Impact and Lessons Learned from A Half-Century of Primate Conservation Action Planning
Bibliographic record
Abstract
Over the last half-century, the world’s human population has doubled, impacting almost all ocean and land areas. The threats facing primates in the wild have never been greater or more complex. Primatologists have long been aware of these threats and, since the 1970s, have coordinated efforts to safeguard these threatened species, through the International Union for Conservation of Nature Species Survival Commission (IUCN SSC) Primate Specialist Group (PSG). In an effort to stem the threat of extinction to primates, this group of now 700 experts+ has published 17 conservation action plans since 1977. As we look toward the next half-century, we take stock of the history of primate action planning to better understand the costs and benefits of these plans as a conservation tool. Here, we reviewed all plans published by the IUCN SSC PSG. In total, they described USD 246 million in planned primate conservation programming and were cited 1657 times by others. We found that half of the plans had been assessed in regard to their implementation, although these assessments were not standardized. Those that had been assessed, showed evidence of positive impacts on awareness raising, collaboration, fundraising, project implementation and policy, although the impact varied by plan. For example, three of the plans directly resulted in USD 15.92 million in funds raised; four plans quantified implementation rates, which ranged from 38% to 74% of actions partially or completely achieved 5 years after plan publication; and four plans attributed the gazettement of 19 protected areas across 11 countries as indirect successes following the publication of plans. Considered together, we reflect on the ‘return-on-investment’ for developing these plans and consider a range of ‘lessons learned’ for future primate action planning efforts.
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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 | 0.054 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".