The modeling of pasture conservation and of its impact on stream water quality using Partial Least Squares-Path Modeling

Cattle grazing is a major source of income across the globe, and therefore conservation of pastures is vital to society. Pasture conservation requires the full understanding of factors contributing to their degradation, which is facilitated through panoramic analyses capable to handle all factors an...

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Veröffentlicht in:The Science of the total environment 2019-12, Vol.697, p.134081-134081, Article 134081
Hauptverfasser: Oliveira, Caroline Fávaro, do Valle Junior, Renato Farias, Valera, Carlos Alberto, Rodrigues, Vinícius Silva, Sanches Fernandes, Luis Filipe, Pacheco, Fernando Antônio Leal
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container_end_page 134081
container_issue
container_start_page 134081
container_title The Science of the total environment
container_volume 697
creator Oliveira, Caroline Fávaro
do Valle Junior, Renato Farias
Valera, Carlos Alberto
Rodrigues, Vinícius Silva
Sanches Fernandes, Luis Filipe
Pacheco, Fernando Antônio Leal
description Cattle grazing is a major source of income across the globe, and therefore conservation of pastures is vital to society. Pasture conservation requires the full understanding of factors contributing to their degradation, which is facilitated through panoramic analyses capable to handle all factors and capture their relationships at once. In this study, Partial Least Squares – Path Modeling (PLS-PM) was used to accomplish that task. The study area was the Environmental Protection Area of Uberaba River Basin (525 km2), located in the state of Minas Gerais, Brazil, and extensively used for livestock pasturing (51%). The selected (15) contributing factors comprised soil characteristics (e.g., organic matter, phosphorus content), runoff indicators (e.g., percentage of sand and clay in the soil), environmental land use conflicts (deviations of actual from natural uses), stream water quality parameters (e.g., oxidation-reduction potential-ORP, turbidity), and pasture conservation indicators (extent of degraded pasture within a pre-defined buffer). These measured variables were assembled into 5 conceptual (latent) variables to form the PLS-PM model, namely Groundcover, Pasture Conservation, Surface Runoff, Environmental Land Use Conflicts and Water Quality. The results elected Groundcover as prominent contributor to Pasture Conservation, because of its largest regression (path) coefficient (β = 0.984). The most influent measured variable was organic matter. Surface Runoff (β = −0.108) and Environmental Land Use Conflicts (β = −0.135) contribute to pasture degradation. The role of conflicts is, however, limited to predefined areas where the deviations of actual from natural uses are more expressive. Pasture Conservation contributes unequivocally to improved Water Quality (β = 0.800), expressed as high ORP. The PLS-PM model was free from multi-collinearity problems and model fits (R2) were high. This gives us confidence to implement conservation measures and improved management techniques based on the PLS-PM results, and to transpose the model to other areas requiring pasture quality improvements. [Display omitted] •PLS-PM is used to assess pasture conservation and stream water quality.•Organic matter and phosphorus play a prominent role in pasture conservation.•Environmental land use conflicts contribute negatively to pasture conservation.•Pasture conservation improves stream water quality.•Robust model fits and parameters allow transposition of results to similar a
doi_str_mv 10.1016/j.scitotenv.2019.134081
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subjects Land capability
Land use
Land use conflict
Organic matter
Partial Least Squares-Path Modeling
Pasture degradation
Runoff
Stream water quality
title The modeling of pasture conservation and of its impact on stream water quality using Partial Least Squares-Path Modeling
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