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Record W3189265643 · doi:10.1111/csp2.553

Invasive species increase biodiversity and, therefore, services: An argument of equivocations

2021· article· en· W3189265643 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

VenueConservation Science and Practice · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsDalhousie University
FundersGordon and Betty Moore Foundation
KeywordsBiodiversitySpecies richnessEcosystem servicesEcosystemProductivityEcologyProvisioningInvasive speciesEnvironmental resource managementBiologyEnvironmental scienceComputer scienceEconomics

Abstract

fetched live from OpenAlex

Abstract Some critics of invasion biology have argued the invasion of ecosystems by nonindigenous species can create more valuable ecosystems. They consider invaded communities as more valuable because they potentially produce more ecosystem services. To establish that the introduction of nonindigenous species creates more valuable ecosystems, they defend that value is provisioned by ecosystem services. These services are derived from ecosystem productivity, the production and cycling of resources. Ecosystem productivity is a result of biodiversity, which is understood as local species richness. Invasive species increase local species richness and, therefore, increase the conservation value of local ecosystems. These views are disseminating to the public via a series of popular science books. Conservationists must respond to these views, and I outline a method of rejecting such arguments against controlling invasive species. Ecological systems are valuable for more than local productivity and biodiversity is not accurately described by a local species count.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.024
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
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 head0.035
GPT teacher head0.281
Teacher spread0.246 · 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