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Grarock et al., The invasion process

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Using invasion process theory to enhance the understanding and

management of introduced species. A case study reconstructing the

invasion sequence of the common myna (Acridotheres tristis).

Kate Grarock* a, David B. Lindenmayerb, Jeff T. Woodc, and Chris R.

Tidemannd

a Fenner School of Environment and Society, The Australian National University,

Canberra, ACT, 0200, Australia

+ Invasive Animals Cooperative Research Centre, University of Canberra, ACT,

2617, Australia.

b Fenner School of Environment and Society, The Australian National University,


+ National Environmental Research Program, Department of Sustainability,

Environment, Water, Population and Communities, GPO Box 787, Canberra, ACT,

2601, Australia.

+Australian Research Council Centre of Excellence for Environmental Decisions

c Fenner School of Environment and Society, The Australian National University,

Canberra, ACT, 0200, Australia.

d Fenner School of Environment and Society, The Australian National University,


* Corresponding author

T: +61 4 07 612 614

F: +61 2 6125 0746

[email protected], [email protected], [email protected],

[email protected].


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Abstract

Research indicates that invasion is a multi-step process, where each stage is

contingent on the stage that precedes it. Numerous hypotheses addressing the factors

that influence each stage of the invasion process have been formulated, but how well

does this theory match what occurs in the natural world? We created a general

conceptual model for the invasion process based on invasion theory. Using a

composite 41-year data set, we then reconstructed the invasion sequence of the

common myna (Acridotheres tristis) to investigate the similarities between invasion

theory and this observed invasion. We observed a lag period before population growth

of 2.7 (±0.3) years, a maximum rate of population growth of 24.1 (±6.4) birds per km2

per year, a lag period before spreading of six years and an average spreading rate of

0.4 km per year. The length and duration of these stages correspond closely with what

invasion process theory would anticipate. We suggest that a conceptual model,

coupled with basic species, environment and event information, could be a useful tool

to enhance the understanding and management of invasions.

Keywords Exotic species; establishment; invasion dynamic; Indian myna; Sturnus

tristis; pest management.

1. Introduction

The number of introduced species is growing globally due to increases in trade

and transport (Ascunce et al., 2011; Hulme, 2006; Lockwood et al., 2005). These

introduced species can have devastating impacts on human health, on economies, and

on biodiversity (Gurevitch et al., 2011). In response, biological invasion research has


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grown exponentially over the past 50 years (Gurevitch et al., 2011). This research

indicates that invasion is a multi-step process, where each stage is contingent on the

stage that precedes it (Evans et al., 2010; Hulme, 2006; Kolar and Lodge, 2001) (Fig.

1). There are numerous hypotheses addressing the factors that influence each stage of

the invasion process (Duncan et al., 2003; Gurevitch et al., 2011), but how well does

this theory match what actually occurs in the natural world?

A firm understanding of the invasion process, and factors influencing the

success of each stage, is critical for decision makers who wish to prevent, eradicate or

control introduced species (Hulme, 2006; Sakai et al., 2001; Tobin et al., 2007). To

develop effective management plans, decision makers need to understand: (1) the

stage an invasion is in, (2) the length of time before the next stage is reached, and (3)

the most effective plan of management for a given stage. Early detection and action

are also important factors for successful management, with the cost of control rapidly

increasing as a species moves through the invasion process (Mack et al., 2000;

McNeely et al., 2003).

The two key elements of successful management: knowledge of a species

invasion sequence and rapid response to invasion; can often be in conflict. There is a

need to act quickly when managing introduced species (McNeely et al., 2003), but it

takes time to be informed about the best management action (Crooks, 2005). A lack

of knowledge about a species invasion sequence may lead to delays in management

action. Management also may be ineffective if the stages of the invasion process are

poorly understood. For example, in 1984 when the invasive marine alga Caulerpa

taxifolia (‘killer’ algae) was discovered at a small isolated site in the Mediterranean

Sea, the species invasion sequence (including the spreading rate and environmental

impact of the species) was poorly understood, leading to management inaction. This


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noxious marine algae spread rapidly, and in 2000, it covered more than 191 km of

coastline, with no sign of the spread abating (Meinesz et al., 2001). Conversely, when

C. taxifolia was discovered off the coast of California in 2000, knowledge of the

species invasion sequence prompted field containment within 17 days of detection

(Anderson, 2005). The eradication of this species was declared a success in 2006

(Williams and Grosholz, 2008).

