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Cited by 1Fish biology, ecology, and behaviorFish Ecology and Management StudiesFreshwater macroinvertebrate diversity and ecology

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The use of fish diversity and abundance as environmental indicators in a mining region in Brazilian Amazonia

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de Oliveira, Claudia Antônia Campos Rodrigues, Morais, Katherine Soares, de Oliveira, João Paulo Silva, de Oliveira Marques, Alexandre, da Silva, Ana Beatriz Ferreira, da Conceição Palheta, Dulcidéia, Bentes, Bianca·2026·Scientific Reports
DOI 10.1038/s41598-026-43889-8PMC PMC13102912

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Abstract

The impacts of mining on aquatic biodiversity pose significant challenges for environmental mitigation, particularly near protected areas. This study assessed fish abundance and diversity (assemblage composition, alpha and beta diversity, indicator species, and Species Contribution to Beta Diversity - SCBD) in the Itacaiúnas and Parauapebas river basins, Brazilian Amazonia, across dry and rainy seasons. We hypothesized that basins near mining-impacted areas would exhibit reduced fish abundance and diversity compared to control areas. To test this, four sampling points were established per basin (two controls, two impacted), totaling eight sites, where fish were collected using gillnets and physicochemical water parameters were simultaneously recorded. Fish abundance and alpha diversity peaked during the rainy season but showed no significant differences between control and impacted areas. Beta diversity was higher in the Parauapebas basin, and indicator species analysis identified taxa associated with particular groups. A Redundancy Analysis (RDA) linked environmental variables (temperature, salinity, and conductivity) to species distributions, suggesting an influence of water quality on assemblage organization. Although abundance and richness did not clearly differentiate areas, the combined assemblage and species-level results support the importance of continuous, integrated monitoring to assess long-term ecological changes.

