能够利用植物的功能特征（如叶面积和质量、每株植物的叶子数量及生物质生产的效率等）来在生态系统尺度上预测植物生长和碳通量的能力，在包括生态学、种群生物学和全球变化研究等一系列领域都具有重要意义。Enquist等人建立了一个模型，该模型能够进行这样的预测，为将预测工作从植物特征多样性扩大到生态系统过程提供一个机制基础。
Nature 449, 218-222 (13 September 2007) | doi:10.1038/nature06061; Received 4 June 2007; Accepted 2 July 2007
A general integrative model for scaling plant growth, carbon flux, and functional trait spectra
Brian J. Enquist1,2,3, Andrew J. Kerkhoff1,4, Scott C. Stark1, Nathan G. Swenson1, Megan C. McCarthy1 & Charles A. Price1
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85719, USA
The Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA
Center for Applied Biodiversity, Science Conservation International, 2011 Crystal Drive, Suite 500, Arlington, Virginia 22202, USA
Departments of Biology and Mathematics, Kenyon College, Gambier, Ohio 43022, USA
Correspondence to: Correspondence and requests for materials should be addressed to B.J.E. (Email: benquist@email.arizona.edu).
Linking functional traits to plant growth is critical for scaling attributes of organisms to the dynamics of ecosystems1, 2 and for understanding how selection shapes integrated botanical phenotypes3. However, a general mechanistic theory showing how traits specifically influence carbon and biomass flux within and across plants is needed. Building on foundational work on relative growth rate4, 5, 6, recent work on functional trait spectra7, 8, 9, and metabolic scaling theory10, 11, here we derive a generalized trait-based model of plant growth. In agreement with a wide variety of empirical data, our model uniquely predicts how key functional traits interact to regulate variation in relative growth rate, the allometric growth normalizations for both angiosperms and gymnosperms, and the quantitative form of several functional trait spectra relationships. The model also provides a general quantitative framework to incorporate additional leaf-level trait scaling relationships7, 8 and hence to unite functional trait spectra with theories of relative growth rate, and metabolic scaling. We apply the model to calculate carbon use efficiency. This often ignored trait, which may influence variation in relative growth rate, appears to vary directionally across geographic gradients. Together, our results show how both quantitative plant traits and the geometry of vascular transport networks can be merged into a common scaling theory. Our model provides a framework for predicting not only how traits covary within an integrated allometric phenotype but also how trait variation mechanistically influences plant growth and carbon flux within and across diverse ecosystems.
