Measuring the Degree of ‘Fit’ Within Social-Ecological Systems to Support Local Flood Risk Decision-Making

Abstract

Effective social-ecological fit is considered essential for properly managing social-ecological systems. Despite this importance, the concept of social-ecological fit lacks the following: clarity in scope and definition, a practical quantitative method to assess effectiveness, and methods capable of equally assessing the social and ecological factors within the system being managed. To address these knowledge gaps, we reviewed how social-ecological fit has been conceptualised in the literature and then tested the use of Bayesian Belief networks and analysis to quantitatively assess “fit” using the case of flooding in the North Onslow saltmarsh region of Truro, Nova Scotia. The objective of this study was to assess which decision-making choices would most likely reduce flood risk, and therefore achieve the best ‘fit’. Drawing from a combination of existing literature and local expert opinion, we identified the relevant factors influencing flood risk in the region, their relationship to each other and their combined relationship to local flood risk. Ice jam frequency, high tide frequency and dyke maintenance were found to have the most influence. The results of this study can be used to inform local flood-risk-related decision-making in Truro and act as a model for quantitatively assessing social-ecological fit in other risk management settings.