A Cognitive Model of an Epistemic Community: Mapping the Dynamics of Shallow Lake Ecosystems

We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake ecosystem model by augmenting the individual cognitive maps drawn by 8 scientists working in the area of shallow lake ecology. We calculated graph theoretical indices of the individual cognitive maps and the collective cognitive map produced by augmentation. The graph theoretical indices revealed internal cycles showing non-linear dynamics in the shallow lake ecosystem. The ecological processes were organized democratically without a top-down hierarchical structure. The steady state condition of the generic model was a characteristic turbid shallow lake ecosystem since there were no dynamic environmental changes that could cause shifts between a turbid and a clearwater state, and the generic model indicated that only a dynamic disturbance regime could maintain the clearwater state. The model developed herein captured the empirical behavior of shallow lakes, and contained the basic model of the Alternative Stable States Theory. In addition, our model expanded the basic model by quantifying the relative effects of connections and by extending it. In our expanded model we ran 4 simulations: harvesting submerged plants, nutrient reduction, fish removal without nutrient reduction, and biomanipulation. Only biomanipulation, which included fish removal and nutrient reduction, had the potential to shift the turbid state into clearwater state. The structure and relationships in the generic model as well as the outcomes of the management simulations were supported by actual field studies in shallow lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to understand the complex structure of shallow lake ecosystems as a whole and obtain a valid generic model based on tacit knowledge of experts in the field.Comment: 24 pages, 5 Figure

An ArcGIS Tool for Modeling the Climate Envelope with Feed-Forward ANN

This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study

Transparency and Reproducibility in Participatory Systems Modelling: the Case of Fuzzy Cognitive Mapping

By aggregating semi-quantitative mind maps from multiple agents, fuzzy cognitive mapping (FCM) allows developing an integrated, cross-sectoral understanding of complex systems. However, and especially for FCM based on individual interviews, the map-building process presents potential pitfalls. These are mainly related to the different understandings of the interviewees about the FCM semantics as well as the biases of the analyst during the elicitation and treatment of data. This paper introduces a set of good practice measures to increase transparency and reproducibility of map-building processes in order to improve credibility of results from FCM applications. The case study used to illustrate the proposed good practices assesses heatwave impacts and adaptation options in an urban environment. Agents from different urban sectors were interviewed to obtain individual cognitive maps. Using this set of data, we suggest good practices to collect, digitalize, interpret, pre-process and aggregate the individual maps in a traceable and coherent way. © 2018 The Authors Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley and Sons Ltd. © 2018 The Authors Systems Research and Behavioral Science published by International Federation for Systems Research and John Wiley and Sons LtdThis study is part of the project Bottom-up Climate Adaptation Strategies for a Sustainable Europe (BASE) funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 308337. MO (FPDI-2013-16631 and IJCI-2016-28835) and MBN (RYC-2013-13628) acknowledge co-funding from the Spanish Ministry of Economy, Industry and Competitiveness (MINECO)

Can multilayer perceptron ensembles model the ecological niche of freshwater fish species?

The potential of Multilayer Perceptron (MLP) Ensembles to explore the ecology of freshwater fish specieswas tested by applying the technique to redfin barbel (Barbus haasi Mertens, 1925), an endemic and mon-tane species that inhabits the North-East quadrant of the Iberian Peninsula. Two different MLP Ensembleswere developed. The physical habitat model considered only abiotic variables, whereas the biotic modelalso included the density of the accompanying fish species and several invertebrate predictors. The results showed that MLP Ensembles may outperform single MLPs. Moreover, active selection of MLP candidatesto create an optimal subset of MLPs can further improve model performance. The physical habitat modelconfirmed the redfin barbel preference for middle-to-upper river segments whereas the importance ofdepth confirms that redfin barbel prefers pool-type habitats. Although the biotic model showed higheruncertainty, it suggested that redfin barbel, European eel and the considered cyprinid species have similarhabitat requirements. Due to its high predictive performance and its ability to deal with model uncertainty, the MLP Ensemble is a promising tool for ecological modelling or habitat suitability prediction in environmental flow assessment.This study was funded by the Spanish Ministry of Economy and Competitiveness with the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065) and the Universitat Politecnica de Valencia, through the project UPPTE/2012/294 (PAID-06-12). Additionally, the authors would like to thank the help of the Conselleria de Territori i Vivenda (Generalitat Valenciana) and the Confederacion Hidrografica del Jucar (Spanish government) which provided environmental data. The authors are indebted to all the colleagues who collaborated in the field data collection and the text adequacy; without their help this paper would have not been possible. Last but not least, the authors would like to specifically thank E. Aparicio and A.J. Cannon, the former because he selflessly provided the bibliography about the redfin barbel and the latter because he patiently explained the 'ins and outs' of the monmlp package.Muñoz Mas, R.; Martinez-Capel, F.; Alcaraz-Hernández, JD.; Mouton, AM. (2015). Can multilayer perceptron ensembles model the ecological niche of freshwater fish species?. Ecological Modelling. 309-310:72-81. https://doi.org/10.1016/j.ecolmodel.2015.04.025S7281309-31

Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector

YesThe prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement.EU FP7 project Policy Compass (Project No. 612133