Ramachandra T V, Negi Paras, Mondal Tulika, Ahmed Syed Ashfaq
Energy & Wetlands Research Group and IISc-EIACP, Centre for Ecological Sciences [CES], Indian Institute of Science, Bangalore, India.
Centre for Sustainable Technologies [astra], Indian Institute of Science, Bangalore, 560012, India.
Sci Rep. 2025 May 4;15(1):15606. doi: 10.1038/s41598-025-00167-3.
Large-scale land cover changes leading to land degradation and deforestation in fragile ecosystems such as the Western Ghats have impaired ecosystem services, evident from the conversion of perennial water bodies to seasonal, which necessitates an understanding of forest structure dynamics with ecosystem services to evolve appropriate location-specific mitigation measures to arrest land degradation. The current study evaluates the extent and condition of forest ecosystems in Goa of the Central Western Ghats, a biodiversity hotspot. Land use dynamics is assessed through a supervised hierarchical classifier based on the Random Forest Machine Learning Algorithm, revealing that total forest cover declined by 3.75% during the post-1990s due to market forces associated with globalization. Likely land uses predicated through the CA-Markov-based Analytic Hierarchy Process (AHP) highlight a decline in evergreen forest cover of 10.98%. The carbon sequestration potential of forests in Goa assessed through the InVEST model highlights the storage of 56,131.16 Gg of carbon, which accounts for 373.47 billion INR (4.49 billion USD). The total ecosystem supply value (TESV) for forest ecosystems was computed by aggregating the provisioning, regulating, and cultural services, which accounts for 481.76 billion INR per year. TESV helps in accounting for the degradation cost of ecosystems towards the development of green GDP (Gross Domestic Product). Prioritization of Ecologically Sensitive Regions (ESR) considering bio-geo-climatic, ecological, and social characteristics at disaggregated levels reveals that 54.41% of the region is highly sensitive (ESR1 and ESR2). The outcome of the research offers invaluable insights for the formulation of strategic natural resource management approaches.
大规模的土地覆盖变化导致了西高止山脉等脆弱生态系统的土地退化和森林砍伐,损害了生态系统服务功能,从常年性水体转变为季节性水体便可明显看出,这就需要了解森林结构动态与生态系统服务功能,以制定适当的因地制宜的缓解措施来遏制土地退化。本研究评估了中西部高止山脉生物多样性热点地区果阿邦森林生态系统的范围和状况。通过基于随机森林机器学习算法的监督分层分类器评估土地利用动态,结果显示,由于与全球化相关的市场力量,20世纪90年代后期森林总面积下降了3.75%。通过基于元胞自动机-马尔可夫模型的层次分析法预测的可能土地利用情况表明,常绿森林覆盖率下降了10.98%。通过InVEST模型评估的果阿邦森林碳固存潜力显示,碳储量为56131.16千兆克,价值3734.7亿印度卢比(44.9亿美元)。森林生态系统的总生态系统供应价值(TESV)通过汇总供给、调节和文化服务来计算,每年总计4817.6亿印度卢比。TESV有助于计算生态系统退化成本,以促进绿色国内生产总值(GDP)的发展。考虑到生物地理气候、生态和社会特征在细分层面上对生态敏感区域(ESR)进行优先排序,结果显示该地区54.41%的区域高度敏感(ESR1和ESR2)。该研究结果为制定战略性自然资源管理方法提供了宝贵的见解。