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One of the factors for the success of simulation studies is close collaboration with stakeholders in developing a conceptual model. Conceptual models are a useful tool for communicating and understanding how real systems work. However, models or frameworks that are not aligned with the perceptions and understanding of local stakeholders can induce uncertainties in the model outcomes. We focus on two sources of epistemic uncertainty in building conceptual models of food-energy-water systems (FEWS): (1) context and framing; and (2) model structure uncertainty. To address these uncertainties, we co-produced a FEWS conceptual model with key stakeholders using the Actor-Resources-Dynamics-Interaction (ARDI) method. The method was adopted to specifically integrate public (and local) knowledge of stakeholders in the Magic Valley region of Southern Idaho into a FEWS model. We first used the ARDI method with scientists and modellers (from various disciplines) conducting research in the system, and then repeated the process with local stakeholders. We compared results from the two cohorts and refined the conceptual model to align with local stakeholders’ understanding of the FEWS. This co-development of a conceptual model with local stakeholders ensured the incorporation of different perspectives and types of knowledge of key actors within the socio-ecological systems models.
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Integrating Values to Improve the Relevance of Climate‐Risk Research
Climate risks are growing. Research is increasingly important to inform the design of risk‐management strategies. Assessing such strategies necessarily brings values into research. But the values assumed within research (often only implicitly) may not align with those of stakeholders and decision makers. These misalignments are often invisible to researchers and can severely limit research relevance or lead to inappropriate policy advice. Aligning strategy assessments with stakeholders' values requires a holistic approach to research design that is oriented around those values from the start. Integrating values into research in this way requires collaboration with stakeholders, integration across disciplines, and attention to all aspects of research design. Here we describe and demonstrate a qualitative conceptual tool called a values‐informed mental model (ViMM) to support such values‐centered research design. ViMMs map stakeholders' values onto a conceptual model of a study system to visualize the intersection of those values with coupled natural‐human system dynamics. Through this mapping, ViMMs integrate inputs from diverse collaborators to support the design of research that assesses risk‐management strategies in light of stakeholders' values. We define a visual language for ViMMs, describe accompanying practices and workflows, and present an illustrative application to the case of flood‐risk management in a small community along the Susquehanna river in the Northeast United States.
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- Award ID(s):
- 2103754
- PAR ID:
- 10554108
- Publisher / Repository:
- Wiley Online Library
- Date Published:
- Journal Name:
- Earth's Future
- Volume:
- 12
- Issue:
- 10
- ISSN:
- 2328-4277
- Page Range / eLocation ID:
- e2022EF003025
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Introduction Integrated water management (IWM) involves a range of policies, actions, and organizational processes that go beyond traditional hydrology to consider multifaceted aspects of complex water resource systems. Due to its transdisciplinary nature, IWM comprises input from diverse stakeholders, each with unique perceptions, values, and experiences. However, stakeholders from differing backgrounds may disagree on best practices and collective paths forward. As such, successful IWM must address key governance principles (e.g., information flow, collective decision-making, and power relations) across social and institutional scales. Here, we sought to demonstrate how network structure impacts shared decision-making within IWM. Methods We explored a case study in Houston, Texas, USA, where decision-making stakeholders from various sectors and levels of governance engaged in a participatory modeling workshop to improve adoption of nature-based solutions (NBS) through IWM. The stakeholders used fuzzy cognitive mapping (FCM) to define an IWM model comprising multifaceted elements and their interrelationships, which influenced the adoption of NBS in Houston. We applied grounded theory and inductive reasoning to categorize tacit belief schemas regarding how stakeholders viewed themselves within the management system. We then used FCM-based modeling to explore how unique NBS policies would translate into more (or less) NBS adoption. Finally, we calculated specific network metrics (e.g., density, hierarchy, and centrality indices) to better understand the structure of human-water relations embedded within the IWM model. We compared the tacit assumptions about stakeholder roles in IWM against the quantitative degrees of influence and collectivism embedded within the stakeholder-defined model. Results and discussion Our findings revealed a mismatch between stakeholders' external belief statements about IWM and their internal assumptions through cognitive mapping and participatory modeling. The case study network was characterized by a limited degree of internal coordination (low density index), high democratic potential (low hierarchy index), and high-efficiency management opportunities (high centrality index), which transcended across socio-institutional scales. These findings contrasted with several of the belief schemas described by stakeholders during the group workshop. We describe how ongoing partnership with the stakeholders resulted in an opportunity for adaptive learning, where the NBS planning paradigm began to shift toward trans-scale collaboration aimed at high-leverage management opportunities. We emphasize how network analytics allowed us to better understand the extent to which key governance principles drove the behavior of the IWM model, which we leveraged to form deeper stakeholder partnerships by identifying hidden opportunities for governance transformation.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2022EF003025
