Conservation Paleobiology: Leveraging Knowledge of the Past to Inform Conservation and Restoration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Humans now play a major role in altering Earth and its biota. Finding ways to ameliorate human impacts on biodiversity and to sustain and restore the ecosystem services on which we depend is a grand scientific and societal challenge. Conservation paleobiology is an emerging discipline that uses geohistorical data to meet these challenges by developing and testing models of how biota respond to environmental stressors. Here we (a) describe how the discipline has already provided insights about biotic responses to key environmental stressors, (b) outline research aimed at disentangling the effects of multiple stressors, (c) provide examples of deliverables for managers and policy makers, and (d) identify methodological advances in geohistorical analysis that will foster the next major breakthroughs in conservation outcomes. We highlight cases for which exclusive reliance on observations of living biota may lead researchers to erroneous conclusions about the nature and magnitude of biotic change, vulnerability, and resilience.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it