climate change on UAE - Stockholm Environment Institute-US Center

species to adapt to a changing <strong>climate</strong> than
for it to migrate and establish in a new
physical location.
Species dispersal: non-mobile species may
be unable to migrate or disperse to new
climatic zones, even over the course of many
generations, while highly mobile species
may be able to exploit much more of their
fundamental <strong>climate</strong> range.
Empirically-based bio<strong>climate</strong> models share an
underlying methodology (Araujo et al., 2005): the
physical locations of a species is recorded over a
wide range (as presence-absence), and <strong>climate</strong>
variables are derived for all locations. Climate
variables may include cooling or warming
degree days, average temperature over a timeperiod,
maximum or minimum temperatures
during a critical period, number of days over a
temperature threshold, volume of precipitation
over a time-period, frequency of rainfall, and
drought lengths. Using a variety of classification
mechanisms (neural networks, statistical
clustering, or decision trees), the variables (and
their ranges) which best discriminate species
presence or absence are determined on a subset
of the data and 70% is a standard (Pearson and
Dawson, 2003). The remaining data is used to
validate the <strong>climate</strong> envelope assumptions.
New <strong>climate</strong> variables are derived for a <strong>climate</strong>
<strong>change</strong> scenario, and the derived rules are
applied to the new variables to determine the
potential species range.
This class of model may be useful in determining
the impact of <strong>climate</strong> <strong>change</strong> in the UAE if the
underlying question is in regard to expected new
species ranges or biodiversity. These models
require significant field and possibly remote
sensing data to run successfully.
Patch structure and spatial
distribution models
Patch structure and spatial distribution models
have at least two distinct lineages, but have
evolved to answer similar questions: how does
the spatial structure of an ecosystem (usually
at a landscape scale) impact the function and
composition of the ecosystem Similarly to the
mechanistic models described above, these
models are usually theoretically based and non
site-specific, and usually track the dynamics of
vegetation, rather than fauna.
Patch structure, or gap, models are derived
from forest stand models, developed to
estimate the rate of growth and height of trees
in dense, light-limited environments (such as
rainforests). These models simulate the light
and water environment for individual stands of
trees, and often explicitly model the shape, size,
and leaf cover of each tree in the stand, using
allometric equations to estimate leaf density,
branch size, and tree height from more simply
tracked metrics, such as stem width (Busing
and Mailly, 2004). Important questions in
these models revolve around how quickly gaps
(treefalls) are replaced with new vegetation in
certain environments.
Spatial distribution models are systems
developed to explore the dynamic systems in
which physical proximity, rather than height, is
important. Such models are often seen applied
in arid or semi-arid ecosystems where nutrient
and water availability are critical limiting
factors. The distance between shrubs or clumps
of grasses may determine how much water
is available to individual plants, how water is
transferred between plants, or where pools of
nutrients are available. Spatial distribution
models may be combined with grazing or fire
simulations to determine how herbivory and
disturbance <strong>change</strong>s the structure, health, or
composition of sparsely vegetated landscapes
(i.e. van de Koppel and Rietkerk, 2004; Adler
et al., 2001; Weber et al., 1998; Aguiar and Sala,
1999)
This class of model may be useful in determining
the impact of <strong>climate</strong> <strong>change</strong> in the UAE in
the context of evaluating both precipitation
frequency and intensity influence on ecosystem
composition, and grazing impacts, primarily by
camels, on arid ecosystem health.
Climate / phenology models
Climate-phenology models are a distinct and
unique class of model, usually empirically
based, which strive to understand the drivers
of seasonality of flora and fauna. Many of
these models relate various <strong>climate</strong> factors
(temperature, precipitation, and available
sunlight at key times of the year) to the timing
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