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The equilibrium population size of a partially migratory population and its response to environmental change

2011· article· en· W2067576397 on OpenAlexaff
Cortland K. Griswold, Caz M. Taylor, D. Ryan Norris

Bibliographic record

VenueOikos · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCyanistesAbundance (ecology)PopulationEnvironmental changePopulation sizePopulation cyclePopulation densityEcologyGeographyDensity dependencePopulation growthPopulation declineBiologyDemographyClimate change

Abstract

fetched live from OpenAlex

A partially migratory population consists of non‐migrant and migrant individuals that share a common site during one period of the annual cycle. In this paper, we derive the expected equilibrium population sizes of migrants and non‐migrants and show how the abundance of one type is dependent on the other because their dynamics are coupled through density‐dependent effects. We present an approach for developing hypotheses about how changes in the environment will influence partially migratory populations and for formulating testable predictions about the effects of future changes on the proportions of migrants and non‐migrants. We apply this approach to a hypothesis put forward by Berthold that improved environmental conditions at the shared site will generally increase the number of non‐migrants and decrease the number of migrants, and to a study by Nilsson et al. which observed an increase in the number of migrants in a partially migratory blue tit Cyanistes caeruleus population in Sweden, but an overall maintenance of the proportion of migrants.

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)0.006
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.243
Teacher spread0.201 · 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

Citations30
Published2011
Admission routes1
Has abstractyes

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