eprintid: 10208
rev_number: 14
eprint_status: archive
userid: 1305
dir: disk0/00/01/02/08
datestamp: 2017-10-13 03:40:57
lastmod: 2017-10-13 03:45:20
status_changed: 2017-10-13 03:40:57
type: article
metadata_visibility: show
contact_email: Library-ICRISAT@CGIAR.ORG
creators_name: Schmitt Olabisi, L
creators_name: Liverpool-Tasie, S
creators_name: Rivers, L
creators_name: Ligmann-Zielinska, A
creators_name: Du, J
creators_name: Denny, R
creators_name: Marquart-Pyatt, S
creators_name: Sidibe, A
icrisatcreators_name: Sidibe, A
affiliation: Department of Community Sustainability, Michigan State University (East Lansing)
affiliation: Department of Agricultural, Food and Resource Economics, Morrill Hall of Agriculture, Michigan State University (East Lansing)
affiliation: Department of Forestry and Environmental Resources, North Carolina State University (Raleigh)
affiliation: Geography Department, Michigan State University (East Lansing)
affiliation: Department of Construction Science, Texas A & M University College Station (Texas)
affiliation: Department of Sociology, Michigan State University (East Lansing)
affiliation: ICRISAT (Bamako)
affiliation: Institut Polytechnique Rural de Formation et de Recherche Appliquée de Katibougou (Koulikoro)
country: USA
country: Mali
title: Using participatory modeling processes to identify sources of climate risk in West Africa
ispublished: pub
subjects: CL1
subjects: P11
subjects: s2.8
subjects: s26
subjects: s28
subjects: s4009
divisions: CRPS1
full_text_status: restricted
keywords: Participatory modeling, Food security, West Africa, System dynamics, Scenarios, Climate risk, Agricultural systems, Scenario planning, Participatory modeling process
note: This study was funded by the National Science
Foundation Directorate for Social, Behavioral and Economic
Sciences (Grant No. 1416730), the USAID/Nigeria funded Food
Security Policy Innovation Lab Associate Award, contract number
AID1-620-LA-15-00001, and the Adaptation at Scale in Semi-Arid
Regions program.
abstract: Participatory modeling has been widely recognized in recent years as a powerful tool for dealing with risk and uncertainty. By incorporating multiple perspectives into the structure of a model, we hypothesize that sources of risk can be identified and analyzed more comprehensively compared to traditional ‘expert-driven’ models. However, one of the weaknesses of a participatory modeling process is that it is typically not feasible to involve more than a few dozen people in model creation, and valuable perspectives on sources of risk may therefore be absent. We sought to address this weakness by conducting parallel participatory modeling processes in three countries in West Africa with similar climates and smallholder agricultural systems, but widely differing political and cultural contexts. Stakeholders involved in the agricultural sector in Ghana, Mali, and Nigeria participated in either a scenario planning process or a causal loop diagramming process, in which they were asked about drivers of agricultural productivity and food security, and sources of risk, including climate risk, between the present and mid-century (2035–2050). Participants in all three workshops identified both direct and indirect sources of climate risk, as they interact with other critical drivers of agricultural systems change, such as water availability, political investment in agriculture, and land availability. We conclude that participatory systems methods are a valuable addition to the suite of methodologies for analyzing climate risk and that scientists and policy-makers would do well to consider dynamic interactions between drivers of risk when assessing the resilience of agricultural systems to climate change.
date: 2017-10
date_type: published
publication: Environment Systems and Decisions
publisher: Springer
pagerange: 1-10
id_number: 10.1007/s10669-017-9653-6
refereed: TRUE
issn: 2194-5403
official_url: http://dx.doi.org/10.1007/s10669-017-9653-6
related_url_url: https://scholar.google.co.in/scholar?hl=en&as_sdt=0%2C5&q=Using+participatory+modeling+processes+to+identify+sources+of+climate+risk+in+West+Africa&btnG=
related_url_type: pub
citation:   Schmitt Olabisi, L and Liverpool-Tasie, S and Rivers, L and Ligmann-Zielinska, A and Du, J and Denny, R and Marquart-Pyatt, S and Sidibe, A  (2017) Using participatory modeling processes to identify sources of climate risk in West Africa.  Environment Systems and Decisions.  pp. 1-10.  ISSN 2194-5403     
document_url: http://oar.icrisat.org/10208/1/Using%20participatory%20modeling%20processes%20to%20identify%20sources.pdf