Data from: Allometric convergence in savanna trees and implications for plant scaling models in variable ecosystems

Theoretical models of allometric scaling provide frameworks for understanding and predicting how and why the morphology and function of organisms vary with scale. It remains unclear, however, if the predictions of ‘universal’ scaling models for vascular plants hold across diverse species in variable environments. Phenomena such as competition and disturbance may drive allometric scaling relationships away from theoretical predictions based on an optimized tree. Here, we use a hierarchical Bayesian approach to calculate tree-specific, species-specific, and ‘global’ (i.e. interspecific) scaling exponents for several allometric relationships using tree- and branch-level data harvested from three savanna sites across a rainfall gradient in Mali, West Africa. We use these exponents to provide a rigorous test of three plant scaling models (Metabolic Scaling Theory (MST), Geometric Similarity, and Stress Similarity) in savanna systems. For the allometric relationships we evaluated (diameter vs. length, aboveground mass, stem mass, and leaf mass) the empirically calculated exponents broadly overlapped among species from diverse environments, except for the scaling exponents for length, which increased with tree cover and density. When we compare empirical scaling exponents to the theoretical predictions from the three models we find MST predictions are most consistent with our observed allometries. In those situations where observations are inconsistent with MST we find that departure from theory corresponds with expected tradeoffs related to disturbance and competitive interactions. We hypothesize savanna trees have greater length-scaling exponents than predicted by MST due to an evolutionary tradeoff between fire escape and optimization of mechanical stability and internal resource transport. Future research on the drivers of systematic allometric variation could reconcile the differences between observed scaling relationships in variable ecosystems and those predicted by ideal models such as MST.

异速生长缩放（allometric scaling）的理论模型为理解和预测生物体的形态与功能如何随尺度变化、以及为何随尺度变化提供了分析框架。然而，针对维管植物的“通用”缩放模型预测，是否适用于多变环境中的多样物种，目前仍不明确。竞争、干扰等现象可能会让异速生长缩放关系偏离基于优化树木的理论预测。本研究采用分层贝叶斯（hierarchical Bayesian）方法，利用从西非马里降雨梯度上3个稀树草原样地采集的树木和枝条水平数据，计算了多种异速生长关系的树木专属、物种专属以及“全局”（即种间）缩放指数。我们借助这些缩放指数，对稀树草原系统中的3种植物缩放模型——代谢缩放理论（Metabolic Scaling Theory, MST）、几何相似性（Geometric Similarity）和应力相似性（Stress Similarity）——开展了严格检验。针对本次评估的异速生长关系（直径与长度、地上生物量、茎生物量以及叶生物量），除长度缩放指数随树木盖度和密度升高而增大外，不同环境下物种的经验计算缩放指数整体较为相近。将经验缩放指数与上述3种模型的理论预测值对比后，我们发现代谢缩放理论的预测结果与观测到的异速生长关系最为契合。在观测结果与代谢缩放理论不符的场景中，我们发现与理论的偏离对应着与干扰和种间竞争相互作用相关的预期权衡。我们提出假说：稀树草原树木的长度缩放指数高于代谢缩放理论的预测值，这源于树木在躲避火灾与优化机械稳定性、内部资源运输之间存在进化权衡。未来针对系统性异速生长变异驱动因子的研究，或可调和多变生态系统中观测到的缩放关系与代谢缩放理论等理想模型的预测结果之间的差异。