Management and impact of a native invasive species: Allocasuarina huegeliana in the sandplain heath of the Western Australian Wheatbelt

Nancy Shackelford B.Sc./B.A.

This thesis is presented for the degree of Masters of Science by Research of Nancy Shackelford of The University of Western Australia

School of Plant Biology

February 2012

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DECLARATION

I declare that this thesis is my own account of my research and contains as its main

content work which has not previously been submitted for a degree at any tertiary

education institution. My work has been built and shaped by the input and aid of many

pivotal people in the last two years. However, direct involvement in any of the content

contained in this document is listed below:

Chapter Two (70% contribution): This paper is in preparation for publication with four

co-authors – Richard Hobbs, Nicole Heller, Lauren Hallett, and Timothy Seastedt.

Lauren Hallett contributed to the initial formation of ideas and structure of the paper,

Nicole Heller drafted much of the introduction, and Richard Hobbs shaped and heavily

contributed ideas and added sections as the paper developed. All authors gave helpful,

important feedback leading to the final version presented here. I wrote the initial outline

and extensive parts of the text, contributed significantly to the main ideas expressed, and

coordinated the finalization of the manuscript.

Chapter Three (90% contribution): This paper is in preparation for publication with four

co-authors – Michael Renton, Kristine Brooks, Michael Perring, and Richard Hobbs.

Kristine Brooks is the rare flora expert with the Wheatbelt Regional Department of

Environment and Conservation. She led and carried out the 2010/2011 floristic survey

used in the paper. The data was analyzed with the close instruction of Michael Renton.

The other co-authors guided and shaped the development of the manuscript. I aided in the

collection of the floristic data and identification, led and carried out the population

surveys with the help of Michael Perring, finalized the data analysis and wrote the

document.

Chapter Four (85% contribution): This paper is in preparation for publication with three

co-authors – Michael Renton, Michael Perring, and Richard Hobbs. All co-authors

contributed ideas and guided the development of the manuscript. Michael Renton helped

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program, test, and refine the model that is central to the paper. I planned and coded the

model, analyzed results, and wrote the included manuscript.

Nancy Shackelford

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ABSTRACT

Invasive species have been a growing concern over the last few decades. Current research

focuses almost entirely on non-native species invasion, with many arguing that origin of a

species is a primary factor in determining management status. In the face of wide-spread,

dramatic anthropogenic change, however, native species have been found to experience

swift range expansion and have many of the same undesirable impacts on the systems in

which they originate; thus, some argue for impact assessment as the driver of species

management. In this thesis, I aim first to find a theoretical middle ground that utilizes

both origin and impact in determining the appropriateness of species management.

I then focus on a native Western Australian tree Allocasuarina huegeliana invading into

adjacent heathlands. This study was guided by previous work and management concerns

that the invasion, thought to be caused by shifting fire regimes, is decreasing heathland

diversity. I quantified the strength of the relationships between the invasion, shifted fire

regimes, and biodiversity through observational study of A. huegeliana densities, time

since last fire, and species loss in eleven individual heath patches. I found a strong

relationship between the invasion and species loss, supporting the hypothesis that A.

huegeliana is a driver of ecological change in invaded systems. I then used simulation

modeling to examine the effect of fire and other management tactics on A. huegeliana

population spread. I found that fire-based management is potentially a viable control

method, though current return intervals are inadequate.

This study shows the applicability of simple impact-based assessment of potentially

detrimental species in established or expanding populations. However, further research

on more complex impact-based analysis is needed. Though A. huegeliana was found to

have a strong correlation with species loss, we were not able to establish mechanistic

causality or to quantify its impact to other levels of biodiversity and other system

attributes such as function and resilience. A well-rounded understanding of species roles

in a system will contribute to more balanced management decision-making.

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ACKNOWLEDGEMENTS

I have to admit that I saved my acknowledgements for the very last moment so that I

could write them with no pressure and no looming, almost-missed deadlines. I have so

much and so many to acknowledge. So readers, brace yourselves. I am using this space to

be long-winded and sometimes vague (because of course my science is concise and

perfectly clear!).

First, an inexpressible thanks to my supervisors and mentors: Richard, Michael, and

Mike. They each taught me something different and each played their own role my

development as a fledgling scientist and as a growing person. To Richard, for showing

me both the serious side of science and the lighter, Scottish jigging side of science. To

Michael, for always being my emergency contact, no matter the size or nature of the

emergency. To Mike, for deserving the nickname ‘Smiley’ and for being an unflagging

field assistant, discussion partner, and ABBA connoisseur.

I also must acknowledge the many other teachers I have found and abused in my time

here: Kris, an inspiration in her depth and humor; Rachel, with always a thoughtful,

inspiring word; Kristine, who is pragmatic and open about every endeavor; the Murdoch

crew for their Friday company and shared experiences. I have also been blessed with a

lab full of students struggling, procrastinating, learning, and teaching each other

alongside me: Maggie (always accommodating conversationalist in my moments of

dubiously necessary distraction), Hilary (my Broadway walking partner), Juan (a poetic

man full of surprises), Cristina (a passionate spirit always ready to find beauty in life), Jo

(fellow basher of Uni vehicles), and Christine (baker of all things comforting in times of

need). Our foundation as a lab comes from the much-beloved Heather, Tim, and Bec.

Thanks to the three of them for keeping our heads on straight. Heather – thanks for

putting up with my absent-mindedness in times of dirty cars, administrative oopses, and

baking beans. Tim – thanks for your experience and patience, even when you come home

from your holiday to a few new dents in your car. Bec – thanks for being

uncompromisingly you in a way that has enriched and enlivened my time here.

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Finally, to my friends and family (really those are synonyms, in my book). My friends

here – Hippy Claire, El Presidente and the First Lady, the Tiny Vegetarians, Deaks, my

climbers and my divers, and all the other folks with whom I have had the privilege and

pleasure to meet, dance, party, laze around, and experience life. My work and play are

intertwined, and the ridiculousness that has been my time in Perth because of you has

helped shape and form this work. Also to my friends back home: Flanny, Junior, Larry

Alex, Angela, Christine, Andy, Rabbit, Jon, Sledge, Roomie, Wally, Merideth, and

everyone else that has been supportive and wonderful, even from 10,000 miles away.

You have all emailed or chatted with me at some of my lowest, most homesick points,

and you have all shared silliness and joy with me in my visits back. And to my father, my

mother, and my brother. You are my foundation and constant guides. Dad – your memory

is with me and drives me forward always; Mom – you’re my confidant and support;

thanks for listening to me cry, exclaim, complain, and perseverate out loud. David – I

couldn’t be luckier in a sibling; your creativity, sensitivity, and enthusiasm are my

constant inspirations.

The people in my life have gotten me to where I am and show me where I want to be.

Thank you!

Nancy

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TABLE OF CONTENTS

Introduction .................................................................................................................................................. 1 Nature of the debate: Building the case for a middle-ground .................................................................... 2 Beyond the theory: the native invasive case study .................................................................................... 3 Thesis Aims and Scope.............................................................................................................................. 7

Finding a home in the middle: The native/non-native debate ................................................................ 11 1. Introduction ......................................................................................................................................... 11 2. Management and research perspectives............................................................................................... 13 3. A Suggested Middle-Ground ............................................................................................................... 15 4. Conclusion ........................................................................................................................................... 28

Investigating the relationships between diversity loss, invasion, and fire regime shifts in a biodiversity hotspot ......................................................................................................................................................... 35

Introduction .............................................................................................................................................35 Methods ................................................................................................................................................... 39 Results ..................................................................................................................................................... 44 Discussion................................................................................................................................................ 49

Modeling disturbance-based native invasive species control and its implications for management... 65 Introduction .............................................................................................................................................65 Methods ................................................................................................................................................... 68 Results ..................................................................................................................................................... 77 Discussion................................................................................................................................................ 83

Conclusions and general discussion .......................................................................................................... 95 Supporting and shaping the middle-ground............................................................................................. 95 Case study findings and lessons............................................................................................................... 96 Conclusion...............................................................................................................................................98

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1

CHAPTER 1

Introduction N. Shackelford

Invasive species are a global phenomenon (Mack et al., 2000; Vitousek et al., 1996) and

within the last two decades have been determined world-wide to be one of the largest

threats to ecological integrity (EEA, 1999; Vitousek et al., 1997; Wilcove et al., 1998).

They have been shown to alter energy pools, trophic interactions, nutrient flows,

ecosystem structure and composition, and other interactions or relationships such as

mutualisms (e.g. Ehrenfeld, 2010; Holmes & Cowling, 1997; Kurten et al., 2008; Mack

& D'Antonio, 1998; Richardson & van Wilgen, 2004). The most widely accepted

definition of an invasive species requires that they overcome – with explicit facilitation

by human forces – an insurmountable barrier to dispersal into the invaded area

(Richardson et al., 2000). In other words, an invasive species by most definitions must be

non-native (but see Valéry et al., 2008, 2009a; Valéry et al., 2009b). In times of rapid

anthropogenic alteration of global conditions, however, it is not uncommon for native

species to behave in the same manner as non-native invasive species: native populations

can swiftly expand ranges and increase in abundance. This process often results in

ecosystem and species-level consequences similar to those caused by non-native invasion

(for examples, see de la Cretaz & Kelty, 1999; Van Auken, 2009).

Despite the similarities in behavior between increasing native and non-native species

populations, there remains a long-standing debate on the relative importance of origin

and impact as determinants of species management (e.g. Davis et al., 2011; Rosenzweig,

2001; Sagoff, 1999; Simberloff, 2005, 2011; Warren, 2007), with some arguing that non-

natives should be uniformly excluded where possible in systems and others arguing that

species management should be based on the impact of a species, regardless of native or

non-native origins. In this thesis, I present a study of the dynamics of invasion by a native

tree into the sandplain heathlands of the Western Australian Wheatbelt region. I first

contextualize the study by exploring the theoretical debate around native versus non-

native species perceptions and management. I then use observational field data and

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simulation modeling to quantify the potential impacts of and control mechanisms for the

native invasive population.

Clarity of language is important, particularly in widely controversial arenas such as

invasive and non-native species management. Throughout this thesis I utilize the

following definitions:

1. Native/indigenous – species that evolved in a given area or arrived there by natural means, without intentional or accidental intervention of humans from an area where they are native (Richardson et al., 2011)

2. Nonnative/exotic/alien – those species whose presence in a region is attributable to human actions that enabled them to overcome fundamental biogeographical barriers (Richardson, et al., 2011)

3. Invasion – the process of a species’ acquiring a competitive advantage following the disappearance of natural obstacles to its proliferation, which allows it to spread rapidly and to conquer novel areas within recipient ecosystems in which it becomes a dominant population (Valéry, et al., 2008)

Nature of the debate: Building the case for a middle-ground In many ways, the native–non-native debate itself seems primarily on the philosophical

questions of how we perceive non-native species as desirable or undesirable in new

systems. Management decisions are often made outside the confines of this debate. Due

to resource and logistical restraints, managers are often forced to be pragmatic in their

decisions, and whether a particular species is theoretically considered ‘good’ or ‘bad’ is

irrelevant. This is evident in the many decision-making tools available to determine

whether management of particular non-native species is worth the effort and expense of

control or eradication (Hiebert, 1997); a large portion of this literature includes extensive

research into risk analysis and considerations therein (e.g. Hiebert et al., 1993; Randall et

al., 2008; Rew et al., 2007; Virtue et al., 2006). The concept of managing the worst and

scariest is not new in species control efforts.

However, there are some very real implications of our philosophical perceptions of non-

native species. The presentation of extremes such as currently espoused in the native/non-

native debate has led to perverse application outcomes in some instances. Some managers

have been known to reject the application of potentially useful non-native species in

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restoration (e.g. fast growing trees in Puerto Rico: (Lugo, 2004)), while others such as

community groups are performing assisted migrations without any extensive

understanding of potential threats or repercussions (e.g. Torreya taxifolia in North

America: (Schwartz, 2005)). Beyond deliberate use, an anti-non-native policy can lead to

ineffective investment of resources such as in the failed removal of Martynia annua from

Gregory National Park in Australia (Gardener et al., 2010). The estimated cost totaled

~$660,000 and attempted to control a plant that has yet show evidence of major

ecological impacts (Davis, et al., 2011). On the other side, the acceptance of seemingly

benign new non-natives in a system without further investigation can result in delayed

response invasion and resulting environmental degradation (Crooks, 2005).

With these examples in mind, I argue that having opposing extremes in our foundational

perception of the importance of species origin plays an undeniable role in how we

conduct research and management. Thus, the currently prevalent view that non-native

species are ecological ‘bad guys’ and native species ecological ‘good guys’ should be

reassessed at regular intervals. I attempt to address these issues by outlining a potential

middle ground perspective on the debate and discussing management implications

thereof.

Beyond the theory: the native invasive case study One of the major issues in using origin as a determiner of management is that the

difference in impact between native invasion and non-native invasion is often small or

non-existent. As Sagoff (1999) points out, some native species have caused dramatic

ecological and economic harm on scales similar to noxious non-native species. In some

extreme cases, control of native species undergoing rapid expansion does occur: for

example, studies of how to reinstate prairie to areas overtaken by native woody invaders

is common in North American literature (e.g. Ansley & Rasmussen, 2005; Johnson et al.,

1999; Wilcox, 2002). However, a middle-ground perspective on origin and impact as

complementary management guides would potentially provide a framework in which to

view and manage a potentially detrimental species, either native or non-native, at

different stages of the establishment and spread process. Management of species in this

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manner is by necessity a case-by-case decision-making process in which certain aspects

and goals must be very clearly articulated.

1. Scale – What scale is the system of concern? At what scale is the invasion

occurring? Does the scale of manageable area match the scale of the invasion?

What is the scale of the potential impact?

2. Impact – What impacts to the system are of highest concern? How do those fit

with larger management goals for the system? Can those impacts be quantified

easily?

3. Cause – Is the invading species the symptom of a larger management issue; i.e. is

the species a passenger of some other environmental change in need of

management? Note here that invasion often co-occurs with and/or is caused by

other forms of environmental degradation (Didham et al., 2007; Mack, et al.,

2000) and care needs to be taken in determining or inferring causality of impact

between the invader and other changes seen in the system.

4. Management –What management tools are available? What are the potential

costs, benefits, and trade-offs in using those tools?

I address some, but not all, of these issues in a case study of Allocasuarina huegeliana

(L.A.S. Johnson) a tree species native to the Western Australia Wheatbelt that is invading

heath systems in the region. The invasion is hypothesized by local land managers to be

driving ecological degradation and species loss in the heath. I focus my study

predominantly in Tutanning Nature Reserve (Figure 1), an approximately 2,140 ha

reserve located in the Western Australian Wheatbelt amidst a landscape largely converted

for agricultural purposes. It is managed by the regional Department of Environment and

Conservation.

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The Reserve contains a mosaic of ecosystem types including Eucalypt woodland, granite

outcrop vegetation, and sandplain heath (kwongan). For the last thirty years, local land

managers have noted the expansion of A. huegeliana into heath patches on the reserve

and the apparent decrease in heath species that follows. To frame the study, I defined the

aspects necessary for specific species management:

1. Scale: Site scale consists of individual heath patches of kwongan, ranging in

Tutanning from <1 to approximately 14 ha. Each patch is relatively unique in its

composition, and so the initial scale of concern should be considered at this level.

Due to the relatively small size of patches, the impacts of the invasion will likely

be more dramatic than would occur on a larger scale with higher landscape

heterogeneity or refuge availability (Powell et al., 2011). The patches are nested

within the reserve and to capture the larger reserve-level consequences of the

invasion, I also attempted to quantify invasion impacts in the mosaic of heath

patches together by looking at all patch losses and gains together. As the

surrounding landscape is so fragmented, the expansion is occurring within a fully

manageable area and on the same scale as the potential resulting degradation.

2. Impact: The type of impact in which we were most interested was A.

huegeliana’s potential to decrease biodiversity: in this study, we could examine

only one element of biodiversity, namely plant species richness (presence/absence

within a patch or the reserve) and composition. Kwongan is extremely biodiverse,

Figure 1: Tutanning Nature Reserve with the surveyed heath patches in red.

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known to contain around a third of all recorded vegetation species in Western

Australia (Pate & Beard, 1984). Many of the species are rare or uncommon and

their presence or absence in intact remnants is of high conservation concern.

Additionally, species lost over the reserve will have little chance of

recolonization. The isolation of Tutanning means that it is unlikely to receive

population influxes from external seed sources except in rare long-distance

dispersal events from other fragments (Robinson & Quinn, 1988). Though there

might be individual patch species turn over, there should be little species turnover

for all patches considered jointly. Potential direct impacts of A. huegeliana on

biodiversity have not been investigated but may include canopy closure,

competition, light restriction through heavy litter deposition, and allelopathy.

3. Cause: Lower fire intervals at lower intensities could be having both direct and

indirect impacts on the A. huegeliana invasion process. As an obligate reseeder

species, A. huegeliana has been found to be sensitive to fire (Yates et al., 2003),

and local managers estimate that high intensity fires lead to mortality rates

approaching 100% (Yates, pers. comm.). Long fire-free intervals or low fire

intensities might allow population expansion of A. huegeliana into areas where

fire was an historical control.

4. Management: In woody invasion around the world, the two most common

management tools are chaining (mechanical removal) and fire (Ansley et al.,

2006; Fuhlendorf et al., 1996). Both are applicable in the control of A.

huegeliana. If fire can be used effectively, its historical occurrence in the system

and potential benefits for ecosystem structure and composition make it the

preferable alternative. The use of fire also addresses the cause of the invasion (fire

suppression) rather than the symptom (tree density). Mechanical removal, on the

other hand, addresses only the invader. It can be used to increase the speed or

efficacy of fire treatments, but as it is resource intensive, it should only be utilized

if showing dramatic benefits to control efforts.

The scope and planning of the case study took into consideration these aspects and

attempted to expand and deepen management understanding of the same.

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Thesis Aims and Scope In this thesis, Chapter Two addresses finding a middle ground in the native/non-native

debate. I first outline the major traditions in non-native species management by

discussing briefly their historical development as well as their aims and goals. I then aim

to find a standpoint that utilizes multiple perspectives, relying on both origin and impact

as the basis of management decisions, each at different stages of the establishment and

population spread process.

I then focus on my case study species and its behavior in the heathland. In this portion of

the study, I strive to understand the likely impacts of the native species invasion. I

quantified the strength of the relationships between species loss, A. huegeliana density,

and disturbance. I additionally attempt to inform potential land management decisions by

investigating population control strategies through simulation modeling. Specifically, I

investigate:

1. How much species loss, biodiversity richness loss, and compositional shifts have

occurred in surveyed kwongan patches in the last thirty years?

2. How do those losses and changes correlate with A. huegeliana invasion and time

since last fire?

3. How does A. huegeliana invasion correlate with time since last fire and what does

that relationship imply about the causes of the invasion?

4. Can fire be used as a control mechanism for A. huegeliana populations in heath?

5. How does the return interval and regularity of the fire regime affect A. huegeliana

population density and spread?

6. How much more effective are A.huegeliana population control efforts if

mechanical removal is used in conjunction with fire?

References

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Ansley, R. J., Wiedemann, H. T., Castellano, M. J., & Slosser, J. E. (2006). Herbaceous restoration of juniper dominated grasslands with chaining and fire. Rangeland Ecology & Management, 59(2), 171-178.

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Davis, M. A., Chew, M. K., Hobbs, R. J., et al. (2011). Don't judge species on their origins. Nature, 474(7350), 153-154.

de la Cretaz, A. L., & Kelty, M. J. (1999). Establishment and control of hay-scented fern: a native invasive species. Biological Invasions, 1(2), 223-236.

