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Record W2493043508 · doi:10.1111/gcb.13456

Barren‐ground caribou (<i>Rangifer tarandus groenlandicus</i>) behaviour after recent fire events; integrating caribou telemetry data with Landsat fire detection techniques

2016· article· en· W2493043508 on OpenAlexafffundabout
Gregory J. M. Rickbeil, Txomin Hermosilla, Nicholas C. Coops, Joanne C. White, Michael A. Wulder

Bibliographic record

VenueGlobal Change Biology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of British Columbia
FundersCanadian Space AgencyNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaNational Science CouncilCanadian Forest ServiceNational Cancer Coalition
KeywordsBorealEnvironmental scienceFire regimeTaigaPhysical geographyEcologyGeographyForestryEcosystemBiology

Abstract

fetched live from OpenAlex

Abstract Fire regimes are changing throughout the North American boreal forest in complex ways. Fire is also a major factor governing access to high‐quality forage such as terricholous lichens for barren‐ground caribou (Rangifer tarandus groenlandicus). Additionally, fire alters forest structure which can affect barren‐ground caribou's ability to navigate in a landscape. Here, we characterize how the size and severity of fires are changing across five barren‐ground caribou herd ranges in the Northwest Territories and Nunavut, Canada. Additionally, we demonstrate how time since fire, fire severity, and season result in complex changes in caribou behavioural metrics estimated using telemetry data. Fire disturbances were identified using novel gap‐free Landsat surface reflectance composites from 1985 to 2011 across all herd ranges. Burn severity was estimated using the differenced normalized burn ratio. Annual area burned and burn severity were assessed through time for each herd and related to two behavioural metrics: velocity and relative turning angle. Neither annual area burned nor burn severity displayed any temporal trend within the study period. However, certain herds, such as the Ahiak/Beverly, have more exposure to fire than other herds (i.e. Cape Bathurst had a maximum forested area burned of less than 4 km2). Time since fire and burn severity both significantly affected velocity and relative turning angles. During fall, winter, and spring, fire virtually eliminated foraging‐focused behaviour for all 26 years of analysis while more severe fires resulted in a marked increase in movement‐focused behaviour compared to unburnt patches. Between seasons, caribou used burned areas as early as 1‐year postfire, demonstrating complex, nonlinear reactions to time since fire, fire severity, and season. In all cases, increases in movement‐focused behaviour were detected postfire. We conclude that changes in caribou behaviour immediately postfire are primarily driven by changes in forest structure rather than changes in terricholous lichen availability.

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 score0.339
Threshold uncertainty score0.674

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 studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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

Citations33
Published2016
Admission routes3
Has abstractyes

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