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Tytuł pozycji:

Wildlife-friendly farming recouples grazing regimes to stimulate recovery in semi-arid rangelands.

Tytuł:
Wildlife-friendly farming recouples grazing regimes to stimulate recovery in semi-arid rangelands.
Autorzy:
Hasselerharm CD; Centre for Compassionate Conservation, School of Life Sciences, University of Technology Sydney, Ultimo 2007, NSW, Australia. Electronic address: .
Yanco E; Centre for Compassionate Conservation, School of Life Sciences, University of Technology Sydney, Ultimo 2007, NSW, Australia. Electronic address: .
McManus JS; Research Department, Landmark Foundation, Riversdale, South Africa; Department of Biodiversity and Conservation Biology, University of the Western Cape, Robert Sobukwe Road, Cape Town 7535, South Africa. Electronic address: .
Smuts BH; Research Department, Landmark Foundation, Riversdale, South Africa; Department of Biodiversity and Conservation Biology, University of the Western Cape, Robert Sobukwe Road, Cape Town 7535, South Africa. Electronic address: .
Ramp D; Centre for Compassionate Conservation, School of Life Sciences, University of Technology Sydney, Ultimo 2007, NSW, Australia. Electronic address: .
Źródło:
The Science of the total environment [Sci Total Environ] 2021 Sep 20; Vol. 788, pp. 147602. Date of Electronic Publication: 2021 May 11.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: Amsterdam, Elsevier.
MeSH Terms:
Animals, Wild*
Ecosystem*
Agriculture ; Animals ; Conservation of Natural Resources ; Farms ; South Africa
Contributed Indexing:
Keywords: Drone; Grazing pressure; Livestock shepherding; Rangeland management; Vegetation cover; Wildlife coexistence
Entry Date(s):
Date Created: 20210524 Date Completed: 20210617 Latest Revision: 20210617
Update Code:
20240105
DOI:
10.1016/j.scitotenv.2021.147602
PMID:
34029808
Czasopismo naukowe
While rangeland ecosystems are globally important for livestock production, they also support diverse wildlife assemblages and are crucial for biodiversity conservation. As rangelands around the world have become increasingly degraded and fragmented, rethinking farming practice in these landscapes is vital for achieving conservation goals, rangeland recovery, and food security. An example is reinstating livestock shepherding, which aims to recouple grazing regimes to vegetation conditioned to semi-arid climates and improve productivity by reducing overgrazing and rewiring past ecological functions. Tracking the large-scale ecosystem responses to shifts in land management in such sparsely vegetated environments have so far proven elusive. Therefore, our goal was to develop a remote tracking method capable of detecting vegetation changes and environmental responses on rangeland farms engaging in contrasting farming practices in South Africa: wildlife friendly farming (WFF) implementing livestock shepherding with wildlife protection, or rotational grazing livestock farming with wildlife removal. To do so, we ground-truthed Sentinel-2 satellite imagery using drone imagery and machine learning methods to trace historical vegetation change on four farms over a four-year period. First, we successfully classified land cover maps cover using drone footage and modelled vegetation cover using satellite vegetation indices, achieving 93.4% accuracy (к = 0.901) and an r-squared of 0.862 (RMSE = 0.058) respectively. We then used this model to compare the WFF farm to three neighbouring rotational grazing farms, finding that satellite-derived vegetation productivity was greater and responded more strongly to rainfall events on the WFF farm. Furthermore, vegetation cover and grass cover, patch size, and aggregation were greater on the WFF farm when classified using drone data. Overall, we found that remotely assessing regional environmental benefits from contrasting farming practices in rangeland ecosystems could aid further adoption of wildlife-friendly practices and help to assess the generality of this case study.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 Elsevier B.V. All rights reserved.)

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