Biology Reference
In-Depth Information
than natural processes. The number of introductions of a species can vary and alter
the rate of expansion. Human pathways of introduction such as horticulture for
ornamental species and ballast water contaminants may cause introductions more
often, affecting propagule pressure, and across a wider range of locations than
accidentally introduced species. These variants across the temporal scale can be
important influences on the rate of spread, but difficult to monitor or predict.
Modeling pathways of spread can be difficult, even if a pathway does not rely
on the unpredictable movements of humans. For example, Myers et al. (2004)
examined the importance of deer in the Eastern United States for long distance dis-
persal of plant seeds, and postulated that deer may be an important vector in the
rapid spread of species in that region. This mode of transportation adds another
level of complexity to modeling the spread of species, as it necessitates prediction
of the feeding habits, spatial movement and rate of movement of deer along with
the other factors related to the invasive plant species' spread. These types of vectors
are not necessarily readily apparent when determining the ability of a species to
spread. An organism like the zebra mussel, which depends mainly on human trans-
port between bodies of water, may be modeled more easily with techniques like
gravity models that are appropriate for human pathways (Leung et al. 2006).
Similar techniques may prove appropriate for aquatic weeds.
6.3 ForecastingInvasions
There have been many studies to spatially model invasions. However, upon review,
there are very few papers that examine the spread of invasive species through time
where time is an independent variable in the model. There are different techniques
that can be used to analyze invasive species spread both spatially and temporally
(Table 6.1). These can include simple literature review and data collation tech-
niques, monitoring field site locations, using statistical techniques, and classifying
remotely-sensed imagery.
6.3.1 DataSynthesis
Although plot-based field data that may contain detailed information for a certain
location is typically limited spatially and temporally, there are broad scale occur-
rence datasets based on observations of organisms that might be used to examine
species' broad scale distributions and patterns of spread. These datasets include
museum and herbarium records, where the location is often very general (e.g.,
county level) and the only information about the organism that can be gleaned is
that it was present at a particular location at some point in time (e.g., generally a
particular year). We typically lack detailed information on species abundance over
time linked to specific coordinates, so analyzing historical datasets like these may
