Back to Search Start Over

A Method for Enhancing Capacity of Local Governance for Climate Change Adaptation

Authors :
D. S. Williams
L. Celliers
K. Unverzagt
N. Videira
M. Máñez Costa
R. Giordano
Source :
Earth's Future, Vol 8, Iss 7, Pp n/a-n/a (2020)
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

Abstract The lack of capacity for climate change adaptation at the subnational level has been highlighted as a key barrier to implementing the UNFCCC National Adaptation Plans. At the same time, the adaptive capacity of local governance is highly context sensitive, making a “one‐size fits all” approach inappropriate. Thus, a versatile methodological approach for application in various local contexts is required. There are several indicator‐based local governance assessment methods for evaluating the effectiveness of local governance for climate change adaptation. However, they fall short of identifying and prioritizing between key factors within local governance for enhancing adaptive capacity and driving positive change. Building on adaptation theory, the authors propose combining two methodological approaches, the Capital Approach Framework for evaluating the adaptive capacity of local governance and Fuzzy Cognitive Mapping for identifying leverage points, into one integrated modeling approach, which can be applied by local researchers. This paper describes the process and benefits of combining the methodological approaches, with an example provided as supporting information. Assisting decision‐makers and policy planners from subnational governance in identifying leverage points to focus and maximize impact of capacity‐enhancing measures would make a key contribution for successful implementation of the UNFCCC National Adaptation Plans.

Details

Language :
English
ISSN :
23284277
Volume :
8
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Earth's Future
Publication Type :
Academic Journal
Accession number :
edsdoj.3239e11851904708b3a5aff7138d10b4
Document Type :
article
Full Text :
https://doi.org/10.1029/2020EF001506