Decoupled responses of biodiversity facets driven from anuran vulnerability to climate and land use changes
Bibliographic record
Abstract
Anthropogenic climate and land use changes are the main drivers of biodiversity loss, promoting a major reorganization of the biota in all ecosystems. Biodiversity loss implies not only in the loss of species, but also entails losses in other dimensions of biodiversity, such as functional diversity, phylogenetic diversity and the diversity of ecological interactions.Yet, each of those facets of biodiversity may respond differently to extinctions. Here, we examine how extinction, driven by climate and land-use changes may affect different facets of diversity (functional, phylogenetic, and interaction diversity) by combining empirical data on interaction networks between anurans and their prey, species distribution modeling and extinction simulations.We used species distribution modeling to forecast the redistribution of anurans and create a species vulnerability rank based on expected range changes, then we simulate the extinction of anurans based on this rank. Next, we computed the variation in the functional, phylogenetic, and interaction diversities resulting from projected extinctions in four different ecoregions in the Neotropics. We found that the anuran vulnerability to climate and land-use change varies according to the level of trophic specialization. We also found a mismatch in the response of functional, phylogenetic, and interaction diversity to species’ extinction, whereby the effects on interaction diversity are stronger than those on phylogenetic and functional diversity. Although it is often assumed that interaction patterns are reflected by functional diversity, assessing the interaction patterns is necessary to understand how species loss may translate into the loss of ecosystem functions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".