A bold and costly management response can be futile if the species invasion

sequence is not understood. For example, one of the longest unbroken fences in the

world was built to exclude the European rabbit (Oryctolagus cuniculus) from the west

coast of Western Australia. However, the spreading rate of the European rabbit was

clearly underestimated, when in 1902, before completion of the fence, the species was

discovered inside the intended exclusion area (Ingersoll, 1964). Other introduced

species can be relatively benign and the management response should reflect this

(Davis et al., 2011). These (and numerous other) examples highlight why knowledge

of an introduced species invasion sequence is critical for timely and effective

management.

In this paper, we investigate the congruence between invasion process theory

and an observed species invasion sequence. At the outset of this study, we created a

general conceptual model (Fig. 1) of the six stages of the invasion process, drawing

on the extensive body of invasion research (see Methods: Theory Section 2.2 and

Supplementary Content 1). Our conceptual model provides a good starting point for

synthesis of theoretical and empirical data to inform understanding and management

of invasive species. However, all models are simple representations of more

complicated processes.


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We use a composite 41-year data set to reconstruct the invasion sequence for

the common myna (Acridotheres tristis) in the Australian city of Canberra. We then

compare how well this observed invasion corresponds with what invasion process

theory would predict. Finally, we discuss how our conceptual model (Fig. 1), coupled

with knowledge on species, environment and event attributes, could be used to

enhance the understanding and management of introduced species.

The introduction and subsequent spread of the common myna in Canberra is a

rare case where the entire invasion process has been well documented. Detailed

records of the location, date and number of birds released, in addition to long-term

bird surveys, enabled us to track the introduction, establishment, population growth

and spread of the species. The common myna has been introduced to many places

around the world and is listed in the top ‘100 of the world’s worst invasive alien

species’ (Lowe, 2000). However, little is known about the species invasion process,

despite growing concern and calls for management (Dhami and Nagle, 2009; Lowe et

al., 2011). Knowledge of the common myna invasion sequence will help inform

management of the species. However, it must be recognised that the invasion

sequence for a species may vary significantly in different locations.

Based on our conceptual model of the invasion process (Fig. 1), stages one to

three (transport, introduction and establishment) have already occurred successfully

for the common myna in Canberra. To compare invasion process theory with the

observed invasion of the common myna we needed to reconstruct the stages after

establishment and determine the answer to the following questions:

• Did the common myna exhibit a lag period before population growth and if so,

how long was this lag?


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• What was the maximum rate of population growth and maximum population

size?

• Did the common myna exhibit a lag period before spreading and if so how

long was this lag?

• How quickly did the common myna spread across Canberra?

2. Methods

2.1 Terminology

We defined an introduced species as any species that occurs outside its natural

range. An introduction occurs when a species arrives in a new location through

human-assisted means either intentionally (e.g. biological control) or unintentionally

(e.g. escape from captivity). Introduction effort is the number of individuals

introduced to the new location. Establishment occurs when an introduced species is

able to maintain a self-replicating wild population, thus an established species is one

capable of maintaining a self-replicating wild population.

2.2 Theory

Research suggests the invasion process is a series of stages with each stage

dependent on the preceding stage (Fig. 1) (Catford et al., 2009; Colautti and

MacIsaac, 2004; Duncan et al., 2003; Evans et al., 2010; Hulme, 2006; Kolar and

Lodge, 2001). However, impact may occur throughout the entire invasion process,

with widespread and significant impacts often occurring once the species has grown


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in numbers and spread throughout the environment (Hengeveld, 1989; Simberloff,

1997). Each stage of the invasion process is supported by a significant (although not

equal) amount of scientific theory (Duncan et al., 2003; Gurevitch et al., 2011)

(Supplementary Content 1).

The first stage of the invasion process is Transport (Fig. 1.1). Humans cause

most long-distance introductions (Ascunce et al., 2011; Hulme, 2006; Sakai et al.,

2001). Therefore, there has been a bias (selectivity) in the types of species chosen for

transport to new locations (Duncan et al., 2003). This bias is based on taxonomic

selectivity, geographic origin and species characteristics. For example, two thirds of

bird species introductions belong to six of the 146 bird families (Duncan et al., 2003).

Similarly, European settlement and trade has driven transport of species from Europe

(Duncan et al., 2003; Hengeveld, 1989). Species characteristics are also important

with many species selected for particular purposes, for example, hunting, agriculture,

aesthetic reasons (caged birds) or biological control (Duncan et al., 2003; Hengeveld,

1989).

The next stage of the invasion process is Introduction (Fig. 1.2). This stage is

closely related to transport, however, once a species arrives in a new location it either

needs to be released or escape (Ascunce et al., 2011; Hulme, 2006; Sakai et al., 2001).

