Articles | Volume 14, issue 20
Reviews and syntheses
23 Oct 2017
Reviews and syntheses |  | 23 Oct 2017

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

Deborah A. Clark, Shinichi Asao, Rosie Fisher, Sasha Reed, Peter B. Reich, Michael G. Ryan, Tana E. Wood, and Xiaojuan Yang

Abstract. For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.

Short summary
Improved modeling of tropical-forest carbon cycling is urgently needed to project future climate and to guide global policy for greenhouse gases. Tropical forests store and process immense amounts of carbon, and their carbon cycling may be responding to climate change. Our goal with this paper, a multidisciplinary collaboration between modelers and field ecologists, is to identify reference-level field data from tropical forests that can be used to guide the models for these key ecosystems.
Final-revised paper