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Titel |
Modelling grassland phenology and growth using near-surface remote sensing derived time series |
VerfasserIn |
Koen Hufkens, Min Chen, Andrew D. Richardson |
Konferenz |
EGU General Assembly 2014
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 16 (2014) |
Datensatznummer |
250098920
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Publikation (Nr.) |
EGU/EGU2014-14642.pdf |
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Zusammenfassung |
Both the size and the duration of rain events have a significant influence on the phenology
and growth of grasslands. This pulse-response nature of grasslands makes quantifying intra
and inter-annual variability in grassland growth challenging and large uncertainties remain on
which precipitation characteristics have the greatest influence on grassland phenology, growth
and ecosystem productivity.
Here we present modeled results of soil water content and grassland growth on a
daily timestep from 16 grassland sites (40 site years) across arid, temperate and
tropical biomes. We build upon a simple threshold-delay concept with provisions
for influences of soil temperature and photoperiod on plant growth. Modelled soil
water content and grassland growth are based upon limited set of widely available
climatic drivers such as daily precipitation, minimum and maximum temperature, to
facilitate scaling, and validated against near-surface remote sensing (PhenoCam)
data of vegetation greenness. This simple model framework allows us to explore
future effects of changes in the size and duration of precipitation events as well
as temperature on grassland phenology and growth across different biome types. |
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