Zewudie Dinka, Ding Wenguang, Rong Zhanlei, Zhao Chuanyan, Chang Yapeng
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China.
College of Geographical Science, Qinghai Normal University, Xining, China.
PeerJ. 2021 Mar 22;9:e10965. doi: 10.7717/peerj.10965. eCollection 2021.
Teff ( (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.
画眉草((Zucc.) Trotter)是埃塞俄比亚一种主要的古老粮食作物。其生长受到气候变化的影响,因此,为了设计应对措施以确保粮食安全,了解气候对其栖息地适宜性的影响至关重要。基于政府间气候变化专门委员会(IPCC)设定的四种代表性浓度路径排放情景(即RCP2.6、RCP4.5、RCP6.0和RCP8.5),我们使用最大熵模型(Maxent)预测了当前和未来情景下画眉草的潜在分布。根据相关性分析并结合它们对分布的贡献率,从19个变量中选出了11个变量。通过曲线下面积(AUC)验证的模拟准确性结果具有很强的可预测性,当前情景和RCP情景下的值为0.83 - 0.85。我们的结果表明,最冷月平均温度、降水季节性、寒冷季节降水量和坡度是驱动画眉草潜在分布的主要因素。相对于整个研究区域,当前气候条件下适宜画眉草生长的面积比例为58%,RCP2.6情景下为58.8%,RCP4.5情景下为57.6%,RCP6.0情景下为59.2%,RCP8.5情景下为57.4%。我们发现,气候变暖与土地适宜性下降相关。正如预期的那样,与温度和降水相关的生物气候变量是画眉草适宜性的最佳预测指标。此外,土地适宜性存在地理转移,在评估对气候变化的总体敏感性时需要考虑这一点。适应气候变化的能力对埃塞俄比亚的农业战略和粮食安全至关重要。一个强大的气候模型对于制定初步的适应战略和政策以尽量减少气候变化对画眉草的有害影响是必要的。