Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA.
Proc Natl Acad Sci U S A. 2012 Dec 18;109(51):20837-41. doi: 10.1073/pnas.1218636109. Epub 2012 Dec 3.
The spatial organization of functional vegetation types in river basins is a major determinant of their runoff production, biodiversity, and ecosystem services. The optimization of different objective functions has been suggested to control the adaptive behavior of plants and ecosystems, often without a compelling justification. Maximum entropy production (MEP), rooted in thermodynamics principles, provides a tool to justify the choice of the objective function controlling vegetation organization. The application of MEP at the ecosystem scale results in maximum productivity (i.e., maximum canopy photosynthesis) as the thermodynamic limit toward which the organization of vegetation appears to evolve. Maximum productivity, which incorporates complex hydrologic feedbacks, allows us to reproduce the spatial macroscopic organization of functional types of vegetation in a thoroughly monitored river basin, without the need for a reductionist description of the underlying microscopic dynamics. The methodology incorporates the stochastic characteristics of precipitation and the associated soil moisture on a spatially disaggregated framework. Our results suggest that the spatial organization of functional vegetation types in river basins naturally evolves toward configurations corresponding to dynamically accessible local maxima of the maximum productivity of the ecosystem.
流域内功能植被类型的空间组织是决定其径流量产生、生物多样性和生态系统服务的主要因素。为了控制植物和生态系统的自适应行为，人们建议优化不同的目标函数，但这通常缺乏令人信服的理由。最大熵产生（MEP）源于热力学原理，为控制植被组织的目标函数选择提供了一种工具。在生态系统尺度上应用 MEP 会导致最大生产力（即冠层光合作用的最大值），这是植被组织似乎演化的热力学极限。最大生产力包含复杂的水文反馈，使我们能够在一个经过彻底监测的流域中重现功能植被类型的空间宏观组织，而无需对潜在的微观动力学进行简化描述。该方法将降水的随机特征和相关的土壤湿度纳入到空间离散的框架中。我们的研究结果表明，流域内功能植被类型的空间组织自然地朝着与生态系统最大生产力的动态可及局部最大值相对应的配置演化。
