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Record W4220735199 · doi:10.4102/koedoe.v64i1.1674

Reflecting on research produced after more than 60 years of exclosures in the Kruger National Park

2022· article· en· W4220735199 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

VenueKoedoe · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsKruger (Canada)
FundersSouth African National Parks
KeywordsExclosureHerbivoreNational parkEcologyEcosystemAridGeographyVegetation (pathology)AgroforestryBiology

Abstract

fetched live from OpenAlex

Herbivores are a main driver of ecosystem patterns and processes in semi-arid savannas, with their effects clearly observed when they are excluded from landscapes. Starting in the 1960s, various herbivore exclosures have been erected in the Kruger National Park (KNP), for research and management purposes. These exclosures vary from very small (1 m2) to relatively large (almost 900 ha), from short-term (single growing season) to long-term (e.g. some of the exclosures were erected more than 60 years ago), and are located on different geologies and across a rainfall gradient. We provide a summary of the history and specifications of various exclosures. This is followed by a systematic overview of mostly peer-reviewed literature resulting from using KNP exclosures as research sites. These 75 articles cover research on soils, vegetation dynamics, herbivore exclusion on other faunal groups and disease. We provide general patterns and mechanisms in a synthesis section, and end with recommendations to increase research outputs and productivity for future exclosure experiments.Conservation Implications: Herbivore exclosures in the KNP have become global research platforms, that have helped in the training of ecologists, veterinarians and field biologists, and have provided valuable insights into savanna dynamics that would otherwise have been hard to gain. In an age of dwindling conservation funding, we make the case for the value added by exclosures and make recommendations for their continued use as learning tools in complex African savannas.

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)0.002
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 score0.012
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.086
GPT teacher head0.373
Teacher spread0.287 · 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