There may be a Lag period before an introduced species becomes established and is

able to maintain a self-replicating wild population (Hengeveld, 1989).

The third stage in the invasion process is Establishment (Fig. 1.3). This stage

has been the focus of much research (Duncan et al., 2003; Fautley et al., 2012;

Gurevitch et al., 2011; Lockwood et al., 2005; Mack et al., 2000; Memmott et al.,

2005). Introduction effort is the strongest independent explanation for the

establishment success in many bird (Duncan et al., 2003), mammal (Fautley et al.,


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2012; Forsyth et al., 2004), reptile (van Wilgen and Richardson, 2012) and plant

species (Colautti et al., 2006; Lockwood et al., 2005; Pyšek and Richardson, 2007).

An invasion may then exhibit a Lag period before population growth (Fig. 1).

This period can last tens or even hundreds of years for some species (Hengeveld and

Van den Bosch, 1991; Rutz, 2008). A lag describes the period of time between the

initial establishment stage and discernible population growth and is a common feature

of many species invasions (Crooks, 2005; Hengeveld and Van den Bosch, 1991). A

lag can occur due to the time it takes for a species to adapt to, and thrive in, a new

environment (Blackburn and Duncan, 2001; Gurevitch et al., 2011; Mack et al., 2000;

Sol and Lefebvre, 2000; Wang and Wang, 2006). A relatively small and newly

introduced population is vulnerable to stochastic events, requiring time to build in

numbers and overcome the chance of extinction (Arim et al., 2006; Mack et al., 2000;

Partecke et al., 2004; Shigesada and Kawasaki, 1997). Crooks (2005) also states that

an apparent lag in population growth would be a normal feature of exponential

population growth.

The fourth stage of the invasion process is Population growth (Fig. 1.4). Key

factors influencing the rate of population growth are the environment and species’

attributes such as reproductive age, development time, and fecundity. An

understanding of population growth is integral to determining how populations will

react to various management outcomes (Hengeveld, 1989; Neubert and Caswell,

2000). Exponential growth can occur when a species reproduces rapidly and

individuals immigrate from surrounding areas, while logistic growth may occur when

a species reproduces at a slower rate and has limited immigration (Hengeveld, 1989).

An invasion may then exhibit a Lag period before spreading to new areas (Fig.

1). This lag period can range from a brief period of time (e.g. <1 year) to decades for


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some species (Hengeveld, 1989; Larkin, 2012; Mack et al., 2000; Wang and Wang,

2006). Dispersing animals may find it difficult to locate mates (an allee effect) or

suitable habitat in new areas and this may lead to a lag in spreading (Mack et al.,

2000; Shigesada and Kawasaki, 1997). These dispersing individuals are also

vulnerable to demographic, environmental and genetic stochasticity (Mack et al.,

2000; Shigesada and Kawasaki, 1997). Alternatively, a lag period before spreading

may be caused by slow population growth and a lack of dispersal by young (Duncan

et al., 2003; Gurevitch et al., 2011; Mack et al., 2000; Wang and Wang, 2006).

Stage five of the invasion process is Spread (Fig. 1.5). Spreading will often

continue until all suitable habitat is occupied (Shigesada and Kawasaki, 1997). A

wide range of factors influences a species’ ability to spread, such as dispersal ability

and resource availability (Fig. 1) (see Supplementary Content 1). However, spreading

can vary significantly between locations even within the same species (Gammon and

Maurer, 2002; Neubert and Caswell, 2000; Pyšek and Hulme, 2005).

The sixth stage of the invasion process is Impact (Fig. 1.6). Impact is the

effect of a species on the environment, ecosystem and/or other species. The impact of

a species can be hard to predict and reliable knowledge on the risk of impact is often

absent (Simberloff, 1997). Furthermore, species’ interactions with various

environmental conditions are complex and often compounded by factors such as

habitat fragmentation (Didham et al., 2005). An adverse impact elsewhere is a key

indicator that a species may have a negative impact in a new environment (Bomford,

2008; Lever, 2001). Although depicted as the final stage of the invasion process,

impacts can occur throughout the entire invasion process, with some species causing

significant (localised) impacts prior to spreading (Simberloff, 1997).


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2.3 Background on the study species

The common myna was first introduced to Melbourne (Australia) in 1862 as a

biological control for insect pests in market gardens (Long, 1981). The species was

then introduced to several locations along the east coast of Australia. The first

documented release in Canberra was a group of 12 birds in the suburb of Forrest in

1968 (Fig. 2). From 1968 to late 1971, 110 birds were released (Gregory-Smith,

1985).

