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Record W2794263711 · doi:10.1002/ecs2.2105

Homogenization of plant diversity, composition, and structure in North American urban yards

2018· article· en· W2794263711 on OpenAlex

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

VenueEcosphere · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
FundersDivision of Emerging FrontiersDirectorate for Biological SciencesNational Science Foundation
KeywordsHomogenization (climate)YardBiodiversityUrban ecologyEcosystemGeographyEcologyHomogeneousUrban ecosystemBiologyUrban planningUrbanization

Abstract

fetched live from OpenAlex

Abstract Urban ecosystems are widely hypothesized to be more ecologically homogeneous than natural ecosystems. We argue that urban plant communities assemble from a complex mix of horticultural and regional species pools, and evaluate the homogenization hypothesis by comparing cultivated and spontaneously occurring urban vegetation to natural area vegetation across seven major U.S. cities. There was limited support for homogenization of urban diversity , as the cultivated and spontaneous yard flora had greater numbers of species than natural areas, and cultivated phylogenetic diversity was also greater. However, urban yards showed evidence of homogenization of composition and structure . Yards were compositionally more similar across regions than were natural areas, and tree density was less variable in yards than in comparable natural areas. This homogenization of biodiversity likely reflects similar horticultural source pools, homeowner preferences, and management practices across U.S. cities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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