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Record W4402550905 · doi:10.1071/rj24021

Managing grazing to increase ground cover in rangelands: using remote sensing to detect change

2024· article· en· W4402550905 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

VenueThe Rangeland Journal · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsCarbon Engineering (Canada)
FundersMeat and Livestock AustraliaUniversity of Warwick
KeywordsRangelandGrazingRemote sensingCover (algebra)Environmental scienceChange detectionGeographyAgroforestryEcologyEngineeringBiology

Abstract

fetched live from OpenAlex

Practices that improve the quantity, composition, and persistence of ground cover can contribute to a range of ecosystem services that support agricultural production, regulate climate, reduce erosion and support nutrient cycling. In rangeland grazing systems, incorporating periods of rest and matching stocking rates to feed availability is commonly used with the goal of improving land condition and productivity at a property scale. Understanding and quantifying differences in ground cover associated with changes to grazing management can provide livestock producers with greater confidence in the outcomes associated with their management. It can also demonstrate their nature positive activities which may be valued in emerging markets. This study sought to quantify any changes in ground cover resulting from changed grazing management (strategically managing the timing, intensity and duration of grazing events to maintain or improve land condition) across seven mixed grazing (cattle, sheep and/or goats) study sites in the semi-arid rangelands of western New South Wales, Australia. Time-series estimates of ground cover derived from Landsat imagery for each study site were compared with biophysically similar regional benchmark areas as controls. Overall, ground cover was found to have increased significantly (2–7%) following change in grazing management at four of the seven study sites, relative to control benchmark areas. It was apparent different land units varied in their response to the management change, and that the preceding 12 months rainfall (such as wet, intermediate or dry rainfall years) did not have a consistently significant effect on the relative response. Results of this study highlight that improvements in ground cover and land condition may be achieved through changes to grazing management, but also that there are complexities in both achieving and measuring any change. This study demonstrates the practical application of remotely sensed cover data and dynamic regional comparison techniques to document environmental outcomes at the property scale from grazing management in low input, extensive rangeland grazing systems.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.027
GPT teacher head0.263
Teacher spread0.236 · 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