Diet of the Purple Swamphen in South Florida and Invasion

DIET OF THE PURPLE SWAMPHEN IN SOUTH FLORIDA AND INVASION

PATHWAYS OF NONNATIVE AVIAN SPECIES IN FLORIDA

Corey Callaghan

A Thesis Submitted to the Faculty of

The Charles E. Schmidt College of Science

In Partial Fulfillment of the Requirements for the Degree of

Master of Science

Florida Atlantic University

Boca Raton, FL

August 2015

ACKNOWLEDGEMENTS

I wish to express the utmost gratitude to those who have helped me through the process of writing this thesis. In particular I would like to thank my advisor, Dr. Dale

Gawlik for his persistence and encouragement throughout the writing process. He helped me realize that you truly do only “get out of it what you put into it”. He also forced me to

“get in the weeds” on various portions of analysis and writing and I am very grateful for this as I feel I come away with a greater understanding. Not only did he foster my help in writing this manuscript, but also helped push and challenge my thinking about ecology as a whole. I am grateful to the Florida Fish and Wildlife Conservation Commission for providing funding for the Purple Swamphen work. Lastly, I thank members of the Gawlik lab who were willing to help any step of the way, share their expertise, and some of whom were willing to read various drafts of this thesis.

ABSTRACT

Author: Corey Callaghan

Title: Diet of the Purple Swamphen in South Florida and Invasion Pathways of Nonnative Avian Species in Florida

Institution: Florida Atlantic University

Thesis Advisor: Dr. Dale Gawlik

Degree: Master of Science

Year: 2015 The spread of nonnative invasive species has become the second greatest threat to global biodiversity, making management of invasive species a critical component of the conservation of biodiversity worldwide. Managers and conservation biologists often lack basic life history data, as well as quantitative and theoretical models to predict risk of invasion or other negative effects. I contribute information to both categories by providing life history information (diet and morphology) of the Purple Swamphen

(Porphyrio porphyrio) and by characterizing the invasion pathways that nonnative avian species in Florida follow. I found Purple Swamphens are predominantly eating and selecting for Eleocharis cellulosa. Additionally, there is a large amount of variation in nonnative avian species’ propensity to colonize natural habitat and the time it takes to do so. Nine out of 15 species investigated colonized natural habitat and the time it took them to do so ranged from 8 to 41 years. It is through a combination of various techniques that ecologists will begin to fully understand the importance of studying nonnative species as well as reducing the impact that nonnatives have on native ecosystems. v

DIET OF THE PURPLE SWAMPHEN IN SOUTH FLORIDA AND INVASION

PATWHAYS OF NONNATIVE AVIAN SPECIES IN FLORIDA

List of Tables ...... viii

List of Figures ...... x

Chapter 1: Introduction ...... 1

Chapter 2: Diet and Selectivity of the Purple Swamphen in South Florida...... 3

Background ...... 3

Methods...... 6

Study Area ...... 6

Food Item Abundance ...... 6

Selectivity ...... 8

Physical Characteristics ...... 10

Results ...... 11

Food Item Abundance ...... 12

Selectivity ...... 13

Physical Characteristics ...... 13

Discussion ...... 14

Food Item Abundance ...... 14

Selectivity ...... 17

Physical Characteristics ...... 18

Conclusion ...... 18

Chapter 3: Invasion Pathways of Nonnative Avian Species in Florida ...... 31

Background ...... 31

Methods...... 35

Study Species ...... 35

Data Analysis ...... 35

Spatial Extent ...... 35

Average Count ...... 36

Habitat Classification ...... 37

Statistical Analysis ...... 37

Spatial Extent ...... 37

Average Count ...... 38

Results ...... 38

Discussion ...... 40

Conclusions ...... 43

Chapter 4: Synthesis ...... 56

Appendices ...... 58

Appendix A ...... 59

Appendix B ...... 63

Appendix C ...... 64

References ...... 65

vii

LIST OF TABLES

Chapter 2: Diet and Selectivity of the Purple Swamphen in South Florida

Table 1. A modified Braun-Blanquet Scale showing the cover class used for the

corresponding range of cover...... 24

Table 2. A summary of the morphological characteristics collected from a total of 85

Purple Swamphens from the three different study sites in

south Florida, 2014...... 25

Table 3. ANOSIM test for differences in morphology between Stormwater Treatment

Area 1W, Water Conservation Area 2B, and Lake Okeechobee across all sex

groups in south Florida, 2014. The global R statistics is accounting for all three

sites while the pairwise groups demonstrates that STA1W is most different than

WCA2B...... 26

Table 4. Biomass estimates of food items in Purple Swamphen stomachs from

Stormwater Treatment Area 1W, Water Conservation Area 2B, and Lake

Okeechobee in south Florida, 2014. The numbers in parantheses indicate the

sample size from the corresponding area...... 27

Table 5. ANOSIM test for differences in Purple Swamphen diet among Stormwater

Treatment Area 1W, Water Conservation Area 2B, and Lake Okeechobee in

south Florida, 2014...... 28

Table 6. Dissimilarity between study sites in diets. Pairwise groups into contributions

from each food item recorded for Stormwater Treatment Area 1W, Water

viii

Conservation Area 2B, and Lake Okeechobee in south Florida, 2014. Food

items are listed in order of decreasing contribution...... 29

Table 7. Percent cover average using the midpoint of the Braun-Blanquet scale of the

plant species sampled in Water Conservation Area 2B, south Florida, 2014. A

total of 10 points were sampled with three different plots at each point. The

average of the 10 points at each hierarchical level is shown in the table...... 30

Chapter 3: Invasion Pathways of Nonnative Avian Species in Florida

Table 1. Species included in the study, along with their scientific name, family

representation, and Alpha Code, using the conventional alpha code rules used

by the American Ornithologist Union...... 54

Table 2. The invasion pathways of 15 nonnative avian species in Florida. Lower AICc

values indicate a better fit with that curve type. The asterisk indicates the curve

of best fit...... 54

Table 3. Number of years for a species to disperse from urban to natural habitat for those

species that were determined to occupy natural habitat based on the criteria

presented in the methodology...... 55

LIST OF FIGURES Chapter 2: Diet and Selectivity of the Purple Swamphen in South Florida

Figure 1. A map of south Florida, showing the three locations that Purple Swamphens

were collected, as well as the initial introduction location and the general spread

of the swamphens, 2014...... 20

Figure 2. An MDS plot showing the morphometric similarity/dissimilarity of individual

Purple Swamphens from each of the three study locations in

south Florida, 2014...... 21

Figure 3. An MDS plot demonstrating the similarity/dissimilarity of Purple Swamphens

diets for the three different study sites in south Florida, 2014...... 22

Figure 4. Mean food type selectivity (Chessons’s index, αi; SD) across all 32 individuals

from Water Conservation Area 2B for each of the three plots sizes. All values

for spikerush are greater than 1/m which indicates selection of spikerush prey

type at all levels...... 23

Chapter 3: Invasion Pathways of Nonnative Avian Species in Florida

Figure 1. A schematic representation of the invasion pathway (Duncan et al. 2003)...... 44

Figure 2. A conceptual model of the four possible pathways that a nonnative species may

follow. (1): Non-sustained establishment occurs when the bird is introduced and

established but the establishment is not sustained through an extended period of

time. (2): Urban-restricted establishment occurs when the bird becomes

established in the urban habitat but fails to disperse into natural habitat. (3):

Urban-threshold establishment occurs when the bird first establishes in the

urban habitat, increasing its population size to a threshold and then dispersing

into the natural habitat. (4): Abrupt dispersal establishment occurs when the

bird increases its population size simultaneously in urban and

natural habitat...... 45

Figure 3. A map of Florida and the designated urban area in red. The remaining area is

deemed natural habitat. The map was created using the U.S. Census Bureau’s

cartographic boundary file...... 46

Figure 4a. – 4f. Change in area occupied for 15 nonnative species in Florida. Area was

regressed on effort in order to adjust area for an increase in effort, and hence the

residuals are shown. If a vertical line is present it indicates when that bird

entered the natural habitat...... 47

Figure 4g. – 4l. Change in area occupied for 15 nonnative species in Florida. Area was

regressed on effort in order to adjust area for an increase in effort, and hence the

residuals are shown. If a vertical line is present it indicates when that bird

entered the natural habitat...... 48

Figure 4m. – 4o. Change in area occupied for 15 nonnative species in Florida. Area was

regressed on effort in order to adjust area for an increase in effort, and hence the

residuals are shown. If a vertical line is present it indicates when that bird

entered the natural habitat...... 49

Figure 5a. – 5f. Average count per checklist of 15 different nonnative species in Florida

since 2002, the inception of eBird...... 50

Figure 5g. – 5l. Average count per checklist of 15 different nonnative species in Florida

since 2002, the inception of eBird...... 51

Figure 5m. – 5o. Average count per checklist of 15 different nonnative species in Florida

since 2002, the inception of eBird...... 52

Figure 6. A modified representation of the invasion pathway as presented by Duncan et al

2003, with expansion of the ‘Spread’ stage to include spread to natural habitat

and spread within urban habitat...... 53

xii

CHAPTER 1: INTRODUCTION The spread of nonnative invasive species has become the second greatest threat to

global biodiversity (Simberloff et al. 2005). Nonnative or exotic species are termed

invasive once they have demonstrated negative ecological or economic impacts (Avery

and Tillman 2005). Negative ecological impacts may arise from indirect and direct

competition for food or nesting sites, transmission of diseases, altering of habitat,

hybridization, and altering the ecological food web. In addition to ecological problems,

nonnative species may cause economic problems, such as the removal of Monk Parakeet

nests from power lines (Avery et al. 2002).

