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ADAPTIVE PLASICITY, EVOLUTION AND SCORPION VENOM

Thesis submitted by Alexander N. Gangur in partial fulfilment of the requirements for

the degree of Bachelor of Science with honours in the School of Marine and Tropical

Biology of James Cook University, Cairns.

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I wish to dedicate this thesis to James; I couldn’t have done it without you.

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Acknowledgments

To my many and varied supervisors – Tobin Northfield, Michael Liddell, Jamie

Seymour, Mic Smout, and David Wilson – I cannot thank you enough for your

infinite patience, invaluable guidance, and especially for the brutal criticism. And

thank you to Norelle Daly for helping to fund the project, and to whom I regretfully

owe a micropipette. I want to thank Sarah Kerr for helping to bring Frank to unlife;

Sandra Abell Davis for #52138 and all things fungi-related; and Alex Cheesman and

Will Edwards for suggesting the PCA analysis.

Sam Barnett – thanks for showing me the ropes, and thank you to QTHA for

providing them, and to everyone there who kindly let me scour their brains for

advice. I also wish to thank Leanne, Jenni, and Jon for bearing with my boundless

capacity for forgetfulness and being such great sports about it. Thanks to all my

volunteers – Chris, Dani, Dave, Eden, Martha (for the dodgy camera work), Nalisa,

Sky, and Tim – for getting your hands dirty in the name of scorpion science.

And a special thanks to Mum and John, for keeping me smiling.

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Copyright Acknowledgement

I, the undersigned, the author of this thesis, understand that James Cook University

will make it available for use within the University Library and, by microfilm or

other photographic means, allow access to users in other approved libraries. All users

consulting this thesis will have to sign the following statement: "In consulting this

thesis I agree not to copy or closely paraphrase it in whole or in part without the

written consent of the author; and to make proper written acknowledgment for any

assistance which I have obtained from it". Beyond this, I do not wish to place any

restriction on access to this thesis. Users of this thesis are advised that the policy for

preparation and acceptance of Honours theses does not guarantee that they are

entirely free of inappropriate analyses or conclusions. Users may direct enquiries

regarding particular theses to the relevant school head.

19th

Oct 2014

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(signature) (date)

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Declaration

I declare that this thesis is my own work and has not been submitted in any form for

another degree or diploma at any university or other institution of tertiary education.

Information derived from the published or unpublished work of others has been

acknowledged in the text and a list of references is given.

19th

Oct 2014

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(signature) (date)

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Abstract

Organisms embedded within food webs typically need to balance arms races between

their predators and prey. Generally, studies of arms races have focused on pairwise

interactions and the co-evolution of prey-capture and anti-predator traits. However,

interactions between three trophic levels may be more representative of natural

systems. Theoretical investigations of arms races in three trophic-level systems have

revealed novel and often-unintuitive insights that are not evident from pairwise

studies of eco-evolutionary dynamics. There has been growing interest in the likely

importance of arms races in venom evolution, and the aim of this thesis is to evaluate

venom evolution in response to tritrophic interactions. Due to the putative high cost

of venom production, the ‘venom optimisation hypothesis’ proposes that venomous

animals employ various strategies to use venom efficiently. Thus, an underlying

selection pressure for economical use of venom is believed to drive these arms races

with venomous predators and prey. The resulting escalation of venom toxicity

towards natural predators and prey and each trophic level’s evolved venom resistance

may give rise to the extensive variation observed in venom use and composition.

Indeed, emerging evidence has strongly supported the role of diet in shaping the

evolution of venom, but the selection pressures and importance of venom in

defensive contexts is less well understood. I perform two general investigations of

predator-prey interactions in order to better understand the role of arms races, co-

evolution, and offensive and defensive selection pressures in venom production.

First, to develop general hypotheses to evaluate in an experiment, I investigated

selection pressures on offensive and defensive venom production in a venomous

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animal using a three trophic-level Lotka-Volterra model of eco-evolutionary

dynamics. I then tested these hypotheses in a microcosm experiment with a rainforest

scorpion. I identified rapid responses in scorpion venom profiles over the course of

six weeks, induced by simulated predator interactions. I manipulated selection for

offensive and defensive venoms by inducing venom-use via stinging, against a model

insect prey and a taxidermied vertebrate predator, respectively. Higher predator

pressure was expected to stimulate defensive venom production, and indeed we

found significant changes in venom composition. In contrast, a change from

predation to scavenging for dead prey did not alter scorpion venom composition. I

discuss the potential for induced defence mediated by venom composition for

stabilizing food webs. In the second investigation, I used a Lotka-Volterra three

trophic-level eco-evolutionary model to evaluate the evolutionary response of a

venomous consumer to co-evolution with its prey in the presence of an apex

generalist predator. I modified the model used in my first investigation to allow

venomous consumers to develop venoms associated with both prey capture and

predator defence, which may functionally overlap. Predator introduction promoted

investment in either defensive or offensive venoms. The investment type depended

on the effectiveness of the offensive venom when used in defensive contexts, and the

relative cost associated with investing in multiple venoms. Furthermore, the

evolutionary response of prey species to apex-predator-induced reductions in

consumer densities promoted the evolution of a novel defensive venom against the

predator. These dynamics suggest that interactions with other species can

substantially alter the venom complexity. Finally, I discuss how my findings may

provide valuable insights into the role of defensive venoms and predatory selection

pressure, co-evolution, and arms races in venomous animals.

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Table of Contents

0 INTRODUCTION TO THE THESIS ........................................................ 1

1 SPECIES INERACTIONS AND VENOM EVOLUTION ...................... 4

Abstract ......................................................................................................... 5

1-1 Introduction .................................................................................................. 5

1-2 Ecological perspectives on venom – an overview of venom ecology ........ 7

The ‘venom optimisation’ hypothesis, a unifying theory of venoms.............8

The costs of chemical warfare .......................................................................9

‘Venom metering’, the behavioural optimisation of venom expenditure ...10

1-3 Economy, arms races, and variation in offensive and defensive venoms .

..................................................................................................................... 11

Offensive venoms and the ‘overkill’ controversy ........................................13

Defensive venoms – time to reconsider? .....................................................15

Demographic variation in offensive and defensive venoms ........................19

Constraints upon venom evolution ..............................................................21

1-4 Venom biochemistry and the optimisation hypothesis ........................... 23

1-5 Future directions ........................................................................................ 26

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2 INDUCED PLASTIC DEFENCE IN VENOM COMPOSITION ........ 28

Abstract ....................................................................................................... 29

2-1 Introduction ................................................................................................ 29

Arms races in venomous animals ................................................................29

Theory and evidence for offensive and defensive venoms ..........................30

Adaptive plasticity in venoms ......................................................................32

Statement of aims and hypotheses ...............................................................33

2-2 Theoretical modelling ................................................................................ 34

Model description ........................................................................................34

Model analysis and results ...........................................................................38

2-3 Experimental materials and methods ...................................................... 41

Study organism ............................................................................................41

Experimental treatments ..............................................................................41

Collection and housing ................................................................................44

Choice of milking method ...........................................................................45

Venom milking ............................................................................................47

Fast protein liquid chromatographs (FPLC) venom analysis .......................47

Statistical analysis ........................................................................................48

2-4 Experimental results .................................................................................. 49

2-5 Discussion ................................................................................................... 52

Defensive venom .........................................................................................52

Offensive venom ..........................................................................................54

Implications of plasticity .............................................................................57

Applications and future directions ...............................................................58

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3 TRITROPHIC INTERACTIONS REVEAL NEW INSIGHTS INTO

VENOM EVOLUTION .......................................................................................... 60

Abstract ........................................................................................................ 61

3-1 Introduction ................................................................................................ 61

Balancing consumer-prey and consumer-predator arms races.....................61

Arms races in venomous animals ................................................................62

Offensive and defensive venoms and statement of aims .............................63

3-2 Model description ...................................................................................... 64

3-3 Analysis and results ................................................................................... 69

3-4 Discussion ................................................................................................... 73

Co-evolution with prey species may facilitate anti-predator venoms ..........73

Restricted co-evolution may give rise to ‘overkill’ .....................................74

Conclusion and future directions .................................................................76

4 GENERAL DISCUSSION ........................................................................ 78

5 LITERATURE CITED ............................................................................. 81

6 APPENDIX I – additional material relevant to Chapter 2 .................... 90

7 APPENDIX II – additional material relevant to Chapter 3 .................. 95

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List of tables

Table 2-1 Description of parameters used in model describing change in

population densities for a prey-venomous consumer-predator system. .................... 36

Table 2-2 Description of functions used in model describing change in

population densities for a prey-venomous consumer-predator system. .................... 37

Table 2-3 MANOVA results, which demonstrated a significant overall difference

between the fraction loadings of predator and without-predator treatments............. 51

Table 2-4 ANOVA results, which demonstrated significantly different fraction

loadings between the predator treatments compared to the without-predator

treatments along both PC1 and PC2. ........................................................................ 51

Table 3-1 Description of parameters and functions used in model equations

describing change in population densities for a three trophic-level system involving a

prey, a venomous consumer, and a predator. ............................................................ 66

Table I-1 MANOVA results, which indicate there were no statistically

significent differences between fraction loadings of scorpions allocated to each

treatment prior to actually having been subjected to those treatments. .................... 93

Table I-2 MANOVA results, which indicate there were no statistically

significent differences between fraction loadings of treatments in the venom obtained

21 days after the cecession of experimental treatments. ........................................... 93

Table I-3 MANOVA results, which indicate there were no statistically

significent differences between fraction loadings of treatments in the venom obtained

21 days after the cecession of experimental treatments. ........................................... 93

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Table I-4 MANOVA results, which indicate there were no statistically

significent differences between fraction loadings of treatments in the venom obtained

21 days after the cecession of experimental treatments. ........................................... 94

List of figures and equations

Figure 1-1 Tree of venomous animals demonstrating the relationship between

animal lineages and the major ecological usage of venom, from Casewell et al.

(2013). ............................................................................................................ 18

Figure 2-1 4-panel figure of effects of offensive and defensive pressures on

equilibrium population densities and traits. .............................................................. 40

Figure 2-2 Comparison of reversed-phase venom profiles obtained via

electrostimulation and manual milking from the same individual. ........................... 46

Figure 2-3 Comparison of post-experiment mean venom profiles. ..................... 49

Figure 2-4 Sample values and priniciple component loadings for peaks 1-11

describing the venom profiles of the experimental scorpions. .................................. 50

Figure 3-1 4-panel figure of eco-evolutionary effects of an invading top predator

on densities and traits for a three-trophic-level food web where the prey species

either can or cannot co-evolve. ................................................................................. 71

Figure 3-2 8-panel figure of eco-evolutionary effects of an invading top predator

on densities and traits for a three-trophic-level food web for high and low M and g3,

where the prey species can always co-evolve. .......................................................... 72

Figure I-1 Comparison of venom profiles obtained prior to experimental

treatments. ............................................................................................................ 90

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Figure I-2 Comparison of venom profiles obtained 21 days after the conclusion of

the experiment, in the absence of treatment pressures. ............................................. 91

Figure I-3 11 fractions as determined by spline fitting, and elution volumes for

local minima. ............................................................................................................ 92

Figure II-1 Evolution of a defensive venom in the absence of co-evolution occurs

under high predatory pressure. .................................................................................. 95

Figure II-2 Effects of high and low M and g3 in the absence of co-evolution. ..... 96

Equations 2-1 Changes in population densities of the prey (Rt), venomous consumer

(Ct), and predator (Pt). ............................................................................................... 35

Equations 2-2 ....... Derivative equations showing changes in prey susceptibility (vR),

consumer prey-capture venom (v1), and consumer anti-predator venom (v2). .......... 37

Equations 3-1: Changes in population densities of the (Rt), venomous consumer

(Ct), and predator (Pt) in the expanded model. ......................................................... 65

Equations 3-2: Derivative equations showing changes prey susceptibility (vR),

consumer prey-capture venom (v1), and consumer anti-predator venom (v2) in the

expanded model. ....................................................................................................... 68

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General introduction to the thesis

While the role of diet in shaping the evolution and ecology of venoms in offensive

contexts is becoming increasingly understood, there is a general paucity of studies

investigating the selection pressures and relative importance of defensive venoms

(Casewell et al. 2013). Similarly, co-evolutionary arms races mediated by venom use

and counter-resistance have been recognized in the venom literature, but the role of

arms races in the evolution and ecology of venoms in offensive and defensive

contexts is poorly understood (Casewell et al. 2013). Thus, the overall aim of my

thesis was to investigate the role of arms races, co-evolution, and offensive and

defensive selection pressures in the evolution and ecology of venom use and

production. My thesis consists of three chapters, which fit within these overarching

themes, each of which will be submitted to a scientific journal.

Chapter 1 is a literature review of the underlying selection pressure for the

economical use of venom, which is believed to frame the evolution and ecology of

venoms, and how this fundamental pressure shapes venom in both offensive and

defensive contexts and may give rise to arms races. My intention is to publish this

chapter as a Toxicon review following the successful publication of the subsequent

two chapters, so that my results may be synthesised into the paper. Toxicon enforces

no strict formatting requirements or word limits for reviews, however I have used the

general article structure described by the Toxicon guide for authors. The broad,

general background to venom ecology, arms races, and offensive and defensive

venoms presented in Chapter 1 is not required, but will enhance an understanding of

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the findings presented in Chapters 2 and 3. Chapter 1 concludes with a consideration

of future directions in venom research, segueing into in Chapter 2.

In Chapter 2 I use both theoretical and experimental approaches to investigate the

effects of offensive and defensive selection pressures on venom production. First, I

present theoretical modelling, which I used to generate hypotheses of the effects of

offensive and defensive selection pressures on venoms in a three trophic-level

context. I then present al microcosm experiment, in which I test these hypotheses by

attempting to provoke a plastic response in the venom composition of the rainforest

scorpion Liocheles waigiensis. I found evidence for an induced plastic defence in

venom composition; and to my knowledge, adaptive plasticity in venom composition

has not been previously reported. I intend to submit Chapter 2 as an American

Naturalist article, and have formatted the chapter accordingly. While there is no

strict page length, the average length for manuscripts is 21 (double-spaced) pages of

text.

Lastly, Chapter 3 continues from the investigation of balancing arms races and the

evidence for a novel defensive response presented in Chapter 2. I expand the co-

evolutionary model used in Chapter 2 in order to evaluate the effects of co-evolution

and a third trophic level (an apex predator) on offensive and defensive venoms. In

doing so, I find and discuss how co-evolutionary arms races with prey may influence

the evolution of defensive venoms, and also discuss novel insights provided by co-

evolution into a long standing controversy in venom ecology, the ‘overkill’

hypothesis (Reviewed in Chapter 1). My intention is to submit Chapter 3 as an

American Naturalist note. Chapter 3 therefore abides by the according formatting

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requirements, including a limit of 3 figures/tables and 12 (double-spaced) pages of

text. When the abstract, figures, tables, and captions are excluded this chapter is

within the 12 page limit. I then conclude my thesis with a general discussion of my

findings.

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1.

Target journal: Toxicon

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Abstract The production and use of venoms is inextricably tied to the ecology

of the animals that use them. The venom optimisation hypothesis attempts to present

a unifying theory of venom, proposing that the putative high cost of venom

production drives selection for economical venom use. This concept frames the

relationship between variation in venom use and toxicity and the ecology of venom-

users. The hypothesis is corroborated by evidence of regulation of venom

expenditure and pressure on venoms for prey-capture and predator deterrence in

natural contexts. However, in general, venom has traditionally been considered to be

an offensive, rather than a defensive, adaptation. In light of emerging evidence

supporting the importance of defence as a selective pressure on venom evolution, we

review the production, use, and variation in venoms in both offensive and defensive

ecological and evolutionary contexts. However, the full extent to which ecology

shapes the immense biochemical variation in venoms remains unclear. We propose

coupling theoretical approaches to empirical work, which may help to inform future

research that attempts to improve both our understanding of defensive venoms and

the role and extent of arms races in venom evolution and ecology.

