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Floral free fall in the Swiss lowlands: environmental determinants of local plant extinction in a peri‐urban landscape

2007· article· en· W2037497982 on OpenAlexaff
Ivana Stehlik, John P. Caspersen, Lea R. Wirth, Rolf Holderegger

Bibliographic record

VenueJournal of Ecology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Toronto
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsExtinction debtIUCN Red ListEcologyExtinction (optical mineralogy)HabitatDominance (genetics)BiologyGeographyPlant communityLocal extinctionEutrophicationHabitat destructionEcological successionNutrientPopulation

Abstract

fetched live from OpenAlex

Summary Local floras are being depleted by a host of human activities, including habitat destruction and fragmentation, eutrophication, and the intensification of agriculture. Species with particular ecological demands or life‐history attributes are more prone to extinction than species with a broader niche. We used an old herbarium from the municipality of Küsnacht (Swiss lowlands) as a historical record for comparison with contemporary plant diversity. This comparison revealed that 17% to 28% of all vascular plants that occurred between 1839 and 1915 were extinct by 2003. Species of different habitats and life‐forms had significantly different rates of extinction: wetlands, disturbed sites and meadows lost most species, whereas forests and rocky habitats were least affected; aquatics and annuals were most prone to extinction, geophytes and hemicryptophytes were intermediate, and phanerophytes and chamaephytes were least affected. Species adapted to nutrient‐poor soils suffered highest extinction in all habitats, indicating that eutrophication poses an urgent threat to species diversity. Light and soil moisture requirements also had significant effects on extinction, but the direction of the effect varied by habitat. When species were grouped into IUCN categories of the red list of Switzerland, the rank order of the observed extinction matched the red list assignment. Because many of the remaining species had high estimated extinction probabilities and because extinction is often delayed (extinction debt), a substantial part of the remaining flora of Küsnacht is likely to go extinct in the near future. This will increase the dominance of the common species that already comprise 81% of the local flora. The rates and patterns of extinction in Küsnacht are probably representative of surrounding Swiss lowlands and peri‐urban landscapes in most developed countries. Studies such as ours can serve as a call for action and form a basis for future monitoring of biodiversity.

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)0.001
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 score0.026
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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

Citations61
Published2007
Admission routes1
Has abstractyes

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