ECOLOGICAL EFFECTS OF PREDATOR INFORMATION MEDIATED BY PREY BEHAVIOR
Tyler C. Wood
A Dissertation
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
May 2020
Committee:
Paul Moore, Advisor
Robert Green Graduate Faculty Representative
Shannon Pelini
Andrew Turner
Daniel Wiegmann ii ABSTRACT
Paul Moore, Advisor
The interactions between predators and their prey are complex and drive much of what we know about the dynamics of ecological communities. When prey animals are exposed to
threatening stimuli from a predator, they respond by altering their morphology, physiology, or behavior to defend themselves or avoid encountering the predator. The non-consumptive effects
of predators (NCEs) are costly for prey in terms of energy use and lost opportunities to access
resources. Often, the antipredator behaviors of prey impact their foraging behavior which can
influence other species in the community; a process known as a behaviorally mediated trophic
cascade (BMTC).
In this dissertation, predator odor cues were manipulated to explore how prey use
predator information to assess threats in their environment and make decisions about resource
use. The three studies were based on a tri-trophic interaction involving predatory fish, crayfish as
prey, and aquatic plants as the prey’s food. Predator odors were manipulated while the foraging
behavior, shelter use, and activity of prey were monitored. The abundances of aquatic plants
were also measured to quantify the influence of altered crayfish foraging behavior on plant
communities.
The first experiment tested the influence of predator odor presence or absence on crayfish
behavior. Crayfish spent more time foraging and less time in shelter in the presence of predator
odor cues compared to predator absent controls. The crayfish also consumed greater quantities of
two macrophyte species in the presence of threatening odors. In the second experiment, crayfish
were exposed to odors from predators that were fed four different diets and varied in their size iii relative to the size of the crayfish. The crayfish responded to the relative size ratios between themselves and their predators, but the direction of the response was determined by the predator’s diet. The third experiment exposed individual crayfish to odors from individual predators which varied in gape size relative to the body size of the crayfish. The crayfish responded along a gradient of relative risk by foraging more and using shelter less in the face of greater threats. Crayfish that were not as threatened foraged less and spent more time in shelter.
The results obtained across all three experiments were largely consistent and indicate that crayfish can extract detailed information from predator odor cues. Further, crayfish incorporate multiple types of predator information into threat assessments as they make resource use decisions. Subtle differences in predator odor cues alter crayfish behavior which mediates the influence of predatory fish in freshwater communities. iv
This dissertation is dedicated to…
Mom, for urging me to chase butterflies and my dreams;
Dad, for leading me into the forest and the fields;
Gram, for inspiring my passion for living things;
Poe, for teaching me the faith of a fisherman;
Ali, for the chance to learn how to lead;
And Sarah, for being my partner in crime.
I love and thank you all. I could not have come so far without all your support. v ACKNOWLEDGMENTS
First, I want to thank my advisor, Dr. Paul A. Moore for his guidance and wisdom over the last four years. His approach to graduate training provided the bootcamp experience that I have long sought to test myself against. Under his tutelage, I learned more philosophy than I ever thought I would know, but more importantly I learned how to think and how to teach.
Thank you to my committee members, Robert Green, Shannon Pelini, Andrew Turner, and Daniel Wiegmann for the inspiration of your work and for your comments on my research along the way. I appreciate your willingness to take me on as a mentee.
To the past and present members of the Laboratory for Sensory Ecology, thank you for the solid foundation laid by those who came before, for the support given by those who were here, and for all the cinderblocks hauled, cold-wet nights collecting crayfish, tedious writing edits, and stimulating conversations whether scientific or pedestrian.
Thank you to Bowling Green State University for financial and infrastructural support over the last four years. Thanks to the Department of Biological Sciences and Graduate Student
Senate for providing travel funding which has allowed me to attend many conferences at locations across the United States. Thank you also for supporting my research with the Barbara
Long-Masters Biological Sciences Research Award.
I would also like to thank the University of Michigan Biological Station for the use of facilities and funding through the Marian P. and David M. Gates Graduate Student Endowment
Fund. My three summers at the station were an amazing opportunity to network with world class scientists while exploring the natural wonders of northern Michigan.
Finally, I would like to thank The Crustacean Society for supporting my research with their Fellowship in Graduate Studies. vi
TABLE OF CONTENTS
Page
CHAPTER I: INTRODUCTION ...... 1
CHAPTER II: FEEDING IN FEAR: INDIRECT EFFECTS OF PREDATORY FISH ON
MACROPHYTE COMMUNITIES MEDIATED BY ALTERED CRAYFISH FORAGING
BEHAVIOUR ...... 12
Methods...... 15
Collection and Housing of Crayfish, Bass, and Aquatic Plants ...... 15
Experimental Design and Arenas...... 16
Experimental Protocol ...... 18
Data Collection ...... 20
Statistical Analysis ...... 21
Ethical Approval ...... 22
Results ...... 25
Macrophyte Consumption ...... 25
Crayfish Behavior ...... 26
Discussion ...... 31
Effect of Predator Odor on Macrophyte Consumption by Crayfish ...... 31
Consequences for Aquatic Systems ...... 32
Conclusions ...... 35
CHAPTER III: BIG AND BAD: HOW RELATIVE PREDATOR SIZE AND DIETARY
INFORMATION INFLUENCE CRAYFISH BEHAVIOR AND RESOURCE USE
DECISIONS ...... 36 vii
Methods...... 41
Collection and Housing of Animals and Plants ...... 41
Experimental Design and Arenas...... 43
Experimental Mesocosms ...... 43
Diet Production ...... 45
Experimental Protocol ...... 45
Data Collection ...... 47
Ethical Approval ...... 48
Statistical Analysis ...... 48
Results ...... 51
Macrophyte Consumption ...... 51
Foraging Effort...... 51
Shelter Use ...... 52
Transitions...... 52
Discussion ...... 58
Chemical Components of Threat ...... 58
Conclusions ...... 63
CHAPTER IV: FINE-TUNED RESPONSES TO CHEMICAL LANDSCAPES:
CRAYFISH USE PREDATOR ODORS TO ASSESS THREATS BASED ON RELATIVE