2.4 General conceptual model of the invasion process

Our conceptual model (Fig. 1) details each stage of the invasion process and

the key species, location, or event factors identified by researchers as influencing a

species invasion sequence (see Supplementary Content 1). This conceptual model

provides a simple synthesis of theoretical and empirical data. We then used the

conceptual model to highlight the stages we needed to reconstruct for the invasion

sequence of the common myna in Canberra.

2.5 Data sources

To reconstruct the establishment, spread and population growth of the

common myna in Canberra, we used an article by Gregory-Smith (1985) and long-

term bird survey data from Canberra Ornithologists Group (COG). Gregory-Smith

(1985) recorded sightings of the common myna from 1969 to 1984. COG established

the Canberra Garden Bird Survey (GBS) that commenced in 1981. GBS volunteers


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were responsible for selecting a 3.1 ha area to survey. Surveyors recorded the

maximum number of each bird species seen or heard in a site at any one time over a

seven-day period. Veerman (2003) provides an in-depth description of the survey

procedures. Survey participation has been substantial, averaging approximately 63

sites per year with each participant averaging 41 survey weeks annually (Veerman,

2003). As the COG survey pre-dates this study, we had no control over survey

procedure, location of survey sites, or the surveyors involved in gathering the data.

However, the data are a valuable resource provided that limitations are recognised and

analysis conducted accordingly.

2.6 Reconstructing establishment and spread

Gregory-Smith’s (1985) article and the GBS data produced a 41-year data set

spanning 1968-2009, sharing three common years (1981-1982, 1982-1983, 1983-

1984). Where discrepancies occurred, we gave priority to the GBS data due to it using

a more structured survey approach. Gregory-Smith (1985) defined establishment as

being ‘one to two birds present throughout the year or breeding’. We defined

establishment for the GBS as occurring when two or more birds were reported at any

site within a suburb, for at least three months of the year.

Using ArcGIS 10® (ESRI, 2010), we mapped the yearly establishment of the

common myna from 1968-1969 through to 2008-2009. To provide a visual

representation of this spread we produced maps of establishment across Canberra for

1971-1972, 1978-1979, 1985-1986, 1992-1993, 1999-2000 and 2006-2007 (Fig. 3).

We calculated the cumulative total area occupied by the common myna each

year and fitted a smoothing spline (Green and Silverman, 1994) relating the square


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root of the area occupied by year (± SE) (Fig. 4). The square root transformation of

area represented the average radial distance of invasion when range is expanding in

approximately concentric circles (Hengeveld, 1989; Mundinger and Hope, 1982;

Okubo, 1988). We also fitted a smoothing spline relating the change in the square root

of total area occupied to time (Fig. 5).

The lag in spreading was deemed to occur from the end of human

introductions (1971-1972) until the spreading rate in Fig. 5 started to increase. This

process provided a simple estimate of the lag phase duration, excluding the period of

repeated human introductions. We then calculated the maximum rate of spread across

Canberra using the rate of change in Fig. 5. Once again, we excluded the spreading

rate for the first four years due to repeated human introductions of the common myna

over this time.

2.7 Reconstructing population growth

ArcGIS 10® (ESRI, 2010) was used to identify the location of each survey site

of the GBS. Survey points that fell outside of Canberra were excluded from our

analysis. We defined four geographic regions in Canberra (Fig. 2). This enabled

grouping of survey sites to ensure continuity of survey effort over region and year, as

new sites were created and old sites were abandoned. Regions were primarily based

on the geographic location and development history of the city.

Using GenStat 14® (VSN International, 2011), we fitted hierarchical

generalized linear models (HGLMs) (Lee et al., 2006) to the individual counts using a

quasi-Poisson model with a logarithmic link function. Region, year and all their

interactions were treated as fixed effects, while sites were treated as a random effect


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with a gamma distribution and a logarithmic function. This process enabled us to

estimate the annual mean numbers of the common myna per km2 per region. We then

fitted a smoothing spline (Green and Silverman, 1994) relating the annual mean

number of common myna birds per km2 by year (± SE) for each region (Fig. 6). We

also fitted a smoothing spline (Green and Silverman, 1994) relating rate of change in

birds per km2 to time (Fig. 7).

Using Fig. 7, we calculated the lag in population growth and maximum rate of

population growth. The lag phase was defined as occurring from establishment until

common myna populations increased by one or more birds per km2 (Fig. 7). This

process provided a simple method for distinguishing the lag phase from population

growth. We avoided using more intricate methods as entire studies have been

dedicated to statistically distinguishing the lag phase from population growth (see

Aikio et al., 2010).

