Fishing for conservation of freshwater tropical fishes in the Anthropocene
Bibliographic record
Abstract
Abstract The ecosystem services provided by freshwater biodiversity are threatened by development and environmental and climate change in the Anthropocene. Here, case studies are described to show that a focus on the shared dependence on freshwater ecosystem functioning can mutually benefit fisheries and conservation agendas in the Anthropocene. Meeting the threat to fish biodiversity and fisher livelihood is pertinent in developing regions where there is often a convergence between high biodiversity, high dependency on aquatic biota and rapid economic development (see Kafue River, Logone floodplain, Tonle Sap, and Rio Negro case studies). These case studies serve as evidence that biodiversity conservation goals can be achieved by emphasizing a sustainable fisheries agenda with partnerships, shared knowledge and innovation in fisheries management (see Kafue River and Kenai River case studies). In all case studies, aquatic biodiversity conservation and fisheries agendas are better served if efforts focused on creating synergies between fishing activities with ecosystem functioning yield long‐term livelihood and food security narratives. A unified voice from conservation and fisheries communities has more socio‐economic and political capital to advocate for biodiversity and social interests in freshwater governance decisions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".