englishhollyspatialanalysis
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Adv. GIS Group ProjectMarch 13, 2015
Mehrgon Sanayei James Watson
Phil Van
GIS Analysis of Invasive English Holly in Saint Edwards State Park
Introduction
Invasive plant species can negatively alter and affect the natural habitat of native species.
The invasion of English holly (Ilex aquifolium) in the Puget Sound has become a problem due to
its rapid spread and range domination (Stokes et al, 2014). In this study we will examine
different characteristics of the species in Kenmore’s St. Edward’s Park. Using a GPS system, the
coordinates and details of individual English Holly plants were collected during projects from
2011-12, 2013, and 2014. Plants were identified, data was gathered, and were cut down as part of
the project to slow the invasion in the park and surrounding areas.
Through Geographical Information System software (ArcMap v10.2.2) this information
will be used to develop a map distinguishing the distribution of individuals based on age, and the
distribution of male plants in relation to females. We want to know if there is clustering
occurring based on age, and if there is any occurrence of clustering based on sex, or if there are
processes associated with the distribution of plants in the study area based on sex. In testing this,
we used a null hypothesis that there is a random distribution of holly in the study areas and
applied local and global analyses within ArcMap.
Methods
The data we used for this study was collected from the University of Washington Bothell
through the work of Professor David Stokes whom specializes in Environmental Ecology. The
data had been collected over a three-year period (2012, 2014, 2014) where he and his team
recorded observations including each individuals GPS coordinates, sex, age, and height.
To get accurate and representational results for the recorded population of English Holly we first
made boundary adjustments because the two groups were discovered during different time
periods and had large distance between them, and the data was not continuous as a result. We
feared that if we kept them as one, the degree of clustering and dispersion could be affected. We
created subpopulations we named area 1 and area 2 (Figure 3). We ran a Nearest Neighbor Test
for each area to describe how the global expected mean of the spatial point pattern varied across
space. This test produced statistics (R value, Z-score, P-test) that allowed us to determining the
distribution of each area.
In order to analyze the distribution of English Holly based on age, we first had to break
up the plant data into young and old. To do this, we has to classify what is young or old based on
the mean population age by calculating Z-scores in a new float field in the attribute table. Z-
scores less than zero were classified as young, and over zero were old plants. The mean center of
each age group per area was calculated using the select by area, select by attribute and mean
center tool. Mean center analysis was also done for the entirety of both study areas (Figure 6) to
show a general movement of the population based on age, however this analysis proved
unreliable since much of the area that included both study area 1 and 2 had no data. A cluster and
outlier analysis based on age was done as a second order analysis to determine whether or not
there was random distribution based on age. A global analysis using spatial autocorrelation
(Morans 1) was done in respect to age to again determine clustering patterns, this time at as a
first order analysis (Figures 6, 7, 8). Cluster analysis using inverse distance weighted spatial
autocorrelation (Morans I) was conducted on individuals observed to have had berries (Figure 9)
to determine if there was clustering occurring in each study area respectively, and to identify
females among the clusters.
Results
Results of the nearest neighbor test produced an R-value of 0.24 indicating a clustered
distribution. The Z score was -33.2 rejecting the null hypothesis that the distribution is random.
The local level cluster and outlier analysis based on age showed old plants clustered together in
area 1 (Figure 7) as well as old and young plants grouped together in area 2 (Figure 8). However,
only study area 1 had a Z-score and P-value that showed evidence to reject the null hypothesis
that distribution is random based on age (Z-score: 4.48, P-Value: .0000007) (Figures 7,8). The
mean center analysis showed differing population movements for area 1 and 2; Northwest and
southeast respectively (Figures 4, 5).
Figure 9 shows the local spatial autocorrelation analysis that was performed using data on
the presence of berries, indicating presence of mature females in relation to males. The Z-score
of 5.42 indicates we can reject the null hypothesis of a random distribution of females. Clusters
and outliers can be seen in Figure 9, all of which are female. The analysis confirms that there is
strong clustering occurring in the study areas, with some female individuals having dense
clusters of males surrounding them, while others could be found with low or non-existent
densities of males nearby.
