Uncovering habitat associations and thresholds—insights for managing breeding waterfowl in Eastern Canada
Bibliographic record
Abstract
Abstract Context Understanding how habitat influences species abundance is crucial in developing ecologically sound wildlife conservation management plans. Exploring habitat associations and ecological thresholds in species’ responses allows for better conservation and management on a landscape-scale. Objectives This work aimed to identify habitat drivers and response thresholds of waterfowl and waterbird species’ densities in eastern Canada to support key landscape-level decisions for habitat conservation and wetland management. Methods We developed predictive abundance models for 17 species across eastern Canada from 2001 to 2015 using data from four regional surveys and identified areas where prioritizing enhancement of wetlands would increase the breeding density of five priority waterfowl species. Results Habitat associations and spatial abundance patterns varied across species, but most species responded strongly to forest composition, agriculture, and wetland features. Threshold effects occurred and varied among species, yet generally once 14% of a plot was covered in wetlands, positive effects of increased wetland diminished for most species. Our results allow for the targeting of investments in increasing wetland area along portions of eastern Canada that provide the best opportunities to increase breeding densities for priority waterfowl species. Conclusions Understanding species-habitat associations and response thresholds allows for landscape management and planning and prioritization of limited resources. We suggest that management and wetland enhancement efforts for waterfowl in eastern Canada should be guided by predictive models and response thresholds of key habitat attributes to best prioritize actions that will have the biggest positive impact on multiple species.
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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) | 0.002 | 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".