首页 | 本学科首页   官方微博 | 高级检索  
     检索      


The perfect landscape
Authors:Jonathan D Phillips  
Institution:aTobacco Road Research Team, Department of Geography, University of Kentucky, Lexington, KY 40506-0027, United States
Abstract:The “perfect storm” metaphor describes the improbable coincidence of several different forces or factors to produce an unusual outcome. The perfect landscape is conceptualized as a result of the combined, interacting effects of multiple environmental controls and forcings to produce an outcome that is highly improbable, in the sense of the likelihood of duplication at any other place or time. Geomorphic systems have multiple environmental controls and forcings, and degrees of freedom in responding to them. This allows for many possible landscapes and system states. Further, some controls and forcings are causally contingent. These contingencies are specific to time and place. Dynamical instability in many geomorphic systems creates and enhances some of this contingency by causing the effects of minor initial variations and small disturbances to persist, and grow disproportionately large, over time. The joint probability of any particular set of global controls is low, as the individual probabilities are < 1, and the probability of any set of local, contingent controls is even lower. Thus, the probability of existence of any landscape or earth surface system state at a particular place and time is negligibly small: all landscapes are perfect. Recognition of the perfection of landscapes leads away from a worldview holding that landforms and landscapes are the inevitable outcomes of deterministic laws, such that only one outcome is possible for a given set of laws and initial conditions. A perfect landscape perspective leads toward a worldview that landforms and landscapes are circumstantial, contingent results of deterministic laws operating in a specific environmental context, such that multiple outcomes are possible.
Keywords:Perfect landscape  Contingency  Geomorphic system  Instability  Probability
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号