climate change on UAE - Stockholm Environment Institute-US Center

9. Modeling <strong>climate</strong>
<strong>change</strong> impacts in the
UAE
9.1 Ecosystem models: limited
understanding, limitless
possibilities
Much of our understanding of ecosystem
structure and function today is derived from
ecosystem models, driven by a variety of data
types, from remote sensing to field observations
to physical first principles, and operating at a
wide range of complexities and scales, from
global vegetation and <strong>climate</strong> coupled models
to empirical observations of time series or
processes at a single field site. Models have
provided some of the best insights into how
<strong>climate</strong> <strong>change</strong> might be expected to impact
ecosystem structure and function.
There is no single clear definition for an
“ecosystem model”, as most are designed with
specific questions in mind. For example, coupled
<strong>climate</strong>-ecosystem models arose from the need
to more accurately portray generic vegetation
characteristics (such as evapotranspiration,
albedo, and surface roughness) in global and
regional <strong>climate</strong> models (Hurtt et al., 1998),
while empirically-based field models are used to
explore explicit relationships such as the impact
of changing groundwater or agricultural regimes
on vegetation cover (Elmore et al., 2003; Elmore
et al., 2006), the effect of seasonal temperature
variations on vegetation phenology (Schaber
and Badeck, 2003; Fisher et al., 2007), or the
impact of rainfall frequency and abundance
on carbon flux (Weltzin et al., 2003; Sponseller,
2007).
There are fundamental differences between
models developed from field-based empirical
data and those that attempt to work at larger
regional or global scales. It is important to note
even before our discussion of model potentials
and fundamentals that ecosystem models are
intrinsically limited by both available data,
computational complexity, and in general by our
imperfect knowledge of ecosystem processes.
The study of ecology asks biologists to explore
and understand data across a vast range of
spatial and time scales, from photosynthetic
reactions in individual leaf cells, to patterns
of water distribution and disturbance across a
landscape, to complex feedback cycles between
vegetation and the atmosphere.
While there have been great insights at every
level of study over recent decades, models
still simplify processes by necessity, assuming
relationships or causations when possible and
not critical to the model outcome. The end
result is that ecologists developing or applying
ecosystem models usually start a modeling
process by determining which fundamental
sets of relationships can be fixed, and which
need to be variables (and how these variables
will be portrayed). Therefore, it has been nearly
impossible, to date, to develop models which
are both general and accurate across biomes.
However, this is not to say that models have not
yielded great steps forward in understanding
ecosystem function and process.
A reasonably good rule of thumb for applying
ecosystem models is that these systems should
be used for exploring patterns and dynamics in a
biome or region, but should not be counted on to
provide predictive capacity in most situations. A
model can help a scientist discern critical factors
driving ecosystem <strong>change</strong> such as <strong>climate</strong>, land
use, or disturbance (Veldkamp and Lambin,
2001), or assist a land manager in determining an
appropriate timing or intensity of fire or grazing
(Anderies et al., 2002). Increasingly, models
are being used to explore potential impacts of
<strong>climate</strong> <strong>change</strong>, ecosystem vulnerabilities, and
the developing field of “adaptive management”,
managing and modeling iteratively to achieve
an ecosystem goal. Below, we describe some
of the fundamental bounds and constructs of
ecosystem models, and explore specific case
examples in arid ecosystems.
Empirical or first principles Topdown
versus bottom-up models
Ecosystem models encompass a wide universe
of possible model constructs, yet there are
some useful first order classifications which
can serve to clarify the philosophy behind the
model, and how the model is ultimately used
and interpreted. One of the most important
classifying mechanisms is whether a model
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Climate Change Impacts, Vulnerability & Adaptation