Predicting the Suitable Current and Future Potential Distribution of the Native Endangered Tree Tecomella undulata (Sm.) Seem. in Pakistan

SUSTAINABILITY(2022)

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摘要
The burgeoning human population exhibited a rapid amplification in demand for timber and fuelwood and as a result, the natural population of the native tree Tecomella undulata reduced rapidly due to its high economic and medicinal significance. The recognition of appropriate regions for threatened plants in the climate change scenario is a fundamental step for the restoration and conservation of biodiversity. The current study predicts the potentially suitable areas in Pakistan for T. undulata restoration. This research identifies the highly appropriate regions for vulnerable T. undulata through the maximum entropy model from MaxEnt software. The model's Area Under Curve 0.968 suggested its accuracy. The mean temperature of the wettest quarter, precipitation of the warmest quarter, and mean temperature in the driest quarter significantly shaped the T. undulata distribution. Future suitable areas for T. undulata were made by using RCP (4.5 and 8.5) for the years 2050 and 2070 through 19 bioclimatic variables and 66 occurrence points. The current highly suitable area for T. undulata is approximately 135,749 km(2) (15.4%) while the unsuitable area identified is approximately 404,917 km(2) (45.91%). The highly suitable area for T. undulata increases by 3.6-7% under climate change regimes (RCP 4.5 and RCP 8.5). The Central Punjab (District Faisalabad, Nankana sahib, Jhang, Kasur, and Okara), Salt Range, Western Khayber Pakhtunkhwa (KPK), FATA area, Eastern Balochistan, and Thar and Tharparker in Sindh are the current appropriate habitats for T. undulata. Under all future climatic circumstances, the extremely appropriate area for T. undulata was anticipated to expand, whereas the unsuitable zones would all shrink. The research would be significant for the further development of T. undulata management and conservation techniques.
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关键词
climate change, conservation, management techniques, maxent modeling, suitable habitats
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