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Predictability and detectability of biogeographic changes in plant distributions Vincent P Gutschick (505-571-2269; vince.gutschick@gmail.com) Global Change Consulting Consortium, 4904 Calabazilla Rd., Las Cruces, NM 88011, United States Rapid climatic changes are envisioned as atmospheric composition is changed by human activities. These changes have long been predicted to drive large-scale changes in the distribution of plants and of all their associated biota. The direct effects of increasing atmospheric CO$_{2}$ on photosynthesis, transpiration, and nutrient dynamics have also been predicted to alter the abundance and density of whole functional groups of plants, particularly those differing in photosynthetic pathways (increases in C$_{3}$ plants at the expense of C$_{4}$s, as one considerable simplification). In recent work, I have pointed out major physiological diversity among individual plant species in their direct responses to elevated CO$_{2}$. The consequences include considerable fragmentation in migration patterns of plant species over decades to centuries. Refining the predictions is a daunting task largely in the areas of physiology, ecology, and evolution. Detecting the changes for validation of predictions and for management/ response strategies is similarly a major challenge. Many changes in plant performance and distribution driven directly by climate and CO$_{2}$ are modest to date, given the modest scale of changes in these two drivers over decadal time scales amenable to both field studies and remote sensing. Large-scale changes, such as in growing season, have occurred but species details have not been resolved in observations with global, repeated coverage. Additional large-scale studies, to merge with small-scale studies, are needed. I review briefly the feasibility of remote-sensing studies for such purposes. For limited campaigns, there is the potential for resolving species by spectral signature, using advance hyperspectral sensing coupled with biophysical models. More general remote-sensing technologies allow detecting shifts between functional types (e.g., grass/woodland) at ecotones, and shifts at all locations in physiological stresses - particularly water stress in its temporal and spatial spectra - directly or via changes in gross primary productivity. |
Meeting: 2007 Fall Meeting Reference Number:6647 Membership Number: Contact Information: Student rate: Willing to chair a session: Meeting Section: Special Session: Index Terms: Theme: Material presented: Contributed Poster presentation requested: Scheduling request: |