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Predicting the distribution of C3 (Festuca spp.) grass species using topographic variables and binary logistic regression model

期刊

GEOCARTO INTERNATIONAL
卷 33, 期 5, 页码 489-504

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2016.1265598

关键词

Topographic factors; Festuca grass species; GIS modelling; binary logistic regression; grassland management

资金

  1. UKZN College of Agriculture, Engineering and Science

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The spatial distribution of different C3 and C4 grass species in tropical montane areas is commonly influenced by a number of factors that include site-specific topography. Hence, the distribution of these grasses across topographic gradients can vary significantly. In this study, we investigate the influence of topographic factors (elevation, slope and aspect) on the spatial distribution of Festuca grass species in a commonage area, comprising agro-biodiversity conservation land use. Integration of the topographic variables using GIS and binary logistic regression (LR) modelling showed that C3, Festuca grass species distribution can be predicted or mapped with an accuracy of 80% in the landscape under study. The study contributes to understanding the spatial distribution of C3 grass species and provides valuable information for designing and optimizing rangeland conservation in the subtropical montane landscapes.

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