11月26日 John Harte :Hybridizing Mechanism and MaxEnt: Ecological Theory for the Anthropocene

来源:中国足球竞彩比分 时间:2020-11-18浏览:45设置


讲座题目:Hybridizing Mechanism and MaxEnt: Ecological Theory for the Anthropocene

主讲人:John Harte  教授

主持人:何 芳 良  教授

开始来源:中国足球竞彩比分 时间:2020-11-26   10:30:00

讲座地址:腾讯会议(或VooV Meeting  ID848 818 218

主办单位:生态与环境科学学院

 

报告人简介:

John Harte is a Professor of the Graduate School of University of California, Berkeley, America. He received a BA in physics from Harvard University in 1961 and a PhD in theoretical physics from the University of Wisconsin in 1965. He was an NSF Postdoctoral Fellow at CERN, Geneva, during 1965–66 and a Postdoctoral Fellow at the University of  California, Lawrence Berkeley Laboratory, during 1966–68. During the next 5 years, he was an Assistant Professor of Physics at Yale University and has been at Berkeley since 1973. He has served on six National Academy of Sciences Committees and has authored over 200 scientific publications, including eight books.

Harte’s research focuses on the effects of   human actions on, and the linkages among, biogeochemical processes, ecosystem   structure and function, biodiversity, and climate.  His work spans a range of scales from plot to   landscape to global and utilizes field investigations, mathematical modeling,   and theory development.  Two themes,   feedback and scaling, weave through much of his research.

 

报告内容:

At the frontier of research in many fields,   from ecology to economics, many of the most exciting problems today have to   do with “complex systems”.  These are   systems characterized by feedbacks, nonlinearities, and a myriad of   non-identical subunits, that are resistant to traditional reductionist   methods of scientific investigation.    Using ecology as an example, I show how a mathematical method based on   information theory provides a promising foundation for constructing complex   systems theory.  Ecosystems display   pervasive patterns in 1. the scaling of species richness with area, 2. the   distributions of abundance across species, 3. The distribution of individuals   within species over space, 4. the distribution of metabolic rates or body   sizes across individuals, 5. the relationship between size and abundance, 6.   the distribution of species richness across higher taxonomic categories, and   7. the distribution of edges across nodes in trophic networks.  A theory of ecology based on the maximum   entropy principle, predicts all these patterns remarkably accurately in relatively   static ecosystems but the theory fails in ecosystems that are responding to   anthropogenic stresses, or are undergoing rapid diversification or   succession.  Hybridizing mechanism with   MaxEnt, however, results in a theory capable of describing dynamic ecosystems   that are changing in response to disturbance.    I conclude that complexity science in the decades ahead may have its   roots in information theory.

 


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