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Mack, R. N., Simberloff, D., Lonsdale, W. M., Evans, H., Clout, M., & Bazzaz, F. A. (2000). Biotic invasions: Causes, epidemiology, global consequences, and control. Ecological Applications, 10(3), 689-710.

Pate, J. S., & Beard, J. S. (1984). Kwongan Plant Life of the Sandplain. Nedlands, Western Australia: University of Western Australia Press.

Powell, K. I., Chase, J. M., & Knight, T. M. (2011). A synthesis of plant invasion effects on biodiversity across spatial scales. American Journal of Botany, 98(3), 539-548.

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of invasive nonnative plants that negatively impact biodiversity. Invasive plant science and management, 1(1), 36-49.

Rew, L. J., Lehnhoff, E. A., & Maxwell, B. D. (2007). Non-indigenous species management using a population prioritization framework. Canadian Journal of Plant Science, 87(5), 1029-1036.

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Richardson, D. M., Pyšek, P., & Carlton, J. T. (2011). A compendium of essential concepts and terminology in invasion ecology Fifty Years of Invasion Ecology: The Legacy of Charles Elton (pp. 409-420): Wiley Online Library.

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Robinson, G. R., & Quinn, J. F. (1988). Extinction, turnover and species diversity in an experimentally fragmented California annual grassland. Oecologia, 76(1), 71-82.

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Schwartz, M. (2005). Conservationists should not move Torreya taxifolia. Wild Earth, 2005, 73-79.

Simberloff, D. (2005). Non-native species do threaten the natural environment! Journal of Agricultural and Environmental Ethics, 18(6), 595-607.

Simberloff, D. (2011). Non-natives: 141 scientists object. Nature, 475(7354), 36-36. Valéry, L., Fritz, H., Lefeuvre, J. C., & Simberloff, D. (2008). In search of a real

definition of the biological invasion phenomenon itself. Biological Invasions, 10(8), 1345-1351. doi: DOI 10.1007/s10530-007-9209-7

Valéry, L., Fritz, H., Lefeuvre, J. C., & Simberloff, D. (2009a). Ecosystem-level consequences of invasions by native species as a way to investigate relationships between evenness and ecosystem function. Biological Invasions, 11(3), 609-617. doi: DOI 10.1007/s10530-008-9275-5

Valéry, L., Fritz, H., Lefeuvre, J. C., & Simberloff, D. (2009b). Invasive species can also be native. Trends in Ecology & Evolution, 24(11).

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Virtue, J., Cunningham, D., Hanson, C., et al. (2006). National post-border weed risk management protocol (Vol. 294).

Vitousek, P. M., D'Antonio, C. M., Loope, L. L., Rejmanek, M., & Westbrooks, R. (1997). Introduced species: A significant component of human-caused global change. New Zealand Journal of Ecology, 21(1), 1-16.

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Warren, C. R. (2007). Perspectives on the 'alien' versus 'native' species debate: A critique of concepts, language and practice. Progress in Human Geography, 31(4), 427-446.

Wilcove, D. S., Rothstein, D., Dubow, J., Phillips, A., & Losos, E. (1998). Quantifying threats to imperiled species in the United States. BioScience, 48(8), 607-615.

Wilcox, B. P. (2002). Shrub control and streamflow on rangelands: A process based viewpoint. Journal of Range Management, 318-326.

Yates, C. J., Hopper, S. D., Brown, A., & van Leeuwen, S. (2003). Impact of two wildfires on endemic granite outcrop vegetation in Western Australia. Journal of Vegetation Science, 14(2), 185-194.

11

CHAPTER 2

Finding a home in the middle: The native/non-native debate N. Shackelford, R. Hobbs, N. Heller, L. Hallett, T. Seastedt

Abstract: Throughout the history of invasion biology, there has been long-standing and sometimes fierce debate on the perception and management of non-native species. Some argue that non-native species are universally undesirable for their unpredictability and their ability to at times dramatically disrupt native species and systems. Others argue for an approach that weighs a species’ impact and role in a system before determining its desirability, irrespective of its identity. We suggest a middle-ground approach, one that does add extra caution about the desirability of non-native species relative to native species, but also bases perception and management decisions on the population stage of the non-native species and in relation to a wider range of conservation goals. In initial stages of introduction and establishment, we argue that a cautious approach is most prudent, one assuming the potential dangers of the new species in systems. In later stages of established populations, we argue that impact assessments will provide the soundest and more efficient management information, with origin and other available data included as part of the subsequent decision-making process. We explore and expand on these suggestions, and hope that the perspective presented respectfully contributes to finding a common ground in a long and polarized debate. Keywords: introduced species, species management, impact assessment, conservation, invasion

1. Introduction

Polarized debate is a feature of many major environmental issues. While properly

informed debate is healthy, it should eventually lead to a new understanding or synthesis

that provides a way forward. In this paper, we consider recent debate surrounding the

focus on non-native species in conservation and management. We suggest the need for a

middle-ground that recognizes the merit in both sides of the argument and prompts focus

on the management implications of this recognition.

Perhaps no issue in conservation spawns as much emotional debate as the issue of

managing non-native species. Depending on the context and perspective, non-native

species may be villains, heroes, victims, or organisms just trying to survive. While

invasive species management became a central conservation concern in the 1980s, there

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have been vigorous debates about the status and naming of non-native species starting in

the late 19th century (see Coates, 2006). Those who defend the removal of non-native

species have been accused of xenophobia and those who are more ambivalent are charged

with biological homogenization. Both sides have merit. Gould (1998) articulated well

how native species are really just species that arrived first, rather than species shaped by

evolution to be the “best conceivable” for any particular place. Various other biologists

and humanities scholars highlight the potential fallibility of a management logic based on

claims to essentialism and authenticity (Warren, 2007). Meanwhile, non-native species

often decrease biodiversity and alter ecosystem function in remarkable ways (e.g.

Mooney & Hobbs, 2000). And while the vast majority of non-native species will not have

major effects on ecosystem structure and function (Williamson, 1996) it is difficult to

determine when, where and which species are going to be problematic, leading many to

err on the side of precaution.

The most recent iteration of debate was sparked in July, 2011 in Nature Magazine (Davis

et al., 2011; Simberloff, 2011a), and continued for months in various global discussion

groups (i.e. EcoLog). Here Mark Davis and co-authors appealed against the native-

versus-alien dichotomy exercised in much of the current conservation work. They argued

that in a world of extreme change and novelty, it is more practical to shift focus from

species origin to the effects species have on “biodiversity, human health, ecological

services and economies.” In a letter of response also published in Nature and signed by

141 prominent scientists, Simberloff (2011) claims that Davis and co-authors have raised

a straw man because land mangers only focus on problematic non-native species anyway,

and that origin is a key indicator of species that are most likely to cause trouble.

Invasion biology has shifted its rhetoric in recent years to reflect a focus on species with

the greatest impact (Pyšek et al., 2008). However, how much of this shift reflects a

change in attitude toward non-native species, rather than just limited resources and

political appeal, is unclear. This point sits at the center of much recent controversy.

Without resource and methodological constraints, many, if not most, conservationists

would still probably prefer to rid systems entirely of non-natives regardless of impact.

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Young and Larson (2011) found that while most invasion biologists do not demonize

non-native species, more agree than disagree with the statement that “exotics are an

unnatural, undesirable component of the biota and environment”. Recognizing that this

attitude toward non-native species exists and is widespread within the field helps

contextualize Davis et al. (2011) and others.

In this paper, we attempt to find a middle ground in the native/non-native debate. We first

highlight different non-native species management stances and their fundamental

conservation goals, and explore management options with respect to these goals. Second,

we present a framework that incorporates different approaches for new occurrences and

introductions of non-native species versus established non-native and invasive species

populations.

2. Management and research perspectives

2.1 The native/non-native dichotomy

Though most famously articulated by Elton (1958), the native/non-native distinction

predates his oft-cited work. Chew and Hamilton (2011) trace the separation of ‘native’

and ‘alien’ species to Hewitt (H.C.) Watson in the early nineteenth century. Watson did

not extend his definition into value judgments or conservation concerns; it took until the

early twentieth century with Elton and his colleagues for the dichotomy to fully develop.

The driving idea is that non-native species in a system – species whose presence in a

region is attributable to human actions that enabled them to overcome fundamental

biogeographical barriers (Richardson et al., 2011) – pose either a currently realized or a

potential future threat to the native system and are therefore undesirable. The fear of

future threat is based on examples in which non-native species appear benign or

beneficial and have been managed accordingly, only to be found to have delayed or

misunderstood negative impacts. In Germany, 51% of the 184 woody weed species took

more than 200 years to become invasive (Kowarik, 1995).

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Decades of accumulated anecdotes to this end have led to a conservative view among

many ecologists, where the assumption is guilty until proven innocent (Ruesink et al.,

1995; Simberloff, 2005). Most invasion biologists in the Young and Larson survey

(2011) classified non-native species as inherently undesirable in natural systems. The

common management application of this viewpoint is the removal of non-native species

wherever possible and the absolute exclusion of non-native species in restoration and

conservation practice. In California, for example, recent efforts have been made to

remove non-native Eucalyptus trees. In some instances, Eucalyptus removal is based on

efforts to manage local fire risk caused by trees that are known to be more-fire prone than

native species (Simberloff, 2011b). However, in some cases, such as the Arastradero

Perserve, CA ,the girdling of a single, old mature tree with high cultural value, seemed to

many to serve little purpose beyond removing a non-native tree species and caused much

antipathy toward conservation aims (Dremann, 2004) Similarly, in the West Australian

city of Perth, enhancement plans for a popular urban park included a proposition to cut

down a group of innocuous non-native plane trees (Plantanus sp.) despite the local

community’s attachment to them. The proposal would have removed key sources of

shade in the park and replaced them with native species known to potentially cause

hayfever and allergic reactions (Trigger & Head, 2010).

Chew and Hamilton (2011) offer an interesting example of origin-based decision-making

in an occurrence in Britain. Pool frogs, Pelophylax lessonae, are a common species

across all of Europe thought to be descendent from a single Central European animal

introduced to Britain in the 1800s. Genetic testing in 2005 found that a subspecies of the

pool frog was descendent from Scandinavia, and was thus ‘native’ to Britain, not Central

Europe. This subspecies, despite being ecologically interchangeable, morphologically

similar, and able to freely interbreed with other (Central European) subspecies common

to Britain, was given legal protection and released throughout regions of Britain in an

effort to build its population. The logic behind decisions such as these demonstrates the

assignment of an inherent value given to the native status of a species.

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2.2 Questioning the dichotomy

An increasing number of scientists and practitioners are questioning the strict native/non-

native dichotomy as a basis for management decisions. Proponents of this perspective

emphasize the complexities of defining ‘native’ versus ‘non-native’, highlighting that

often the definitions are purely a matter of temporal or spatial scale. This ‘relativity’ of

native or non-native status has led some to suggest that there is a lack of scientific

support for separating species based on their origin (e.g. Gould, 1998; Head, 2011), and

thus it should be abandoned in favor of a purely impact-based determination of species

control in a natural system (e.g. Brown & Sax, 2004; Chew & Hamilton, 2011; Warren,

2007).

A more contentious perspective goes further to highlight the desirability of some non-

native species in systems to promote their active use in conservation and restoration

planning. As some conservationists have shifted their focus from native biodiversity and

historical fidelity, a higher emphasis has been placed on other ecological values such as

biodiversity, ecosystem function, and resilience. Thus, the origin of a species is less

relevant than its contribution to these values. This perspective stems from emerging

examples of non-native species performing beneficial roles in novel communities, such as

habitat provision (e.g. trees for bird species, such as pine in Australia for the endangered

Carnaby’s cockatoo (Valentine & Stock, 2008)), functional provision (e.g. native plant

pollinators, such as non-native birds in Hawaii (Cox, 1983)), and nursing effects during

succession (Lugo, 2004).

3. A Suggested Middle-Ground

Most scientists and practitioners in conservation and restoration have opinions that fall

between the two extreme perceptions of non-native species. Often for pragmatic reasons

and/or due to resource constraints, managers have long tolerated the persistence of low-

impact non-native species. Many scientists have also adopted this approach. As

Simberloff (2011) points out, "…most conservation biologists and ecologists do not

oppose non-native species per-se - only those targeted…as threatening ecosystems,

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habitats or species". Similarly, Richardson et al. (2008) states that ‘xenophobes’ in

invasion biology are on the fringe of the conservation movement, and that most invasion

ecologists see the native/non-native classification as a continuum rather than absolute

poles.

The extreme perspectives detailed above offer blanket generalizations about how to

perceive and manage non-native species. We, and many before us, argue that a single-

perspective framework on the value of non-native species is a poor fit for the

complexities of ecosystem management. We propose that considering different

approaches at different stages of non-native species establishment may provide a formal

middle-ground approach to the native/non-native debate. The stages of invasion have

been schematized in many ways, most recently by Blackburn et al. (2011), and here we

generalize these stages to represent the corresponding stages of non-native arrival,

establishment, and spread (Figure 1). Fundamentally different considerations come into

play depending on whether a non-native species is in the transport or introduction phases

versus whether it is in the establishment or spread phases.

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Figure 1: Non-native species population density by time. Overlaying the graph are the categories of barriers to establishment and spread as delineated by population stage. For instance, to move from the establishment phase to the spread phase, a species must have life history traits that are able to overcome potential barriers to survival and reproduction caused by conditions in the new range. Management is advised by origin, impact, or a balance of the two dependent upon population stage and can include prevention (thwarting the occurrence of a species), eradication (extirpation of a species population within a management unit), containment (restriction of increase or spread of a species population), mitigation (reduction of a species population or offsetting population impacts), or acceptance (allowing or fostering persistence of a species population). Figure adapted from the invasion stages of Blackburn et al. (2011).

In the initial phases of a new introduction, we suggest that decisions to exclude species

based on their non-native status are wise given the unpredictability of species’ behavior

(Mack et al., 2000; Pyšek & Richardson, 2010). For already-established non-native

populations, we argue that management decisions based on impact become more relevant

and useful. Though origin can inform decision-making at this stage (as discussed later),

weighing the benefits and drawbacks of controlling an individual species based on its

impacts to a system relative to a range of conservation goals may lead to more effective

and efficient management. This framework is in line with many strategic management

plans (van Wilgen et al., 2011) and weed risk assessments that have long offered

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practical approaches to targeting non-native species (e.g. Hulme, 2012; McGregor et al.,

2011).

3.1 Managing for transport and introduction

Given that many non-native species can and have become problematic, it seems prudent

to predominantly rely on origin as a judgment tool in the case of unintentional

introductions. In the Americas, non-native pests from Eurasia have inflicted billions of

dollars of agricultural impact throughout the last two centuries (Coates, 2006).

Foundational species such as the American chestnut have been nearly wiped out by a

non-native fungal pathogen (Griffin, 2000). Waterways have been choked by non-native

aquatic plants and invertebrates (e.g. Canadian water weed – Elodea canadensis – in the

Thames River, though interestingly this has since become a relatively low-density

population of non-noxious non-native species (Walker, 1912)). The enormous

consequences that can result from the arrival, establishment, and spread of non-native

species across geographical barriers have led to policies that aim to strictly control

species entry points and rapidly respond to new detections; if applied effectively, these

are likely some of the soundest policies to preserve conservation goals against further

global species exchange. Many have pointed out that controlling arrival is the only way

to prevent further issues with invasion, but that given entry by a new species, early

detection and rapid eradication response are the most powerful tools at our disposal

(Pyšek & Richardson, 2010). These policies should continue to be explicitly applied and

strengthened for both inadvertent and deliberate introductions, including those for

horticultural and land management purposes. An extension of this point-of-entry policy is

manager response to the new appearance of a species within a reserve or locality.

Populations of non-native species may be present on a large scale but not on the local

scale. The general cautious response of removal or local eradication is still valid,

particularly if a species has known invasive or noxious behavior in other localities.

However, decisions to locally control new species may be more complicated if the native

status of a species is less clear. Much literature debating the definition of ‘native’ exists

(e.g. Gould, 1998; Warren, 2007; Webb, 1985) and highlights that it is often a matter of

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temporal or spatial scale. For instance, a species can be native to a country, but not found

in an individual region of that country. This becomes particularly important under the

current reality of a rapidly changing global environment. It is well established that

species migrate in response to changing climate and environmental conditions.

Prevention of species movement through eradication of new propagules may potentially

reduce the resilience of a species by reducing its capacity to respond to environmental

change through migration and colonization (Walther et al., 2009). Additionally, overall

resilience of a system to changing conditions may be impacted by preventing natural

shifts in composition that occur through species colonization and spread (Harris et al.,

2006; Millar et al., 2007). When assessing new arrivals, contextualization of the species’

origin within multiple scales – temporal and spatial – can contribute to a better

management response. For instance, recent attempts to map ‘projected dispersal

envelopes’ based on biogeography and niche theory help define the regions where a

species could be considered native under changing environmental conditions, irrespective

of human involvement (Webber & Scott, 2011). The further development of this and

other tools could help clarify some of the definitional confusion around native status.

Recently, questions on the value of new deliberate introductions have arisen from long-

term considerations of environmental change and impacts to species and systems (Ewel et

al., 1999). The introduction of species that deliver valuable services has been an

important option throughout human land-management history. These questions are

particularly important in a restoration context. Increasingly prevailing assumptions are

being questioned and debate is ensuing about how best to restore an ecosystem that will

be able to persist in the coming decades in the face of inevitable climate change

(Broadhurst et al., 2008; McClanahan et al., 2008). Some argue that it remains prudent to

prioritize local species and provenances, while others argue that it is better to either pick

species on the basis of expected climate change, or to hedge bets and plant a variety of

populations or species from different climate conditions to increase the chance that some

will thrive in conditions of rapid change and uncertainty (Heller & Zavaleta, 2009).

Individual species might also require intervention to survive climate shifts, particularly in

highly fragmented landscapes; the merits and risks of assisted migration of species

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outside of their historical range is an ongoing topic of discussion in conservation (Hewitt

et al., 2011; Ricciardi & Simberloff, 2009). These deliberate introductions are potentially

pivotal in maintaining viable species populations against rapidly changing conditions, but

there is large uncertainty in our ability to quantify and compare the benefits and harms of

such management action.

Research for the deliberate introduction of species for other conservation or restoration

purposes would have to be extensive and explore a range of scenarios, both likely and

seemingly unlikely. As Ricciardi and Simberloff (2009) point out in their arguments

against assisted migration, “contingency is the largest impediment to prediction”. Genetic

adaptation can increase the chance of invasiveness, shifting conditions can suddenly and

dramatically favor a novel species, crossbreeding can dilute native species gene pools and

result in new invasive hybrids, and synergistic relationships can cause unexpected

indirect impacts. To deliberately introduce a species with any confidence in knowing its

likely impacts, it is prudent to suggest that the justification of benefits should be great,

alternative native species are considered, and the risk-analyses must be able to at least

project a variety of scenarios that capture the complexity of the ecological context.

Further research into sophisticated, yet widely applicable, techniques might be the pivotal

development towards conserving many species and systems under rapidly changing

conditions.

3.2 Managing for establishment and spread

There is a range of cultural and ecological reasons for considering established species

separately, with origin becoming a relatively less important informer of management

decision-making. An established species has had time to become embedded into the

ecosystem and potentially more populous. Its removal may lead to unanticipated and

undesirable impacts (Zavaleta et al., 2001), or involve more direct killing or use of toxic

chemicals, a strategy that is alarming to some stakeholders and may have its own

environmental impacts. Finally, an established population has had more time to become

relevant to people’s sense of place or to provide other cultural services that need to be

considered in evaluation of the costs and benefits an invasive population.

