Improving representation of leaf respiration in large-scale predictive climate-vegetation models.

Estimates of plant respiration (R ) profoundly influence our understanding of ecosystem and Earth system functioning. Each year, R releases six to eight times more CO2 into the atmosphere than does the burning of fossil fuels (Canadell et al., 2007; Le Quere et al., 2009), with half being released by leaves (Atkin et al., 2007). Small fractional changes in leaf R can thus have large impacts on ecosystem functioning (Piao et al., 2010) and the magnitude of future atmospheric CO2 concentrations and related climate change (Cox et al., 2000; Huntingford et al., 2013). Given this, it is essential that Earth system models (ESMs) accurately account for spatial and temporal variations in leaf R (King et al., 2006; Wythers et al., 2013). However, at present, variations in leaf R are poorly represented in ESMs and this has led to substantial uncertainty in future modelled scenarios (Atkin et al., 2008; Leuzinger & Thomas, 2011). Thus, there is an urgent need to improve representation of leaf R in predictions of future vegetation–climate scenarios (Atkin et al., 2010), including in models that seek to predict the terrestrial carbon–nitrogen (C–N) cycle in a future, high-CO2 world (Zaehle et al., 2014; this issue of New Phytologist pp. 803–822). Several factors are responsible for the poor representation of R in ESMs. First, until recently, only limited data were available describing biogeographically and taxonomically related variations in leaf R around the world (Wright et al., 2006). Second, our understanding of how climate-change drivers impact R remains limited (Kruse et al., 2011; Searle et al., 2011; Huntingford et al., 2013; Kornfeld et al., 2013), although quantitative approaches are now emerging that will enable dynamic climate responses ofR to be incorporated into ESMs over different timescales (King et al., 2006; Atkin et al., 2008; Smith & Dukes, 2013; Wythers et al., 2013). Finally, there has been insufficient communication between climate and large-scale ecosystem modellers and empirical biologists (Leuzinger & Thomas, 2011; Atkin, 2013); this has constrained improvements in the representation of leaf R in ESMs in recent years. In May 2010, the 24 New Phytologist Symposium (Plant respiration and climate change: scaling frommitochondria to the globe) was held at the University of Oxford (UK; Atkin et al., 2010); this was followed by a Virtual Special Issue on Plant respiration in 2011 (Atkin, 2011). The symposium led to the establishment of several new collaborations among modellers and empirical biologists, and the coordination of field campaigns to expand data sets quantifying global variations in leaf R. When combined with the TRY global plant trait data set (Kattge et al., 2011), these newly collected data provide an opportunity to assess global variations in R, and, in doing so, to formulate new algorithms to better account for spatial/ temporal/taxonomic variations in leaf R. Taking advantage of this opportunity, however, required that ecosystem modellers and empirical biologists come together to discuss how to improve representation of leaf R in ecosystem and global vegetation–climate models. It was in this context that the 8 New Phytologist Workshop, ‘Improving representation of leaf respiration in largescale predictive climate–vegetation models’, was held at the Australian National University (ANU) on 1–4 July 2013.