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Record W2473311262 · doi:10.2981/wlb.00186

Influence of habitat type on the decay and disappearance of elk <i>Cervus canadensis</i> pellets in boreal forest of northwestern Canada

2016· article· en· W2473311262 on OpenAlexaffabout
Thomas S. Jung, Piia M. Kukka

Bibliographic record

VenueWildlife Biology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsYukon Department of Environment
Fundersnot available
KeywordsUngulatePelletTaigaHabitatPelletsEnvironmental scienceEcologyBorealAnimal scienceBiology

Abstract

fetched live from OpenAlex

Fecal pellet counts are often used to assess trends in ungulate population size and habitat use. However, various factors may influence the physical decay and disappearance of pellets, where disappearance may be a result of physical decay and other factors (e.g. trampling, scattering and concealment by vegetation). Knowing pellet decay and disappearance rates in different habitats is a prerequisite to acquiring reliable information from pellet counts. We examined elk Cervus canadensis pellet decay and disappearance of individual pellets and pellet groups in six habitats in the boreal forest of northwestern Canada. We monitored 120 pellet groups deposited in May 2008 at 4, 12, 16 and 28 month intervals (i.e. the end of each of three plant growing seasons) to assess differences in physical decay and disappearance. Pellet decay and disappearance varied among habitats. In moist habitats, pellets showed little sign of decay by the end of our study, likely due to a short plant growing season. In drier, open habitat types, pellet decay was more rapid, likely due to exposure to sun and wind. By the end of our study, the percent of pellets remaining varied from a 14–82% among the sampled habitats. Pellets in moist forest habitats had the lowest decay rates but the highest disappearance rates, whereas those in dry, grassland sites had the highest decay, but the lowest disappearance rates. Our study further demonstrates that ungulate pellet decay and disappearance may differ substantially among habitats, which has important implications for the design of ungulate monitoring programs that utilize pellet counts. We conclude by recommending that fecal accumulation rate (FAR) methods are likely more appropriate in our study area than fecal standing crop (FSC) methods for estimating elk density, because FAR methods are less prone to biases associated with differential pellet decay and disappearance among habitats.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.467

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)0.0000.000

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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.

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

Citations20
Published2016
Admission routes2
Has abstractyes

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