Biology Reference
In-Depth Information
potential distribution and abundance as it will have a relatively more stable distribu-
tion, having had time for propagules to reach all suitable habitat. However, despite
the abundance of model comparison papers, we were unable to find any that have
analyzed this topic, although Wilson et al. (2007) do discuss the importance of resi-
dence time as a consideration when modeling potential distribution. They created
simple logistic models of rate of spread including this term.
This temporal context for invasive species is important in assessing current and
potential impacts and spread. A general trend in nonnative species invasions is a lag
time between establishment and explosive spread, where populations in the new
range follow the logistic growth curve (Hobbs and Humphries 1995; Sakai et al.
2001; Strayer et al. 2006). Although some of this lag may be contributed to low
detection rates when a species has not yet been identified as a problem, there are
definitive examples of species exhibiting lag times whose establishment and subse-
quent spread has been well studied (e.g., Liebhold and Tobin 2006). The potential
length of a lag period is an important consideration when trying to predict the
spread of a species and its invasion potential. The duration of the lag time may vary
considerably with a species' reproductive strategy and propagule pressure
(Lockwood et al. 2005), its adaptability to a new environment, the identity, and
availability of vectors of spread (Barney 2006), or hybridization with other nonna-
tive or native species (Ellstrand, Schierenbeck 2000; Ellstrand and Schierenbeck
2006). Cheatgrass (
Bromus tectorum
), a species now very widespread in the
Western US, had a 30 year lag time before spreading rapidly (Mack 1981). In con-
trast, Brotherson and Field (1987) suggest that salt cedar (
Tamarix
sp.) had a lag
time of 100 years before becoming well established in riparian ecosystems through-
out the United States. These lag times are very different, and may not even cover
the full range that exists. Given these disparate times, integrating potential lag times
and rates of spread for invasive species into predictive models is not an easy task.
With low population levels, short-range movements are much more likely than
long-distance dispersal, at least for gypsy moths (
Lymantria dispar
) in the early
stages of invasion (Liebhold and Tobin 2006). Given that long distance dispersal
drives the invasion process (Hastings et al. 2005; Nehrbass et al. 2007), this finding
reinforces the lag effect. The almost 10 year lag time identified for gypsy moths
informs management decisions by indicating that time could be taken in eradication
of local infestations to ensure that the entire area is treated. As population increases,
Allee effects become less important and long-distance movement becomes much
more likely.
Spread rates will also not be constant through time, as demonstrated by the
gypsy moth lag effect, which resulted from interannual stochasticity in population
growth rates and Allee effects (Liebhold and Tobin 2006). Spread rates may be
affected by differences in climate between years (Neubert et al. 2000); perfect con-
ditions one year for a particular species will result in quicker spread and greater
abundance than poor conditions (e.g., drought, flooding, extreme cold). Additional
introductions of an already established and spreading species may also affect the
rate of spread by either new foci appearing on the landscape or a greater number of
propagules available for dispersal at an existing foci.
