Integrating modeling and empirical approaches to improve predictions of tropical forest responses to global warming

Tropical forests contain > 50% of the world’s known species (Heywood 1995), 55% of global forest biomass (Pan et al. 2011), and exchange more carbon (C), water and energy with the atmosphere than any other ecosystem type (e.g., Saugier et al. 2001). Despite their importance, there is more uncertainty associated with predictions of how tropical forests will respond to warming than for any other biome (Randerson et al. 2009). This uncertainty is of global concern due to the large quantity of C cycled by these forests and the high potential for biodiversity loss. Given the importance of tropical forests, decision makers and land managers around the globe need increased predictive capacity regarding how tropical forests will respond to climatic change.

Here we propose a set of workshops designed to bring together modelers and empiricists to evaluate and compare predictions of tropical forest response to increased temperature at a variety of temporal and spatial scales. First, we will model and critically evaluate the responses of a range of tropical forest sites to increased temperature using a selection of models that operate at multiple scales and specialize in different processes. Results will greatly help constrain expected tropical forest responses and will be used to generate hypotheses for a future tropical forest warming experiment in Puerto Rico. Second, we will develop strategies and proposals with the goal of linking three finer-scale models to a larger, global-scale model in order to improve the predictive capacity of the global-scale model. Instead of collecting new data or focusing on a single model, these workshops will build upon current knowledge to amass existing datasets and take advantage of a suite of models. Exceptional scientists in the appropriate fields have agreed to participate in these meetings. The Powell Center is the perfect venue for this endeavor due to its focus on facilitating data synthesis and cross-disciplinary scientific communication. The US Forest Service and INTERFACE (a NSF Research Coordination Network) also strongly support the meetings.







Publication(s):

Cavaleri, M.A., Coble, A.P., Ryan, M.G., Bauerle, W.L., Loescher, H.W., and Oberbauer, S.F.. (2017). “Tropical Rainforest Carbon Sink Declines during El Niño as a Result of Reduced Photosynthesis and Increased Respiration Rates.” New Phytologist, August. doi:10.1111/nph.14724.



Cavaleri, M. A., Reed, S. C., Smith, W. K. and Wood, T. E. (2015), Urgent need for warming experiments in tropical forests. Glob Change Biol, 21: 2111-2121. doi:10.1111/gcb.12860



Clark, D. A., Asao, S., Fisher, R., Reed, S., Reich, P. B., Ryan, M. G., Wood, T. E., and Yang, X. (2017). Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests, Biogeosciences, 14, 4663-4690, doi:10.5194/bg-14-4663-2017.



Donovan, J. (2015) Will Climate Change Hurt Tropical Rainforests? Scientists Study the Effects of Warming on Puerto Rican Forest. Michigan Tech.



Feng, X., Uriarte, M., González, G., Reed, S., Thompson, J., Zimmerman, J.K., and Murphy, L. Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling. Glob Change Biol. 2017;00:1-20. doi:10.1111/gcb.13863



Reed, S.C., Yang, X., and Thornton, P.E., (2015). Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor. New Phytologist. 208:(2)324-329 doi: 10.1111/nph.13521.