Lira-Martins Demetrius, Humphreys-Williams Emma, Strekopytov Stanislav, Ishida Francoise Yoko, Quesada Carlos Alberto, Lloyd Jon
Department of Life Sciences, Imperial College London, Ascot, United Kingdom.
Imaging and Analysis Centre, Natural History Museum, London, United Kingdom.
Front Plant Sci. 2019 Jul 5;10:877. doi: 10.3389/fpls.2019.00877. eCollection 2019.
Bivariate relationships between plant tissue nutrient concentration have largely been studied across broad environmental scales regardless of their covariation with soil and climate. Comparing leaf and branch wood concentrations of C, Ca, K, Mg, N, Na, and P for trees growing in tropical forests in Amazonia and Australia we found that the concentrations of most elements varied with sampling location, but with foliar and branch woody tissues varying from site to site in different ways. Using a Mixed Effect Model (MEM) approach it was further found that relationships between branch and leaf concentrations within individual plots differed in terms of both slope and/or significance to the ordinary least squares (OLS) estimates for most elements. Specifically, using MEM we found that within plots only K and Mg were correlated across organs, but with the K cross-organ intercept estimates varying significantly between sites. MEM analyses further showed that within-plot wood density variations were also negatively related to wood K and Na, suggesting a potentially important role for these cations in water transport and/or storage in woody tissues. The OLS method could not detect significant correlations in any of the above cases. By contrast, although Ca, N, and P leaf and wood tissue concentrations showed similar patterns when individual elements were compared across sites, MEM analyses suggested no consistent association within sites. Thus, for all these three elements, strong within-tree scaling relationships were inferred when data were analyzed across sites using OLS, even though there was no relationship within individual sites. Thus (as for Ca, N, and P) not only can a pooling of data across sites result in trait (co)variations attributable to the environment potentially being incorrectly attributed solely to the species and/or individual (the so-called "ecological fallacy"), but in some cases (as was found here for K and Na) the opposite can also sometimes occur with significant within-site covariations being obscured by large site-site variations. We refer to the latter phenomenon as "environmental obfuscation."
植物组织养分浓度之间的双变量关系在很大程度上是在广泛的环境尺度上进行研究的,而没有考虑它们与土壤和气候的协变关系。通过比较生长在亚马逊和澳大利亚热带森林中的树木叶片和树枝木质部中碳(C)、钙(Ca)、钾(K)、镁(Mg)、氮(N)、钠(Na)和磷(P)的浓度,我们发现大多数元素的浓度随采样地点而变化,但叶片和树枝木质组织在不同地点的变化方式不同。使用混合效应模型(MEM)方法进一步发现,单个样地内树枝和叶片浓度之间的关系在斜率和/或显著性方面与大多数元素的普通最小二乘法(OLS)估计值不同。具体而言,使用MEM我们发现,在样地内只有钾和镁在不同器官之间存在相关性,但钾的跨器官截距估计值在不同地点之间存在显著差异。MEM分析进一步表明,样地内木材密度的变化也与木材中的钾和钠呈负相关,这表明这些阳离子在木质组织中的水分运输和/或储存中可能发挥重要作用。在上述任何情况下,OLS方法都无法检测到显著的相关性。相比之下,尽管当跨地点比较单个元素时,钙、氮和磷的叶片和木材组织浓度呈现出相似的模式,但MEM分析表明在样地内没有一致的关联。因此,对于这三种元素,当使用OLS跨地点分析数据时,推断出树木内部存在很强的尺度关系,尽管在单个样地内没有关系。因此(就像钙、氮和磷的情况一样),不仅跨地点的数据汇总可能导致可归因于环境的性状(共)变异性被错误地仅归因于物种和/或个体(所谓的“生态谬误”),而且在某些情况下(就像这里发现的钾和钠的情况),相反的情况有时也会发生,即显著的样地内协变被大的地点间变异所掩盖。我们将后一种现象称为“环境混淆”。