SIZE RATIOS ...... 64
Methods...... 70
Collection and Housing of Animals ...... 70
Diet Production ...... 71 viii
Plant Collection and Storage ...... 72
Experimental Design ...... 73
Experimental Mesocosms ...... 73
Experimental Protocol ...... 74
Data Collection ...... 75
Ethical Approval ...... 77
Relative Size Analyses ...... 77
Macrophyte Consumption Analysis ...... 77
Crayfish Behavioral Analysis ...... 78
Comparison of Gape Ratio and Total Length Models ...... 78
Results ...... 82
Macrophyte Consumption by Crayfish ...... 82
M. exalbescens Consumption and Gape Ratio ...... 82
Chara spp. Consumption and Gape Ratio ...... 82
E. canadensis Consumption and Gape Ratio ...... 82
Crayfish Behavioral Responses ...... 82
Foraging Behavior and Gape Ratio...... 82
Shelter Use and Gape Ratio ...... 83
Transitions and Gape Ratio ...... 83
Comparison of Gape Ratio and Total Length Models ...... 83
Discussion ...... 87
CHAPTER V: SUMMARY AND IMPACTS ...... 94
REFERENCES ...... 100 ix
LIST OF FIGURES
Figure Page
1 Experimental Mesocosm ...... 23
2 Plant Resource Zone Example ...... 24
3 Effects of Crayfish Grazing and Bass Odor on Macrophyte Biomass ...... 27
4 Bass Odor Influence on Crayfish Foraging Behavior ...... 29
5 Bass Odor Influence on Crayfish Sheltering Behavior ...... 30
6 Flow Through Stream Mesocosm ...... 49
7 Macrophyte Feeding Brackets ...... 50
8 Macrophyte Consumption ...... 53
9 Foraging Effort...... 55
10 Shelter Use ...... 57
11 Artificial Stream Mesocosm and Macrophyte Feeding Bracket ...... 79
12 Fish Gape Widths Against Crayfish Carapace Widths ...... 80
13 Total Lengths and Gape Ratios of Fish Used for Odor Generation ...... 81
14 Influence of Gape Ratio on Macrophyte Consumption by Crayfish ...... 85
15 Behavior of Crayfish Responding to Gape Ratio ...... 86
x
LIST OF TABLES
Table Page
1 Effects of Predator Odor on Macrophyte Consumption ...... 28
2 Number of Trials Performed in each Treatment ...... 48
3 Effect of Predator Diet and Gape Percentage on Total Consumption of Macrophytes 52
4 Effect of Predator Diet and Gape Percentage on Total Foraging Effort ...... 54
5 Effect of Predator Diet and Gape Percentage on Total Shelter Use ...... 56
6 Comparison of Gape Ratio and Fish Total Length Effects on Crayfish Response
Variables ...... 84
Running head: ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 1
CHAPTER I: INTRODUCTION
The ecological relationships between predators and prey are complex and involve multiple levels of interactions. Dusenbery (1992) defined three types of interactions between organisms which can be used to describe the components of predator-prey interactions. The first, a physical interaction, occurs when two organisms come into contact with one another and involves a transfer of mechanical forces or heat (Dusenbery, 1992). A mantis shrimp smashing a shell with its raptorial appendage represents a physical interaction (Patek & Caldwell, 2005).
Second are trophic interactions, which occur when organisms obtain energetic or nutritional resources by feeding on other organisms (Dusenbery, 1992). The consumption of Daphnia by planktivorous fish is an example of a trophic interaction (Luecke et al., 1990). The third type of interaction is informational and occurs when information passes from one organism to another
(Dusenbery, 1992). The aposematic coloration of a monarch butterfly provides avian predators with warning information, pertaining to the butterfly’s chemical defenses (Brower, 1988).
Although all three types of interactions are important to our understanding of ecology, the study of informational interactions is particularly important because the use of information allows organisms to predict future physical and trophic interactions (Lima & Dill, 1990).
Informational interactions reduce uncertainty in the world of an organism (Dusenbery,
1992). Uncertainty in this case refers to the relative inability of organisms to predict future events that may affect their fitness. Acquiring information generally improves an animal’s performance, by allowing the animal to better predict where or when threats or resources might be encountered (Hasson, 1991; Laughlin, 2011). Animals often respond to new information by changing their behavior. For example, Arctiid moths have tympanic organs which allow them to detect the ultrasonic calls of echolocating bats (Fenton & Fullard, 1979). Such a moth will likely ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 2
change its flight pattern in response to hearing a bat call, which reduces the chance of being
caught (Roeder, 1962). A moth that successfully evades the bat, increases its chances of
surviving long enough to reproduce. The moth’s fitness has thus increased because information
was extracted from a stimulus, which enabled the moth to respond accordingly (Dall et al.,
2005). A stimulus is a pattern of energy or chemicals that can activate the sensory systems of life
forms (Stevens, 2013). Light, sound, electromagnetic fields, vibrations, pressure, and
temperature are all forms of stimuli that can carry information via wave propagation, while
chemicals can provide information as single compounds or in mixtures (Dusenbery, 1992). The
value of information and the variety of different stimuli has led animals to evolve many different sensory organs of varying sensitivities to detect stimuli and extract information.
The information that can be extracted from a stimulus is limited by the organism’s sensitivity to the stimulus. For any given sensory system of an organism, there are threshold energies or concentrations above and below which the organism cannot detect stimuli. For example, lab rats show behavioral responses to components of red fox odor at concentrations as low as 0.04 parts per trillion, while several species of small primates are only sensitive to concentrations exceeding 0.14 parts per billion (Laska et al., 2005). Although all the primates tested could detect the odor, the rats were more sensitive to the scent by greater than six orders of magnitude. This is because rats have been subject to greater selective pressures to detect fox odors than tropical primates have (Laska et al. 2005). Thus, stimuli which provide information to some organisms, may not be relevant to others. Before an organism can detect and extract information from a stimulus, the energy or chemicals carrying the information must travel through the environment to reach a sensory apparatus. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 3
As a stimulus travels through the environment, the information being transmitted can be masked or modified by physical factors of the environment (Bradbury & Vehrencamp, 1998).
