Insect-weather indicies and the effects of insect harassment on caribou behaviour and activity budgets
Bibliographic record
Abstract
Many barren-ground caribou (Rangifer tarandus groenlandicus) populations in the Central Arctic are experiencing declin ing numbers. Possible causes include conditions on the post-calving/summer range, especially harassment by biting and parasitic insects. Insect harassment alters habitat use and activity budgets of caribou, potentially leading to reduced forage intake and elevated energy expenditures. This is of particular concern as climatic warming is predicted to increase the duration and intensity of insect activity. In this study, I collected weather, insect catch, and caribou behaviour data on the summer range of the Bathurst caribou herd in the Northwest Territories/Nunavut in 2007 and 2008. I used count models within a generalized linear model framework to explore the relationship between weather parameters and insect activity. The best models, selected using Akaike's information criteria (AIC), were used to develop a correlative insectweather index applicable across the Bathurst range. Additionally, I developed models of fine-scale caribou behaviour as a function of vegetation type, phenological stage, topography, time, and insect activity. Model sets were developed for six behaviour categories, and the most parsimonious models selected using AIC. In this poster presentation, I will discuss results regarding insect indices and factors affecting fine-scale caribou behaviour (completion of analysis expected by September/October 2008). In continued work on this project, these results will be used in conjunction with GPS collar data and energetics modeling to explain patterns of movement and habitat use at coarser spatiotemporal scales, as well as to explore consequences for caribou population productivity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".