi.org/10.1016/j.fishres.2010.02.008 -
IBAMA - INSTITUTO BRASILEIRO DO MEIO AMBIENTE E DOS RECURSOS NATURAIS RENOVÁVEIS. 2007. Estatística da pesca: Brasil – Grandes regiões e unidades da federação. Brasília: Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis / CEPNOR. Available at: https://www.gov.br/ibama/pt-br/assuntos/biodiversidade/biodiversidade-aquatica/gestao-da-biodiversidade-aquatica/estatistica-pesqueira Accessed on: February 11, 2026.
» https://www.gov.br/ibama/pt-br/assuntos/biodiversidade/biodiversidade-aquatica/gestao-da-biodiversidade-aquatica/estatistica-pesqueira -
ISAAC VJ & BRAGA TMP. 1999. Rejeição de pescado nas pescarias da região Norte do Brasil. Arq Cienc Mar 32: 39-54. https://doi.org/10.32360/acmar.v32i1-2.31342.
» https://doi.org/10.32360/acmar.v32i1-2.31342 - ISAAC VJ, ESPIRITO SANTO RV & NUNES JLG. 2008. A estatística pesqueira no litoral do Pará: resultados divergentes. Pan-Am J Aquat Sci 3: 205-213. Available at: https://panamjas.org/pdf_conteudos/PANAMJAS_3(3)_205-213.pdf.
-
ISAAC VJ, SANTO RVE, BENTES B, FRÉDOU FL, MOURÃO KRM, & FRÉDOU T. 2009. An interdisciplinary evaluation of fishery production systems off the state of Pará in North Brazil. J Appl Ichthyol 25: 244-255. https://doi.org/10.1111/j.1439-0426.2009.01274.x.
» https://doi.org/10.1111/j.1439-0426.2009.01274.x - LECHETA TP, AFONSO MG & CHAVES PDT. 2017. Investigação sobre fishing down marine food webs no sul do Brasil: implicações financeiras e para a sustentabilidade. Arq Ciên Mar 50: 30-44. Available at: http://www.repositorio.ufc.br/handle/riufc/29765.
-
MARCENIUK AP ET AL. 2019. Sharks and batoids (Subclass Elasmobranchii) caught in the industrial fisheries off the Brazilian North coast. Rev Nordestina Biol 27: 120-142. https://doi.org/10.22478/ufpb.2236-1480.2019v27n1.47112.
» https://doi.org/10.22478/ufpb.2236-1480.2019v27n1.47112 - MATOS IP & LUCENA F. 2006. Descrição da pesca da pescada amarela Cynoscion acoupa da costa do Pará. Arq Cienc Mar 39: 66-73. Avaiable at: http://www.repositorio.ufc.br/handle/riufc/53940.
-
MOURA H, NUNES Z, SARMENTO G, PINHEIRO L, CARVALHO A, SANTOS F, TRINDADE D, SANTOS W & BENTES B. 2025. Frontiers of the unknown: the value chain of meat and fish maw of acoupa weakfish from Amazon continental shelf. Front Mar Sci 12: 2296-7745. https://doi.org/10.3389/fmars.2025.1549269.
» https://doi.org/10.3389/fmars.2025.1549269 -
MOURA H, TRINDADE DG, GOUVEIA NA, NUNES ZMP & BENTES BS. 2024. Impacts of climatic and oceanographic variability on the landing of Cynoscion acoupa (Lacepède, 1801) captured on the Amazon continental shelf. Reg Stud Mar Sci 76: e103608. https://doi.org/10.1016/j.rsma.2024.103608.
» https://doi.org/10.1016/j.rsma.2024.103608 - MOURÃO KRM, FRÉDOU FL, SANTO RVE, ALMEIDA MC, BENTES BS, FREDOU T & ISAAC VJ. 2009. Sistema de produção pesqueira pescada amarela - Cynoscion acoupa Lacèpede (1802): Um estudo de caso no litoral Nordeste do Pará Brasil. Bol Inst Pesca 35: 497-511.
