Assessing high conservation value areas for rare, endemic and threatened (RET) species: A study in high altitude Changthang landscape of India

濒危物种 IUCN红色名录 环境资源管理 公民科学 地理 栖息地 稀有物种 鉴定(生物学) 物种分布 生态学 环境科学 生物 植物
作者
Mehebub Sahana,G. Areendran,Akhil Sivadas,Krishna Raj,Diwakar Sharma,Md. Sajid Sultan,Abhishek Ghoshal,Siddharth Parameswaran
出处
期刊:Journal for Nature Conservation [Elsevier BV]
卷期号:73: 126406-126406 被引量:3
标识
DOI:10.1016/j.jnc.2023.126406
摘要

The Forest Stewardship Council developed the concept of High Conservation Values (HCVs) as a criteria in the forest certification process in order to promote sustainable forest management. It has six major components or values and component one and two of HCVs deal with the habitat for viable populations of “rare, endemic and threatened (RET) species” using the IUCN Red List category and other national / regional / local lists. But a consistent robust methodology for identification of these areas, does not exist. The present study tried to develop for the first time, a straight forward inclusive methodology for identification of HCVAs for the RET species on a spatio-temporal scale. A total of 50 RET and other significant species (32 flora, 10 fauna and 8 avifauna) were identified after a thorough literature review, field surveys and consultations with experts. Occurrence data of the selected species was collected from different secondary sources, field surveys, institutes and scientists who have worked on them. A 10 km grid-based approach and stratified random sampling was used for the primary GPS field surveys conducted during 2018–2019. MaxEnt species distribution model (SDM) software was used based on the occurrence data and environmental variables for identification of potential suitable habitats for the selected species. Linear support vector machine (LSVM) model was used for assessing the performance of the SDMs. The performance of each SDM has been validated through Cohen's Kappa (KAPPA), true skill statistic (TSS) and receiver operating characteristics (ROC) models. The proposed methodology addresses the urgent need for a holistic and robust set of techniques to apply the HCV toolkit. This is key to identify and map HCVAs for RET species at the landscape level and can be easily adapted to and adopted at the national, regional, state or local level in India. The methods offer an efficient, reliable approach for the application of the HCV concept, elsewhere in the world.

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