The maximum rate of population growth for the four regions was calculated

from data on the rate of change in Fig. 7. We also calculated the maximum population

size for each region from the peak of the spline curve in Fig. 6. Table 1 summarises

data on the establishment year, lag time, maximum population growth rate and the

maximum number of common myna birds per km2 for each of the four regions of

Canberra.

3. Results

3.1 Establishment and spread


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The common myna successfully established in the suburb of Forrest in 1969

where it was originally released (Fig. 2). Initially, the spreading rate was relatively

high and by 1971-1972, the species was established in four suburbs. However, this

period corresponds with the release of over 100 birds and the rate of spread decreased

over this period (Fig. 5). After human introductions of the common myna stopped

(1971-1972), the rate of spread slowed and almost plateaued for five years (Fig. 4). In

1977-1978, the rate of spread began to increase (Fig. 5). The common myna exhibited

a lag period in natural spreading of approximately six years (1971 to 1977). In 1990-

1991, the rate of spread reached a maximum spreading rate of 0.43 km per year (Fig.

5). The rate of spread slowed as the common myna became established in the majority

of suburbs, resulting in diminished expansion rates (Fig. 4, Fig. 5). By 2000-2001,

the common myna had become established in all suburbs surveyed, 31 years after

introduction. Once established in a suburb the common myna remained established

despite fluctuations in abundance.

The common myna spread predominantly southwest from the initial release

site. There was also an isolated jump dispersal to the north-west, approximately 10

km from the main spreading centre (Fig. 3C). It was not until 1987-1988, that the

common myna began to establish in and around the city centre, less than five km from

the initial release site (Fig. 2). Therefore, the common myna took approximately 18

years (1969-1970 to 1987-1988) to establish north of an artificial lake (Lake Burley

Griffin) that is less than two km from the initial release site.

3.2 Population growth


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Population growth of the common myna followed the same pattern in all four

regions with numbers remaining low before steadily increasing. Common myna

abundance reached a peak size before decreasing in each region (Fig. 6). After

establishment in a region, numbers of the common myna remained low for an average

of 2.7 (±0.3) years (Table 1). The lag period before population growth ranged from

two to three years (Table 1). After this lag, the rate of population growth increased,

reaching an average maximum rate of population growth of 24.1 (±6.4) birds per km2

(Table 1). The maximum rate of population growth varied between regions, ranging

from an increase of 10.7 birds per year in Region 1, to 40.4 birds per year in Region 2

(Table 1, Fig. 7).

The average maximum population size for all regions was 205.9 (±34.6) birds

per km2. However, regions varied considerably in their maximum population density

with Region 1 supporting a maximum of 128.0 (±4.2) birds per km2 and Region 4

supporting 266.2 (±10.0) birds per km2 (Table 1).

4. Discussion

We observed that the reconstructed invasion sequence for the common myna

in Canberra followed closely with what invasion process theory would predict. We

discuss these similarities and how invasion process theory can be used to enhance the

understanding and management of introduced species.

4.1 Similarities between invasion process theory and the observed invasion


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All stages of the invasion process from introduction to spread were observed

for the common myna invasion sequence in Canberra. Below we discuss the key

elements of invasion process theory that potentially influenced the invasion sequence

of the common myna.

Invasion process theory suggests there is a bias in the species selected for

transport and introduction to new areas (Duncan et al., 2003). One bias is for species

characteristics, with many species selected for particular purposes (Duncan et al.,

2003; Hengeveld, 1989). The common myna was transported and introduced to

Australia as a biological control due to the species’ appetite for insects (Dhami and

Nagle, 2009; Gregory-Smith, 1985).

Invasion process theory demonstrates that introductory effort is the strongest

independent explanation for establishment success (Colautti et al., 2006; Duncan et

al., 2003; Fautley et al., 2012; Forsyth et al., 2004; Lockwood et al., 2005; Pyšek and

Richardson, 2007; van Wilgen and Richardson, 2012). We also found that the

common myna became successfully established after a repeated and large

introductory effort (110 birds). Two separate reviews of introduced bird species in

Australian and New Zealand both found that 83% of bird species became established

when introduced in groups of over 100 (Green, 1997; Newsome and Noble, 1986).

The common myna also has a strong history of establishment in other countries (Feare

and Craig, 1998); an attribute that theory suggests is a good indicator of future

establishment success (Duncan et al., 2003; Duncan et al., 2001; Kolar and Lodge,

2001).

