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."

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