From meta-studies to modeling : using synthesis knowledge to build broadly applicable process-based land change models
Nicholas R. Magliocca
(1)
,
Jasper van Vliet
(2)
,
Calum Brown
(3)
,
Tom P. Evans
(4)
,
Thomas Houet
(5)
,
Peter Messerli
(6)
,
Joseph P. Messina
(7)
,
Kimberly Nicholas
(8)
,
Christine Ornetsmuller
(2)
,
Julian Sagebiel
(9)
,
Vanessa Schweizer
(10)
,
Peter Verburg
(11)
,
Qiangyi Yu
(12)
1
SESYNC
2 Institute for Environmental Studies
3 School of Geosciences [Edinburgh]
4 Indiana University [Bloomington]
5 GEODE - Géographie de l'environnement
6 CDE - Centre for Development and Environment [Bern]
7 Michigan State University [East Lansing]
8 LUCSUS - Lund University Centre for Sustainability Studies
9 Institute for Ecological Economy Reserach
10 University of Waterloo [Waterloo]
11 Department of Environmental Sciences - Land Dynamics Group
12 Institute of Agricultural Resources and regional Planning
2 Institute for Environmental Studies
3 School of Geosciences [Edinburgh]
4 Indiana University [Bloomington]
5 GEODE - Géographie de l'environnement
6 CDE - Centre for Development and Environment [Bern]
7 Michigan State University [East Lansing]
8 LUCSUS - Lund University Centre for Sustainability Studies
9 Institute for Ecological Economy Reserach
10 University of Waterloo [Waterloo]
11 Department of Environmental Sciences - Land Dynamics Group
12 Institute of Agricultural Resources and regional Planning
Thomas Houet
- Fonction : Auteur
- PersonId : 9663
- IdHAL : thomas-houet
- ORCID : 0000-0001-5890-6145
- IdRef : 104518642
Résumé
This paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitative
data needed to derive agent behaviors more readily than from case study or aggregate data sources alone. Recent land change synthesis studies provide sufficient topical breadth and depth to support the development of broadly applicable process-based LCMs, as well as the potential to accelerate the production of generalized knowledge through model-driven synthesis.
Format du dépôt | Fichier |
---|---|
Type de dépôt | Article dans une revue |
Titre |
en
From meta-studies to modeling : using synthesis knowledge to build broadly applicable process-based land change models
|
Résumé |
en
This paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitative
data needed to derive agent behaviors more readily than from case study or aggregate data sources alone. Recent land change synthesis studies provide sufficient topical breadth and depth to support the development of broadly applicable process-based LCMs, as well as the potential to accelerate the production of generalized knowledge through model-driven synthesis.
|
Auteur(s) |
Nicholas R. Magliocca
1
, Jasper van Vliet
2
, Calum Brown
3
, Tom P. Evans
4
, Thomas Houet
5
, Peter Messerli
6
, Joseph P. Messina
7
, Kimberly Nicholas
8
, Christine Ornetsmuller
2
, Julian Sagebiel
9
, Vanessa Schweizer
10
, Peter Verburg
11
, Qiangyi Yu
12
1
SESYNC
( 431001 )
- University of Mariland
1 Park Place
Annapolis
MD21401 USA
- États-Unis
2
Institute for Environmental Studies
( 248169 )
- Pays-Bas
3
School of Geosciences [Edinburgh]
( 258673 )
- The King's Buildings, James Hutton Road, Edinburgh EH9 3FE
- Royaume-Uni
4
Indiana University [Bloomington]
( 300689 )
- 107 S. Indiana Avenue, Bloomington, IN 47405-7000
- États-Unis
5
GEODE -
Géographie de l'environnement
( 742 )
- 5 Allée Antonio Machado 31058 TOULOUSE CEDEX 1
- France
6
CDE -
Centre for Development and Environment [Bern]
( 425953 )
- Mittelstrasse 43, 3012 Bern
- Suisse
7
Michigan State University [East Lansing]
( 235550 )
- 220 Trowbridge Rd
East Lansing, MI 48824
- États-Unis
8
LUCSUS -
Lund University Centre for Sustainability Studies
( 431004 )
- Box 170, Lund University
SE 221 00 Lund
Suède
- Suède
9
Institute for Ecological Economy Reserach
( 431005 )
- Potsdamer street 105
10785 BERLIN
ALLEMAGNE
- Allemagne
10
University of Waterloo [Waterloo]
( 301081 )
- 200 University Avenue West, Waterloo, ON, Canada N2L 3G1
- Canada
11
Department of Environmental Sciences - Land Dynamics Group
( 110792 )
- Wageningen University, PO Box 47, 6700 AA Wageningen, The Netherlands
- Pays-Bas
12
Institute of Agricultural Resources and regional Planning
( 431007 )
- Chinese Academy of Agricultural Sciences
12 Zhongguancun South Street
Beijing 100081
CHINE
- Chine
|
URL éditeur |
http://www.sciencedirect.com/science/article/pii/S1364815215001723
|
Langue du document |
Anglais
|
Nom de la revue |
|
Vulgarisation |
Non
|
Comité de lecture |
Oui
|
Audience |
Internationale
|
Volume |
72
|
Date de publication |
2015
|
Page/Identifiant |
10-20
|
Domaine(s) |
|
Mots-clés |
en
Land use change, model development, meta-analysis, synthesis, model validation, agent-based models
|
DOI | 10.1016/j.envsoft.2015.06.009 |
Origine :
Accord explicite pour ce dépôt
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