Current and future predicting potential areas of Oxytenanthera abyssinica (A. Richard) using MaxEnt model under climate change in Northern Ethiopia

Ecological Processes - Tập 9 Số 1 - 2020
Yikunoamlak Gebrewahid1, Selemawi Abrehe2, Esayas Meresa1, Gebru Eyasu1, Kiros Abay3, Gebrehiwot Gebreab4, Kiros Kidanemariam4, Gezu Adissu4, Gebrekidan Abreha5, Girmay Darcha1
1Mekelle Agricultural Research Center (MARC), Tigray Agricultural Research Institute (TARI), P.O. Box 256, Tigray, Ethiopia
2Mekelle Soil Research Center (MSRC), Tigray Agricultural Research Institute (TARI), P.O. Box 1070, Tigray, Ethiopia
3Shire-Mytsebri Agricultural Research Center (SmARC), Tigray Agricultural Research Institute (TARI), P.O. Box 241, Tigray, Ethiopia
4Humera Agricultural Research Center (HuARC), Tigray Agricultural Research Institute (TARI), P.O. Box 62, Tigray, Ethiopia
5Abergele Agricultural Research Center (AARC), Tigray Agricultural Research Institute (TARI), P.O. Box 44, Tigray, Ethiopia

Tóm tắt

Abstract Introduction 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. Methods 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. Results 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. Conclusion This study can provide vital information for the protection, management, and sustainable use of Oxytenanthera abyssinica, the resource to address the global climate challenges.

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Ecological Processes

Tập 9 Số 1

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