Evaluating how stand level forest dynamics influence caribou winter range
Bibliographic record
Abstract
Forest ecosystems and the ecological services they provide are complex and dynamic. Disturbance and successional processes impact habitat for animals such as caribou (Rangifer tarandus caribou Gmelin 1788, Banfield 1961, 1974) and moose (Alces alces L.). The forested winter habitat of the Tweedsmuir-Entiako caribou herd has been significantly affected by recent disturbance. In order to evaluate the mid- and long-term consequences for habitat, we require an understanding of how habitat attributes change as stand structure changes over time. I developed a framework to link a stand dynamics model (SORTIE-ND), via linker functions, to three ecosystem elements relevant to caribou populations: terrestrial forage lichen, moose forage, and vertical cover. I first used SORTIE-ND to model stand structure dynamics following mountain pine beetle (Dendroctonus ponderosae Hopkins) attack and clearcut harvesting. I developed linker functions and refined them with empirical data. These functions were applied to stand structure output from SORTIE-ND to project the response of habitat to the disturbance agents. I addressed three questions: 1. What is the influence of edaphic site on the provision of elements of caribou habitat over time? 2. What is the influence of stand type on the provision of elements of caribou habitat over time? 3. How do recovery trajectories of caribou habitat elements differ in response to disturbances such as mountain pine beetle and clearcut harvest? I found that site and stand type interacted to influence the suitability of terrestrial lichen, moose forage and vertical cover. Poor productivity sites were most favourable for terrestrial forage lichen. Higher productivity stands and broadleaf stands provided the greatest suitability for moose shrubs. Both mountain pine beetle attack and clearcut harvest improved stand suitability for lichen and moose browse though for different sites and stand types. Interestingly, I found that severe mountain pine beetle attack resulted in conditions that favoured forage lichen for longer than clearcuts. Clearcuts resulted in conditions that were more suitable than mountain pine beetle attack for winter forage for moose. When operating on landscapes with caribou winter habitat, forest managers should consider disturbance history, the distribution of sites and stand types, silviculture systems and the future desired state of ecosystem services. The SORTIE-ND modelling framework could be used to support the evaluation of alternative management decisions in caribou winter habitat including alternative silviculture strategies. This approach could also provide stand- and site-specific trajectories of the recovery of caribou habitat that could be applied to habitat supply models.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".