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Of the latter, six are dynamic vegetation models.
Bias in precipitation patterns is critical with coupling to terrestrial vegetation models.
Foliage or vegetation models estimate the path loss due to propagation though trees and foliage [36].
In the literature one can find descriptions of established vegetation models for use on different scales [8 11].
Vegetation models are increasingly used for assessing impacts of a changing environment on landscapes.
Therefore, improved temperature estimates also improved the explanatory performance of vegetation models.
Supporting these observations are studies of continuum vegetation models that have reproduced many of the observed patterns.
Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems.
The authors claim that dynamic vegetation models offer a means to simulate annual primary productivity, which gives insight to the vegetation patterns.
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"The paper shows that current climate-vegetation models are not able to reproduce the observed legacy effects and are therefore underestimating the effects of drought on vegetation and carbon cycling". .
Mapping the outcome of the complex interplay of these processes has become possible due to the development of Dynamic Global Vegetation Models (DGVMs) [6], which simulate the terrestrial balances of carbon and water as well as the temporal development of vegetation in response to changing climate.
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