Priority research needs to inform amphibian conservation in the Anthropocene
Bibliographic record
Abstract
Abstract The problem of global amphibian declines has prompted extensive research over the last three decades. Initially, the focus was on identifying and characterizing the extent of the problem, but more recently efforts have shifted to evidence‐based research designed to identify best solutions and to improve conservation outcomes. Despite extensive accumulation of knowledge on amphibian declines, there remain knowledge gaps and disconnects between science and action that hamper our ability to advance conservation efforts. Using input from participants at the ninth World Congress of Herpetology, a U.S. Geological Survey Powell Center symposium, amphibian on‐line forums for discussion, the International Union for Conservation of Nature Assisted Reproductive Technologies and Gamete Biobanking group, and respondents to a survey, we developed a list of 25 priority research questions for amphibian conservation at this stage of the Anthropocene. We identified amphibian conservation research priorities while accounting for expected tradeoffs in geographic scope, costs, and the taxonomic breadth of research needs. We aimed to solicit views from individuals rather than organizations while acknowledging inequities in participation. Emerging research priorities (i.e., those under‐represented in recently published amphibian conservation literature) were identified, and included the effects of climate change, community‐level (rather than single species‐level) drivers of declines, methodological improvements for research and monitoring, genomics, and effects of land‐use change. Improved inclusion of under‐represented members of the amphibian conservation community was also identified as a priority. These research needs represent critical knowledge gaps for amphibian conservation although filling these gaps may not be necessary for many conservation actions.
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 | 0.111 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".