Variation in physical factors like flow in air or water, density of the media, temperature, and relative noise level can influence both intensity and distribution of stimuli in space and time
(Payne & Webb, 1971; Moore & Atema, 1991; Weissburg & Zimmer-Faust, 1994; Moore &
Crimaldi, 2004). For example, predatory crabs are less effective at tracking and locating prey using odor cues in fast or turbulent flow conditions (Weissburg & Zimmer-Faust, 1994).
Similarly, hardshell clams do not respond as strongly to the odors of crabs when flow velocity is high (Smee & Weissburg, 2006). However, the disturbance in odor intensity and spatial distribution caused by turbulent flow does not affect the prey tracking abilities of predatory whelks (Ferner & Weissburg, 2005). Regarding temporal variation in stimuli, isopods show reduced responses to predatory fish odors when they are exposed to the odor for increasing durations (Holomuzki & Hatchett, 1994). Because of sustained exposure to the predatory odor, the isopods become habituated to the stimulus, and ignore the information (Holomuzki &
Hatchett, 1994). These examples demonstrate how environmental factors can alter stimuli and how even small changes in information or its availability can affect animal behavior. Thus, environmental factors can alter the information released by predators which is used by prey to make decisions about avoiding areas of high or low predation risk.
Prey animals increase the chance of avoiding their predators by gathering information from cues released by the predator (Lima & Dill, 1990). A cue is a stimulus whose release is not beneficial to the emitter (Stevens, 2013). Areas in the environment where aversive predator cues are abundant are perceived by prey as high risk, while habitats where predator cues are uncommon or absent are perceived as low risk (Laundre et al., 2010). Ecologists refer to spatial ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 4 variation in risk perception as the landscape of fear theory (Gaynor et al., 2019). The landscape of fear is based on observations made in Yellowstone National Park following the reintroductions of wolves into the region. Elk and bison in the park display increased vigilance behaviors in areas frequented by wolves. The elk have nearly abandoned their foraging efforts in the river bottoms because of the high perceived risk of wolf predation there (Laundre et al.,
2001; Hernandez et al., 2005; Ripple & Beschta, 2006, 2007). Using this framework, we imagine the distribution of perceived predation risk in the environment like a topographic map, in which high elevations indicate regions of high risk and low elevations indicate regions of low risk.
Thus, animals rely on information gathered from predator cues to make decisions about where and when to forage, search for mates, and seek shelter (Lima & Dill, 1990; Laundre et al., 2010).
Once the decision has been made, prey animals will alter their behavior accordingly. However, as predators move throughout the environment, they change the distribution of cues in the landscape.
Predator movements are constantly changing the landscape of fear by altering the distribution of aversive stimuli in space and time. The predator’s sphere of influence is the region surrounding the predator in which the sensory landscape is altered by new cues the predator emits (Turner & Montgomery, 2003). If we consider the rate at which a predator moves through the environment, how long prey behavioral responses last after detecting predator cues, the distance at which prey begin responding to predator cues, and the density of the predator population in the habitat, we can estimate the predator’s influence on a given prey species across space and time (Turner & Montgomery, 2003). This concept allows ecologists to predict the effects that a mobile predator will have on prey behavior. For example, snails in the littoral zone of Pymatuning Reservoir spend much of their time in sheltered areas, because the stimuli ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 5
released by the population of predatory sunfish keeps the snails in a threatened state (Turner &
Montgomery, 2003). To take this idea further, we need to consider the sensory ecology of the
prey, and the effects of environmental factors on the information. Here, we can apply the concept
of the reaction space, which is the spatially and temporally dynamic zone surrounding a predator
that prey can respond to (Jurcak & Moore, 2018). The reaction space encompasses the various
types of stimuli released by predators, the movement of predators across spatial and temporal
scales, the changes in stimulus properties caused by environmental conditions, and prey
sensitivity to the stimuli that are present (Jurcak and Moore, 2018). This concept allows for
changes in cue distribution caused by factors like wind or flowing water. It also considers
differences in responsiveness to stimuli both within and among prey species. However, the
dynamic nature of the landscape of fear goes even further, when we consider that different
predator species and even different individual predators can represent different levels of risk to
the same prey animal.
Helfman (1989) formed his threat-sensitive predator avoidance hypothesis which suggests that prey employ graded responses to predators depending on their perception of risk, after observing the fear responses of damselfish to predator models of different sizes. Variation in the cues released by individual predators allow prey to extract detailed information beyond predator presence or absence. As in the previous example, predator size is an indicator of risk for prey species. Similarly, the wolf spider Pardosa milvina, shows strong avoidance of cues from large adult Hogna helluo spiders while it does not avoid cues from juvenile Hogna (Persons &
Rypstra, 2001). Variation in predator diet can also alter prey perceptions of risk (Murry &
Jenkins, 1999). Tadpoles exposed to odors from predatory dragonfly larvae, show increased predator avoidance and altered body morphology in the presence of dragonfly larvae that have ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 6 recently fed on a conspecific tadpole diet (Laurila et al., 1997; Ferland-Raymond & Murray,
2008). Predator hunting mode also alters predator avoidance behaviors by prey. Grasshoppers showed different antipredator behaviors when exposed to several species of spiders which employ sit-and-wait, sit-and-pursue, and active hunting modes (Miller et al., 2013). The responses of prey to detailed predator information allow them to heighten their responses when predation seems likely while avoiding costly antipredator responses when the predator does not pose a real risk. The costs associated with antipredator behavior include reductions in foraging, mating, or other activities and/or relocation to other less favorable habitats. Thus, avoiding unnecessary responses can reduce the negative effects of predators on prey animals.
The cues released by predators can have negative effects on prey beyond the predator’s potential to remove individuals from the prey population through consumption (Brown, 1999).
Non-consumptive effects (NCEs) occur when prey respond to information obtained from predators and incur a cost (Preisser & Bolnick, 2008). Prey responses involve the improvement of defenses by changes in morphology, physiology, or behavior in response to predator information (Brown, 1999). Although defensive responses to predator information decrease the probability that prey will be consumed, the responses themselves are costly for prey (Maynard
Smith, 1982; Nelson et al., 2004). An example is provided by the effects of diel vertical migration, a defensive behavioral response of many zooplankton species to fish odor cues
(Lampert, 1989, 1993). Daphnia that migrate show significantly reduced growth and reproductive rates caused by the amount of time they spend in deep cold-water during daylight hours (Loose & Dawidowicz, 1994). Thus, the large body of research on NCEs that has accumulated over the last 20 year indicates that NCEs can have larger impacts on prey populations and community dynamics than consumptive effects do (Abrams, 1990; Anholt & ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 7
Werner, 1995; Preisser et al., 2005; Peacor et al., 2013). Although NCEs do contribute to changes in predator and prey populations, changes in community dynamics result from altered prey behaviors which affect the way that prey species interact with others in the community.