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Thus, criteria for choosing a species management option post-establishment (eradicating,

controlling, containing, accepting, or even encouraging a particular population) should be

more impact focused. It is widely acknowledged that the impact of a species will often be

complex and include multiple ecological, cultural, and/or economic components

(Andersen et al., 2004). Once a species is imbedded in a system, contextualizing

management decisions within these components of impact, rather than focusing on

whether the species is native or non-native, is important to form effective control

strategies.

Here, we focus on the ecological aspects of impact by reviewing potential non-native

species impacts to the ecological dimensions of biodiversity, ecosystem function, and

resilience – three common goals in conservation and restoration projects (Chapin et al.,

2010; Society of Ecological Restoration International Science and Policy Working

Group, 2004). For a discussion of more socio-cultural species impacts, see (Pejchar &

Mooney, 2009). We emphasize that impact assessment must consider more than just the

detrimental role the species may play. Non-native species often cause a range of negative,

neutral, and positive impacts (Figure 2). Though clear classification into any of these

three categories is often difficult, the entire spectrum of impacts – defined within the

appropriate spatial and temporal context – needs to be recognized for effective

management. We address key considerations to understand impact ‘to what’ without

explicitly outlining methodologies for measuring that impact (see Parker et al., 1999).

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Figure 2: Potential impacts of a non-native species on other species. Assigning these decisions involve both extensive knowledge of the impacted system as well as the assumption that impacts can be quantified into the three options shown. Adapted from Goodenough (2010).

3.2.1 Understanding Impacts to Biodiversity

One of the most contentious debates about the negative effects of non-native species

centers around their impact on native biodiversity (Davis, 2003; Gurevitch & Padilla,

2004). To address the question for an individual species or system, researchers and/or

managers must clearly define the type of biodiversity of concern – richness (α: within

site, β: between sites, or ɣ: over all sites) or some combination of abundance and richness

captured in one of many diversity indices. Additionally, richness alone neglects to

quantify impacts to abundance or distribution that might be critical in defining ecosystem

biodiversity. Even those indices that measure both richness and relative abundances (e.g.

Shannon-Weiner, Simpson, or Berger-Parker) do not capture all aspects of biodiversity

concerns such as genetic diversity. There has been some work to develop reliable metrics

to quantify the level and impacts of invasion (Catford et al., 2012), and these are a

meaningful step towards establishing standard measurements of non-native species

impact in a whole ecosystem context. One important consideration for continued

development along these lines is the importance of uniqueness. Many parts of the world

have high rates of local or regional endemism. If local or regional species diversity is

maintained or increased after an invasion but at the cost of numbers or abundances of

globally unique species and assemblages, then this is a net negative in overall

conservation terms.

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Though many impacts of non-native species on biodiversity have been shown to be

negative (Vilà et al., 2011), there can be important biodiversity benefits of non-native

species. Increasingly, there are observations that non-native species provide important

resources, habitat or mutualisms for maintaining native species populations (Ewel &

Putz, 2004), including listed threatened species (e.g. non-native honeysuckle as the

preferred habitat of birds (Whelan & Dilger, 1992) and the invasive tree, tamarisk, as

habitat for the threatened Southwestern Willow Flycatcher in the United States (Sogge et

al., 2008). This is often the result of a decline in the abundance of native species that

previously performed these supporting roles, and the cause of decline cannot always be

attributed to the presence of non-native species. In cases where native species may

depend on the presence of a new non-native, the simplistic solution of removing the non-

native species may result in negative impacts.

3.2.2 Understanding impacts to ecosystem function

Ecosystem function is a synthetic framework for understanding the dynamic processes

that occur in systems. Functions can encompass energy pathways (e.g. productivity, inter-

trophic exchange rates, respiration, or decomposition rates), biotic-abiotic interactions

(e.g. nutrient cycling, water cycling, or disturbance regimes), and biotic-biotic

interactions (e.g. habitat provision, lowering invasibility, pollination). It is not an a priori

truth that a non-native species population in a system will significantly alter existing

function. If for instance, a non-native species replaces a native species that is functionally

similar, such as the replacement of golden wattle by Chrysanthemoides monilifera in

Australia (Weiss & Noble, 1984), overall ecosystem function will be maintained. On the

other end of the spectrum, some individual species populations can play roles that

fundamentally alter an entire system through one or multiple functional shifts (Crooks,

2002). These species are known as transformer species and are widely targeted for

management and control because of the dramatic, often irreversible ecological changes

resulting from their presence.

Most non-native species will subtly alter ecosystem functioning through the alteration of

ecosystem processes such as nutrient and energy flows (Vitousek et al., 1987) or by

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altering system structure (Crooks, 2002). In many instances, multiple ecosystem

functions are affected by a single non-native species. There are sometimes trade-offs,

with one function potentially enhanced, and one degraded. In restored mine sites in the

US Midwest, for instance, the overwhelmingly invasive non-native grasses provide good

habitat for some bird species but due to their vegetative homogeniety, not others (Scott et

al., 2002). Additionally, one single species may negatively alter functioning in one

location, but neutrally or positively alter function in another. Spotted knapweed,

considered responsible for poisoning plants and rerouting elk migrations is now being

discussed for protection by the honeybee growers in Michigan and by butterfly

conservationists in New York (Runk, 2011). There may be instances when different

values and assessments will lead to eradication of a species in one location, control

elsewhere, and tolerance in another, choices that are independent of the native/non-native

distinction but rather dependent on the specifics of the landscape and its interaction with

the non-native species. Because of the complexity of non-native species impacts, the

ecosystem functions that are considered as key within the system of concern must be

understood in order to quantify net impact. What is considered “key” is likely to be

context-dependent and will vary among different elements of society. Hence, it may be

hard to pin down: this is an often overlooked aspect of the entire debate on invasive

species management.

3.2.3 Understanding Impacts to Resilience

Resilience is a complex term that has been defined in a number of ways throughout its

30+ years of use. If we use the most recent of these (e.g., Chapin et al. (2010):

“capacity of a social–ecological system to absorb a spectrum of shocks or perturbations

and to sustain and develop its function, structure, identity and feedbacks as a result of

recovery or reorganization in a new context.”), origin of species can play multiple roles in

this function. Non-native species have not evolved with the historical disturbance regime

and may lower system resilience by being more susceptible to change than displaced

native species: however, the converse can also be true. Additionally, some displaced

species might play an important role in system recovery that is not filled by the non-

native species.

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Functionally dissimilar non-native species may become a force in the system that pushes

it to a different state. Non-native grasses in woodland systems are well-known to interact

with fire and ultimately lead to a state-change from woodland to grassland (D'Antonio et

al., 1999). In instances such as these, the non-native species is both a driving force

behind the disturbance as well as a force limiting the system's resilience to the

disturbance. Once the state-change has occurred, the non-native species can function to

increase the resilience of the new state. In the case mentioned above, the new grassland is

difficult to restore to a woodland state because of the grasses’ high resilience to further

fire.

Conversely, the presence of some non-native species may increase a native system’s

resilience to disturbance and change. Many current disturbance regimes are not

reflections of historical regimes. Altered fire regimes, clearing, grazing, and other

human-induced disturbances have been introduced in many systems through the sustained

interaction of humans with ecosystems. The impact of severe disturbance in Argentina

has, for instance, been mediated by the presence of a non-native shrub, Rosa rubiginosa.

It moves into highly degraded Argentine woodland systems and dramatically shortens

recovery time by providing shelter to native seedlings from cattle grazing (De Pietri,

1992). Additionally, slow changes that are occurring globally such as climate change and

atmospheric nutrient deposition are shifting the conditions in which systems must sustain

their state and processes (Steffen, 2005). Non-native species that are adapted to these

new changes may act to reinforce an ecosystem’s structure, function, and processes

against dramatic changes.

3.2.4 The continued utility of origin

The choice between using origin or impact as informative tools is not a one-or-the-other

decision. We argue that it is more of a continuum, with origin playing a decreasing role

as the non-native species becomes more embedded in the ecosystem. At more

established stages, a fair assessment of the consequences of the non-native species can

more adequately inform necessary management tactics such as control, mitigation, or

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acceptance. Still, knowing a species is non-native can guide impact assessment to some

extent. The consequences of disjunctive evolution are that non-native species are more

likely to be ecologically disruptive (Simberloff et al., 2011; Williamson & Fitter, 1996),

an a priori understanding that encourages caution and careful monitoring not required for

most native species. Additionally, the species behavior and traits in its native range can

potentially predict behavior and traits in new ranges. Research has shown strong links

between the geographic extent or abundance in the native range and the likelihood of a

species becoming invasive in an introduced range (Goodwin et al., 1999).

Unpredictability of future behavior is a major factor limiting the adoption of impact

assessment as the main or only guide in non-native species control. Experience has

shown that despite our best efforts to understand impacts, even seemingly benign non-

native species can swiftly and unexpectedly undergo population expansion that results in

severe repercussions in the invaded system (Crooks, 2005; Mack, et al., 2000). Therefore

the benefits of a non-native species, though requiring quantification and consideration,

may clearly need to be weighed against future detrimental effects arising after a lag

phase. Here, origin can again be a potential guide as non-native species from climatically

similar home ranges may potentially be assumed to have shorter lag times (Larkin, in

press). However, other considerations such as the potential for increasing propagule

pressure may also determine the probability of a species experiencing a lag phase (Essl et

al., in press). Additionally, the relationship between non-native species populations and

their impacts is an interactive process between the novel organism and the recipient

system and is often inherently unpredictable and context-driven. Hence, there remain

severe and inevitable limitations in our ability to predict the future and manage

accordingly.

3.2.5 Further considerations in management decision-making

Beyond origin and impact, there are many considerations managers assess in the

decision-making process. The impacts of the management action should be weighed

against the impacts of the non-native species. Often control methods may themselves lead

to ecosystem degradation: heavy use of chemicals may have adverse system impacts and

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thus undermine native species population survival, ecosystem function and resilience.

Evidence of past impacts of pesticide and herbicide use is abundant, and chemicals such

as the widely used glyphosate have been found to have long-term impacts on soil biota

and chemistry (Araújo et al., 2003) while other herbicides that were touted to increase

native plant diversity can reduce native diversity over the long-term (Rinella et al., 2009).

Although modern chemicals are often considered less harmful and more specific, few are

thoroughly field tested across a range of environments and the cumulative effects of

multiple chemical applications is largely unknown. For example, recent findings show

that systematic insecticides can lead to a dramatic loss of queens and can interfere in

foragers’ ability to navigate back to the hive (Stokstad, 2012). Additionally, increasing

community disquiet with the heavy use of chemicals and toxins can place control

programs at risk of discontinuation. For example in New Zealand, the poison 1080 is

used extensively to control non-native mammal species, but is now the subject of an

emotive popular campaign to stop its use (Winters, 2009). There is mounting evidence

that the general public have very negative attitudes to the use of poisons and pesticides to

control species (Bremner & Park, 2007).

In many cases, the probability of successful management may be unclear. Non-native

species often respond positively to disturbance. If control methods cause continual

disturbance, it may re-enforce non-native species propagation rather than diminish it.

Similarly, removing a species without a clear plan for filling that niche often leaves a

"weed-shaped hole" (Buckley et al., 2007). Sometimes what moves in and fills it can be

worse. In the north and mid-west of the United States, efforts to remove knapweed often

lead to a subsequent invasion by cheatgrass. Though both species are known to be

conservation threats and poor forage material, cheatgrass is more flammable and has been

shown to increase fire frequency in heavily invaded systems (Menakis et al., 2002).

Finally, management may be better served by focusing less on removal and more on

ecological and evolutionary dynamics. At the moment, we often take snapshots of

impacts and develop concomitant snapshot goals. However, when we look at longer

timescales native species may be able to adapt to non-native species. In Puerto Rico,

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some abandoned pasture and coffee plantations initially fill in with non-native tree

species. However, as the time since colonization increases, native species increase in

importance, often out-competing the more shade-intolerant non-native species. The

resulting mixed forest has been found to be equally resilient to hurricane damage as

native forest (Lugo, 2004). A further example is the recent finding that some fauna

species are adapting behaviorally or otherwise to the cane toad which is spreading across

northern Australia. The poison secreted by the toad is lethal to many native species and

has caused significant mortality, but in areas where toads have been common for some

time, some native species numbers are increasing through either learned avoidance or

rapid evolutionary responses (Shine, 2012).

4. Conclusion

In the past few decades, the language and understanding of ecology and conservation

biology has moved from an almost exclusive focus on biodiversity, to a broader focus

encompassing biodiversity, ecosystem function, and resilience. This distinction is

important for understanding the issue of non-native species in light of conservation goals.

From the perspective of traditional global conservation, the preservation of native

biodiversity is the main driver behind management decisions. From the perspective of

broader goals linked with managing complex socio-ecological systems, the maintenance

of ecosystem function and resilience may shift management decisions in ways that

require changes in procedures necessary to achieve biodiversity goals. Non-native species

management decisions may involve similar trade-offs and complex considerations.

These trade-offs and complexities extend into socio-cultural issues (Richardson, et al.,

2008), with consideration of community interests and values, stakeholder goals, and

economic constraints or repercussions playing just as large – or a larger – role in species

control decision-making than ecological considerations. Often this can make impact

assessments, decision criteria, and final decision-making difficult and value-charged. The

challenge for modern invasion biology is to inform these management processes with

relevant research. One avenue that needs further development is research into trade-offs:

within ecological, conservation, and socio-cultural goals, and between them all.

29

Additionally, further development of adaptive management techniques can offer a set of

iterative decision-making tools. If properly implemented, many of the risks or

uncertainties inherent in allowing non-native species to persist in a system or in removing

them from a system in which they have been established long-term can be monitored and

ameliorated through adaptive response of managers.

Young and Larson (2011) found that invasion biologists are relatively ambivalent about

their advocacy role in policies. However, it is argued that environmental law is made

powerful and legitimate by the science behind it (Tarlock, 1994), and there is some fear

among scientists that their approaches and debates will have larger repercussions. Should

scientists and managers begin to loosen their strict perspectives against invasive species,

will regulatory agencies follow? Will they see it as an opportunity to reroute those

resources, disregarding the careful consideration required to understand the long-term

implications of allowing an invader to persist in an ecosystem? These questions highlight

not that political fears should guide scientific direction, but that science should be carried

out with careful planning, detail, and clear communication of findings, and that

management applications should be cautious and closely follow scientific results. As

noted by Gould (1998), “We have some ethical responsibility for the consequences of our

actions.” Current debate around the management of native and non-native species is

essential for pragmatic application. However, finding a middle ground on which all sides

of the debate can respectfully agree, rather than perpetuating the divisive debate on points

of difference, is a vital process. We hope that this paper contributes to that process and

that all sides will continue to reflect on new information and new context and its bearing

on these questions.

Acknowledgments The authors would like to acknowledge the vast array of researchers that have contributed to this debate over the years. More specifically, N. Shackelford would like to thank Dr. Kris Hulvey for her insightful and constructive comments on earlier versions of the manuscript and Dr. Sarah Swope for an enlightening discussion of certain sections. R. Hobbs acknowledges funding support from an Australian Research Council Australian Laureate Fellowship, the Australian Government’s national Environmental Research Program and the Australian Research Council Centre of Excellence for Environmental

30

Decisions. T. Seastedt’s research on invasive species has been supported by a series of USDA grants.

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CHAPTER 3

Investigating the relationships between diversity loss, invasion, and fire regime shifts in a biodiversity hotspot

N. Shackelford, M. Renton, M. Perring, K. Brooks, R. Hobbs

Abstract: The relationships between disturbance, invasion, and species loss are often difficult to tease apart but teasing these apart is essential for effective management of some systems. We investigated fire history, invasion by a native tree species, and diversity loss in eleven heathland patches across a single reserve in Western Australia. We used plant species surveys from 1983 and from 2011 to quantify species loss, population surveys of the invasive tree, and fire history, to examine the strength and direction of the relationships between them. Within the last thirty years, approximately 11% of the plant species richness was lost from all surveyed patches across the reserve. On a patch-level, we found only a 4% average decrease in plant species richness, but large species losses and gains that imply considerable compositional shifts. Though such shifts would be expected in thirty years, many of the gained species were common, potentially opportunistic species, while those lost were often locally rare woody perennials. In further analysis, we found that time since last fire correlated only weakly with either species loss or invasion density. The relationship between invasion and species loss was strong. However, the strength of that relationship was not fully consistent between spatial scales: at a patch-scale the relationship was much stronger and clearer than at a quadrat-scale. We identified a potential state-change to dominance by the native invasive and the need to directly address invasion in these extreme cases. Though we were unable to pinpoint causal relationships between fire regime, invasion, and species loss through observational study, there is now strong evidence supporting the role of invasion in species loss and the resulting need for invasive species control. Further experimentation is required for a mechanistic understanding of the exact causes of species loss.

Keywords: kwongan, sandplain heath, Allocasuarina huegeliana, native invasion, woody encroachment

Introduction This study investigates the relationships between invasion by a native tree species, fire,

and species loss in the biodiverse heath of Western Australia. Understanding ecosystem

dynamics often depends on trying to disentangle the interactions among disturbance,

invasion, and biodiversity loss, processes that can occur together in seemingly

inextricable links and feedbacks, with the nature of the relationship between them

36

dependent on the exact circumstances and system under study (Didham et al., 2007).

Invasive species are known to alter ecosystem processes (Ehrenfeld, 2010; Vitousek et

al., 1997), but whether biodiversity loss is due to these invader-driven ecological changes

or whether the disturbance that often co-occurs with invasion is the root cause is at times

unclear. It is particularly difficult in the case of plant invasions, which result

predominantly in competitive and indirect effects such as shifts in mutualistic

relationships; thus, their impact to invaded systems can be difficult to quantify. Though

large declines of species have been detected in heavily invaded areas, few if any proven

examples exist of extinction caused by competitive exclusion alone (Davis, 2003;

Gurevitch & Padilla, 2004). Therefore it is difficult in most plant invasions to

unequivocally classify the invaders as a cause of species loss, despite some cases of

invasive species clearly acting as drivers of detrimental change in an ecosystem.

When invasion and disturbance are both present, attempts to pull apart the cause of

biodiversity loss have been both observational and experimental with a range of results.

In a study of biodiversity loss, invasion, and habitat perturbation in freshwater systems,

Hermoso et al. (2010) used structural equation modeling to analyze spatially large scale

observational data. They found that invasion intensity was the single-most important

predictor in native species decline, with habitat perturbation having a negligible role in

native species decline, per capita effect of the invasion, or the local proliferation of

invasive species. In contrast, Chabrerie et al. (2008) studied habitat conditions,

disturbance history, plant loss, and invasion in European forest and found that habitat

conditions and disturbance history correlated most strongly with final plant communities.

Using experimental manipulation of marine systems, Bulleri et al. (2010) attempted to

determine whether Caulerpa racemosa is a passenger or driver of ecological change

responsible for the loss of native canopy-forming algae in Mediterranean rocky reefs.

They found that C. racemosa was both a passenger and a driver, its role being dependent

upon the stage of invasion. It starts invading rocky reef systems as a passenger of canopy

disturbance, but becomes a driver of change through the alteration of sediment loads.

This led to declines in canopy algae species, even under low density invasions. The

variety of results found in previous studies imply that though the relationships among

37

invasion, degradation or disturbance shifts, and diversity might have some generalizable

patterns, the specifics will be largely system and species dependent.