-
MPA - MINISTÉRIO DA PESCA E AQUICULTURA. 2025. Boletim estatístico da pesca e aquicultura 2023/2024. Brasília: Departamento de Pesquisa e Estatística, Secretaria Nacional de Registro, Monitoramento e Pesquisa. Available at: https://www.gov.br/mpa/pt-br/assuntos/cadastro-registro-e-monitoramento/estatistica-pesqueira/retomada-estatistica-pesqueira/boletim_estatistico_2023-2024.pdf Accessed on: October 22, 2025.
» https://www.gov.br/mpa/pt-br/assuntos/cadastro-registro-e-monitoramento/estatistica-pesqueira/retomada-estatistica-pesqueira/boletim_estatistico_2023-2024.pdf -
PAULY D, CHRISTENSEN V, DALSGAARD J, FROESE R & TORRES-JR F. 1998. Fishing down marine food webs. Science 279: 860-863. https://doi.org/10.1126/science.279.5352.860.
» https://doi.org/10.1126/science.279.5352.860 -
PAULY D, CHRISTENSEN V, GUÉNETTE S, PITCHER TJ, SUMAILA UR, WALTERS CJ, WATSON R & ZELLER D. 2002. Towards sustainability in world fisheries. Nature 418: 689-695. https://doi.org/10.1038/nature01017.
» https://doi.org/10.1038/nature01017 -
PAULY D & WATSON R. 2005. Backgroup and interpretation of the ‘Marine Trophic Index’ as a measure of biodiversity. Philos Trans R Soc B Biol Sci 360: 415-423. https://doi.org/10.1098/rstb.2004.1597.
» https://doi.org/10.1098/rstb.2004.1597 -
R CORE TEAM. 2024. R: A Language and Environment for Statistical Computing. Version 4.4.1. Available at: https://cran.r-project.org/bin/windows/base/ Accessed on: August 15, 2024.
» https://cran.r-project.org/bin/windows/base/ -
SCHILLER L, ALAVA JJ, GROVE J, RECK G & PAULY D. 2014. The demise of Darwin’s fishes: evidence of fishing down and illegal shark finning in the Galápagos Islands. Aquat Conserv Mar Freshw Ecosyst 25: 431-446. https://doi.org/10.1002/aqc.2458.
» https://doi.org/10.1002/aqc.2458 -
TRINDADE DG, GOUVEIA NA, MESCOUTO NLC, MOURA HTGS, SILVA UIP & BENTES B. 2023. Effects of marine climate variability on the relative abundance of Lutjanus purpureus (Poey, 1866) on the Amazon Continental Shelf. Fish Oceanogr 33(2): e12662. https://doi.org/10.1111/fog.12662.
» https://doi.org/10.1111/fog.12662 -
WALTHER G, POST E, CONVEY P, MENZEL A, PARMESAN C, BEEBEE TJC, FROMENTIN J, HOEGH-GULDBERG O & BAIRLEIN F. 2002. Ecological responses to recent climate change. Nature 416: 389-395. https://doi.org/10.1038/416389a.
» https://doi.org/10.1038/416389a -
WICKHAM H, CHANG W, HENRY L, PEDERSEN TL, TAKAHASHI K, WILKE C, WOO K, YUTANI H, DUNNINGTON D & VAN DEN BRAND T. 2024. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. R package version 3.5.1. Available at: https://ggplot2.tidyverse.org Accessed on: August 20, 2024.
» https://ggplot2.tidyverse.org -
WOLFF M, KOCH V & ISAAC V. 2000. A trophic flow model of the Caeté Mangrove Estuary (North Brazil) with considerations for the sustainable use of its resources. Estuar Coast Shelf Sci 50: 789-803. https://doi.org/10.1006/ecss.2000.0611.
» https://doi.org/10.1006/ecss.2000.0611
Edited by
-
Handling editor
Luiz Drude Lacerda
Data will be made available on request.
