Elsevier Advanced Modelling Techniques Studying Global Changes in Environmental Sciences (Developments in Environmental Modelling): Volume 27

Product Description Advanced Modelling Techniques Studying Global Changes in Environmental Sciences discusses the need for immediate and effective action, guided by a scientific understanding of ecosystem function, to alleviate current pressures on the environment. Research, especially in Ecological Modeling, is crucial to support the sustainable development paradigm, in which the economy, society, and the environment are integrated and positively reinforce each other. Content from this book is drawn from the 2013 conference of the International Society for Ecological Modeling (ISEM), an important and active research community contributing to this arena. Some progress towards gaining a better understanding of the processes of global change has been achieved, but much more is needed. This conference provides a forum to present current research using models to investigate actions towards mitigating and adapting to change. Presents state-of-the-art modeling techniques Drawn from the 2013 conference of the International Society for Ecological Modeling (ISEM), an important and active research community contributing to this arena Integrates knowledge of advanced modeling techniques in ecological and environmental sciences Describes new applications for sustainability Review This book provides overviews and perspectives on advanced modeling techniques in ecology and the environmental sciences as presented at the 2013 conference of the International Society for Ecological Modeling (ISEM), an important and active research community contributing to this arena. About the Author Young-Seuk Park is a Professor at the Department of Biology, Kyung University, Seoul, Republic of Korea. After completing a PhD at Pusan National University, he undertook post-doctoral research at CNRS, Université Paul Sabatier, and Cemagraf in France, and he obtained an HDR (Habilitation à Diriger des Recherches / Accreditation to Supervise Research) from the Université Paul Sabatier in Toulouse, France, before returning Korea to establish his independent reseach group at Kyung Hee University. His laboratory studies the effects of environmental changes on biological systems at different hierarchical levels from molecules, individuals, populations, and communities through ecological modelling and ecological informatics approaches. In particular, his research is focused on the effects of global changes on ecosystems, and ecological monitoring and assessment for sustainable ecosystem management. He is interested in computational approaches such as machine learning techniques and advanced statistical methods. He is an associate editor of two scientific journals Annales de Limnologie - International Journal of Limnology and Journal of Ecology and Environment, and he is also on the editorial boards of several journals including Ecological Informatics and Animal Cells and Systems. He was a guest editor for several Special Issues in scientific journals including Ecological Modelling, Ecological Informatics, Annales de Limnologie - International Journal of Limnology, Inland Waters, and Water. He is the recipient of the 2014 Yeocheon Ecology Award. Sovan Lek is a Professor at the University of Toulouse. His research is mainly in Fish Community Ecology and Ecological Modelling. In Fish Community Ecology, his research concerns the biodiversity and the spatial distribution of fish according to the environmental characteristics and the response of fish community to the human disturbances, especially land-use, hydromorphology, climate warming. The distribution of fish is considered according to the scale of variation, varying from local to regional and global scales, in relationship with the environmental variables. In Ecological Modelling, he is mainly interested in the use of machine learning techniques. He is also familiar with the uses of classical modelling techniques like classical statistic methods (multiple linear regression