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Record W3083149720 · doi:10.3389/fevo.2020.00280

What Will the Future Bring for Biological Invasions on Islands? An Expert-Based Assessment

2020· article· en· W3083149720 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

VenueFrontiers in Ecology and Evolution · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsMcGill University
FundersAgencia Estatal de InvestigaciónAustrian Science FundBundesministerium für Bildung und Forschung
KeywordsBiodiversityInvasive speciesSpecies richnessGeographyIntroduced speciesAlien speciesEcologyEnvironmental resource managementClimate changeEcosystemEcosystem servicesAlienEnvironmental planningBiologyEnvironmental sciencePolitical sciencePolitics

Abstract

fetched live from OpenAlex

Biological invasions are a major threat to global biodiversity with particularly strong implications for island biodiversity. Much research has been dedicated towards understanding historic and current changes in alien species distribution and impacts on islands and potential changes under future climate change. However, projections of how alien species richness and impacts on islands might develop in the future are still lacking. In the absence of reliable projections, expert-based assessments are a valuable tool to investigate the importance of different drivers and pathways and the distributions of potential impacts of future biological invasions. These insights can guide subsequent quantification efforts and inform invasive species management and policy. In this study, we performed a survey among 126 experts in invasion science ranging from scientists to managers and decision makers with a focus on island systems until the mid-21st century. The survey revealed that out of 15 drivers, six were considered important by almost all respondents (>90%). Of these, trade & transport was identified as most important at the introduction stage (99.2%) and land use/cover change as most important at the establishment (96.8%) and spread (95.2%) stage. Additionally, the experts considered that alien species were more likely to be introduced (93.7%) and spread (78.6%) as stowaways than through any other pathway. In general, respondents agreed that the impacts of alien species will increase on all types of islands, particularly on oceanic islands, followed by atolls and continental islands. Within islands, terrestrial ecosystems were assumed to be impacted more severely than marine ecosystems. Finally, the survey hints towards the potential for effective communication, scientific research and increased pro-active management of alien species on islands to reduce their future consequences. Given the major threat represented by invasive alien species on islands, these results provide crucial insights relevant for global and regional conservation efforts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.286

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)0.0000.000

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 head0.020
GPT teacher head0.249
Teacher spread0.228 · 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