Spatiotemporal dynamics of habitat suitability for the Ethiopian staple crop, Eragrostis tef (teff), under changing climate

Abstract

Teff (Eragrostis tef (Zucc.) Trotter) is a staple, ancient food crop in Ethiopia. Its growth is affected by climate change, so it is essential to understand climatic effects on its habitat suitability in order to design countermeasures to ensure food security. Based on the four Representative Concentration Pathway emission scenarios (i.e., RCP2.6, RCP4.5, RCP6.0 and RCP8.5) set by the Intergovernmental Panel on Climate Change (IPCC), we predicted the potential distribution of teff under current and future scenarios using a maximum entropy model (Maxent). Eleven variables were selected out of 19, according to correlation analysis combined with their contribution rates to the distribution. Simulated accuracy results validated by the area under the curve (AUC) had strong predictability with values of 0.83–0.85 for current and RCP scenarios. Our results demonstrated that mean temperature in the coldest season, precipitation seasonality, precipitation in the cold season and slope are the dominant factors driving potential teff distribution. Proportions of suitable teff area, relative to the total study area were 58% in current climate condition, 58.8% in RCP2.6, 57.6% in RCP4.5, 59.2% in RCP6.0, and 57.4% in RCP8.5, respectively. We found that warmer conditions are correlated with decreased land suitability. As expected, bioclimatic variables related to temperature and precipitation were the best predictors for teff suitability. Additionally, there were geographic shifts in land suitability, which need to be accounted for when assessing overall susceptibility to climate change. The ability to adapt to climate change will be critical for Ethiopia’s agricultural strategy and food security. A robust climate model is necessary for developing primary adaptive strategies and policy to minimize the harmful impact of climate change on teff.

Changes in habitat suitability and population size of the endangered Przewalski's gazelle

“…We used the Band Collection Statistics tool in ArcGIS 10.2 to analyze the spatial correlation of the above environmental variables. Among the paired variables with correlation coe cients > 0.8, we discarded the ones (curvature and relief) with less contribution to the habitat suitability model to reduce the over-tting of the model caused by multicollinearity among variables (Graham 2003;Liu et al 2005;Swanepoel et al 2013;Zewudie et al 2021). For the raster data of all the above factors, the spatial resolution was resampled to 30 m, the projection coordinates were set to WGS1984 UTM Zone 47N, and then they were converted to ASCII format.…”