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Record W2121514248 · doi:10.1111/1365-2745.12398

Edge influence on vegetation at natural and anthropogenic edges of boreal forests in <scp>C</scp>anada and <scp>F</scp>ennoscandia

2015· article· en· W2121514248 on OpenAlex
Karen A. Harper, S. Ellen Macdonald, Michael S. Mayerhofer, Shekhar R. Biswas, Per‐Anders Esseen, Kristoffer Hylander, Katherine Stewart, Azim U. Mallik, Pierre Drapeau, Bengt‐Gunnar Jonsson, Daniel Lesieur, Jari Kouki, Yves Bergeron

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Ecology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueYukon UniversityLakehead UniversityUniversity of AlbertaMount Saint Vincent UniversityNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à MontréalDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBorealVegetation (pathology)Abundance (ecology)BryophyteUnderstoryTaigaEcologyBasal areaTemperate rainforestEnvironmental scienceCanopyDisturbance (geology)ForestryTemperate climateGeographyAgroforestryEcosystemBiology

Abstract

fetched live from OpenAlex

Summary Although anthropogenic edges are an important consequence of timber harvesting, edges due to natural disturbances or landscape heterogeneity are also common. Forest edges have been well studied in temperate and tropical forests, but less so in less productive, disturbance‐adapted boreal forests. We synthesized data on forest vegetation at edges of boreal forests and compared edge influence among edge types (fire, cut, lake/wetland; old vs. young), forest types (broadleaf vs. coniferous) and geographic regions. Our objectives were to quantify vegetation responses at edges of all types and to compare the strength and extent of edge influence among different types of edges and forests. Research was conducted using the same general sampling design in Alberta, Ontario and Quebec in Canada, and in Sweden and Finland. We conducted a meta‐analysis for a variety of response variables including forest structure, deadwood abundance, regeneration, understorey abundance and diversity, and non‐vascular plant cover. We also determined the magnitude and distance of edge influence (DEI) using randomization tests. Some edge responses (lower tree basal area, tree canopy and bryophyte cover; more logs; higher regeneration) were significant overall across studies. Edge influence on ground vegetation in boreal forests was generally weak, not very extensive (DEI usually &lt; 20 m) and decreased with time. We found more extensive edge influence at natural edges, at younger edges and in broadleaf forests. The comparison among regions revealed weaker edge influence in Fennoscandian forests. Synthesis . Edges created by forest harvesting do not appear to have as strong, extensive or persistent influence on vegetation in boreal as in tropical or temperate forested ecosystems. We attribute this apparent resistance to shorter canopy heights, inherent heterogeneity in boreal forests and their adaptation to frequent natural disturbance. Nevertheless, notable differences between forest structure responses to natural (fire) and anthropogenic (cut) edges raise concerns about biodiversity implications of extensive creation of anthropogenic edges. By highlighting universal responses to edge influence in boreal forests that are significant irrespective of edge or forest type, and those which vary by edge type, we provide a context for the conservation of boreal forests.

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.

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)0.001
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 score0.017
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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