To understand the probable drivers of species loss - specifically the associations between

loss, disturbance, and invasion in an area of conservation priority - we focused our study

on kwongan, a highly biodiverse sandplain heath system in southwestern Australia. These

systems are historically fire-prone, with much of the biodiversity composed of pyrogenic

species with life history strategies adapted to the local fire disturbance regime (Keith et

al., 2002). This makes kwongan an ideal system for investigating the effects of shifting

disturbance. We surveyed eleven protected heath patches anecdotally thought by local

land managers to be losing plant species biodiversity at dramatic rates in the past few

decades. The patches are contained in a Tutanning Nature Reserve, an area in the

Western Australian Wheatbelt managed by the Department of Environment and

Conservation (DEC) since the 1960s. Local land managers believe the perceived species

loss is likely due to one or both of two potential causes: a shift in the fire regime due to

extensive land use changes and fragmentation in the last century and/or invasion by the

native tree Allocasuarina huegeliana (L.A.S. Johnson).

Investigations of fire occurrence in the Wheatbelt have found that the smaller, highly

isolated fragments have a lower fire frequency, lower intensity, and smaller size of fire

events than unfragmented landscapes (Parsons & Gosper, 2011). Changes in fire regimes

can have large implications for fire-dependent species; in the absence of fire, some

populations may experience sharp declines or local extinction (Keith, et al., 2002;

Quintana-Ascencio et al., 2003; Yates & Ladd, 2010). Mallee-heath, a similar system

also found in the Wheatbelt, has been found to undergo structural changes and

senescence after approximately 45 years without fire (Gosper et al., 2011). In addition to

directly impacting species richness and vegetative composition, the decrease of fire

occurrence or intensity might allow fire-sensitive species to spread and thrive in areas

previously unavailable due to repetitive fire events, potentially leading to native invasion.

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Though invasive species are most commonly aliens, native species at historically absent

or at low levels can function as invasive drivers of ecological change – often to the

detriment of surrounding species – when undergoing population expansion and spread

(Valéry et al., 2009). The native tree Allocasuarina huegeliana was rare in heath

historically (Bamford, 1995; Main, 1993) but commonly occurs in adjacent, almost

monoculture woodland stands. In the last thirty years, it has increasingly been invading

Tutanning heath patches (Maher et al., 2010). Other sites across Australia have similarly

recorded an increase in Allocasuarina density and a corresponding degradation of historic

species composition (Kirkpatrick, 2004; Lunt, 1998; Main, 2001). In the case of

Allocasuarina invasion, changes in canopy structure, heavy litter fall, nutrient shifts, and

competition are all potential drivers of biodiversity loss as a result of the invasion process

(Figure 1).

Figure 1: Example of advanced stage A. huegeliana expansion into Tutanning Nature Reserve heath patch (left) with little living but some dead heath species in the understory; example of an A. huegeliana expansion front into Tutanning heath patch (right)

In order to investigate the relationships between fire history, invasion by A. huegeliana,

and plant species loss, we first quantified the plant species loss in the last 30 years, as yet

anecdotal, using observational data from plots surveyed in 1980-1983 and repeated in

2010-2011. We then examined patterns of tree invasion and time since last fire to address

three major questions:

1) What is the relative strength of the relationships between disturbance regime (fire

history) and plant species loss, and invasion density of Allocasuarina huegeliana

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and plant species loss in Tutanning Nature Reserve, a case study of kwongan in

Western Australia?

2) What is the relative strength of the relationship between disturbance regime (fire

history) and invasion density in Tutanning?

3) What are the plant compositional changes over the last thirty years, including both

species losses and gains, and their relative environmental correlates?

A better understanding of the mechanisms behind species loss could aid managers in

mitigating causal factors and so prevent further loss.

Methods Site

Tutanning Nature Reserve (32°31′ S, 117° 23′ E) is a class “A” reserve approximately

2,140 ha in size. Located 150 km southeast of Perth, Western Australia, it is surrounded

on all sides by agriculture, making it an island of remnant vegetation. Elevations on

reserve range from 320 m to 430 m. It contains a mosaic of vegetation including

Eucalyptus woodland, granite outcrop vegetation, and kwongan heathland. The climate is

Mediterranean, with an average annual rainfall of only 420 mm falling mostly in winter,

which creates distinct seasonality in plant growth and flowering rhythms. The reserve

experiences low human traffic or impact, and contains few non-native invasive species.

Though Tutanning is a large reserve (~2,250 ha), it is entirely surrounded by private

agriculture, a landscape characterized by strict wildfire control. Controlled burns for

biodiversity management are now being implemented, but individual heath patches have

often gone 60-70 years without fire. Within the reserve, all heath patches were identified

and surveyed for plant species composition in the early 1980s (Brown & Hopkins, 1983)

and were the focus of this study. When original floristic surveys were completed in 1983,

the longest fire-free intervals in a single patch ranged from 16 to 45 years. Between that

time and the recent survey, most patches went without additional fire, resulting in eight of

the eleven patches having > 45 years without fire (fire-free intervals in a single patch

ranged from 13 to 73 years). Thus, the longer intervals experienced at Tutanning are

potentially of some management concern.

40

Floristic surveys

We followed the nested survey design laid out in Brown and Hopkins (1983). In the

original survey, 13 patches were surveyed in spring (September – November) over three

years from 1980-1983. The surveys included 11 individual patches, two of which – Sites

5 and 6 – were surveyed as two ‘sites’ each. Site 5 was bisected by a woodland stand of

Banksia attenuata and so subdivided, and Site 6 contained two areas with different fire

ages. However, in the original survey, there was no significant compositional difference

between 6 and 6a and no physical separation between the patches. Therefore, we did not

survey 6a separately. Sites 5 and 5a, however, are still split by a woodland stand and had

some notable compositional differences; thus, we sampled them individually.

Additionally, Sites 8, 1, and 5 were burned within the two most recent survey years. Site

8 was burned in 2010 and could not be surveyed at all due to the sensitive topsoil

structure of recently burned patches. Sites 1, 5, and 5a were burned in 2011, and so were

surveyed in 2010 only. We therefore had eleven patches, three of which had a lower

sampling effort than the other eight.

In each of the surveyed patches, the bottom left corner of a 10 m x 10 m quadrat was

staked with a permanent marker in 1983. In 2010, the quadrats were relocated and re-

surveyed for presence data on all species. The marker was then used as the bottom left

corner of an expanded quadrat measuring 10 m x 50 m, and then expanded again to 20 m

x 50 m. Finally, the rest of the heath patch was blanket surveyed for any missed species

(sensu the species lists of Brown and Hopkins, 1983). This helped prevent small

vegetation shifts from resulting in skewed absence recordings. The surveys were

conducted in the spring of 2010 and 2011 to match the previous surveys. Rainfall over

the 2010/2011 period showed extreme behavior. In 2010, there was a severe summer

drought and rainfall well below average in winter, while in 2011 there was consistently

high rainfall in all seasons. The data captured species loss, species gains, and both

considered together as changes in total raw species richness. Species loss is defined here

as any species recorded in original surveys but not recorded in the recent surveys while

41

species richness is the number of species found in each patch in the 1983 data and the

same in 2011 data.

Population survey

The intensity of the invasion by Allocasuarina huegeliana in individual patches was

captured through population surveys. Population surveys of the species of concern,

Allocasuarina huegeliana, were conducted in all heath patches over the summer of

2010/2011 (November – January). Three transects were laid out in each patch from edge

to edge of the heath as delineated by a combination of aerial imagery and on-ground tree-

line observation. Again, we built on previous work in the area by following a similar

protocol to Maher (2007). The transects ranged in length from 100 m to 280 m depending

on the size of the patch. Every 30 m, we surveyed a 10 m x 10 m quadrat using the

transect point as the bottom right corner. In rare instances, we were forced to use the

transect point as the bottom left corner of the quadrat; for example in one patch,

exclosures from previous work in the patch were directly adjacent to the right side of the

transect line. A. huegeliana was counted and each tree measured for diameter at 0.4 m

above ground level for adults (defined as any tree greater than 1 m tall), 0.1 m above

ground level for seedlings less than 1 m tall. When investigating potential environmental

correlations with A. huegeliana populations, we used population density measures (tree

ha-1). As a possible explanatory environmental variable input into all other analyses,

however, we used the allometric substitution of the radius cubed (AH.Vol or volumetric

density in reported results) to capture the effects of tree coverage.

Environmental variables

Average slope, elevation, and aspect were determined for each heath patch from a

georeferenced digital elevation map (DEM) available from the U.S. Geological Survey,

while distance from the edge of the patch (Dist in reported results) to the edge of the

reserve was estimated using 2007 aerial imagery. Aspect data from the DEM (A) was

transformed for use in the generalized linear models using the equation:

a = cos(A*π/180)

42

The resulting data ranged from -1 (south) to 1 (north) with 0 representing directly east or

west. Patch size (Size) and species richness in 1983 were taken directly from Brown and

Hopkins (1983).

Soil information and time since last fire were obtained from DEC records. Over the

eleven patches, there were six soil types: laterite, sandy-laterite, yellow sand, grey sand,

duplex, and sandy clay. We combined yellow sand with grey sand and duplex with sandy

clay according to similarities in soil description, location, and vegetation composition,

thus leaving four soil classifications (laterite, sandy-laterite, sand, and duplex). While

compiling information on the time since last fire for each patch (TSF in reported results),

we noted one issue. DEC carried out a managed fire through Site 10 in 2007. However,

the fire was described as a ‘fizzle’, one that burned cool and small. Thus, the fire caused

relatively low mortality in adult vegetation and due to its autumn timing would not have

interrupted flowering or seed set in annual species (Greg Durell, pers. comm.). As we

were considering fire because of its role in the system as a mortality-inducing

disturbance, we decided to discount the 2007 fire in Site 10.

Surveys in 1983 and 2011 were conducted by different surveyors and there were possible

inconsistencies in the distance and detail each surveyor used in collecting species outside

the quadrats. Because of this possible inconsistency, when analyzing loss and differences

in composition and richness between years we performed two separate analyses: one with

all records included, and one in which we dropped all species recorded outside of the

nested quadrats. However for analyses of richness and floristic composition within a

given year, we utilized all collected floristic data. We also used all recorded species when

constructing the non-parametric analysis of composition of both years together. In order

to do so, we first ran the non-parametric analysis with all data and compared those results

to the results using only data in the quadrats. As there were no major discrepancies, we

determined that using all data was a viable and ecologically sound option in the analysis.

43

Statistical analysis

We analyzed invasive species population data for correlation with the plant species

results. We also explored correlations of the plant species and invasive species population

results with environmental variables to test the hypotheses that shifted fire regimes have a

strong correlative – and thus potentially causal – relationship with the species loss and/or

the invasion. Species gains, A. huegeliana density, and species richness were all modeled

using Poisson generalized linear models (GLMs). We checked for overdispersion and

found the Poisson model to be a good representation of the data. Because species loss is a

binary lost-or-retained distribution, it was modeled using the binomial GLM rather than

the Poisson distribution. All continuous explanatory variables were transformed to

standard normal distributions (mean of zero and standard deviation of one) for ease of

relative effect size interpretation. We did not include interaction terms in our modeling

due to our low initial degrees of freedom (ten). Model optimization was carried out

starting with the maximal model and using stepwise deletion of non-significant

continuous terms (Crawley, 2007). Once all continuous variables had been reduced as

much as possible, we then grouped non-significantly different soil categories together one

pairing at a time. Significance of reduced models was tested with Chi-squared ANOVAs

(Zuur et al., 2009). Where significant differences were found between models, the model

with the lower AIC-value was retained.

We also used permutational ANOVAs (PERMANOVAs) to identify significant

environmental variables that contributed significantly to explaining differences in

composition among patches (Anderson, 2001). We used Bray-Curtis distance as our

measure of compositional dissimilarity. The best models were found by first fitting the

full model and then stepping backwards by dropping non-significant (p > 0.05) variables

until the drop caused any significant explanatory variables to lose significance. In all

analyses, only first order interactions were considered due to the limited number of data

points. For comparing composition between the two years we performed non-metric

multi-dimensional scaling (MDS) for exploratory analysis (Faith et al., 1987). All

statistical models were run in R (R Development Core Team, 2009) using either the base

44

program or the vegan library modeling functions for non-parametric and permutational

analyses (Oksanen et al., 2011).

Heath systems are hyperdiverse (Hopper, 1979; Marchant, 1973) and Tutanning is not an

exception (Figure 2). Thus comprehensive, detailed analysis on individual species losses

and gains at scales below the reserve scale was difficult. We therefore report on general

trends with a focus on species that seemed consistently lost or gained.

Figure 2: Species-area relationship for heath patches in Tutanning Nature Reserve. The grey points are results from floristic surveys for all sites and both years. The black line represents the estimated exponential relationship (S = cAz where c ≈ 27.2 and z ≈ 0.14).

Results Species losses and gains

When excluding species outside the quadrats, we found that an average of 39% of those

species recorded in 1983 was lost by 2011. The strongest relationship of loss was with

soil type (Table 1), with the sandy-laterite and duplex soils grouping together. Laterite

soils and sand showed a significant reduction in losses relative to the other two soils.

Species gains were fairly high within the quadrats, with 27% of 2011 species found to be

new recruits from the 1983 surveys. Increasing time since last fire, higher elevation,

gentler slopes, and laterite soils all correlated with increasing species gains. All other

soils showed similar gains.

45

Response Final Model Dev Df

Loss (all) -1.17±0.16 + AH.Vol (0.23±0.16) + Size (0.18±0.18) –

Dist (0.4±0.2) + Soil[laterite2] (1.33±0.56) 0.96 6

Loss (in quadrats) 2.46±1.08 + AH.Vol (0.22±0.18) + Size (0.5±0.24) –

Dist (0.67±0.24) + Elevation (2.32±0.92) + Aspect(0.28±0.26) – Soil[laterite] (6.01±2.2) – Soil[sand] (4.97±1.86)

0.99 3

Gains (all)

5.17±1.24 – AH.Vol (0.43±0.26) + TSF (0.95±0.42) + Elevation (3.47±1.4) – Slope (2.47±0.96) –

Soil[laterite] (7.44±13.2) + Soil[laterite2] (3.24±2.3) – Soil[sand] (3.61±2.06)

0.94 3

Gains (in quadrats) 2.8±0.16 + TSF (0.38±0.26) + Elevation (0.71±0.36) –

Slope (1.25±0.54) – Soil[laterite] (0.95±0.78) 0.91 6

Diversity loss (all)

0.01±0.003 + AH.Vol (0.14±0.01) + Slope (0.4±0.04) – TSF (0.22±0.02) + Size (0.1±0.01) – Dist (0.15±0.01) –

Elevation (0.31±0.02) + Soil[laterite] (0.44±0.05) – Soil[laterite2] (0.55±0.04)

~1 2

Diversity loss (in quadrats)

0.96±0.06 + AH.Vol (0.03±0.01) + TSF (0.05±0.02) + Size (0.21±0.02) – Dist (0.11±0.02) + Elevation (0.56±0.05) –

Soil[laterite] (1.9±0.12) – Soil[sand] (1.3±0.1) ~1 3

Richness 1983 5.28±0.62 + Size (0.11±0.09) + Elevation (0.55±0.52) – Soil[laterite] (1.72±1.24) – Soil[laterite2] (0.57±0.4) –

Soil[sand] (1.22±1.02) 0.89 5

Richness 2011 5.44±0.5 + Elevation (0.78±0.21) + Aspect (0.16±0.08) –

Soil[laterite] (1.91±1.0) – Soil[laterite2] (1.3±0.43) – Soil[sand] (1.62±0.82)

0.96 5

Table 1: Final models with 95% Confidence Interval of the estimated parameter values, proportion of null deviance explained (Dev), and remaining degrees of freedm (Df) for species losses, losses excluding species outside the quadrats, species gains, gains excluding species outside the quadrats, diversity loss (or gain), diversity loss excluding species outside the quadrats, and species richness for 1983 and 2011. Biodiversity loss both with and without the species collected outside of the quadrats had more parameters in the final model than degrees of freedom and thus were not able to be used in finding parameter CIs. Parameters include A. huegeliana volumetric density (AH.Vol), distance to the edge of the reserve (Dist), patch size (Size), soil type, elevation, aspect, and time since last fire (TSF).

We found that including the species outside the 1,000 m2 quadrats made some differences

in the analysis results of species losses and gains. Biodiversity changes were distinct at

each scale, with an average of 27% species lost from the 1983 surveys balanced by 22%

new species gains in the 2011 surveys, smaller results than when analyzing the quadrats

only: average species losses from quadrats was 39% and average species gains in

quadrats was 27%. Those variables found to be significant were similar for losses and

gains between scales. However, losses on the larger scale showed weaker responses to

those variables than losses on the quadrat-scale. Gains on each scale showed the reverse –

with stronger relationships found on the larger scale than those found on the smaller,

quadrat-scale. Notably, on the site scale, A. huegeliana volumetric density had a

significant, negative correlation with species gains.

46

Composition of losses and gains was relatively consistent regardless of the inclusion of

species outside quadrats. New gains (Table 2) tended to be common species, many of

which were herbaceous (e.g. Ericksonella saccharata, Hydrocotyle pilifera, and

Trachymene pilosa). Some were found to be either specialized for drought-tolerance such

as Calandrinia corrigioloides (Harrison et al., 2008) or relatively prolific seeders such as

Lepidobolus chaetocephalus (Meney & Dixon, 1988). Lost species were both herbaceous

and woody; however, there was a predominant loss of shrub species (e.g. Acacia sp.,

Jacksonia sp., Leucopogon sp., and Persoonia sp.) and little corresponding gains of

woody species. Both herbaceous and woody species that were lost often showed

characteristics opposite of those that were gained: some such as Crassula sp. have shown

sensitivity to heat and drought (Facelli et al., 2005), while others such as Persoonia sp.

have been found to have extremely low recruitment rates with likely dormancy

mechanisms (Abbott, 1984).

Species Life form Patches Gained Total Patches

Eucalyptus accedens Tree 4 5 Baeckea floribunda Shrub 7 8 Boronia ramose Shrub 3 5 Daviesia incrassate Shrub 5 7 Jacksonia racemosa Shrub 6 6 Lysinema ciliatum Shrub 3 4 Verticordia chrysantha Shrub 3 3 Rytidosperma setaceum Perennial herb 3 4 Caustis dioica Perennial herb 7 7 Ericksonella saccharata Perennial herb 6 7 Lepidobolus chaetocephalus Perennial herb 5 6 Lepidosperma pubisquameum Perennial herb 3 5 Logania tortuosa Perennial herb 4 4 Thysanotus thysoideus Perennial herb 3 3 Tricoryne elatior Perennial herb 3 4 Calandrinia corrigioloides Annual herb 5 5 Hydrocotyle pilifera Annual herb 4 4

Table 2: Species gained in at least three patches between 1983 and 2011 including their growth structure (tree, shrub, perennial herb, or annual herb), the number of patches in which they were gained in 2011, and the total number of patches in which they were found in 2011.

47

Average net biodiversity change per patch similarly varied depending on the inclusion of

species recorded outside the quadrats. When only analyzing the quadrat richness, there

was an average loss of 14% richness per patch. However, when including all species

recorded in each site, diversity loss per patch of heath decreased to only a 4% loss.

