Improving representation of leaf respiration in large-scale predictive climate-vegetation models
8th New Phytologist Workshop
1–4 July 2013, Australian National University, Canberra and Kioloa, Australia
A meeting report on this workshop, authored by Owen K. Atkin, Patrick Meir and Matthew H. Turnbull, was published in issue 200:3 of New Phytologist and can be read for free here: http://onlinelibrary.wiley.com/doi/10.1111/nph.12686/full.
- To use existing and emerging plant respiration data; to summarise existing knowledge on temporal and spatial variations in leaf respiration, across scales, site to global.
- To establish how these data and their analysis can be used to improve parameterization of plant respiration in global and ecosystem level models.
- To use the understanding gained from the preceding analysis to examine how future experimental work might be conducted to account for genotypic differences and environment-mediated changes in respiration in predictive models
Rationale and scope
Estimates of plant respiration (R) profoundly influence our understanding of ecosystem and Earth system functioning. Each year, R releases 6-8 times as much CO2 into the atmosphere than does the burning of fossil fuels, with half being released by leaves. Small fractional changes in R can thus have large impacts on ecosystem functioning and the scale/magnitude of future global warming. Given this, it is essential that climate-vegetation Earth System Models (ESMs) accurately account for spatial/temporal variations in leaf R. However, at present, variations in leaf R are poorly represented in ESMs leading to substantial uncertainty in future modelled scenarios. There is thus an urgent need to improve representation of in leaf R in predictions of future vegetation-climate scenarios.
Several factors are responsible for the poor representation of R in ESMs. Firstly, until recently, only limited data were available on biogeographical/taxonomic variations in R around the world. However, the emergence of new global sets (both within the TRY plant trait data set and data collected by participants in this proposed workshop) provides an opportunity to assess global variations in R, and in doing so, formulate new algorithms to better account for spatial/temporal/taxonomic variations in leaf R. Secondly, our understanding of how climate-change drivers impact on R was limited; however, quantitative approaches are emerging that will enable dynamic climate responses of R to be incorporated into ESMs over different timescales. Finally, until recently there has been insufficient communication between climate and large-scale ecosystem modellers and empirical biologists; this has constrained improvements in the representation of R in ESMs in recent years and the meeting we propose here will greatly enhance the interaction needed to help advance the relevant models.
Prof. Owen Atkin, Australian National University, Canberra, Australia
Prof. Patrick Meir, Australian National University, Canberra, Australia
Prof. Matthew Turnbull, University of Canterbury, Christchurch, New Zealand
For more information about this workshop please contact the main organiser Owen Atkin or Michael Panagopulos (email@example.com) in the New Phytologist Central Office.