Marine Ecosystems Research Department - jamstec japan agency ...
Marine Ecosystems Research Department - jamstec japan agency ...
Marine Ecosystems Research Department - jamstec japan agency ...
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Japan <strong>Marine</strong> Science and Technology Center<br />
Frontier <strong>Research</strong> System for Global Change<br />
effects on lower branch shedding besides conventionally<br />
known shortage of light source (figure ).<br />
In addition, we launched research on dynamic global<br />
vegetation models (DGVM), which will play a critical<br />
role in constructing ecosystem models in the future.<br />
c. Ecosystem Geographical Distribution Model Group<br />
The objectives of Ecosystem Geographical<br />
Distribution Model (EGDM) Group are remotely sensed<br />
satellite observations to monitor and model terrestrial<br />
ecosystems and their relation to environmental and climate<br />
variability. We focused on the effects of snow<br />
cover on vegetation dynamics in Northern Hemisphere<br />
land areas and satellite-based photosynthetically active<br />
radiation (PAR) and its role in terrestrial primary production<br />
and ecosystem-atmosphere carbon exchange.<br />
In FY , we used -year satellite observations of<br />
snow cover, vegetation greenness (measured by the<br />
normalized difference vegetation index, NDVI), and air<br />
temperature data for North Eurasian land areas to<br />
examine the spatial and temporal patterns in the relation<br />
between snow cover, climate, and vegetation growth<br />
(Figure ). Since reliable data on the global distribution<br />
and temporal variability of PAR are essential to<br />
accurate modeling of the terrestrial carbon cycle, we<br />
applied PAR data obtained from a tropical site in northcentral<br />
Thailand into a two-leaf (sun-shade) model of<br />
forest canopy photosynthesis. The results show that<br />
daily net canopy photosynthesis increases with increasing<br />
diffuse fraction (DF) (when the total available PAR<br />
becomes a limiting factor). These results reinforce past<br />
studies that have relied on modeled or empirical estimates<br />
of PAR. This research contributes to improving<br />
latitude<br />
70<br />
65<br />
60<br />
55<br />
50<br />
a<br />
50 100 150 200 250 300 350<br />
day of year<br />
latitude<br />
70<br />
65<br />
60<br />
55<br />
50<br />
b<br />
-0.02 -0.01 0.00 0.01 0.02<br />
ZFSF (linear trend, fraction/yr)<br />
50 100 150 200 250 300 350<br />
day of year<br />
latitude<br />
70<br />
65<br />
60<br />
55<br />
50<br />
c<br />
0.000 0.002 0.004 0.006 0.008<br />
ZNDN (linear trend, fraction/year)<br />
50 100 150 200 250 300 350<br />
day of year<br />
-0.20 -0.10 0.00 0.10 0.20<br />
ZT (linear trend, deg. C/yr)<br />
Fig.15 View of 54-year-old stand of subalpine fir forest, simulated<br />
by PipeTree.<br />
Fig.16 Linear trends (1982-1999) in (a) zonal snow-cover (ZFSF), (b)<br />
normalized NDVI (ZNDN), and (c) air temperature (ZT). For<br />
ZNDN and ZT, only active growing season values are displayed<br />
(days in which the 18-year mean ZT > 0 degrees C).<br />
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