Models of diversity loss on both scales showed significant, but weak, relationships with

all environmental variables (with one exception that slope was dropped from the quadrat-

scale model). The strongest relationships at both scales were with soils (Table 1). On a

broader scale, biodiversity over all patches combined decreased by 11%. The losses were

slightly weighted towards woody shrub species (Table 3), and most species that were lost

were originally recorded in only one or two patches total and thus were locally rare in

1983. There was one major exception to this pattern – Stylidium affine was recorded in

eight patches in 1983 and not recorded once in 2011 – but this is likely a taxonomic

misidentification between surveyors.

Table 3: Species lost from all combined heath patches between 1983 and 2011 including their growth structure (tree, shrub, perennial herb, or annual herb), the number of patches in which they were recorded in the 1983 surveys.

Composition and richness

We found relatively consistent correlations between certain environmental variables and

both composition and richness, though there were slight differences found between years

Species Life form Patches Species Life form Patches Acacia alata Shrub 1 Isopogon divergens Shrub 1 Asteridea nivea Perennial 1 Leporella fimbriata Perennial 3 Banksia prionotes Shrub 1 Leucopogon polymorphus Shrub 1 Banksia squarrosa Shrub 1 Levenhookia dubia Annual 1 Burchardia congesta Perennial 2 Melaleuca lecanantha Shrub 1 Calothamnus planifolius Shrub 1 Monotaxis grandiflora Shrub 1 Crassula closiana Annual 1 Paracaleana nigrita Perennial 2 Cryptandra nutens Shrub 1 Persoonia elliptica Shrub 1 Diuris longifolia Perennial 2 Persoonia trinervis Shrub 1 Erodium cygnorum Perennial 1 Pimelea sulphurea Shrub 1 Eutaxia parvifolia Shrub 1 Siloxerus multiflorus Annual 1 Goodenia caerulea Perennial 1 Stylidium affine Perennial 8 Hakea gilbertii Shrub 1 Stylidium emarginatum Perennial 2 Hakea trifurcate Shrub 2 Verticordia acerosa Shrub 2 Hibbertia microphylla Shrub 2 Verticordia densiflora Shrub 1 Hybanthus floribundus Shrub 1 Wurmbea pygmaea Perennial 1 Hypoxis glabella Perennial 2

48

and between the two compositional measures (Tables 1 and 4). Elevation and soil type

were significant in both years’ compositional PERMANOVAs. For richness in 1983, size

of the patch was also consistent in all models, while aspect was found to be significant

for richness in 2011. In compositional analysis, only elevation and soil type were found

to be significant in the final model for 1983. Analysis of 2011 composition found the

addition of slope retained in the final model.

AH.Vol TSF Slope Aspect Elevation Dist Size Soil Comp1983 - X X X < 0.01 X X < 0.01 Comp2011 X X < 0.01 X < 0.01 X X < 0.02

Table 4: PERMANVOA results as p-values for the significance of environmental variables in composition models for 1983 and 2011. Variables with Xs were included in the full model but using a step-wise method dropped due to lack of significance.

The MDS plot of composition in 1983 and 2011 (non-metric r2 = 0.989) showed close

similarities between years in the same patches (Figure 3). Only Site 2 was found to have

dramatic differences between 1983 and 2011 floristic surveys.

1

2

3

4

5

5a

6

7 9

1011

Non-metric fit, R2=0.989Linear fit, R2=0.947

Figure 3: MDS plot of composition. The MDS includes both 1983 (dots in the plot) and 2011 (stars). Each pair of points is labeled with the patch number, and the colors represent soil types (red=laterite, green=laterite/sand, blue=sand, black=duplex).

49

Allocasuarina huegeliana density

Surveys of A. huegeliana density showed a large variety in invasion levels between heath

patches, ranging from 20 (SE=8) trees/ha in Site 3 to 1425 (SE=3) trees/ha in Site 2.

When compared to the findings of Maher (2007), we found an increase in A. huegeliana

density from 2007 to 2010 in all but one of the eleven patches. In some patches, the

increase was small (an additional ~6 trees/ha) and could be a stochastic result of the

sampling. However, other patches experienced a large increase of up to ~150 trees/ha

with a high density of seedlings, implying a significant and real intensification in the

invasion. The maximal model of A. huegeliana volumetric density was not able to

reduced without significant loss of model explanatory power.

Discussion Species loss and gains differed across the three scales studied: whole reserve (all patches

combined), patch (all species recorded in a patch), and quadrat (only those species found

within the nested quadrats). Scale differences added to the hyper-biodiversity of the

kwongan and the diversity of species responses to environmental change made it difficult

to come to broad generalizations on the links between species loss, invasion, and fire

history. Thus, we separately analyzed individual scales and focused on specific species or

groups that were lost within each scale. On the reserve-scale, we found an 11% decrease

in overall plant species richness. Those species that were lost seemed to be a mix of

herbaceous species such as Siloxerus multiflorus whose natural habitat is adjacent to, but

not present in, heath and thus might just have been opportunistic records in the 1980-

1983 surveys, and low seed-producing woody and perennial species. Of those species

gained over the whole reserve, approximately one third of them appear to be from ranges

in which Tutanning was on the western-most edge (Figure 4).

On the patch-scale, the biodiversity loss was less than 5%. Most of the species changes

we found seem to be compositional shifts rather than dramatic diversity loss. The MDS

results showed that patches are most similar to themselves, but that some changes are

occurring between the two survey periods. This is to be expected over thirty years;

however, the shifts seem directed towards gains of herbaceous species or common shrub

species that are widespread in the landscape. Finally, on a quadrat scale, we found higher

50

losses than on a patch scale, though patterns of which species were being lost and which

gained seemed similar to those found on the patch level.

Though species were gained, some caution is needed in assuming the long-term nature of

the gains. Surveys in 2011 occurred after an exceptionally good year of steady rain, and

some gains on the patch and quadrat scales appear to be opportunistic herbaceous species.

Kwongan is characterized by its predominantly woody structure (Beard, 1984) as well as

the prevalence of rarity and endemism in plant species, and large amounts of variation

between patches (Hopper & Muir, 1984) Thus, conservation of locally rare woody and

perennial species is the management priority for heath, and these species are apparently

dropping out of the system at all scales. Many losses were of those species with a

predicted low annual recruitment rate, which explains to some extent their local rarity.

51

Figure 4: Florabase (Western Australian Herbarium, 1988-) distribution maps of Chloanthes coccina, Jacksonia racemosa, Logania tortuosa, and Verticordia chrysantha, all species gained in more than three patches, and the latter three new species recorded in Tutanning heath. The large black spot on each map is the approximate location of Tutanning.

The same caution should be exercised in assumptions of the permanence of species loss.

Woody and perennial losses on a patch- or reserve-scale might be only above-ground

loss, with the next fire or other necessary environmental condition leading to the breaking

52

of seedbank species dormancy. There have been many studies finding that species in

heath systems survive dormant in the soil seedbank for long periods of time (Auld et al.,

2000; Auld & Ooi, 2008). Life history traits such as those leading to fire-cued seedbanks

could imply the survival of species in the below-ground banks. However, fire-cued

strategies underlay our hypothesis that there would be a correlation between species loss

and fire history. However, the effect of time since last fire was unclear in our results,

making it difficult to claim that lost species were due to lack of dormancy-breaking cues

such as heat or smoke. Based on the type of data we collected and the results of previous

findings, the lack of strong correlation between fire history and species loss was not

wholly unexpected. In other similar heath systems, plant species diversity has been found

to peak immediately after a fire, decrease for a short time period, and then stay steady

despite longer spans of fire-free periods (Gosper, et al., 2011). Canopy and structural

senescence, however, was found to occur after approximately 45 years, a finding

confirmed for sandy and duplex patches at Tutanning: those exceeding 45 years since the

last fire showed major structural senescence. Additionally, the effects of fire might

depend in large part on season, uniformity, and intensity (e.g. Enright & Lamont, 1989;

Russell-Smith et al., 2003), information that we do not have for the patches.

Interspecific competitive exclusion (Tilman, 1982) could also be a cause of diversity

decrease over time in a resource-limited setting such as the Wheatbelt, and has been

shown to restrict the presence of certain locally rare woody species in Western Australian

shrublands (Lamont et al., 1989). A. huegeliana is an example of a highly competitive

species appearing in greater abundances in the heath that might be leading to competitive

exclusion. Though A. huegeliana volumetric density did not come out as a clear correlate

in our modeling of species loss at the quadrat-scale, it did appear in some models and the

relationship between invasion density and species loss on the patch-scale was

consistently strong. Notably, one reason for its weaker relationship on the quadrat-scale

might be a sampling effect from one particular patch. Site 7 experienced extremely high

species and diversity losses within the quadrat because it is now located in an A.

huegeliana woodland stand. The population surveys, however, were conducted within the

remnant heath patch and did not cross the surveyed quadrat. Survey results, therefore,

53

were a medium density of tree individuals in a patch with some medium density areas

and some high density areas.

However, given the assumption that losses in the quadrats were driven in part by A.

huegeliana invasion, our findings corroborate the scale-dependent relationship between

invasion and impact that has been found in previous studies. Research has often shown

that species diversity exhibits a lower correlation between invasion impacts and species

loss as the scale increases (see Powell et al., 2011 for a review). We found decreasing

potential impact at our two scales: species loss at a patch-scale was significantly lower

than at a quadrat scale.

Field observations paired with collected data support the hypothesis that A. huegeliana

invasion is having a dramatic impact on diversity once the invasion has progressed to a

certain density level. Sites 2 and 10 are almost completely converted to A. huegeliana

woodland (> 1,200 trees/ha) and experienced the highest species and diversity losses at

both scales. There is potentially a state-change at a certain density threshold in which the

system rapidly reconfigures from highly biodiverse heath to woodland with sparse

understory richness. Invasive species have been known to act as drivers of state-changes

in ecological systems. For instance, woody invasion due to fire suppression in prairie

barrens in southern Illinois have been shown to alter the impacts of reinstated fire

regimes and prevent barren return (Anderson, 1977). It is unknown whether this threshold

point potentially operating in heath systems would be reversible. Abrupt change does not

necessarily imply that the new state is stable or resilient to stress (Andersen et al., 2009;

Beisner et al., 2003), though the seedbank presence of heath species would be a

prerequisite for a natural shift back to a heathland state. Though recolonization by many

of the woody species would be unlikely due to low dispersal distances (Suding et al.,

2004), the longevity of many of these species in the seedbank may allow them to

reestablish given altered conditions.

The temporal data necessary to confirm and quantify the threshold at which such a state-

change might be occurring is currently not available. Additionally, our analysis of

54

environmental variables and their relationship to A. huegeliana spread did not reveal any

clear driver behind the invasion. Therefore the exact cause and consequences of the

invasion require further investigation, with a focus on attempting to quantify mechanism

rather than on observational study. Our study highlighted the need for management of

invasive species in the case of evident state changes. Current tools for identifying stable

state changes are available in the form of Threshold Autoregressive models, Average

Standard Deviates compositing methods, and a range of other uni- and multivariate

statistical methods (Andersen, et al., 2009) and further investigation is needed to confirm

and quantify the nature of the state changes linked with species invasion. The

identification of particular life history traits that might make species more prone to cause

state changes could lead to a generalizable understanding of which species might be of

highest management priority.

Ecological changes in Tutanning heath patches are complex, and broad generalizations

from our study rely on observational evidence alone. As has been found in the past (Pate

& Beard, 1984), soil type correlated strongly with different patterns of heath dynamics,

including composition, invasion density, and loss. Other factors not explicitly considered

in our study, such as climatic variables, also might play a major role. Many of the patch

and quadrat scale species gains were herbaceous species potentially responding to the

unusually high rainfall in 2011. On a larger and longer scale, the climate in Western

Australia has become drier and warmer over the last few decades as global climate

change has progressed (Bates et al., 2008; CSIRO, 2007). Species better adapted to these

environments may become more dominant and shift the overall composition to reflect the

novel climate. Many of the species gained on the reserve scale seem to be on their

western-most range extensions, implying their likely preference for the drier, warmer

conditions found further inland to the east.

Overall, however, the data suggests that A. huegeliana invasion seems to be a driving

force behind species loss, particularly in the case of extremely high densities such as at

Sites 2 and 10. How the invasion is impacting lesser invaded patches is unclear, and more

detailed investigation into abundance shifts and impact mechanisms is necessary for a

55

deeper understanding. Shifted fire history, hypothesized to be a cause both of the

invasion as well as species loss showed no clear pattern of correlation with any dependent

variable we investigated. Again, presence-absence data is likely inadequate for

quantifying the relationship of the heath flora with fire, as senescence is occurring but is

not captured in our floristic surveys. Fire history’s relationship with the invasion was

weak, and implies that there are other causes such as a drying climate that might be

involved in the spread of A. huegeliana. Finally, due to the limited number of patch

replicates, we were unable to capture interactions between invasion and disturbance, a

key component of the overall degradation that might change the impact of one or both of

the individual factors (Didham, et al., 2007).

Research into the underlying cause of an invasion and/or state change can be used to

guide management decisions. If shifts in the disturbance regime have been the

predominant driver behind an invasion, reinstating historic regimes may be the only

necessary management action needed to return a system to its pre-invaded state.

However, a resilient invader population or a resilient alternative state might necessitate

further management actions such as focused population control. Additionally, shifts in

disturbance regime might themselves be direct drivers of species loss (Hobbs &

Huenneke, 1992). Thus, addressing the disturbance regime is another potential avenue for

conservation management. Causal links between disturbance, invasion, and

environmental degradation are often difficult to establish in management scenarios when

observational data is the primary source of information. However, observational data

such as presented here provide essential information from which more detailed studies

experimental management programs can be designed.

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CHAPTER 4

Modeling disturbance-based native invasive species control and its implications for management

N. Shackelford, M. Renton, M. Perring, R. Hobbs

Abstract: Shifts in disturbance regime have often been linked to invasion in systems by native and non-native species. This process can have negative effects on biodiversity and ecosystem function but these may be ameliorated by the reinstatement of the disturbance regimes such as the reinstatement of fire in pyrogenic systems. Modeling is one method through which potential outcomes of different regimes can be investigated. We created a population model to examine the control of a native invasive that is expanding and increasing in abundance due to suppressed fire. Our model, parameterized with field data from a case study of the tree Allocasuarina huegeliana in Australian sandplain heath, simulated different fire return intervals with and without the additional management effort of mechanical removal of the native invader. Population behavior under the different management options was assessed, and general estimates of potential biodiversity impacts were compared. We found that changes in fire return intervals made no significant difference in the increase and spread of the population but did affect average and maximum densities reached in the simulated heath patch and estimated maximum biodiversity impacts. When simulating both mechanical removal and fire, we found that the effects of removal depended on the return intervals and the strategy used. Removal over the whole patch was more effective at slowing the population spread and decreasing average patch densities than just removing satellite populations. Our simulation model shows that disturbance based management has the potential to control native invasion in cases where shifted disturbance is the likely driver of the invasion. The increased knowledge gained through the modeling methods outlined can inform management decisions in fire regime planning that takes into consideration control of an invasive species. Though particularly applicable to native invasives, when properly informed by empirical knowledge, these techniques can be expanded to management of invasion by non-native species, either by restoring historic disturbance regimes or by instating novel regimes in innovative manners.

Keywords: native encroachment, individual-based model, fire, sandplain heathland, rock sheoak, adaptive management, intermediate disturbance

Introduction Invasive species have been shown to negatively impact biodiversity levels and ecosystem

function through direct effects of competition, mutualism, or predation, as well as

indirect effects such as changes to microclimate, disturbance regimes, and nutrient

cycling (Mack & D'Antonio, 1998; Parker et al., 1999; Vitousek et al., 1996). Although

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the term invasion most often applies to non-natives, similar indirect and direct effects can

be seen in the human-induced spread of some species within their own native range

(Davis, 2009; Valéry et al., 2008). Invasions by native species can represent major shifts

in species structure such as invasion by woody species in North American grasslands

(Van Auken, 2009).

The causes of native species invasion are not fully understood. However, disturbance is

often a precusor to biological invasion and this has been shown repeatedly in

observational and experimental studies (Hierro et al., 2006; Hobbs & Huenneke, 1992).

The link between disturbance and invasion is intuitively strong in the case of native

invaders since other factors commonly invoked to explain invasion by alien species, such

as enemy release, pathogen avoidance, or new mutualistic associations (Pyšek &

Richardson, 2010), do not usually apply. Instead, native species generally become

invasive due to a change in a factor related to the overall system, such as human-

mediated disturbance (Simberloff et al., 2011). For example, the alteration of historic

disturbance regimes, or new disturbances such as ungulate grazing, can act to shift

resources in such a way as to allow previously rare species to increase rapidly in

abundance and distribution. Hey-scented fern (Dennstaedtia punctilobula) in New

England has been shown to become invasive under altered grazing and thinning regimes,

spreading to create dense understories that restrict seedling germination of tree species

(de la Cretaz & Kelty, 1999).

The causes of invasion often suggest appropriate management strategies. To control a

native invasion, often treating the underlying cause of the invasion can manage the

species itself (Hobbs, 2000). Thus, returning a system to historical disturbance regimes –

or implementing well-planned novel regimes in the face of environmental change – can

be used in conjunction with more targeted species management such as manual removal

to manage invasion of native species. However, utilizing disturbance as a management

tool requires a foundation of ecological knowledge about a system that is generally not

available. Disturbance regimes are often multi-scale, both spatially and temporally, and

gathering comprehensive experimental and observational data over more than a single

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scale can be challenging. In particular, historical observations are often poorly

documented and replicated long-term experiments of large-scale disturbance events are

rare (but see the Coweeta LTER and accompanying publications: http://coweeta.uga.edu).

To date, the lack of information has prevented the widespread use of disturbance as a

management strategy. Here, we explore the utility of simulation modeling to inform the

disturbance-based management of native invasives by using it to understand disturbance

impacts to a native invasive population. In addition, the approach allows us to assess the

effects of multiple management scenarios. This is not a new technique in exploring

disturbance-based invasion control; there are many examples of fire regime modeling and

its impacts on invasive species populations (e.g. Higgins & Richardson, 1998; Higgins et

al., 2000; Pausas et al., 2006). However, application to native invasive species tends to be

limited to understanding how the disturbance regime shifts have led to the invasion rather

than how the disturbance may be used as a control measure (e.g. Fuhlendorf et al., 1996).

We created a spatially-explicit stochastic model parameterized using empirical field data

from a case study species – a native invasive tree (Allocasuarina huegeliana L.A.S.

Johnson) spreading in highly diverse Australian sandplain heath. An altered fire regime

over the last century has been implicated in the spread of A. huegeliana into the heath, an

invasion that is likely resulting in diversity declines and eventual loss of entire heath

patches (Beecham et al., 2009). Unlike experimental and observational data, this

methodology allowed us to assess management impacts over century-long time scales, a

necessary trait when disturbance in the system occurs only once every 40-70 years. Our

broad aim was to examine ways in which management decisions using disturbance

regimes to maintain conservation goals could be informed through modeling techniques,

illustrated with a particular system, but mindful of the need to be sufficiently general as

to be of use and interest more widely. Specifically, we focused on two key management

questions:

1. How does the return interval or regularity of fire regime affect the abundance of

Allocasuarina huegeliana and its spread into heath patches?

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2. How does mechanical removal in coordination with fire regime alter the

abundance of Allocasuarina huegeliana, its spread into heath patches, and its

estimated impacts to biodiversity?

Given the increase in germination immediately post-fire that is a trait of A. huegeliana,

we hypothesized that the longer fire intervals characterizing long return intervals and

occurring in random regimes would result in higher reproductive tree densities and thus

more rapid spread in the simulated system immediately post-fire. Additionally, we

hypothesized that mechanical removal in conjunction with fire – a strategy currently

utilized in some reserves for A. huegeliana control – would reduce population density but

not dramatically affect spread rates due to the fact that removal does not affect seedling

recruitment.

