Effects of interspecific interaction-linked habitat factors on moose resource selection and environmental stress
Bibliographic record
Abstract
Resource selection of herbivores is a complex ecological process that operates in relation to biological or non-biological factors, which may affect the feeding and movement, and subsequently their spatial distribution and environmental stress. Here, we estimated moose (Alces alces cameloides) resource selection for habitat variables and the effect of interspecific interactions related to roe deer (Capreolus pygargus bedfordi) on its population distribution and environmental stress in the Khingan Mountain region of northeast China at local and regional scales. Different response patterns of moose resource selection, spatial distribution, and environmental stress to interspecific interaction-linked habitat factors were shown at the two scales. A general ecological chain, response of moose to interspecific interaction-linked habitat factors, was exhibited at the regional scale, and at the local scale, heterogeneous responses, linkages of habitat selection and environmental stress of moose population might be driven by different interspecific interaction patterns. Our study firstly suggested that moose resource selection, food availability, diet quality, population density and environmental stress indicators were impacted by interactions with the distribution of other sympatric herbivore species and showed differences in ecological response chains at various spatial scales. These findings are useful for sympatric herbivore assembly conservation, habitat quality monitoring and management.
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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 | 0.000 | 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) | 0.001 | 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".