Influence of hybridization on animal space use: a case study using coyote range expansion
Bibliographic record
Abstract
Hybridization between animal species is likely to increase as distributional and reproductive barriers continue to break down due to anthropogenically driven changes in habitat and climate. Yet, the influence of hybridization on ecological interactions and ecosystem function remains understudied. Animal space use, an important component of ecosystem dynamics, is a complex relationship between intrinsic factors, which hybridization can influence, and extrinsic factors, such as environmental heterogeneity. Using the coyote Canis latrans , a well‐studied species with a long history of hybridization with wolves and dogs Canis spp., we sought to assess the influence of hybridization relative to environmental factors in determining animal space use. We conducted a meta‐regression analysis of 67 datasets on coyote home range size across North America and generated models to predict coyote home range size. Climate (latitude) and environmental variability played important roles in determining patterns of coyote space use, likely through their influence on availability of prey resources. However, we found hybridization to be the preeminent factor driving variation in coyote space use, with non‐introgressed populations having considerably smaller home ranges than those from within the Canis hybrid zone of eastern North America. This pattern was upheld despite the variation in environmental factors between areas inside and outside the Canis hybrid zone. Our findings suggest that hybridization may serve as an important factor affecting ecosystems, as hybrids may have altered space requirements, and presumably different niche dimensions, compared to parental species. This, in turn, may influence the role that particular species play within communities. Synthesis Hybridization between animal species is likely to increase due to anthropogenically driven changes in habitat and climate. We used a meta‐regression analysis (n = 67) to examine the relationship between hybridization and coyote Canis latrans space use across North America. We found that independent of environmental factors, introgressed coyotes had larger home ranges. Our findings suggest that hybridization may serve as an important factor affecting ecosystems, as hybrids may have altered space requirements, and presumably different niche dimensions, compared to parental species. This, in turn, may influence the role that particular species play within communities.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".