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Record W4402915289 · doi:10.24124/2024/59543

Spatiotemporal overlap of sympatric mesocarnivores in central British Columbia, Canada

2024· dissertation· en· W4402915289 on OpenAlexaboutno aff
Lauren Wheelhouse

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsSympatric speciationGeographyEcologyBiology

Abstract

fetched live from OpenAlex

,Many wildlife species use similar resources, leading to the potential for overlapping niches. These overlaps can create negative interspecific interactions, including different forms of competition. Niche overlap can be experienced on several different axes, including spatial, temporal, and dietary. There are many factors that may affect species co-occurrence patterns, including population cycles, natural and anthropogenic landscape change, harvest mortality, and changes in resource availability. Effective wildlife management is dependent on an understanding of the interaction between community dynamics and competition. Many mesocarnivores in central British Columbia overlap spatially, temporally, and dietarily. This high degree of overlap means that understanding the mechanisms facilitating their coexistence is particularly important. I used five years of data from remote cameras and fine-scale habitat data from LiDAR to assess patterns in the spatial and temporal co-occurrence of short-tailed weasels (Mustela erminea), American mink (Neogale vison), American marten (Martes americana), fishers (Pekannia pennanti), wolverines (Gulo gulo), and Canada lynx (Lynx canadensis). During this study, there were fluctuations in snowshoe hare (Lepus americanus) abundance, as well as many predators, specifically decreases in lynx and increases in fisher. Habitat features, like structural complexity, can facilitate species co-occurrence by allowing for fine-scale niche partitioning. I used multi-species occupancy models to test hypotheses about the relationships between mesocarnivore co-occurrence and habitat. Mesocarnivores were more likely to co-occur at sites with greater complexity of vertical forest structure and at sites closer to riparian zones. Short-tailed weasels, however, did not co-occur with other mustelids in riparian zones. Importantly, I found that habitat covariates associated with co-occurrence were relatively similar over time despite notable changes in the abundance of predators and prey. My findings highlight the importance of riparian habitats and forest complexity in facilitating species co-occurrence in harvested forests. Temporal niche partitioning is a second mechanism that allows species to co-exist in space and may occur if one species shifts its temporal activity patterns to avoid interactions with another. I tested the hypothesis that smaller-bodied species would shift their activity in the presence of larger-bodied species. I found partial support for this hypothesis in that marten activity differed in the presence of larger-bodied lynx when lynx were abundant but not when lynx were rare. Furthermore, the activity patterns of the largest mesocarnivores in our study, lynx and wolverine, were unaffected by the presence of smaller species. In contrast with my hypothesis, weasel activity was similar in the presence of larger-bodied species. Collectively, these findings suggest that mesocarnivores may alter their temporal use of habitat to avoid co-occurrence in response to the presence of other species. Combined, my research provides insight into the mechanisms by which mesocarnivores—species with overlap in diet and habitat—share space. My findings highlight the importance of forest management practices that retain structural complexity and riparian areas to promote the co-existence of sympatric mesocarnivores. Further, my results emphasize the responses of sympatric species to changes in community dynamics, which is important for understanding the effects of population cycles on species co-occurrence.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.003
GPT teacher head0.180
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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