Recovery, conservation status, and environmental effects on arapaima populations in Guyana
Bibliographic record
Abstract
Abstract Using population estimates that were made regularly between 2001 and 2013, the state of recovery of arapaima populations and their IUCN conservation status were assessed after they were almost extirpated from the upper Essequibo basin, Guyana. Recovery rates were compared across multiple areas with different degrees of access by fishers to evaluate effectiveness of conservation efforts. Population estimates were also used to investigate the influence of environmental factors on arapaima abundance in lakes with different morphometries, vegetation, and water types and to determine the relationship between the numbers of spawning individuals and subsequent recruits (at about age 2 years). The most recent census conducted in November–December of 2013 indicated a 5.6‐fold increase in overall abundance compared with 2001, with 4,591 individuals, of which 1,932 were juveniles (1.0–1.5 m total length) and 2,659 adults. Assessment of conservation status following IUCN criteria indicated that arapaima populations in the upper Essequibo basin in 2001 would have been considered borderline Critically Endangered, but in 2013 after conservation interventions, status would be categorized as Near Threatened. Arapaima in the Essequibo basin appear to favour larger but shallow lakes with low conductivity, clear water, and abundant aquatic macrophytes. Stock–recruitment relationships suggest that the entire upper Essequibo basin population may still be growing and that there is approximately a 1:1 juvenile to adult ratio. This ratio of juveniles to adults across all areas suggests a paucity of young fishes to sustain overall population growth, which might reflect widespread illegal removals of young fishes in the basin. Comparisons of arapaima densities in the upper Essequibo basin with those at four localities across the Amazon Basin, suggest that with enhanced conservation efforts in the Essequibo, populations could potentially increase two‐fold or more.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".