463
enhances cooperative decision-making, as compared to individual or personal displays. See also Sect. 20.3.4 on collaborative governance.
Through an actively managed process, FEW system collaborators can cooperatively negotiate scale, level, and specificity of the high-resolution integrated assessments to ensure that analyses address questions that are scientifically important and
decision-relevant. The challenge lies in explaining the decision-space of uncertainty
in an accessible, transparent manner, and without presenting all possible permutations and potential ramifications of the uncertainty itself. When framed in a context
consistent with sustainable resource management and planning objectives, and
within timelines consistent with decision processes, modeling can help assuage
stakeholder concerns about the usefulness of FEW system modeling for decisionmaking and ensure the outputs can be used to help make decisions.
17.3 Tools for Decision-Making
Working with stakeholders to evaluate alternative scenarios in the FEW Nexus
requires collaboration between stakeholder facilitators, planners, social scientists,
geospatial/biophysical scientists, data scientists, and communication professionals.
To be effective, the process of generating computational tools and visualization support for stakeholder decision-making should include stakeholders in the design process of these tools and in a manner that goes beyond surveying their questions and
goals. Non-scientist stakeholders should also have a say in the assumptions, rules,
processes, and outputs represented throughout the decision-making process. Such
input can help guide how models are built and how results are conveyed.
In general, scientists transform data into metrics using different kinds of models.
Existing models, however, do not easily connect from local to regional to global
scales: the processes and data represented vary at these different scales. Finer-scale
with coarser-scale models need to be connected to help transform data and assumptions into performance indicators across wider spatial and temporal scales. Rather
than coupling models, cross-scale connection could be achieved through ranges or
ensembles of local to global models, or process-based to data-driven models. This
will help stakeholders, and decision-makers understand how gains at one scale
might translate into costs at a different scale, putting them in a stronger position to
collectively design meaningful landscape change. Pattern recognition and classification tools could help generalize models that evaluate alternative land, water, and
energy management scenario impacts on various performance indicators and at different spatial or temporal scales. In addition, running scenarios through models may
be a helpful way to test assumptions, try on future outcomes, and see what results.
Figure 12.4 illustrated the logic of an integrated approach to modeling of FEW
systems that can address the research questions and stakeholder needs, must both
couple modeling tools for food, energy, and water systems, and also connect to decision science, data integration, and visual analytics.
Computational tools can create platforms for conducting conversations, group
design, planning exercises, and for transforming data into performance indicators.
17 Applying Science to Practice
enhances cooperative decision-making, as compared to individual or personal displays. See also Sect. 20.3.4 on collaborative governance.
Through an actively managed process, FEW system collaborators can cooperatively negotiate scale, level, and specificity of the high-resolution integrated assessments to ensure that analyses address questions that are scientifically important and
decision-relevant. The challenge lies in explaining the decision-space of uncertainty
in an accessible, transparent manner, and without presenting all possible permutations and potential ramifications of the uncertainty itself. When framed in a context
consistent with sustainable resource management and planning objectives, and
within timelines consistent with decision processes, modeling can help assuage
stakeholder concerns about the usefulness of FEW system modeling for decisionmaking and ensure the outputs can be used to help make decisions.
17.3 Tools for Decision-Making
Working with stakeholders to evaluate alternative scenarios in the FEW Nexus
requires collaboration between stakeholder facilitators, planners, social scientists,
geospatial/biophysical scientists, data scientists, and communication professionals.
To be effective, the process of generating computational tools and visualization support for stakeholder decision-making should include stakeholders in the design process of these tools and in a manner that goes beyond surveying their questions and
goals. Non-scientist stakeholders should also have a say in the assumptions, rules,
processes, and outputs represented throughout the decision-making process. Such
input can help guide how models are built and how results are conveyed.
In general, scientists transform data into metrics using different kinds of models.
Existing models, however, do not easily connect from local to regional to global
scales: the processes and data represented vary at these different scales. Finer-scale
with coarser-scale models need to be connected to help transform data and assumptions into performance indicators across wider spatial and temporal scales. Rather
than coupling models, cross-scale connection could be achieved through ranges or
ensembles of local to global models, or process-based to data-driven models. This
will help stakeholders, and decision-makers understand how gains at one scale
might translate into costs at a different scale, putting them in a stronger position to
collectively design meaningful landscape change. Pattern recognition and classification tools could help generalize models that evaluate alternative land, water, and
energy management scenario impacts on various performance indicators and at different spatial or temporal scales. In addition, running scenarios through models may
be a helpful way to test assumptions, try on future outcomes, and see what results.
Figure 12.4 illustrated the logic of an integrated approach to modeling of FEW
systems that can address the research questions and stakeholder needs, must both
couple modeling tools for food, energy, and water systems, and also connect to decision science, data integration, and visual analytics.
Computational tools can create platforms for conducting conversations, group
design, planning exercises, and for transforming data into performance indicators.
17 Applying Science to Practice