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The provision of useful guidance to inform policy requires observation and
description of human contributions to global change, as well as theoretical
studies of the underlying social processes that shape them. We also need to
understand how global change affects human welfare. This requires not merely
studies of direct exposure but also of the capacity to respond.
Causal models of social processes have large uncertainties, and pose problems
that are of a qualitatively different character than those encountered in modelling
non-human components of the Earth system. This is due, first and foremost, to
the inherent reflexivity of human behaviour; i.e., the fact that human beings
have intellectual capabilities and emotional endowments enabling them to invent
new solutions and transcend established “laws” in ways that no other
species can do. As a consequence, predictive models may well alter the behaviour
that they seek to predict and explain – indeed, such models are sometimes
deliberately used exactly for that purpose. Moreover, the diversity of societies,
cultures, and political and economic systems often frustrates attempts to generalise
findings and propositions from one setting to another. Representation of human
behaviour at the micro (individual) and macro (collective) scale may require
fundamentally different approaches (see Gibson et al., 1998).
These kinds of difficulties intrinsically limit the predictive power that can
be ascribed to models of social processes. As a consequence, research on human
drivers and responses to climate change cannot be expected to produce conventional
predictions beyond a very short time horizon. This does not imply, however,
that research on human behaviour and social processes cannot provide knowledge
and insight that can inform policy deliberations. A considerable amount of basic
knowledge and insight exist, and this knowledge can be used, inter alia, for
constructing scenarios showing plausible trajectories and identifying the critical
factors that will have to be targeted in order to switch from one trajectory
to another. From the perspective of policy-makers, this can indeed be an important
contribution.
To make the most of this potential, further progress is required along two
main frontiers. One challenge is to develop a more integrated understanding
of social systems and human behaviour. With some exceptions, the first generation
of models in this area represented “the human system” by a few key
variables. For example, resource use was often conceived of as a function of
population size and income level. The performance of such simplistic models
was by-and-large poor. It is abundantly clear that the impact of human activities
as drivers of climate change depends upon a complex set of interrelated factors,
including also technologies in use, social institutions, and individual beliefs,
attitudes, and values. At present, it seems fair to say that we have a reasonably
good theoretical grasp of important types of institutions, such as markets and
hierarchies, in ideal-type form. What we need to understand better is how their
impure real-world counterparts work, and to improve our understanding of the
intricate interplay of institutional complexes, i.e., how markets, governments
and other social institutions interact to shape human behaviour. Research in
political economy clearly indicates that phenomena such as economic growth are
to a significant extent affected by the functioning of interlocking networks
of institutional arrangements.
Similarly, we have a fairly good grasp on particular kinds of intellectual
processes - in particular, the logic of rational choice - but we are doing less
well when it comes to understanding how beliefs, attitudes and values change
and how change in these factors in turn affects manifest human behaviour, such
as consumption patterns. To address these challenges we need more interdisciplinary
research designed to integrate knowledge from different fields and sub-fields
into a more holistic understanding of “the human system”. The intellectual
and organisational problems involved should not be underestimated, but we are
confident that the prospects for making progress along this frontier are better
now than ever before.
The other main challenge is to find better ways of integrating models of the
biogeophysical Earth system with models of social systems and human behaviour.
Some encouraging progress has been made at this interface, particularly over
the last decade. For example, there has been a rapid increase in attempts to
integrate representations of human activities in models with explicit formal
linkages to other components of the Earth system. Such integrated assessment
models have offered preliminary characterisations of human-climate linkages,
particularly through models of multiple linked human and climate stresses on
land cover. Moreover, they have provided preliminary characterisation of broad
classes of policy responses, and have been employed to characterise and prioritise
policy-relevant uncertainties.
Yet, effective integration is frustrated by at least two main obstacles. One is incongruity of temporal and spatial scales. Social science research cannot match the long time horizons of much natural science research. On the other hand, in studying consequences for human welfare and responses to these consequences, social scientists need estimates of biophysical impacts of climate change differentiated by political units or even smaller social systems. Aggregate global-scale estimates are of limited use in this context; human sensitivity to climate change varies significantly across regions and social groups, and so does response capacity. We can expect to see some progress in alleviating the spatial resolution problem, as regional-scale models of climate change are further developed, but we have to recognise that the scale problems are fundamental and that no quick fixes are in sight. The other problem pertains to the interface between different methodological approaches. In particular, concerted efforts are required to develop better tools for coupling approaches relying on numerical modelling with “softer” approaches using interpretative frameworks and qualitative methods. Some of these differences are too profound to be eliminated, but that does not imply that bridges cannot be built. Learning how to work more effectively across these methodological divides is essential to the further development of integrated global change research. Again, some encouraging progress is being made.
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