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Record W3185374053 · doi:10.1111/ddi.13381

Invasion disharmony in the global biogeography of native and non‐native beetle species

2021· article· en· W3185374053 on OpenAlexaff
Andrew M. Liebhold, Rebecca M. Turner, Rachael E. Blake, Cléo Bertelsmeier, Eckehard G. Brockerhoff, Helen F. Nahrung, Deepa S. Pureswaran, Alain Roques, Hanno Seebens, Takehiko Yamanaka

Bibliographic record

VenueDiversity and Distributions · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCanadian Forest Service
FundersU.S. Forest ServiceMinistry of Business, Innovation and EmploymentBundesministerium für Bildung und ForschungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungBiodiversa+Fakulta Lesnická a Drevarská, Česká Zemědělská Univerzita v PrazeNew Zealand’s Biological HeritageNational Socio-Environmental Synthesis CenterNational Science FoundationInternational Programs, US Forest ServiceU.S. Department of Agriculture
KeywordsIntroduced speciesEcologyBiogeographyBiologyInvasive speciesNestednessGeographyTaxonBiodiversity

Abstract

fetched live from OpenAlex

Abstract Aim The concept of “island disharmony” has been widely applied to describe the systematic over‐ and under‐representation of taxa on islands compared to mainland regions. Here, we explore an extension of that concept to biological invasions. We compare biogeographical patterns in native and non‐native beetle (Coleoptera) assemblages from around the world to test whether beetle invasions represent a random sample of species or whether some families are more prone to invade than others. Location Global. Methods Numbers of non‐native beetle species established in ten regions worldwide were compared with the land area of each region. The distribution of species among families was compared with the distribution among families for all species native to the same region and with the distribution among families for the global pool of all known beetle species. Ordination analysis was used to characterize differences among native and non‐native assemblages based upon the distribution of species among families. Results We report a total of 1,967 non‐native beetle species across all ten regions, and a classic log–log relationship between numbers of species per region and land area though relationships are generally stronger for native assemblages. Some families (e.g., Dermestidae and Bostrichidae) are over‐represented and others (e.g., Carabidae, Scarabaeidae and Buprestidae) are under‐represented in non‐native assemblages. The distribution of species among families is generally similar among native assemblages with greatest similarities among nearby regions. In contrast, non‐native species assemblages are more similar to each other than to native species assemblages. Main conclusions Certain families are over‐represented, and others are under‐represented in non‐native beetle assemblages compared to native assemblages, indicating “invasion disharmony” in the global representation of beetle families. Similarities in composition among non‐native assemblages may reflect unobserved associations with invasion pathways and life‐history traits that shape invasion success of different insect groups.

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)0.000
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 score0.006
Threshold uncertainty score0.472

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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

Citations30
Published2021
Admission routes1
Has abstractyes

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