HR: 17:45h
AN: B44A-07 [Abstracts]
TI: A generalized, bioclimatic index to predict foliar phenology in response to climate
AU: * Jolly, W M
EM: mattj@ntsg.umt.edu
AF: NTSG, College of Forestry and Conservation, SC428
Univ. of Montana, Missoula, MT 59812
United States
AU: Nemani, R R
EM: ramakrishna.r.nemani@nasa.gov
AF: NASA Ames Research Center, Mail Stop: 242-4
Ecosystem Science & Technology, Moffett Field, CA 94035
United States
AU: Running, S W
EM: swr@ntsg.umt.edu
AF: NTSG, College of Forestry and Conservation, SC428
Univ. of Montana, Missoula, MT 59812
United States
AB:
The phenological state of vegetation significantly affects exchanges of heat, mass, and momentum between the Earth's surface
and the atmosphere. Although current patterns can be estimated from satellites, we lack the ability to predict future trends
in response to climate change. We searched the literature for a common set of variables that might be combined into an index
to quantify the greenness of vegetation throughout the year. We selected as variables: daylength (photoperiod), evaporative
demand (vapor pressure deficit), and suboptimal (minimum) temperatures. For each variable we set threshold limits, within
which the relative phenological performance of the vegetation was assumed to vary from inactive (0) to unconstrained (1). A
combined Growing Season Index (GSI) was derived as the product of the three indices. Ten-day mean GSI values for nine widely
dispersed ecosystems showed good agreement (r $>$ 0.8) with the satellite-derived Normalized Difference Vegetation Index
(NDVI). We also tested the model at a temperate deciduous forest by comparing model estimates to average field observations
of leaf flush and leaf coloration. The mean absolute error of predictions at this site was 3 days for average leaf flush
dates and 2 days for leaf coloration dates. Finally, we used this model to produce a global map that distinguishes major
differences in regional phenological controls. The model appears sufficiently robust to reconstruct historical variation as
well as to forecast future phenological responses to changing climatic conditions.
DE: 3322 Land/atmosphere interactions
DE: 1630 Impact phenomena
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting