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