Wildlife Forage Recovery Following Boreal Wildfire
Bibliographic record
Abstract
Climate change is altering the boreal wildfire regime through increases in the extent and severity of burning and reductions in fire return intervals. These changes can alter the regeneration trajectory of canopy species and ground vegetation, with implications for wildlife habitat. There is some uncertainty about the timelines of when different animal species will use burned areas as their preferred forage taxa recover following fire, and how such recovery is mediated by environmental factors. Here, we aim to address these knowledge gaps through the following questions: 1) What are the main forage types consumed by boreal wildlife and how much dietary overlap is there among taxa?, 2) How does time after fire affect boreal vegetation recovery and how do environmental factors mediate recovery processes? and 3) Can information on post-fire community assembly processes be used to anticipate periods of habitat selection by different boreal wildlife taxa and where overlap in timing of use may occur? A literature review examining the diets of several boreal wildlife taxa (e.g., caribou, moose) was performed to identify major forage types. Vegetation data collected from 581 plots in the Northwest Territories, Canada, ranging from 1 to more than 100 years post-fire, was then used to model trends in the relative abundance of key forage taxa for different wildlife species, and to test the influence of time after fire and local environmental conditions on plant community composition. Time after fire was a significant driver of boreal vegetation recovery, but accounted for only a small proportion of total community variation. Patterns of post-fire recovery varied greatly among forage species and were often strongly mediated by soil moisture. This suggests that, although time after fire influences wildlife forage over the long-term, site-specific environmental conditions are also important and should be considered when assessing the implications of increased fire activity. The results of this research are intended for use by northern communities, to help anticipate and plan for the consequences of increased burning, and by land-use managers charged with the effective conservation of wildlife habitat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".