Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin.
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Abstract
Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Biodiversity underpins fisheries resilience to exploitation in the Amazon River basin. |
| Series title | Proceedings of the Royal Society B, Biological Sciences |
| DOI | 10.1098/rspb.2022.0726 |
| Volume | 289 |
| Issue | 1976 |
| Publication Date | June 08, 2022 |
| Year Published | 2022 |
| Language | English |
| Publisher | The Royal Society |
| Contributing office(s) | Coop Res Unit Leetown |
| Description | 20220726, 10 p. |
| Country | Brazil, Peru |
| Other Geospatial | Amazon River basin |