These negative consequences makes the management of invasive species a critical

component for the conservation of biodiversity worldwide. The large number of invasive species and the pace of new invasions make it evident that stopping all introductions is

not possible. The success and increase of invasive species in the United States has been challenging for policy makers (U.S. Fish and Wildlife 2006) and conservation biologists.

However, effective management tools are possible. Typically only a small proportion of

introduced species become abundant and significantly impact local populations (Duncan

et al. 2003a). As globalization increases, the development of criteria to determine the

impact invasive species will have on natural ecosystems is critical (Blackburn et al.

2009).

Nonnative and invasive species stretch across all taxa, however I chose to focus on avian invaders as they are well-studied, historical data is available, and are a common

conservation concern. Surprisingly, avian species receive little attention as biological invaders (Blackburn et al. 2009), partially due to their charismatic nature (Herring and

Gawlik 2007).

While there are advantages in studying avian species, there are still two difficulties in using them for invasion studies. First, the high rate at which nonnative bird species are found and established can create difficulties in gathering the appropriate information to make informed management decisions. For example, in 1992 there were

146 nonnative avian species documented in Florida (Robertson and Woolfenden 1992), by July 2014 that number had risen to 225 species (Pranty, pers. comm.). Second, nonnative avian species are often studied to a lesser degree in invasion studies because they closely associate with human-altered or urban habitats (Blair 1996, Duncan et al.

2003a) and therefore are thought to be less detrimental to natural habitats.

Nonnative avian species are found throughout North America; however, I chose to focus my study on Florida because that state has one of the highest number of exotic birds (Pranty and Kimball 2011) and little is known about potential for many of them to become invasive. This lack of understanding is due to the absence of basic life history data as well as the lack of quantitative and theoretical models. I contribute information to both categories by providing life history information (diet and morphology) of the Purple

Swamphen (Porphyrio porphyrio) in chapter 2 and by characterizing the invasion pathways of nonnative avian species in Florida in chapter 3. Chapter 4 is a summary of the collective body of research in this thesis.

CHAPTER 2: DIET AND SELECTIVITY OF THE PURPLE SWAMPHEN IN SOUTH FLORIDA

BACKGROUND

The Purple Swamphen (Porphyrio porphyrio; hereafter swamphen), a member of the Rallidae family, ranges widely across Europe, Australia, Asia, Africa, and New

Zealand (Pranty et al. 2000, Pranty 2012); there are 12 described subspecies (Pranty et al.

2000). Like other Rallidae members, they are secretive birds that spend the majority of their time in marshes. However, they show a wide range of habitat breadth that includes the use of both freshwater and brackish wetlands dominated by emergent vegetation as well as the use of pastures and disturbed areas (del Hoyo et al. 1996, Freifeld et al. 2001,

Sanchez-Lafuente et al. 2001). Swamphen breeding strategies can be either monogamous or communal mating (Jamieson 1997), which can result in small or large aggregations, respectively, of swamphens during the breeding period.

In 1996, a wild population of Purple Swamphens was discovered in south Florida.

Thought to be escapees from a private collection, they are now considered an established part of the Florida avifauna (Pranty et al. 2000). Two of the 12 subspecies of Purple

Swamphens, the blue-headed and gray-headed subspecies, have been found in south

Florida, the gray-headed subspecies are most predominant (Pranty et al. 2000, Pranty

2012).

Since 1996, the swamphen has expanded its range to the northwest, from

Pembroke Pines in Broward County, through the Water Conservation Areas, the

Stormwater Treatment Areas, and Lake Okeechobee (Pearlstine and Ortiz 2009, Pranty

2013), a distance of approximately 60 km. In their native range, individual swamphens

can move more than 300 km to colonize new habitats and territories (Sanchez-Lafuente et

al. 2001). In one instance, an individual swamphen was photographed in southeastern

Georgia, suggesting that this individual may have dispersed a distance of more than 600 km (Pranty 2012). Their excellent dispersal ability raises concerns in Florida about further expansion of the species.

Swamphens are known to be predominantly herbivorous throughout their range

(Balasubramaniam and Guay 2008), but they are also opportunistic and have been

observed consuming a wide range of taxa, including birds, amphibians, reptiles, fish,

eggs, insects, arthropods, and mollusks (del Hoyo et al. 1996, Balasubramaniam and

Guay 2008). In their native range of Australia, swamphens were found to eat herbaceous

materials from the families Graminae (59%), Cyperaceae (17%), and Hydrocharitaceae

(11% Norman and Mumford 1985). Although little is known about their diet in Florida,

swamphens in Florida are found in places dominated by herbaceous wetland plants.

Because of this, it is reasonable to suggest that a subset of the plant species within their

range in Florida will comprise a large portion of their diet. Diet studies from other

continents suggest swamphens are generalists that exploit a variety of local plant species

(Johnson and McGarrity 2009), indicating that selective preference of plants may be low

in south Florida. However, anecdotally, the bird has been observed using copious

amounts of Gulf Coast Spikerush (Eleocharis cellulosa; hereafter spikerush) at Lake

Okeechobee, which suggests that swamphens could be selecting for this plant species.

The degree to which swamphens pose a threat to native fauna in Florida is

unknown. Impacts could be through direct or indirect competition with other birds. For

instance, swamphens are known to be aggressive towards the much larger Great Blue

Heron (Ardea herodia, Pranty et al. 2000); it is possible that swamphens have the same, or stronger, aggressive tendencies toward smaller birds. Swamphens have been observed preying on Black Swan (Cygnus atratus) eggs and cygnets in Australia

(Balasubramaniam and Guay 2008). In Florida, a swamphen was observed carrying a presumed Black-necked Stilt (Himantopus mexicanus) chick (Hardin et al. 2011). In addition, swamphens may consume foods used by native species (Pearlstine and Ortiz

2009). The degree to which diet overlap would impact other species is partly a function of the degree to which the swamphen is a diet specialist and how much its diet changes in

response to the hydrologic fluctuations that limit the populations of other wetland birds

(Kushlan 1986). The negative effect would be strongest if the species occurs at high densities and is highly selective for plants preferred by other animals.

The Florida Fish and Wildlife Conservation Commission (FWC) attempted to eradicate the swamphen, removing over 3,000 birds (Hardin et al. 2011), but was unsuccessful, which led to the swamphen being considered a permanent part of the

Florida avifauna. Hence, this species is likely still at an early stage in its invasion trajectory (Simberloff 2001), leaving wildlife management agencies with an urgent need for additional information on the resources the swamphen uses to fuel its population increase. More detailed information on the basic biology and life history information gaps for the swamphen in their invaded ecosystem is needed. In support of swamphen

management, I intended to (1) quantify the diet of swamphens found in south Florida, and

(2) determine the selectivity of food items by swamphens.

Finally, invasion of swamphens into novel habitats provides a unique opportunity to study the evolutionary process (Duncan et al. 2003b). Phenotypic or genotypic divergence from source populations, as well as any divergence among different Florida populations could provide insight into how invaders may be successful. Though not the primary focus of the project, morphological measurements were collected, which provide a comparison of morphology among Florida populations.

METHODS

STUDY AREA

The sample birds were collected by the FWC from three different sites across

south Florida; Stormwater Treatment Area 1W (STA1W), Water Conservation Area 2B

(WCA2B), and Lake Okeechobee (Fig. 1). From all three sites, the birds were collected

from emergent marshes.

FOOD ITEM ABUNDANCE

Following morphometric measurements, the proventriculus, gizzard, and

esophagus were removed, and carefully examined for any food items. The contents were

then stored in 70% ethanol. Prior to analysis of stomach contents, a macro and micro

level reference collection of plants from the WCA2B site was created; from which birds

were collected. Food items were identified in a hierarchical manner through a

macroscopic and microscopic level of sorting and identification (Ward 1968), described

below. The stomach contents from birds obtained at both WCA2B and Lake Okeechobee

were more intact, and therefore, more reliably identified macroscopically and microscopically than were contents from STA1W.

Stomach contents were first sorted at the macroscopic level by aggregating items with the same texture and structure visible to the naked eye. The remaining contents of smaller plant particles, termed homogenate, were retained for subsequent microscopic analysis. Prior to analysis, I followed Dusi’s (1949) method of slide preparation to create a reference collection at the microscopic (cellular) level. This material also appeared to be homogenous but was more masticated and lacked structures large enough to distinguish with the naked eye. The microscopic analysis was initiated by spreading the homogenate evenly across a 10 x 10 grid with 100 cells that were 0.8cm x 0.8cm each.

Ten cells were randomly selected and the contents transferred onto a slide for microscopic identification (5X and 10X variable power) based on cellular structure. In addition, the macroscopic identification was verified microscopically by randomly selecting five items from macroscopic subsets and confirming the identification at the cellular level.

