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This edited book is focused on SDG 15. This volume covers aspects of species and ecosystem modelling in understanding the complexity of ecological systems, restoration, protected area management, and species conservation. The book follows a systematic and situation-sensitive approach to discuss ecosystem and species modelling tools, approaches, science, case studies, opportunities, and gaps for enhancing conservation efforts, ensuring ecosystem resilience, and addressing sustainability issues. The book emphasizes on science, innovations, case studies, and strategic relevance as the main pillars of using ecosystem and species modelling tools and implementing the outcomes and results. In addition, clear conceptual frameworks, elaborated methodologies, and their applications are included to support policy planning and interventions to reduce and reverse human encroachment in human-dominated natural ecosystems, their degradation, and the loss of important species and ecosystem services. Essential information with a special focus on advances and opportunities in advancing the implementation of results and outputs of the modelling tools, challenges and constraints for addressing the loss of ecosystem services, designing and implementing sustainable landscape restoration, environmental risk assessment, and finally understanding policy implications and concerns for mainstreaming modelling results in conservation planning and decision-making is included in Ecosystem and Species Habitat Modeling for Conservation and Restoration. Further topics include the ultimate translational value of modelling tools and efforts across transitional ecosystems and species habitats to provide better evidence to influence the nature-based solutions (NbS) and ecosystem health assessment using the Red List of Ecosystems (RLE). The emerging roles of integrative socio-ecological as well as techno-cultural factors in promoting the relevance of ecosystem and species modelling are one of the key features of this book. This edited volume is of interest and useful to researchers, students, scholars, policymakers, forest managers, consultants, and policymakers in the fields of protected area management, forest department, conservation, modelling, climate change, and sustainability science, and also authors engaged in IPBES, IPCC, and several other assessments.
Dr Shalini Dhyani is a Senior Scientist with the Critical Zone Group of Water Technology and Management Division of CSIR-NEERI, India. She is a seasoned ecologist with two decades of experience. She uses observational, empirical, and modelling approaches to investigate and understand issues related to the environment, loss of natural and urban greenspaces, interlinkages between ecological, and social systems through sustainability science approaches. She is an Asia Vice Chair member of CEM (Commission on Ecosystems Management) and also a Steering Committee member.
Dr Dibyendu Adhikari is a Principal Scientist at CSIR-National Botanical Research Institute (NBRI), India. He is a seasoned researcher with over 15 years of experience in ecology and environmental science. He is skilled in terrestrial ecosystem restoration, threatened plant conservation, forest carbon assessment, ecological data analysis and modelling.
Dr Rajarshi Dasgupta is Assistant Professor at IIT Delhi. He was previously with the Institute for Global Environmental Strategies (IGES), Kanagawa, Japan. He holds diverse research interests in the field of landscape ecology and planning, which include Ecosystem-based Disaster Risk Reduction (Eco-DRR), spatial quantification of ecosystem services, land change simulation, development of socio-ecological scenarios, participatory conservation, and social forestry.
Dr Rakesh Kadaverugu is a Senior Scientist associated with CSIR National Environmental Engineering Research Institute. He has more than 10 years of research experience in environmental systems modelling and his work is focused on better understanding the socio-environmental systems at multiple spatial and temporal scales using geospatial, soft-computing, and process-based modelling approaches.
