Impacts of climate change on the movement ecology of an imperfect homeotherm
Bibliographic record
Abstract
Rapid, human-induced climate change has posed significant challenges to wildlife. One key strategy animals use to cope with environmental temperature fluctuations is behavioral thermoregulation. Understanding how climate change is expected to influence animal behavior is crucial for assessing its impact on species survival and informing effective conservation efforts. Giant anteaters have been found to exhibit conspicuous behavioral responses to temperature changes. Despite their broad thermal neutral zone (15 - 36°C), climate projections indicate that this vulnerable mammal is increasingly likely to experience heat stress. We used GPS tracking and continuous-time analyses to investigate how environmental temperature influences the movement ecology of giant anteaters. We integrated our findings with climate change projections to link giant anteater's responses to present weather conditions with those expected under future climate scenarios. Giant anteaters' movement speed exhibited a negative quadratic response to temperature, peaking at 23.7°C. 95% of their movement occurred between 15.0 - 32.3°C, which aligns with their thermal neutral zone. The increasing temperature led giant anteaters to increase selection for native forests, but had no effect on selection for exotic tree plantations. This shows the importance of native forests as these thermal shelters help to mitigate the negative consequences of high temperatures on anteater's movement. However, the warmer temperatures predicted for Brazil throughout the rest of the 21st century indicate that giant anteaters may experience a reduction of up to 84% in their movement speed. This would hinder the acquisition of sufficient energy resources and threaten the species' persistence. We emphasize the need for conservation efforts that account for the impacts of climate change on species survival and stress the importance of preserving forests as essential refuges that help wildlife to cope with rising temperatures.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".