After food items were sorted and identified, they were placed in a drying oven at

55ºC until they reached a constant weight (Free et al. 1971), approximately 48 hours.

Following drying, each macroscopic subset, as well as the homogenate, was weighed. To determine the dry mass of each food item in the homogenate, the proportion of each food item identified in the subsamples was applied to the dry mass of the homogenate as a whole.

It has been shown that using an aggregate percentage approach is advantageous compared to using an aggregate volume approach (Swanson et al. 1974). Therefore the

former method was followed and the diet data, nested by site, is presented as (1) the

average percent of dry weight, (2) the percent occurrence of food items, and (3) the

percent occurrence in the swamphens or how many swamphens consumed a particular

item from that particular area (Prevett et al. 1979). The average percent of dry weight is

defined as ΣWi/N, where Wi is the weight of the ith food item expressed as a percentage

of all food items in the sample and N is the total number of swamphen samples for a

particular site. The percent occurrence of food items is defined as ΣFi/ΣFs and the percent occurrence in the swamphens is defined as ΣFi/N; where Fi = occurrence of food item i in

a sample, and Fs = number of food items in a sample.

Differences in diet were investigated by performing a Multi-Dimensional Scaling

(MDS) ordination with a Bray-Curtis similarity matrix. From there, an analysis of

similarity (ANOSIM) was performed to test for significant differences among sites. This

ANOSIM provides a global R value that indicates the degree of discrimination among

sites that may or may not exist. Lastly, a similarity percentages (SIMPER) procedure was

done to indicate the percentage each food item contributes to any differences that may

exist among sites. All techniques were performed using PRIMERv6 (Clarke and Gorley

2006).

SELECTIVITY

To determine the degree to which swamphens were selecting or avoiding

particular food items in south Florida, the relative percentage of available food types in

the environment was compared to those consumed by swamphens. This analysis was

done only in WCA2B. This analysis assumes that the plants detected and measured in the

environment were also detected, and potentially eaten, by swamphens. Thus, a vegetation

sampling area defined by the approximate spatial ranges of the swamphens that were collected for our study was carefully delineated. The spatial range was determined by plotting the coordinates of the locations from which each bird in the study was initially flushed. A 1.03 hectare buffer was applied to each location, which represents the average size of the home range of the Purple Gallinule (West and Hess 2002), a congener of the

Purple Swamphen; the home range of the swamphen in Florida is unknown. The outermost edges of all the buffers were connected to form a minimum convex polygon that delineated the extent of the area used for sampling vegetation. Twenty random points were generated within this defined area and considered a priori, that each point represented the northeast corner of three nested vegetation sampling plots. The three plots were 5m x 5m, 3m x 3m, and 1m x 1m in size and all utilized the same northeast corner

(Ross et al. 2003). Three different sized plots were selected because habitat selection is a hierarchical process and the scale at which swamphens might select food items is unknown. Within each of these subplots, I estimated the percent cover of each species found using a modified Braun-Blanquet scale (Mueller-Dombois and Ellenburg 1974).

The Braun-Blanquet scale uses scores of 1-5 to represent binned categories of percent cover (Table 1). The number of random sampling points was determined by identifying the point at which no new species of plants were detected. Vegetation was sampled at 10 random points, but no new species were added in the final four plots; thus six random points were adequate to characterize the available plant species (Cain 1938).

Chesson’s index of selectivity was used (Chesson 1978) to investigate whether swamphens showed preference towards any particular plant species in WCA2B.

Chesson’s index quantifies selectivity and determines food preference by comparing the

proportions and distribution found in the environment to those found in the diet. This

technique assumes that prey abundance is large compared to the amount of food

consumed. Also, it assumes that the ability of the organism to consume a particular item

is equal for each item (Chesson 1983). The index is calculated by using the formula:

/ , 1,...., ∑ /

where αi is the selectivity index for prey type i; ri is the relative abundance of prey type i

consumed by the swamphen; pi is the percent of prey type i in the environment calculated

from the vegetation surveys; and m is the number of prey types available in the

environment (m=7 prey types which were encountered during the vegetation surveys). In

order to interpret Chesson’s index, values of αi are related to 1/m. Random feeding occurs

when αi = 1/m. Preferential selection of a prey type occurs when αi > 1/m, and avoidance

of a prey type occurs when αi < 1/m. The αi was calculated at the individual level and

then the mean indices of all individuals were taken, providing a mean selectivity index

(Rudershausen et al. 2005).

Vegetation available to swamphens in the environment was calculated as the plot

averages for the 5x5, 3x3, and 1x1 meter plot at each of the 10 random points. Percent

cover of each plant type was determined by converting each Braun-Blanquet value to the

midpoint of the corresponding percentage range.

PHYSICAL CHARACTERISTICS

In this effort, airboats flushed birds into the air where they were shot using a

shotgun and steel shot. At each location where birds were collected, GPS coordinates and

the following basic descriptive information was obtained: date and time, water depth, and vegetation type and height. Thirty birds were collected from Lake Okeechobee, of which

25 were intact enough to be used for morphometric analysis. Twenty-nine birds were

collected from STA1W, of which 28 were intact and included in the morphometric

analysis. Thirty-two birds were collected from WCA2B, all of which were included in the

morphometric analysis. Our samples of birds included only two juveniles, both collected

from Lake Okeechobee, out of a total of 87 collected birds. Therefore, I excluded them

from the analysis and a total of 85 birds were measured.

Body mass, bill length to gape, exposed culmen, bill width, bill depth, tarsus

length, wing chord, and tail length were measured for each bird carcass (Pyle et al. 2008).

A pectoral score to represent the amount of fat present for each bird using a pectoral muscle score guide developed by the British Trust for Ornithology. Swamphens are sexually dimorphic (Marchant and Higgins 1993) and therefore sex determination is an important factor in considering morphologic differences among sites. Hence, feathers were plucked from each individual and sent to Animal Genetics, Tallahassee FL, to be genetically sexed. Four of the 85 birds were returned as inconclusive sex, therefore those individuals were not used in the multivariate analysis for differences in morphology between sites.

Morphometric differences among sites were investigated using PRIMERv6

(Clarke and Gorley 2006), software for multivariate statistics. An MDS, with a Euclidian distance similarity matrix, and an ANOSIM were used to determine if there were significant differences among groups (Clarke and Gorley 2006). The data were normalized before performing the analysis to account for the difference in morphological measurement types.

RESULTS

FOOD ITEM ABUNDANCE

The macroscopic level sorting procedure showed a low diversity of food types,

that was confirmed with microscopic analysis. Spikerush was the dominant plant consumed (Table 4), and comprised more than 70% of the average dry weight of birds’ diets from Lake Okeechobee and WCA2B, and about 50% from STA1W. Spikerush also occurred in 100% of swamphen samples from both WCA2B and Lake Okeechobee as well as 96% of samples from STA1W. Birds from STA1W had a more diverse diet, with a few different plants present in small amounts, than birds from other sites. Only 3.3% of the average dry weight was unidentified (Table 4). Although seeds were shown to be an important part of the diet in similar species (Mulholland 1982), seeds did not represent a large percentage of the total dry weight in our study. Additionally, there was no grit found in the stomachs of birds from WCA2B, whereas 25% and 59% of samples from the

Lake and STA1W, respectively, had grit present.

Only six birds consumed organisms from the class Insecta, but all specimens were

small and presumed to have been consumed incidentally while birds were eating plants.

Two birds consumed an animal from the order Lepidoptera. In WCA2B, 50% of

swamphens had mollusks in their stomachs, whereas only one sample from STA1W had

a mollusk, and no mollusks were found in samples from Lake Okeechobee.

The diet among the three sites were found to be significantly different (R=0.525,

p<0.1; Table 5 and Fig. 3). The SIMPER analysis uses the dissimilarity to demonstrate

the degree to which food items contribute to the difference of diet among sites. The three

pairwise tests were calculated for each site location (Table 6). Panicum seeds accounted

for 46% of the dissimilarity between WCA2B and Lake Okeechobee whereas they

accounted for 30% of the dissimilarity between STA1W and WCA2B. This is because

Panicum seeds were only recorded in the diets of those birds found in WCA2B.

Likewise, grit accounts for 42% of the dissimilarity between WCA2B and STA1W because WCA2B was the only location that grit was not found in the contents.

SELECTIVITY

The diversity of plant species found on vegetation surveys in WCA2B was low.

Seven different species of plants were identified throughout the ten plots. The plant

species were all emergent vegetation with the only exception being Utricularia spp.,

which occurred only below the water surface. The two most abundant emergent species

were Gulf-coast spikerush (Eleocharis cellulosa) and Nymphaea odorata, with the rest of

the plant species comprising a small percentage of the total (Table 7).

The swamphens in WCA2B were selecting for spikerush at each of the three

hierarchical levels (5x5, 3x3, and 1x1 meter) in which the vegetation surveys were

carried out (Fig. 4). I also found that swamphens were selecting Cladium seeds, but that

selection was weaker than selection for spikerush.

PHYSICAL CHARACTERSTICS

The physical characteristics of adult swamphens differed among study sites

(R=0.164, p<0.1; Table 3, Fig. 2). Additionally, the STA1W birds tend to be most

different than birds from WCA2B, whereas there is no difference between birds from

WCA2B and Lake Okeechobee (Table 3). This finding is also supported by the summary

statistics found in Table 2, as the largest mean body mass, bill length to gape, exposed

culmen, bill depth, bill width, and wing chord measurements came from the STA1W

study birds.

