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Record W4409765095 · doi:10.1080/11956860.2025.2495427

Forest structure but not tree diversity differs among urban woodlands with differing conservation status

2025· article· en· W4409765095 on OpenAlexafffundvenueabout
Erica Padvaiskas, Isabella C. Richmond, Carly D. Ziter

Bibliographic record

VenueEcoscience · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWoodlandGeographyEcologyDiversity (politics)BiodiversityConservation statusTree (set theory)Species diversityAgroforestryBiologyHabitatMathematics

Abstract

fetched live from OpenAlex

While biodiversity conservation in urban areas is a topic of great interest, few studies have focused on the role that urban conservation areas have for preserving biodiversity. Urban woodlands, which are patches of forest habitat confined within the city’s boundaries, offer a promising approach to evaluate the importance of conservation areas within cities. Here, we examined the relationship between conservation status, forest structure and composition across 11 urban woodlands in Montréal, Canada. We used field surveys to assess biodiversity, canopy cover, and structural complexity for urban woodlands with a conservation status and those without. We found that Montréal’s urban woodlands fostered similar levels of biodiversity regardless of conservation status. Similarly, all urban woodlands supported high proportions of native tree species despite differences in conservation status and associated management. Our results suggest that both conservation areas and non-status woodlands play an important role in safeguarding urban biodiversity. Woodlands with a conservation status, however, had higher canopy cover and vegetative complexity, but also contained higher average proportions of invasive trees, particularly Rhamnus cathartica (Common Buckthorn). While the high complexity in vegetation layers observed may provide habitat to native wildlife, these benefits may be limited by the high proportion of invasive trees.

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 score0.068
Threshold uncertainty score0.999

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 studies0.0010.000
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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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

Citations0
Published2025
Admission routes4
Has abstractyes

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