Combined impacts of climate and land use change and the future restructuring of Neotropical bat biodiversity
Bibliographic record
Abstract
Forecasting the effects of global change on biodiversity is necessary to anticipate the threats operating at different scales in space and time. Climate change may create unsuitable environmental conditions, forcing species to move to persist. However, land-use changes create barriers that limit the access of some species to future available habitats. Here, we project the impacts of climate and land-use change on 228 Neotropical bat species by forecasting changes in environmental suitability, while accounting for the effect of habitat type specialization and simulating dispersal across suitable patches. We also identify the most vulnerable ecoregions and those that may offer future stable refugia. We further investigate potential functional changes by analysing the response of different trophic guilds. We found that the range contraction of habitat specialists, especially frugivores, was more frequent and stronger under all simulated scenarios. Projected changes differ markedly across ecoregions. While the Amazon region is likely to undergo high turnover rates in bat composition, the Andean grassland, Cerrado and Chaco might experience the greatest losses. The expansion of habitat generalists, which forage in open areas and commonly establish large colonies in manmade structures, coupled with the range contraction of habitat specialists is projected to homogenize bat communities across the Neotropics. Overall, dispersal will likely be the key for the future of Neotropical bat diversity. Therefore, safeguarding the refugia highlighted here, by expanding and connecting the existing network of protected areas, for example, may allow species to move in response to global change.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".