Problems, Errors and Results
Problems:
There were a couple of major problems with obtaining the data for this project.
Half the time the project took was just the data preparation. It
took a surprisingly large amount of time to reprocess the spatial coordinates
to a usable form. Fortunately this was just a time factor and not a
major problem. The second major problem was that there was originally
supposed to be 3 years worth of samples available. However, due to oversight,
the spatial coordinates were not recorded for two years worth of data, and
so it was unusable. This left me with only the 1997 data to work with.
Finally, I also had plans to do a comparison between a local temperature
and precipitation map and the sample results to determine if there was any
correlation, but unfortunately I could not obtain that data in time either.
It appears that data at the scale I am working at is extremely difficult
to obtain.
Error Analysis:
The purpose behind using the two metrics to get the results was to see how
far the results from a single sample point can be extrapolated without losing
to much accuracy in the result. The 10 kilometer metric is very obviously
to large. The problem with it is that it blocks out a great deal of
the geographical diversity that has not been sampled in the Fraser Valley.
For example, if you look at the center of the final maps, there are
two clusters of sample sites that make a pair of east-west running lines.
One cluster is north of the Fraser River in the Mission and Hatzic lake
area. The second cluster is on the Sumas Flats in Abbotsford. Between
these two areas is Sumas Mountain which has a very different climate than
the floodplain to the north and south. The 10 kilometer metric overlaps
the results from Sumas mountain and thus we loose a great deal of accuracy.
For all we know, none of the species might be found in such a different
climatic area. The five kilometer metric shows a much more accurate
result in comparison. However, it also shows that many more samples
will be need to fill in the holes in the map, especially in areas where there
are major climatic changes such as Sumas Mountain.
Results:
Despite the difficulties in obtaining data we can still make several interesting
discoveries about the maps. First of all, samples of Lygus Hesperus
are concentrated in two locations. One population is in the vicinity
of Delta and White Rock, and a couple of insects were found out in Agassiz.
If we ignore the sample in Agassiz, this result is consistent with
an insect close to the northern end of its range since it is staying close
to the shoreline where the temperature is warmer. I suspect that the
insects out in Agassiz were either transported there by human means or they
represent a fragment of the population indicating that although they may
be capable of surviving in colder areas, they are being out competed by the
other two species.
The relationship between Lygus Elisus and Lygus Hesperus is an interesting
one. There was not a single sample of Lygus Elisus taken alone without
Lygus Shulli. First of all, this shows that there is competition between
the two species since they are being found during sweeps on the same plants.
There are many samples of Lygus Shulli that occur without any other
species. Lygus Shulli appears to be more common in this region than
Lygus Elisus. Perhaps Lygus Elisus is not as general in the habitats
it prefers when compared with Lygus Shulli. Or maybe Lygus Shulli is
just out competing Lygus Elisus for resources in many areas.
Based on the results of this project, I would conclude that an invasion of
Lygus Shulli into a greenhouse operation is most likely in this region. That
is not to say that the other two species will not invade greenhouses. However,
Lygus Hesperus is pretty much only found near the coast and so is most likely
to affect greenhouse operations in that area. Lygus Elisus is less
common than Lygus Shulli in the Fraser Valley, and so is less likely to invade
purely by a smaller population. On a personal note, this project shows
the difficulties of modeling biological systems. It is very difficult
to map the range of something that can run away when you try to catch and
identify it. It provided good experience with solving a spatial problem.
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