1.0 Introduction

An animal’s niche can be broadly defined as what it eats and where it lives, and the

threats that it faces there. The behavioural, morphological, and physiological traits an

animal uses to cope with these challenges, such as venom, can thereby benefit its

growth, reproduction, and survivability – its fitness (Kearney et al. 2010). Venoms

generally perform three functions: prey capture, threat deterrence, and digestion,

which assists in prey capture and assimilation. Indeed, although a precise definition

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has been contentious (Weinstein et al. 2013), the consensus view is essentially that

venom involves a complex mixture of chemicals variously used in the subjugation

and digestion of prey and in defence (Weinstein et al. 2012). The production and use

of venoms are therefore shaped by these functions in predator-prey interactions.

Offensive venoms (for prey capture) are typically biochemically complex and

variable in their physiological action and chemical composition (Fry et al. 2009). In

contrast, defensive venoms tend to be biochemically simpler and highly conserved in

their composition, producing the physiological effect of immediate, localised pain

(Church and Hodgson 2002; De Graaf et al. 2009; Peiren et al. 2005). Recent work

has challenged the characterisation of defensive venoms as comparatively simple

(Dutertre et al. 2014). Defence has traditionally been considered to be of secondary

importance to the use of venom in prey-capture (Casewell et al. 2013). Nonetheless,

because their use can thereby affect the vital rates – growth, reproduction, and

survivability – of a venom-user in different ways, offensive and defensive venoms

may be thought of as two different traits of venomous animals (Violle et al. 2007).

Together, offensive and defensive chemical warfare confers a substantial fitness

advantage by reducing the need to physically compete with and overcome potential

predators and prey (Morgenstern and King 2013). The broad taxonomic diversity of

animals which have independently evolved venoms attests to the significance of this

fitness advantage (Casewell et al. 2013). Venoms themselves are highly diverse,

exhibiting a huge variation in venom characteristics between phyla (Kordiš and

Gubenšek 2000), closely related species (Mackessy 2010), between populations of

the same species (Calvete et al. 2009; Glenn and Straight 1978), and even within the

lifespan of an individual in ontogenic variation (Andrade and Abe 1999) and

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between sexes (Menezes et al. 2006). This literature review will first address the

underlying pressure for economical use of venom that frames the relationship

between venom evolution and the ecology of venom-users (Section 2). How

variation in venom use and production is shaped by predator-prey interactions in

light of this fundamental pressure will then be considered (Section 3). Finally, we

will highlight the paradox of the lavish biochemical complexity of venoms in spite of

the hypothesised selection for venom economy (Section 4), and consider future

directions in venom research (Section 5).

2.0 Ecological perspectives on venom – an overview of venom ecology

Although there has been a traditional focus on human toxicity in venom research

(Fry et al. 2009), major advances in venom ecology have emerged in recent years.

Evidence explaining the geographic variation in venom composition in terms of diet

(Daltry et al. 1996) and for judicial behavioural regulation of venom-use (‘venom

metering’) culminated in the proposition that venomous animals employ various

strategies to minimize venom expenditure (Morgenstern and King 2013; Wigger et

al. 2002). The potentially high costs underlying this pressure to use venom

economically have been subsequently elucidated (McCue 2006; Nisani et al. 2012;

Nisani et al. 2007; Pintor et al. 2010). In addition to venom metering, strategies for

minimising costs may include the differential secretion of venom components in

different ecological interactions (Inceoglu et al. 2003) and the evolution of toxicity

towards natural predators and prey (Barlow et al. 2009), which may drive co-

evolutionary arms races (Casewell et al. 2013). And while most attention has been

paid to the use of venom for prey-capture (Casewell et al. 2013), the recent discovery

of separate offensive and defensive venoms in cone snails may prompt a renewed

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focus on understanding venom evolution and ecology in defensive contexts (Dutertre

et al. 2014). Objections have been raised to the hypothesised behavioural choice to

meter venom volumes in snakes (‘pressure-balance hypothesis’ (Young et al. 2002,

see section 2.3) and selection pressures driving economical use of venom snakes

(‘overkill hypothesis’ Mebs 2001, see section 3.1).

Nonetheless, the scope of our understanding still remains relatively narrow due to a

general research focus on pharmacologically important taxa. Indeed, venom research

has traditionally focused on snakes, and spiders and scorpions to lesser extent (Fry et

al. 2009). Relatively little attention has been afforded to other venomous taxa

including other arthropods and reptiles, cnidarians, molluscs, echinoderms, fish,

mammals, and amphibians (Casewell et al. 2013). Further, relatively little is

generally known about the ecology and natural history of venomous animals and

venom-use (Casewell et al. 2013). Improving our knowledge of venomous animal

ecology is critical to understanding the causes and processes underlying variation in

venoms, as well as critical for applied outcomes such as improving antivenoms and

human health outcomes (Richards et al. 2012).

2.1 The venom optimisation hypothesis, a unifying theory of venoms

The ‘venom optimisation hypothesis’ is central to venom ecology, conceptually

framing the evolution and ecology of venom use and production. Wigger et al.

(2002) demonstrated a frugal choice in the volume of venom injected by a

polyphagous spider on the basis of prey type, and proposed that this behaviour

served to minimise waste of a valuable and expensive resource. Further evidence has

since emerged from a broader range of taxa and was synthesised by Morgernstern &

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King (2013) in an attempt to generalize the hypothesis into a ‘unifying theory of

venoms’. It is argued that since venoms are rich in costly proteins and peptides (Fry

et al. 2009; Inceoglu et al. 2003), the expense of venom constrains the ability of

venomous animals to simply inject larger volumes in predator-prey interactions.

Instead, venomous animals evolve strategies to reduce venom expenditure

(Morgenstern and King 2013), including behavioural regulation (Section 2.3).

Although originally synonymous with venom metering only (Morgenstern and King

2013), selection for venom economy may also drive the evolution of venom toxicity

towards natural predators and prey (Section 3) (Casewell et al. 2013). Evidence for

the high cost of venom corroborates this hypothesised need for efficient venom

expenditure.

2.2 The costs of chemical warfare

It has been inferred from the secondary loss of venoms in a number of taxa that

venoms incur a considerable cost (King 2004; Li et al. 2005). Only four published

studies - limited to two species of snakes (McCue 2006; Pintor et al. 2010) and one

scorpion (Nisani et al. 2012; Nisani et al. 2007) - have investigated the metabolic

cost of venom regeneration to date. The nutritional costs of producing venom and the

maintenance of glands for venom production and storage have also been proposed as

potentially substantial costs (McCue 2006; Nisani et al. 2012), but remain un-

investigated. Though venom quantities are small relative to body mass (less than

0.5%) in snakes, spiders, and scorpions (Morgenstern and King 2013), increases in

metabolic rate ranging from 11% (McCue 2006) to 40% (Nisani et al. 2007) follow

the complete expulsion of venom (though see Pintor et al. 2010). This elevated

metabolic rate can be attributed to both the production of the biochemical

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components of the venom itself, and the metabolic cost of maintaining the venom-

producing and storage tissues (Morgenstern and King 2013). The time to fully

regenerate all components of a venom is not insignificant, requiring at least 28 days

in snakes (Oron and Bdolah 1973; Rotenberg et al. 1971), and from as few as 16

(Boevé et al. 1995) to as many as 85 days in spiders (Perret 1977). Given that

elevated metabolic rates must be sustained in some degree to synthesise venom

components for such durations, the maintenance of a venom system is likely to be

metabolically expensive (Morgenstern and King 2013). However, further studies are

needed to confirm, generalize, and quantify the physiological and (though difficult to

estimate) direct reproductive fitness costs of venom to fully evaluate the evolutionary

implications for venom production.

2.3 ‘Venom metering’, the behavioural optimisation of venom expenditure

If chemical warfare is costly, then the optimisation hypothesis posits that regulatory

behaviour should ration this valuable resource (Wigger et al. 2002). Indeed, a

growing body of research has shown such ‘venom metering’ in a range of venomous

taxa (Morgenstern and King 2013). Spiders, for instance, may evaluate venom

resistance in prey based on olfactory cues and use their venom accordingly

(Hostettler and Nentwig 2006). But the bulk of the research has historically come

from snakes, for which the evidence of metering has been disputed. Proponents of

the ‘pressure-balance’ hypothesis maintain that variable secretion volumes are a

consequence of mechanical constraints and passive regulation upon contact of the

venom apparatus, not behavioural regulation prior to contact (Young and Kardong

2007). While more recent evidence has cast doubt upon this view (Morgenstern and

King 2013), there remain some valid criticisms. Notably, there is an inadequate

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understanding of the sensory mechanisms by which venomous animals in general can

assess an interaction and utilize their venom accordingly (Morgenstern and King

2013; Young et al. 2002; Young et al. 2003).

In any case, the emerging evidence strongly supports behavioural metering of venom

to varying degrees in different taxa. A choice of whether or not to envenomate at all

or to simply physically subdue prey has been shown in both snakes and arachnids

based on the relative size and threat posed by the target (Edmunds and Sibly 2010;

Rein 1993). Once the decision to envenomate is made, a range of factors have been

shown to influence the delivery and volume of venom to minimize venom-use in

different trophically venomous taxa, including the relative sizes of the venom-user

and target (Edmunds and Sibly 2010; Hayes 1995; Malli et al. 1999), intensity of

struggling by the victim (Malli et al. 1999), venom-user hunger (Hayes 1993),

handling time (Edmunds and Sibly 2010), prey type (Edmunds and Sibly 2010;

Hayes 1992), and venom availability (Hostettler and Nentwig 2006). Thus, it appears

likely that venomous animals behaviourally regulate venom expenditure to minimize

the high cost of chemical warfare.

3.0 Economy, arms races, and variation in offensive and defensive venoms

Venom evolution, as well as behavioural strategies in the use of venom, is likely

driven by a pressure for economical use of venom (Casewell et al. 2013). Indeed,

selection for economy appears to drive the evolution of toxicity towards prey in

scorpion-eating saw-scaled vipers (Echis spp.), rather than kill-speed (Barlow et al.

2009). By increasing toxicity towards natural predators and prey, efficacy (i.e. in

subduing prey or deterring a threat) can be sustained with a smaller quantity of

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venom. The resulting selection pressure on predators and prey to evolve venom

resistance to mitigate evolving toxicity may give rise to a reciprocal selection

pressure on venomous animals for yet higher toxicity and/or novel toxins (Casewell

et al. 2013). The net result is a ‘Red Queen’ effect (Van Valen 1974), an escalating

co-evolutionary arms race. Venomous predator-prey systems demonstrate the basic

requirements for co-evolutionary arms races to occur, exhibiting specific toxicity

towards natural predators (Binford 2001; Dutertre et al. 2014) and prey (Barlow et al.

2009; Pekár et al. 2008), as well as venom resistance occurring in both natural

predators (Jansa and Voss 2011) and prey (Biardi and Coss 2011; Heatwole and

Poran 1995; Poran et al. 1987) of venomous animals.

There is a paucity of direct evidence of arms races between venomous animals and

their prey, and even more meagre evidence for defensive arms races with predators

(Casewell et al. 2013). Nonetheless, arms races and co-evolution may be key

processes driving the evolution of, and variation in, venoms across a mosaic of

different predator-prey communities, in both offensive and defensive contexts.

However, it is important to remember that this evolutionary adaptation is restricted

by the genetic constraints imposed by ancestral morphology and physiology.

Furthermore, other predator-prey systems show that arms races may not necessarily

escalate perpetually, but can be limited by settling to an equilibrium between prey-

capture and anti-predatory traits (Becks et al. 2010). In sum, selection for venom

economy in offensive and defensive contexts, which may give rise to arms races, are

likely major drivers of the inter- and intraspecific variation in the composition,

function and delivery of venoms.

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3.1 Offensive venoms and the ‘overkill’ controversy

Selection for diet is a potent force which drives variation in venoms both between

and within venomous taxa (Casewell et al. 2013). But this view - and, more broadly,

the concept of venom optimisation - has been contentious. In snakes, there has

historically been inadequate evidence of adaptive venom composition (Chippaux et

al. 1991; Sasa 1999; Williams et al. 1988), and evidence of extreme venom toxicity

(Mebs 2001) and injection volumes (e.g. (Hayes et al. 2002; Young et al. 2002). The

‘overkill’ hypothesis cites such evidence of seemingly indiscriminate use of venom

and a lack of dietary pressures acting upon venom composition, and presents an

alternative neutral hypothesis of venom evolution (Gibbs et al. 2013; Mebs 2001).

Multiple studies of snake venom composition have failed to demonstrate a

correlation between venom composition and geographical differences in diet

(Chippaux et al. 1991; Williams et al. 1988). Williams et al. (1988) found that

variation in venom composition between populations of the tiger snakes Notechis

ater niger and N. scutatus was instead correlated with geographic distance, indicative

of neutral evolutionary processes, but noted that didn’t exclude selection for genes

encoding particular venom components. Early evidence for a correlation between

diet and inter-population variation in the venom of the Malayan pit viper

Calloselasma rhodostoma was criticized for lacking toxicity data to demonstrate a

causal relationship between venom variation and toxicity towards prey (Mebs 2001;

Sasa 1999). Yet subsequent studies have since suggested that venom production is

generally subject to a strong island effect, giving rise to inter-population variation

driven by differences in diet (Zelanis et al. 2008).

14

Indeed, a wealth of evidence for prey-selection in venom has emerged from a broad

array of taxa, including spiders (Pekár et al. 2008), scorpions (Abdel-Rahman et al.

2009; Zhao et al. 2010), jellyfish (Kintner et al. 2005; McClounan and Seymour

2012), cone snails (Duda Jr et al. 2009; Elliger et al. 2011; Fainzilber et al. 1991;

Remigio and Duda Jr 2008), and also snakes (Barlow et al. 2009; Furry et al. 1991;

Jorge da Silva and Aird 2001). These studies have variously demonstrated adaptive

evolution for prey-specific toxicity extending from the whole venom to individual

toxins, such as the avian-specific denmotoxin in the mangrove snake Boiga

dendrophila (Pawlak et al. 2006). The secondary loss of venom toxicity in the sea-

snake Aipysurus eydouxii due to a dietary shift to an ovivorous diet corroborates the

importance of prey-selection, and provides compelling evidence for a strong positive

selection on venom production (Li et al. 2005). Thus, the emerging picture from

empirical evidence is in favour of selection upon venom composition for optimised

prey-capture and venom economy.

Nonetheless, remaining evidence for the ‘overkill’ of prey via excessive venom

injection and toxicity by snakes is problematic. Sasa (1999) proposed that the

adaptive value of snake venoms may exhibit a continuum, where selective

advantages of venom might be evident in some taxa but absent in others. But such a

view is seemingly irreconcilable with the putative cost of venoms, the consequent

selection for venom economy, and the strong selective pressure that appears to act on

venom production. Thus, the evidence for wastefully large injection volumes and

excessive toxicity of some snake venoms must be addressed. Firstly, generalist

venomous predators, which can encounter prey exhibiting a broad range of

susceptibilities to their venom, may inject large quantities of venom as a form of ‘bet

15

hedging’ to guarantee a meal (Hayes 1992). Investigations quantifying toxicity have

also frequently used model organisms, such as mice, which fail to exhibit the

physiological resistances to venom toxins arising in natural predators and prey

(Chippaux et al. 1991), potentially as a consequence of co-evolutionary arms races.

Secondly, laboratory studies have shown that snakes will inject venom volumes

hundreds of times greater than the lethal dose requirements (Mebs 2001). But studies

investigating metering by snakes upon different size classes of prey have indicated

that snakes do meter venom, but can only coarsely distinguish between smaller prey,

perhaps owing to the relatively insignificant venom volumes required or a limited

ability to finely meter their venom (Hayes et al. 2002; Young et al. 2002). In sum,

while minor points of contention may remain, empirical evidence strongly supports

the role of prey-capture and diet as a major force driving venom variation (Casewell

et al. 2013).