Methods We focus on concerns about invasion by the native species A. huegeliana, a fire-sensitive

tree species that has in the last several decades been invading in sandplain heath

(kwongan) habitat where previously it was recorded as rare or absent (Bamford, 1995;

Main, 1993). There is increasing concern that invasion by A. huegeliana is causing a

decrease in kwongan biodiversity through canopy closure, micro-environmental change,

and competition. Consequently management organizations such as the Department of

Environment and Conservation (DEC) have established site-specific adaptive

management plans incorporating the control of A.hugeliana spread for the preservation of

alpha (within-site) species diversity (Beecham, et al., 2009). However, there is currently

limited understanding of how to achieve that control with minimal interference in the

native system. We developed an individual-based model of A. huegeliana populations to

examine the efficacy of a number of single and combined management options with a

focus on fire as the predominant method of control. Our goal was to predict how differing

fire regimes, and the pairing of fire with mechanical removal, affect A.huegeliana spread

in kwongan.

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The native invader

Allocasuarina huegeliana (rock sheoak) is a dioecious tree species native to Western

Australia. Though it creates a relatively open canopy, its pine-like needles shed heavily,

resulting in a thick litter layer in the understory with little light penetration to the ground

surface. The seed is morphologically adapted to wind dispersal, thought to be its primary

mechanism of dispersal. As a reseeder species, A. huegeliana germinates in large

numbers after fire (Yates, Hopper, Brown et al 2003). However, post-fire seedling

mortality can be high under the post-fire conditions, which include harsh micro-climatic

conditions and preferential grazing by native herbivores (Maher, et al., 2010).

Kwongan study system

Kwongan is a highly diverse shrub-dominated ecosystem found predominantly in the

wheatbelt region of Western Australia (Pate & Beard, 1984) that resembles the fynbos of

South Africa and the chaparral of the southwestern United States. It is composed mainly

of woody cover less than two meters tall, a feature that can be attributed to the low

moisture and nutrient levels of the sandy soils commonly associated with the kwongan

(Pate & Beard, 1984). Vegetation in the kwongan is adapted to frequent fires that can

occur from early spring (September) through late Autumn (May), with many life history

characteristics dependent on fire for optimal occurrence (Keith et al., 2007). Fire also

maintains high species diversity among canopy layers, opening large portions of the

canopy post-fire and facilitating recruitment and growth in the understory (Keith, et al.,

2002).

We parameterized the model using data on A. huegeliana invasion in Tutanning Nature

Reserve, a 2,140 ha reserve located approximately 150 km southeast of Perth, Western

Australia. The site presents an ideal opportunity to look at the impacts of disturbance

regime shifts in an otherwise relatively intact system. Though surrounded by agriculture,

the reserve itself is under protection and management by DEC, experiences low human

traffic, and contains few exotic invasive species. Fragmentation and land use change have

likely caused the fire frequency in the region to decline (Prober & Smith, 2009).

Prescribed fires [fires that are deliberately lit and carefully controlled by DEC] occur

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infrequently. Though the parameter values used in this study are mostly based on

research conducted at this particular site, we expect the results of this study to be

applicable throughout the sandplain heath ecosystem.

Model structure

The A. huegeliana population model was coded in R (R Development Core Team, 2009)

and is an individual-based matrix model (See Table 1 for complete list of parameters). A

single cell has three possible states: absence of A. huegeliana, presence of A. huegeliana

seedling, or presence of A. huegeliana adult individual. Each cell is a square with length

2.25 meters. Parameter values were based on field observations. Studies of A. huegeliana

have been conducted in heath patches at Tutanning Nature Reserve and the empirical data

collected was used for parameterization; for a more detailed description of the

determination of each parameter, please see Shackelford et al. (2011) [Appendix A].

Timesteps are annual and include seed production, establishment, aging, and death

(Figure 1). A. huegeliana is dioecious, and we designated 40% of the population as seed-

producing females. Once of reproductive age, female trees produce a uniform number of

seeds each year, st, all assumed to germinate immediately. Little data exists on

Allocasuarina seed production, so we calibrated st based on field collected density data

(Maher, 2007).

71

Figure 1: Life stages of Allocasuarina huegeliana including proportions of individuals in each stage moving to the next. Female adults do not begin producing seed until they are a minimum of nine years old. The ~ proportions are those that change annually dependent upon the stochastic seasonal suitability variable (see main text).

Newly produced seeds are distributed throughout the landscape with a dispersal distance

drawn randomly from a Cauchy distribution with location x0=0 and scale γ=1.25 to

simulate a seed rain in which 98% of the seed falls within 20 cells [45 meters] of the

parent tree (Standish et al., 2007). The direction of dispersal is randomly drawn from a

uniform distribution from 0 to 2π. Seedlings are more vulnerable to mortality than fully

established adults. Therefore, a high rate of individual mortality is assumed for the first

two years, at which point any surviving seedling becomes an adult, though reproductive

maturity is not reached until later in the lifecycle. As an adult, a mortality probability of

5% per year is assumed, whether reproductive or not and irrespective of environmental

conditions.

All species experience ‘good’ and ‘bad’ years in relation to the environmental conditions

that determine the survival and growth of their populations. To simulate this stochasticity,

our model randomly assigns an annual seasonal suitability variable, yt. This variable

ranges over a uniform distribution from 0 to 1, with 0 representing the extreme of bad

72

years and 1 the extreme of good years. The values of three parameters vary from year to

year dependent upon yt: seedling mortality, seed production, and age at which the tree

first reproduces (See Table 1). The values of the first two parameters are calculated from

yt based on zero-truncated normal distributions. The parameters are set at their means in

years when yt = 0.5. If seasonal suitability is lower than 0.5 (a ‘bad year’), seedling

mortality will be higher than average and seed production lower, while if seasonal

suitability is higher than 0.5 (a ‘good year’), seedling mortality will be lower than

average and seed production higher. The third varying parameter R [reproductive age] is

nominally set at nine years (Yates et al., 2003), but to simulate the effect of seasonal

suitability on the initiation of seed production, a female tree only becomes reproductive

in the first year in which it is nine years or older and yt ≥ 0.5.

Table 1: Parameters used in the model, their values and literature sources

Parameter Definition Notes Value Source

F Female probability Probability that new seed will

be female 0.4

(Maher 2007, Shackelford et al, unpublished data)

R Minimum

reproductive age Reproductive maturity only

occurs in years where yt > 0.5 9 (Yates, et al., 2003)

X0 Cauchy parameter:

location 0

(Maher, 2007; Standish, et al., 2007)

Γ Cauchy parameter: scale

1.25 (Maher, 2007; Standish, et

al., 2007)

D Adult mortality 0.05 Stochastic Parameters

yt Seasonal suitability

Found at start of each time step; truncated normal distribution

µ=0.5, σ=0.1

dt Seedling mortality Truncated normal distribution:

dt = q(1- yt, µ, σ)* µ=0.82, σ=0.06

(Maher, 2007)

dft Seedling mortality:

post-fire Truncated normal distribution:

dft = q(1- yt, µ, σ)* µ=0.97, σ=0.01

(Maher, 2007; Yates, et al., 2003)

st Viable seed

production per tree Normal distribution: st = q(1- yt, µ, σ)*

µ=150, σ=30

Calibration to (Maher 2007)

Management Parameters

Df Adult mortality: fire

1 C.J. Yates, personal

communication

Dr Adult mortality: managed removal

0.9

*q(1- yt, µ, σ) is the quantile function, where the point found is that at which (1- yt) percent of the normal probability distribution with mean µ and standard deviation σ lies at less than or equal to that point

73

Simulation of control measures

We examined two methods of control based on strategies currently used in A. huegeliana

control: fire alone and fire in combination with the mechanical removal of adult trees.

Because of the inevitable presence of fire in the system – both wildfires and management

fires for fuel load and heath regeneration purposes, we did not look at managed removal

alone. Simulated fire is homogeneous across the patch because we were simulating a

high-temperature intense management fire aimed at maximum A. huegeliana mortality

(C.J. Yates, DEC, personal communication). Additionally, fire stimulates potentially

massive seed bank germination in reseeder species such as A. huegeliana, which is

simulated in the model by increasing seed production in years of fire occurrence by a

factor of ten. Once the simulated patch is burned, it is considered bare of vegetation. In

accordance with field findings (Maher, 2007; Yates, et al., 2003), the probability of

individual seedling mortality is increased for any germinants in the first three years

immediately post-fire (See Table 1).

For simulation of managed removal of A. huegeliana adults, trees that are ‘cut down’

experience mortality and are removed from the simulation without the increased seed rain

or harsher seedling environment. We assume some human error, so adult trees have a

90% chance of removal.

Virtual Experiments

The parameterized model was used to conduct a series of virtual experiments. Kwongan

patches are generally between 1 and 50 ha. For these simulations, the model was scaled

to represent an area of 20.25 ha. There are generally existing stands of A. huegeliana

adjacent to kwongan patches providing a continuous source of seed. These stands tend to

occur in areas such as the base of granite outcrops that historically experienced less

frequent fire than the kwongan due to higher moisture and lower dry fuel load (Clarke,

2002; Morris, 2000). To simulate this condition in our model, the bottom 10% of the

landscape was designated as fire refugium that did not burn during the model runs, thus

creating a constant seed source of A. huegeliana into kwongan patches. The remaining

74

upper 90% of the site represented the fire-prone kwongan patch. This patch was initially

empty of A. huegeliana and was subjected to a range of management strategies

throughout the simulation. Initialization consisted of the random placement of 100 A.

huegeliana individuals in the fire-refugium. Because the model is stochastic, 50 fire

cycles were simulated for each scenario.

We considered several different management regimes: regular fire occurrence, random

fire occurrence, and regular fire occurrence in conjunction with managed removal. In the

regular fire occurrence, we considered return intervals of between 20 and 80 years, in

increments of ten years. For the random pattern, fire occurred each year with a certain

probability. We considered a range of probabilities corresponding to the same 20-80 year

range of return intervals considered for the regular pattern (i.e. 0.05 ≤ p ≤ 0.0125).

Four management options of mechanical removal were considered, consisting of

combinations of two different removal intervals and two different removal strategies. The

first removal interval considered was based on A. huegeliana reproductive cycles:

managed removal of adults occurred every 9 years. We also considered a longer removal

interval of only once every 27 years, which would involve correspondingly lower effort

and expense. We tested two removal strategies: removing all trees over the whole heath

patch and removing only satellite populations. Many studies have shown that control of

satellite populations – or small, incipient populations away from the original point of

invasion – is a more effective tool against spreading invasion than controlling the

original source (e.g. Taylor & Hastings, 2004). Though we are assessing control on a

relatively small scale (< 100 ha), we were interested to see if removing dense clumps of

A. huegeliana in a heath patch (away from the invasive edge along the seed source)

would decrease overall density through the reduction of concentrated, reproductive

individuals. The strategy would be lower cost and more easily implemented than whole

site removal. We defined satellite populations as any approximately 100 m2 (or larger)

area with greater than or equal to 80% coverage by A. huegeliana. We then simulated the

removal of all A. huegeliana individuals within the area covered by the satellite

population.

75

The fires paired with mechanical removal were simulated over all fire return intervals in

the regular occurrence pattern. Trees in the adjacent stand (the seed source) never

underwent mechanical removal as it is considered natural habitat for the species not

appropriate for control measures.

Analysis of results

The purpose of this study is to advise which management choices will lead to the most

efficient and effective control of the population and its impacts. In order to do so, we had

to clearly define the relationship between the invasion and its impact. We used two

different estimations. Primarily, we focused on the behavior of the invading population

density and its response to management strategies. This can be interpreted as a linear

measure of impact: as density increases, the impact is assumed to increase accordingly.

Additionally, we wanted to have an estimate of impact that was more directly ecological

in its interpretation. We therefore used a very general estimate of impact to species

richness through the species-area relationship, resulting in a logarithmic relationship

between invader density and impact (Figure 2).

Invader Density

Est

imat

ed Im

pact

Invader Density Figure 2: Two estimated relationships of invasion density with its impact. The figure on the left shows a linear relationship: as density increases, impact increases at the same rate. The figure on the right shows a logarithmic relationship of density with impact: as density increases, there is initially little increase in invader impact until a point at which there is a rapid increase in impact.

Population response

Our focus was on density per ha, temporal and spatial variation in density, and varying

rates of increase in populations of A. huegeliana. Primarily, we were interested in the

76

population densities based on time since last fire. We recorded rates of increase as linear

regression estimates of the tree density/ha from the time since the last fire to the timestep

of interest. In order to consider spatial variability, the portion of the site undergoing

simulated management was divided in its entirety into 100, 40 m × 40 m subplots. For

each scenario, and at each time step, we recorded the mean density within each subplot

and the variation across subplots to calculate the dispersion index σ2/µ (Cox & Lewis,

1966).

Estimated species richness impacts

Species richness loss is an accessible and common way of measuring impact to a system.

There are no specific rules for how an invasion will alter species richness, and no direct

studies that we know of have been performed on A. huegeliana or a taxonomically related

species to estimate its impact. Though controversial (e.g. He & Hubbell, 2011), the

species area-relationship is a commonly used estimate of species richness impact, and

thus we chose to use it as a preliminary estimate of potential impact to biodiversity. We

consider its appropriateness as a measure of ecological impact in more detail in the

discussion.

We used data on species richness recorded by Brown and Hopkins (1983) in heath

patches of different sizes to model species richness as a function of area according to the

species-area relationship: S=cAz where S is species richness, A is area, c is a constant, and

z is the rate at which species accumulate with increasing area (Connor & McCoy, 1979).

We found the predicted species richness of one hectare to be approximately 99, with c ≈

27.24 and z ≈ 0.14. As other species tend not to co-occur in the area occupied by A.

huegeliana individuals, we assumed each A. huegeliana individual reduced the area

available for other species by the area of its occupied cell (2.25m × 2.25m). We then

estimated impact as the reduction in species due to the maximum area occupied by A.

huegeliana under a particular management scenario based on our fitted species-area

relationship.

77

Sensitivity analysis

We conducted sensitivity analyses on parameters where their chosen value was uncertain.

For all sensitivity analyses, we simulated a 30 and 60 year fire interval over 2000 time

steps, and used average and maximum density as the output variable for analysis. We

tested post-fire mortality (Df), the Cauchy dispersal scale parameter (γ), the kernel

distribution function, female probability (F), and viable seed production (st). Dispersal

scale, female probability, and viable seed production were all tested at +/-50% of the

model values, while post-fire mortality was tested in 10% decreasing increments. For the

dispersal kernel distribution function, we assessed the sensitivity of the model to using

kernels with lower long distance dispersal event occurrences: the Weibull distribution

and lognormal functions. Parameters for these dispersal kernels were set such that the

98% quantile was the same as for the original Cauchy parameter values. Additionally, we

examined fire occurrence in the seed source by subjecting it to fire over a range of

intervals between 60 and 240 years in 60 year increments.

Results Model output

Model outputs from example runs with a sixty year fire return interval are given in

Figure 3. Note the decrease in density between fire with no removal (a) and fire with

managed removal over the whole patch (c: every nine years; and d: every 27 years).

Small decreases can be seen in the management option of removing satellite populations

(e: every nine years; and f: every 27 years).

78

Figure 3: Example output at 119 timesteps after initiation for a) regular 60 year fire return interval; b) random 60 year fire return interval (here, two years since last fire); c) regular 60 year fire return interval with mechanical removal over the whole patch every nine years; d) regular 60 year fire return interval with mechanical removal over the whole patch every 27 years; e) regular 60 year fire return interval with mechanical removal of satellite populations every nine years; and f) regular 60 year fire return interval with mechanical removal of satellite populations every 27 years. The area depicted, totaling 20.25 ha, is both the simulated fire refugium (lower 10% of area; below the black line) and heath patch (upper 90% of area), with green space being those cells unoccupied by A. huegeliana. Each white cell represents an A. huegeliana individual.

Managed fire: regular and stochastic regimes

We found that under all fire return intervals, the population experienced mild exponential

growth – the rate of increase gradually sped up as the time since last fire lengthened. This

pattern did not change even when approaching eighty years since the last fire, implying

that no population asymptote had yet been reached. The return interval of the fire made

only a small difference in relative growth rates. For example, at 40 years since the last

fire, average growth rate was found to vary only by approximately 5% between fire

return interval of 40, 50, 60, 70, and 80 years. The longer the time between fires,

however, the higher the maximum densities reached in the heath patch (Figure 4). Based

on these maximums, the estimated impact to species richness consistently increased with

the length of the fire return interval: at the shortest interval, estimated species loss

79

reached only a maximum of 1 species/ha while at the longest interval it reached up to six

species/ha (Table 2). 0

100

200

300

400

Ave

rage

Den

sity

(tre

es/h

a)

20 30 40 50 60 70 80

020

060

010

00

Time Since Last Fire (yrs)

Max

imum

Den

sity

(tre

es/h

a)

Figure 4: The average density in trees/ha over all of the 50 fire cycles (top) and the maximum density reached within the 50 fire cycles (bottom) for: regular fire return intervals (Regular); random fire return intervals (Random); regular fire return intervals with mechanical removal over the whole patch every nine years (Whole site 9 yrs); regular fire return intervals with mechanical removal over the whole patch every 27 years (Whole site 27 yrs); regular fire return intervals with mechanical removal of satellite populations every nine years (Satellite 9 yrs); and regular fire return intervals with mechanical removal of satellite populations every 27 years (Satellite 27 yrs). Note that the two y-axes are different ranges due to the maximum densities being higher than the average densities.

When the models were run with random burns, the density and rates of increase based on

time since last fire did not differ from those under the regular regime. However, when

long spans of time occurred without fire, the patch continued experiencing increasing

rates of invasion and thus the highest density levels were reached and maintained under

random regimes (Figure 5). The random regime runs consistently reached 1,000 trees/ha

80

under all but the shortest return interval. At such high densities, the richness impact is

estimated to be around seven species lost per patch.

020

060

010

00

0 100 200 300 400 500

020

06

0010

00

Figure 5: Trees/ha in the last 500 years of each fire return interval simulated over 50 cycles of each return interval for the regular regime (top) and the random regime (bottom).

Managed fire and mechanical removal

The additional benefits derived from mechanical removal were dependent on both fire

regime and removal option. At shorter fire return intervals, when fires were occurring at

intervals less than every thirty to forty years, mechanical removal at any level provided

only small benefits. At longer fire intervals, however, the rates of population increase

were lowered dramatically by mechanical removal. For instance, compared with an

eighty year fire return interval with no mechanical removal, the rate of increase slowed

by approximately 85% when trees were removed over the whole patch every nine years

and approximately 20% when satellite populations were removed every 27 years.

Average and maximum densities were reduced by all mechanical removal treatments.

However, even at the highest removal of over the whole patch every nine years, and the

longest fire return interval of once every 80 years the maximum density reached was

reduced by only 31%. That reduction was less under other return intervals and other

mechanical removal options. The two ‘moderate effort’ removal strategies (removal over

the whole patch every 27 years and removal of satellite populations every nine years)

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resulted in similar population responses, with satellite population removal every nine

years yielding slightly higher patch averages over the 50 simulated cycles but lower

maximum densities (Figure 4). Additionally, dispersion was often higher under all

removal options due to the higher density in simulations without removal leading to

relatively more uniform coverage by the invading population.

