Species distribution modelling of Monotheca buxifolia (Falc.) A. DC.: Present distribution and impacts of potential climate change

Fayaz Ali; Nasrullah Khan; Arshad Mahmood Khan; Kishwar Ali; Farhat Abbas

doi:10.1016/j.heliyon.2023.e13417

Species distribution modelling of Monotheca buxifolia (Falc.) A. DC.: Present distribution and impacts of potential climate change

Heliyon. 2023 Feb 3;9(2):e13417. doi: 10.1016/j.heliyon.2023.e13417. eCollection 2023 Feb.

Authors

Fayaz Ali^{1

2}, Nasrullah Khan², Arshad Mahmood Khan³, Kishwar Ali⁴, Farhat Abbas⁵

Affiliations

¹ Department of Botany, Shaheed Benazir Bhutto University Sheringal, Dir Upper, 18050, Pakistan.
² Department of Botany, University of Malakand, Dir Lower, 18800, Pakistan.
³ Department of Botany, Government Hashmat Ali Islamia Associate College Rawalpindi, Rawalpindi, 46300, Pakistan.
⁴ College of General Education, University of Doha for Science and Technology, P.O. Box 24449, Doha, Qatar.
⁵ College of Engineering Technology, University of Doha for Science and Technology, P.O. Box 24449, Doha, Qatar.

Abstract

Species distribution modelling (SDM) is an important tool to examine the possible change in the population range and/or niche-shift under current environment and predicted climate change. Monotheca buxifolia is an economically and ecologically important tree species inhabiting Pakistan and Afghanistan in dense patches, and species range is contracting rapidly. This study hypothesize that predicted climate change might remarkably influence the existing distribution pattern of M. buxifolia in the study area. A total of 75 occurrence locations were identified comprising M. buxifolia as a dominant tree species. The Maximum Entropy (MaxEnt) algorithm was utilized to perform the SDM under current (the 1970s-2000s) and two future climate change scenarios (shared socioeconomic pathways: SSPs 245 and 585) of two time periods (the 2050s and 2070s). The optimal model settings were assessed, and simulation precision was assessed by examining the partial area under the receiver operating characteristic curve (pAUC-ROC). The results showed that out of 39 considered bio-climatic, topographic, edaphic, and remote sensing variables which were utilized in the preliminary model, 6 variables including precipitation of warmest quarter, topographic diversity, global human modification of terrestrial land, normalized difference vegetation index, isothermality, and elevation (in order) were the most influential drivers, and utilized in all reduced SDMs. A high predictive performance (pAUC-ROC; >0.9) of all the considered SDMs was recorded. A total of about 67,684 km² of geographical area was predicted as suitable habitat (p > 0.8) for M. buxifolia, and Pakistan is the leading country (with about 54,975 km² of suitable land area) under the current climate scenario. Overall, the existing distribution of the tree species in the study area might face considerable loss (i.e. rate of change %; -27 to -107) in future, and simultaneously a northward (high elevation) niche shift is predicted for all the considered future climate change scenarios. Hence, development and implementation of a coordinated conservation program is required on priority basis to save the tree species in its native geographic range.

Keywords: Biodiversity loss; Conservation planning; Future prediction; Potential habitat suitability; Species distribution models.