3.2 Defensive venoms – time to reconsider?

Venoms are typically thought of as a foraging adaptation and, indeed, this has

historically been the main focus of study (Casewell et al. 2013). However, recent

evidence for the separate selection and production of a discrete defensive venom in

cone snails has led to the prediction that specialised defensive venoms may be more

widespread and important in other venomous taxa than previously recognized

(Dutertre et al. 2014). Histological evidence for different secretory units has been

found in sea anemones (Moran et al. 2013), spiders (Silva et al. 2008), snakes (Sakai

et al. 2012), centipedes (Nagpal and Kanwar 1981), and scorpions (Yahel-Niv and

Zlotkin 1979), suggesting that other venomous animals may be able to produce and

secrete separate venoms as in Conus. Scorpions can secrete a clear, chemically

16

cheap, pain-inducing ‘prevenom’ to deter threats before resorting to their more

complex, protein-rich and chemically expensive ‘main’ venom (Inceoglu et al. 2003).

Indeed, specialised pain-inducing toxins are known in snakes (Bohlen et al. 2011),

spiders (Siemens et al. 2006), ants (Schmidt 1990), centipedes (Undheim and King

2011), lizards (Strimple et al. 1997), and various fishes (Bohlen and Julius 2012) and

can effectively deter potential threats without causing significant tissue damage

(Bohlen and Julius 2012).

Though venom is employed primarily for defence by hymenopterans, lepidopterans,

echinoderms, stingrays, ‘bony fish’, amphibians, and eutherians, there is relatively

little empirical evidence to demonstrate defensive-related selection pressures acting

upon venom composition in any taxon (Casewell et al. 2013). The deleterious effects

of venom upon an aggressor in defensive contexts has been typically explained as

arising from conserved pharmacology between the predators and prey of venom-

users, rather than from a separately-evolved defensive strategy (Dutertre et al. 2014;

Fry et al. 2009). Nonetheless, in addition to cone snails, defensive pressures have

been implicated in the evolution of defensive venoms in age-related (ontogenic)

shifts in ecology which heighten exposure to predators in bees (Owen and

Braidwood 1974) and spiders (Binford 2001; de Andrade et al. 1999).

Similarly, while many studies have supported the view that venomous animals can

behaviourally control venom expenditure in predatory contexts, few have

investigated metering in defensive situations. Those which do have been limited to

snakes (Hayes et al. 2008), ants (Haight 2006; Obin and Vander Meer 1985),

scorpions (Nisani and Hayes 2011), and spiders (Nelsen et al. 2014). High rates of

17

‘dry biting’ or stinging, in which no venom is actually delivered seems to be a

common mode of defensive venom-use (Morgenstern and King 2013), and snakes

exhibit highly variable injection volumes in threatening interactions (Hayes et al.

2002). ‘Dry bites’ have been hypothesised, but not demonstrated, to deter predators,

perhaps with the threat of injection, while preserving valuable venom (Cooper et al.

2014). The threat of predation could pressure venomous animals to stockpile large

volumes of venom to ensure successful deterrence in a threatening encounter

(Cooper et al. 2014). Furthermore, there is limited evidence for defence-specific

morphological adaptations, such as specialized fangs to spit venom at an aggressor in

the elapid genera Naja and Hemachatus (Wüster and Thorpe 1992). In sum, the

accumulated evidence appears to implicate prey selection as a stronger selective

force than defence in most venomous animals (Casewell et al. 2013), for which there

seems to be lower levels of adaptive evolution (Wüster and Thorpe 1992) (Figure 1).

This supposedly generally weaker selection pressure on the defensive venoms seems

counter-intuitive. Survival is a compromise between resource acquisition, avoidance

of predation, and reproduction. But while the consequence of a failed foraging event

or mating event is simply a missed meal or opportunity to produce offspring, the

penalty for failing to avoid a predator is death, or at least injury. The ‘life-dinner’

principle describes this asymmetry in the price of failure for predators and prey

(Dawkins and Krebs 1979), and might superficially predict that selection for

investment in defensive venom-use should be stronger. However, ‘winning’ a

defensive interaction only requires escape, while ‘winning’ a predatory interaction

necessitates subduing and consuming prey. Defence is a major selective force for

cone snail venoms (Dutertre et al. 2014), but their limited mobility means that cone

18

Figure 1: Tree of venomous animals demonstrating the relationship between animal lineages and

the major ecological usage of venom, from Casewell et al. (2013). Coloured branches indicate

lineages which include venomous taxa. Red branches indicate a predominantly predatory role for

venom, blue a defensive role, and green a role in intraspecific competition. Note that for

Protostomes and reptiles, venom is predominantly used for prey-capture, while the use of venom by

other Deuterostomes is mainly for predator-deterrence.

snails possess few other means of effectively deterring threats, besides their shell.

Other venomous animals may be less dependent on their venom in defensive

contexts, given the putative high cost of venom production. Indeed, scorpions

generally prefer to retreat from threats (van der Meijden et al. 2013). Behavioural

responses in predatory contexts may thereby blur the relationships between

morphology, behaviour, and ecology, and decouple selection for maximum

19

performance in defensive contexts from ecology (van der Meijden et al. 2013). In

other words, venoms may appear to be relatively unimportant for defence because

venomous animals instead rely more heavily upon less costly behavioural anti-

predator strategies, such as retreat.

Lastly, there is relatively meagre evidence of co-evolutionary arms races between

venomous animals and their predators (Casewell et al. 2013). Sufficient reciprocal

selective pressure inducing the rapid evolution of defensive venom compounds is

more likely where the physiological and taxonomic diversity of predators do not

present a broad physiological target, and where the frequency of interactions with

predators are sufficiently high. Where predators are more generalist in their dietary

preferences there may be inadequate pressure to drive the co-evolution of venom-

resistance, whereas specialized predators are more likely to develop venom

resistance (Jansa and Voss 2011). In general, while the available evidence suggests

that the use and function of defensive venom may substantially differ to offensive

venoms, significantly more work is needed to understand the role of venom in

defensive contexts and the selection pressures acting on the evolution of defensive

venoms.

3.3 Demographic variation in offensive and defensive venoms

Ontogenetic niche shifts, whereby individuals exploit different resources, reduce

intraspecific competition between life stages and can thereby increase individual

fitness and the carrying capacity of the population (Werner and Gilliam 1984). When

this occurs, the venom optimisation hypothesis suggests that venom production and

use will change to mirror variation in the diet and threats faced by a venomous

20

animal across its lifespan, and sex-related differences in ecology. Indeed, the

avoidance of competition between adults and juveniles is regarded as the principal

ecological model to explain ontogenic shifts in venom composition (Underwood and

Seymour 2007).

There has been a long history of studies which correlate ontogenic shifts in prey

choice with concurrent shifts in venom use and composition, primarily in snakes

(Andrade and Abe 1999), spiders (Casper 1985), scorpions (Morgenstern and King

2013), and more recently also in jellyfish (McClounan and Seymour 2012;

Underwood and Seymour 2007). In offensive contexts, ontogenic shifts in venom are

thought to be associated with an increase in the energetic requirements of adults

(Hayes 1995; Zelanis et al. 2008). The resulting dietary change can be coupled with

changes in venom toxicity towards new prey (Underwood and Seymour 2007) and in

protease production to aid in the digestion of larger prey (Zelanis et al. 2008).

Upon reaching maturity, divergences may occur in venoms in tandem with the

emergence of different life histories between sexes. For example, male hobo spiders

(Tegenaria agrestis), which actively wander outside their burrows for mates, exhibit

selection for defence from the higher vertebrate toxicity of their venom compared to

that of more sedentary females, as a consequence of their higher exposure to

vertebrate predators (Binford 2001). Sexual dimorphism, which gives rise to

increased energy requirements in one sex, can also drive demographic variation in

offensive venom composition (Daltry et al. 1997; Furtado et al. 2006). And in the

burrowing scorpion Scopio maurus palmatus, the more complex chemical

composition of female venoms was attributed to a high frequency of sexual

21

cannibalism (Abdel-Rahman et al. 2009). Thus, evidence for variation in offensive

and defensive venoms precipitated by demographic differences highlights the need

for further research of the natural histories of venomous animals. Only knowledge of

the life histories of venom-users can elucidate this individual-level of variability

which may be invisible to geographic studies comparing venom composition

between populations.

3.4 Constraints upon venom evolution

While selection pressures drive evolution, constraints restrict and delimit the

pathways along which it can occur. Thus, it is also vital to consider the ancestral

morphological, physiological, and chemical innovations and limitations which

influence the present production, use, and delivery of venoms in offensive and

defensive contexts. Morphology is strongly genetically constrained, which limits the

evolution of delivery systems. The limited ability of cone snails to retreat from

threats may be responsible for the strong selection pressure for defensive venom (see

section 3.2). Similarly, spiders and scorpions have been shown to exhibit far more

sophisticated, highly judicial venom metering than snakes (Bub and Bowerman

1979; Malli et al. 1999; Nisani and Hayes 2011). Why might this be so? Spiders and

scorpions evaluate the need to continue injecting venom by assessing the struggling

of their grappled prey, injecting more venom as required (Morgenstern and King

2013). Snakes, conversely, tend to immediately release and then track their

envenomated prey by scent (Furry et al. 1991; Smith et al. 2000), avoiding retaliatory

injury and perhaps ultimately owing to a generally greater difficulty in maintaining a

grapple without limbs. Indeed, it has been suggested that necessary adaptations of

musculature and body conformation to suit constriction may generally be mutually

22

exclusive with the speed and agility necessary for venom-use in snakes (Shine and

Schwaner 1985), also constriction is known in some venomous snakes (Morgenstern

and King 2013; Shine and Schwaner 1985).

Similarly, phylogenetic constraints and ecological selection pressures may both

contribute to variation in the composition of venoms. Correlations between diet and

venom variation between congeners should be considered within a phylogenetic

context to pinpoint where evolutionary shifts in diet and venom composition have

occurred, to rule out similarities due to common ancestry (Barlow et al. 2009).

Toxins employed and adapted for prey- and predator-specificity by a venomous

animal are constrained by the venom components that have already been made

available for modification by ancestral evolution, which can vary between taxa.

Indeed, fundamental differences in toxin chemistry arises between major lineages of

venomous animals, shaping variation between taxa (Kordiš and Gubenšek 2000).

Toxic proteins generally evolve via recruitment and modification of proteins from

other physiological processes which satisfy a range of requirements (reviewed in Fry

et al. 2009) These proteins then typically undergo extensive gene duplication with

modification, generating closely-related ‘toxin families’ (Casewell et al. 2013).

There is a high degree of convergence in the underlying biochemical structure and

pharmacology of toxic proteins between protein families (Fry et al. 2009). For

example: cone snails, scorpions, spiders, centipedes, bees, cnidarians, echinoderms,

and reptiles have all evolved different molecular strategies for targeting the same ion

channels (Fry et al. 2009). Further, there is a high frequency of independent

recruitment of the same proteins families in closely and distantly-related taxa

23

(Casewell et al. 2013). For example, the underlying chemical structure of

phospholipase A2 has been independently recruited four times into squamate reptiles,

but also in the venoms of cephalopods, cnidarians, insects, and scorpions (Casewell

et al. 2013). So long as they satisfy they satisfy the necessary biochemical criteria to

be eligible for recruitment as toxins, then is there any advantage to recruiting a given

protein over another? So long as they ultimately exhibit the same functional effects

of killing or immobilizing prey and deterring predators, the recruitment of a given

protein may simply be subject to chance and neutral processes. The relative extent to

which this underlying biochemical variation is related to adaptive significance is a

question that has yet to be seriously addressed.

4.0 Venom biochemistry and the optimisation hypothesis

The most confounding problem facing the optimisation hypothesis is the seemingly

lavish biochemical complexity of venoms (Morgenstern and King 2013). Non-toxic

proteins and peptides constitute a large proportion of venom, despite the substantial

reduction in metabolic cost that could be gained by even a small decrease in these

non-active proteinaceous components (Morgenstern and King 2013). Additionally,

the extraordinary degree of functional redundancy in the biochemical action

exhibited by different toxins in the same venom seems at odds with the putative

pressure for venom economy (Casewell et al. 2013).

The rapid evolution of seemingly redundant venom components may be a necessary

price to pay in order to continually generate novel toxins for use in predator-prey

interactions. When applied to venom evolution, the ‘birth and death’ model of

evolution of multigene families (Nei and Rooney 2005) posits that extensive,

24

imperfect duplication of toxin genes to increase toxin production gives rise to

chemical redundancy due to minor mutations in the amino-acid sequence (Casewell

et al. 2013; Li et al. 2005). This process is hypothesized to provide the necessary

diversity of toxins for venomous animals to compete against evolving resistances in

co-evolutionary arms races with their predators and prey, and to target potentially

new predators and prey (Casewell et al. 2013). But though this model predicts that

redundant toxins, which confer no functional advantage, should degrade, this does

not always appear to be the case. For example, the venom of the scorpion Leiurus

quinquestriatus hebreus contains 14 toxins which bind to the same receptor in insects

(Morgenstern and King 2013). Some may truly be redundant and retained and

transcribed from the genome as a ‘toll’ worth paying to maintain a large collection of

toxin encoding genes subjected to duplication and diversification (Weinberger et al.

2010).

To some extent, the lavish diversity of venom components can be explained by

synergistic effects, which improve the toxicity of the venom. These seemingly weak,

redundant, and even non-toxic compounds may cooperatively enhance the activity of

other venom components (Cohen et al. 2006). Indeed, the birth and death model

suggests that there is more benefit to maintaining large, multilocus ‘toxin families’

arising from gene duplication compared to ‘optimising’ the potency of a single toxin,

due to the synergistic effects they could provide (Casewell et al. 2013). For example,

the nontoxic mutant scorpion peptide Bj-xtrIT-E15R induces a conformational

change in the physiological target of the alpha toxin LqhαIT, enhancing its binding

and toxicity (Cohen et al. 2006). Similarly, cone-snails use synergistic pairs of toxins

called “toxin-cabals” to induce rapid paralysis in prey (Espiritu et al. 2001). Weak

25

and non-toxic venom components may provide other benefits, such as antimicrobial

activity to resist infection from prey ingestion (Kuhn-Nentwig 2003) or antiseptic

activity for honeycomb construction by bees (Baracchi et al. 2011).

Specific components from a broad armoury of available toxins may be selectively

produced or secreted in response to specific predator or prey interactions

(Morgenstern and King 2013). Similar ‘biochemical modulation’ of venom has been

seen in the cheap and rapidly-regenerating prevenom of scorpions. Prevenom

contains pain-inducing potassium ions and fewer, simpler proteinaceous toxins, and

is preferentially used first in defensive interactions, preserving the more complex and

costly main venom (Inceoglu et al. 2003). Furthermore, prevenom can also be used

to immobilize arthropod prey, enabling scorpions to actively forage as well as deter

predators while main venom slowly regenerates (Inceoglu et al. 2003). The absence

of specific venom proteins in the initial stings of the scorpion Parabuthus

transvaalicus also suggests the selective use of certain proteins (Nisani and Hayes

2011). The potential for biochemical or physiological modulation in snakes (Cascardi

et al. 1999) and spiders (Boevé et al. 1995) has been observed, but identification of

modulation in natural secretions was confounded in the latter by the use of

electrostimulation, which induces the complete evacuation of the venom glands.

Further research is needed in order to determine the extent to which biochemical

modulation in offensive and defensive encounters can explain the adaptive

significance of the venom complexity.

26

5.0 Future directions

The venom optimisation hypothesis lays a conceptual framework that relates venom

ecology and evolution to the high cost of venom production and a strong selection

pressure for venom economy. The underlying pressure to use venom economically

thereby frames the way in which venom and venom-use has evolved in response to

the predators and threats of venomous animals. While there has been growing

support for an association between variation in venoms and prey-capture (Casewell

et al. 2013), we still have a poor understanding of the pressures upon and role of

defence in venom evolution, likely due to the logistical difficulties in exposing

individuals to the often wide range of predators venomous animals might interact

with. Theoretical modelling can help to deal with these logistical difficulties, to

consider evolutionary questions that are difficult to empirically investigate due to the

time-frames involved, and to generate hypotheses that can be empirically tested. For

example, the recent discovery of separate offensive and defensive venoms in cone

snails has prompted a reconsideration of the role of defence in venom production,

and whether or not separate venoms might be more widespread (Dutertre et al. 2014).

