The value and propriety of reintroduction as a conservation tool for rare plants
Bibliographic record
Abstract
Three recent reviews of reintroduction for conservation purposes, which draw on substantial and largely nonoverlapping data sets, have come to strikingly different conclusions about its value. One concludes that “reintroduction is generally unlikely to be a successful conservation strategy as currently conducted”. Another concludes that “…this review cannot conclusively comment on the effectiveness of reintroductions…” The third concludes that there is “strong evidence in support of the notion that reintroduction, especially in combination with ex situ conservation, is a tool that can go a long way toward meeting the needs it was intended to address”. The argument over the conservation value of reintroduction is of more than academic interest. It illustrates a challenge facing land managers and decision makers who may be tempted to act on stated conclusions without thoroughly understanding their underlying assumptions, methodology, and terminology. The differing conclusions can be partially explained by different criteria of what constitutes success, how to measure it, and differing time scales considered. The propriety of reintroduction is briefly discussed and focuses on the following two issues: translocation of naturally occurring individuals to new locations and introduction outside a species' naturally occurring range. Both have appropriate uses but can be used in ways that detract from the survival prospects of taxa.
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 | 0.039 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".