Reproductive rate and body size predict road impacts on mammal abundance
Bibliographic record
Abstract
It has been hypothesized that mobile species should be more negatively affected by road mortality than less-mobile species because they interact with roads more often, and that species with lower reproductive rates and longer generation times should be more susceptible to road effects because they will be less able to rebound quickly from population declines. Taken together, these hypotheses suggest that, in general, larger species should be more affected by road networks than smaller species because larger species generally have lower reproductive rates and longer generation times and are more mobile than smaller species. We tested these hypotheses by estimating relative abundances of 17 mammal species across landscapes ranging in road density within eastern Ontario, Canada. For each of the 13 species for which detectability was not related to road density, we quantified the relationship between road density and relative abundance. We then tested three cross-species predictions: that the slope of the relationship between road density and abundance should become increasingly negative with (1) decreasing annual reproductive rate; (2) increasing home range area (an indicator of movement range); and (3) increasing body size. All three predictions were supported in univariate models, with <i>R</i><sup>2</sup> values of 0.68, 0.50, and 0.52 respectively. The best overall model based on AIC<sub>c</sub> contained both reproductive rate (<i>P</i> = 0.008) and body size (<i>P</i> = 0.072) and explained 77% of the variation in the slope of the relationship between road density and abundance. Our results suggest that priority should be placed on mitigating road effects on large mammals with low reproductive rates.
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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 | 0.001 |
| 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) | 0.359 | 0.002 |
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".