Modelling can help elucidate the circumstances under which two separate venoms

for prey capture and predator deterrence might be more beneficial than using a single

venom that fulfils both functions.

Theoretical modelling has also been extensively used to investigate co-evolutionary

arms-races, due to difficulties in tracking the values of traits and their associated

fitness costs (Abrams 2000). Modelling may provide a rare opportunity for guided

empirical studies of arms races in venomous predator-prey systems. Theoretical

27

models may also be used to generalize the results found from simpler systems such

as toxin-producing bacteria (Kerr et al. 2002), where real-time evolutionary

experiments are more logistically feasible than for most venomous animals.

Further studies of the natural histories of venomous animals and venoms are vital,

especially in taxa that have traditionally been neglected, such as centipedes and

insects, fishes, mammals, and echinoderms. Indeed, the historical focus of study has

been on taxa for which venom is primarily an offensive adaptation. Broadening our

understanding of venom ecology in a wider range of venomous taxa, especially the

understudied organisms for which venoms are primarily a defensive adaptation, will

help to ensure the generality of the unifying theory of venoms, the optimisation

hypothesis. The optimisation hypothesis would further benefit from a more thorough

understanding of the precise nature of the costs of venom production, and from a

broader understanding from a wider range of taxa. In light of these costs, the

unexplained biochemical complexity and redundancy remains largely unexplained

and remains the biggest challenge to the optimisation hypothesis.

Finally, other strategies that may be employed by venomous animals to optimise the

use of their venom remain to be explored. Whether or not biochemical modulation of

venoms is consistent with the optimisation hypothesis should be a focus of future

studies (Morgenstern and King 2013). To our knowledge, the possibility for

phenotypic plasticity in venom biochemistry remains unexplored and may present

another important mechanism for managing the costs of chemical warfare in a

changing environment.

28

2.

Target journal: American Naturalist

29

Abstract Animals generally balance the costs and benefits of prey-capture and

anti-predator traits in two simultaneous co-evolutionary arms races. We investigated

selection pressures on offensive and defensive venom production in a venomous

animal for prey-capture and for predator-defence using a co-evolutionary model

describing the dynamics of a 3-level trophic chain. We used the models to develop

hypotheses and tested them in a microcosm experiment with a rainforest scorpion.

We identified rapid responses in scorpion venom profiles over the course of six

weeks, induced by manipulated predator interactions. We manipulated selection for

offensive and defensive scorpion venoms by inducing stinging (venom use) against a

model insect prey and a stuffed model vertebrate predator, respectively. Higher

predation pressure was expected and confirmed to stimulate defensive venom

production. We discuss the potential for this induced defence for stabilizing food

webs.

Introduction

Arms races in venomous animals

Co-evolutionary arms races involving predatory and anti-predator traits are

ubiquitous in food webs (Wade 2007), and may be important in venom production

and counter-defence systems (Casewell et al. 2013). Perhaps as it is a costly resource

(McCue 2006; Nisani et al. 2012; Nisani et al. 2007; Pintor et al. 2010), venomous

animals employ various strategies to reduce the use of venom in both offensive and

defensive contexts (Morgenstern and King 2013). Behavioural strategies, such as the

metering of venom secretion volumes and assessment of the risk posed by a potential

predator, are employed to varying extents by venomous taxa (Morgernstern & King

30

2013). There is also growing evidence that venom economy drives selection for

lethality towards natural predators and prey (Barlow et al. 2009). In doing so, venom

can be used more economically to achieve the same efficacy. This gives rise to a

reciprocal selection pressure between predators and prey of the venomous animal,

which evolve a resistance to mitigate the increasing toxicity of the venom (Casewell

et al. 2013). The result, known as the “Red Queen” effect, is a co-evolutionary arms-

race of escalating venom toxicity and venom resistance (Van Valen 1974). Although

venomous predator-prey systems demonstrate the basic requirement of a reciprocal

selection pressure for these arms races to arise, they have received little empirical

attention in offensive contexts and less-so for defensive contexts (Casewell et al.

2013). Nonetheless, evidence for the extraordinarily rapid evolution of venom toxins

compared to other Metazoan protein-coding genes (Chang and Duda 2012), for

toxin-specificity towards natural predators and prey (e.g. Dutertre et al. 2014), and

for a co-evolving resistance in both predators (e.g. Jansa & Voss 2011) and prey (e.g.

Coss et al. 1993) of venomous animals broadly supports the emergence of arms-races

in venomous animals. How these arms races influence the evolution of prey-capture

and anti-predator traits – including venom – may be understood by examining arms

races in other predator-prey systems, and using theoretical modelling of these

systems (Abrams 2000).

Theory and evidence for offensive and defensive venoms

The physiological, behavioural, and morphological traits with which an animal deals

with the challenges of capturing prey and deterring predators affect its vital rates –

growth, reproduction, and survivorship and, therefore, fitness (Kearney et al. 2010).

Since the use of venom to facilitate feeding predominantly benefits growth and

31

reproduction, while its use for defence by the producing animal primarily benefits

survivorship, offensive and defensive venom efficacy could be thought of as two

traits of a venom-user (Violle et al. 2007). Further, they can be considered to be traits

which may overlap due to the potential for individual venom toxins to biochemically

target prey only, predators only, or both. Venoms consist of toxins which are both

broadly toxic and phyla-specific in their toxicity (Nicholson 2007), and different

toxins in a venom can separately target different taxa for maximal efficacy (Fry et al.

2009; Kordiš and Gubenšek 2000). Offensive and defensive venom-use may

consequently overlap to varying degrees, depending on the extent to which toxins are

specialized towards predator and prey physiology and biochemistry. For example,

Na+-channel blocking α-toxins are a category of scorpion toxins containing a

subgroup of toxins only highly active only towards mammalian voltage-gated

sodium channels (VGSCs), another subgroup active only towards insect VGSCs, and

a third group of ‘α-like’ toxins toxic towards both insects and mammals (Quintero-

Hernández et al. 2013). This capacity for different toxins to target separate

physiologies is seen in other venomous animals including jellyfish (McClounan and

Seymour 2012), centipedes (Yang et al. 2012), cone snails (Dutertre et al. 2014),

snakes (Zlotkin et al. 1975), and spiders (Nicholson 2007). In some venomous taxa

the same toxins may be used in both offensive and defensive contexts, resulting in no

distinctly different ‘offensive’ and ‘defensive’ toxins. For example, the diversity and

complexity of both phyla-specific and general toxins in spider venoms enable them

to prey upon specific groups of insects, though most are considered to be generalist

predators (Kuhn-Nentwig et al. 2011; Nicholson 2007). If there is sufficient selection

pressure and if the physiologies and biochemistries of predators and prey are

32

sufficiently different then the potential certainly exists for distinctly offensive and

defensive venom components to coexist in the same whole-venom mixture.

Adaptive plasticity in venoms

To our knowledge, an adaptive plastic response in underlying venom composition

arising from altered ecological interactions has not been previously reported.

Existing studies have found the that specific components of a whole-venom can be

differentially secreted in response to different interactions in a limited number of

venomous taxa including the spitting cobra Naja pallida (Cascardi et al. 1999), the

wandering spider Cupiennius salei (Boevé et al. 1995), the dark scorpion Parabuthus

transvaalicus (Nisani and Hayes 2011). Cone snails can deploy separate offensive

and defensive venoms in prey and predator interactions, respectively (Dutertre et al.

2014). Scorpions can secrete a cheap ‘pre-venom’ which can induce pain to deter

potential predators before resorting to a more costly “main” venom (Inceoglu et al.

2003), and which is preferentially used in low-threat encounters (Nisani and Hayes

2011). None of these studies have shown a plastic response in the composition of the

whole-venom itself. In sum, we know that different “ingredients” in the whole-

venom recipe can be selectively used in a limited number of venomous animals, but

we don’t know whether this “recipe” is fixed, or if it can plastically respond to a

changing environment. Previous studies in plant-herbivore and other predator-prey

systems have suggested that inducible defences should be most common when cues

for biological threats are reliably available, when biological attacks are

unpredictable, and when the fitness benefits exceed the costs of plasticity (Harvell

1990). Furthermore, plastic induced defences should also be favoured if defences are

costly and not always needed, as in the chemical warfare employed by both plants

33

and venomous animals (Karban 2011). Thus, the potential ability to mitigate the

costs of venom production by decreasing production or altering composition to

favour prey-capture and feeding would be consistent with the optimisation

hypothesis.

Statement of aims and hypotheses

In our broad investigation of the effects of predator-prey interactions upon venom

composition, the aims of this study were twofold, and combined theoretical and

experimental approaches. Our first aim was to understand how the offensive and

defensive traits of venoms might evolve when subjected to different ecological

interactions, using mathematical modelling of 3-trophic level predator-prey dynamics

and co-evolutionary trait-change. Although venomous animals are predators

themselves, for clarity we refer to the venomous animal in our model as a

“consumer” to avoid confusion with the apex generalist predator. The modelling was

used to investigate two hypotheses: 1) that applying a predatory pressure would

diminish the co-evolutionary arms race between the venomous consumer and prey by

decreasing their predatory and anti-predator trait and 2) increasing prey abundance

should enhance the arms race by increasing consumer and prey predatory and anti-

predator traits.

The second aim of the study was to evaluate the potential and direction for adaptive

plasticity in the venom profile of a venomous animal in response to manipulated

ecological interactions. Venoms are a complex mixture of molecules (Casewell et al.

2013), and this molecular diversity can be teased apart to varying extents and

34

captured using a range of analytical techniques such as chromatography and mass-

spectrometry to obtain a ‘venom profile’ (Shen and Noon 2004). We tested the null

hypothesis that manipulating ecological interactions would not give rise to changes

in venom profile compared to a control. Any observed change in the mature venom

profile in response to either the predatory or prey treatment would indicate a plastic

response. Theoretical studies suggest that plastic trait change is a good predictor of

the direction of evolutionary change (Draghi and Whitlock 2012), and we therefore

hypothesized that any plasticity we observed would occur in the same direction as

predicted by our eco-evolutionary model.

Theoretical modelling

Model description

Theoretical modelling of natural systems can be used to guide empirical work and to

investigate natural systems that are difficult to empirically study (Abrams 2000). In

our study, we investigate the evolution of prey-capture (offensive) and anti-predatory

(defensive) traits in a venomous animal embedded in a food web. The venomous

animal (e.g. a scorpion) feeds on a co-evolving prey (e.g. an insect), and is itself

preyed-upon by a generalist (non-co-evolving) predator (e.g. a small mammal).

Theoretical studies of 2 trophic-level predator-prey systems involving co-

evolutionary arms races suggest that reciprocal selection pressures give rise to an

escalating increase in offensive and defensive traits (Dieckmann et al. 1995). Studies

of co-evolution in tri-trophic-level systems involving plants, herbivores, and

herbivore-predators suggest that herbivores attempt to balance these arms races to

minimize their net costs (Nersesian et al. 2011). Thus, a consumer may adopt

35

intermediate trait values when arms races between their predators and prey need to

be balanced.

We used a three trophic-level, discrete-time Lotka-Volterra model of co-evolutionary

trait change to investigate the evolution of two traits – offensive venom and

defensive venom – in a venomous consumer. Our model is an extension of the 2

trophic-level model described by Northfield and Ives (2013), we also assume a type

1 functional response for simplicity. The changes in population densities of the prey

(Rt), venomous consumer (Ct), and predator (Pt) at time t are given by (Equations

2.1):

tRtRR CvvqRvrr

tt eRR),(),(

1110

ttR PvqvvmRvvcq

tt eCC)(),(),(

1222111

PtPP mCvqcPr

tt ePP)()(

122

In the model we assume that consumer fitness is balanced by predation on the prey

species (where higher offensive venom investment increases consumer predation

rate), density-dependent mortality due to predation by the predator (where more

highly defensive venom reduces apex-predator predation rate), and mortality due to

other density-independent effects (which increases with investment in each venom).

The prey species may mitigate mortality due to consumer predation by investing in

venom resistance (modelled as venom ‘susceptibility’, where lower susceptibility

provides higher venom resistance), which is balanced by a cost (modelled as density-

independent mortality). Because we modelled the predator as a generalist predator,

its growth does not entirely depend on preying on the consumer species. Rather, it

36

has an alternative growth rate and carrying capacity. Since the predator’s fitness is

not tightly linked with the defensive venom of the consumer, we assume that it does

not co-evolve with the consumer. The parameters and general functions used in the

population density expressions are presented in Tables 1 and 2, respectively.

Table 1: Description of parameters used in model equations describing change in population densities

for a three trophic-level system involving a prey, a venomous consumer, and a predator.

Parameter Description

Rt Prey species population density at time t.

Ct Consumer species population density at time t.

Pt Predator species population density at time t.

vR Prey susceptibility to the offensive venom of the venomous

consumer (higher values results in higher predation rate).

v1 Offensive trait (venom) of the venomous consumer (higher values

results in higher predation rate).

v2 Defensive trait (venom) of the venomous consumer (higher values

results in higher success rate by top predator).

vP Predator susceptibility to the offensive venom of the venomous

consumer (higher values results in higher predation rate of the

consumer).

r0 Prey intrinsic rate of increase.

f Fitness cost of venom susceptibility in the prey species (investing in

lower susceptibility to venom is more costly).

m0 Venomous consumer base mortality rate (due to density-independent

effects).

g1 Fitness cost of offensive venom in venomous consumer (investing

more in offensive venom is more costly).

g2 Fitness cost of defensive venom in venomous consumer (investing

more in offensive venom is more costly).

rP0 Predator intrinsic rate of increase.

k Carrying capacity of the predator population.

mP,0 Predator base mortality rate (due to density-independent effects).

gP Fitness cost of venom susceptibility in the predator species (investing

in lower susceptibility to venom is more costly).

c Base conversion rate of eaten prey into new venomous consumers.

cP Base conversion rate of eaten venomous consumers into new

predators.

a1 Baseline attack rate of the venomous consumer, quantifying

searching efficiency for prey.

a2 Baseline attack rate of the predator, quantifying searching efficiency

for venomous consumers.

37

Table 2: Description of functions used in model equations describing change in population densities

for a three trophic-level system involving a prey, a venomous consumer, and a predator.

Function Description

rR(r0,vR) = Rv

fr0

Population growth of the prey species. Large values

are given by high intrinsic rates of increase, high

susceptibility to venom, and small fitness cost of

venom susceptibility.

q1(v1, vR) = )1(1

1

Rvvea

Predation rate of the prey species by the venomous

consumer. Large values are given when offensive

venom investment, prey susceptibility, and baseline

consumer attack rate are higher.

m(v1, v2) =

22110vgvgm

Density-independent consumer mortality. Increases

with base mortality rate, cost of offensive and

defensive venoms, and investment in offensive and

defensive venoms.

q2(v2) = Pvv

Pea2

2 Predation rate of the consumer species by the

predator. Decreases when defensive venom

investment is higher, and predator susceptibility and

baseline predator attack rate are lower.

rP(P) = )1(0 tP

kPr Population growth of the predator species on

alternative food sources. Higher values are driven by

higher predator intrinsic rate of increase and carrying

capacity.

mP = P

P

P v

gm

0, Density independent predator mortality. Increases

with predator base mortality rate and susceptibility to

venom, and decreases with the increased cost of

venom susceptibility.

