MétaCan
Menu
Back to cohort
Record W4307711628 · doi:10.1186/s12983-022-00470-z

Realized niche shift of an invasive widow spider: drivers and impacts of human activities

2022· article· en· W4307711628 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Zoology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsEcological nicheNicheSpiderEcologyBiologyInvasive speciesEnvironmental niche modellingRange (aeronautics)HabitatBiodiversityIntroduced speciesSpecies distributionNiche segregationEcological release

Abstract

fetched live from OpenAlex

BACKGROUND: Predicting invasiveness requires an understanding of the propensity of a given species to thrive in areas with novel ecological challenges. Evaluation of realized niche shift of an invasive species in its invasive range, detecting the main drivers of the realized niche shift, and predicting the potential distribution of the species can provide important information for the management of populations of invasive species and the conservation of biodiversity. The Australian redback spider, Latrodectus hasselti, is a widow spider that is native to Australia and established in Japan, New Zealand, and Southeast Asia. We used ecological niche models and ordinal comparisons in an integrative method to compare the realized niches of native and invasive populations of this spider species. We also assessed the impact of several climatic predictor variables and human activity on this niche shift. We hypothesized that human impact is important for successful establishment of this anthropophilic species, and that climatic predictor variables may determine suitable habitat and thus predict invasive ranges. RESULTS: Our models showed that L. hasselti distributions are positively influenced by human impact in both of the native and invasive ranges. Maximum temperature was the most important climatic variable in predictions of the distribution of native populations, while precipitation seasonality was the most important in predictions of invasive populations. The realized niche of L. hasselti in its invasive range differed from that in its native range, indicating possible realized niche shift. CONCLUSIONS: We infer that a preference for human-disturbed environments may underlie invasion and establishment in this spider species, as anthropogenic habitat modifications could provide shelters from unsuitable climatic conditions and extreme climatic stresses to the spiders. Because Australia and the countries in which the species is invasive have differing climates, differences in the availability of certain climatic conditions could have played a role in the realized niche shift of L. hasselti.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.993

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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