MétaCan
Menu
Back to cohort
Record W6929870454 · doi:10.5061/dryad.rfj6q579r

Source pool diversity and proximity shape the compositional uniqueness of insular mammal assemblages worldwide

2021· dataset· en· W6929870454 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

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldComputer Science
TopicAdvanced Clustering Algorithms Research
Canadian institutionsMcGill UniversityConcordia UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsEctothermPopulationVariation (astronomy)Range (aeronautics)Natural (archaeology)Lacertidae

Abstract

fetched live from OpenAlex

Islands have been the test bed of several theories in community ecology, biogeography, and evolutionary biology. Progress within these disciplines has given a more comprehensive and mechanistic understanding of the processes governing variation in species richness among islands. However, it remains unclear whether these same processes also explain variation in species and phylogenetic composition among islands. Integrating theory from ecology and biogeography, we infer the roles of dispersal, selection, and stochasticity on the composition of insular assemblages within archipelagos. We further assess the influence of source pool diversity and connectivity on the compositional uniqueness of insular assemblages. Island systems worldwide. We compiled data on species composition of non-volant mammals on ∼200 islands in nine archipelagos distributed worldwide from the literature. We used variation partitioning to quantify the relative influence of the environment (selection) and geographic distance (dispersal) relative to a null model (stochasticity, randomness) on taxonomic and phylogenetic compositional turnover within archipelagos. We then used a linear mixed model to gain further insight into the underlying mechanisms shaping variation in assemblage composition among islands at a global scale. Specifically, we assessed the influence of source pool diversity, isolation from the source pool, and island characteristics on compositional uniqueness. Our results suggest that within-archipelago variation in the composition of insular mammal assemblages is associated with stochastic or unmeasured processes rather than abiotic selection or dispersal limitation. The diversity and proximity of the source pool, as well as some island characteristics, explained variation in phylogenetic, but not taxonomic, compositional uniqueness globally. Within archipelagos, the largely unexplained variation in compositional turnover points to the overwhelming influence of extinction mediated by ecological drift or other stochastic processes, which obscures or overrides the signature of selection and/or dispersal. Globally, isolated islands associated with highly diverse source pools exhibit high phylogenetic uniqueness whereas well-connected islands associated with small source pools show the opposite trend. Phylogenetically unique assemblages also tend to occur on islands with a small elevational span and low annual temperature variation. Taken together, our results suggest that source pool diversity, along with the potential for colonization from those pools, plays an important role in shaping the composition of insular mammal assemblages worldwide.

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 categoriesScience and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.255
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0040.026
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.254
Teacher spread0.222 · 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