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Record W2033270550 · doi:10.7557/2.28.1.150

A synthesis of scale-dependent ecology of the endangered mountain caribou in British Columbia, Canada

2008· article· en· W2033270550 on OpenAlexaboutno aff
Robert Serrouya, Bruce N. McLellan, Clayton D. Apps, Heiko U. Wittmer

Bibliographic record

VenueRangifer · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsWoodland caribouEcologyGeographyEndangered speciesPopulationAbundance (ecology)PredationArboreal locomotionSpatial ecologyHabitatBiology

Abstract

fetched live from OpenAlex

Mountain caribou are an endangered ecotype of woodland caribou (Rangifer tarandus caribou) that live in highprecipitation, mountainous ecosystems of southeastern British Columbia and northern Idaho. The distribution and abundance of these caribou have declined dramatically from historical figures. Results from many studies have indicated that mountain caribou rely on old conifer forests for several life-history requirements including an abundance of their primary winter food, arboreal lichen, and a scarcity of other ungulates and their predators. These old forests often have high timber value, and understanding mountain caribou ecology at a variety of spatial scales is thus required to develop effective conservation strategies. Here we summarize results of studies conducted at three different spatial scales ranging from broad limiting factors at the population level to studies describing the selection of feeding sites within seasonal home ranges of individuals. The goal of this multi-scale review is to provide a more complete picture of caribou ecology and to determine possible shifts in limiting factors across scales. Our review produced two important results. First, mountain caribou select old forests and old trees at all spatial scales, signifying their importance for foraging opportunities as well as conditions required to avoid alternate ungulates and their predators. Second, relationships differ across scales. For example, landscapes dominated by roads and edges negatively affect caribou survival, but appear to attract caribou during certain times of the year. This juxtaposition of fine-scale behaviour with broad-scale vulnerability to predation could only be identified through integrated multi-scale analyses of resource selection. Consequently we suggest that effective management strategies for endangered species require an integrative approach across multiple spatial scales to avoid a focus that may be too narrow to maintain viable populations. Abstract in Norwegian / Sammendrag:Skala-avhengig økologi og truet fjellvillrein i Britisk ColumbiaFjellvillreinen i de nedbørsrike fjellområdene i sørøstre Britisk Columbia og nordlige Idaho som er en truet økotype av skogsreinen (Rangifer tarandus caribou), har blitt kraftig redusert både i utbredelse og antall. Mange studier har vist at denne økotypen er avhengig av vinterføden hengelav i gammel barskog hvor det også er få andre klovdyr og dermed få predatorer. Slik skog er også viktige hogstområder, og å forstå økologien til fjellvillreinen i forskjellige skaleringer er derfor nødvendig for å utvikle forvaltningsstrategier som kan berge og ta vare på denne reinen. Artikkelen gir en oversikt over slike arbeider: fra studier av begrensende faktorer på populasjonsnivå til studier av sesongmessige beiteplasser på individnivå. Hensikten er å få frem et mer helhetlig perspektiv på fjellvillreinen og finne hvordan de begrensende faktorene varierer etter skaleringen som er benyttet i studiet. Oversikten vår frembragte to viktige resultater; 1) Uansett skalering så velger dyrene gammel skog og gamle trær. 2) Dyrenes bruk av et område kan variere med benyttet skalering, for eksempel vil landskap utbygd med veier og hogstflater være ufordelaktig for overlevelsen, men synes likevel å kunne tiltrekke fjellvillreinen til visse tider av året. Forholdet mellom atferd ut fra fin-skalering og stor-skalering sårbarhet hva gjelder predasjon, ville kun blitt avdekket ved flere-skaleringsanalyse av hvordan ressursene benyttes. Ut fra dette foreslår vi at forvaltningsstrategier for truete bestander som eksempelvis fjellvillreinen, må baseres på tilnærminger ut fra ulike skaleringer for å hindre at et for snevert perspektiv kan begrense muligheten for vedvarende levedyktighet.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

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)0.0010.000

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 head0.005
GPT teacher head0.166
Teacher spread0.161 · 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 teacher head, not a consensus.

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".

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Citations1
Published2008
Admission routes1
Has abstractyes

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