2.2.1.3. Bioclimatic Models
A variety of modeling techniques have been used to determine the strength of
association between suites of biotic and abiotic variables and species distributions.
These associations can then be used to predict responses to environmental change,
including climatic change. Bioclimatic models encompass a wide range of complexity.
The simplest model is described as a "climate envelope." It is designed
to describe static associations between a species' distribution and a single
set of climatic variables (Grinnell, 1924, 1928). Modern statistical analyses
and improved computer power have facilitated determination of complex suites
of climatic and nonclimatic variables that correlate with the range boundaries
for a given species (e.g., software such as BIOCLIM and GARP) (Stockwell and
Noble, 1991). These models incorporate biological realism, such as local adaptation
and differences in the nature of range limitations at different edges. Modern
biogeographic models have demonstrated a high level of predictive power in cross-validation
tests (Peterson and Cohoon, 1999).
2.2.1.4. Strengths and Limitations of Data
In assessing the strengths of studies as indicators of response to climate
change, it is helpful to consider where they lie along axes of time, space,
and replication (numbers of populations, numbers of species, etc.). To assess
changes in species distributions, data over large geographic areas are important,
especially for areas that represent the boundaries of a species' range
or migratory destination. To assess trends through time, frequent (yearly is
ideal) observations over many decades are most informative. And to assess the
generality of the result, good replication is necessary, with many populations/census
sites per species to indicate distributional changes within species or many
species per community to indicate community shifts.
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