The potential benefits of removal at longer fire return interval were emphasized in the

estimates of species richness loss. Except at the lowest level of removal effort – satellite

population removal every 27 years – maximum patch species loss was estimated to be 30-

50% lower with mechanical removal than without (Table 2). When removing trees over

the whole patch every nine years, no more than two species/ha were estimated to be lost

under any fire return interval at maximum tree densities, a 67% reduction from the

maximum species loss estimated for regular fire regimes without mechanical removal.

Regular Random Whole site

9 yrs Whole site

27 yrs Satellite

9 yrs Satellite 27 yrs

20 yrs 1 3 1 1 1 1 30 yrs 2 6 1 1 1 1 40 yrs 3 6 1 2 2 2 50 yrs 3 7 1 2 3 3 60 yrs 4 7 1 3 3 3 70 yrs 5 7 2 4 3 4 80 yrs 6 7 2 4 3 5

Table 2: Maximum estimated number of species lost due to A. huegeliana density under fire return intervals of 20-80 years for: regular fire return intervals (Regular); random fire return intervals (Random); regular fire return intervals with mechanical removal over the whole patch every nine years (Whole site 9 yrs); regular fire return intervals with mechanical removal over the whole patch every 27 years (Whole site 27 yrs); regular fire return intervals with mechanical removal of satellite populations every nine years (Satellite 9 yrs); and regular fire return intervals with mechanical removal of satellite populations every 27 years (Satellite 27 yrs).

Sensitivity analysis

Varying post-fire mortality had a dramatic impact on the population densities (Table 3).

At a 30 year fire return interval, average density quadrupled when mortality was reduced

by only 10% from 100% to 90%. At 70% mortality, average density was five times

higher than at 100% and maximum density was more than double. At a 60 year fire return

interval, the average density more than doubled between 100% mortality and 70%

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mortality, while the maximum density was held fairly constant due to the already high

maximum density of the 60 year return interval with 100% mortality.

30 year fire return interval 60 year fire return interval Cauchy Scale Parameter (γ)

Scale Avg Density Max Density Avg Density Max Density -50%: 0.625 69 210 233 727

0%: 1.25 124 442 362 887 +50%: 1.875 167 519 437 951

Dispersal Kernel Kernel Avg Density Max Density Avg Density Max Density Weibull 40 117 116 410 Cauchy 122 437 362 890

LogNormal 30 90 82 261

Female Proportion (F)

Proportion Avg Density Max Density Avg Density Max Density -50%: 0.2 95 271 275 808 0%: 0.4 120 381 362 899

+50%: 0.6 144 509 402 908

Seed production (st)

Production Rate Avg Density Max Density Avg Density Max Density -50%: 75 68 235 217 699 0%: 150 123 386 367 888

+50%: 225 173 535 438 934

Post-fire Mortality (dft)

Mortality Rate Avg Density Max Density Avg Density Max Density 1 123 426 361 894

-10%: 0.9 483 865 695 987 -20%: 0.8 582 938 728 973 -30%: 0.7 625 908 756 982

Fire in Refugium Return interval Avg Density Max Density Avg Density Max Density

60 4 251 2 99 120 49 321 17 416 180 74 381 73 553 240 86 378 87 507

Table 3: Results of the sensitivity analysis for each varied parameter for the 30 and 60 year fire regimes. Results are presented as the average density over the 2,000 year runs and the maximum density reached in the patch.

When the patch was subjected to a 30 year fire return interval, removing the fire refugium

resulted in population extinction if fires in the refugium were more frequent than once

every 100 years. If fires in the refugium were less frequent than once every 100 years, the

population was able to recover from fire through its own seed production; though average

densities were reduced by up to half, maximum densities were unchanged. Under the 60

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year fire return interval, removing the seed source by burning the refugium resulted in

similar average densities as under the 30 year fire return interval but higher maximum

densities.

The functional form of the dispersal kernel was much more important than the value of

the Cauchy function scale parameter, with the Cauchy kernel resulting in three to four

times the average density and two to four times the maximum density when compared

with results from the Weibull and lognormal kernels. Finally, varying the proportion of

the population designated female had only a small affect on average and maximum

densities.

Discussion Invasive species control is often required to maintain biodiversity in ecosystems.

Managers are faced with choosing among multiple options for achieving optimal control,

and simulation modeling can help inform the decision of where and when to apply

management. Using our preliminary estimate of impact to biodiversity based on fitted

species area curve and simulated A. huegeliana density, we found that A. huegeliana

consistently began causing species loss after approximately 30 years without fire. At fire

return intervals of 70-80 years between fires, incorporation of mechanical removal

resulted in significant decreases in average A. huegeliana density over the patch.

Interestingly, maximum density under the most intensive removal effort – whole patch

every nine years – was only decreased by 31% while the corresponding decrease in

species impact was estimated at ~67%. This highlights the differences in interpretation of

management efficacy based on the estimated relationship between the invasion and its

impact. If basing measures of efficacy on a linear relationship determined by maximum

densities, a 30% decrease in estimated resulting impacts might not be enough to justify

mechanical removal at any level. However, a 67% decrease in impact due to a defined

logarithmic relationship might reinforce the usefulness of the additional management

measure of mechanical removal.

Current fire return intervals in heath patches are often 70 years or more and thus

mechanical removal in areas where A. huegeliana invasion is a concern could potentially

84

be worth the expense. As found in other studies (e.g. Taylor & Hastings, 2004), there

were clear benefits of removing trees over the whole patch rather than focusing on

satellite populations. In small heath patches, removal over the whole patch is relatively

straightforward. In larger patches, it becomes a question of resource availability versus

benefit. It is important to note that managed removal prior to fire would also potentially

be worth the expense and effort required if mortality rates approaching 100% cannot be

achieved during fire events, as the model was extremely sensitive to post-fire mortality

levels. If fire return intervals were increased to every 30–40 years and high fire mortality

rates achieved, mechanical removal at any level gives returns that are not a great

improvement on fire alone.

In our model, the regular fire regime resulted in constant fire intervals whereas the

random application of fire resulted in both short and long intervals without fire. Long

fire-free intervals result in higher reproductive populations and thus an increased seedling

appearance immediately post-fire. We hypothesized that this would lead to a more rapid

coverage in post-fire population spread, i.e. that rates of increase would differ between

return intervals and between the regular and random regimes. We did not find this to be

true. Though fire in the model first causes a dramatically increased fire-induced

germination, the seedlings have very low survival and therefore the effects of the

germination in repopulating the patch are overshadowed by the seed rain from the fire

refugium. This causes the post-fire population to effectively ‘start from scratch’, so the

rate of spread is not affected by previous long fire-free intervals. Thus, fire return interval

or having long periods without fire interspersed with short periods should not affect the

speed of spread and establishment of A. huegeliana following a fire. Therefore, it appears

that managers have flexibility in their timing of subsequent fires to control A. huegeliana

while still being able to predict its likely spread and establishment.

In applying a relatively large-scale disturbance such as fire over an entire heath patch, the

system-wide impacts of the management choice need to be considered. Studies have

shown in some heath systems that fire intervals longer than around 45 years can lead to

structural senescence and heath degradation (Gosper, et al., 2011). On the other hand,

85

excessively rapid fire return intervals can lead to the loss of other fire-sensitive species

important to the diversity of the heath system (e.g. Bradstock et al., 2006; McCarthy et

al., 2001). Through the use of simulation modeling, Keith and Bradstock (1994) found

that a fire cycle of short fire intervals intermixed with long fire intervals maintained the

highest level of diversity within modeled heath patches. Therefore, an intermediate fire

return interval that varies between 25 and 50 years would potentially maximize benefits

to the system. According to our model results, a similar fire regime would likely prove

effective at controlling the A. huegeliana population. One final consideration for

management is the type of fire used in A. huegeliana control. The simulated fire type

would be novel relative to historical fires: the goal would be a hot, uniform fire to

maximize A. huegeliana mortality as opposed to the patchy fires of varying intensity that

would have been the historical norm. The impacts of this type of fire to the system are not

currently understood. Adaptive management would be required to respond to any adverse

effects seen from the novel fire type, and mechanical removal options may allow for

lower-mortality fires as previously mentioned.

As with all models, our model is an oversimplification of the many variables shaping the

system and populations within it. In most instances, invasion is a complex process that

co-occurs and interacts with several other factors that together cause environmental

change. Kwongan in Western Australia is currently undergoing many environmental

changes including fire suppression, regional shifts towards an increasingly drier climate

(Bates, et al., 2008), and land use changes. A. huegeliana is a drought-tolerant species

(Ladd, 1989) that germinates reliable under a variety of conditions. These factors could

all be synergistically contributing both to the invasion process and species decline.

Though general management suggestions can be made from models such as ours, more

precise management information could be obtained from a higher level of detail within

the model that takes into consideration other environmental factors.

Additionally, we do not include data on the disturbance event itself such as fire intensity

or season because there is no current information on whether these are pivotal factors in

A. huegeliana population dynamics. In systems such as North American prairie, however,

86

specific invaders require specific conditions in order for fire to be an effective

management tool. For example, alien grasses can be better controlled by fires within the

early growing season of the invader (Simmons et al., 2007), while high fuel load is more

important for control of invasive native woody species (Wink & Wright, 1973). The

modeling approach used in this study is general in that it could be applied to the

management of invasive species in other systems, but at the same time, can be tailored as

required using details such as fire season and intensity to address specific management

problems.

We have shown that control of a native invasive species is potentially achievable through

disturbance-based management alone. However, this management tactic – the

reinstatement of historic disturbance regimes or the application of novel regimes – could

be effectively applied to non-native invasion in certain contexts. Fire is a common

example of altered disturbance, and as mentioned has been used to control alien-grass

invasion in North American prairie. In arid stream and river habitats, the interruption of

free-flow and natural flood regime has been a driver behind invasion by three Tamarix

species (Stromberg et al., 2007), and the reinstatement of historic disturbance regimes in

this system might be utilized for its control. Disturbance-based management may also be

applied along with other control methods to manage novel systems, such as those with

multiple invaders. In Australia, the herbaceous invader Verbena tenuisecta increased

dramatically in response to the removal of the grassy invader Eragrostis curvula.

However, when removal of Eragrostis was combined with ungulate grazing and nutrient

addition, both novel disturbances to the system, the invasive herb was maintained at low

levels (Firn et al., 2010).

Finally, of utmost concern in our model and in the management of invasive species is the

clear definition of impact. In our model, one estimate of impact is area reduced by

invader cover. Recent research suggests that this approach may overestimate species

extinctions from habitat loss (He & Hubbell, 2011). However, we believe that it is a

relatively conservative estimate of invasive species impact given that it is a process that

does not involve direct habitat loss but rather area lost to a competitive species. In most

87

cases of plant invasion, direct impact is difficult to quantify (Davis, 2003) but involves

interactions between the invader and surrounding species that goes beyond mere spatial

coverage. The impacts can arise from competitive interactions, exploitative or

interference, and potential allelopathic behavior by the invader. In the particular case of

A. huegeliana in heath, there is data showing much higher species loss in heavily invaded

areas than would be predicted by the species-area relationship alone (Shackelford, et al.,

unpublished data). Though achieving an exact quantification of invasion impact is

unlikely, a clear definition with defined thresholds of effective or ineffective management

is key to successful planning and implementation of management strategies.

Invasive species are and will remain a high conservation concern in coming decades

(Vitousek, et al., 1997). Management of invasive species will become increasingly

sophisticated as we make full use of the tools available to us to make good decisions

(Polasky et al., 2011). An advantage of simulation modeling is its ability to test the utility

of different management scenarios over long time scales that is generally not possible

with other approaches. In our case we were able to predict the outcome of using fire for

the management of a native invader, mimicking both historic and novel fire regimes.

Having reasonable predictions means that managers have a basis of hypotheses to test

with field experimentation and observational research. The continued development of

simulation modeling in combination with other decision-making tools is likely to lead to

improved ecological understanding of invaded systems and ultimately, will advance our

ability to manage invasive species in the coming decades.

Acknowledgements

The data used in this paper was contributed by the Department of Environment and

Conservation Narrogin office. We would like to thank the Ecological Restoration and

Intervention Ecology Research Group, notably Dr. Rachel Standish and Dr. Kris Hulvey

for their comments and suggestions. We would also like to gratefully acknowledge the

helpful and insightful comments of two anonymous reviewers.

88

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CHAPTER 5

Conclusions and general discussion N. Shackelford

Ecological science is often directed towards understanding and contributing to the

solution of global issues, and the problem of invasive species is one currently receiving

high levels of attention. Acknowledgement of the enormity of the invasion problem has

contributed to the length and complexity of the debate that surrounds the perception of

native versus non-native species. In many ways, this debate is largely academic in nature:

in practice, species management is generally a case-by-case basis such as decisions made

surrounding the control of the case study species Allocasuarina huegeliana. The

knowledge needed to make case-by-case decisions is rooted in our theoretical

understanding of the issues and our subsequent empirical investigation. Both have been

explored in this thesis.

Supporting and shaping the middle-ground I have presented in this thesis a middle-ground perspective that references both origin and

impact as management determinants, with relative emphasis placed on each at different

stages of the invasion process. The goal is to utilize the strengths and merits of two major

viewpoints: the first that relying on origin as the driver of species management decisions

is the safest and soundest strategy, and the second that relying on impact to inform

management of established species is the most efficient and effective strategy.

Refinement of any theoretical or management perspective can be reached through

directed research at the known information gaps. Further investigation into the links

between behavior seen in native ranges and invasiveness could help managers and

scientists understand when nonnative species may pose a significant threat in new

systems based on their origin range (Goodwin et al., 1999; Hierro et al., 2005). Research

into topics such as traits showing the propensity to rapidly evolve (Parker et al., 2003),

the impacts of projected ongoing global change to species behavior and system dynamics

(Dukes & Mooney, 1999; Hellmann et al., 2008), and potential range expansion under

96

climatic shifts (Webber & Scott, 2011) can help redefine and support our understanding

of origin as an informative tool. Additionally, a generation of invasion biologists has

been attempting to create accessible methodologies for quantifying the impact of a

species considered for control (e.g. see Hejda et al., 2009; Pejchar & Mooney, 2009; Vilà

et al., 2011). There is a pressing need to investigate not only the negative or neutral

impacts, but the potential uses and benefits of non-native species as we face swift and

dramatic global change.

Case study findings and lessons The true test of a sound management perspective is whether it maintains its integrity and

usefulness under application. Given an established species of potential management

concern – Allocasuarina huegeliana – determining whether management action was

necessary to control the species was informed by whether it was found to negatively

impact the surrounding system. This study in its entirety performed one aspect of impact-

based assessment of A. huegeliana as a management issue by defining the perceived scale

of the problem, investigating its potential impacts and causes, and exploring management

options for its control.

As suggested in Chapter 2, however, origin was not abandoned as an informative tool in

this study. I defined potential management options with the understanding that A.

huegeliana is a native species and thus its invasion is due most likely to lost

environmental barriers previously constraining the population to adjacent habitats. If

anthropogenic forcing has changed those environmental factors, management of the

population is unlikely to be fully effective. Rather, reinstatement of the environmental

barrier – shortening fire return interval and intensity – was the primary goal of the

management options explored. However, if A. huegeliana is also becoming a driver of

further environmental change, both indirect management of fire and direct management

of the population might be required, and thus I also included mechanical removal as a

management strategy in our investigation.

I found that the spread of A. huegeliana into the heath was highly correlated with species

loss and is a management concern due to its likely impacts to species and composition.

97

Though there was little impact to biodiversity in the form of pure species richness per

patch, the recruitment seen in the heath patches was more likely to be common,

widespread species that do not contribute to biodiversity in the same manner as the rare

woody or perennial species that were often being lost. Further causal and mechanistic

understandings of the relationship between species loss and A. huegeliana invasion

should be developed where possible. Additionally, the possible state-change that could be

occurring in heath patches with high A. huegeliana density is a potentially enormous

problem that requires further investigation. Whether there exists a separate state, what

nature of positive feedbacks it might have, and whether there are quantifiable thresholds

of A. huegeliana density leading to a state-change are all important questions.

Thus, my management recommendation is to continue controlling A. huegeliana

population spread. Simulation modeling highlighted that fire could be used as an

effective management tool on its own. Because fire is a natural and necessary disturbance

in the system, the approach of using it to control A. huegeliana spread can potentially

address more within the system than just the consequences of the invasion. Whether fire

was the primary driver of the invasion, however, was not clear from my study results.

Further mechanistic investigation into the response of A. huegeliana to shifting

environmental factors such as the fire regime, changing climates, and nutrient shifts is

required for an understanding of the population drivers. Therefore, the fire under

consideration was a novel regime intended to elicit 100% mortality of A. huegeliana

individuals; with such goals in mind, managers would aim for a high intensity, uniform

fire over each patch. Larger implications to heath species and interactive effects with

patch conditions are poorly understood at this time.

The case study emphasized the need for and utility of multiple investigation methods. By

including both field studies and modeling techniques, I was able to at least initially

address all the primary aspects necessary for impact-based decisions regarding an

existing population of management concern. Though my findings can advise

management that A. huegeliana control is likely to help prevent further species loss and

maintain compositional integrity, many questions and caveats must be acknowledged

98

within the data. The inability to determine the mechanisms behind the causes and impacts

of A. huegeliana spread was a recurrent issue. Observational studies and monitoring are

some of the most common tools used in management. Data collected in this manner can

provide supportive evidence for hypotheses and can help illuminate the dynamics in the

system under study. The drawback is that observational methods are unable to clearly

show causality.

Though Tutanning has an Adaptive Management Plan written in 2009 (Beecham et al.,

2009), its implementation has been limited in its quest to experimentally understand the

dynamics of the reserve. I suggest adaptive management (Lee, 1999; Walters & Holling,

1990) in its intended form, which aims to actively plan experimental techniques into

management decisions and then monitor results for informing future decisions. Those

patches at Tutanning that have been heavily covered by A. huegeliana present good

opportunities to experimentally address questions regarding state-changes and thresholds

through selective tree removal, heath species plantings, or other experimental designs.

Less logistically feasible, but no less important, is the opportunity to experimentally test

the effects of very short fire-free intervals on A. huegeliana spread as well as on heath

species, the effects of high intensity, uniform fire regimes, and the effects of increasingly

long fire-free intervals. Monitoring efforts will remain pivotally important, particularly in

the face of continued management adaptation and anthropogenic pressures from the

surrounding landscape and shifting climate.

Conclusion Anthropogenic changes have resulted in global compositional shifts, be it through

invasion by non-native species or the rapid spread and abundance increases of native

species. In understanding and managing the problem, we first need a sound framework

and then the tools and methods to refine that framework and answer specific questions on

a case-by-case basis. Additional research needs to be done to confirm causal relationships

between species loss and A. huegeliana, as well as to determine causal factors behind the

species spread itself. Management decisions to address those causal links will likely be

more effective than addressing the population itself.

99

An essential part of the scientific process is the feedback between conceptual

understanding and empirical results (Pickett et al., 2007). One guides and is guided by

the other in a constant process to refine our conceptual understanding and thus direct our

empirical research. In ecology, this process is also linked with the application of our

ecological understanding in real management scenarios (Hobbs & Harris, 2001; Lawton,

1996). Management needs should feed into the conceptual and empirical process, and

results should be applicable and accessible to management. The case study presented here

begins to achieve many of these goals: it is rooted in management concerns and

involvement, guided by the framework of impact-based species control, and emphasizes

the utility of monitoring to inform management while also highlighting the need for more

direct quantification of the causes and consequences of species spread.

