A generic method to assess species exploratory potential under climate change
Bibliographic record
Abstract
Climate, by altering the spatio-temporal distributions of suitable habitats, leads to modifications in a multitude of species ranges. In recent years, the ability of species to adjust to changing climatic conditions is of growing concern. In the present study, a generic trait-based method to assess species exploratory potential under climate change is proposed. “Exploratory potential” is here defined as the capacity of species to initiate the act of leaving their current habitats and to reach new ones outside of their range, at a rate fast enough to keep pace with climate change. The presented method is based on the calculation of the Exploratory Potential Index (EPI), a metric that combines several life-history traits into a single numeric value. Both coefficients and variables of this composite metric are flexible. They depend on the set of species under consideration through a two-step participatory expert-based procedure. A panel of experts on the species’ biology, ecology and conservation is first to be constituted. Then, experts are separately consulted to validate the variables to be integrated in the composite EPI index and are asked to rank the importance of these variables relative to each other following an Analytic Hierarchy Process. Coefficients in the EPI index and scores are given a credibility distribution using a Bayesian inference model. Anadromous species are chosen as a first application case. Scripts and raw survey data are made available to readers to ease applications to other species groups.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.228 | 0.016 |
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; both teacher heads agree on what is shown here.
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".