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Record W2837004038 · doi:10.1101/364182

Predation risk and resource abundance mediate foraging behaviour and intraspecific resource partitioning among consumers in dominance hierarchies

2018· preprint· en· W2837004038 on OpenAlexaff
Sean M. Naman, Rui Ueda, Takuya Sato

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
FundersJapan Society for the Promotion of Science
KeywordsForagingPredationDominance (genetics)BiologyEcologyIntraspecific competitionPopulationPredatorAbundance (ecology)Trade-offOptimal foraging theoryDemography

Abstract

fetched live from OpenAlex

Abstract Dominance hierarchies and unequal resource partitioning among individuals are key mechanisms of population regulation. The strength of dominance hierarchies can be influenced by size dependent trade-offs between foraging and predator avoidance whereby competitively inferior subdominants can access a larger proportion of limiting resources by accepting higher predation risk. Foraging-predation risk trade-offs also depend on resource abundance. Yet, few studies have manipulated predation risk and resource abundance simultaneously; consequently, their joint effect on resource partitioning within dominance hierarchies are not well understood. We addressed this gap by measuring behavioural responses of masu salmon to experimental manipulations of predation risk and resource abundance in a natural temperate forest stream. Responses to predation risk depended on body size such that larger dominants exhibited more risk-averse behaviour (e.g., lower foraging and appearance rates) relative to smaller subdominants after exposure to a simulated predator. The magnitude of this effect was lower when resources were elevated, indicating that dominant fish accepted a higher predation risk to forage on abundant resources. However, the influence of resource abundance did not extend to the population level, where predation risk altered the distribution of foraging attempts (a proxy for energy intake) from being skewed towards large individuals to being skewed towards small individuals after predator exposure. Our results imply that size dependent foraging-predation risk trade-offs can mediate the strength of dominance hierarchies by allowing competitively inferior subdominants to access resources that would otherwise be monopolized. Author Contributions: SN, TS, and RU designed the study and performed the fieldwork; SN analyzed the data and wrote the manuscript with input from all authors.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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