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）理论模型为理解与预测生物体形态和功能如何随尺度变化、及其变化的内在机制提供了分析框架。然而，目前仍不清楚针对维管植物的“通用”缩放模型的预测结果，是否能在多变环境中的多样物种间成立。诸如竞争与干扰等现象，可能会使异速生长缩放关系偏离基于最优树木构建的理论预测。本研究采用分层贝叶斯（hierarchical Bayesian）方法，利用取自西非马里一条降雨梯度上3个稀树草原样地的树木与枝级观测数据，计算了多种异速生长关系的树木特异性、物种特异性及“全局”（即种间）缩放指数。我们利用这些缩放指数，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）、几何相似性模型与胁迫相似性模型——开展了严格的检验。针对我们评估的异速生长关系（直径与长度、地上生物量、茎生物量及叶生物量），除长度的缩放指数随树木盖度与密度升高而增大外，其余来自不同环境的物种的实测缩放指数总体上重合度较高。将经验缩放指数与三种模型的理论预测值对比后可知，代谢缩放理论的预测结果与我们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，与预期的干扰与种间竞争权衡效应相契合。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，这是因为其面临逃避免火与优化机械稳定性、内部资源运输之间的进化权衡。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。