A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies.

Bibliographic Details
Title: A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies.
Authors: Adrian Mark Tompkins, Luca Caporaso, Riccardo Biondi, Jean Pierre Bell
Source: PLoS ONE, Vol 10, Iss 9, p e0136154 (2015)
Publisher Information: Public Library of Science (PLoS), 2015.
Publication Year: 2015
Collection: LCC:Medicine
LCC:Science
Subject Terms: Medicine, Science
More Details: A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001-2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1932-6203
Relation: http://europepmc.org/articles/PMC4579079?pdf=render; https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0136154
Access URL: https://doaj.org/article/e15ec8e1b3c84d238d5caa989cbe8409
Accession Number: edsdoj.15ec8e1b3c84d238d5caa989cbe8409
Database: Directory of Open Access Journals
More Details
ISSN:19326203
DOI:10.1371/journal.pone.0136154
Published in:PLoS ONE
Language:English