MAXIMUM ENTROPY AND THE STATE-VARIABLE APPROACH TO MACROECOLOGY
MAXIMUM ENTROPY AND THE STATE-VARIABLE APPROACH TO MACROECOLOGY
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DOI：
10.1890/07-1369.1
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发表时间：
2008-10-01
期刊：
影响因子：
4.8
通讯作者：
Smith, A. B.
中科院分区：
文献类型：
--
作者：
Harte, J.;Zillio, T.;Smith, A. B.
在宏观生态学中广泛研究的生物多样性尺度包括种-面积关系（SAR）、尺度依赖的种-多度分布（SAD）、种内和种间个体质量或代谢能的分布、种间多度-能量或多度-质量关系、种级空间占有分布。我们提出了一个理论框架，预测这些和其他指标的标度形式的基础上的状态变量的概念和分析方法来自信息论。在统计物理学中，一种基于信息熵的推理方法导致了经典热力学系统在状态变量体积，温度和分子数量方面的完整宏观描述。类似地，我们将生态系统的状态变量取为其总面积、该区域内任何特定分类群内的物种总数、这些物种中的个体总数以及所有这些个体的总代谢能率。仅在这些状态变量的比率，而不调用任何特定的生态机制，我们表明，现实的功能形式的宏观生态指标上面列出的推断基于信息熵。Fisher对数级数SAD自然地从理论中出现。SAR在双对数图上预测为负曲率，但随着物种数与个体数之比的降低，SAR越来越接近幂律，预测斜率z在0.14-0.20范围内。利用3/4次方质量-代谢比例关系将能量需求与实测体型联系起来，并预测了与质量和丰度相关的Damuth比例规则。我们认为，宏观生态指标的预测形式是在合理的协议从植物普查数据中观察到的模式在栖息地和空间尺度。虽然这是令人鼓舞的，由于缺乏可调的拟合参数的理论，我们进一步认为，即使是数据和预测之间的微小差异，可以帮助确定生态机制，影响宏观生态模式。
The biodiversity scaling metrics widely studied in macroecology include the species-area relationship (SAR), the scale-dependent species-abundance distribution (SAD), the distribution of masses or metabolic energies of individuals within and across species, the abundance-energy or abundance-mass relationship across species, and the species-level occupancy distributions across space. We propose a theoretical framework for predicting the scaling forms of these and other metrics based on the state-variable concept and an analytical method derived from information theory. In statistical physics, a method of inference based on information entropy results in a complete macro-scale description of classical thermodynamic systems in terms of the state variables volume, temperature, and number of molecules. In analogy, we take the state variables of an ecosystem to be its total area, the total number of species within any specified taxonomic group in that area, the total number of individuals across those species, and the summed metabolic energy rate for all those individuals. In terms solely of ratios of those state variables, and without invoking any specific ecological mechanisms, we show that realistic functional forms for the macroecological metrics listed above are inferred based on information entropy. The Fisher log series SAD emerges naturally from the theory. The SAR is predicted to have negative curvature on a log-log plot, but as the ratio of the number of species to the number of individuals decreases, the SAR becomes better and better approximated by a power law, with the predicted slope z in the range of 0.14-0.20. Using the 3/4 power mass-metabolism scaling relation to relate energy requirements and measured body sizes, the Damuth scaling rule relating mass and abundance is also predicted by the theory. We argue that the predicted forms of the macroecological metrics are in reasonable agreement with the patterns observed from plant census data across habitats and spatial scales. While this is encouraging, given the absence of adjustable fitting parameters in the theory, we further argue that even small discrepancies between data and predictions can help identify ecological mechanisms that influence macroecological patterns.