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APPENDIX A

Management implications of modeling invasion by Allocasuarina huegeliana in

kwongan heathland

Management implications of modeling invasion by Allocasuarina huegeliana in kwongan heathland

N. Shackelford a, M. Renton a,b,c, M. P. Perring a and R. J. Hobbs a

a University of Western Australia, School of Plant Biology, 35 Stirling Highway Crawley WA 6009, Australia

b Cooperative Research Centre for National Plant Biosecurity, Australia c Centre of Excellence for Climate Change, Forest and Woodland Health, The University of Western

Australia Email: shackn01@student.uwa.edu.au

Abstract: Biotic invasion is a recognized global issue that can lead to biodiversity and ecosystem function loss. It is caused by and interacts with a whole suite of other factors in environmental degradation: climate change, nutrient deposition, disturbance regime shifts, and others. The link between disturbance regime shifts and biotic invasion is particularly well developed in the literature. It is increasingly apparent that in systems where disturbance and invasion are interactively co-occurring, addressing one without addressing the other often leaves both problems not fully resolved. By manipulating the disturbance regime of interest, the disturbance-linked spread of an invasive species can often be controlled. However, the knowledge base necessary for the appropriate use of disturbance as a management tool is difficult to gain from historical, experimental, or observational studies. Therefore, we developed a simulation modeling approach to inform disturbance-based management of invasion.

As a case study, we focus on a native invasive tree in the kwongan heathland of Western Australia. We constructed an individual-based population model of its spread into the system from an adjacent seed source. The model was parameterized from empirically-derived data on important life history stages of the tree, including reproduction, dispersal, germination, aging, and death. Because of potential density-dependence in the population spread, we also included stochasticity through the use of a single ‘seasonal suitability’ parameter that determined seed production, seedling mortality, and initiation of reproductive maturity.

The management strategy of primary concern was fire over a range of intervals and over two interval types: regular fire and a probabilistic randomized regime. We confirmed parameter and model assumption details with local experts and found that outputs of the model were supported by available field data. With an understanding of the modeling technique limitations, we were able to make informative recommendations on the use of fire as a control technique for invasion in the heathland. These techniques could be generalized to assess fire in other systems worldwide, or further to assess the efficacy of any major control effort in population management.

Keywords: individual-based model, sheoak, disturbance, management, fire

Shackelford, et al. Modeling Invasion and its management implications

1. INTRODUCTION

Biotic invasion is widely recognized as a driver of global change through its direct and indirect effects on local biodiversity and ecosystem functioning. Invasion often occurs in conjunction with a list of other human-induced causes of global change such as climate change, habitat loss, nitrogen deposition, and disturbance regime shifts. There is growing recognition that these ecological drivers have strongly interactive relationships with biotic invasion (Didham et al., 2007), and that management must attempt to mitigate both the individual and interactive forces in a system. Thus, when managing biotic invasion, the root cause of the invasion must be understood and addressed to fully confront the issue.

The link between biotic invasion and disturbance has been particularly well established in theoretical, observational, and experimental studies (Hobbs & Huenneke, 1992). The relationship can be strongly interactive, and it is argued that in these cases, the invasion cannot be managed without managing the disturbance as well (Hobbs, 1991). This can be accomplished through utilizing disturbance itself as the management tool. However, this requires knowledge about a system on multiple scales, both spatial and temporal, as disturbance can often have impacts both in the long and short term, and over both large and small scales. Collecting data on multiple scales can often be impractical. Additionally, historical data can be inadequate in drawing strong conclusions about past disturbance regimes. It is often incomplete and relies on anecdotal evidence from sources ranging from untrained travelers to expert scientists. The lack of information can create serious barriers to the use of disturbance as a management strategy. Improperly informed decision-making can potentially have long-term, landscape-scale repercussions.

One method which can help managers overcome major information gaps is simulation modeling. Population modeling techniques are commonly utilized in invasive species management to assess the efficacy of direct control measures (Buckley et al., 2003; Taylor & Hastings, 2004). These models often span very large spatial and temporal scales and simulate manual and chemical control strategies to predict optimal strategies of application (Higgins & Richardson, 1996; Parker, 2000; Schreiber & Lloyd-Smith, 2009). These methods have rarely been used to take into account indirect control methods, but can be expanded to look at the efficacy of disturbance-based management over long time periods across entire systems.

2. PROJECT SUMMARY

In this study, we investigated population modeling techniques to assess fire as a disturbance-based management tool for the control of a native invasive in kwongan heathland, a fire-prone Australian system. We focused on Tutanning Nature Reserve, located approximately 35 kilometers from Pingelly, Western Australia. It is a highly diverse reserve with approximately 15 individual heath patches contained in a mosaic of woodland and exposed granite outcrop systems. In the past 30 years, large biodiversity losses have been recorded in eleven of the reserve’s kwongan patches (Shackelford, et al., unpublished data). Local land managers believe these losses result from invasion by the native tree Allocasuarina huegeliana. Though found in abundance in adjacent systems, A. huegeliana has previously been absent or rare in heath systems (Bamford, 1995; Main, 1993). It is a fire sensitive species, and managers believe its spread is due to an interaction with local fire regime shifts that have occurred since European colonization (personal communication, C. Yates, 2010) Fire intervals are currently at 50-70 years between fires, and land managers lack full understanding of resulting implications for the invasion process. Sound experimental or observational data is difficult to collect over such a large temporal scale. Therefore in coordination with the Department of Environment and Conservation (DEC), we designed an empirically-based population model to analyze the effects of a range of fire intervals. Our goal was to create a model strongly linked with the specific ecology of the system and determine whether it could be used to reach informative conclusions about disturbance-based management. Because the species is native, eradication in and around these patches is not desirable; rather, containment of its spread into the heath is the final goal.

3. MODEL STRUCTURE

3.1. Overview

We chose a spatially-explicit individual-based modeling approach. Models of this type allow flexibility in the choice of parameterization and inclusion of stochasticity. The flexibility in parameterization allows the model to be well-supported by available empirical knowledge of a system and the invading species. Though the benefits of the technique are usually overridden by the prohibitive computational power necessary for

Shackelford, et al. Modeling Invasion and its management implications

simulations, in a size-limited landscape such as kwongan heathland, we were able to keep computational requirements to a manageable minimum by considering a site approximately 18 ha in total invasible area.

The simulation represents a single heath patch using a grid of square cells. Each cell is approximately 5 m2, with cell size determined by the carrying capacity of 2,000 trees/ha found for a related Casuarinaceae species (Ladd, 1989). Cells have three possible states: absence of A. huegeliana, presence of A. huegeliana seedling, or presence of A. huegeliana adult individual.

3.2. Parameterization

Many heath patches are located adjacent to an A. huegeliana stand. We therefore include in the model approximately 2 ha of constant seed source located at the bottom end of the simulated site that contains 100 individuals at the initiation of each run. From that persistent seed source the population spreads into the simulated heath patch. Model parameterization is based on existing knowledge of the life history of A. huegeliana in heathland. Time steps are annual and include five stages: reproduction by seed-producing adult females, dispersal of seed, germination, aging of existing individuals, and seedling and adult mortality. The model is coded in the R programming language and is available upon request to the authors. See Table 1 for a complete list of parameter values (adapted from Shackelford, et al., unpublished data).

Table 1: Parameters used in the model and their values

Parameter Definition Value

F Female probability 0.4

R Minimum reproductive age 9

X0 Cauchy parameter: location 0

Γ Cauchy parameter: scale 1.25

D Adult mortality 0.05

Stochastic Parameters

yt Seasonal suitability µ=0.5, σ=0.1

dt Seedling mortality µ=0.82, σ=0.06

dft Seedling mortality: post-fire µ=0.97, σ=0.01

st Viable seed production per tree µ=150, σ=30

Management Parameters

Df Adult mortality: fire 1

Dr Adult mortality: managed removal 0.9

Reproduction

Allocasuarina huegeliana is a dioecious species. However, little data exists on exact population proportions between males and females. Maher (2007) performed surveys on 11 of the Tutanning heath patches and recorded 20% of the total population as fruiting females. Since it was impossible to determine the gender of plants not yet of reproductive maturity in the field, we assumed only 50% of the population had reached a stage of maturity enabling accurate identification. Based on the determination that 20% of reproductive adults were female, and assuming the same proportion for non-reproductive juveniles, 40% of the total population is estimated to be seed-producing female. This variable is parameterized in the model as F = 0.4, the probability that newly produced seed is female. The nominal age at which females begin producing seed has been found to be approximately nine years. This parameter, R, is subject to some stochasticity, as detailed further below in Section 3.3.

For female trees of reproductive maturity, effective seed production is defined within the model as the number of seeds that are produced, are viable, and find suitable microenvironments for germination. For computational simplicity, we estimate this process as a single parameter, viable seed production st. This

Shackelford, et al. Modeling Invasion and its management implications

parameter was difficult to base in empirical study. Therefore we calibrated the parameter by running the simulation with a range of values and adjusting the value so that model results correlated with existing density data collected in the field. The parameter changes stochastically between years. However, all reproductive trees have equal st within a timestep.

Dispersal

Once individual trees have produced seeds, they are dispersed across the landscape according to a Cauchy distribution:

f (x; x0, γ) = γ / π* (x - x0)2 + γ2 (1)

with location x0 = 0 and scale γ = 1.25. This simulates a seed rain in which 98% of the seed falls within 20 cells, or 45 meters, of the parent tree, which matches empirically based estimates (Standish et al., 2007). The Cauchy distribution is a leptokurtic distribution that allows long distance dispersal events. Dispersal kernels accounting for long distance events have been found to represent seed dispersal relatively well for wind-dispersed tree species such as A. huegeliana in many instances (Howe & Smallwood, 1982). Once dispersal distance for each individual seed is determined, the direction of dispersal is randomly chosen from a uniform distribution ranging from 0 to 2π. In the case of a negative dispersal distance, dispersal occurred in the opposite direction of that produced by the uniform distribution selection. Because of the nature of kwongan patch size limitation, we did not simulate a ‘wrap-around’ function for seeds dispersing beyond the site; if seeds are dispersed off the edges of the simulation, they are considered to be lost.

Germination

Though cell size accommodates more than a single seedling, field observations have been that intra-specific competition leads to a single individual per area depicted by each cell. Therefore, if the cell in which a seed is distributed is currently occupied, seed mortality is assumed. Otherwise, once distributed across the landscape, all seeds are assumed to germinate. Because mortality occurs after germination in the chronology of a single timestep, germinated seeds are designated to have an age of 1. This ensures that seedling mortality, described in detail below, lasts only for two total timesteps of the individual’s lifespan, at which point the seedling is assumed to have reached a size that provides resilience to environmental threats such as grazing and drought.

Aging

All existing individuals except newly germinated seeds increase in age by one year per timestep.

Mortality

There are two life stages – seedling and adult – and three whole site conditions – unburned, burned, or burned within the last three years. If the site is burned in a timestep, 100% mortality is assumed for seedlings and adults in the burned heath within that timestep (personal communication, C. Yates, 2010). Though fires occur in generally patchy patterns that would not produce such uniform impacts, we are assuming a managed burn at the high temperatures necessary for maximum A. huegeliana mortality. Under all other conditions, adults are assumed to be capable of surviving environmental stresses and so are designated a set 5% annual mortality rate to account for natural senescence.

We altered seedling mortality rates dependent upon whether a site has been burned in the last three years or not. Studies on A. huegeliana seedling survival in heath patches were conducted by Maher (2007) in Tutanning Nature Reserve and very low seedling survival rates were found. Due to environmental stress including preferential grazing by native herbivores, an average seedling mortality rate of 82% was found in vegetated areas. Additionally, Yates et al. (2003) tracked mortality of A. huegeliana over 12 years. The study found no new seedlings over the 12 year span and found that only 13.7% of the original seedlings had survived; i.e. they experienced an approximately 86% mortality rate. We therefore set the average seedling mortality under unburned conditions at 82%. This parameter is stochastic and varies annually. If recently burned, we set a higher mortality rate, because recently burned heath sites are generally bare of shrubs and other potential ‘nursing’ cover that otherwise protects A. huegeliana seedlings. In the same study previously mentioned, seedling mortality found by Maher in bare patches was 97%. Accordingly, for the first three timesteps after a fire event, any seedlings present in the model experienced higher mortality averaging 97% but again subject to annual stochasticity. Under all conditions, if a seedling survived its first two years, it is assumed to become an ‘adult’ and is no longer subjected to higher mortality rates due to environmental stress.

Shackelford, et al. Modeling Invasion and its management implications

3.3. Stochasticity

All environments experience fluctuations in the suitability of climate and environmental conditions for the survival or performance of particular species. That stochasticity is potentially important in population spread and we therefore included three parameters that varied stochastically: seedling mortality, seed production, and age at which a female tree first reproduces. Annual values for seedling mortality and viable seed production and the probability of female trees starting to produce seeds all depend on seasonal factors such as rainfall, so are likely to be tightly correlated. Therefore, in the model, all three depend upon a single parameter that we termed the ‘seasonal suitability’ parameter, yt. Seasonal suitability ranges from 0 to 1 and is randomly chosen at the beginning of each timestep from a truncated normal distribution with mean µ = 0.5 and standard deviation σ = 0.1. Seedling mortality is calculated from a normal distribution function varying from 0 to 1, using yt as the input quantile. This is then truncated at 0 and 1. The parameters for this normal distribution are µ = 0.97 and σ = 0.01 for the three years immediately post-fire and µ = 0.82 and σ = 0.06 for all other years. Variance was set so that in a ‘worst’ year mortality was approximately 0.99. Viable seed production is similarly calculated using yt from a normal distribution with µ = 150 and σ = 30. For example, if yt = 0.5 for a given year, representing a median season, then seedling mortality and viable seed production for that year will both be at their mean value. If seasonal suitability is higher than 0.5 (a ‘good year’), seedling mortality will be less than average and seed production greater than its average. The final stochastic parameter, the age at which a female tree first reproduces, is determined by seasonal suitability only insofar as it is a limiting factor on seed production initiation. Once an individual female is older than the nominal reproductive age of 9 years, it will begin producing seed in the first timestep in which yt ≥ 0.5. Once seed production has been initiated, it continues every timestep until mortality.

3.4. Sensitivity Analysis

For good prediction of population behavior it is essential to accurately parameterize the model, but some parameters are likely to affect outcomes more than others. This can be addressed through parameter sensitivity analysis. Though we had empirical data supporting most of our parameters, there is always concern as to the level of impact a single, uncertain parameter might have on the outcome of the simulation. For all sensitivity analyses, we tested two scenarios of a regular 30 year fire interval over 2,000 timesteps and a regular 65 year fire interval over 2,000 timesteps. We first assessed the impact of reduced post-fire mortality, decreasing the probability of mortality for individuals in a fire from 100% to 50% in 10% increments. We assessed both the parameter values of the Cauchy kernel and the dispersal kernel itself. Parameter values for the Cauchy kernel were tested at +/-50% of the model values, altering the average distance seeds fall from the parent tree. However, the choice of kernel has been shown to dramatically affect patterns of spread and invasion (Kot et al., 1996). As a contrast to the heavily fat-tailed Cauchy kernel, we tested the Weibull distribution and the lognormal distribution, two leptokurtic kernels that are less weighted away from the mean. We parameterized them to have 98% of the seed fall within the same 45 m distance as used for the Cauchy distribution definition. Finally, we tested the percentage of reproductive females within the population and the calibrated parameter st, viable seed production per reproducing female tree. Similar to the dispersal parameters, we tested the proportion of reproductive females at +/-50% the model parameter values. Because seed production is a normal distribution that varies stochastically, we altered the average value +/-50%. Each parameter that was tested in the analysis was tested individually, and not in combination with other parameters.

3.5. Management Strategies

We investigated fire occurring in set, regular frequencies ranging from 10-80 years between fires in 5 year increments. Additionally, we investigated randomized fire occurrence, with fire frequency determined by annual probabilities corresponding to the same 10-80 frequencies as in the regular simulation; i.e. there was a 10% chance of fire for each individual timestep in the 10 year randomized regime, a 5% chance in the 20 year randomized regime, and so on.

4. RESULTS AND DISCUSSION

We wanted to assess the adequacy of the model in regards to its empirical soundness. Though most of the parameters were well-grounded in literature, the literature itself is fairly limited. We had local land managers check inputs, assumptions, and outputs and confirm that it seemed well within field evidence (C. Yates, K. Brooks, B. Beecham, personal communication, 2010). The sensitivity analysis showed that the two factors with the most influence over model results were the dispersal kernel and post-fire mortality rates. The dispersal kernel chosen – the Cauchy kernel – is one commonly used in long distance dispersal. Additionally,

Shackelford, et al. Modeling Invasion and its management implications

Figure 2: Model density output and real data. The black line represents average A. huegeliana densities based on time since last fire as predicted by the simulation model; the surrounding grey is the standard deviation; the red points are field densities at eleven separate sites in Tutanning Nature Reserve (Shackelford, et al., unpublished data)

when studying the sensitivity outputs, the Cauchy kernel resulted in population behavior closest to that seen in the field (Figure 1). Post-fire mortality is a parameter potentially under the control of managers, and thus the model’s sensitivity to it is not of great concern. The inherent factor untested in our model is the influence of the many environmental variables omitted through our choices in ecological simplification.

Independent quantitative model validation was not possible due to our use of the available data to calibrate parameters. Even after calibration, the clear pattern of fire-dependent increase found in the output is not reflective of the more scattered density levels found in the field (Figure 2). However, the data does confirm the significant, positive relationship between time since last fire and density levels. Those sites that contribute most to weakening that relationship are of a substrate types that is thought to be inhospitable to A.

huegeliana. Though A. huegeliana density was found to have a significant relationship with several other environmental variables as well, its relationship with fire is the one of primary interest when using disturbance as a management tool. The positive relationship in the data supports the hypothesis that key management strategies can be determined from model results and our model explores the mechanisms behind that relationship, allowing further options to be investigated such as fire paired with managed removal.

Keith and Bradstock (1994) found that a fire regime of alternating short and long intervals would likely be ideal in maintaining the highest levels of diversity in the heathland. This type of study can be paired with our model output to move towards a better understanding of fire management that may address many issues in the system beyond only invasion. Fire as natural disturbance is prominent in many systems worldwide, for example the fire-prone South African chaparral and the North American prairie. This type of modeling can easily be adapted to these other systems in which there is a species or suite of species with fire-dependent population behavior.

Figure 1: Model output after 65 years without fire using Cauchy distribution (left), Weibull distribution (middle), and the logNormal distribution (right) for seed dispersal. The images are ‘aerial’ views of the simulated heath space, with green being uninvaded heath and white invaded. In field results, invasion is up to 1425 trees/ha after 70 years without fire, correlating most closely with the Cauchy distribution results.

Shackelford, et al. Modeling Invasion and its management implications

Empirically-based population modeling techniques of the kind used in this study can be expanded to explicitly look at any number of single or combined disturbance-based management strategies. There is enormous variety in management practices that are pivotal in the maintenance of specific species populations. For instance, in a further application of our model, we plan to combine fire with mechanical removal and assess the difference in control efficacy. Similarly, any control method of interest can be included and parameterized to predict management outcomes. Considerations in these applications would be the scale of the model and the nature of the species of concern. Individual-based models are most applicable in instances of relatively low-density species on relatively small scales. High density species like grasses and larger landscape level scales might be better suited for an alternative method of population modeling. Nevertheless, our study showed the applicability of individual-based population modeling in population management under strategic, disturbance-based control measures.

ACKNOWLEDGMENTS

We would like to thank the Department of Environment and Conservation, specifically Dr. Kristine Brooks[and[Dr. Brett Beecham for their advice and willingness to collaborate. In addition, we must acknowledge the support and guidance of the ERIE Research Group and its individual members.

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