Peng2000

Référence

Peng, C. (2000) From static biogeographical model to dynamic global vegetation model: A global perspective on modelling vegetation dynamics. Ecological Modelling, 135(1):33-54. (Scopus )

Résumé

Predicting the potential effects of future climatic change and human disturbances on natural vegetation distribution requires large-scale biogeographical models. There have been two basic approaches to modelling vegetation response to changing climates: static (time-independent) or dynamic (time-dependent) biogeographical models. This paper reviews and compares two major types of static biogeographical models, climate-vegetation classification and plant functional type models, and the first generation of Dynamic Global Vegetation Models (DGVMs). These models have been widely used to simulate the potential response of vegetation to past and future climate change. Advantage and disadvantage of each type of model are discussed. Global vegetation modelling for investigations of climate change effects has progressed from empirical modelling to process-based equilibrium modelling to the first generation of DGVMs. Some DGVMs are able to capture the responses of potential natural vegetation to climate change with a strong orientation towards population processes. Nevertheless, the uncertainty around the quantitative simulated results indicates that DGVMs are still in the early stages of development. Validating and capturing disturbance-related effects are major challenges facing the developers of the next generation of DGVMs. In future, DGVMs will become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. (C) 2000 Elsevier Science B.V.

Format EndNote

Vous pouvez importer cette référence dans EndNote.

Format BibTeX-CSV

Vous pouvez importer cette référence en format BibTeX-CSV.

Format BibTeX

Vous pouvez copier l'entrée BibTeX de cette référence ci-bas, ou l'importer directement dans un logiciel tel que JabRef .

@ARTICLE { Peng2000,
    AUTHOR = { Peng, C. },
    TITLE = { From static biogeographical model to dynamic global vegetation model: A global perspective on modelling vegetation dynamics },
    JOURNAL = { Ecological Modelling },
    YEAR = { 2000 },
    VOLUME = { 135 },
    PAGES = { 33-54 },
    NUMBER = { 1 },
    ABSTRACT = { Predicting the potential effects of future climatic change and human disturbances on natural vegetation distribution requires large-scale biogeographical models. There have been two basic approaches to modelling vegetation response to changing climates: static (time-independent) or dynamic (time-dependent) biogeographical models. This paper reviews and compares two major types of static biogeographical models, climate-vegetation classification and plant functional type models, and the first generation of Dynamic Global Vegetation Models (DGVMs). These models have been widely used to simulate the potential response of vegetation to past and future climate change. Advantage and disadvantage of each type of model are discussed. Global vegetation modelling for investigations of climate change effects has progressed from empirical modelling to process-based equilibrium modelling to the first generation of DGVMs. Some DGVMs are able to capture the responses of potential natural vegetation to climate change with a strong orientation towards population processes. Nevertheless, the uncertainty around the quantitative simulated results indicates that DGVMs are still in the early stages of development. Validating and capturing disturbance-related effects are major challenges facing the developers of the next generation of DGVMs. In future, DGVMs will become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. (C) 2000 Elsevier Science B.V. },
    COMMENT = { Cited By (since 1996): 40 Export Date: 14 May 2012 Source: Scopus CODEN: ECMOD doi: 10.1016/S0304-3800(00)00348-3 },
    ISSN = { 03043800 (ISSN) },
    KEYWORDS = { Biogeochemistry model, Carbon storage, Climate change, Climate-vegetation classification, Dynamic global vegetation model, Plant functional type model, biogeography, climate change, ecological modeling, global perspective, vegetation dynamics },
    OWNER = { Luc },
    TIMESTAMP = { 2012.05.14 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-0034716037&partnerID=40&md5=463ec24a55039d6bce834dac0c8d15c8 },
}

********************************************************** ***************** Facebook Twitter *********************** **********************************************************

Abonnez-vous à
l'Infolettre du CEF!

********************************************************** ***************** Pub - Mycorhizes_2019 ****************** **********************************************************

********************************************************** ***************** Pub - Symphonies_Boreales ****************** **********************************************************

********************************************************** ***************** Boîte à trucs *************** **********************************************************

CEF-Référence
La référence vedette !

Jérémie Alluard (2016) Les statistiques au moments de la rédaction 

  • Ce document a pour but de guider les étudiants à intégrer de manière appropriée une analyse statistique dans leur rapport de recherche.

Voir les autres...