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Neophyte species richness at the landscape scale under urban sprawl and climate warming

2009· article· en· W2004560178 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

VenueDiversity and Distributions · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsConcordia University
Fundersnot available
KeywordsSpecies richnessUrban sprawlGeographyEcologyClimate changeBiodiversityVascular plantSpecies distributionLandscape ecologyEnvironmental scienceLand useBiologyHabitat

Abstract

fetched live from OpenAlex

Abstract Aim Land use and climate are two major components of global environmental change but our understanding of their simultaneous and interactive effects upon biodiversity is still limited. Here, we investigated the relationship between the species richness of neophytes, i.e. non‐native vascular plants introduced after 1500 AD, and environmental covariates to draw implications for future dynamics under land‐use and climate change. Location Switzerland, Central Europe. Methods The distribution of vascular plants was derived from a systematic national grid of 1 km 2 quadrates ( n = 456; Swiss Biodiversity Monitoring programme) including 1761 species, 122 of which were neophytes. Generalized linear models (GLMs) were used to correlate neophyte species richness with environmental covariates. The impact of land‐use and climate change was thereafter evaluated by projections for the years 2020 and 2050 using scenarios of moderate and strong changes for climate warming (IPCC) and urban sprawl (NRP 54). Results Mean annual temperature and the amount of urban areas explained neophyte species richness best, with a high predictive power of the corresponding model (cross‐validated D 2 = 0.816). Climate warming had a stronger impact on the potential increase in the mean neophyte species richness (up to 191% increase by 2050) than ongoing urban sprawl (up to 10% increase) independently from variable interactions and model extrapolations to non‐analogue environments. Main conclusions In contrast to other vascular plants, the prediction of neophyte species richness at the landscape scale in Switzerland requires few variables only, and regions of highest species richness of the two groups do not coincide. The neophyte species richness is basically driven by climatic (temperature) conditions, and urban areas additionally modulate small‐scale differences upon this coarse‐scale pattern. According to the projections climate warming will contribute to the future increase in neophyte species richness much more than ongoing urbanization, but the gain in new neophyte species will be highest in urban regions.

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 categoriesScience and technology studies, Insufficient 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 score0.019
Threshold uncertainty score0.998

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 studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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