Invasion process theory indicates a lag period before population growth may

occur as a relatively small and newly introduced population would take time to build

in numbers and overcome the chance of stochastic extinction (Arim et al., 2006; Mack


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et al., 2000; Partecke et al., 2004; Shigesada and Kawasaki, 1997). We observed that

the common myna exhibited a lag period of 2.7 (±0.3) years before population

growth. This period is relatively short compared to the 10-year lag period of a closely

related species the common starling (Sturnus vilgaris) in New York City (Wing,

1943). The main factor driving the short lag period for the common myna was likely

to be the large number of birds released. This would have resulted in a greater initial

population size and the ability for rapid population growth (Arim et al., 2006; Mack et

al., 2000; Partecke et al., 2004). The common myna also has a broad niche breadth

and exhibits behavioural flexibility. Theory suggests these traits make it unlikely that

a species would require a significant period of adjustment in the new environment

before growing in population size (Blackburn and Duncan, 2001; Sol and Lefebvre,

2000).

Theory indicates logistic growth may occur when species reproduce at a slow

rate and have limited immigration (Hengeveld, 1989). We observed a logistic ‘s-

shaped’ pattern of population growth for the common myna. The single release site

and sedentary nature of the common myna may have limited immigration and resulted

in this logistic pattern of population growth (Hengeveld, 1989). Environment and

species’ attributes (such as reproductive age, development time, and fecundity) may

also have influenced the rate of population growth (Fig. 1; Supplementary Content 1).

The common myna population size slowly increased before reaching a peak growth

rate. As the population reached its maximum size, the growth rate slowed and, after

this point, the population size decreased. The maximum population size in Regions 2

and 4 was much higher than in Regions 1 and 3. This may be due to Regions 2 and 4

containing a greater proportion of urban area that the common myna is known to

prefer (Feare and Craig, 1998).


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Invasion process theory predicts dispersing animals may find it difficult to

locate mates or suitable habitat in new areas and this may lead to a lag in spreading

(Mack et al., 2000; Shigesada and Kawasaki, 1997). We observed a relatively short

(six year) lag before spreading for the common myna compared to other studies that

report periods of seven to ten years (Lensink, 1998; Mack et al., 2000; Rutz, 2008;

Silva et al., 2002). The collared dove (Streptopelia decaocto) invasion of Europe from

Syria and Turkey had a lag period of approximately 200 years (Hengeveld and Van

den Bosch, 1991). The relatively short lag period for the common myna is likely to be

caused by the large number of birds released and the proximity of suitable habitat

(human modified environments).

Theory predicts dispersal ability and resource availability can influence a

species’ ability to spread (Fig. 1) (see Supplementary Content 1). We observed a very

slow spreading rate of 0.43 km per year for the common myna in Canberra. Invasion

theory suggests common myna spreading should be enhanced by a large initial

population size and the availability of connected suitable habitat (Fig. 1) (Cassey,

2001; Karatayev et al., 2011; Pyšek and Hulme, 2005; Smallwood, 1994). However,

the slow spreading rate for the common myna may be due to the species’ sedentary

nature (Feare and Craig, 1998) and limited dispersal ability of their young.

Additionally, evidence suggests bird species can become more sedentary in urban

areas (Partecke et al., 2004).

To the best of our knowledge, our work is the first study to estimate a rate of

spread for the common myna. This speed is much slower than the median spreading

rate of six km per year found by Evans et al., (2010) for 47 bird species outside their

natural ranges. However, spreading rates can vary considerably, especially at different

spatial scales (Karatayev et al., 2011). Van den Bosch et al. (1992) reported a


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spreading rate of 10.2 km per year for the house sparrow (Passer domesticus) in the

United States of America and 27.9 km per year in Europe. Several other studies of

introduced species also have noted the occurrence of initially slow spreading,

followed by substantially faster rates (Lensink, 1998; Mundinger and Hope, 1982;

Pyšek and Hulme, 2005). However, other introductions of the common myna appear

to also be spreading at a slow rate, supporting our finding. Notably, the common

myna was introduced to Melbourne over 150 years ago and has spread less than 200

km west from this location despite the occurrence of suitable habitat (Martin, 1996;

RAOU, 2011).

A rapid spreading rate may be driven by jump dispersal, creating numerous

new invasions that enhance the spreading rate (Mack et al., 2000; Shigesada and

Kawasaki, 1997). We observed only one instance of potential jump dispersal (10 km)

by the common myna. However, this sudden movement may have been human-

assisted. Jump dispersal of larger distances may not have been detected in our study

due to the relatively small size of the study area.

Theory suggests that an adverse impact elsewhere is the key indicator that a

species may have a negative impact in the new environment (Bomford, 2008; Lever,

2001). In this study, we did not attempt to quantify the impact of the common myna

in the study area. However, previous research indicates the species has a negative

impact on some cavity-nesting and small bird species (Grarock et al., 2012; Dhami

and Nagle, 2009).