When changes in prey behavior in response to a predator also impact other species that interact with the prey, a behaviorally mediated trophic cascade (BMTC) can occur (Schmitz et al., 1997; Gaynor et al., 2019). BMTCs should be considered distinct from density mediated indirect effects because the latter are caused by changes in prey population density due to the consumptive effects of predators (Abrams et al., 1996). For a BMTC to occur, there must be at least three or more species involved to fill the initiator, transmitter, and receiver roles (Abrams,
1995). The initiator species is usually a predator that releases information into the environment and elicits a defensive response from prey. The prey, in responding to information from a predatory threat, acts as the transmitter species when altered prey behavior impacts a third species. This third species is the receiver of the indirect effect, and often experiences a change in abundance as a result (Abrams, 1995). Multiple species are often involved at each level of the interaction, especially in the receiver role (Schmitz et al., 2004). Within the field of trophic ecology, BMTCs are interesting because they represent trophic cascades which begin with informational interactions, rather than trophic interactions between predators and prey. Due to their prevalence in many communities, BMTCs may be equally important to the net effects of predators, as consumptive trophic interactions (Peacor & Werner, 2001).
In the last two decades of trophic ecology research, numerous studies have found evidence of NCEs induced in a plethora of prey species by many different predators (Peckarsky et al., 2008; Preisser & Bolnick, 2008), and the importance of BMTCs has come to light (Werner
& Peacor, 2003; Schmitz et al., 2004; Ohgushi et al., 2012). BMTCs play an important role in ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 8
structuring ecological communities and they also greatly influence the ways in which animals
shape the environment (Turner & Peacor, 2012). However, a key component is missing that
connects these two concepts, which is the understanding of how behavioral NCEs in prey
actually mediate the indirect effects of predators. On one side of the issue, experts on NCEs
know that prey reception of predator information drives changes in prey behavior, but most
studies stop at identification of the new behavior. On the other side, those that study BMTCs
know that prey behavior mediates the indirect effect of predators, but most are focused on
quantifying or categorizing the indirect effect. Behavior is currently a conceptual black box
because very few studies have directly observed the process by which predator information alters
the behavior of prey animals through sensory stimuli, who then exert different forces on receiver
species. This is a significant gap in our knowledge of trophic ecology, which likely exists
because sensory ecologists need to use information theory to form the bridge between NCEs and
BMTCs.
Therefore, for my dissertation, I performed a series of investigations into the specific behaviors mediating BMTCs that resulted from changes in predator information. I addressed how changes in information lead to different animal behaviors which resulted in community level consequences. I manipulated sources of predator information to elicit different behaviors in prey animals, then I directly observed behavior using video analyses, while the animals simultaneously impacted a controlled producer community. The producer communities were assessed to determine the relative impacts of the observed behaviors on producer abundance resulting from different predator information inputs. I devised a model system which provided the degree of control required to produce quality data, while maintaining many characteristics of natural systems. I studied a tri-trophic interaction in which largemouth bass (Micropterus ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 9
salmoides) served as the predator or initiator species, rusty crayfish (Faxonius rusticus) acted as
the prey or transmitter species, and three species of aquatic plants (Myriophyllum exalbescens,
Elodea canadensis, & Chara spp.) received the indirect effects in this experimental community.
The bass, crayfish, macrophyte tri-trophic system described was ideal for testing my ideas because all these organisms have been well studied previously, were simple to maintain, locally available, and were adaptable to mesocosm experiments. Crayfish are ideal models because they are opportunistic omnivores (although adults are primarily herbivorous) (Hogger,
1988; Momot, 1995); they receive sensory information through visual, mechanosensory, and olfactory channels (Kennedy & Bruno, 1961; Bergman & Moore, 2005; Clark & Moore, 2018); and they have well stereotyped behaviors (Stein & Magnuson, 1976; Garvey, 1994; Jurcak &
Moore, 2014). Although crayfish receive sensory input from multiple sensory channels, they are well adapted to use primarily chemical information to understand their environment (Moore &
Bergman, 2005). Crayfish are known to respond strongly to kairomones (odor cues) released by predatory fish, and they are sensitive to chemical gradients (Moore & Grills, 1999; Moore &
Crimaldi, 2004; Gherardi et al., 2011). Largemouth bass are common predators of crayfish throughout both their native and anthropogenically expanded ranges. Primarily piscivorous, the prey choices of largemouth bass may change with size and prey abundance, but they generally consume high protein diets. Studies have demonstrated antipredator responses to largemouth bass in many different crayfish species (McNeely et al., 1990; Hill & Lodge, 1995; Gherardi et al., 2011). The macrophyte species selected for these experiments are all locally abundant in the study region and would be commonly encountered by crayfish (Moore et al., 2012). Previous research has shown that all these plant species are consumed by crayfish, although they are not equally preferred (Chambers et al., 1990; Nystrom & Strand, 1996; Dorn & Wojdak, 2004). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 10
Macrophytes which are chemically defended with phenolic compounds are considered unpalatable (Bolser et al., 1998; Cronin et al., 2002). Buoyant species are harder for benthic animals like crayfish to manipulate while feeding under stress (Chambers et al., 1991). Research has also shown that crayfish prefer to consume macrophytes with fine leaf structures (Cronin et al., 2002). The macrophytes in use here were selected because they have traits that range across the criteria mentioned and may cause the crayfish to show different preferences under changing threat conditions. M. exalbescens contains the most phenolic compounds in its tissues, is buoyant and has a fine leaf structure. E. canadensis has low phenolic content, is less buoyant than M. exalbescens and has a larger whorled leaf structure. The Chara spp. macroalgae contains the least phenolic compounds, is negatively buoyant, and has a fine leaf structure. However, the carbonate encrusted cell walls of Charophytes are coarse in texture.
