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Record W3172356715 · doi:10.1111/aje.12893

Effect of high population density of eastern black rhinoceros, a mega‐browser, on the quality of its diet

2021· article· en· W3172356715 on OpenAlexfundno aff
Benson Okita‐Ouma, Richard A. Pettifor, Marcus Clauß, H.H.T. Prins

Bibliographic record

VenueAfrican Journal of Ecology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersWageningen University and ResearchMemorial University of NewfoundlandMohamed bin Zayed Species Conservation FundZoological Society of London
KeywordsRhinocerosBiologyNutrientHerbivorePopulationPopulation densityAnimal scienceOvisForageFecesEcologyAgronomyDemography

Abstract

fetched live from OpenAlex

Abstract High density of herbivore populations can lead to intense foraging competition and depletion of food consequently lowering diet quality and population performance. We tested for the effects of the density of eastern black rhinoceros ( Diceros bicornis michaeli ) in nine in situ populations of 0.01–0.7 individuals per km 2 density range on the quality of their diet while controlling for plant available moisture and plant available nutrients. We used faecal calcium, phosphorus, copper and zinc concentrations as proxy indices for dietary quality from 473 fresh faecal samples obtained from 77 adult animals in situ , after determining a positive faeces‐diet mineral correlation in feeding trials with black rhinoceros in zoos. Some populations surpassed 70%–80% of their estimated maximum stocking densities expected to cause impact on forage. However, we did not find significant correlation between rhino population density and dietary quality, as measured via faecal mineral nutrient content. This suggests that black rhinoceros may have sufficient behavioural plasticity to adjust their diet to cover their nutritional requirements when density increases. Instead, 1‐month lagged plant available moisture, reflecting precipitation over the 4 weeks preceding each sampling effort, significantly explained the mineral concentrations in the faeces. By contrast, plant available nutrients had no effect.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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