Fuzzy Cognitive Mapping as a Tool to Define Management Objectives for Complex Ecosystems

Abstract

Defining objectives for ecological rehabilitation requires consideration of how an ecosystem responds to management. Validated quantitative models of physical, chemical, and biological processes are the best way to project such impacts; however, time, data, and model limitations often make these approaches impractical. An alternative is to encode expert knowledge about interactions among ecosystem components in a fuzzy cognitive map (FCM), which then translates that subjective, qualitative information into predictions of the effects of management on an ecosystem. Herein, we present the steps involved in constructing an FCM of an ecosystem, interpreting FCM output using multivariate statistics, and portraying the information in an easily communicated fashion. To illustrate these ideas, we rely on a complex (>160 variables) ecosystem model built for the Lake Erie watershed under the auspices of the Lake Erie Lakewide Management Plan (LaMP). Based on our experiences in building this model, we also offer recommendations for increasing the efficiency of the model‐development and interpretation process. Use of the FCM method in this case promoted constructive interaction among dozens of scientists, managers, and the public, as well as providing insights concerning the potential effects of broad classes of management actions upon the Lake Erie ecosystem. The analysis focused the attention of participants on four broad alternatives for the Lake. One represents present conditions, and another results from a decrease in nutrient inputs but an increase in stresses from land use and human disturbance. The two others involve reduced stress from nutrients and land use, with one having relatively more nutrients and less human disturbance and fishing. The latter ecosystem alternative was tentatively endorsed by LaMP management, and all four alternatives will be reviewed by the public.

The Water–Energy–Food Nexus: A Fuzzy-Cognitive Mapping Approach to Support Nexus-Compliant Policies in Andalusia (Spain)

“…FCMs enable systems modelling with limited data, including both quantitative and qualitative variables, whilst considering feedback relationships between concepts [37]. Furthermore, this methodology encourages stakeholder discussion, facilitates their involvement in the modelling process and increases reliance on the model [30]. Nevertheless, the outcome from the FCM model needs to be interpreted in relative terms (no absolute changes in variables can be provided).…”

“…FCM has proven to be very useful in a variety of domains, as emphasized by Papageorgiou and Salmeron [29] in a review of recent applications of this approach. In the environmental field, FCMs have been used to support watershed ecosystems management [30][31][32][33][34], landscape modelling [35,36], forest management [37], farming systems analysis [38], fisheries management [39], bioethanol production from biowaste [40], and intrusion of mining into landscape [41]. FCMs have been also applied to assess climate change impacts and effects of adaptation measures [42,43].…”

Using fuzzy cognitive mapping techniques to model situation awareness for army infantry platoon leaders

“…FCM has been applied in working with different stakeholder groups (Özesmi and Özesmi 2003;Skogoey and Skov 2007) and in cases where the focus has been nature conservation and landscape management (Isak 2008;Khan and Quaddos 2004). Also, FCMs have been used in domains (e.g., medical; Taber 1991; distributed networks; Ndousse and Okuda 1996; and health care; Smith and Eloff 2000), knowledge mapping instruments (Özesmi 1999;Özesmi 2003, 2004;Hobbs et al 2002;Banini and Bearman 1998;and Gettings et al 2004) and decision support systems (Siraj et al 2001;Geogropoulous et al 2003;Xirogiannis et al 2004). …”

A Generic Shallow Lake Ecosystem Model Based on Collective Expert Knowledge

“…Known examples include Radomski & Goeman (1996) who analyzed possible management options for sports fisheries; Hobbs et al (2002), who used FCM to define management objectives for Lake Erie ecosystem; Ö zesmi & Ö zesmi (2003), who analyzed the perceptions of different stakeholder groups about a lake ecosystem in order to develop a management plan; and Skov & Svenning (2003), who combined FCM with a GIS to use expert knowledge to predict plant habitat suitability in a forest. It is often the case in ecological applications that a detailed mathematical model of the ecosystem is absent or that the particular ecosystem under consideration is not fully characterized scientifically and the knowledge about the ecosystem is only partial.…”

“…Fuzzy cognitive mapping (FCM) approach has the advantage that the experiences and observations can be iteratively incorporated and represented symbolically in a mathematically consistent fashion, and enables manipulation of this symbolism to achieve a ''collective opinion''. The approach has been successfully applied to cases including political decision making and development (Taber, 1991), environmental management (Hobbs et al, 2002;Ö zesmi & Ö zesmi, 2004), and data mining of the World Wide Web (Hong & Han, 2002). Cognitive maps are defined as qualitative models of how a given system operates.…”