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Fig. 1 Location of the sampling points at which fish specimens were collected in the Carajás Mineral Province, Brazil, in May and November 2022. (A) – Points 1 and 3 are the control sites, and points 2 and 4, the impacted sites in the Itacaiúnas Basin, while points 5 and 8 are impacted, and points 6 and 7 are the control sites in the Parauapebas Basin. (B) – Municipalities located within the study region: Marabá, Parauapebas, and Canaã dos Carajás. (C) – State of Pará. (D) – Brazil.
Fig. 1 Location of the sampling points at which fish specimens were collected in the Carajás Mineral Province, Brazil, in May and November 2022. (A) – Points 1 and 3 are the control sites, and points 2 and 4, the impacted sites in the Itacaiúnas Basin, while points 5 and 8 are impacted, and points 6 and 7 are the control sites in the Parauapebas Basin. (B) – Municipalities located within the study region: Marabá, Parauapebas, and Canaã dos Carajás. (C) – State of Pará. (D) – Brazil.CC BY-NC-ND · PubMed Central
Fig. 2 Overview of the variation in the physicochemical parameters (temperature, salinity, and conductivity) of the water between: (a) the dry and rainy seasons; (b) the impacted and control areas; (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB, dry: PRB, rainy: IRB, rainy: PRB) and (e) the interaction between areas and basins (impacted: IRB, impacted: PRB, control: IRB, control: PRB) in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).
Fig. 2 Overview of the variation in the physicochemical parameters (temperature, salinity, and conductivity) of the water between: (a) the dry and rainy seasons; (b) the impacted and control areas; (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB, dry: PRB, rainy: IRB, rainy: PRB) and (e) the interaction between areas and basins (impacted: IRB, impacted: PRB, control: IRB, control: PRB) in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).CC BY-NC-ND · PubMed Central
Fig. 3 PCA ordination based on Hellinger-transformed fish assemblage composition showing variation among (a) periods (dry and rainy), (b) areas (impacted and reference), (c) sites (IRB and PRB), (d) the interaction between period and site, and (e) the interaction between area and site, in the Carajás Mineral Province, Brazil, sampled in May and November 2022. Small symbols represent individual samples, whereas larger symbols indicate group centroids. Asterisk indicates a significant difference between sites (PERMANOVA, p < 0.05).
Fig. 3 PCA ordination based on Hellinger-transformed fish assemblage composition showing variation among (a) periods (dry and rainy), (b) areas (impacted and reference), (c) sites (IRB and PRB), (d) the interaction between period and site, and (e) the interaction between area and site, in the Carajás Mineral Province, Brazil, sampled in May and November 2022. Small symbols represent individual samples, whereas larger symbols indicate group centroids. Asterisk indicates a significant difference between sites (PERMANOVA, p < 0.05).CC BY-NC-ND · PubMed Central
Fig. 4 Variation in the total abundance of fish between: (a) the dry and rainy seasons; (b) the control and impacted areas; (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins (impacted: IRB; impacted: PRB; reference: IRB; reference: PRB) in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).
Fig. 4 Variation in the total abundance of fish between: (a) the dry and rainy seasons; (b) the control and impacted areas; (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins (impacted: IRB; impacted: PRB; reference: IRB; reference: PRB) in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).CC BY-NC-ND · PubMed Central
Fig. 5 Variation in the alpha diversity (α) of the fish assemblages between: (a) the dry and rainy seasons, (b) the control and impacted areas, (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).
Fig. 5 Variation in the alpha diversity (α) of the fish assemblages between: (a) the dry and rainy seasons, (b) the control and impacted areas, (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).CC BY-NC-ND · PubMed Central
Fig. 6 Variation in the beta diversity (β) of the fish assemblages between: (a) the dry and rainy seasons, (b) the control and impacted areas, (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).
Fig. 6 Variation in the beta diversity (β) of the fish assemblages between: (a) the dry and rainy seasons, (b) the control and impacted areas, (c) the IRB and PRB basins, and (d) the interaction between seasons and basins (dry: IRB; dry: PRB; rainy: IRB; rainy: PRB), (e) the interaction between areas and basins in the Carajás Mineral Province, Brazil, in May and November 2022. *Indicates a significant difference among the factors (p < 0.05).CC BY-NC-ND · PubMed Central
Fig. 7 Ordination of the Redundancy Analysis (RDA), showing the relationships between the selected abiotic factors (Temp. = temperature; Salin. = salinity; Cond. = conductivity) and the distribution of the fish species collected in the Carajás Mineral Province, Brazil, in May and November 2022.
Fig. 7 Ordination of the Redundancy Analysis (RDA), showing the relationships between the selected abiotic factors (Temp. = temperature; Salin. = salinity; Cond. = conductivity) and the distribution of the fish species collected in the Carajás Mineral Province, Brazil, in May and November 2022.CC BY-NC-ND · PubMed Central