Using this model community, I tested the effects of different crayfish behaviors produced by manipulations of bass information on the relative abundances of the three macrophyte species across a series of three experiments. The first project in this series was published in Freshwater
Biology in 2018 and can be found in Chapter 2 of this dissertation. The experiment tested the effects of largemouth bass presence or absence on crayfish foraging behavior and shelter use, and to examine how the altered crayfish behavior impacted the experimental macrophyte community. This proof of concept study demonstrated that the mesocosm system I designed functions properly, the predator manipulations I performed were sufficient to produce observable
NCEs, and the NCEs altered crayfish behavior enough to produce significant BMTCs on the macrophytes. The second project (Chapter 3) was published in the Canadian Journal of Zoology in 2019 and examined changes in crayfish behavior across a gradient of threats generated by feeding the largemouth bass different diets. A fish meal protein diet represented the low threat ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 11
condition, a diet of allopatric congeneric northern clearwater crayfish (Faxonius propinquus) represented a low-moderate threat condition, a diet of sympatric congeneric virile crayfish
(Faxonius virilis) represented a high-moderate threat condition, and a diet of conspecific rusty crayfish (Faxonius rusticus) represented the high threat condition. There was also variation in the relative size relationships between the crayfish and the bass within each diet treatment that interacted with predator diet to produce significant differences in crayfish behavior. The third project (Chapter 4) is currently under review at Ecosphere and studied the influence of the ratio between fish gape size and crayfish body size on crayfish behavior and impact on macrophyte communities. The crayfish were not sensitive to changes in absolute predator size, but they were sensitive to differences in predator gape size relative to their own size. This relationship was based on cues related to the predator gape communicated through odor cues alone. The following chapters will cover each of the studies mentioned above in much greater detail. Together, these studies are some of the first in the field to combine direct observation of behaviors to demonstrate how subtle changes in predator odors alter the behavior of prey animals, while also quantifying the ecological impacts resulting from the changes in prey behavior. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 12
CHAPTER II: FEEDING IN FEAR: INDIRECT EFFECTS OF PREDATORY FISH ON
MACROPHYTE COMMUNITIES MEDIATED BY ALTERED CRAYFISH FORAGING
BEHAVIOUR
This article was published in Freshwater Biology, volume 63, issue 12, November 2018.
The journal had given permission for the work to be submitted as part of this dissertation.
Non-consumptive effects (NCE) occur when prey alter their behavior in response to detection of predator related stimuli (Brown et al., 1999). NCEs can alter trophic cascades and have larger impacts on food webs than direct consumption of prey by altering prey behavior, morphology, or physiology (Preisser et al., 2005; Peacor et al., 2013). One of the ways in which prey change their behavior under the threat of predation is by altering their foraging behavior
(Laundré et al., 2010). The reintroduction of wolves (Canis lupus) into Yellowstone National
Park has caused the elk (Cervus canadensis) population to switch from feeding on aspen
(Populus tremuloides) saplings in the river bottoms and lowlands to browsing farther up in the mountain valleys (Ripple & Beschta, 2006; Laundré et al., 2010). Similarly, in stream environments the presence of piscivorous bass (Micropterus salmoides and Micropterus punctulatus) limits the foraging of herbivorous minnows (Campostoma anomalum) and promotes the growth of filamentous algae (primarily Spirogyra spp. and Rhizoelonium spp.; Power &
Matthews, 1983). These increases in plant growth, ultimately resulting from the presence of a predator, are called trait-mediated indirect interactions (TMII) (Abrams, 1995). Foraging behavior is a trait of prey that when altered changes their impact on food resources (Peacor &
Werner, 2001). Thus, the predator has an indirect effect on the prey’s food resource (Abrams,
1995). For example, prairies with spider (Pisaurina mira) populations have increased grass diversity because of a feeding strategy adopted by grasshoppers (Melanoplus femurrubrum) to ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 13 avoid spider webs (Schmitz, 1998). Cladocerans (Daphnia, Diaphanosoma, and Ceriodaphnia) are more abundant when piscivores (M. salmoides) are present, because planktivorous fish
(Lepomis macrochirus) spend more time in vegetated refuge (Turner & Mittelbach, 1990). These examples of TMIIs illustrate how the presence of a predator alters the foraging behavior of prey populations (Sih, 1982; Trussell et al., 2003; Grabowski, 2004). Indirect effects, mediated through NCEs, can only occur if prey detect and respond to the presence of predatory cues within the environment (Luttbeg & Trussell, 2013)
Before NCEs can manifest, prey must first detect the predator’s presence by sensing cues released by the predator (Turner & Peacor, 2012). The detectability of cues is ultimately based on the types of cues produced and their transmission throughout the environment (Atema, 1988;
Bouwma & Hazlett, 2001; Moore & Crimaldi, 2004). Predator attributes can influence the types of signals that are released into the environment (Persons & Rypstra, 2001). Larger predators may produce cues that are greater in magnitude and thus more likely to be detected by prey (Hill
& Weissburg, 2013). Different predators release cues of varying quality and composition, and prey will not respond the same way to two predators of different species (Turner et al. 1999).
There is also variation within and among prey species in their ability to detect predatory stimuli.
If the intensity and composition of the cue is sufficient to exceed the sensory threshold for a given prey, then the animal will respond to the cue, and attempt to avoid the predator. In aquatic environments, most predator-prey interactions and NCEs are mediated through chemical signals
(Brönmark & Hansson, 2000; Hay & Kubanek, 2002, Derby & Sorenson, 2008).
Crayfish are ideal model organisms for testing the indirect effects of predator odors in aquatic environments because crayfish are highly sensitive to olfactory stimuli (Hazlett &
Schoolmaster, 1998; Keller et al., 2005; Gherardi et al., 2011). Adult crayfish also feed primarily ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 14 on macrophytes (Hogger, 1988). Crayfish are known to severely impact the density and diversity of macrophyte beds when their foraging is unchecked by natural predators (Lodge et al., 1994;
Feminella & Resh, 1989; Carreira et al., 2017). Thus, predators must have an important influence on crayfish behavior and population dynamics in locations where stable populations of crayfish and macrophytes coexist. We hypothesize that the consumption of macrophyte biomass by crayfish will be reduced in the presence of predatory threats. This effect will be mediated by a reduction in foraging effort by the crayfish under threat conditions.
