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Linking moose habitat selection to limiting factors

2005· article· en· W1990608295 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEcography · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHabitatPredationEcologySnowLimitingRange (aeronautics)Spatial ecologySelection (genetic algorithm)Vegetation (pathology)GeographyHome rangeScale (ratio)BiologyCartography

Abstract

fetched live from OpenAlex

It has been suggested that patterns of habitat selection of animals across spatial scales should reflect the factors limiting individual fitness in a hierarchical fashion. Animals should thus select habitats that permit avoidance of the most important limiting factor at large spatial scales while the influence of less important factors should only be evident at fine scales. We tested this hypothesis by investigating moose Alces alces habitat selection using GPS telemetry in an area where the main factors limiting moose numbers were likely (in order of decreasing importance) predation risk, food availability and snow. At the landscape scale, we predicted that moose would prefer areas where the likelihood of encountering wolves was low or areas where habitats providing protection from predation were dominant. At the home‐range scale, we predicted that moose selection would be driven by food availability and snow depth. Wolf territories were delineated using telemetry locations and the study area was divided into 3 sectors that differed in terms of annual snowfall. Vegetation surveys yielded 6 habitat categories that differed with respect to food availability, and shelter from predation or snow. Our results broadly supported the hypothesis because moose reacted to several factors at each scale. At the landscape scale, moose were spatially segregated from wolves by avoiding areas receiving the lowest snowfall, but they also preferentially established their home range in areas where shelter from snow bordered habitat types providing abundant food. At the home‐range scale, moose also traded off food availability with avoidance of deep snow and predation risk. During winter, moose increased use of stands providing shelter from snow along edges with stands providing abundant food. Habitat selection patterns of females with calves differed from that of solitary moose, the former being associated primarily with habitats providing protection from predation. Animals should attempt to minimize detrimental effects of the main limiting factors when possible at the large scale. However, when the risk associated with several potential limiting factors varies with scale, we should expect animals to make trade‐offs among these.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.212
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