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References 82 · Cited by 1

Research works printed but not linked: 17

  1. Correa, S. B. et al. Floodplain forests drive fruit-eating fish diversity at the Amazon Basin-scale. Proc. Natl. Acad. Sci. USA 122 (2025).
  2. Dani, A. et al. Social and environmental impacts of mining and spatialization of human development index (HDI) to the microregion of Parauapebas (PA). Revista GeoAmazônia. 10, 141–158 (2022). https://periodicos.ufpa.br/index.php/geoamazonia/index
  3. Pontes, P. R. M. et al. Environmental assessment based on soil loss, deforestation in permanent preservation areas, and water quality applied in the Itacaiúnas Watershed. East. Amazon. 13, 248–262 (2025).
  4. Ribeiro, E. S. et al. Multitemporal evaluation of the vegetation cover of the Tapirapé biological reserve, Pará. Res. Soc. Dev. 10, 4 (2021).
  5. Pontes, F. H. G. et al. For whom is the environmental protection? Territorial disputes between Vale and rural peasant communits: The case of the Rio Gelado Environmental Protection. Ambientes 3, 330–359 (2021).
  6. Camargo, M., Junior, H. G. & Py-Daniel, L. H. Ornamental Plecos of the Middle Xingu River, first edition (Belém-PA, 2012).
  7. Ohara, W. M. et al. Peixes do Rio Teles Pires: diversidade e guia de identificação. Neotropical Ichthyol. 15, 160085 (2017).
  8. Legendre, P., Legendre, L. & Edition Numerical Ecology, 2nd English Elsevier, Amsterdam, 1-853. - References - Scientific Research Publishing. Scirp.org (1998). https://www.scirp.org/reference/referencespapers?referenceid=3103110 (2021).
  9. Rigby, R. A. & Stasinopoulos, D. M. Generalized additive models for location, scale and shape (with discussion). J. Roy. Stat. Soc.: Ser. C (Appl. Stat.). 54, 507–554 (2005).
  10. Legendre, P. & Legendre, L. Numerical ecology (Elsevier, 2012).
  11. Dufrene, M. & Legendre, P. Species Assemblages and Indicator Species: The Need for a Flexible Asymmetrical Approach. Ecol. Monogr. 67, 345 (1997).
  12. Bührnheim, C. M. & Fernandes, C. C. Low seasonal variation of fish assemblages in Amazonian rain forest streams. Ichthyological Explor. Freshwaters. 12, 65–78 (2001).
  13. Ayoola, S. O. & Kuton, M. P. Seasonal variation in fish abundance and physicochemical parameters of Lagos lagoon, Nigeria. Afr. J. Environ. Sci. Technol. 3, 149–158 (2016).
  14. Gerking, S. D. Feeding ecology of fish (Academic Press, 1994).
  15. Mazzoni, R. & Caramaschi, E. P. Spawning season, ovarian development and fecundity of Hypostomus affinis (Osteichthyes, Loricariidae). Rev. Bras. Biol. 57, 455–462 (1997).
  16. De Oliveira, C. et al. Genotoxicity assessment in two Amazonian estuaries using the Plagioscion squamosissimus as a biomonitor. Environ. Sci. Pollut. Res. 29, 41344–41356 (2022). · DOI
  17. Rossoni, D. M. A utilização das descargas dos órgãos elétricos de Apteronotus hasemani e Apteronotus bonapartii (Apteronotidae-Gymnotiformes) como bioindicadores em ambientes aquáticos. Manaus: INPA. (2005).

Metadata

Authors
de Oliveira, C. A. C. R., Morais, K. S., de Oliveira, J. P. S., de Oliveira Marques, A., da Silva, A. B. F., da Conceição Palheta, D., & Bentes, B.
Affiliations
  • Universidade Federal do Pará (BR)
  • Instituto Federal de Educação, Ciência e Tecnologia do Pará (BR)
Corresponding author
de Oliveira, Claudia Antônia Campos Rodrigues
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2026-03-12
Volume
16
Issue
1
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-026-43889-8
PMC
PMC13102912
OpenAlex
W7135095830
Cited by
1
References
82
Citations by year
2026: 1
FWCI
3.99
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Instituto Chico Mendes de Conservação da Biodiversidade
Topics
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish biology, ecology, and behavior
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
  • Physical Sciences › Environmental Science › Ecology › Freshwater macroinvertebrate diversity and ecology
Keywords
fish diversity, fish abundance, environmental indicators, mining impacts, aquatic biodiversity, beta diversity, indicator species, seasonal variation, water quality, Amazon basin, protected areas, environmental monitoring
MeSH terms
Animals, Brazil, Environmental Monitoring, Fishes, Mining, Seasons, Ecosystem, Biodiversity, Rivers

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de Oliveira, C. A. C. R., Morais, K. S., de Oliveira, J. P. S., de Oliveira Marques, A., da Silva, A. B. F., da Conceição Palheta, D., & Bentes, B. (2026). The use of fish diversity and abundance as environmental indicators in a mining region in Brazilian Amazonia. Scientific Reports. https://doi.org/10.1038/s41598-026-43889-8

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