95th ESA Annual Meeting (August 1 -- 6, 2010)

COS 47-10 - Quantifying the precipitation "memory" of plant photosynthesis in deserts

Wednesday, August 4, 2010: 11:10 AM
329, David L Lawrence Convention Center
Lisa Patrick Bentley, Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, Kiona Ogle, School of Life Sciences, Arizona State University, Tempe, AZ, Jessica M. Cable, International Arctic Research Center, University of Alaska, Fairbanks, AK, Greg A. Barron-Gafford, School of Geography & Development; B2 Earthscience / Biosphere 2, University of Arizona, Tucson, AZ, Travis E. Huxman, Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA, Michael Loik, Environmental Studies, University of California, Santa Cruz, CA, Stanley D. Smith, School of Life Sciences, University of Nevada, Las Vegas, Las Vegas, NV and David T. Tissue, Hawkesbury Institute for the Environment, University of Western Sydney, Richmond NSW, Australia
Background/Question/Methods

The timing and magnitude of seasonal precipitation impacts the photosynthetic responses of plants in the major deserts of the United States (Great Basin, Mojave, Sonoran, and Chihuahuan). While many studies have examined the short-term impacts of altered precipitation regimes on plant physiological responses, much is unknown about the longer-term effects of antecedent environmental conditions on plant carbon gain. As such, our objectives are: (1) to explore the effects of longer-term (5-10 years) altered seasonal precipitation on plant photosynthetic responses to CO2 and light, and (2) to develop a “memory” model that explicitly determines the role of and temporal scale of antecedent (past) environmental factors on current photosynthesis. We address these objectives using a time series of environmental data and plant photosynthesis measurements from seven plant species (C3 shrubs and C4 grasses) across four deserts. We estimate maximum carboxylation efficiency (Vcmax) and maximum rate of electron transport (Jmax) using semi-mechanistic models of photosynthesis placed within a hierarchical Bayesian (HB) framework. In these models, estimates of Vcmax and Jmax are explicitly linked to an antecedent effect. That is, we coupled photosynthesis and memory models to explicitly determine antecedent effects and associated time-scale (or memory) of temperature and precipitation on photosynthesis parameters. 
Results/Conclusions

Using the HB approach to fitting photosynthesis response curves, we found a significant memory effect on photosynthesis parameters. Indeed, increased summer precipitation in the past significantly increased current Vcmax and Jmax in both C3 and C4 plants. Responses were species-specific, and most likely related to plant rooting distribution and phenology, rather than desert location. Increased leaf water potential, photosynthesis, and electron transport efficiency in plants that historically received supplemental water in the Great Basin corroborated changes in biochemical parameters in response to historical watering events. Results from the coupled photosynthesis-memory model identified species- and variable-specific differences in memory effects. For example, only precipitation had a memory effect on photosynthesis of shrubs, while both precipitation and temperature had significant memory effects on photosynthesis of grasses. Also, the precipitation regime over the previous 1-2 days affected current photosynthesis in grasses, but precipitation over the past month affected current photosynthesis in shrubs. These leaf-level responses indicate the importance of understanding and quantifying antecedent conditions when attempting to disentangle the role of environmental factors controlling ecosystem carbon and water fluxes in desert ecosystems.