The changes in traits for the prey (i.e., prey susceptibility) and consumer (i.e.,

offensive and defensive venom investment) at each time step are then determined by

the population’s genetic variance and mean fitness, as well as the derivative of mean

fitness with respect to the trait. If Fi is the mean fitness for species i, and VR, VC1 and

VC2 are additive genetic variance for prey susceptibility vC, consumer offensive

venom v1, and consumer defensive venom v2, respectively, then co-evolution of these

traits is given by the following derivatives (Equations 2.2):

R

vv

t

R

RR

R

R

R

RR VeCavv

fvV

v

F

Fvv R

ttt)(

11

1 112

11111

1

11 )(1

1

1 C

vv

tRC

C

C

C

VgeRcavvVv

F

Fvv R

tttt

38

22222

2

22 )(1

1 CtPC

C

C

C

VgPqvvVv

F

Fvv

ttt

For our simulations predator venom susceptibility was considered a constant that

does not co-evolve. We made additional assumptions in our model as per the

assumptions presented by Northfield and Ives (2013). Firstly, although spatial

structure may influence predator-prey interactions and give rise to a geographic

mosaic of co-evolution, we assumed that each species was represented by a single,

panmictic population to focus on local adaptation. We used a quantitative genetics

approach and held the additive genetic variance of the traits constant, so that the rate

of evolution depended on the strength of selection. Although this assumption doesn’t

hold true in the long term (without mutations to maintain genetic variation), under

very strong selection (resulting in loss of genetic variation, and for small populations

(which lack large initial genetic variation and are affected by genetic drift), we

believe this approach provides a reasonable starting point to investigate the short-

term (hundreds of generations) effects of changing ecological interactions.

Model analysis and results

Prey-driven arms races typically give rise to reciprocal co-evolution, while predator-

driven arms races typically result in escalation whereby prey evolution is driven by a

predatory pressure, but predator evolution is not driven by a reciprocal pressure from

its prey (Dietl and Kelley 2002). To investigate the bottom-up and top-down effects

on venom of manipulating predator-prey interactions, we conducted two sets of

simulations. For each of these simulations, we assumed that all of the populations

began at eco-evolutionary equilibrium, with identical genetic variances for the co-

evolving prey and venomous consumer. In the first type of simulation, we changed

39

prey density by increasing prey intrinsic rate of increase r0. In the second type, we

changed top-predator density by increasing top-predator carrying capacity k. After

altering these ecological parameters, to find the equilibriums we simulated the

models for an additional 5000 generations to allow population densities and trait

values to stabilize (Figure 1). We tracked the trajectories of population densities and

traits as the parameters r0 and k increased. We ran the simulations with a range of

starting population density and trait values to evaluate the potential for alternative

stable states. Although alternative stable states were found for certain parameter

values, they did not qualitatively change the results.

When prey density is increased through increases in the intrinsic growth rate,

consumer and apex predator densities also subsequently increase (Figure 1A). The

increased consumer density enhances selection pressure on the prey, which leads to

reduced susceptibility to consumer venom. This prey trait change stimulates the

consumer species to invest more in venom production to compensate for the reduced

susceptibility. In response to higher densities of the apex predator, the venomous

consumer also increases investment in defensive venom to mitigate mortality due to

increasing top-predator density (Figure 1C).

40

Figure 1: Equilibrium population densities and traits. Equilibrium population densities (A, B) and

trait values (C, D) under changing bottom-up (prey growth rate) conditions (A, C) and top-down

(top-predator carrying-capacity) conditions (B, D). Red lines represent venomous consumer density

(A, B) and offensive and defensive venom investment (C, D. Solid and dashed lines, respectively).

The solid blue lines represent co-evolving prey density (A, B) and susceptibility to the offensive

venom trait (C, D). The dotted black line represents generalist, non-co-evolving top-predator density

(A, B). For changing prey growth rate, top-predator carrying-capacity k=0.015 was used. For

changing top-predator carrying capacity, the prey growth-rate r0 = 0.5 was used. For both

simulations, the parameters used were rP = 0.01, vR = 0.4, v1 = 0.3, v2 = 0.1, vR = 0.4, m0 = 0.05, mP0 =

0.01, a1 = 4, a2 = 3, c0 = cP = 0.25, f = 0.07, g1 = g2 = 0.02, gP = 0.005, Vn = V1 = V2 = VP = 1.

When the apex predator carrying capacity increases, higher apex predator densities

apply a stronger selection pressure for defence on the consumer and defensive venom

41

investment increases in the consumer species. Elevated mortality due to predation

reduces consumer density, resulting in a trophic cascade (Figure 1B). Consequently,

the prey experience less pressure from predation, and the co-evolutionary arms race

between the consumer and prey diminishes. The reduced consumer density results in

increased prey susceptibility, and reduced offensive venom in the consumer (Figure

1D).

Experimental materials and methods

Study organism

Loicheles waigienis is a rainforest scorpion found along the east coast of Australia,

South-East Asia, and the Pacific (Koch 1977). In the Wet Tropics of Far North

Queensland, L. waigiensis is a generalist predator of invertebrates, including crickets,

and is in turn preyed upon by a range of invertebrate and vertebrate (marsupial)

predators (Schneider 2011). Scorpions exhibit an inverse relationship between the

relative sizes of the pincers (chelae) and stinger (telson), and generally prefer to rely

upon the larger weapon for prey-capture and defence (van der Meijden et al. 2013).

L. waigiensis possesses relatively large, robust chelae and a small telson (Isbister et

al. 2004; Jeliffe 2010; Koch 1977). This ecomorphotype is consistent with other

members of Hemiscorpiidae (formerly Ischnuridae and Liochelidae) (van der

Meijden et al. 2013).

Experimental treatments

To subject scorpions to both offensive and defensive pressures (manipulated

ecological interactions) and elicit a plastic response, we used a 2 × 2 factorial design

with a prey treatment to provide an offensive pressure in one factor, and a predatory

42

treatment to provide an offensive pressure in the other. Each factor contained two

levels, which either attempted to provoke a sting (venom use) or not provoke a sting.

Thus, the treatments were live prey with predation (offensive and defensive

pressures), live prey without predation (offensive pressure), dead prey with predation

(defensive pressure), and dead prey without predation (control). Previous work has

shown that L. waigiensis produces different toxins that can target vertebrate and

invertebrate biochemistry (Schneider 2011). Because L. waigiensis preys upon many

insects, including crickets (Schneider 2011), and because they were readily available,

we used the common house cricket (Acheta domesticus) as a surrogate prey species.

Similarly, L waigiensis is preyed upon by a variety of marsupials including

bandicoots, white-tailed rats, and Antechinus sp. (Seymour, unpublished data). We

used a stuffed mouse (Mus musculus) to elicit anti-predator responses in a similar

fashion to the ‘predator-on-a-stick’ method from Ramirez et al. (2010). Taxidermied

predators, including vertebrate predators, have been widely used in other studies of

prey behaviour (e.g. Digweed & Rendall 2009). Due to the small number of males (N

= 6), 4 males were picked at random and evenly dispersed between the four

treatments. The remaining 2 males were then randomly dispersed, to one treatment

each, for a total of 16 replicates per treatment. All other individuals in the experiment

were females (N = 58).

Previous studies investigating the venom regeneration in this species have shown that

L. waigiensis recovers a mature venom profile within 21 days of complete depletion

of the venom glands via electrostimulation (Jeliffe 2010; Schneider 2011). Thus, we

ran the treatments for 42 days so that the experiments lasted twice as long as the

venom regeneration time. By providing the scorpions with the full length of time

43

necessary to regenerate their venoms, we ensured that comparisons between

experimental treatments could detect differences in the complete, mature venom.

Although no ontogenic or sexual variation has been previously detected in the venom

profiles of L. waigiensis (Schneider 2011), we used mature scorpions only.

For the prey treatment, scorpions were each fed a cricket once per week (6 feedings

over 6 weeks). ‘Live prey’ scorpions were given a cricket that was larger than their

chelae size, as larger prey are more likely to be stung during prey-capture (Edmunds

and Sibly 2010). Crickets for ‘dead prey’ scorpions were frozen overnight before

feeding, to minimize loss of nutritional value. Cricket remains were removed the

following day to reduce fungal growth.

Our taxidermied mouse was used to provoke defensive stings from ‘predation’

scorpions three times a week (Monday, Wednesday, and Friday) for weeks 2-6, with

a one week acclimation period (15 treatments total per individual over 5 weeks).

Scorpion containers were placed within a 33 cm × 17 cm × 10 cm cardboard arena to

prevent animals from escaping, and animals were exposed without making direct

contact to avoid prematurely eliciting defensive behaviour. The mouse was then

continuously jabbed at the cephalothorax of the scorpions for 30 seconds, which

readily stimulated scorpion anti-predator responses, including alert and threat

postures (with chelae extended and open, and metasoma erect), grappling, pinching,

stinging, squirming, and retreat (van der Meijden et al. 2013; Warburg 1998).

Animals that escaped into the ‘arena’ were immediately returned to their container

with forceps and the treatment resumed. The mouse was cleaned of dirt between each

treatment to prevent the spread of mould. ‘Without predation’ scorpions were placed

44

in the arena and their containers opened for 30 seconds. This ensured that animals in

both treatments were handled and exposed to laboratory conditions outside their

growth chambers equally. Six weeks after commencement of the experiment,

scorpions were subjected to the control (dead prey without predation) treatment for

one week prior to re-milking to allow them time to recover a significant quantity of

mature venom.

Collection and housing

Individual Liocheles waigiensis, were collected from rainforest populations at

Crystal Cascades (16°57'43.1"S 145°40'46.9"E), Cairns, Queensland, Australia,

between 26th

and 30th

of March, 2014. Mature scorpions were collected, based on

cephalothorax shape and size, and sex was determined according to the presence

(males) or absence (females) of a distinctive notch in the chelae (Koch 1977).

Following Schneider (2011), we used this feature to identify the smallest mature

male in our collection and designated all smaller scorpions as juveniles (and

excluded them from the experiment) and larger scorpions without a notch as mature

females. Scorpions were then individually held in 170 × 110 × 50 mm 650 ml clear

plastic takeaway containers with one stone and moist organic soil (300 ml Searles

Premium Potting Mix brand potting mix) to provide a suitable microclimate for the

animal and to aid with moulting. These containers were randomly sorted and stacked

two high, in two Wisecube WGC-450 temperature and humidity chambers at 28 ⁰C

on a 14/10 light/dark cycle. Relative humidity was maintained at 70%, and after 3

weeks of treatments all scorpions were moved to new containers containing freshly

autoclaved soil to reduce fungal growth.

45

Choice of milking method

Repeated milking by electrostimulation can cause the venom apparatus to degrade in

a range of venomous taxa including some scorpions, compromising venom yield

(Cooper et al. 2014). However, previous work indicates that this is not the case for L.

waigiensis (Schneider 2011). It has also been proposed that electrostimulation may

contaminate venom samples with hemolymph or cellular contents (Oukkache et al.

2013). We found no evidence for this with L. waigiensis (Figure 2), and manual

milking produced inadequate volumes for chemical analysis of venom.

Electrostimulation is assumed to expel all venom material (Morgenstern and King

2013), and in scorpions may therefore elicit mixture of both prevenom and main

venom.

To evaluate whether or not milking method had an effect upon the venom profile

obtained from L. waigiensis we milked 4 scorpions with electrostimulation and 5

scorpions manually. Manual milking was carried out by dorsally poking the

scorpions to provoke stings to a triangular wire frame wrapped with Parafilm.

Droplets of venom were then collected and diluted in 10 µL of deionised water.

Following Schneider (2011), electrostimulation was performed using an Arthur H.

Thomas Co. Z789 Square Wave Stimulator. Frequency, duration, pulse mode, and

output mode were 5.5 pulses/sec, 15 milliseconds, ‘continuous’, and ‘+ monophasic’,

respectively. Scorpions were secured to a block of foam with a heavy-duty rubber

band, and a pair of electrodes wetted with saline solution were placed into contact

with opposing sides of the telson. A 20V stimulus was then applied, which was

gradually increased to up to 30V until venom was exuded. The venom was captured

with a micropipette tip slipped over the aculeus until no more venom was released

46

Figure 2: Reversed-phase venom profile obtained via electrostimulation (green chromatogram)

and manual milking (blue chromatogram) from the same individual. These venom profiles were

typical of the data we obtained to compare milking methods. Identical peaks aligned along the x-

axis, indicating the presence of the same venom components. The elution time and relative heights

of peaks in the profiles closely matched with the exception of the very first peak, although

concentrations were lower due to a smaller volume of venom obtained via manual milking.

and then mixed with 10 µL of deionised water. Following milking, the scorpions

were then fed a dead cricket, and subsequently fed each week for 3 weeks. They

were then each re-milked with the alternative milking method (i.e. manual, for

scorpions previously electrostimulated).

Venom samples were analysed using reversed-phase HPLC on a 1% gradient of 90%

acetonitrile/ 0.45% TFA at 0.4 mL/min using a Phenomonex C12 150 x 2 mm Jupiter

4µm Proteo 90Å column. We compared the venom profiles of individual animals

milked both manually and using electrostimulation and determined that the milking

method did not have a substantial effect upon the extracted venom composition.

Therefore, we used electrostimulation in order to maximize sample volumes for

47

optimal signal in the chemical analysis of venom composition in each of the

treatments.

Venom milking

Electrostimulation was used to obtain venom samples, which were then stored and

frozen at -80 ⁰C. After initial venom samples were collected and animals that did not

secrete venom excluded, individual scorpions were randomly, evenly assigned to one

of four treatments. Scorpions were first milked within 5 days of collection, and then

re-milked at the end of the experiment, 42 days later. All scorpions were then milked

a third time 21 days after the experimental treatments ceased to assess how it had

changed in the absence of offensive and defensive pressures.

Fast protein liquid chromatography (FPLC) venom analysis

Milked venoms were diluted in 150 µL of degassed 50% phosphate buffered solution

(PBS), centrifuged for 10 minutes total at 32,000 RPM, and filtered through a

syringe-driven 0.22 µm Millipore filter. Venom profiles were obtained using size-

exclusion fast protein liquid chromatograpy (FPLC) using a Superdex™ 75 10/300

(Tricorn) GL Column (13µm, 10mm×300mm) with PBS buffer at 0.50 ml/minute for

45 mL on an ÄKTA™ FPLC. Venom contents were detected at a wavelength of 280

nm. Fractions were collected every 0.5 mL in 96 well plates and stored at 4ºC.

Venom profiles were then processed and exported using UNICORN™ 5.20 software

(2008, General Electric Company, General Healthcare Bio -Sciences AB, Sweden).

48

Statistical analysis

All analyses were performed in R (R Development Core Team 2014). In order to

compare between the venom profiles obtained in each treatment, we standardised

each FPLC chromatogram by dividing the intensity of each data point in a

chromatogram by the sum of all the data points for that chromatogram (the Riemann

sum), thereby normalizing every chromatogram so that the integral for each

chromatogram is equal to 1 (Sauve and Speed 2004). We then obtained the mean

chromatogram for each of the four treatments. This allowed us to compare relative

quantities of venom material in different parts of the venom profile, between

treatments. We removed four scorpions from the analysis, two of which gave rise to

chromatograms with a very poor signal-to-noise ratio, indicating low venom

concentrations. This may have been due to damage to the venom-producing glands of

these individuals, either as a result of electrostimulation or due to injury in the wild.

The other two scorpions were excluded due to highly atypical venom profiles,

suggesting that the venom samples were contaminated.

To delimit and evaluate the distinct fractions present in scorpion venom profiles, we

generated a mean chromatogram from all normalized chromatograms from the post-

treatment milking and fitted a spline curve to the entire chromatogram using the

smooth.spline function in R, with the smoothing parameter, λ = 0.5 (R Development

Core Team 2014; Wehrens 2011). Fractions were then separated by local minima to

generate 11 fractions (Wehrens 2011), ignoring the first and final fractions as they

contained only noise (Appendix I, see Figure 3). Principle component analysis (PCA)

was then used to describe these 11 fractions across the data set (Wehrens 2011).

49

Finally, MANOVAs and ANOVAs were performed to evaluate treatment effects on

the principle components using type III sums of squares (Gotelli and Ellison 2004).

Experimental results

From the principle component analysis we obtained two major principal components,

PC1 and PC2, which explained 50% and 27% of the overall variability, respectively.

Venom profiles obtained from the mouse (defensive pressure, N=27) and non-mouse

(no defensive pressure, N=25) treatments were found to be significantly different

using a MANOVA to evaluate the treatments on the principal component weightings

(F1,48 = 0.237, p = 0.002; Figure 3; Figure 4; Table 2).

