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Effects of sward structure on herbivore foraging behaviour in a South African savanna: An investigation of the forage maturation hypothesis

2006· article· en· W2161951659 on OpenAlexaff
Michael Drescher, I.M.A. Heitkönig, Paul J. Van den Brink, H.H.T. Prins

Bibliographic record

VenueAustral Ecology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsForageForagingHerbivoreBiologyEcologyAgronomyOptimal foraging theory

Abstract

fetched live from OpenAlex

Abstract: The grass layer of savannas is characterized by strong temporal and spatial heterogeneity in the quantity and quality of forage. Besides this, there is strong variation in other aspects of sward structure, here defined as sward chemistry, morphology, architecture and species composition. The forage maturation hypothesis (FMH) is based on the temporal dynamics of forage quantity and quality of grasslands. Recently this hypothesis has been used to explain the foraging behaviour of large herbivores as an optimal solution for balancing forage ingestion and forage digestion, leading to a maximization of daily rates of forage intake in patches of intermediate forage quantity. However, so far studies using this hypothesis have been constrained to mono‐specific forage resources or have ignored inter‐patch variation in sward structure. We studied the foraging behaviour of cattle in a South African savanna. We explicitly addressed forage quantity and quality, and the structure of seven sward types in order to investigate (i) their effects on foraging behaviour; and (ii) the assumptions and predictions of the FMH for foraging behaviour in grasslands with pronounced variation in sward structure. The results indicated that the assumptions of the FMH were met and that forage quantity affected forage intake the most, with sward structure having little or no effect. The predicted maximum rate of daily forage intake agreed with the results of previous studies. However, the forage quantity at which this maximum intake rate was found, was larger than expected based on the results of some studies. It is likely that this discrepancy resulted from the use of artificial leaf‐only grass swards in these studies. The results suggest that the FMH can be used to explain the foraging behaviour of herbivores over a wide range of sward structures.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.196
Teacher spread0.189 · 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

Citations45
Published2006
Admission routes1
Has abstractyes

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