Kerkhoff, A.J., W.F. Fagan , J.J. Elser, and B. J. Enquist. 2006. Phylogenetic and growth form variation in the scaling of nitrogen and phosphorus in the seed plants. American Naturalist. 168 (4): E103-E122.

Patterns of plant biomass and nutrient allocation explicitly link the evolved strategies of plant species to the material and energy cycles of ecosystems. The allocation of nitrogen (N) and phosphorus (P) is of particular interest because N and P play pivotal roles in many aspects of plant biology, and their availability frequently limits plant growth and primary productivity. Generalized scaling relationships among plant traits provide important ‘major axes' of functional variation which are useful for understanding plant strategies and the structure of plant communities. Here we present a comparative scaling analysis of a global data compilation detailing the N and P contents of leaves, stems, roots, and reproductive structures of 1,287 species in 152 seed plant families. Within all organs, P and N contents are highly correlated, as has been previously documented in leaves. With one exception, the N and P contents and N:P ratios are also significantly correlated across organs, indicating a high degree of functional integration, though differences exist between woody and herbaceous taxa. The quantitative form of the scaling relationships between plant organs changes systematically, depending on whether the organs considered are primarily structural (i.e., stems, roots) or metabolically active (i.e., leaves, reproductive structures). The combination of significant phylogenetic signals and the maintenance of similar scaling relationships in independently evolving plant lineages implies that both the contingencies of evolutionary history and some degree of environmental convergence have led to a common set of rules that constrain nutrient allocation. By providing more complete knowledge of the partitioning of nutrients among plant organs, our findings can contribute to evolutionary explanations of plant functional diversity, the development of more accurate nutrient budgets from sparse and costly data and a more continuous parameterization of models of ecosystem function.