Ambiguity in social ecological system understanding: Advancing modelling of stakeholder perceptions of climate change adaptation in Kenya

Abstract Climate change adaptation requires understanding of complex social ecological systems (SESs). One source of uncertainty in complex SESs is ambiguity, defined as the range and variety of existing perceptions in and of an SES, which are considered equally valid, resulting in a lack of a unique or single system understanding. Current modelling practices that acknowledge the presence of ambiguity in SESs focus on finding consensus with stakeholders; however, advanced methods for explicitly representing and aggregating ambiguity in SESs are underdeveloped. Moreover, understanding the influences of ambiguity on SES representation is limited. This paper demonstrates the presence and range of ambiguities in endogenous and exogenous system drivers and internal relationships based on individual fuzzy cognitive maps derived from stakeholder perceptions of climate change adaptation in Kenya and introduces an ambiguity based modelling process. Our results indicate that acknowledging ambiguity fundamentally changes SES representation and more advanced methods are required.

[1]  C. Folke,et al.  Social-ecological systems as complex adaptive systems: organizing principles for advancing research methods and approaches , 2018 .

[2]  T. Webler,et al.  Learning Through Participatory Modeling: Reflections on What It Means and How It Is Measured , 2017 .

[3]  Steven A. Gray,et al.  Fuzzy Cognitive Maps as Representations of Mental Models and Group Beliefs , 2014, Fuzzy Cognitive Maps for Applied Sciences and Engineering.

[4]  Philippe J. Giabbanelli,et al.  Should we simulate mental models to assess whether they agree? , 2018, SpringSim.

[5]  Uygar Özesmi,et al.  Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach , 2004 .

[6]  Hans Jørgen Henriksen,et al.  Use of Bayesian belief networks for dealing with ambiguity in integrated groundwater management , 2012, Integrated environmental assessment and management.

[7]  R. Biggs,et al.  Synthesis, part of a Special Feature on Applied Research for Enhancing Human Well-Being and Environmental Stewardship: Using Complexity Thinking in Southern Africa Strategies for managing complex social-ecological systems in the face of uncertainty: examples from South Africa and beyond , 2015 .

[8]  Claudia Pahl-Wostl,et al.  Toward a Relational Concept of Uncertainty: about Knowing Too Little, Knowing Too Differently, and Accepting Not to Know , 2008 .

[9]  Anthony J. Jakeman,et al.  Eight grand challenges in socio-environmental systems modeling , 2020 .

[10]  Mark E. Borsuk,et al.  Methods for translating narrative scenarios into quantitative assessments of land use change , 2016, Environ. Model. Softw..

[11]  Carlos Alonso,et al.  Using fuzzy cognitive maps for predicting river management responses: A case study of the Esla River basin, Spain , 2017 .

[12]  C. Prell,et al.  Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling. , 2018, Ecological Applications.

[13]  Kasper Kok,et al.  Fuzzy Cognitive Maps for futures studies—A methodological assessment of concepts and methods , 2014 .

[14]  Uygar Ozesmi Ecosystems in the Mind: Fuzzy Cognitive Maps of the Kizilirmak Delta Wetlands in Turkey , 2006, q-bio/0603022.

[15]  L. Downsborough,et al.  Synthesis, part of a Special Feature on Applied Research for Enhancing Human Well-Being and Environmental Stewardship: Using Complexity Thinking in Southern Africa Exploring the implications of critical complexity for the study of social- ecological systems. , 2013 .

[16]  Kasper Kok,et al.  Combining participative backcasting and exploratory scenario development: Experiences from the SCENES project , 2011 .

[17]  Christophe Simon,et al.  A companion modelling approach applied to forest management planning , 2010, Environ. Model. Softw..

[18]  C. Pahl-Wostl,et al.  Research, part of a Special Feature on A Framework for Analyzing, Comparing, and Diagnosing Social-Ecological Systems Comparison of Frameworks for Analyzing Social-ecological Systems , 2013 .

[19]  Ali Sharifi,et al.  From individual Fuzzy Cognitive Maps to Agent Based Models: Modeling multi-factorial and multi-stakeholder decision-making for water scarcity. , 2019, Journal of environmental management.

[20]  Kasper Kok,et al.  Linking stakeholders and modellers in scenario studies: The use of Fuzzy Cognitive Maps as a communication and learning tool , 2010 .

