In this dissertation, we explore the properties of correlation structure for spatio-temporal
point processes and a quantitative spatial process. Spatio-temporal point
processes are often assumed to be separable; we propose a formal approach for testing
whether a particular data set is indeed separable. Because of the resampling methodology,
the approach requires minimal conditions on the underlying spatio-temporal
process to perform the hypothesis test, and thus is appropriate for a wide class of
models.
Africanized Honey Bees (AHBs, Apis mellifera scutellata) abscond more frequently
and defend more quickly than colonies of European origin. That they also
utilize smaller cavities for building colonies expands their range of suitable hive locations
to common objects in urban environments. The aim of the AHB study is
to create a model of this quantitative spatial process to predict where AHBs were
more likely to build a colony, and to explore what variables might be related to the
occurrences of colonies. We constructed two generalized linear models to predict
the habitation of water meter boxes, based on surrounding landscape classifications,
whether there were colonies in surrounding areas, and other variables. The presence
of colonies in the area was a strong predictor of whether AHBs occupied a water
meter box, suggesting that AHBs tend to form aggregations, and that the removal of
a colony from a water meter box may make other nearby boxes less attractive to the
bees.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-08-8351 |
| Date | 2010 August 1900 |
| Creators | Kolodziej, Elizabeth Young |
| Contributors | Sherman, Michael |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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