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Record W2783294498 · doi:10.1111/ddi.12706

At the landscape level, birds respond strongly to habitat amount but weakly to fragmentation

2018· article· en· W2783294498 on OpenAlexafffundabout
Rafael X. De Camargo, Véronique Boucher‐Lalonde, David J. Currie

Bibliographic record

VenueDiversity and Distributions · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaBird Studies CanadaAssociation of Field OrnithologistsMinistry of Natural Resources
KeywordsFragmentation (computing)Species richnessHabitat fragmentationHabitatEcologyHabitat destructionBiodiversityForest fragmentationBiologyGeography

Abstract

fetched live from OpenAlex

Abstract Aim It is usually thought that habitat fragmentation acts negatively on species survival, and consequently, on biodiversity. Recent literature challenges whether habitat fragmentation per se affects species richness, beyond the effect of habitat area. Theoretical studies have suggested that fragmentation may matter most when the amount of available habitat is small or at intermediate levels. However, a recent review suggests that the effect of fragmentation on species richness is usually positive. Here, we dissect the richness–fragmentation relationship. What is the effect size? Does it depend upon the amount of habitat cover? How do individual species respond to fragmentation? Methods Applying a macroecological approach, we empirically related avian richness and the probability of occurrence (pocc) of individual species to fragmentation (number of patches), after controlling for habitat amount in 991 landscapes, each 100‐km2, in southern Ontario, Canada. Results Species richness was strongly related to total habitat amount, but habitat fragmentation had no detectable additional effect. Individual species’ pocc related strongly to habitat amount. For some species, pocc also related secondarily to habitat fragmentation within landscapes. Logistic models revealed that pocc related significantly negatively to fragmentation after controlling for habitat amount for only ~13% of forest‐ and 18% of open‐habitat species bird species. However, pocc related significantly positively to fragmentation for even greater proportions of species, including some red‐listed species. Fragmentation effects were not stronger at low or intermediate levels of habitat amount within landscapes. Conclusion In earlier studies, negative effects of isolation were observed at the patch level in experimental manipulations. However, at the landscape level, avian species richness in southern Ontario apparently responds primarily to habitat amount and negligibly to fragmentation. We argue that the evidence is inconsistent with the hypothesis that reducing habitat fragmentation per se would be an effective conservation strategy for birds at the landscape level.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.151
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.094
GPT teacher head0.229
Teacher spread0.134 · 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

Citations72
Published2018
Admission routes3
Has abstractyes

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