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Edge effects of wildfire and riparian buffers along boreal forest streams

2011· article· en· W1490199946 on OpenAlexafffundabout
Nicholas T. Braithwaite, Azim U. Mallik

Bibliographic record

VenueJournal of Applied Ecology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsLakehead University
FundersMinistry of Natural Resources
KeywordsRiparian bufferEnvironmental scienceClearcuttingUnderstoryRiparian zoneCanopySTREAMSBorealEcologyBuffer zoneHabitatBiology

Abstract

fetched live from OpenAlex

Summary 1. Clearcutting and wildfire are the two major edge‐creating disturbances in boreal forests. While clearcutting retains at least a 30 m buffer, wildfires burn close to streams killing most of the trees and potentially creating a different edge structure. Different edge structures are likely to support different plant assemblages. The riparian buffer and fire edge structures and their effects on plant assemblages are unknown, but they have implications for forest management that aims to harvest trees and conserve biodiversity by emulating natural disturbance. 2. We hypothesized that environmental filters created by post‐fire residual structures at the fire edge will support a different plant assemblage than the buffer edge. We further hypothesized that the fire edge with a weaker environmental filter because of post‐fire residual structures and proximity to streams will result in lower depth of edge effects (DEEs) and magnitude of edge effects (MEEs) than buffer edges. 3. We determined the structure of canopy trees, understorey cover and the near‐ground microclimate by sampling 576 (5 × 10 m) and 1820 (1 × 1 m) quadrats along 96 transects beside 24 streams near Thunder Bay, Canada. We determined DEEs and MEEs by comparing edge variables with reference forests. We used repeated measures/factorial anova s with Tukey’s post hoc tests to determine DEEs and manova for MEEs. 4. The average microclimatic DEEs extended 8 m into the buffer but only 2·5 m from the fire edge. Similarly, the DEEs for plant life‐forms extended 20 m from the buffer edge and 5 m from the fire edge. At the fire edge, the structural MEEs were significantly higher, but the microclimatic MEEs were lower than the buffer edge. We found no significant difference in the overall life‐form MEEs, but shrubs, shade‐tolerant herbs and grasses were increased at the buffer edge and decreased at the fire edge. 5. Synthesis and applications . We discovered that the ecological structure at buffer and fire edges in boreal forests creates different environmental filters supporting different plant assemblages. Lower structural and microclimatic DEEs and MEEs at the fire edge result from (i) edge location, (ii) intact shrub layer and (iii) disturbance‐resilient riparian vegetation. We suggest that replacing the conventional sharp edges of the riparian clear‐cut buffer with ‘feathered’ edges by selective harvesting of trees will create wider edges mimicking wildfire legacy and will help to emulate natural disturbance for conserving biodiversity.

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 score0.036
Threshold uncertainty score0.483

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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

Citations50
Published2011
Admission routes3
Has abstractyes

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