Crayfish are also known to be selective in the herbivory component of their diet
(Nystrom & Strand, 1996; Cronin et al., 2002, Carreira et al., 2014). Plants with low concentrations of phenolic compounds are preferred by crayfish over those with greater phenolic content (Bolser et al., 1998) Over time, selective grazing by crayfish may reduce the abundance of their preferred macrophyte species, replacing them with species that are not commonly grazed
(Parsons et al., 1991; Moretto & Distel, 1999; Carreira et al., 2014). However, if crayfish shift their dietary preferences for different macrophytes under threat of predation, then the presence of threats would indirectly affect the distribution and diversity of macrophyte species in aquatic habitats (Rodríguez et al., 2005). Previous work in a variety of other animals show changes in food preferences under threating conditions as reviewed in Lima & Dill (1990). Such a disturbance could result in significant changes in aquatic habitat structure and the complexity of the environment because macrophytes are diverse in their shapes and forms (Taniguchi et al.,
2003; Warfe & Barmuta, 2006). Thus, we hypothesize that crayfish will focus their foraging effort on more preferred macrophyte species when threatened, resulting in larger differences in biomass loss between macrophyte species ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 15
Methods
Collection and Housing of Crayfish, Bass, and Aquatic Plants
A total of 160 form II (non-reproductive) female rusty crayfish (F. rusticus) were collected from Maple Bay of Burt Lake, in Cheboygan County, Michigan (45.4873ºN,
84.7065ºW). All crayfish (post orbital length 3.21 ± 0.02 cm [mean ± SEM]) had intact appendages and were free of any visible signs of disease. The crayfish were held in a flow through stock tank (200 x 60 x 60 cm: l x w x d) filled with 640 l of water from the Maple River filtered through elastic nylon mesh. Crayfish were allowed to feed on natural detritus in the stock tank from the river water. Twenty short PVC pipe sections provided shelter for crayfish in the stock tank. Before use in a trial, crayfish were marked with an identifying symbol drawn in non- toxic white-out pen (BIC® Wite-Out® Shake 'N Squeeze™ Correction Pens). Each crayfish was only used in a single trial.
Largemouth Bass (M. salmoides) were utilized as a source of predator odor. Forty-eight bass (total length = 15.86 ± 0.20 cm [mean ± SEM]) were purchased from Harrietta Hills Trout
Farm LLC, in Harrietta Hills, Michigan. The bass were maintained in an identical, but separate
640 L flow through stock tank (200 x 60 x 60 cm: l x w x d) filled with water from the Maple
River at a density of approximately one bass per 13 l. The stock tank was divided in half by a plastic egg crating partition so that bass used in previous trials could be separated from unused bass. Given the number of trials and number of bass, some individual bass were reused. Any individual bass was not used in more than two trials, with a minimum of 24 hours between uses.
Bass were fed pellets made by pulverizing whole frozen rusty crayfish in a coffee grinder. The resulting crayfish slurry was then partitioned into approximately 0.5 ml portions before freezing. The frozen pellets were offered once daily at a rate of one pellet per bass, by ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 16
broadcasting into the stock tank. All bass were fed a diet of crayfish pellets for at least two days
before use in any trials. Feeding of a conspecific prey diet was intended to increase the threat
strength of the predator odor stimulus (Weissburg et al., 2016; Turner, 2008; Chivers et al.,
1996).
Three species of aquatic plants including American waterweed (E. canadensis,),
muskgrass (Chara spp.), and northern watermilfoil (M. exalbescens) were collected from South
Fishtail Bay of Douglas Lake, in Cheboygan County, Michigan (45.5618°N, 84.6762°W). Plants were collected by casting a macrophyte sampling rake from a boat into submerged vegetation mats. The macrophytes were stored until needed in three 100 l flow-through plastic drums fed with unfiltered water from the Maple River. The macrophyte storage drums were situated outdoors in direct sunlight, away from any overhead cover to prevent shading of plants. Plants were maintained from June 23, 2017 until August 12, 2017. All five species (bass, crayfish, macrophytes) are quite common in this part of the Midwest of the United States and co-occur across a wide diversity of habitats.
Experimental Design and Arenas
The experiment followed a 2 x 2 fully factorial design with bass presence or absence as the first factor and crayfish presence or absence as the second factor. A total of n = 80 trials were run across four different treatments. All three macrophyte species were present in every trial.
There were n = 20 control trials which included no animals, n = 20 trials including only bass, n =
20 trials including only crayfish, and n = 20 trials with both bass and crayfish present.
Eight identical flow-through stream mesocosms (200 x 60 x 25 cm: l x w x d) were constructed from cinderblocks, lined with 0.1 ml thick plastic sheeting and 5 cm of gravel substrate at the University of Michigan Biological Station Stream Research Facility in Pellston, ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 17
Michigan. Mesocosms were fed from 208 l plastic drums functioning as constant head tanks
filled with filtered water from the Maple River. Water from the head tanks was delivered to the
mesocosms through two 10 mm diameter garden hoses per mesocosm, each regulated by a spigot
at the head tank (flow rate = 0.26 ± 0.01 l s-1 [mean ± SEM]). Each mesocosm was further
divided in half by a screened opening in a partial wall that permitted water flow but inhibited
animal movement. The two halves were defined as the predator section and the crayfish section
(Figure 1). The predator sections (80 x 60 x 25 cm: l x w x d) received the inflow water directly
from the head tank hoses.
The crayfish sections (100 x 60 x 25 cm: l x w x d) were filled with water flowing
through the screened wall from the predator section. The crayfish sections also contained four
PVC half-pipe shelters (10 x 8.5 x 4 cm: l x w x d) placed at the down current end. Similar
shelters have been used in other crayfish behavior studies (Chibucos et al., 2015; Jurcak &
Moore, 2014). A screened opening at the down current end of the crayfish sections allowed
water to flow out of the system and back to the Maple River.