DISCUSSION

FOOD ITEM ABUNDANCE

Prior to this study, no formal diet study had been done on swamphens in Florida.

It was thought that they were predominantly herbivorous but also took some small invertebrate prey (Pranty 2012). Swamphens collected near STA1W during the eradication effort were found almost exlusively full of rice grains (Pranty 2012) and additionally, Hardin et al. (2011) observed a swamphen carrying something that was thought to be a Black-necked Stilt (Himantopus mexicanus) chick (Hardin et al. 2011).

These opportunistic observations suggest that swamphens could be generalists in Florida as they are thought to be in most of their native range.

A diet study of swamphens from their native range in Australia found that they primarily ate plants from families Graminae (59%), Cyperaceae (17%), and

Hydrocharitaceae (11%; Norman and Mumford 1985). My study confirmed that swamphens in Florida are also predominantly herbivorous. However, as opposed to a generalist diet, strong selection for spikerush, which belongs to the Cyperaceae family, was found. In two of the three study sites, swamphens consumed predominantly one plant species rather than a more even mix of several species. The heavier use of

Cyperaceae in Florida than in Australia likely reflects the available plants in the environment. However the narrower range of plant species consumed by birds in Florida demonstrates that across their range, swamphens have the ability to specialize to different degrees on specific plants.

The ability to specialize on specific plants raises concern in south Florida that swamphens may depredate rice crops. Swamphen stomachs have previously been

collected bursting with rice grains (Pranty 2012) and it is known that large congregations

of swamphens occur in rice fields (Pearlstine and Ortiz 2009) in south Florida. If

swamphens specialize on particular plants, as they did with spikerush in WCA2B, then

those swamphens inhabiting rice fields could be selecting for rice grains, potentially leading to negative economic impacts to rice farmers.

Although swamphens are considered to be primarily herbivores, individual birds may feed on small animal prey such as mollusks, leeches, crabs, fish, frogs, birds and their eggs, and rodents (del Hoyo et al. 1996). This study found mollusks, caterpillars and insects present. Although a high percentage of animal matter was not found in the

diet of swamphens, caution is warranted because the birds were collected during a single

dry season so inferences about diet should be restricted to that period. By collecting the

birds in such a narrow timeframe (January to early April), I would have been unable to

detect seasonal switches from one food item to another could have been missed. For

instance, it has been noted that in their native range swamphens took Black Swan eggs

(Balasubramaniam and Guay 2008). In south Florida swamphens have acted aggressively

towards other avifauna including an observation of a swamphen carrying an unidentified

chick [likely Black-necked Stilt (Himantopus mexicanus)] (Hardin et al. 2011). However,

by collecting swamphens before the breeding season was fully underway for most south

Florida breeding birds, this type of predation and diet component could have gone

undetected. Indeed, the closest relative of the swamphen here in south Florida, the Purple

Gallinule, has a diet that varies greatly with seasonality (West and Hess 2002) and have

been shown to consume animal material such as arthropods, annelids, and mollusks,

greater than 50% of the time during spring and summer (Mulholland and Percival 1982), both seasons that were not investigated in this study.

Diet breadth and establishment success are positively correlated among exotic species (Blackburn et al. 2009). Therefore, it is surprising that swamphens had such a narrow diet. However, because the swamphens were well established once the study was conducted, it is possible that the swamphens initially had a wide diet breadth but underwent a narrowing of the diet breadth once they were successfully established

(Overington et al. 2011). This idea is also supported by the previously mentioned anecdotal observations of swamphens’ consumption in Florida earlier on in their invasion trajectory. This lends possible evidence towards Wright et al.’s (2010) ‘adaptive flexibility hypothesis’ in which they predict a decline in behavioral diversity during the

establishment of a population due to successful strategies being learned and passed on.

The related species Purple and Common Gallinules also eat more plant than

animal matter (Bannor and Kiviat 2002, West and Hess 2002). Both bird species have

been known to feed on exotic plants (Mulholland and Percival 1982), demonstrating that

they are generalists as well as being able to shift their diet in response to the available plant community. This ability to be a generalist throughout their entire range with the

additional ability to specialize on certain species are traits shared by both the swamphen

and gallinules; this could lead to a large diet overlap and competition between the exotic

swamphen and native species.

Grit, used to aid digestion, made up a larger proportion of the stomach contents of

birds from Lake Okeechobee and STA1W, 5% and 35% dry weight, respectively, than in

WCA2B where no grit was found. Moreover, two birds in STA1W had ingested a large

number of shot pellets, too many to be a case of incidental ingestion. I suspect that the

large amount of grit in the diet of birds from STA1W is related to some component of

their diet, possibly the higher amount of Typha ingested in this area. I considered the

possibility that grit was ingested incidentally while birds were feeding on the roots of the

plants, but this seems unlikely because the amount of grit ingested by some individual

birds was quite high (up to 96% dry weight; Table 4). STA1W experiences the heaviest

hunting pressure of the study sites, so presumably shot pellets are more available there

than the other study sites.

SELECTIVITY

Resource selection occurs in a hierarchical fashion with first-order selection being

the physical or geographical range of a species, second-order selection representing the

home range of an individual or group of individuals, third-order selection being the usage

of habitat components within a home range, and fourth-order selection being the usage of

particular food items (Johnson 1980). Based on anecdotal evidence, I hypothesized a

priori that swamphens were selecting for spikerush in the WCA2B site at the fourth-order

selection level, which was confirmed. However, vegetation at lower-order levels of

selection was not sampled so it leads to uncertainty whether swamphens were selecting

spikerush at those levels as well. In addition, I found weaker selection for Cladium seeds, which would vary seasonally in availability. I speculate that the selection for spikerush would be more consistent regardless of season.

It was beyond the scope of this study to compare selectivity across all three study sites; however, anecdotal observations of the low amount of spikerush available in Lake

Okeechobee and STA1W relative to the proportion in the diets suggest the birds may be exhibiting strong selection in these two areas as well as WCA2B.

PHYSICAL CHARACTERISTICS

Body size in birds is often related to habitat quality (Johnson 2007), suggesting that the STAs may provide better habitat for swamphens than the other sites. Given the short time that swamphens have taken to expand across the region, it is surprising to find the degree of difference in morphological measurements among the study sites. This pattern is puzzling because swamphens were clearly selecting for spikerush, but they were largest in STA1W, where spikerush made up the smallest proportion of their diet.

The strong selection for spikerush in the area where the birds were smallest suggests that factors other than plant species may play a role in habitat quality, or alternately, the benefit of spikerush is not reflected in body size but rather some demographic response, such as productivity. The trend in body size among sites is consistent with their trophic status, with the STAs being thought to generally have the highest water nutrient levels, followed by Lake Okeechobee and the WCAs, respectively. If swamphen habitat quality is determined by plant community characteristics and trophic status, then quantification of these effects could be used to model future range expansion in Florida.

CONCLUSION

This study provides a quantitative basis for the perception that the Purple

impact native species. Potential effects of resource competition could be evident for other species that rely heavily on spikerush. Spikerush is known to provide habitat for small fish and invertebrates as well as cover and habitat for waterfowl and other wetland wildlife. Some waterfowl will eat the tubers, seeds, or basal portions of rhizomes of the spikerush as well. In addition to potential ecological impacts, potential economic impacts are also noted, specifically to rice farmers in south Florida.

Figure 1. A map of south Florida, showing the three locations that Purple Swamphens were collected, as well as the initial introduction location and the general spread of the swamphens, 2014.

Figure 2. An MDS plot showing the morphometric similarity/dissimilarity of individual Purple Swamphens from each of the three study locations in south Florida, 2014.

Figure 3. An MDS plot demonstrating the similarity/dissimilarity of Purple Swamphens diets for the three different study sites in south Florida, 2014.

Figure 4. Mean food type selectivity (Chessons’s index, αi; SD) across all 32 individuals from Water Conservation Area 2B for each of the three plots sizes. All values for spikerush are greater than 1/m which indicates selection of spikerush prey type at all levels.

Table 1. A modified Braun-Blanquet Scale showing the cover class used for the corresponding range of cover. Braun-Blanquet scale Range of cover (%) 5 75-100 4 50-75 3 25-50 2 5-25

1<5

Table 2. A summary of the morphological characteristics collected from a total of 85 Purple Swamphens from the three different study sites in south Florida, 2014.

