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Record W4408192493 · doi:10.1016/j.biocon.2025.111070

Protected area edges host more warm-dwelling bird communities than the rest of the landscape

2025· article· en· W4408192493 on OpenAlexaboutno aff
Leena Hintsanen, Emma‐Liina Marjakangas, Andrea Santangeli, Aleksi Lehikoinen

Bibliographic record

VenueBiological Conservation · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsHost (biology)GeographyRest (music)EcologyBiology

Abstract

fetched live from OpenAlex

Protected areas can mitigate climate-driven changes in species' abundances and community compositions. However, protected areas vary in size and habitat composition as do areas outside them. Our knowledge of how ecological communities are changing in a landscape under climate change and at the interface between protected and unprotected land is scarce. Here, we evaluated if the temperature niche composition of bird communities changed with the distance to the protected area edge, and whether this change was mediated by habitat type and heterogeneity. We used long-term monitoring data on breeding birds from Canada during 1997–2019. We analysed the variation in average temperature niche of bird communities' using the community temperature index (CTI) that allows quantifying the relative dominance of warm- or cold-dwelling species, and the impact of environmental change on communities' thermal signature. We found a lower CTI value indicating dominance of cold-dwelling species in the core of protected areas and far outside them, while edges are characterised by warmer-dwelling communities. Over time, we observed a similar increase in CTI inside and outside protected areas. CTI change over time depended on the habitat type, with fastest shifts in broadleaf forests. Our results suggest that the management of the entire landscape, habitat type and edge distance, may mediate climate change responses of wildlife communities. Minimising the edge effect of protected areas under climate change will be key, especially for preserving cold-adapted wildlife communities at high latitudes.

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 score0.009
Threshold uncertainty score0.322

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 communication0.0000.000
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 head0.043
GPT teacher head0.249
Teacher spread0.206 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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