Abstract
ABSTRACT Soil compaction and pasture degradation are often due to the pressure exerted by the animals’ hooves. In this sense, this study aimed to verify possible changes in the soil and changes in the pasture vegetation coverage due to animal trampling. Thus, a study was carried out on a farm in the ‘Agreste’ region of Pernambuco, Brazil. Soil samples were collected before and after the grazing period, with 36 points regularly distributed in an area of 40 × 40 m managed under continuous grazing, with a stocking rate of 12 AU ha-1. At each point, density, total porosity, humidity, and penetration resistance of the soil at a depth of 0-0.10 m, as well as hydraulic conductivity and organic matter in the soil surface, were determined. Before and after grazing, images from the Sentinel-2A satellite were also obtained to observe the response pattern of pasture vegetation over time using the Normalized Difference Vegetation Index (NDVI) and Pasture Vegetation Coverage (PVC). The physical-hydric attributes of the soil were subjected to factor analysis. NDVI and PVC maps were evaluated for spatial variability. After the grazing period, there was a change in the attributes of the soil under study due to the animal trampling. Remote sensing (NDVI and PVC) highlighted patterns of variation, such as the reduction of pasture and possible areas of preference for the animals.
Highlights
With 221.81 million head of cattle in 2018, Brazil occupies a prominent position, with the largest cattle herd in the world
Soil compaction and pasture degradation are often due to the pressure exerted by the animals’ hooves
Normalized Difference Vegetation Index (NDVI) and Pasture Vegetation Coverage (PVC) maps were evaluated for spatial variability
Summary
With 221.81 million head of cattle in 2018, Brazil occupies a prominent position, with the largest cattle herd in the world. Given the possible impacts caused on grazed fields, the use of remote sensing techniques for spatial monitoring of changes in pasture areas, especially when using vegetation indexes such as the Normalized Difference Vegetation Index (NDVI) and the Pasture Vegetation Coverage (PVC), present themselves as essential allies in monitoring the response patterns of pasture vegetation cover, important mainly for the assessment of environmental degradation (Oldoni et al, 2019). In this context, the use of remote sensing techniques in conjunction with information on soil attributes can help to make management decisions to reduce the negative environmental impact of agriculture and livestock (Bernardi et al, 2017)
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