Morphological Water Conservation Area 2B (n=32) Lake Okeechobee (n=25) Stormwater Treatment Area 1W (n=28) Characteristic Min Max Mean SD Min Max Mean SD Min Max Mean SD Body Mass (g) 505 730 621 57 555 850 689 81 570 815 702 66 Pectoral Score 0 2 1 1 0 3 1 1 0 3 1 1 Bill Length to Gape (mm) 21.48 32.47 25.28 2.57 21.73 27.72 24.84 1.74 23.34 29.61 26.07 1.61 Exposed Culmen (mm) 25.59 39.85 33.68 2.87 32.49 38.41 34.73 1.72 32.02 39.41 35.45 1.91 Bill Depth (mm) 20.13 24.52 22.40 1.24 20.79 25.71 23.33 1.57 21.42 27.17 24.32 1.32 Bill Width (mm) 10.86 15.74 13.47 1.32 12.01 15.84 14.19 0.82 11.63 16.17 14.39 1.23 Tarsus Length (mm) 84.93 109.12 96.32 6.28 84.38 106.04 95.77 5.63 93.16 112.54 102.90 4.88 Wing Chord (mm) 22.3 25.9 24.0 0.8 22.4 25.0 23.7 0.8 21.5 26.7 24.5 1.3 25 Tail Length (mm) 7.3 9.2 8.2 0.6 6.9 8.7 7.7 0.5 7.2 9.4 8.2 0.5 Note: The number of decimal places present in the table corresponds to the level of accuracy that was achieved while measuring that particular morphological characteristic.

Table 3. ANOSIM test for differences in morphology between Stormwater Treatment Area 1W, Water Conservation Area 2B, and Lake Okeechobee across all sex groups in south Florida, 2014. The global R statistics is accounting for all three sites while the pairwise groups demonstrates that STA1W is most different than WCA2B. R Significant Number ≥ Pairwise Groups Statistic Level % Permutations Observed LKO, STA1W 0.154 0.8 999 7 LKO, WCA2B 0.098 1 999 9 STA1W, WCA2B 0.236 0.1 999 0

Global Test 0.164 0.1 999 0

Table 4. Biomass estimates of food items in Purple Swamphen (PUSW) stomachs from Stormwater Treatment Area 1W, Water Conservation Area 2B, and Lake Okeechobee in south Florida, 2014. The numbers in parantheses indicate the sample size from the corresponding area. Water Conservation Area 2B (32) Lake Okeechobee (24) Stormwater Treatment Area 1W (27)

Average % % occ. of % of Average % % occ. of % of Average % % occ. of % of Items in diet dry weight food item PUSW dry weight food item PUSW dry weight food item PUSW

Eleocharis cellulosa 79.6 27.8 100.0 72.5 44.4 100.0 49.3 32.9 96.3 Typha spp. 1.2 19.0 55.6

a Cladium jamaicense Seeds 9.4 22.6 81.3 p 3.7 8.3 p 3.8 11.1 Panicum spp. Seeds 5.3 14.8 53.1 Eleocharis spp. Seeds p 2.6 9.4 21.8 33.3 75.0

27 Typha seeds 3.6 2.5 7.4

Insecta sp. p 4.3 15.6 p 1.9 4.2 Lepidoptera sp. pp3.1 p1.33.7 Mollusk sp. 3.3 13.9 50.0 p 1.3 3.7

Grit 5.1 11.1 25.0 35.3 20.3 59.3 Shot pellets 7.1 2.5 7.4

Unknown plant matter 2.1 13.0 46.9 p 5.5 12.5 3.3 16.5 48.1 a The p indicates that the item was present in that instance but that it was less than 1.0%.

Table 5. ANOSIM test for differences in Purple Swamphen diet among Stormwater Treatment Area 1W, Water Conservation Area 2B, and Lake Okeechobee in south Florida, 2014. R Significant Number ≥ Pairwise Tests Statistic Level % Permutations Observed LKO, STA1W 0.31 0.1 999 0 STA1W, WCA2B 0.572 0.1 999 0 LKO, WCA2B 0.728 0.1 999 0

Global Test 0.525 0.1 999 0

Table 6. Dissimilarity between study sites in diets. Pairwise groups into contributions from each food item recorded for Stormwater Treatment Area 1W, Water Conservation Area 2B, and Lake Okeechobee in south Florida, 2014. Food items are listed in order of decreasing contribution. STA1W & LKO WCA2B & LKO STA1W & WCA2B cumulative % cumulative % cumulative % Food items dissimilarity Food items dissimilarity Food items dissimilarity grit 41.94 panicum seeds 46.57 panicum seeds 30.41 eleocharis 64.34 eleocharis 63.1 grit 57.66 shot pellets 75.46 eleocharis seeds 73.81 eleocharis 82.25 eleocharis seeds 83.86 grit 82.69 shot pellets 90.24 cladium Seeds 88.91 cladium Seeds 88.5 typha flower 93.67 unknown 93.75

Table 7. Percent cover average using the midpoint of the Braun- Blanquet scale of the plant species sampled in Water Conservation Area 2B, south Florida, 2014. A total of 10 points were sampled with three different plots at each point. The average of the 10 points at each hierarchical level is shown in the table. 5x5 3x3 1x1 Eleocharis cellulosa 10.5 9.3 9.0 Panicum spp. 1.3 2.5 1.0 Utricularia spp. 28.8 14.8 18.0 Nymphaea odorata 7.3 7.0 8.0 Cladium jamaicense 1.0 0.5 0.0 Typha spp. 1.5 1.5 0.3 Pontedaria cordata 1.5 1.5 0.3 Open water 80.0 80.0 77.8

CHAPTER 3: INVASION PATHWAYS OF NONNATIVE AVIAN SPECIES IN FLORIDA

BACKGROUND

The spread of nonnative invasive species is one of the greatest threats to global

biodiversity (Simberloff et al. 2005), therefore the management of invasive species is a

critical component for the conservation of biodiversity worldwide. The large number of

invasive species, the pace of new invasions, and the complexity of managing these

invasions (Buckley 2008) highlight the need for more effective management strategies.

Given that only a small proportion of introduced species become abundant and

significantly impact local populations (Duncan et al. 2003a) the development of criteria

to determine which species will invade, how they do so, and the impact they will have on

natural ecosystems is critical (Blackburn et al. 2009).

Once a nonnative bird becomes a permanent part of the biotic community an

important management question is what impacts that species may have on the ecosystem.

Unfortunately, most nonnative species are poorly studied and therefore it is difficult to

assess their environmental impacts. Even when impacts are documented it can be difficult

to assign cause to a particular species. For example, the spread of diseases or crop

damage by mixed blackbird flocks that include the nonnative European Starlings.

However, environmental or economic impacts are inevitable because the majority of

exotic birds are classified as either primarily harmful (56%) or have mixed impacts (39%;

Temple 1992).

Methods by which nonnative avian species may cause negative impacts include:

indirect and direct competition for food or nesting sites, transmission of diseases,

hybridization, alteration of habitat, and alteration of the food web (Temple 1992, Avery and Tillman 2005). For example, House Sparrows (Passer domesticus) harass or displace

many native species in North America including bluebirds, orioles, and swallows

(Laycock 1966). The competition between invasive House Sparrows or European

Starlings (Sturnis vulgaris) and the native Eastern Bluebird (Sialia sialis) is often cited as

a cause for the decline in bluebird numbers in eastern North America (Zeleny 1978).

Nonnative Ruddy Ducks (Oxyura jamaicensis) spread over Western Europe after being

introduced into the United Kingdom and now threaten the native, globally threatened,

White-headed Duck (Oxyura leucocephala) through hybridization (Hughes et al. 1999).

Additionally, introduced birds in island habitats often have a high tendency to consume

exotic plant fruits (Mandon-Dalger et al. 2004), which can facilitate exotic plant

invasions, thereby causing significant negative ecological impacts.

The majority of avian biomass and biodiversity exists in non-urban habitats (Blair

1996, McKinney 2002), which has led to “down-weighting” of the importance of

nonnative species in urban areas. This view is justified when nonnative species remain

confined to urban habitats, but there is no guarantee that this will be true indefinitely.

Urban areas act as a reservoir, supporting a population increase until a threshold is

reached at which point individuals disperse to surrounding natural areas. In this scenario,

the apparent confinement of the nonnative species to urban areas is an artifact of the

population threshold not yet being reached, due to known lag phases in invasive species

(Crooks and Soulé 1999). In other cases, the nonnative species quickly disperse to

natural areas (e.g., Herring and Gawlik 2007). In south Florida, the Sacred Ibis

(Threskiornis aethiopicus) was confirmed breeding in urban Miami-Dade and Palm

Beach counties, and believed to be restricted to the urban environment. However, in

2005, a decade after it was first sighted in south Florida, the species began a range

expansion into natural habitat (Herring and Gawlik 2008), stopping only after an

intensive eradication program was implemented (Calle and Gawlik 2011).

Before a nonnative species is termed invasive, it must undergo a series of stages that begin in the native range and end in the successful establishment in a previously unoccupied range. This process is termed the invasion pathway (Lockwood et al. 2007),

and includes four main stages: Transport, Introduction, Establishment, and Spread. Figure

1 is a schematic representation of the most widely accepted invasion pathway model

(Duncan et al. 2003b, Blackburn et al. 2009) which is derived from Williamson (1996).

Each stage in the invasion pathway acts as a filter in which only a small

proportion of species become invasive. Williamson (1996) found that roughly 10% of

species that are introduced become established and of those, only 10% become invasive.

Although the ‘tens’ rule is often debated in the invasion literature, it highlights the notion that the invasion process should be treated as a series of stages (Blackburn et al. 2009), with particular traits differentially affecting the probability of species transitioning through each stage in the invasion pathway (Blackburn et al. 2009).

