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Record W2065920970 · doi:10.1139/f10-006

The fire pulse: wildfire stimulates flux of aquatic prey to terrestrial habitats driving increases in riparian consumers

2010· article· en· W2065920970 on OpenAlexvenueno aff
Rachel L. Malison, Colden V. Baxter

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersForskningsrådet om Hälsa, Arbetsliv och Välfärd
KeywordsRiparian zonePeriphytonEnvironmental scienceBenthic zoneEcologyCladophoraCanopyHabitatInvertebratePredationCobbleBiomass (ecology)BiologyAlgae

Abstract

fetched live from OpenAlex

We investigated the midterm effects of wildfire (in this case, five years after the fire) of varying severity on periphyton, benthic invertebrates, emerging adult aquatic insects, spiders, and bats by comparing unburned sites with those exposed to low severity (riparian vegetation burned but canopy intact) and high severity (canopy completely removed) wildfire. We observed no difference in periphyton chlorophyll a or ash-free dry mass among different burn categories but did observe significantly greater biomass of benthic invertebrates in both high severity burned and unburned reaches versus low severity burned reaches. Moreover, a significantly greater flux of adult aquatic insect emergence occurred at sites that experienced high severity fire versus low severity burned and unburned sites. The greatest number of spiders and bat echolocation calls were also observed at sites of high severity fire. Our results suggest that fires of different severity may have very different affects on stream-riparian food webs and that high severity wildfire may lead to an extended “fire pulse” that stimulates aquatic productivity and flux of prey to terrestrial habitats, driving local increases in riparian consumers.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.495
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.216
Teacher spread0.206 · 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

Citations100
Published2010
Admission routes1
Has abstractyes

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