林业科学和森林生态系统经营决策系统的关系

 

Society invests in science to advance human interests and limit human impacts on the environment. However, despite great progress in forest science, governments and forest companies remain reluctant to invest adequately in research. We believe this reflects the perception that forest science servers itself than forestry, and that one determent is a misunderstanding of science. Science involves knowing, understanding, and predicting. Many feel that only reductionist, disciplinary, hypothetico-deductively-derived understanding component is hard science. Inductively derived knowledge and experience are often regarded as soft science. Predicting future states of forest involve complex hypotheses that are not amenable to traditional hypothesis testing, according to some, this renders prediction of complex systems soft science. Science-based forest policy frequently employs hard science: the understanding component of science based on reductionist, jigsaw puzzle research. Necessary for the development of SFM, this is not sufficient for reliable prediction of possible forest ecosystem futures, for which knowledge and understanding must be synthesized into decision support systems at appropriate temporal, spatial and complexity scales. Thesis should be linked to visualization software to creat a common language by which to communicate to diversity of audiences the available choices and their possible consequences.

专家简介：南京林业大学校长、党委副书记。森林培育学和经济林栽培学教授，博士生导师。先后主持25项国家、部省级研究课题，有15项成果获国家、部省级科技进步奖。入选“江苏省普通高校跨世纪学术带头人培养对象”、江苏省“333跨世纪学术、技术带头人培养工程”第二层次培养对象、“林业部跨世纪学术带头人培养对象”， 先后被授予“江苏省青年科技奖“、“江苏省有突出贡献的中青年专家”和“江苏省青年科技标兵”等称号, 享受国务院特殊津贴、2008年被评为江苏省“333第一层次江苏省中青年首席科学家人选”。