Biology Reference
In-Depth Information
the invading species, including changes in native species abundance and the struc-
ture of communities. Here, rusty crayfish have taken the role of most dominant
species from the two of the native crayfish fauna. These impact data may inform
management decisions in other locations where the invader establishes. It may also
be possible to use this historic data to parameterize models to predict future
invasions.
We extracted a time series county level dataset of invasive plants from the
INADERS on-line database (Rice 2006) to use for temporal analyses. This dataset
helped validate a simple forecasting model for use on species initially arriving in
the US. We also used this dataset to examine patterns of invasion through time in
the Pacific Northwest of the US (Stohlgren et al. 2008). These data showed that
invasions were continuing to increase through time. Both examples using existing,
coarse scale temporal data could be useful in informing management of issues
related to invasions by nonnative species.
6.3.2 Field Data
For invasive plant species, weed mapping is a very common technique used by
many resource management agencies. This technique involves a person in the field
with either a map and writing implement or a GPS unit that can be used to capture
coordinates for point locations or polygons of patches by physically traveling
around an area searching for a single species or a small suite of species. These data,
if captured through time with samples taken at the same locations, can be used to
track changes in species presence or absence or changes in abundance.
However, ecologists often lack “absence” data, meaning records of areas
searched for a particular species where it was not found. Knowing where a species
was not found is important for several different reasons. From a temporal stand-
point, we want to know when a species first arrives at a particular location, which
we are unable to do if we do not know it was absent last year and is present this
year. Without these data, spread rates are indeterminable. Additionally, many dif-
ferent statistical modeling techniques require absence locations along with pres-
ence locations. Characterizing unsuitable habitat for a species may be as important
as knowing where suitable habitat exists.
We also lack monitoring data, where we return to the same locations to map
species each year. This oversight makes it difficult to capture changes in species
distributions and abundance through time. It has the same temporal implications as
unrecorded absence data, where we do not know initial establishment because of
lack of time series data. These issues could be solved by adding recording what
locations were sampled to mapping protocols. For example, the North American
Weed Mapping Association has developed a weed mapping standard that is widely
used but only includes instructions for mapping locations where a species is present
(North American Weed Management Assocation 2002). A suggestion to modify the
standards to address the oversight of recording all sampled locations is to add a step