[21]  Anthony J. Jakeman,et al.  An overview of the system dynamics process for integrated modelling of socio-ecological systems: Lessons on good modelling practice from five case studies , 2017, Environ. Model. Softw..

[22]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[23]  E. Turnhout,et al.  The politics of co-production: participation, power, and transformation , 2020 .

[24]  Louis Lebel,et al.  Guest Editorial, part of a Special Feature on Scale and Cross-scale Dynamics Scale and Cross-Scale Dynamics: Governance and Information in a Multilevel World , 2006 .

[25]  Anil Graves,et al.  Who's in and why? A typology of stakeholder analysis methods for natural resource management. , 2009, Journal of environmental management.

[26]  Martina Flörke,et al.  FCMs as a common base for linking participatory products and models , 2017 .

[27]  Arend Ligtenberg,et al.  Which Sensitivity Analysis Method Should I Use for My Agent-Based Model? , 2016, J. Artif. Soc. Soc. Simul..

[28]  Suzanne A. Pierce,et al.  Modelling with stakeholders e Next generation , 2015 .

[29]  Cécile Barnaud,et al.  A participatory Bayesian Belief Network approach to explore ambiguity among stakeholders about socio-ecological systems , 2017, Environ. Model. Softw..

[30]  M. Lubell,et al.  The structure of mental models of sustainable agriculture , 2018, Nature Sustainability.

[31]  Robert Arlinghaus,et al.  Wisdom of stakeholder crowds in complex social–ecological systems , 2020, Nature Sustainability.

[32]  Vanessa J. Schweizer,et al.  Systematic construction of global socioeconomic pathways using internally consistent element combinations , 2014, Climatic Change.

[33]  K. Sepp,et al.  Drivers of European landscape change: stakeholders’ perspectives through Fuzzy Cognitive Mapping , 2019 .

[34]  Marcela Brugnach,et al.  Ambiguity: the challenge of knowing and deciding together , 2012 .

[35]  Michael Paolisso,et al.  Cognitive, Material and Technological Considerations in Participatory Environmental Modeling , 2017 .

[36]  C Pahl-Wostl,et al.  Integrated management of natural resources: dealing with ambiguous issues, multiple actors and diverging frames. , 2005, Water science and technology : a journal of the International Association on Water Pollution Research.

[37]  Kasper Kok,et al.  The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development, with an example from Brazil , 2009 .

[38]  Jarno Vanhatalo,et al.  Making the most of mental models: Advancing the methodology for mental model elicitation and documentation with expert stakeholders , 2020, Environ. Model. Softw..

[39]  S. Bremer,et al.  Co‐production in climate change research: reviewing different perspectives , 2017 .

[40]  Elinor Ostrom,et al.  Complexity of Coupled Human and Natural Systems , 2007, Science.

[41]  C. Pahl-Wostl,et al.  A broadened view on the role for models in natural resource management: Implications for model development , 2008 .

[42]  P. Reason,et al.  A Participatory Inquiry Paradigm , 1997 .

[43]  Claudia Pahl-Wostl,et al.  Transitions towards adaptive management of water facing climate and global change , 2006 .

[44]  H. Carlsen,et al.  Quantifying transnational climate impact exposure: New perspectives on the global distribution of climate risk , 2018, Global Environmental Change.

[45]  E. Gaddis,et al.  Values in participatory modeling : Theory and practice , 2017 .

[46]  K. Kok,et al.  Mapping future changes in livelihood security and environmental sustainability based on perceptions of small farmers in the Brazilian Amazon , 2015 .

[47]  K. Arrow,et al.  Social-ecological systems as complex adaptive systems: modeling and policy implications , 2012, Environment and Development Economics.

[48]  E. Ostrom A General Framework for Analyzing Sustainability of Social-Ecological Systems , 2009, Science.

[49]  Noshad Rahimi,et al.  Soft Data Analytics with Fuzzy Cognitive Maps: Modeling Health Technology Adoption by Elderly Women , 2018 .

[50]  Anthony J. Jakeman,et al.  Selecting among five common modelling approaches for integrated environmental assessment and management , 2013, Environ. Model. Softw..

[51]  M. Falkenmark The massive water scarcity now threatening Africa - why isn't it being addressed? , 1989 .