Influence of habitat type on the decay and disappearance of elk <i>Cervus canadensis</i> pellets in boreal forest of northwestern Canada
Bibliographic record
Abstract
Fecal pellet counts are often used to assess trends in ungulate population size and habitat use. However, various factors may influence the physical decay and disappearance of pellets, where disappearance may be a result of physical decay and other factors (e.g. trampling, scattering and concealment by vegetation). Knowing pellet decay and disappearance rates in different habitats is a prerequisite to acquiring reliable information from pellet counts. We examined elk Cervus canadensis pellet decay and disappearance of individual pellets and pellet groups in six habitats in the boreal forest of northwestern Canada. We monitored 120 pellet groups deposited in May 2008 at 4, 12, 16 and 28 month intervals (i.e. the end of each of three plant growing seasons) to assess differences in physical decay and disappearance. Pellet decay and disappearance varied among habitats. In moist habitats, pellets showed little sign of decay by the end of our study, likely due to a short plant growing season. In drier, open habitat types, pellet decay was more rapid, likely due to exposure to sun and wind. By the end of our study, the percent of pellets remaining varied from a 14–82% among the sampled habitats. Pellets in moist forest habitats had the lowest decay rates but the highest disappearance rates, whereas those in dry, grassland sites had the highest decay, but the lowest disappearance rates. Our study further demonstrates that ungulate pellet decay and disappearance may differ substantially among habitats, which has important implications for the design of ungulate monitoring programs that utilize pellet counts. We conclude by recommending that fecal accumulation rate (FAR) methods are likely more appropriate in our study area than fecal standing crop (FSC) methods for estimating elk density, because FAR methods are less prone to biases associated with differential pellet decay and disappearance among habitats.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".