4.2 Management strategies throughout the invasion process


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Information on speed of establishment, rate of spread, and population growth

is the foundation of any good management plan aimed at the prevention, eradication

or control of a species (Hulme, 2006; Sakai et al., 2001; Tobin et al., 2007). It is also

imperative that critical opportunities for effective management are not missed through

inaction, due to a perceived lack of understanding of how a species will interact in the

environment. Our findings suggest a conceptual model of the invasion process can be

coupled with species, environment and event attributes to enhance understanding of a

species invasion sequence. However, the limitations of this method must be

acknowledged with the potential for unexpected outcomes in novel locations.

Decision makers need to ensure the correct management interventions are

implemented at different stages during the invasion process to ensure effective

management (Fig. 1) (see Hulme (2006) for further details). Below we demonstrate

how different management actions are required throughout each stage of a species

invasion sequence depending on the duration, speed or probability of an event.

Preventing the transport and introduction of new species is always the best

strategy as management complexity and costs both increase as a species moves

through the invasion process (Mack et al., 2000; McNeely et al., 2003; Sakai et al.,

2001). It is important to investigate and prevent potential transport pathways (e.g.

stowaways on ships). Areas at risk from invasion or close to existing introductions

should be monitored to ensure new arrivals are dealt with swiftly. For example,

transportation of the common myna on container ships and spreading of the species to

new areas should be prevented. Areas at risk of invasion should be monitored.

Detection at low numbers and over vast areas may be difficult, but online initiatives

such as FeralScan© (IACRC, 2011) may enable community members to map

introduced species sightings.


21

If a newly introduced species is likely to establish successfully (e.g. large

introduction effort and suitable habitat) the possibility of eradication should be

assessed. Eradication attempts have a greater chance of success when conducted early

in the establishment phase (McNeely et al., 2003; Simberloff, 1997). However,

introduction pathways must also be identified and disrupted for eradication to be

successful (Hulme, 2006). Therefore, it deemed viable, attempts should be made to

eradicate new introductions of the common myna as it has a strong history of

establishment elsewhere. This is especially important for introductions of over 100

individuals. Conversely if it is unlikely that a species will become established (e.g.

unsuitable climate), monitoring may be an appropriate action to preserve management

resources.

If a species is anticipated to have short lag periods before population growth

and spread (such as the common myna or C. taxifolia) eradication should be

attempted quickly. If efforts to eradicate the species at this time fail, or are not

conducted, the species may grow in numbers and continue to spread (Sakai et al.,

2001). This would result in significant increases in the costs and complexity of

management (Hulme, 2006). Alternatively, if a species is believed to have long lag

periods before population growth or spread, rapid action may not be as critical.

Monitoring and containment could be used to provide time to conduct further research

and develop an effective management plan (Hulme, 2006).

Understanding the population dynamics of a species is critical for assessing

the effectiveness of potential control measures (Hengeveld, 1989; Neubert and

Caswell, 2000). The type of population growth (logistic or exponential), growth rate,

and maximum population size influence the level of culling required to control

population size (Newton, 1998). Eradication is still possible at this stage but control


22

operations need to remove a greater number of individuals than the population’s

natural rate of increase (Hulme, 2006; Newton, 1998). For example, to control the

common myna in Canberra, culling may need to be at a rate greater than population

growth (24 birds per km2 per year). For a summary of potential common myna control

techniques see Dhami and Nagle (2009) and Tidemann et al. (2011).

Monitoring and containment should be used to slow the spread of new

introductions (Hulme, 2006). Containment may be difficult for rapidly spreading

species and they may jump containment lines. However, slowly spreading species

may be more easily contained and therefore this would allow additional time for

research and management planning (Hulme, 2006). A slow spreading rate and limited

jump dispersal may also enhance the effectiveness of control, as areas are unlikely to

be rapidly re-invaded. For example, the slow spreading rate of the common myna

observed in this study, may enable individuals in one area to be controlled, without

rapid immigration of individuals from surrounding areas. However, once a species

becomes widespread and abundant, total eradication is unlikely (Mack et al., 2000;

Sakai et al., 2001).

The level of impact a species has is fundamental to determining the level of

management response required (Davis et al., 2011). Management prioritisation also

needs to consider the cost of management and the effectiveness of management

actions. However, the magnitude of introduced species impacts and effectiveness of

control can be variable. Nevertheless, adverse impact elsewhere is a good indicator

that the species may have a negative impact in the new environment (Bomford, 2008;

Lever, 2001).