In the current invasion pathway by Duncan et al. (2003b; Fig. 1), the spread from urban to natural habitat is not addressed. However, the pattern of species dispersing from urban to natural habitat is of unusual importance for management of invasive species because it identifies the threshold in time and space beyond which management will have

to include natural areas. Managing invasive species in natural ecosystems, intermingled with other sensitive species and with more limited access than urban areas, poses logistic constraints and requires a significant increase in resources compared to invasive species confined to an urban areas. I hypothesize four pathways that an established nonnative species in an urban area may take to reach (or not reach) natural habitat (Fig. 2): (1) The bird is introduced and established but the establishment is not sustained through an extended period of time (Non-sustained Establishment), (2) The bird becomes established in an urban habitat but does not disperse to natural habitat (Urban-restricted

Establishment), (3) The bird first becomes established in the urban habitat and then increases its population size to a threshold before dispersing into natural habitat (Urban- threshold Establishment). (4): The bird quickly disperses into the natural habitat and increases its population size and distribution simultaneously in urban and natural habitat

(Abrupt dispersal Establishment).

Many studies have investigated avian diversity in urban or suburban areas

(Palmer et al. 2008, MacGregor-Fors et al. 2011, Sandstrom et al. 2006) or on urban to rural gradients (Blair 1996, McKinney 2002), but fewer studies have done this with a focus on native and exotic species (van Heezik, 2008). Likewise, many ecologists have studied traits of nonnative species that may predict successful establishment in a novel ecosystem (Blackburn et al. 2009, Duncan and Blackburn 2003 and references within).

However, to my knowledge, this is the first study to investigate the pathway by which nonnative avian species disperse from urban to natural habitat. I tested the fit of my four hypothesized pathways (Fig. 2) to annual changes in the distribution and abundance of 15 avian species in Florida. Pathways were calculated from an annual measure of the spatial

range and from the average count of each species over time. Ultimately, this

understanding and theoretical framework could be applied to nonnative invasion

pathways in other parts of the world and adapted to other taxa.

METHODS

STUDY SPECIES

I chose to study nonnative avian species in Florida because that state has one of

the highest number of exotic bird species in North America and thus offers a rich

opportunity to study nonnative avian species (Pranty and Kimball 2011). I included in the

study 14 species (Table 1) that are considered established by the Florida Ornithological

Society (Greenlaw et al. 2014). A fifteenth species, the Egyptian Goose (Alopochen

aegyptiaca), was also included despite its exclusion from this list because it was only

recently considered established (Pranty and Ponzo 2014).

DATA ANALYSIS

I used eBird1, a large citizen science database housed at the Cornell lab of

Ornithology (Sullivan et al. 2009), to calculate an annual measure of abundance and

range for each target species. eBird is a repository for millions of bird records collected

daily, thereby providing the means for real-time tracking of the distribution, timing, and

abundance of avian species (Sullivan et al. 2009). Data records include a species name, abundance, time of observation, several measures of observer effort, and the spatial coordinates of the observation.

Spatial Extent

1 For a more in depth overview of eBird, its use, and its applications see Appendix A. 35

Although kernel density estimators are commonly used to calculate home range

size it was not the best approach in my study because (i) in the early years of eBird, some

species had sample sizes that were below the minimum (30) requirements (Seaman et al.

1999). (ii) Many species have relatively low abundances but wide, patchy distributions

throughout Florida. This means that the kernel estimates would have a difficult time

approximating the amount of area those species are using because they would capture the space between the points which are not being used. (iii) The interest in this study lies in investigating the use of urban or natural habitat, and kernel estimates are often more suited to calculating range size and does not appropriately investigate the fine level of habitat use in question.

I used the grid cell method (IUCN 2001, Klemann and Vieira 2013) to calculate area on an annual basis. This was done by overlaying a grid on the spatial eBird points of observation, the number of cells in which points fell being counted, and this number of cells multiplied by the area of the cell in order to provide a total area of occupancy. The size of the cell in this study is an important factor that influences the results of calculated area. A 1-km2 cell size was chosen to avoid overestimating values for the area of

occupancy (Klemann and Vieira 2013). This was done for each year, which differed by species, and created a plot with year on the x-axis and total area occupied by that species on the y-axis. This allows for the temporal distribution trends to be visualized on an annual basis and thereby comparisons drawn among different nonnative species.

Average Count

For each species, I calculated the average count per year across all checklists since 2002, the year that ebird was launched, that contained a record of the target species.

Habitat Classification

Habitat was classified as either natural or urban because the focus of this study

was to examine the potential spread from urban to natural areas. Urban habitat was

delineated with the United States Census Bureau cartographic boundary file (Fig. 3).

Rural areas are defined as all population, housing, and territory that does not fall within

an urban area (U.S. Census Bureau) and were used as a proxy for the “natural” habitat for

this study.

STATISTICAL ANALYSIS

Spatial Extent

The four pathways identified above (Fig. 2) were best described by three different

nonlinear functions. The non-sustained establishment pathway is most closely

represented by a log normal function. The urban-restricted establishment pathway as well

as the abrupt dispersal establishment pathway are best represented by a sigmoidal

function. These two pathways are differentiated based on whether a particular species

reached the natural habitat (abrupt dispersal) or not (urban-restricted) based on the

following criterion: a species was considered to be in natural habitat in a particular year if

at least 25% of its observations were from the natural habitat for at least the two previous

consecutive years in which 40 observations were recorded. Lastly, the urban-threshold

establishment pathway is represented by a double sigmoidal function. The pattern of each

species’ spatial distribution over time was fit to the functions representing the four pathway hypotheses identified above (Fig. 2). To account for an exponential increase in number of participants and their data in eBird, I analyzed the residuals of a regression of the area occupied against overall effort, as measured by cumulative time spent in the field

by all observers in Florida (Rudolf et al. 1961, Helsel and Hirsch 2002). Akaike

Information Criterion corrected (AICc) values were used to determine which curve most

closely fit the temporal pattern of the residuals for each species (Hurvich and Tsai 1989).

Curves were fit using Sigmaplot 13.0’s dynamic curve fitter.

Average Count

No statistical analyses were performed on the average count calculations. Instead,

they were used as a qualitative addition to the above analysis.

RESULTS

The 15 species analyzed represent nine different families and a broad range of

ecological traits. The most abundant family is Psittacidae (four species), which is not

surprising due to their abundance in the pet trade, followed by Columbidae and Anatidae, with two species each (Table 1). The number of observations that were included in

analysis ranged from 253 (Budgerigar) to 45,897 (Eurasian Collared-Dove). In total, there were 196,493 observations across the 15 species included in the study.

Nine out of the 15 species dispersed from urban habitat to natural habitat, whereas six species remained constrained to urban habitat (Table 2). Although most species moved from urban to natural habitat, this occurred much later on in their trajectory than I expected based on my hypothesized pathways. For instance, the only birds that entered the natural habitat before 2000 were Eurasian Collared-Dove (Fig. 4f), European Starling

(Fig. 4e), and Rock Pigeon (Fig. 4j; Table 3). The temporal variation among species in time it took to enter natural habitat from the urban habitat ranged from 8 (Purple

Swamphen) to 41 years (Budgerigar; Table 3). For the 9 species which entered the

natural habitat, it took an average of 24.1 years. This serves as an overview of dispersal

time to natural habitat, but the focus was on the variation in dispersal times and therefore

I do not account for the increase in eBird participants over time, as was done in the other

analyses.

Twelve out of the 15 species were found to have the closest fit to the sigmoidal function (Table 2) with 8 of the 12 species representing the abrupt dispersal function:

Budgerigar, Common Myna, Eurasian Collared-Dove, House Sparrow, Muscovy Duck,

Nanday Parakeet, Purple Swamphen, and Rock Pigeon. The other four species which represent the urban-restricted curve were House Finch, Monk Parakeet, Spot-breasted

Oriole, and White-winged Parakeet. The only birds that did not have a sigmoidal curve

(urban-restricted or abrupt dispersal) were the Egyptian Goose, European Starling, and

Red-whiskered Bulbul. Both Egyptian Goose and Red-whiskered Bulbul had the best fit for the non-sustained establishment curve, while the European Starling had the best fit

with the urban-threshold curve. The variation in results is seen among species, but also

within families. The Psittids were split between urban-restricted and abrupt dispersal

curves as Monk Parakeet and White-winged Parakeet were both restricted to urban

habitat while Budgerigar and Nanday Parakeets colonized natural habitat. Similarly,

Egyptian Goose are restricted to the urban habitat while Muscovy Duck occupy both urban and natural habitat.

I note that the European Starling, House Sparrow, Muscovy Duck, and Rock

Pigeon curves all look very similar with a long tail in the beginning, suggesting that they have been established for a long period of time, but not reported regularly by contributors to eBird.

The qualitative analysis of average count of the species shows a large variation in

abundance among the different nonnative species. The variation ranged from Nanday

Parakeet, whose highest average count per checklist was 51 to Spot-breasted Oriole

whose highest average count per checklist was 2. As expected, gregarious species such as

Rock Pigeon (Fig. 5e), European Starling (Fig. 5k), Egyptian Goose (Fig. 5d), Muscovy

Duck (Fig. 5i), Purple Swamphen (Fig. 5l), and Monk Parakeet (Fig. 5j) had a higher

average count per checklist than more territorial species such as the Common Myna (Fig.