Treatments were alternated amongst the eight mesocosms such that each mesocosm
produced a roughly equal number of trials for every treatment type. The systems are flow
through and any odors present from a previous trial are naturally flushed overnight. Based on the
flow velocity and the volume of the mesocosms, water turnover in each stream occurs in
approximately17 minutes.
An infrared DVR security camera (Swann SWDVK-430004) was mounted above each of the eight mesocosms to capture the nocturnal behaviors of crayfish. The mesocosms were illuminated from above with low intensity, red filtered light bulbs. A black utility tarp awning (9 x 6 m) covered all eight of the experimental mesocosms. The awning limited direct overhead ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 18
sunlight exposure and prevented surface disturbance during rain events. Sunlight entered the
system at the sides of the tanks. The awning also served to shield video cameras and lighting
equipment from weather and from glare by moonlight and starlight.
Experimental Protocol
Experimental trials began June 27th, 2017 and were concluded on August 14th, 2017. All
trials lasted 48 hours in duration. Setup began at approximately 8:00 AM on the first day of a
trial and was completed by 2:00 PM. On the second day of the trial, the mesocosms were only
disturbed briefly to remove detritus from the screens of the dividing wall and outflow openings
(detritus was removed once daily in all mesocosms). Trials were dismantled beginning at 8:00
AM and completed by 11:30 AM on the third day of the trial.
In trials that included predator odor, two bass were placed into the predator section of
each mesocosm. The bass were placed in the predator sections at least two hours before the
crayfish were introduced to the crayfish sections. Introduction of bass into the mesocosms
allowed the crayfish sections to fill with water containing bass odor before crayfish were
introduced, so that there would not be any delay in odor exposure.
Only visually fresh macrophyte samples were selected from the storage system to reduce any effect of plant condition on herbivore preference. Macrophyte samples were selected that showed bright coloration and fullness of leaf structure. Three 25 cm length stems of each macrophyte species were utilized per trial. Surface water was removed from the macrophyte stems using a salad spinner. This device uses centrifugal force to throw water from the surfaces of vegetation. After drying, each set of macrophyte stems were weighed to the nearest 0.01 g.
Each macrophyte stem was attached to a glass stir rod (25 x 0.6 cm: l x dia.) with 26- gauge green-painted steel floral wire. Three stir rods, one for each plant species, were then ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 19 attached to a hardware cloth bracket (24 x 19 cm: l x w). The positions of each macrophyte species on a bracket were rotated to prevent any false preferences related to plant position. Three plant brackets were then placed into the up current third of each crayfish section, directly onto the substrate. The configuration of the brackets within the crayfish section was rotated between trials to reduce any feeding bias caused by the location of plant samples in the arena (Figure 2).
Attaching the macrophyte samples to brackets prevents the tissue samples from floating away from the crayfish and it also prevents the crayfish from dragging the samples into the shelter zone to feed.
Four crayfish were selected from their holding tank for use in each trial that included crayfish presence as a factor. The post orbital carapace length of each crayfish was measured to the nearest 0.5 mm. Each crayfish was marked for individual identification and added to the crayfish section of the mesocosm.
During trials involving crayfish, overhead video cameras recorded the nocturnal behaviors of the crayfish for four hours each night. The cameras began recording at 0000 and stopped at 0400 each night, thus recording a total eight hours of video per trial in two four-hour blocks.
After the 48-hour trials were complete all crayfish were removed from the system. The crayfish were then euthanized by freezing. The macrophyte samples were removed from the streams and surface dried in the salad spinner before weighing a second time. All macrophyte samples were flash frozen with liquid nitrogen and were stored in a freezer at -80 °C. A subset of the macrophyte samples (n = 5 per treatment) were randomly selected for total phenolic content analysis using the Folin-Ciocalteu method (Folin & Ciocalteu, 1927). This technique uses colorimetry to analyze methanol extracts of freeze-dried plant tissues that have been treated with ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 20
Folin’s phenol reagent against a gallic acid standard. Previous research has shown that plant derived phenolic compounds deter herbivory by crayfish (Bolser et al. 1998).
Data Collection
The masses of plant tissue samples for each macrophyte species were recorded before and after the 48-hour duration of each trial. To quantify changes in macrophyte biomass, the mass of each sample after the trial period was subtracted from its initial mass before the trial.
These differences were then normalized by the initial mass to calculate a percentage of biomass change.
Percent Biomass Change = ((Wf – Wi) / Wi ) * 100
Where Wi is the initial mass of three stems of one macrophyte species used in a single trial and Wf is the final mass of the same three macrophyte stems at the end of the trial. Positive percentages would indicate an increase in biomass, while negative percentages would indicate a loss of biomass. Using this technique, we do not assume that autogenic plant growth is the same across treatment conditions which may cause plants to grow at different rates from controls due to grazing pressure or the presence of nutrients released by animals in the system.
The overall nocturnal activity of the crayfish was examined in an effort to assess how the presence of bass altered their behavior. Video recordings were manually scored for behaviors by a reviewer blind to the treatment. Two separate behaviors were recorded for the crayfish: foraging and shelter use. A crayfish was scored as either foraging or using shelters when and only when the entire marker (located on its carapace) was within the foraging zone or shelter zone (Figure 1). Given the clarity limitations of the overhead camera, we are uncertain of whether the crayfish is actually foraging while in the foraging zone. So, for ease of ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 21
communication, we are defining the term foraging as when the animal was present in the zone
with the plants.
From this analysis, a total of four different behavioral measures are recorded: time in
foraging zone, transition into or out of foraging zone, time in shelter zone, transition into or out
of shelter zone. Transitions into or out of zones were chosen as a proxy for overall activity of the
crayfish.
From these initial behavioral measures, secondary behavioral measures were calculated
and used for statistical analysis. The total foraging effort was calculated by multiplying the time
spent foraging by the number of crayfish foraging. For example, if the total time that only one
crayfish was found within the foraging zone for a night was 90 minutes then that foraging effort
was 90 crayfish minutes. If the total time that two crayfish were found in the foraging zone was
15 minutes then that effort was 30 crayfish minutes. After these multiplications, the values were
summed to produce total foraging effort. This number was divided by 960 crayfish minutes. This
value (960 crayfish minutes) was the total maximum amount of foraging effort the four crayfish
could demonstrate (four hours x four crayfish). This final result produced a proportion of total
foraging effort. This proportion provides insight into how the population of crayfish responded to
the presence or absence of bass. Values for total sheltering effort were calculated in the same
manner as total foraging effort.