Once a species is widespread and abundant, population control and impact

mitigation are the best management strategies (Hulme, 2006). Slowing the dispersal


23

and spread of species should remain a priority with newly established populations

eradicated. Control measures could focus on the long-term reduction in population

size to a predefined level based on impact mitigation and management costs.

However, defining this level can be difficult and highly problematic (Hulme, 2006,

2003).

5. Conclusion

A conceptual model is a useful tool for understanding a species invasion

sequence and implementing effective management. Our results suggest that a simple

conceptual model (Fig. 1) may be a useful management tool to quickly anticipate the

general stages of the invasion process for new invasions. Using a conceptual model

coupled with basic species, environment or event knowledge (even if that knowledge

is limited) will enhance the understanding of potential invasions.

Detailed studies on all introduced species are not possible due to limited

resources and an increasing number of invasions. Therefore, anticipating the invasion

process could identify potential high-risk species to target for management and further

research. This potential predictability could also bring together the two key elements

of successful management: knowledge of the invasion process and rapid response to

invasion. An ability to quickly predict the general stages of the invasion process

would enable more timely management responses, leading to more successful

outcomes.

Acknowledgments


24

We thank the Canberra Ornithologist Group for providing data from the

Garden Birds Survey, especially M. Butterfield. We also thank five anonymous

reviewers for their comments on this manuscript.

Electronic supplementary material

The online version of this article (doi:…) contains supplementary material,

which is available to authorized users: Supplementary Content 1: Stages of the

invasion process and the key species, environment and event attributes found to

influence each stage.

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32

Table 1. Elements of the common myna (Acridotheres tristis) invasion sequence in

Canberra, Australiaa.

Region Year

established

Year

population

growth

started

Lag in

population

growth

(years)

Maximum rate

of population

growth (birds

per km2)

Maximum

population size

(birds per km2)

Region 1 1982-1983 1985-1986 3 10.7 128.0 (±4.2)

Region 2 1986-1987 1988-1989 2 40.4 262.3 (±9.4)

Region 3 1970-1971 No data No data 18.3 167.2 (±7.7)

Region 4 1980-1981 1983-1984 3 27.1 266.2 (±10.0)

Mean

(±SE)

2.7 (±0.3) 24.1 (±6.4) 205.9 (±34.6)

a Lag in population growth and maximum rate of population growth were calculated from Fig. 7. We

defined the lag phase as occurring from establishment until common myna populations increased by

one or more bird per km2 (Fig. 7). We calculated the maximum population size for each region from

the peak of the spline curve in Fig. 6.


33

Fig. 1. A general conceptual model for the invasion process with the relevant

management strategies and key hypotheses that influence each stage. The general

conceptual model was created by drawing on the extensive body of invasion research

(Supplementary Content 1). Although depicted as the final stage of the invasion

process, impacts can occur throughout the entire invasion process. However,

widespread and significant impacts often occur once the species has grown in

numbers and spread throughout the environment.

Fig. 2. Location of the study site in Canberra, South East Australia. The initial

common myna (Acridotheres tristis) release site and the four regions for analysing

population growth are detailed on the map.

Fig. 3. The spread and establishment of the common myna (Acridotheres tristis) in

Canberra, Australia. Data modified from Gregory-Smith (1985) for box A and B and

Canberra Ornithologists Garden Bird Survey for boxes C-F. Black sections indicate

established common myna population, light grey indicates establishment has not

occurred and dark grey indicates the site has not been adequately surveyed. For

definition of establishment see Section 2.6.

Fig. 4. Smoothing spline relating the square root of the area established (km2), over

time (years) (± SE), for the spread of the common myna (Acridotheres tristis) in

Canberra, Australia. The solid line represents the smoothing spline and dashed lines

represent the standard error of the smoothing spline. Common myna establishment is


34

calculated from Gregory-Smith (1985) and Canberra Ornithologists Garden Bird

Survey. For definition of establishment see text.

Fig. 5. Smoothing spline relating the change in the square root of the area established

(km2) over time (years) for the spread of the common myna (Acridotheres tristis) in

Canberra, Australia.

Fig. 6. Smoothing spline relating the abundance (birds per km2) of the common myna

(Acridotheres tristis) over time (years) (± SE) in four regions across the rural city of

Canberra, South East Australia. The solid lines represent the smoothing spline and

dashed lines represent the standard error of the smoothing spline

Fig. 7. Smoothing spline relating the change in abundance (birds per km2) of the

common myna (Acridotheres tristis) over time (years) in four regions in Canberra,

Australia.

Fig 1

Graphical Abstracts (for review)

Fig. 2.

Fig. 3

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

using invasion process theory to enhance the understanding ...€¦ · around the world and is...

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