Elution volume (mL) elution time

N

orm

alis

ed

mill

iab

sorb

ance

(2

80

nm

)

(n=14)

(n=13)

(n=11)

(n=14)

50

Figure 3: Comparison of post-experiment venom profiles. Because these represent the averaged,

normalized venom profiles for each treatment, the response variable is normalized milliabsorbance

units, and indicate relative quantity between any given portion of the mean of the venom profiles of

each treatment. Venom contents were detected at 280 nm. Defensive treatments are indicated in dark

and light blue, while the non-defensive treatments are shown in orange and red.

Examination of the ordination graphs suggests clustering for the predator treatment

(Figure 4A). There were no interaction effects overall, nor any significant effects

from the live versus dead prey treatments. Scorpions for which anti-predator

stimulation was induced exhibited lower values of both PC1 (F1,48 = 6.42, p = 0.014)

and PC2 (F1,48 = 6.66, p = 0.013)(Table 3). Peak 10 strongly increased each principle

component (Figure 4B), where as peaks 6,7, and 9 reduced the values for both

(Figure 4B). Peaks 2 and 5 each had different effects on the two principle

-0.15 -0.05 0.05 0.15

-0.1

00

.00

0.0

50

.10

0.1

5

PC1 (50%)

PC

2 (

27

%)

A

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

PC1

PC

2

B

1

2

3

4

5

67

89

10

11

Figure 4: Sample values (A) and priniciple component loadings for peaks 1-11 (B) describing the

venom profiles of the experimental scorpions. Defensive treatments are indicated in dark (live

prey) and light (dead prey) blue, while the non-defensive treatments are shown in red (live prey)

and orange (dead prey). The principle components were developed from the, 11 distinct fractions

fitted to the mean chromatogram obtained from all of the individual chromatograms. The two

main principal components (ANOVAs), PC1 and PC2, described 50% and 27% of the overall

variation, respectively.

51

components (Figure 4B). There were no interaction effects, nor any significant

effects from the live versus dead prey treatments. Furthermore, profiles obtained

after a 21 day recovery period following cession of treatments exhibited the same

patterns of difference between treatments as seen in Figure 3, but these differences

were not statistically significant (Appendix I). Lastly, the venom profiles obtained

from milking before the experimental treatments began were not significantly

different from each other (Appendix I).

Table 3: MANOVA results, which demonstrated a significant overall difference between the

fraction loadings of predator and without-predator treatments. There was no interaction effect.

Source d.f. Pillai approx F Df den P

1. 2.

Prey 1 0.028 0.698 2, 47 0.503

Predator 1 0.236 7.395 2, 47 0.002**

Predator

✕Prey 1 0.029 0.702

2, 47 0.501

Residuals 48

Table 4: ANOVA results, which demonstrated significantly different fraction loadings between the

predator treatments compared to the without-predator treatments along both PC1 and PC2. There were

no interaction effects.

Source d.f. MSE F P

PC 1

Prey 1 0.008 1.385 0.245

Predator 1 0.038 6.522 0.014*

Predator ✕Prey 1 0.001 0.203 0.654

Residuals 48 0.006

PC 2

Prey 1 0.000 0.124 0.727

Predator 1 0.021 6.626 0.013*

Predator ✕Prey 1 0.004 1.336 0.254

Residuals 48 0.003

52

Discussion

In this study we have shown adaptive plasticity in the venom profile of a venomous

animal for the first time, to our knowledge. To understand and generate hypotheses

about how predator-prey interactions might influence offensive and defensive venom

production, we modelled eco-evolutionary dynamics in a three trophic-level

predator-prey system with a venomous consumer. In doing so, we found that

increasing predatory pressure would diminish a co-evolutionary arms race between

the consumer and its prey, while increasing defence. We also found that

independently increasing prey abundance would enhance the escalation of the arms

race. We then evaluated whether the direction of plastic change in offensive and

defensive venom components would be the same as expected from evolutionary

modelling. In doing so, we identified an induced plastic defence in a venomous

animal due to a predatory pressure that was consistent with our modelling.

Defensive venom

Our experimental results supported our modelling, which suggested that increasing

predatory pressure in the presence of consumer-prey co-evolution would diminish

the arms race between the consumer and prey. We have found evidence for adaptive

plasticity to predatory pressures in venom composition, whereby increasing pressure

for defence modifies venom composition to likely enhance venom components that

are associated with defensive interactions. This was consistent with our expectation

that a plastic response to this pressure would occur in the same direction as an

evolutionary response. Venom profiles obtained three weeks after the cessation of

experimental treatments sustained the general patterns of compositional change

observed in the profiles obtained at the end of the experiment. However, these

53

patterns had diminished and were no longer statistically significant in the absence of

a predatory pressure, suggesting that periods of relaxed selection pressure can return

scorpion venom to its original state.

A plastic response to predator exposure, which enhances toxicity towards that

predator, would be consistent with the venom optimisation hypothesis. The

optimisation hypothesis proposes that venomous animals must employ a range of

strategies to reduce the waste of their costly venom (Morgenstern and King 2013). A

plastic increase in vertebrate toxicity towards predators on a per-volume basis of

venom would improve the efficiency of venom-use, by demanding smaller injection

volumes in order to effectively deter a potential threat (Casewell et al. 2013). Indeed,

this same strategy is seen in venomous animals as an evolutionary response in prey-

capture contexts (Richards et al. 2012).

In addition to this strategy for optimising the use of defensive venom, L. waigiensis

is likely to partition its venom into at least two separate secretions – a cost-effective

prevenom and a ‘main’ venom. When milking L. waigiensis, we observed the same

succession of clear (prevenom) to milky (main venom) secretions, as has been

reported in other scorpion species (Gopalakrishnakone et al. 1995; Inceoglu et al.

2003; Nisani et al. 2012; Yahel-Niv and Zlotkin 1979). Studies of venom

regeneration in other scorpions have shown that prevenom toxins regenerate

substantially faster than main venom toxins (Nisani and Hayes 2011). Previous work

investigating regenerated venom profiles in L. waigiensis indicates that fractions 1

and 2 rapidly replenish only 1 day after milking, compared to 21 days for fractions 3-

11, and are therefore likely to constitute the prevenom (Schneider 2011). Our results

54

suggest that both fractions 1 and 2 increased in response to the predation treatment,

in addition to fractions 7, 8, and 9, while fractions 4, 5, and 10 decreased. Thus, it

would appear that L. waigiensis reduces its relative investment in particular main

venom components in order to increase the relative production of both prevenom and

defensive main venom toxins in response to a predatory pressure. Prevenom in the

dark scorpion P. transvaalicus was found to be chemically cheaper to produce,

containing K+ ions and simpler, shorter peptide chains compared to the larger

neurotoxins in the main venom (Inceoglu et al. 2003; Nisani et al. 2012). Inceoglu et

al. (2003) concluded that prevenom is likely to be used as a rapidly-recovering

warning-shot to cheaply deter threats with immediate, localized pain, before

resorting to main venom, as well as acting as a less-effective ‘back-up’ venom to

capture invertebrate prey when the main venom is depleted. Given its low cost and

rapid regeneration, induced investment in prevenom by L. waigiensis may be

indicative of a strategy to cope with a more uncertain, hostile environment.

Offensive venom

From our modelling results we hypothesized that the arms race between a venomous

consumer and its co-evolving prey would be enhanced. In contrast to our results for a

defence-inducing pressure, we did not observe a plastic increase in offensive venom

investment in response to our live prey treatment. Broadly speaking, the inability of

the live prey treatment to induce offensive-investment could have been due to

inadequate pressure to overcome the venom resistance of the model prey, or due to

an inability to plastically respond to prey resistance with an induced venom

investment. But given the plasticity observed from the defensive treatment, a

physiological inability to respond to any resistance pressure to venom resistance in

55

prey is unlikely. Instead, an inadequate (or entirely absent) pressure was likely

responsible, due to characteristics of both L. waigiensis and the model prey, which

could be taken into consideration for future studies.

Although theoretical studies have suggested that plastic phenotypic change should be

a good predictor of the direction of evolutionary change, empirical studies have also

shown that this is not necessarily always the case (Schaum and Collins 2014).

Furthermore, we did not model the eco-evolutionary effects of environmental

stochasticity to hypothesize the effects of increasing offensive pressure. When traits

respond to a selective pressure, evolution balances this response between optimising

the trait for the maximum fitness benefit, and over-investing in the trait to

compensate for the effect of environmental stochasticity to avoid extremely low

fitness (Rosenheim 2011). Such ‘bet hedging’ strategies are ubiquitous (Beaumont et

al. 2009), and are also observed in venomous animals. For example, snakes will

‘overkill’ flying prey to ensure a meal, injecting quantities greatly in excess median

lethal doses (LD50 value) in order to guarantee that their prey cannot fly away

(Hayes 1992). Similarly, in times of prey scarcity where scavenging becomes an

alternative foraging strategy, or in the presence of an alternate prey which doesn’t

require stinging to be subdued, it may be favourable to continue producing costly

venom even in the absence of live prey to ensure success in future opportunities to

catch a meal. Thus, bet hedging may have been responsible for a lack of plastic

response in venom composition due to the prey treatments.

We observed scorpions both stinging their prey and subduing the crickets with their

pincers alone. Thus, our venomous animal may have had a low preference for

56

stinging the prey used in our experiment. If this were the case then we might have

expected venom profiles from naive, freshly-captured scorpions to differ from those

after the treatments, where they were only fed crickets (and did not consistently need

to sting to subdue their prey). Our data appear consistent with this expectation. The

propensity to use venom in any given interaction is a property of both the venomous

animal and its prey (or threat), and is influenced by a wide range of factors of each

(for a review, see Morgernstern and King (2013). Previous studies have shown an

inverse relationship between pincer and stinger size in scorpions, and that scorpions

prefer to use their larger weapon in both offensive and defensive encounters

(Edmunds and Sibly 2010; van der Meijden et al. 2013). L. waigiensis has relatively

larger pincers than its metasoma and indeed, the scorpions were sometimes observed

catching and killing live crickets with their pincers alone. Although we anticipated

and attempted to mitigate this effect by feeding prey larger than the pincers, which

increases preference for envenomation to subdue prey in other scorpions (Edmunds

and Sibly 2010), it is possible that these crickets were still too small to reliably

provoke stinging (personal observation).

In sum, it remains unclear as to whether or not the lack of a plastic response in the

offensive venom of L. waigiensis was due to an inadequate pressure, due to a

preference by the scorpion to subdue its prey with pincers, or both. While the

availability of important ecological and toxicological information made L. waigiensis

a highly suitable model organism for our study, future work could better elucidate

the relationship between prey-capture and offensive venom by using a model

venomous animal which more readily relies upon venom to subdue prey, and a more

resistant model prey (such as cockroaches, e.g. Hostettler & Nentwig 2006) or even

57

natural prey. A longer study may be able to observe a delayed plastic response, and

the collection of milked venom volume data would enable the detection of any

changes in absolute volumes, whereby a decrease in absolute venom volumes would

indicate a plastic response to mitigate the costs of venom production.

Implications of plasticity

The capacity for plasticity in a given trait is – itself – a trait that is selected for, and

presents interesting ecological and evolutionary implications. Plasticity is favourable

in highly variable or cyclic environments where the fitness benefits of the phenotypic

flexibility it bestows outweigh the cost of maintaining this capacity for variability

(Svanbäck et al. 2009). Plasticity would therefore enable a venomous animal to

minimize the production of costly venom between fluctuations in predator densities

or alternate prey with variable venom resistance. By comparing the lower-resolution

venom profile of L. waigiensis obtained from FPLC (Figure 3) to the higher-

resolution venom profile obtained from HPLC (Figure 2) it is clear that only a subset

of the peptides present in the venom have been increased or decreased in response to

a predatory pressure. Venomous animals evolve vast, complex armouries of peptides

and proteins in their venoms (Morgenstern and King 2013), and it would appear that

from its armoury of at least 40 different peptides L. waigiensis is able to modify the

production of small subset of these to suit a changing environment. Such a cost-

effective strategy would be consistent with the venom optimisation hypothesis, and

the magnitude of the pressure to minimize venom cost and the predatory pressure

may relate to how closely venom production tracks the rate of ecological dynamics.

Indeed, we found that the difference in venom profiles between predatory and non-

58

predatory treatments had noticeably diminished three weeks after the conclusion of

the experiment (Appendix I).

Thus, our findings suggest that L. waigiensis experiences sufficient variability in

predator density in its natural environment to select for venom plasticity. In addition

to the benefits for economical venom production, an induced plastic defence could

stabilize venomous animal populations against fluctuating predatory pressures,

stabilizing food webs (Cortez 2011). If more widespread in other venomous animals,

this could present a potent stabilizing force in ecological communities by

diminishing trophic cascades. Confronted with additional environmental pressures,

such as climate change and invasive species, adaptive plasticity can mitigate the

effects of these strong selective pressures on populations of venomous animals by

allowing more time for evolutionary adaptation and reducing the amount of

evolutionary change necessary to track a moving optimal trade-off between the costs

and benefits of venom production (Reed et al. 2011). Indeed, populations which

exhibit greater phenotypic plasticity can evolve more under global change and

thereby adapt to changing environments (Schaum and Collins 2014).

Applications and future directions

Venom research has historically been intently focused on human toxicity (Fry et al.

2009). The ecological and evolutionary perspectives that have been increasingly

explored, particularly in the last decade, offer critical insights that has improved

health outcomes as well as enriched our understanding of venom-use and production.

Indeed, if plastic responses are widespread in the other venomous animals,

antivenom production could be improved by accounting for this potential source of

59

variation (Richards et al. 2012). The potential role of venom in structuring and

stabilising ecological dynamics needs to be further explored and may be substantial.

For example, scorpions provide a major food resource in some ecological

communities (Polis 1990). Corroborating previous work (Casewell et al. 2013), our

modelling suggests that venomous animals and their predators and prey may provide

new insights into evolutionary arms races arising from both reciprocal co-evolution

and predator-driven escalation (Dietl and Kelley 2002). Finally, the evidence that

we’ve found for rapid trait change and adaptive plasticity in venomous animals may

present new opportunities for the empirical study of eco-evolutionary dynamics

using venomous animals as a model system.

60

3.

Target journal: American Naturalist

61

Abstract Though pairwise co-evolution has received more attention due to

analytical simplicity, organisms embedded within multi-trophic food webs need to

balance two general arms races, between their predators and their prey. Here, we use

a simple co-evolutionary model to evaluate the evolutionary response of a venomous

consumer co-evolution of its prey and the presence of an apex generalist predator.

We assume that consumers can develop venoms for prey capture and predator-

deterrence that can functionally overlap. Predator introduction promotes investment

in either defensive or offensive consumer venoms, or both. The investment type

depends on the effectiveness of offensive venom for predator-deterrence, and the

relative cost associated with investing in multiple venoms. Furthermore, the

evolutionary response of prey species to apex-predator-induced reductions in

consumer densities can promote evolution of a novel consumer anti-predator venom.

These dynamics suggest that interactions with other species can substantially alter

the venom complexity in predatory venomous animals.

Introduction

Balancing consumer-prey and consumer-predator arms races

Arms races between predatory and anti-predatory traits are likely to emerge when an

organism has an enemy that is capable of an evolutionary response (Dercole et al.

2010). Indeed, arms races may be of sufficiently widespread importance to shape the

evolution of consumer-prey interactions along all phylogenetic branches of the tree

of life (Dietl and Kelley 2002). Although consumer species are typically embedded

within food webs, there has been an historical emphasis on pairwise interactions in

theoretical and empirical studies of evolutionary arms races (Mougi and Nishimura

2009). Pairwise models offer the convenience of analytical simplicity (Mougi and

62

Nishimura 2009). However, paleontological and phylogenetic analyses have

accumulated evidence for the important role of three trophic-level interactions in co-

evolution (Currie et al. 2003; Dietl and Kelley 2002). Furthermore, the small but

growing body of studies of tri-trophic systems have shown that extending beyond

pairwise interactions can reveal novel processes and dynamics which are often not

intuitive (Abrams 1991; Dercole et al. 2010). Thus, there is a need for further

investigations of the evolutionary processes that govern arms races in a multi-trophic

level context (Dietl and Kelley 2002).

