Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America

Authors: SMITH, W.K. - University Of Arizona; Biederman, Joel; Scott, Russell - Russ; MOORE, D.J.P. - University Of Arizona; HE, M. - University Of Montana; KIMBALL, J.S. - University Of Montana; YAN, D. - University Of Arizona; HUDSON, A. - University Of Arizona; BARNES, M.L. - University Of Arizona; MACBEAN, N. - University Of Arizona; FOX, A. - University Of Arizona; LITRVAK, M.E. - University Of New Mexico

Submitted to: Geophysical Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/29/2017
Publication Date: 1/4/2018
Citation: Smith, W., Biederman, J.A., Scott, R.L., Moore, D., He, M., Kimball, J., Yan, D., Hudson, A., Barnes, M., MacBean, N., Fox, A., Litrvak, M. 2018. Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America. Geophysical Research Letters. 45(2):748-757. https://doi.org/10.1002/2017GL075922.
DOI: https://doi.org/10.1002/2017GL075922

Interpretive Summary: Satellite images provide valuable information about agroecosystems. The “greenness” of a crop or other vegetation can be used to estimate plant growth. However, the relationship between greenness and growth is weak in rangeland ecosystems for several reasons including: 1) the plants in these semi-arid lands cover less land, making them difficult to detect; 2) dryland plants often maintain a similar greenness even when they are not actively growing, unlike deciduous forests or temperate grasslands. Here we compared traditional greenness data with emerging datasets of solar-induced fluorescence (SIF), which more directly indicates photosynthesis (plant growth). We compared these with carbon uptake measurements, indicators of plant growth, in 21 diverse ecosystems in the Southwest region of North America. We found SIF better captured seasonal and interannual variations, although greenness better captured spatial variations. This work suggests the combination of new and existing technologies will produce superior results.

Technical Abstract: Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under-represented by long-term field measurements. Here we utilize a flux tower data synthesis for southwestern North America in a first assessment of how accurately satellite-derived vegetation proxies capture seasonal to interannual GPP dynamics. We evaluate the Enhanced Vegetation Index (EVI), Solar-Induced Fluorescence (SIF), and the Photochemical Reflectivity Index (PRI). We find that SIF best captures seasonal to interannual dryland GPP dynamics. However, EVI and PRI better capture spatial GPP variability. These results suggest that combinations of these independent vegetation growth proxies could yield synergistic improvements in satellite-based GPP estimates.