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

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 km 2 (2.52%), 7226.28 km 2 (13.29%), and 5377.26 km 2 (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.

Potential Global Distribution of Daktulosphaira vitifoliae under Climate Change Based on MaxEnt

“…Evaluation of model performance is an important step in niche modeling [ 35 ]. The model generated was evaluated usually through calculating the AUC (area under the curve) of the receiver operating characteristic (ROC) plot [ 36 ]. However, some disadvantages were found in the current study due to equal weighting of omission and commission errors, and even AUC value could not provide effective information on the spatial distribution of model errors [ 37 ].…”

Projecting the Potential Distribution of Glossina morsitans (Diptera: Glossinidae) under Climate Change Using the MaxEnt Model

“…A correlation coefficient greater than 0.8 or less than −0.8 is generally considered significant. Variables having a larger contribution rate are retained, while the others should be removed after a correlation test [ 29 ]. Nine environmental variables were reserved.…”

Global potential distribution prediction of Xanthium italicum based on Maxent model

“…The output is a thematic map reflecting the suitability of the relative distribution of species 29 , 30 . Maxent model has been widely used in the field of species distribution research 31 , 32 , such as the potential distribution of Haloxylon persicum in Central Asia under global warming 33 , the prediction of the suitable growth zone of Rhinopithecus roxellana due to the sharp reduction of human disturbance 34 , and the distribution of five economic tree species in the Amazon River basin combined with remote sensing technology 35 . Besides, Maxent niche models have also been used to study the potential distribution of invasive species in recent years, such as Solidago canadensis, Ageratina adenophora, Mimosa pigra, Flaveria bidentis, Solenopsis invicta and Ambrosia artemisiifolia 36 – 41 .…”