Mule deer–cattle interactions in managed coniferous forests during seasonal grazing periods in southern British Columbia, Canada
Bibliographic record
Abstract
Context In young forests of the Pacific North-west of North America, the potential impacts of domestic grazing by cattle (Bos taurus) on forest ecosystems and native ungulates such as mule deer (Odocoileus hemionus) are poorly understood. It is not clear how cattle and deer may interact in young forests used for summer range by both ungulates, and winter range used by deer, where pre-commercial thinning (PCT) and fertilisation enhance both timber and forage. Aims To test the following two hypotheses: (H1) that PCT and repeated fertilisation of young lodgepole pine (Pinus contorta var. latifolia) stands would increase relative habitat use by cattle; and (H2) that increased use of forested range by cattle would result in decreased use by mule deer. Methods Replicate study areas were located near Summerland, Kelowna, and Williams Lake in south-central British Columbia, Canada. Each study area had the following nine treatments: four pairs of stands thinned to densities of ~250 (very low), ~500 (low), ~1000 (medium), and ~2000 (high) stems ha–1 with one stand of each pair fertilised five times at 2-year intervals. Relative habitat use was measured by counting cowpies for cattle in summer and pellet groups for deer in summer and winter periods 1998–2003. Key results Relative habitat use by cattle was significantly enhanced by fertiliser treatments and heavy thinning, supporting H1. Relative habitat use by deer during summer periods was not affected by stand density, but was significantly higher in fertilised than unfertilised stands, with no difference in winter months, thereby not supporting H2. Conclusions Summer habitat use by mule deer appeared to be a function of forage opportunities and no significant correlations in relative habitat use between cattle and mule deer during the summer were detected. Negative correlations were better explained by the need for tree cover by deer during severe winter conditions than a negative response to cattle grazing. Implications Domestic grazing by cattle may be compatible with native ungulates such as mule deer, at least in those forest sites that are managed intensively for timber production. Fertilisation may result in sufficient forage production in the understorey vegetation of these forest ecosystems, to compensate for cattle grazing that reduces the live forage biomass.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".