Conclusion/Discussion
Through this study we were able to develop data that has been absent in regards to
controlling the invasive holly species throughout the Pacific Northwest. This research has
provided the initial basis of understanding regarding English holly distribution in St. Edwards
Park, and could potentially be elaborated upon further as a model for many other sites in the
Puget Sound region facing an invasion of English holly.
The clustering of holly based on age in area 1 leads us to believe it could have spread
from the south end of area 1 upwards, likely starting in the ecotone between the college campus
and the forest (Figure 7). Since the average ages of holly is much lower in area 1 than in area 2,
we are tempted assume that the population started in area 2 and spread northwards, however we
must have more data for the surrounding area in order to have more evidence for this assumption
(Figure 4, 5).
The presence of females surrounded by clusters of males (Figure 9) in both study areas is
an interesting finding. With both High-High Clusters and High-Low outliers (all points are
female individuals) we found clusters of male individuals. This allows for more optimized
pollination of females by nearby males, which will provide the highest capacity for berry
production. When the plant produces berries, it becomes more readily dispersed by animals,
particularly birds. If this is a pattern of colonization exhibited throughout the Puget Sound
region, targeting females in particular can help to manage resources and contain the spread of
English holly.
In the future the study could be expanded on in many ways. A digital elevation model can
be found or created to map the areas topography, and would aid in analyzing relationships holly
may have with elevation. Further analysis of aspect or other characteristics of light reaching the
canopy floor could be done using an aspect map or LIDAR data. This could be helpful in
analyzing relationships holly may have with light penetration. Also, future data collection of
English holly could be done to include sex without observing presence of berries, allowing for a
more thorough analysis of the patterns of spread based on sex.
Sources:
Figure 1 shows the Nearest Neighbor Test for area 1. The yellow dots represent all individuals in the area during the 2012 research.
Figure 2 shows the Nearest Neighbor Test for area 2. The yellow dots represent all individuals in the area during the 2013 and 2014 research.
Figure 3 shows the whole study area divided into study areas 1 (top) and 2 (bottom). The dark green square represents the old mean center for the whole population, and the light green for the young. Ages
were broken into two categories: young and old; tan and brown.
*Note* more data is needed outside of study areas 1 and 2 to give a more accurate representation of the whole population’s directional movement.
Figure 4 and 5 show study areas 1 and 2 respectively. Dark green dots are the mean center of the old Holly, while light green dots are the young mean center. Ages were defined over a spectrum from light
tan to dark brown.
Figure 6 shows the cluster and outlier analysis performed on the entire study area. It shows a high amount of older Holly clustering in area 2 as well as young clusters and young-old clusters in area 1.
*Note* due to the absence of data outside of study areas 1 and 2, we needed to do individual cluster and outlier analysis of each area separately. This map was included to show how scale can affect and/or
skew results. See Figures 7 and 8 for more accurate representation.
Figure 7 shows the study area 1 cluster and outlier analysis as well as spatial autocorrelation results. The extremely low P-value, along with a Z-Score outside the range of -1.98 to 1.98, supplies strong evidence
to reject the null hypothesis that distribution based on age is random in study area 1.
Figure 8 shows the study area 2 cluster and outlier analysis as well as spatial autocorrelation results. With a Z-Score inside the range of -1.98 to 1.98, and a P-value higher than .05; we fail to reject the null
hypothesis and must assume without further research that distribution is random based on age for study area 2.
Figure 9 shows the spatial autocorrelation (Morans I) analysis of areas one and two, based on presence of berries (only plants with visible berries were counted as female). An inverse distance weighted
measure was used for determining clustering. The Z-score of 5.42 indicates that we would reject the null hypothesis of a random distribution of individuals based on presence of berries, and shows a strong
clustering is occuring.
Works Cited
Stokes, David L., Elliott D. Church, David M. Cronkight, and Santiago Lopez. "Pictures of an
Invasion: English Holly (Ilex Aquifolium) in a Semi-natural Pacific Northwest Forest."
Northwest Scientific Association 88, no. 2 (2014): 75-93. Accessed March 6, 2015.
http://www.bioone.org.offcampus.lib.washington.edu/doi/abs/10.3955/046.088.0204
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