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Record W2889141130 · doi:10.1139/cjfas-2018-0171

Beaver activity increases habitat complexity and spatial partitioning by steelhead trout

2018· article· en· W2889141130 on OpenAlexvenueno aff
Gus Wathen, Jacob E. Allgeier, Nicolaas Bouwes, Michael M. Pollock, Daniel E. Schindler, Chris E. Jordan

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceBonneville Power AdministrationNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsBeaverHabitatEcologyFisheryStream restorationRange (aeronautics)MetapopulationChannel (broadcasting)Rainbow troutEnvironmental scienceBiologyFish <Actinopterygii>Biological dispersalPopulationComputer science

Abstract

fetched live from OpenAlex

Freshwater habitat restoration is a major conservation objective, motivating efforts to restore habitat complexity and quality for fishes. Restoration based on the engineering activities of beavers (Castor canadensis) increases fish habitat complexity, but how this affects fish habitat use and movement behaviours is not well known. We used a network of passive integrated transponder antennas to quantify small-scale movement and microhabitat use of 175 individual juvenile steelhead (Oncorhynchus mykiss) in a stream channel with a complex bathymetric profile resulting from a beaver impoundment and in a simplified channel devoid of beaver activity. Our results show that juvenile steelhead exploit microhabitat heterogeneity by employing a range of behaviours that maximizes available habitat via spatial and temporal partitioning among individuals. These results suggest spatial resource partitioning as a potential mechanism for the previously established positive correlations among steelhead density, survival, and production with beaver-based restoration within the study watershed. More broadly, our findings provide insight as to how populations can exploit habitat complexity through spatial partitioning that can be informative for planning restoration and management actions.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.998

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 studies0.0010.004
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 head0.030
GPT teacher head0.217
Teacher spread0.188 · 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".

Quick stats

Citations12
Published2018
Admission routes1
Has abstractyes

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