Occupancy dynamics of rare cyprinids after invasive fish eradication
Bibliographic record
Abstract
Abstract The eradication of invasive species is a management strategy implemented to eliminate adverse impacts of invaders on native species communities. After eradications, follow‐up studies are done to confirm eradication of the invasive species and the short‐term recovery of the native species, but long‐term monitoring to confirm full population recovery and stability is often not completed. In this study, long‐term monitoring of native fishes was carried out over 5 years after the eradication of an invasive fish from the Rondegat River, South Africa. Forty‐six sites distributed along four river sections were sampled for presence/absence using underwater cameras and snorkel surveys. Density data were collected by snorkel surveys. Using multi‐season occupancy models, the annual probability of colonization and local extinction of the native fishes and annual rate of change in occupancy along the river were estimated. Changes in native fish densities across time and across the control and treatment sections were analysed using Kruskal–Wallis analysis, followed by Dunn's post‐hoc test. Probability of colonization and local extinction differed for each native fish species and may have been affected by extrinsic factors, such as rainfall, and intrinsic density‐dependent factors, hypothesized from the density data. The occupancy rates of change revealed that the two Near Threatened fish species have reached an occupancy dynamic equilibrium but the Endangered fish has not, suggesting that other conservation efforts may be needed. Long‐term monitoring of native fishes after an eradication programme has confirmed the successful removal of the invader and the recovery and stability of the community. However, successful eradication was not sufficient for full recovery of all species; additional conservation management strategies are needed to secure the population stability and persistence of endangered fishes. We recommend that eradication programmes, regardless of locality, should employ long‐term monitoring to ensure full recovery of a native fish community.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".