Arms races in venomous animals

Arms races involving predatory and anti-predator traits are ubiquitous in food webs

(Wade 2007), and are seen in venomous predator-prey systems (Casewell et al.

2013). Although studies have typically focused upon venom production as an

offensive adaptation for prey capture, venomous consumers may also co-evolve with

their predators (Casewell et al. 2013; Jansa and Voss 2011), and therefore need to

balance the costs and benefits of these offensive and defensive arms races.

Scorpions, for example, are prey for many species (Castilla et al. 2014; Polis 1991),

and may provide an important food prey in some habitats (van der Meijden et al.

2013). Indeed, venom provides venomous animals with one of the basic requirements

for the emergence of co-evolutionary arms races – an effective defensive or offensive

weapon, which incurs a potentially steep allocation cost and therefore requires fitness

tradeoffs to produce (Dietl and Kelley 2002; McCue 2006; Nisani et al. 2012; Nisani

et al. 2007; Pintor et al. 2010). How consumers, including venomous consumers,

balance the costs and benefits associated with predatory and anti-predator traits in

63

these arms races can be better understood by examining arms races in other predator-

prey systems and by using theoretical modelling (Abrams 2000).

Offensive and defensive venoms and statement of aims

Venomous animals must balance arms races between predators and prey with toxins

that exhibit toxicity towards both predators and prey. Some traits which aid prey-

capture, such as crab claws, can also be used for defence (Abrams 1991), and the

same is true for venom toxins. Because some venom toxins act upon biochemical

processes which are highly conserved across all of Anamalia (Fry et al. 2009), the

same toxins can function both in offensive and defensive contexts. For example,

there are three sub-groups of scorpion α-toxins. One exhibits activity towards insect

voltage-gated sodium channels (VGSCs) only, another towards mammalian VGSCs

only, and the third contains toxins that are active against both insects and mammals

(Quintero-Hernández et al. 2013). Though most are considered to be generalist

predators, spiders can produce a suite of both general toxins and phyla-specific

toxins to predate upon specific groups of insects (Kuhn-Nentwig et al. 2011;

Nicholson 2007). Conversely, the evolution of discretely different offensive and

defensive venoms has been recently shown in Conus (Dutertre et al. 2014).

Scorpions secrete a chemically cheap ‘prevenom’ for use in low-threat agonistic

interactions before resorting to the more chemically complex and costly main venom

(Inceoglu et al. 2003). Thus, venomous animals appear to vary in the extent to which

they can function with either two distinctly different offensive and defensive

venoms, or with a more functionally versatile single venom that can be used in both

prey-capture and predatory contexts.

64

Given the likely importance of arms races in venom evolution and the paucity of

studies addressing the potential need for venomous animals to balance prey and

predator arms races, we sought to investigate the effects of co-evolution on venom

production in a venomous consumer embedded in a tri-trophic chain. We use

theoretical models to evaluate how venomous animals may balance these two general

arms races with their predators and prey and to determine the circumstances under

which it would be preferable to evolve a separate defensive venom, rather than invest

more heavily in the venom used for prey capture.

Model Description

We use a trophic-level, discrete-time Lotka-Volterra model of co-evolutionary trait

change to investigate the evolution of two traits – offensive venom and defensive

venom – in a venomous consumer. The consumer feeds on a co-evolving prey, and is

itself preyed-upon by a generalist predator. Our model is an extension of the two

trophic-level model described by Northfield and Ives (2013). We re-parameterised

the model to suit venomous animals. Here, the venomous consumer has two traits

that correspond with two types of venom: offensive and defensive venom. Predation

of the prey by the consumer increases with the value of the offensive trait, whereas

predation of the consumer by the apex predator decreases with the value of the

defensive trait. Investing in each trait is associated with a cost administered to

consumer mortality.

We also include an additional fitness cost to produce two venoms, g3. This cost may

represent the additional cost associated with maintaining the physiological machinery

associated with producing two venom types, or super-additive metabolic costs

65

associated with producing two venom types. There have been relatively few studies

of venom costs (Morgenstern and King 2013). Investment in both offensive and

defensive venoms may be particularly costly due to the need to maintain specialised

structures and tissues to separately store or secrete two separate venoms, as in Conus

(Dutertre et al. 2014). We therefore considered the effects of including and excluding

g3 in our simulations. Venom toxins can exhibit general toxicity by attacking

biochemical targets that are conserved across Metazoans, or may be more specialized

(Dutertre et al. 2014). A prey-capture venom may also exhibit toxicity towards

predators. Furthermore, venom is typically considered to be driven by selection

pressures for offense (Casewell et al. 2013). Therefore we also include a measure of

the effectiveness of the prey-capture venom in deterring predators, M. We assume

the value of the parameter measuring this cross-effectiveness can range from 0 and 1,

with 0 representing no effectiveness of prey-capture venom at deterring predators,

and 1 representing the case where the offensive venom has equal effectiveness

against both prey and predators.

The changes in population densities of the prey (Rt), venomous consumer (Ct), and

predator (Pt) at time t are given by (Equations 3.1):

tRtRR CvvqRvrr

tt eRR),(),(

1110

ttR PvvqvvmRvvcq

tt eCC),(),(),(

12122111

PtPP mCvvqcPr

tt ePP),()(

1212

In the model we assume that consumer fitness is balanced by predation on the prey

species (where higher prey-capture venom investment increases predation rate),

density-dependent mortality due to predation by the predator (where higher anti-

66

predator venom reduces predation rates, as does higher prey-capture venom if M >

0), and mortality due to other density-independent effects (which increases with

investment in each venom). The prey species may mitigate mortality due to

consumer predation by investing in venom resistance (modelled as venom

‘susceptibility’, where lower susceptibility provides higher venom resistance), which

is balanced by a cost (modelled as density-independent mortality). Because we

modelled the predator as a generalist predator, its growth does not entirely depend on

preying on the consumer species. Rather, it has an alternative growth rate and

carrying capacity, and since the predator’s fitness is not tightly linked with the

defensive venom of the consumer, we assume that it does not co-evolve with the

consumer. The parameters and general functions used in the population density

expressions are presented in Table 1.

Table 1: Description of parameters and functions used in model equations describing change in

population densities for a three trophic-level system involving a prey, a venomous consumer, and a

predator.

Parameter Description

Rt Prey species population density at time t.

Ct Consumer species population density at time t.

Pt Predator species population density at time t.

vR Prey susceptibility to the prey-capture venom of the venomous

consumer (higher values results in higher predation rate).

v1 Prey-capture trait (venom) of the venomous consumer (higher values

results in higher predation rate).

v2 Anti-predator trait (venom) of the venomous consumer (higher values

results in higher predation rate by top predator).

vP1 Predator susceptibility to the anti-predator venom of the venomous

consumer (higher values results in higher predation rate of the

consumer).

vP2 Predator susceptibility to the prey-capture venom of the venomous

consumer (higher values results in higher predation rate of the

consumer, if M > 0).

M Effectiveness of prey-capture venom for defence (ranges from 0 to 1,

with 0 representing no effectiveness of prey-capture venom at

deterring predators).

67

r0 Prey intrinsic rate of increase.

f Fitness cost of venom susceptibility in the prey species (investing in

lower susceptibility to venom is more costly).

m0 Venomous consumer base mortality rate (due to density-independent

effects).

g1 Fitness cost of prey-capture venom in venomous consumer (investing

more in offensive venom is more costly).

g2 Fitness cost of anti-predator venom in venomous consumer (investing

more in offensive venom is more costly).

g3 Fitness cost of investing in two venoms in venomous consumer

(investing more in both venoms is more costly).

rP0 Predator intrinsic rate of increase.

k Carrying capacity of the predator population.

mP,0 Predator base mortality rate (due to density-independent effects).

gP1 Fitness cost of venom susceptibility in the predator species to the

anti-predator venom (investing in lower susceptibility to venom is

more costly).

gP2 Fitness cost of venom susceptibility in the predator species to the

prey-capture venom (investing in lower susceptibility to venom is

more costly).

c Base conversion rate of eaten prey into new venomous consumers.

cP Base conversion rate of eaten venomous consumers into new

predators.

a1 Baseline attack rate of the venomous consumer, quantifying

searching efficiency for prey.

a2 Baseline attack rate of the predator, quantifying searching efficiency

for venomous consumers.

Function Description

rR(r0,vR) = Rv

fr0

Population growth of the prey species. Large values are

given by high intrinsic rates of increase, high

susceptibility to venom, and small fitness cost of venom

susceptibility.

q1(v1, vR) = )1(1

1

Rvvea

Predation rate of the prey species by the venomous

consumer. Large values are given when prey-capture

venom investment, prey susceptibility, and baseline

consumer attack rate are higher.

m(v1, v2) =

21322110vvgvgvgm

Density-independent consumer mortality. Increases with

base mortality rate, cost of prey-capture, anti-predator,

and maintaining both venoms, and investment in prey-

capture and anti-predator venoms.

q2(v2) = 2112

2

PvMvPvvPea

Predation rate of the consumer species by the predator.

Decreases when anti-predator and prey-capture (if M >

0) venom investment is higher, and predator

susceptibility and baseline predator attack rate are

lower.

rP(P) = )1(0 tP

kPr Population growth of the predator species from

alternative food sources. Higher values are driven by

higher predator intrinsic rate of increase and carrying

capacity.

68

mP = 2

2

1

1

0,P

P

P

P

P v

g

v

gm

Density independent predator mortality. Increases with

predator base mortality rate and susceptibility to venom,

and decreases with the increased cost of venom

susceptibility.

The changes in traits for the prey (i.e., prey susceptibility) and consumer (i.e.,

offensive and defensive venom investment) at each time step are determined by the

population’s genetic variance and mean fitness, as well as the derivative of mean

fitness with respect to the trait. If Fi is the mean fitness for species i, and VR, V1 and

V2 are additive genetic variance for prey susceptibility vR, consumer offensive venom

v1, and consumer defensive venom v2, respectively, then co-evolution of these traits

is given by the following derivatives (Equations 3.2):

R

vv

t

R

RR

R

R

R

RR VeCavv

fvV

v

F

Fvv R

ttt)(

11

1 112

122231111

1

11 ))1((1

1

1VPqMvvggeRcavvV

v

F

Fvv tP

vv

tRC

C

R

tt

t

tt

2213222

2

22 )(1

1VPqvvggvV

v

F

Fvv tP

C

Ct

t

tt

For our simulations predator venom susceptibility was considered a constant that

does not co-evolve. We made additional assumptions in our modelling. Firstly,

although spatial structure may influence predator-prey interactions and give rise to a

geographic mosaic of co-evolution, we assumed that each species was represented by

a single, panmictic population to focus on local adaptation. We used a quantitative

genetics approach and held the additive genetic variance of the traits constant, so that

the rate of evolution depended on the strength of selection. Although this assumption

doesn’t hold true in the long term (without mutations to maintain genetic variation),

under very strong selection (resulting in loss of genetic variation, and for small

populations (which lack large initial genetic variation and are affected by genetic

69

drift), we believe this approach provides a reasonable starting point to investigate the

short-term (hundreds of generations) effects of changing ecological interactions

(Abrams 2001).

Analysis and Results

To understand the effects of co-evolution and the introduction of a third trophic level

on venom production, we performed simulations of an ecological invasion. Each of

these simulations began with a pairwise venomous consumer-prey system which was

able to reach eco-evolutionary equilibrium before the introduction of the generalist

predator after 1000 time steps. We performed two general types of simulations, and

set parameters to ensure non-zero equilibriums in both traits and densities. In the first

type, both the venomous consumer and prey species were assumed to have large

additive genetic variances (Vi = 1, for trait i) following the invasion of the predator,

promoting a high rate of evolution and thereby enabling the co-evolutionary arms

race to respond to this predatory pressure. In order to better understand the effects of

prey evolution on venom production in the consumer species, in the second

simulation the prey was assumed to have lost all additive genetic variance after

reaching equilibrium, but before predator introduction (at t = 1000). This second

scenario represents a stark contrast to the co-evolutionary scenario to better

understand the effects of evolution in the prey species on the final equilibrium

densities and consumer traits. We tracked the changes in population densities and

trait values as the simulation progressed and they reached equilibrium. To investigate

the effects of co-evolution and the invasion on the evolution of a novel ‘anti-

predator’ venom, in both types of simulation we also investigated the effect of

additional costs associated with maintaining two venoms (g3 = 0 or g3 = 0.01) and the

70

effectiveness of the prey-capture venom as a defence against the predator (M = 0 vs.

M = 0.7). We ran these simulations with a range of starting population density and

trait values to evaluate the potential for alternative stable states.

Where the prey species can always evolve, elevated mortality due to the invasion of a

predator results in a decline in the consumer density (Figure 1A). Predatory pressure

on the prey species is thereby reduced, and allows the prey species to become more

susceptible to the consumer venom (Figure 1C). The arms race between consumer

and prey becomes diminished, enabling the consumer to divert investment to its anti-

predator trait (Figure 1C). The reduced arms-race cost and reduced consumer

pressure together increase prey densities (Figure 1A), and allow the consumer

species to invest less in offensive venom (Figure 1C).

In the absence of prey evolution after apex predator invasion, increased predation of

the consumer species does not stimulate reduced arms race investment by the prey

species (Figure 1D), unless predator carrying capacities are relatively high (data not

shown). There is no negative feedback loop mediated by prey trait change to reduce

the strength of the trophic cascade and the declines in consumer density are greater

than in the prey evolution case (Figure 1B). Because low venom susceptibility is

maintained in the prey species, the consumer may no longer decrease prey-capture

investment without compromising growth (Figure 1D). Thus, even when the

multiplicative cost of investing in two traits is low, and there is little overlap between

the functions of the prey-capture and anti-predator traits, the consumer does not

divert prey-capture to investing in a novel anti-predation trait for relatively low

predator carrying capacities. Instead, the predatory pressure induces a greater

71

investment in the prey-capture trait, taking advantage of its defensive properties even

when its effectiveness compared to the dedicated anti-predator trait is low (Figure

1D).

Figure 1: Eco-evolutionary effects of an invading top predator (at time = 1000) on the densities (A,B)

and traits (C,D) for a three-trophic-level food web where the prey species either can (A,C) or cannot

(B,D) co-evolve. Values for the prey, consumer, and predator species are shown in blue, black, and

red, respectively. Prey consumption increases with prey trait values (solid blue line) and consumer

traits associated with prey-capture (i.e., offensive venom investment; solid red line). Predator attack

rates decrease greatly with consumer anti-predator traits (i.e., offensive, and defensive venom

investment; dashed red line), and to a lesser extent the prey-capture trait. Addition of a predator

pressure when prey co-evolution becomes restricted gives rise to an ‘overkill’ effect (D). The

parameters rP = 0.01, vR = 0.4, v1 = 0.3, v2 = 0.1, vP1 = 0.3, vP2 = 0.1, m0 = 0.05, mP0 = 0.01, a1 = 4, a2 =

72

3, c0 = cP = 0.25, f = 0.07, g1 = g2 = 0.02, g3 = 0, M = 0 gP1 = gP2 = 0.001, V1 = V2 = 1 were used for all

simulations. For the prey co-evolution scenario, VR = 1. For the inhibited co-evolution scenario, VR =

0.

Further evaluation of the no prey-evolution case suggests that investment in anti-

predator venom in response to the invasion only occurs under co-evolution, or when

predator carrying capacity is sufficiently large (Appendix II). In the case where the

prey species can evolve we find that evolution of a second, defensive venom is

discouraged by a high fitness cost g3 associated with producing multiple venoms and

the efficacy, and to a lesser degree by a low effectiveness of the prey-capture trait on

reducing attacks by the top predator (Figure 2).

