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Record W2266457134 · doi:10.1111/jvs.12387

Factors driving structure of natural and anthropogenic forest edges from temperate to boreal ecosystems

2016· article· en· W2266457134 on OpenAlex
Per‐Anders Esseen, Anna Ringvall, Karen A. Harper, Pernilla Christensen, Johan Svensson

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.

Bibliographic record

VenueJournal of Vegetation Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsDalhousie University
FundersVetenskapsrådetNaturvårdsverketSvenska Forskningsrådet Formas
KeywordsEnvironmental scienceCanopyBiomeEcosystemDisturbance (geology)DeciduousWetlandTemperate climatePhysical geographyBorealEcologyTaigaGeographyBoreal ecosystemAtmospheric sciencesGeologyForestryBiologyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Questions What factors control broad‐scale variation in edge length and three‐dimensional boundary structure for a large region extending across two biomes? What is the difference in structure between natural and anthropogenic edges? Location Temperate and boreal forests across all of Sweden, spanning latitudes 55–69° N. Methods We sampled more than 2000 forest edges using line intersect sampling in a monitoring programme (National Inventory of Landscapes in Sweden). We compared edge length, ecosystem attributes (width of adjacent ecosystem, canopy cover, canopy height, patch contrast in canopy height, forest type) and boundary attributes (profile, abruptness, shape) of natural edges (lakeshore, wetland) with anthropogenic edges (clear‐cut, agricultural, linear disturbance) in five regions. Results Anthropogenic edges were nearly twice as abundant as natural edges. Length of anthropogenic edges was largest in southern regions, while the abundance of natural edges increased towards the north. Edge types displayed unique spectrums of boundary structures, but abrupt edges dominated, constituting 72% of edge length. Anthropogenic edges were more abrupt than natural edges; wetland edges had the most gradual and sinuous boundaries. Canopy cover, canopy height, patch contrast and forest type depended on region, whereas overall boundary abruptness and shape showed no regional pattern. Patch contrast was related to temperature sum (degree days ≥ 5 °C), suggesting that regional variability can be predicted from climate‐controlled forest productivity. Boundary abruptness was coupled with the underlying environmental gradient, land use and forest type, with higher variability in deciduous than in conifer forest. Conclusions Edge origin, land use, climate and tree species are main drivers of broad‐scale variability in forest edge structure. Our findings have important implications for developing ecological theory that can explain and predict how different factors affect forest edge structure, and help to understand how land use and climate change affect biodiversity at forest edges.

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)0.000
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 score0.239
Threshold uncertainty score0.200

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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