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HABITAT LOSS AND FRAGMENTATION IN DYNAMIC LANDSCAPES: AVIAN PERSPECTIVES FROM THE BOREAL FOREST<sup>*</sup>

2002· article· en· W2131550934 on OpenAlexaffabout
Fiona K. A. Schmiegelow, Mikko Mönkkönen

Bibliographic record

VenueEcological Applications · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTaigaFragmentation (computing)EcologyHabitatHabitat fragmentationForest fragmentationHabitat destructionBorealGeographyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Although habitat loss and fragmentation are widely regarded as major factors contributing to the decline of many populations, the relative importance of each phenomenon is seldom evaluated. Some researchers have questioned the generality of responses to habitat fragmentation, given variation in life history characteristics, the natural dynamics of systems, and land use patterns. Furthermore, a fundamental mismatch may exist between ecological theory, with its emphasis on the spatial configuration of habitats, and empirical observations of population response. Nevertheless, the paucity of quantitative land management guidelines often leads to inappropriate generalizations of conservation paradigms to regional issues. We reviewed the empirical evidence for true fragmentation effects in boreal bird communities in Fennoscandia and Canada, and concluded that most responses may be attributed to pure habitat loss in landscapes where forest harvesting is the dominant land use practice. In these dynamic landscapes, total forest cover may not change, and predicting patterns of species decline requires identification of the habitats and species of concern. We constructed simple empirical models of benchmark communities in boreal forests of Finland and Canada based on species composition, species abundance distribution, and habitat requirements, in order to identify features of bird species sensitive to the loss of older forests. These models require a solid understanding of the underlying structure of the community of interest, and predict species loss based on a random-sample hypothesis. Our results were consistent with observed patterns of bird population decline and species loss in these regions. This approach provides null models for comparison with habitat remnants in order to test for fragmentation effects, and a basis for more detailed exploration of population dynamics and persistence in these systems. The results of our review and analyses indicated that system- and species-specific considerations are important when assessing the potential outcome of habitat loss and fragmentation on regional biota. Indiscriminate application of conservation paradigms may lead to misguided research efforts and poor management guidelines.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.069
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.225
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations148
Published2002
Admission routes2
Has abstractyes

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