Figure 2: Eco-evolutionary effects of an invading top predator (at time = 1000) on the densities (top

row) and traits (bottom row) for a three-trophic-level food web, where the prey species can always co-

evolve. Values for the prey, consumer, and predator species are shown in blue, black, and red,

respectively. Here we show the effect when g3 is set high (0.01, C,G,D,H) and low (0, columns

A,E,B,F), and M is also set high (0.7, columns B,F,D,H) and low (0, columns A,E,C,G). Investment in

the anti-predator venom is most strongly determined by the magnitude of g3, and is greater when g3 is

lower. Investment is affected to a lesser extent by M, to which it is also inversely proportional. The

outcome of the arms race between the venomous consumer and its prey is also affected by the values

73

of g3 and M. Low g3 and low M both result in higher prey-capture investment and higher susceptibility

in the prey species. The parameters rP = 0.01, vR = 0.4, v1 = 0.3, v2 = 0.1, vP1 = 0.3, vP2 = 0.1, m0 = 0.05,

mP0 = 0.01, a1 = 4, a2 = 3, c0 = cP = 0.25, f = 0.07, g1 = g2 = 0.02, gP1 = gP2 = 0.001, V1 = V2 = VR = 1

were used for all simulations.

Discussion

Co-evolution with prey species may facilitate anti-predator venoms

Our modelling suggests that a co-evolutionary interaction between a venomous

consumer with its prey can affect the consumer’s evolutionary response to a

generalised apex predator. Because it enables the trade-off between trait investments

via a reciprocal ‘disarmament’, a co-evolutionary arms race with its prey species can

facilitate the evolution of a novel anti-predator venom in a venomous consumer. This

finding brings new insight to an interesting paradox of the use of venoms in

defensive contexts. Currently, our understanding of the evolution and use of venoms

in defensive contexts is limited, and it is generally held that venoms are primarily an

offensive adaptation (Casewell et al. 2013). The ‘life-dinner’ principle, proposed by

Dawkins and Krebs (1979), points out the inherent asymmetry of predator-prey

interactions. If a predator fails in a given interaction, it only loses a meal, but failure

by the prey results in death or injury. Given the life-dinner principle, it may seem

more intuitive that chemical warfare should be a more valuable mode of defence for

venomous animals to preserve their own lives, rather than as a weapon for prey-

capture. To some extent, behavioural responses may explain this apparent

discrepancy (van der Meijden et al. 2013).

There is a range of evidence suggesting that venom may be more important for

defence than previously thought. Recent identification of separate offensive and

74

defensive venoms in cone snails has suggested that venoms arising to deter predators

are more common than previously thought (Dutertre et al. (2014). Our findings

suggest that diets involving arms races with prey species are more likely to facilitate

the evolution of such defensive venoms, even at relatively low predator densities.

The use and evolution of defensive venom has been documented in other trophically

venomous taxa, including scorpion pre-venom and spitting cobras (Hayes et al. 2008;

Inceoglu et al. 2003). Furthermore, histological evidence suggests that a wider range

of venomous taxa may possess the necessary tissues for regionalized toxin

production and the deployment of separate offensive and defensive venoms (Moran

et al. 2013; Morgenstern and King 2013). In light of all this, and the putative

ubiquity of prey co-evolution in venomous animal systems, our findings may support

recent calls to reconsider the traditional view that defence is generally not a

significant selection-pressure or function of venoms (Dutertre et al. 2014).

Restricted co-evolution may give rise to ‘overkill’

Our results suggest that the ability to use prey-capture venom to deter predators,

paired limited co-evolution in prey, can lead to elevated investment in that venom in

response to increased predator exposure. In order to maximize the efficacy of the

prey-capture venom in defensive contexts, investment can elevate beyond that

necessary for prey capture. Consequently, when the pairwise consumer-prey

interaction is viewed in isolation of the predator, the decoupled arms race may

falsely suggest maladaptation by the venomous consumer due to overinvestment in

venom potency relative to its prey, reminiscent of the ‘overkill’ hypothesis (Mebs

2001).

75

The view that adaptive venom composition, under selection for diet, gives rise to co-

evolutionary arms races between venomous consumers and their prey has not been

universally accepted (Casewell et al. 2013; Mebs 2001; Sasa 1999). The ‘overkill’

hypothesis instead proposes that neutral evolutionary processes are responsible for

the wide variability observed in the chemical composition, injection volumes, and

potency of snake venoms (Mebs 2001). A wealth of contrary evidence supporting a

strong selective pressure for diet has since emerged in the literature (Barlow et al.

2009; Gibbs and Mackessy 2009; Pawlak et al. 2009; Starkov et al. 2007). The

concept has been formalized by the venom optimisation hypothesis, which posits that

the high cost of venom production drives a strong selective pressure for strategies to

use it efficiently (Casewell et al. 2013; Morgenstern and King 2013). There is a

growing body of evidence for venom metering in a wide range of venomous taxa

which casts doubt over the assertion that injection volumes are highly variable

(Morgenstern and King 2013). Here we suggest that predator exposure may also

influence investment in prey-capture venoms, and these multi-trophic interactions

must be considered when developing estimations for optimal venom production.

Under what circumstances might co-evolution become restricted, potentially giving

rise to the overkill-like scenario? Co-evolution can become constrained due to

tradeoffs with other competing selection pressures (Dietl and Kelley 2002). Co-

evolution may also be limited or even entirely absent when the prey species is a

relatively rare species in a diverse community, or if the consumer feeds on a wide

range of prey species. According to the ‘escalation’ hypothesis, these asymmetries in

predator-prey interactions can give rise to an escalation in the anti-predator traits of

prey species without a reciprocal elevation of prey-capture traits in the consumer,

76

which is characteristic of co-evolution (Vermeij 1994). Escalation may therefore be

a more common process in venomous consumer-prey interactions in venomous

animals that are dietary generalists. Thus, co-evolution may be limited or even absent

in generalist venomous consumers, satisfying what our results suggest to be the key

condition for the emergence of the ‘overkill’ pattern in venom evolution.

Conclusion and future directions

In general, our investigation has shown that prey co-evolution has a marked effect on

the evolutionary response in the venom of a venomous consumer to the invasion of a

generalist apex predator. Abrams (1991) modelled a similar system, in which a

specialist (but non-co-evolving) predator was introduced to a co-evolutionary

consumer-prey arms race. When he assumed a negative correlation of prey-capture

and anti-predator traits in the consumer (as we did in our modelling using fitness

costs, such that investing in one trait requires a trade-off in the other) he also found

that consumer response to prey was diminished (Abrams 1991). Our results also

support earlier work proposing that additional interacting species will reduce the co-

evolutionary response in the members of an arms race (Vermeij 1982). Indeed,

empirical studies of tri-trophic chains in plant-herbivore systems have shown that

anti-herbivore defences are stronger in patches where there is less predation on

herbivores (Nersesian et al. 2011). The extent of a reciprocal ‘disarmament’ between

venomous consumer and its prey species is strongest when the costs of possessing

multiple venoms are high and there is high functional overlap between these two

traits (i.e. when the prey-capture venom is effective in defensive contexts).

77

Venomous consumers offer fascinating opportunities as model systems for the study

of arms races, escalation, and co-evolution. For example, pit vipers and opossums

may be engaged in a co-evolutionary arms race involving a unique, biochemically-

mediated process of role-switching between consumer and prey (Voss 2013). In our

investigation of the effects of predator-venomous consumer-prey interactions in a tri-

trophic chain we did not include evolution of the top predator, which can further

complicate the co-evolutionary arms races (e.g. giving rise to chaotic dynamics

Dercole et al. 2010). Nonetheless, our results suggest that considering venom

evolution in three-trophic levels can produce novel insights not readily apparent from

pairwise interactions. In sum, our study illustrates the importance of establishing a

theoretical framework for venom evolution, and that novel and unintuitive insights

can emerge by investigating more realistic, multi-trophic models of natural predator

prey systems.

78

4. General discussion

In sum, from the induced defence observed in response to manipulated predator

interactions I found evidence for adaptive plasticity in venom composition for the

first time, to my knowledge. Additionally, I have made a number of findings using

theoretical modelling of arms races in venomous predator-prey systems. While an

offensive pressure enhances the arms race between a venomous animals and its prey,

a predatory pressure diminishes the arms race between a venomous animal and its

co-evolving prey and instead prompts investment in defensive venom. I have found

that co-evolution may enable the evolution of a novel defensive venom in response to

predatory pressures, and the absence of co-evolution may give rise to an ‘overkill’

effect in the presence of a defensive pressure.

There have been calls for a renewed interest for more research to understand the

evolution and ecology of defensive venoms (Casewell et al. 2013; Dutertre et al.

2014). My findings present several new insights into the importance of defensive

venoms and defensive pressures in venom evolution. The potential role for prey co-

evolution in facilitating the evolution of a separate defensive venom is of particular

interest in light of the recent discovery of a separate defensive venom in cone snails

(Dutertre et al. 2014). Studies of plant-herbivore systems have suggested that

induced plastic defences are generally favoured if defences are costly and are not

always needed (Karban 2011).Thus, induced plastic defence in the composition of

venom may present a new strategy for using venom economically, and adds further

evidence corroborating the venom optimisation hypothesis. The potential to provide

a vast armoury of toxins to plastically cope with different environmental conditions

79

may help to reconcile the seemingly lavish complexity of venoms can be reconciled

with the optimisation hypothesis (Morgenstern and King 2013).

Similarly, the likely importance of arms races in venom ecology and evolution has

been recognized, but studies of arms races in venomous animals are lacking

(Casewell et al. 2013). Furthermore, studies of predator-prey arms races in general

have traditionally focused on pairwise interactions (Mougi and Nishimura 2009), as

has the relatively meagre evidence for arms races in venomous animals (Casewell et

al. 2013). But multi-trophic models may be more representative of natural systems,

particularly three trophic-level models (Abrams 1991; Abrams 2000; Dercole et al.

2010). My results support the view that evaluating species-interactions in a three

trophic-level context can provide valuable new insights that are invisible to pairwise

studies. The accumulated, if limited, evidence for arms races in venomous animals

suggests that venomous animal systems may provide fertile ground as excellent

models for general studies of arms races in species interactions. For example, pit

vipers and opossums may be engaged in an entirely novel co-evolutionary arms race

involving a biochemically-mediated process of role-switching between predator and

prey (Voss 2013). Thus, further investigation of arms races in venomous animals is

essential.

There is also a growing acknowledgement of the need to investigate the interactions

between venomous animals in the broader context of their ecological communities

(Casewell et al. 2013), and of the potential role of venom in the structuring of food

webs and ecological communities (van der Meijden et al. 2013). Induced plastic

defences and co-evolution can stabilize predator-prey interactions and food webs

80

(Cortez 2011; Northfield and Ives 2013). Relationships between geographic variation

in venom composition and diet are becoming well established, but future studies

should consider how venom properties may also vary with respect to different

predators, different densities of predators and prey, as well as density-neutral

disturbances that can alter densities. Finally, a better understanding of the precise

costs of venom production is also essential, in order to better inform and improve the

modelling of fitness costs in future theoretical studies of venomous animal systems,

which in turn can guide and inform empirical work in this rapidly evolving and

exciting field of research.

81

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90

6. Appendix I – additional material relevant to

Chapter 2

Figure 1: Comparison of venom profiles obtained prior to experimental treatments. Patterns of

difference between venom profiles were not statistically significant and arose from conditions in the

wild. Because these represent the averaged, normalized venom profiles for each treatment, the

response variable is normalized milliabsorbance units, and indicates relative quantity between any

given portion of the mean of the venom profiles of each treatment. Defensive treatments are indicated

in dark and light blue, while the non-defensive treatments are shown in orange and red.

Elution volume (mL) elution time

(n=14)

(n=15)

(n=15)

(n=15)

No

rmal

ise

d m

illia

bso

rban

ce (

28

0 n

m)

91

Figure 2: Comparison of venom profiles obtained 21 days after the conclusion of the experiment, in

the absence of treatment pressures. Patterns of change between predator and without-predator

treatments in venom profiles obtained immediately after the conclusion of treatments were observed,

but were diminished and statistically insignificant. This lingering effect of the predatory pressure is

suggestive of an induced, plastic defence. Because these represent the averaged, normalized venom

profiles for each treatment, the response variable is normalized milliabsorbance units, and indicates

relative quantity between any given portion of the mean of the venom profiles of each treatment.

Defensive treatments are indicated in dark and light blue, while the non-defensive treatments are

shown in orange and red.

Elution volume (mL) elution time

No

rmal

ise

d m

illia

bso

rban

ce (

28

0 n

m)

(n=14)

(n=13)

(n=11)

(n=14)

92

10 15 20 25 30 35 40 45

0e

+00

1e-0

42e

-04

3e-0

44e-0

45

e-0

46

e-0

4

Volume

Abso

rba

nce

Figure 3: We delimitated fractions by combining the normalized chromatograms of all individuals

into a single mean chromatogram, then fitted a spline curve (λ = 0.5) and obtained 11 fractions by

separating at local minima. The correspinding elution volumes (mL) delimiting the fractions (from

smallest to highest) were as follows: 10.48, 13.75, 16.72, 17.93, 19.63, 22.70, 24.02, 28.73, 31.02,

34.66, 40.61, 44.10.

1 2 3 4 5 6 7 8 11 10 9

93

Table 1: MANOVA results, which indicated there were no statistically significent differences

between fraction loadings of scorpions allocated to each treatment prior to actually having been

subjected to those treatments (obtained from the first venom milking).

Source d.f. Pillai approx F Df den P

3. 4.

Prey 1 0.017 0.483 2,54 0.619

Predator 1 0.033 0.927 2,54 0.402

Predator ✕Prey 1 0.006 0.165 2,54 0.849

Residuals 55

Table 2: ANOVA results, which demonstrated significantly different fraction loadings between the

predator treatments compared to the without-predator treatments along both PC1 and PC2 for

scorpions prior to experimental treatments (obtained from the first venom milking). There were no

interaction effects.

Source d.f. MSE F P

PC 1

Prey 1 0.006 0.651 0.423

Predator 1 0.015 1.711 0.196

Predator ✕Prey 1 0.001 0.110 0.742

Residuals 55 0.009

PC 2

Prey 1 0.002 0.334 0.565

Predator 1 0.001 0.175 0.678

Predator ✕Prey 1 0.001 0.225 0.637

Residuals 55 0.005

Table 3: MANOVA results, which indicate dthere were no statistically significent differences

between fraction loadings of treatments in the venom obtained 21 days after the cecession of

experimental treatments (obtained from the final venom milking).

Source d.f. Pillai approx F Df den P

5. 6.

Prey 1 0.042 1.076 2,48 0.349

Predator 1 0.025 0.619 2,48 0.543

Predator ✕Prey 1 0.012 0.299 2,48 0.743

Residuals 49

94

Table 4: ANOVA results, which demonstrated significantly different fraction loadings between the

predator treatments compared to the without-predator treatments along both PC1 and PC2 for

scorpions milked 21 days after treatments ceased (obtained from the final venom milking). There were

no interaction effects.

Source d.f. MSE F P

PC 1

Prey 1 0.002 0.285 0.596

Predator 1 0.001 0.098 0.756

Predator ✕Prey 1 0.004 0.591 0.446

Residuals 49 0.007

PC 2

Prey 1 0.008 1.899 0.174

Predator 1 0.005 1.170 0.285

Predator ✕Prey 1 0.000 0.018 0.895

Residuals 49 0.004

95

6. Appendix II – additional material relevant to

Chapter 3

Figure 1: Under high predatory pressure (k=0.02 instead of 0.01, other parameters as per Figure 1), a

specialized defensive venom may evolve in the absence of co-evolution when both are true: the prey-

capture venom has no effect in defensive contexts (M=0), and there is no cost of maintaining two

venoms (g3=0).

96

Figure 2: High/low effectiveness of the prey-capture venom for defence, and high/low cost of

maintaining two venoms have a minimal effect on the population dynamics trait evolution in the

absence of co-evolution (Parameters as per Figure 2). Values for the prey, consumer, and predator

species are shown in blue, black, and red, respectively. Here we show the effect when g3 is set high

(0.01, C,G,D,H) and low (0, columns A,E,B,F), and M is also set high (0.7, columns B,F,D,H) and

low (0, columns A,E,C,G).