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Record W4239824732 · doi:10.1093/jmammal/gyab132

Effects of rainfall, forage biomass, and population density, on survival and growth of juvenile kangaroos

2021· article· en· W4239824732 on OpenAlexafffund
Charles-Alexandre Plaisir, Wendy J. King, David M. Forsyth, Marco Festa‐Bianchet

Bibliographic record

VenueJournal of Mammalogy · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaHolsworth Wildlife Research EndowmentNational Geographic Society
KeywordsJuvenileForageBiomass (ecology)BiologyDensity dependencePopulationPopulation densityHerbivoreEcologyPopulation growthDemography

Abstract

fetched live from OpenAlex

Abstract A central goal of ecology is to understand how environmental variation affects populations. Long-term studies of marked individuals can quantify the effects of environmental variation on key life-history traits. We monitored the survival and growth of 336 individually marked juvenile eastern grey kangaroos (Macropus giganteus), a large herbivore living in a seasonal but unpredictable environment. During our 12-year study, the population experienced substantial variation in rainfall, forage biomass, and density. We used structural equation modeling to determine how variation in temperature and rainfall affected juvenile survival and growth through its effect on forage biomass and population density. Independently of population density, forage biomass had strong positive effects on survival from 10 to 21 months. At low population density, forage biomass also had a positive effect on skeletal growth to 26 months. Increasing maternal body condition improved rearing success for daughters but not for sons. High population density reduced skeletal growth to 26 months for both sexes. Rainfall had an increasingly positive effect on forage biomass at high temperatures, indicating a seasonal effect on food availability. Our study reveals interacting effects of environmental variation on juvenile survival and growth for a large mammal with a conservative reproductive strategy that experiences substantial stochasticity in food availability.

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 score0.011
Threshold uncertainty score0.184

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)0.0000.000

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 head0.006
GPT teacher head0.207
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 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

Citations13
Published2021
Admission routes2
Has abstractyes

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