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Record W7066518966

How competition dynamics drive access to shared scavenging opportunities amongst a group of mesocarnivores in the Rocky Mountains of Alberta

2021· dissertation· en· W7066518966 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2021
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCompetition (biology)CarrionGuildFacultativeInterspecific competitionEcosystemUnderstoryIntraguild predationBromus tectorum
DOInot available

Abstract

fetched live from OpenAlex

Mesocarnivores occupy critical functional roles in regulating ecosystems and maintaining biodiversity. In the Canadian Rocky Mountains, mustelid species depend heavily on carrion as an important dietary contribution, particularly in winter when resources are scarce. In diverse mesocarnivore communities such as this, sympatric species must balance energetic resource acquisitions through scavenging with avoidance of costly competition dynamics, in a manner that optimizes energetic gain through risk aversion. We examined the nature of spatial-temporal interactions between wolverine (Gulo gulo), American marten (Martes Americana), and short-tailed weasel (Mustela erminea) in the Willmore Wilderness Park in western Alberta. Data were collected from camera traps (n = 59) baited with a simulated scavenging opportunity during winter months between 2006 to 2008. The spatial-temporal dimensions of intraguild competition were evaluated using a multi-model approach. Zero-inflated negative binomial (ZINB) or zero-inflated Poisson (ZIP) regression models were used to identify the competitive and environmental factors that affected (1) species presence/absence and (2) how intensely a species would spatiotemporally optimize a carrion site. A time-to-event analysis was used to quantify the directionality of fine-scale (hourly) reactionary behavioural responses of species to potential sources of competition. An extension of this group of models, the Cox proportional hazard (CPH) model was used to further reveal the relative influence of external environmental variables (i.e. diel period, landcover, and snow depth) on temporal spacing. Pairing CPH and ZINB/ZIP models enables us to recognize the relative contribution of fine-scale spatial and temporal behavioural responses to competitors in shaping coexistence strategies. Our results suggest that facultative scavengers adopt different coexistence mechanisms based on the interspecific competitor and environmental conditions they encounter at carrion sites. We found that carrion use was impacted for all species by competition and snow depth. Marten scavenging behaviours were additionally impacted by habitat character. We also found evidence of fine-scale temporal attraction between marten and wolverine, thought to indicate a shared net-energetic gain at scavenging sites. Our results suggest that mesocarnivore scavengers are likely to adopt spatiotemporal mechanisms to facilitate carrion resource partitioning and adapt to conditions specific to carcass placement in a spatially complex environment. Given their vital ecological roles, it is important that we recognize the ability of individual mustelid species to exploit scavenging opportunities and identify the external factors that influence coexistence. Understanding the factors that drive access to these ephemeral resources will provide valuable information for anticipating impacts of climate change on facultative scavengers in the boreal forests of western Canada.

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)0.001
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 score0.152
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.252
Teacher spread0.202 · 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
Published2021
Admission routes1
Has abstractyes

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