5f), Spot-breasted Oriole (Fig. 5o), and Red-whiskered Bulbul (Fig. 5m).

DISCUSSION

The results of my study suggest that there is little reason to classify a nonnative

avian species as low risk, as is often done (Avery and Tillman 2005), because it occupies

only urban habitat. The majority of study species eventually moved into natural habitat,

taking on average 24.1 years to do so. The long lag time to get to natural habitat may justify a lower priority ranking for urban species; however, that ranking should be viewed as temporary, periodically revised upwards if other criteria suggest the species has potential to expand into natural habitat. My study differed from the “10% rule” regarding the invasion pathway process (Blackburn et al. 2009, Williamson 1996) because a much greater proportion of species dispersed to natural habitat (60%).

Given that my study found that 60% of species disperse to natural habitat and

species on average 24 years before dispersing from urban to natural habitats, I suggest that the ‘Spread’ stage in the current invasion pathway (Fig. 1) be expanded to include spread from urban to natural habitats (Fig. 6). This idea seems valuable because greater

avian biomass and diversity resides in natural habitat (Blair 1996) and therefore potential

for negative impacts (Avery and Tillman 2005) is greater in natural habitat.

Further, I suggest that management efforts should be aimed at (1) attempting to

contain nonnative avian species in urban environments and (2) prioritizing species that

are most likely to enter the natural habitat based on proposed pathways. This suggestion

is similar to the framework proposed by Forrest et al. (2009), in which they identify

borders to dispersal and establishment of alien species and prioritize gaps in those

borders as a management necessity. Likewise, ‘borders’ could be constructed around

urban habitat with a focus on managing nonnative species for containment within these

borders. This framework is similar to the U.S. Environmental Protection Agency risk

paradigm, which calls for an ‘analysis of exposure and effects’ as one of its three

principal elements (U.S. Environmental Protection Agency 1998). The analysis of

exposure is carried out through the probability of spread as well as timing (lag) and route

(pathway). The analysis of effects is coupled with exposure and on the premise that as

native avian biodiversity increases in natural habitats (Blair 1996, McKinney 2002, van

Heezik et al. 2008) the potential negative impacts of nonnative species (Temple 1992,

Avery and Tillman 2005) increase as well.

The variation in dispersal pathways within taxonomic groups found in this study confirms that there are fundamental differences among nonnative species in their abundance, ability to disperse to natural habitat, and the time it takes to disperse to natural habitat. The wide range in abundance was demonstrated by the Nanday Parakeet, which had a high average count of 51 individuals, and the Spot-breasted Oriole, which

had a high average count of 2 individuals. Territorial species such as Spot-breasted

Oriole, Common Myna, and Red-whiskered Bulbul had the lowest average counts while

gregarious species such as European Starling, Rock Pigeon, and Nanday Parakeets had the highest average counts. Additionally, there were differences among taxonomically-

related species. For example, the Monk Parakeet and White-winged Parakeet being

restricted to urban habitats whereas the Nanday Parakeet and Budgerigar, all four belong

to the same family, dispersed into natural habitats. Likewise, the Egyptian Goose was

constrained to urban habitat while the Muscovy Duck, also in Anatidae, occupied urban

and natural habitats. Lastly, there was a wide range in species’ dispersal rates from urban

to natural habitats, with the Purple Swamphen taking 8 years to spread and the

Budgerigar taking 41 years to spread.

Although it was beyond the scope of this study to determine the cause for the

differences in dispersion pathways, I speculate that they could be a result of individual

variation, plasticity, and behavioral adaptations, and thereby variation among species in

relation to their ability to adapt to novel environments (Sih et al. 2011). Habitat

preferences (Mills et al. 1989), species demographics, breeding strategies, brain size, diet

breadth, degree of sociality, preferred nesting sites, and sedentariness (Kark et al. 2007,

Sol et al. 2014) among other traits, have been used as predictors of species’ ability to

adapt to novel environments. I investigated 15 nonnative species that have already been

deemed established in Florida and by using this framework, the information gathered can

be applied to those areas in which these species are not yet established. Furthermore, I

investigated three parameters in this study (lag time, average count, and dispersal to

natural habitat) that could be used to predict which nonnative avian species disperse to

natural habitat. Based on potential exposure and effects (U.S. Environmental Protection

Agency 1998), those species which were always detected in low abundance and were constrained to the urban habitat (e.g. House Finch, Spot-breasted Oriole, and Red- whiskered Bulbul) should be given lower priority than a species found in relatively high abundance that quickly dispersed to the natural habitat (e.g. Purple Swamphen).

CONCLUSIONS

Although there is the potential for negative ecological impacts arising from nonnative birds within urban areas due to the use by native species (Moore and Simons

1992, Seewagen et al. 2010, Hostetler et al. 2005), the potential for negative impacts is likely higher in the natural landscape because native avian biodiversity is greatest there

(Blair 1996) . Managers and conservation biologists are faced with difficult decisions regarding allocation of funds and resources to put towards combatting nonnative species

(Andersen 2004, Mehta et al. 2007). Decisions need to be made to focus on combatting certain species over others, namely those which may have the greatest negative ecological impacts. Therefore, the ability to predict which nonnatives may enter the natural habitat and how quickly they do becomes an excellent screening tool. By utilizing the framework put forth in this case study and identifying traits that are associated with the species that disperse into natural habitat, it will be possible to develop a better understanding of nonnative avian species’ affinity to colonize natural habitat.

Figure 1. A schematic representation of the invasion pathway (Duncan et al. 2003).

Figure 2. A conceptual model of the four possible pathways that a nonnative species may follow. (1): Non-sustained establishment occurs when the bird is introduced and established but the establishment is not sustained through an extended period of time. (2): Urban-restricted establishment occurs when the bird becomes established in the urban habitat but fails to disperse into natural habitat. (3): Urban-threshold establishment occurs when the bird first establishes in the urban habitat, increasing its population size to a threshold and then dispersing into the natural habitat. (4): Abrupt dispersal establishment occurs when the bird increases its population size simultaneously in urban and natural habitat.

Figure 3. A map of Florida and the designated urban area in red. The remaining area is deemed natural habitat. The map was created using the U.S. Census Bureau’s cartographic boundary file.

Figure 4a. – 4f. Change in area occupied for 15 nonnative species in Florida. Area was regressed on effort in order to adjust area for an increase in effort, and hence the residuals are shown. If a vertical line is present it indicates when that bird entered the natural habitat.

Figure 4g. – 4l. Change in area occupied for 15 nonnative species in Florida. Area was regressed on effort in order to adjust area for an increase in effort, and hence the residuals are shown. If a vertical line is present it indicates when that bird entered the natural habitat.

Figure 4m. – 4o. Change in area occupied for 15 nonnative species in Florida. Area was regressed on effort in order to adjust area for an increase in effort, and hence the residuals are shown. If a vertical line is present it indicates when that bird entered the natural habitat.

Figure 5a. – 5f. Average count per checklist of 15 different nonnative species in Florida since 2002, the inception of eBird.

Figure 5g. – 5l. Average count per checklist of 15 different nonnative species in Florida since 2002, the inception of eBird.

Figure 5m. – 5o. Average count per checklist of 15 different nonnative species in Florida since 2002, the inception of eBird.

Figure 6. A modified representation of the invasion pathway as presented by Duncan et al 2003, with expansion of the ‘Spread’ stage to include spread to natural habitat and spread within urban habitat.

Table 1. Species included in the study, along with their scientific name, family representation, and Alpha Code, using the conventional alpha code rules used by the American Ornithologist Union. Common Name Scientific Name Family Alpha Code Budgerigar Melopsittacus undulatus Psittacidae BUDG Common Myna Acridotheres tristis Sturnidae COMY Egyptian Goose Alopochen aegyptiaca Anatidae EGGO Eurasian Collared-Dove Streptopelia decaocto Columbidae EUCD European Starling Sturnus vulgaris Sturnidae EUST House Finch Haemorhous mexicanus Fringillidae HOFI House Sparrow Passer domesticus Passeridae HOSP Monk Parakeet Myiopsitta monachus Psittacidae MOPA Muscovy Duck Cairina moschata Anatidae MUDU Nanday Parakeet Aratinga nenday Psittacidae NAPA Purple Swamphen Porphyrio porphyrio Rallidae PUSW Rock Pigeon Columba livia Columbidae ROPI Red-whiskered Bulbul Pycnonotus jocosus Pycnonotidae RWBU Spot-breasted Oriole Icterus pectoralis Icteridae SBOR White-winged Parakeet Brotogeris versicolurus Psittacidae WWPA

Table 2. The invasion pathways of 15 nonnative avian species in Florida. Lower AICc values indicate a better fit with that curve type. The asterisk indicates the curve of best fit. A priori Curve type Year Entered Species Urban-restricted Abrupt dispersal Urban-threshold Non-sustained Natural Budgerigar N/A *55.33 63.86 60.92 2012 Common Myna N/A *98.89 109.48 105.81 2007 Egyptian Goose 79.45 N/A 112.88 *67.12 N/A Euasian Collared-Dove N/A *218.02 228.16 220.90 1996 European Starling N/A 377.12 *318.03 378.47 1985 House Finch *149.56 N/A 161.40 166.06 N/A House Sparrow N/A *380.49 388.46 380.70 2000 Monk Parakeet *215.03 N/A 223.91 232.90 N/A Muscovy Duck N/A *257.03 265.81 257.95 2004 Nanday Parakeet N/A *175.36 185.31 176.34 2006 Purple Swamphen N/A *47.97 68.44 49.46 2007 Rock Pigeon N/A *314.83 323.16 317.13 1994 Red-whiskered Bulbul 60.39 N/A 68.41 *60.23 N/A Spot-breasted Oriole *143.84 N/A 152.30 146.58 N/A White-winged Parakeet *72.40 N/A 90.88 84.00 N/A

