MétaCan
Menu
Back to cohort
Record W2804891151 · doi:10.1080/17513758.2018.1469791

Dispersal altering local states has a limited effect on persistence of a metapopulation

2018· article· en· W2804891151 on OpenAlexafffund
Jingjing Xu, Geoff Wild

Bibliographic record

VenueJournal of Biological Dynamics · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMetapopulationBiological dispersalPersistence (discontinuity)Extinction (optical mineralogy)BiologyEcologyLocal extinctionRange (aeronautics)Conservation biologyPopulationDemography

Abstract

fetched live from OpenAlex

Metapopulations are collections of local populations connected by dispersal. Metapopulation models often assume would-be colonists affect the states of local populations they disperse from and those they disperse to. Here, we build a new framework to include that effect and to assess the impact of dispersal. Our model predicts that a metapopulation will, in general, be found either in the state of global extinction or in the state of persistence. Our key finding is that dispersal, and the state changes associated with dispersal, have significant qualitative and quantitative effects on long-term dynamics only in a narrow range of parameter space. We conclude that life history features other than dispersal (e.g. mortality rate) have a greater influence over metapopulation persistence. We discuss the implications of our results for conservation biology, the future application of our model to the study of cooperative breeding, as well as our model's limitations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.270
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Biological DynamicsSame topicAnimal Ecology and Behavior StudiesFrench-language works237,207