Reach and Effectiveness of Conservation Translocations When Founder Animals Are Sourced From Zoos
Bibliographic record
Abstract
ABSTRACT Conservation translocations (e.g., reintroductions) are an important tool to replenish wildlife populations and manage biodiversity in lieu of emerging threats around the globe. Determining available and effective founder animal sources and evaluating outcomes in conservation translocations are critical to help mitigate challenges and maximize opportunities. Zoos and aquaria have a history of broad conservation engagement, but a global assessment of conservation translocations that used zoo‐sourced founder animals is lacking. We reviewed publications of conservation translocations that sourced founders from zoos ( n = 117) and qualitatively and quantitatively assessed global trends and factors associated with post‐release monitoring (PRM) duration and author‐perceived project outcomes. Confirmed reproduction occurring in recipient population(s) was associated with longer PRM durations. Projects having long‐term objectives and ex situ animal preconditioning (i.e., enriched for post‐release adaptability) had lower odds of author‐deemed translocation failure. Notably, the rate of perceived failures among projects with zoo‐sourced founders was lower (8.6%) when compared to broader conservation translocation trends of various founder sources (20.9%). Projects with zoo founders had a global reach across varying species risk statuses, although common regional and taxonomic biases in translocations remain. This review provides support that zoo animal founders can lead to effective conservation translocations and identifies factors useful to mitigate challenges linked to unsuccessful outcomes. Founder quality over quantity may be key—sourcing individuals optimal for post‐release survival and viability in the long term will be paramount. We support standardized reporting of all translocation project outcomes and recommend that conservation practitioners maximize opportunities to engage with zoos early in project planning stages to assess feasibility and inform strategies that facilitate effective conservation across the ex situ–in situ spectrum.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".