Scaling up from traits to communities to ecosystems across broad climate gradients: Testing Metabolic Scaling Theories predictions for forests

Abstract:

Key insights in global ecology will come from mechanistically linking pattern and process across scales. Macrosystems ecology specifically attempts to link ecological processes across spatiotemporal scales. The goal s to link the processing of energy and nutrients from cells all the way ecosystems and to understand how shifting climate influences ecosystem processes. Using new data collected from NSF funded Macrosystems project we report on new findings from forests sites across a broad temperature gradient. Our study sites span tropical, temperate, and high elevation forests we assess several key predictions and assumptions of Metabolic Scaling Theory (MST) as well as several other competing hypotheses for the role of climate, light, and plant traits on influencing forest demography and forest ecosystems. Specifically, we assess the importance of plant size, light limitation, size structure, and various climatic factors on forest growth, demography, and ecosystem functioning. We provide some of the first systematic tests of several key predictions from MST. We show that MST predictions are largely upheld and that new insights from assessing theories predictions yields new observations and findings that help modify and extend MST’s predictions and applicability. We discuss how theory is critically needed to further our understanding of how to scale pattern and process in ecology – from traits to ecosystems – in order to develop a more predictive global change biology.