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LPJ-GUESS Release v4.0.1 model code

Authors: Lindeskog, Mats; Arneth, Almut; Miller, Paul; Nord, Johan; Mischurov, Michael; Olin, Stefan; Schurgers, Guy; +3 Authors

LPJ-GUESS Release v4.0.1 model code

Abstract

The files included here are LPJ-GUESS (Lund Potsdam Jena-General Ecosystem simulator) model code Release 4.0.1: model code, reference documentation, licence, etc (svn revision number 5869), released April 2017. LPJ-GUESS is a process-based dynamic vegetation-terrestrial ecosystem model designed for studies ranging from local to global. Models of this kind are commonly known as dynamic global vegetation models (DGVMs). Given data on climate conditions, atmospheric carbon dioxide concentrations and soil properties, LPJ-GUESS can predict structural, compositional and functional properties of the native ecosystems of major climate zones of the Earth. In the majority of cases, it is recommended to use the latest release of LPJ-GUESS, which includes the most recent developments and bugfixes from the LPJ-GUESS Developer Consortium: see the release notes below. To identify the latest release of LPJ-GUESS among those archived here and connect to the user community for the latest updates, please refer to the LPJ-GUESS website: https://web.nateko.lu.se/lpj-guess/download.html LPJ-GUESS is distributed under the Mozilla Public Licence 2.0. This applies to all versions. The same code package as here was released April 2017 from our server stormbringer.nateko.lu.se (but without the licence file - the licence applies anyway).

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Keywords

Dynamic Global Vegetation Model; DGVM; ecosystem carbon cycle; soil biogeochemistry; vegetation demography; plant functional types

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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