Climate change will either improve, reduce, or shift its appropriate climatic habitat of a particular species, which could result in shifts from its geographical range. Predicting the potential distribution through MaxEnt modeling has been developed as an appropriate tool for assessing habitat distribution and resource conservation to protect bamboo species. Our objective is to model the current and future distribution of Oxytenanthera abyssinica (A. Richard) based on three representative concentration pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5) for 2050s and 2070s using a maximum entropy model (MaxEnt) in Northern Ethiopia. For modeling procedure, 77 occurrence records and 11 variables were retained to simulate the current and future distributions of Oxytenanthera abyssinica in Northern Ethiopia. To evaluate the performance of the model, the area under the receiver operating characteristic (ROC) curve (AUC) was used. All of the AUCs (area under curves) were greater than 0.900, thereby placing these models in the “excellent” category. The jackknife test also showed that precipitation of the coldest quarter (Bio19) and precipitation of the warmest quarter (Bio18) contributed 66.8% and 54.7% to the model. From the area of current distribution, 1367.51 km2 (2.52%), 7226.28 km2 (13.29%), and 5377.26 km2 (9.89%) of the study area were recognized as high, good, and moderate potential habitats of Oxytenanthera abyssinica in Northern Ethiopia, and the high potential area was mainly concentrated in Tanqua Abergele (0.70%), Kola Temben (0.65%), Tselemti (0.60%), and Tsegede (0.31%). Kafta Humera was also the largest good potential area, which accounts for 2.75%. Compared to the current distribution, the total area of the high potential regions and good potential regions for Oxytenanthera abyssinica under the three RCPs (RCP2.6, RCP4.5, and RCP8.5) would increase in the 2050s and 2070s. However, the total area of the least potential regions under the three RCPs (RCP2.6, RCP4.5, and RCP8.5) in 2050s and 2070s would decrease. This study can provide vital information for the protection, management, and sustainable use of Oxytenanthera abyssinica, the resource to address the global climate challenges.

中文翻译：

---

利用MaxEnt模型在埃塞俄比亚北部气候变化下当前和未来的奥比斯牛（A. Richard）潜在面积预测。

气候变化将改善，减少或改变其特定物种的适当气候栖息地，这可能导致其地理范围的变化。通过MaxEnt建模预测潜在分布已被开发为评估栖息地分布和资源保护以保护竹种的适当工具。我们的目标是使用最大熵模型，基于2050年代和2070年代的三个代表性浓度路径（RCP）（RCP2.6，RCP4.5和RCP8.5），对深红木（A. Richard）的当前和未来分布进行建模（MaxEnt）在埃塞俄比亚北部。对于建模过程，保留了77个发生记录和11个变量，以模拟埃塞俄比亚北部奥比斯滕（Oxytenanthera asssinica）的当前和未来分布。要评估模型的性能，使用接收器工作特性（ROC）曲线（AUC）下的面积。所有AUC（曲线下的面积）均大于0.900，因此将这些模型置于“优秀”类别中。折刀测试还显示，最冷的四分之一（Bio19）的降水和最暖的四分之一（Bio18）的降水占模型的66.8％和54.7％。从目前的分布区域来看，埃塞俄比亚北部奥比斯滕南奥比斯汀牛的高，好和中度潜在生境被认为是研究区域的1367.51 km2（2.52％），7222.68 km2（13.29％）和5377.26 km2（9.89％），高潜力地区主要集中在坦夸·阿贝格勒（0.70％），科拉·滕本（0.65％），特塞勒姆蒂（0.60％）和瑟格德（0.31％）。Kafta Humera也是最大的潜在潜力区，占2.75％。与目前的分布相比，在三个RCP（RCP2.6，RCP4.5和RCP8.5）下，深渊Oxytenanthera asssinica的高电势区域和良好电势区域的总面积将在2050年代和2070年代增加。但是，到2050年代和2070年代，三个RCP（RCP2.6，RCP4.5和RCP8.5）下潜力最小的区域的总面积将减少。这项研究可以为保护，管理和可持续利用深加工草（Oxytenanthera asssininica）提供重要信息，该资源可以应对全球气候挑战。5）在2050年代和2070年代将会减少。这项研究可以为保护，管理和可持续利用深加工草（Oxytenanthera asssinica）提供重要信息，这是应对全球气候挑战的资源。5）在2050年代和2070年代将会减少。这项研究可以为保护，管理和可持续利用深加工草（Oxytenanthera asssininica）提供重要信息，该资源可以应对全球气候挑战。