Project Funding: 2011 - 2014

NRA: 2009 NASA: The Science of Terra and Aqua   

Funded by NASA

Abstract:
A fundamental unanswered question for global ecology is the vulnerability of tropical forests to climate change, up to and including widespread Amazon forest collapse and conversion to savanna due to global warming-induced drought, a projection of some coupled carbon/climate models. Remote sensing methods, by observing broadscale vegetation responses to climatic variability, offer potentially powerful insight into this question on observable timescales. For example, recent studies using MODIS products have detected positive vegetation responses to seasonal drying and interannual drought. Such observations are somewhat controversial, but if accurate, indicate that tropical vegetation is more complex, and possibly more robust, than ecosystem models suggest, with implications for vulnerability to climate change. TECHNICAL CHALLENGE: However, multiple satellite products collected from the AVHRR and MODIS platforms show different, inconsistent seasonal and interannual patterns over Amazon rainforests with some sensor products showing canopy drying and negative forest responses to dry periods. Some argue that the observed positive responses are an artifact of aerosol contamination and that satellite studies cannot differentiate vegetation responses to drought events. Plot-based studies report increased tree mortality during the 2005 Amazon drought suggesting a possible inconsistency between ground plots (showing long-term mortality) and remote sensing (showing short-term green-up or an absence of browning), though it might be that the two observations are reconcilable once the different timescales are taken into account. In any case, more fully validated observations are needed to build confidence in remotely sensed ecosystem function before community acceptance of observed results, and to realize the full potential of the  present and future array of space-based spectral sensors, including the Terra- and Aqua- MODIS sensors. OBJECTIVES AND METHODS: We propose a study to investigate the mechanisms underlying the divergent responses to the 2005 Amazonian drought, and to decisively test competing hypotheses about mechanisms underlying green-up forest during dry periods (including, increased light use efficiency under aerosol-induced increases in diffuse radiation, evolutionarily prescribed leaf-flush phenology, and the null hypothesis of contamination artifacts). We propose four components. FIRST, we will compare independent measures of the seasonality of: (1) vegetation photosynthetic capacity at both leaf and ecosystem scales, (2) atmospheric characteristics (aerosol optical depth and cloud cover), (3) surface radiation components (direct and diffuse radiation), and (4) vegetation reflectances and indices derived from satellites and from in-situ AERONET sunphotometers, at four sites across the Amazon which span a range of tropical ecosystems and seasonal atmospheric aerosol characteristics. SECOND, we will use spectral observations at both the tower-level and from space to diagnose key physiological processes and further test the accuracy and interpretation of coarse- resolution MODIS products. THIRD, we will use the first airborne LIDAR dataset obtained for the Brazilian Amazon to parameterize a sophisticated 3-D canopy photosynthesis model (FLiES) to scale up our integrated understanding of vegetation characteristics (including phenology of leaf spectral reflectance) and radiation components (aerosol-, cloud-, and subcanopy- influence effects of diffuse radiation fraction). FOURTH, we will conduct a more detailed re-analyses of forest response to the 2005 Amazon drought.

Publications:

Wu, J., Albert, L. P., Lopes, A. P., Restrepo-Coupe, N., Hayek, M., Wiedemann, K. T., Guan, K., Stark, S. C., Christoffersen, B., Prohaska, N., Tavares, J. V., Marostica, S., Kobayashi, H., Ferreira, M. L., Campos, K. S., da Silva, R., Brando, P. M., Dye, D. G., Huxman, T. E., Huete, A. R., Nelson, B. W., Saleska, S. R. 2016. Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests. Science. 351(6276), 972-976. DOI: 10.1126/science.aad5068

Wu, J., Chavana-Bryant, C., Prohaska, N., Serbin, S. P., Guan, K., Albert, L. P., Yang, X., Leeuwen, W. J. D., Garnello, A. J., Martins, G., Malhi, Y., Gerard, F., Oliviera, R. C., Saleska, S. R. 2016. Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests. New Phytologist. 214(3), 1033-1048. DOI: 10.1111/nph.14051

Wu, J., Guan, K., Hayek, M., Restrepo-Coupe, N., Wiedemann, K. T., Xu, X., Wehr, R., Christoffersen, B. O., Miao, G., Silva, R., Araujo, A. C., Oliviera, R. C., Camargo, P. B., Monson, R. K., Huete, A. R., Saleska, S. R. 2016. Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales. Global Change Biology. 23(3), 1240-1257. DOI: 10.1111/gcb.13509

Wu, J., Kobayashi, H., Stark, S. C., Meng, R., Guan, K., Tran, N. N., Gao, S., Yang, W., Restrepo-Coupe, N., Miura, T., Oliviera, R. C., Rogers, A., Dye, D. G., Nelson, B. W., Serbin, S. P., Huete, A. R., Saleska, S. R. 2017. Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. New Phytologist. 217(4), 1507-1520. DOI: 10.1111/nph.14939

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile