AUTHOR=Lira-Martins Demetrius , Humphreys-Williams Emma , Strekopytov Stanislav , Ishida Francoise Yoko , Quesada Carlos Alberto , Lloyd Jon TITLE=Tropical Tree Branch-Leaf Nutrient Scaling Relationships Vary With Sampling Location JOURNAL=Frontiers in Plant Science VOLUME=Volume 10 - 2019 YEAR=2019 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2019.00877 DOI=10.3389/fpls.2019.00877 ISSN=1664-462X ABSTRACT=Comparing leaf and 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 soils and/or climate: but with the patterns of concentration variation within the two tissues occurring in non-consistent ways. Using a Mixed Effect Model (MEM) approach it was further found that relationships between wood 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 are correlated across organs, but with the K cross-organ intercept estimates varying significantly between sites. This within plot correlation was not detected using OLS and with the difference between statistical approaches attributed to higher K within wood (but not leaves) in response to increased precipitation seasonality. MEM analyses further showed that within-plot wood density variations were also negatively related to wood K and Na, and with precipitation seasonality again implicated: this again pointing to an important role for these cations in water transport and/or storage in woody tissues. As for potassium, these associations were not detectable using OLS. 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. Nevertheless, for all these three elements, strong within-tree scaling relationships were inferred when data were analysed using OLS. Thus (as for Ca, N and P) not only can a naïve pooling of data across sites result in trait (co)variations attributable to the environment ending up being incorrectly attributed solely to the species and/or individual (the so-called ‘ecological fallacy), but (as was found here for K and Na) also the opposite can sometimes occur, a phenomenon we refer to here as “environmental obfuscation”.