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TitleIPR 1.0: An efficient method for calculating solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities
AuthorZhang, Y; Chen, W; Li, J
SourceGeoscientific Model Development vol. 7, issue 4, 2014 p. 1357-1376, https://doi.org/10.5194/gmd-7-1357-2014
Year2014
Alt SeriesEarth Sciences Sector, Contribution Series 20100075
PublisherElsevier
Documentserial
Lang.English
Mediapaper; digital; on-line
File formatpdf
Subjectsremote sensing; modelling; climate effects; vegetation; ecosystems; ecology; solar radiation
Illustrationsdiagrams; graphs
ProgramClimate Change Impacts and Adaptation for Key Economic and Natural Environment Sectors, Climate Change Geoscience
AbstractClimate change may alter the spatial distribution, composition, structure and functions of plant communities. Transitional zones between biomes, or ecotones, are particularly sensitive to climate change. Ecotones are usually heterogeneous with sparse trees. The dynamics of ecotones are mainly determined by the growth and competition of individual plants in the communities. Therefore it is necessary to calculate the solar radiation absorbed by individual plants in order to understand and predict their responses to climate change. In this study, we developed an individual plant radiation model, IPR (version 1.0), to calculate solar radiation absorbed by individual plants in sparse heterogeneous woody plant communities. The model is developed based on geometrical optical relationships assuming that crowns of woody plants are rectangular boxes with uniform leaf area density. The model calculates the fractions of sunlit and shaded leaf
classes and the solar radiation absorbed by each class, including direct radiation from the sun, diffuse radiation from the sky, and scattered radiation from the plant community. The solar radiation received on the ground is also calculated. We tested the model by comparing with the results of random distribution of plants. The tests show that the model results are very close to the averages of the random distributions. This model is efficient in computation, and can be included in vegetation models to simulate long-term transient
responses of plant communities to climate change. The code and a user's manual are provided as Supplement of the paper.
GEOSCAN ID285517