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Record W2103538233 · doi:10.1071/wr01074

Beyond population regulation and limitation

2002· article· en· W2103538233 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

VenueWildlife Research · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPopulationPopulation growthPopulation sizeDensity dependencePopulation densityEcologyEmpirical researchPositive economicsEconomicsEpistemologySociologyBiologyDemography

Abstract

fetched live from OpenAlex

The study of population dynamics addresses three questions that are not always separated in discussions with empirical data. Two questions address population regulation. What stabilises population density is the first question, and, in spite of much theory, little progress has been made in answering this question empirically. The assumption of an equilibrium density is impossible to test and direct experimental tests to answer this question are rare. What prevents population growth is a second question, and is the classic question of population regulation. To answer this question requires an increasing population, and, with adequate experimental manipulations, the density dependent factors preventing increase can be identified. Surprisingly, answering this question has provided little assistance in solving practical problems in population dynamics, possibly because most populations are rarely in the state of growth and show a limited range of densities. What limits population density in good and poor habitats is a third question, which addresses population limitation rather than regulation, and has been the most useful question for empirical ecologists to ask. Population limitation admits of little theory and no elegant models, and highlights the gap between theory and practice in much of ecology. Defining the question clearly and adopting an experimental approach with clear alternative hypotheses will be essential to avoiding the controversies of the past while building useful generalisations for the practical problems of population management.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.094
GPT teacher head0.343
Teacher spread0.249 · 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