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Record W6976624740 · doi:10.6084/m9.figshare.1005173

Europe’s top 10 invasive species: relative importance of climatic, habitat and socio-economic factors

2014· article· en· W6976624740 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2014
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatInvasive speciesCrayfishBayKelp forestIntroduced speciesWetlandMarine habitats

Abstract

fetched live from OpenAlex

Using a representative set of 10 of the worst invasive species in Europe, this study investigates the relative importance of climatic, habitat and socio-economic factors in driving the occurrence of invasive species. According to the regression models performed, these factors can be interpreted as multi-scale filters that determine the occurrence of invasive species, with human degradation potentially affecting the performance of the other two environmental filters. Amongst climate factors, minimum temperature of the coldest month was one of the most important drivers of the occurrence of Europe’s worst freshwater and terrestrial invaders like the red swamp crayfish (<i>Procambarus clarkii</i>), Bermuda buttercup (<i>Oxalis pes-caprae</i>) and Sika deer (<i>Cervus nippon</i>). Water chemistry (alkalinity, pH, nitrate) determines the availability of habitat and resources for species at regional to local levels and was relevant to explain the occurrence of aquatic and semi-aquatic invaders such as the brook trout (<i>Salvalinus fontinallis</i>) and Canada goose (<i>Branta canadensis</i>). Likewise, nitrate and cholorophyll-<i>a</i> concentration were important determinants of marine invaders like the bay barnacle (<i>Balanus improvisus</i>) and green sea fingers (<i>Codium fragile</i>). Most relevant socio-economic predictors included the density of roads, country gross domestic product (GDP), distance to ports and the degree of human influence on ecosystems. These variables were particularly relevant to explain the occurrence of the zebra mussel (<i>Dreissena polymorpha</i>) and coypu (<i>Myocastor coypu</i>), species usually associated to disturbed environments. The Japanese kelp (<i>Undaria pinnatifida</i>) was generally distributed much closer to ports than the other two marine organisms, although insufficient information on human impacts prevented a correct assessment of the three marine species. In conclusion, this study shows how socio-economic development is associated with the presence of the top 10 worst European invasive species at a continental scale, and relates this fact to the provision and transport of propagules and the degradation of natural habitats that favour the establishment of invasive species.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.997

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)0.0040.001

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 head0.035
GPT teacher head0.250
Teacher spread0.215 · 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