Predicting Suitability of Upland Rice for Adoption as Food Security and Poverty Alleviation Crop in Uganda

Abstract

This study was carried out in Uganda with the aim of developing a suitability map for upland rice crop based on physio-chemical soil properties and climatic factors. The analysis used physio-chemical variables of soil pH, Cation Exchange Capacity of the soils (CEC), Soil organic carbon (SOC), Digital elevation (DEM) and 19 bioclimatic variables. The physio-chemical suitability maps were derived using Geographical information system approach based on weighted overlay analysis in ArcGIS10.3, while the climate suitability map was generated using MaxEnt species distribution model. The cross raster overlay operations were done in ILWIS 3.3 to combine the overall physio-chemical suitability and climate suitability maps into the final Upland rice suitability map and the area under each suitability class calculated. The overall results show that 18.1% (43598.71km 2 ) of the arable land is suitable (S) for Upland rice production while another 20.8% (50135.63km 2 ) is moderately suitable (MS) for Upland rice production. About the same proportions of the combined Moderately (MS) and Suitable (S), 37.8% (91278.96km 2 ) is marginally suitable (mS) for Upland rice production, while just above 23.4 % (56376. 9km 2 ) of the Arable land is currently not suitable (nS) for Upland rice production.

Prediction of Bhutan's ecological distribution of rice (Oryza sativaL.) under the impact of climate change through maximum entropy modelling

“…The projected distribution area for the species is basically the probability of habitat suitability niches, or the niche models generated by using MaxEnt software (Phillips et al ., 2006; Elith and Leathwick, 2009), which could be potentially used for forecasting distribution pattern of agricultural crops. Similar studies have been reported for invasive species (Lamsal et al ., 2018), rare trees (Deb et al ., 2017; Qin et al ., 2017) and cereal crops (Ojara et al ., 2017). In the current study, the MaxEnt models indicated large changes in climatic suitability across the agro-ecological zones, which is a crucial factor for the adaptability and distribution of crops.…”

“…In the current study, the MaxEnt models indicated large changes in climatic suitability across the agro-ecological zones, which is a crucial factor for the adaptability and distribution of crops. Therefore, monitoring crop habitat suitability dynamics is important in assessing their distribution path for sustainable production and future planning (Ojara et al ., 2017; Sharma et al ., 2018). In the current research, the models under all the three anthropogenic forcing of IPCC showed large variations, in terms of magnitude and space.…”

“…Studies have reported that MaxEnt is an internationally accepted and widely used model for mapping and analysis of both animals and plant species under different climate scenarios (Qin et al ., 2017; Esfanjani et al ., 2018; Lamsal et al ., 2018; Sharma et al ., 2018). There are also reports of species distribution modelling (SDM) being developed for rice and its ecosystem (Heumann et al ., 2011; Ojara et al ., 2017; Byeon et al ., 2018). Modelling studied of Kim et al .…”