2017
DOI: 10.1007/s40333-017-0058-7
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Modelling the impact of climate change on rangeland forage production using a generalized regression neural network: a case study in Isfahan Province, Central Iran

Abstract: Monitoring of rangeland forage production at specified spatial and temporal scales is necessary for grazing management and also for implementation of rehabilitation projects in rangelands. This study focused on the capability of a generalized regression neural network (GRNN) model combined with GIS techniques to explore the impact of climate change on rangeland forage production. Specifically, a dataset of 115 monitored records of forage production were collected from 16 rangeland sites during the period 1998-… Show more

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Cited by 8 publications
(1 citation statement)
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“…In mesic and semi-arid savannas south of the Sahara, both shrub and tree cover are projected to increase, albeit at lower productivity and standing biomass. Rangelands in western and south-western parts of the Isfahan province in Iran were found to be more vulnerable to future drying-warming conditions (Saki et al 2018;Jaberalansar et al 2017).…”
Section: Observedmentioning
confidence: 99%
“…In mesic and semi-arid savannas south of the Sahara, both shrub and tree cover are projected to increase, albeit at lower productivity and standing biomass. Rangelands in western and south-western parts of the Isfahan province in Iran were found to be more vulnerable to future drying-warming conditions (Saki et al 2018;Jaberalansar et al 2017).…”
Section: Observedmentioning
confidence: 99%