Table 3. Number of years for a species to disperse from urban to natural habitat for those species that were determined to occupy natural habitat based on the criteria presented in the methodology. Year of first record in Year of occupying Species eBird natural habitat Lag time Budgerigar 1971 2012 41 Common Myna 1986 2007 21 Euarasian Collared-Dove 1984 1996 12 European Starling 1968 1986 18 House Sparrow 1963 2000 37 Muscovy Duck 1974 2004 30 Nanday Parakeet 1983 2006 23 Purple Swamphen 1999 2007 8 Rock Pigeon 1968 1995 27 Mean (SD) 24.1 (10.89)

CHAPTER 4: SYNTHESIS

Basic life history information as well as theoretical models are equally important to assess the threat of nonnative species and thereby assist managers and conservation

biologists in their decision making. This thesis provides both types of information and

idealizes a framework in which we have the ability to make more informed decisions regarding the management of nonnative avian species.

First, I provided a quantitative analysis of the anecdotal perception that Purple

Swamphens in south Florida are utilizing spikerush as a main food resource. Given that spikerush is widespread and fairly abundant throughout Florida and the southeast U.S., it is not likely to limit the distribution of the swamphen in Florida. It is uncertain how this preference for spikerush and likely expansion of swamphens throughout Florida might impact native species. Potential effects of resource competition could be evident for other species that rely heavily on spikerush. Spikerush is known to provide habitat for small fish and invertebrates as well as cover and habitat for waterfowl and other wetland wildlife. Some waterfowl will eat the tubers, seeds, or basal portions of rhizomes of the spikerush as well. The combination of the Purple Swamphen’s diet and potential economic impacts to rice farmers make this species an excellent candidate for future studies as a model nonnative species in south Florida.

Additionally, I quantified the invasion pathways of nonnative avian species in

Florida and this is a model that could be adapted for nonnatives elsewhere. I found that

60% of the nonnatives analyzed dispersed to the natural habitat with wide variation

among the species included in the study in their abundance and how quickly they

disperse. Although there is the potential for negative ecological impacts arising from

nonnative birds within the urban areas, the potential for negative impacts is likely higher

in the natural landscape. Under this assumption the ability to predict which nonnatives

may enter the natural habitat and how quickly they do becomes important.

It is only through a combination of techniques that we can reduce the impacts of nonnative invasive species. This study used spatial extent, pathways, diet breadth, and diet preferences to quantify potential impacts of nonnative species. By utilizing case studies such as these and identifying traits that are associated with those species that do colonize natural habitat, a further understanding of nonnative avian species’ affinity to colonize natural habitat can be achieved. For instance, the diet breadth and preference as well as morphology are traits that were quantified for the Purple Swamphen through my work. Swamphens were found to be an abrupt disperser in the modelling portion of my work. By combining these two studies, we could gather information that may predict which nonnative species may follow a similar abrupt dispersal trajectory.

APPENDICES

Appendix A: A more in-depth view of eBird

In order to elaborate on the use of eBird, highlight some of the strengths, and

validate it as a data source I prepared this section.

The use of a citizen science project, such as eBird, as a data source allows for

very robust data collection over a vast geographic scale. However, citizen science

projects also have limitations because they rely on volunteer observer submissions. Some

limitations could include misidentified species, inaccurate data estimation, or data entry

errors. Limitations are curbed by implementing a variety of data control strategies. eBird

works by volunteer observers submitting bird records. When they do this they choose a

location on a map and based on the spatiotemporal coordinates for the date a list of species is presented to them. Next the observer records the type of observation such as traveling (the observer travels a specified distance), incidental (birds observed while bird- watching was not the primary focus), or stationary (birds observed from one location for a specified duration). The observer also records how much time was spent observing birds as well as distance traveled for that time period. For each species observed they record the number of individuals seen. All of this information is composed in one

“checklist” that is then submitted to the eBird database (Sullivan et al. 2009). Any entry that exceeds this plausible data is sent to an expert reviewer to review details of the sighting.

This attention to data collection in conjunction with the large volume of bird observations provides scientists with high quality data (Lagoze 2014). As the eBird database continues to grow, there are more scientists that are using this data to publish findings. In a recent study, eBird data was used to assess the geographic range of Black-

fronted Ground-Tyrants (Gibbons et al. 2013). Similarly, eBird data was used in a study

on population-level scaling of avian migration speed with body size and migration

distance for powered fliers (La Sorte et al. 2013).

When eBird first launched in 2002 (eBird) participation initially struggled and

therefore the development was tweaked to provide tools that would appeal to birders.

This included allowing birders to keep track of their observations, view their personal

lists, and compare their observations with others (Wood et al. 2011). Since these

revisions, the volume of data coming into eBird has increased exponentially for a decade

(Sullivan et al. 2014). This increase in users has resulted in a large collection of data and suggests that the citizen project has been successful, making it a valid data source.

However, this exponential increase in participation makes it more difficult to discern the results of this study. There is a large amount of bias in sampling intensity

throughout time. eBird does allow historical records to be entered into the database,

which allowed for this study to be conducted over a longer period of time. However, the

sampling intensity bias over time is still evident. Although this was taken into account

during the data analysis, it is something to be cognizant of and is difficult to fully account

for. For example, the graphs of the European Starling, House Sparrow, Muscovy Duck,

and Rock Pigeon all have a very similar beginning portion of their curve. This is best

explained by the fact that there was very little data on those species until eBird was

launched and therefore little variation. Although, there is the ability of users to enter

historical records, that takes time and energy and very few eBirders have exercised this

ability as of yet.

In the particular case of exotic birds, the listing and competitive nature of birders,

which eBird helps drive, could have some drawbacks. There is a varying level of interest

among birders in exotic birds and in particular the ‘listing’ of exotic birds. It ranges from

people who ‘count’ any exotic bird seen in the wild to other birders who apply the no

introduced birds (NIB) rule to their lists. However, many birders abide by the American

Birding Association’s (ABA) guidelines when it comes to listing exotic birds in which it

is only deemed countable when added to the official ABA checklist. eBird counts exotic

birds on peoples’ lists, which could lead to a difference in participation of birders in

terms of submitting checklists that include or exclude exotic birds. One may be less

willing to submit a checklist from an urban strip mall in which only exotic birds occurred,

particularly if that person’s interest in exotic birds is low. Additionally, if an exotic bird

is deemed ‘countable’ by a listing committee, the American Birding Association, then it

is possible an increase in interest could lead to an increase in submissions of observations of that species. Due to the nature of eBird; using birders’ competitive natures in order to

collect data, raises the potential drawbacks of data collection in regards to nonnative

birds.

When a birder submits a checklist to eBird they have two options for each species

recorded; (1) submit the count or number of that species or (2) submit an ‘x’ for that

species, which signifies presence of that species without specification of how many were

present. An individuals’ interest level in exotic birds, discussed above, as well as certain

demographic characteristics of the particular exotic bird could also play a role in the type

of submissions that get entered into eBird for that species. For instance, those species that

are gregarious and can be seen in large flock sizes, reaching 100s, are more likely to

receive an ‘x’ on a checklist instead of a count. Vice versa, birds that are generally territorial and occur in pairs or small groups are more likely to receive a count as opposed to an ‘x’. This is demonstrated in Appendix B in which European Starling and Rock

Pigeon, two highly gregarious birds, have some of the largest percentage of ‘x’ submitted, in contrast to House Finch and Spot-breasted Oriole which occur in small numbers or groups, have the fewest percentage of ‘x’ submissions. This is an important consideration as the value of eBird data increases as birders submit sightings with an abundance.

Appendix B: The species included in the study and the percentage of observations that received an x in the eBird database. An ‘x’ indicates the bird is present but does not include any indication of abundance. Percentage of Species Name observations that receive an 'x' Budgerigar 21.91 Common Myna 15.25 Egyptian Goose 5.39 Eurasian Collared-Dove 18.55 European Starling 23.97 House Finch 5.32 House Sparrow 19.90 Monk Parakeet 17.93 Muscovy Duck 16.45 Nanday Parakeet 13.30 Purple Swamphen 24.81 Red-whiskered Bulbul 20.31 Rock Pigeon 24.89 Spot-breasted Oriole 8.07 White-winged Parakeet 21.15

Appendix C: The percentage of observations, on average, originating from the natural habitat. Overall, nonnative birds were observed in the urban habitat more than the natural habitat.

120 COMY HOFI PUSW BUDG HOSP ROPI EGGO MOPA RWBU 100 EUCD MUDU SBOR EUST NA PA WWPA

20 Average Percent of Observations in Natural in Observations of Percent Average 0 2002200420062008201020122014

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