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can become overly detailed or specified, making it impossible to generalize and
draw policy implications for a larger population, e.g., a community or region.
Third, accounting for how individual decisions relate to higher-level decisions
made by communities or governments, and the proper scaling of models from an
individual level to a regional or global scale, is a continuing challenge. As human
agency varies across different scale levels, the ways that human agency and human
decision-making are represented should similarly depend on the scale of analysis.
In addition, behavioral interactions and feedbacks that occur across scales, such as
many of the rebound and spillover effects discussed earlier, greatly increase the
complexity of a model and thus may be difficult to incorporate.
By definition, models are simplifications of reality. Given the pace with which
advances in behavioral research are occurring, the above and other challenges to
incorporating behavioral realism into FEW system research are likely to be
addressed. Paradoxically, as we discover more about the anomalies and differences
of human behavior, determining the right amount of detail and which details to track
becomes harder, not easier. What is needed is to scale up our current level of understanding, making the focus of research more about determining the sources of heterogeneity that matter at an aggregate or systems level, which is the scale that is
relevant for policy. This is perhaps the greater challenge, as policymakers do not
require perfect models to develop well-informed policies. Hence, for research to be
policy relevant, researchers need to produce models that achieve these appropriate
levels of detail and accuracy.
Key Points
• Studying either the natural or human system in isolation omits important drivers
of change in FEW systems and how people respond and adapt to these changes.
This can potentially lead to an incomplete understanding of these integrated
systems.
• Relying on inaccurate representations of human behavior may lead to policies
that fail to achieve their stated aims or policies that are not implemented at all.
• Allowing for an accurate representation of human behavior requires drawing on
social science disciplines and data that may not otherwise be employed in
research of the natural systems alone, and often requires drawing on various
theoretical and empirical approaches of social sciences.
• Recognizing that environmental and social changes may cause people to respond
in different ways is important in accurately accounting for human behavior and
adaptation in FEW systems. Allowing for behavioral heterogeneity recognizes that
individuals may have different motivations for their actions and that how they react
to changes in their social or natural environments may also be different.
• People can respond to changes in FEW systems or to new FEW policies with
desirable changes in their behavior, or with undesirable changes (e.g., rebound or
boomerang effects). It is also important to consider potential connections among
FEW behaviors themselves (e.g., behavioral spillover).
• Including human behavior in the study of FEW systems requires collecting of
data on individuals and their decision-making processes to inform models of
4 Human Behavior and Adaptation
can become overly detailed or specified, making it impossible to generalize and
draw policy implications for a larger population, e.g., a community or region.
Third, accounting for how individual decisions relate to higher-level decisions
made by communities or governments, and the proper scaling of models from an
individual level to a regional or global scale, is a continuing challenge. As human
agency varies across different scale levels, the ways that human agency and human
decision-making are represented should similarly depend on the scale of analysis.
In addition, behavioral interactions and feedbacks that occur across scales, such as
many of the rebound and spillover effects discussed earlier, greatly increase the
complexity of a model and thus may be difficult to incorporate.
By definition, models are simplifications of reality. Given the pace with which
advances in behavioral research are occurring, the above and other challenges to
incorporating behavioral realism into FEW system research are likely to be
addressed. Paradoxically, as we discover more about the anomalies and differences
of human behavior, determining the right amount of detail and which details to track
becomes harder, not easier. What is needed is to scale up our current level of understanding, making the focus of research more about determining the sources of heterogeneity that matter at an aggregate or systems level, which is the scale that is
relevant for policy. This is perhaps the greater challenge, as policymakers do not
require perfect models to develop well-informed policies. Hence, for research to be
policy relevant, researchers need to produce models that achieve these appropriate
levels of detail and accuracy.
Key Points
• Studying either the natural or human system in isolation omits important drivers
of change in FEW systems and how people respond and adapt to these changes.
This can potentially lead to an incomplete understanding of these integrated
systems.
• Relying on inaccurate representations of human behavior may lead to policies
that fail to achieve their stated aims or policies that are not implemented at all.
• Allowing for an accurate representation of human behavior requires drawing on
social science disciplines and data that may not otherwise be employed in
research of the natural systems alone, and often requires drawing on various
theoretical and empirical approaches of social sciences.
• Recognizing that environmental and social changes may cause people to respond
in different ways is important in accurately accounting for human behavior and
adaptation in FEW systems. Allowing for behavioral heterogeneity recognizes that
individuals may have different motivations for their actions and that how they react
to changes in their social or natural environments may also be different.
• People can respond to changes in FEW systems or to new FEW policies with
desirable changes in their behavior, or with undesirable changes (e.g., rebound or
boomerang effects). It is also important to consider potential connections among
FEW behaviors themselves (e.g., behavioral spillover).
• Including human behavior in the study of FEW systems requires collecting of
data on individuals and their decision-making processes to inform models of
4 Human Behavior and Adaptation