Statistical Analysis
Changes in plant biomass (percent biomass loss) were analyzed using a non-linear mixed model in R (R Core Team, 2018; Bates et al., 2015). The plant biomass model was constructed with full interactions using three fixed factors (bass treatment, crayfish treatment, and macrophyte species) and two random factors (trial number and mesocosm). The trial number as a ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 22
random factor accounted for the interdependence of the macrophyte species and the mesocosm
account for the different mesocosm effects. When significant differences were found with the
interaction terms, differential contrasts were used with a Tukey-HSD post-hoc test to determine
where significant differences existed (R Core Team, 2018; Hothorn et al., 2008).
A three-way analysis of variance was used to test the effects of crayfish presence or
absence, bass presence or absence, and plant species on the total phenolic content of a subset of
macrophyte samples (R Core Team, 2018). A Tukey-HSD post-hoc test was used to determine
which groups were significantly different (R Core Team, 2018; Hothorn et al., 2008).
The crayfish behavior data was analyzed similarly to the changes in plant biomass. A
non-linear mixed model analysis in R was performed with two fixed effects (bass treatment and trial night) and two random factors (trial number and mesocosm). Significant differences in interactions terms were found using a Tukey-HSD post-hoc test (R Core Team, 2018; Bates et al., 2015; Hothorn et al., 2008).
Ethical Approval
All bass were maintained following established animal care and use procedures. Use of animals in this experiment was approved by the Institutional Care and Use Committees at
Bowling Green State University (Protocol: 856543-5) and the University of Michigan (Protocol:
PRO00006840). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 23
Figure 1. Experimental Mesocosm
Filtered river water enters from a constant head tank through the inflow hoses on the left. Water resides temporarily in the predator section before flowing through a screened opening into the crayfish section. Water then flows out of the screened outflow on the right. The boxes outlined with dashes define the boundaries of the plant resource zone (gridded area) and the shelter zone
(white boxed area).
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 24
Figure 2. Plant Resource Zone Example
The illustration above demonstrates one of three possible arrangements of macrophyte stems
offered in the plant resource zone during a trial. Starting on the left, the first bracket shows M.
exalbescens, E. canadensis, and Chara spp. The second bracket shows a shift in the order, E.
canadensis, Chara spp., and M. exalbescens. The third bracket shows Chara spp., M. exalbescens, and E. canadensis. The three wire brackets can be reordered to give two additional
arrangements of plant species. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 25
Results
Macrophyte Consumption
There was an overall interaction effect of bass presence or absence, crayfish presence or absence, and macrophyte species on changes in plant biomass (F(2, 152, 0.05) = 5.202, p = 0.007).
Comparisons of biomass changes within macrophyte species across treatments indicates that crayfish consumed significantly more of E. canadensis when odors from the bass were
present (Tukey-HSD test, p < 0.001; Figure 3, left panel; Table 1, top left). The biomass of
Chara spp. was also reduced a marginally significant amount by crayfish grazing when bass
odors were present compared to trials without bass odors (Tukey-HSD test, p = 0.058; Figure 3,
center panel; Table 1, top center). M. exalbescens did not show a significant difference in biomass consumption by crayfish under bass present or bass absent conditions (Tukey-HSD test, p = 0.99; Figure 3, right panel; Table 1, top right).
When crayfish consumption of macrophytes was compared across species, crayfish did consume a significantly greater percentage of E. canadensis than M. exalbescens in bass odor present trials (Tukey-HSD test, p < 0.001; Table 1, bottom center). The crayfish also consumed a significantly greater percentage of Chara spp. biomass than M. exalbescens when bass odors were present (Tukey-HSD test, p < 0.001; Table 1, bottom right). However, crayfish did not consume significantly different percentages of the biomass of E. canadensis and Chara spp.
(Tukey-HSD test, p = 0.99; Table 1, bottom left).
Plant species had a significant effect on the total phenolic content of the macrophyte samples tested (three-way ANOVA, p < 0.001). The mean total phenolic content of M. exalbescens across all treatments was 11.26 mg g-1 in gallic acid equivalents. M. exalbescens
contained significantly more phenolics than either E. canadensis or Chara spp. (Tukey-HSD test, ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 26
p < 0.001 and p < 0.001, respectively). The mean total phenolic content of E. canadensis was
1.88 mg g-1 in gallic acid equivalents. The mean total phenolic content for Chara spp. was 0.34
mg g-1 in gallic acid equivalents. There was no significant difference in the phenolic content of
E. canadensis and Chara spp. (Tukey-HSD test, p = 0.468).
Crayfish Behavior
There was a significant effect of bass presence on the number of crayfish transitions into and out of the plant and shelter resource zones (linear mixed model fit by REML, p = 0.023).
The number of transitions between the resource zones decreased from an average of 232 transitions per night without bass to an average of 190 transitions per night with bass present. A significant effect of night of observation was also detected on the number of transitions. Crayfish crossed the boundaries of the resource zones significantly more on the first night of the trial
(mean = 232 transitions) than on the second night of the trial (mean = 190 transitions).
Crayfish displayed a marginally greater percentage of total foraging effort when bass were present as opposed to when bass were absent (Tukey-HSD test, p = 0.051: Figure 4, left panel). Crayfish significantly decreased the percentage of total shelter use when bass were present as opposed to when bass were absent (Tukey-HSD test, p < 0.005: Figure 5, left panel). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 27
Figure 3. Effects of Crayfish Grazing and Bass Odor on Macrophyte Biomass
Percent change in macrophyte biomass (mean ± SEM) resulting from crayfish absence (black closed squares) and crayfish presence (gray closed circles). The left two points in each plot indicate trials with bass absent and the right two points are trials with bass present. Points labeled with different letters indicate a significant difference resulting from a linear mixed model analysis followed by a Tukey-HSD post-hoc test (p < 0.05). †Note: see Table 1 for within species comparison for Chara spp.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 28
Table 1
Effects of Predator Odor on Macrophyte Consumption
Within Species Comparison
Bass Odor Elodea vs. Elodea Chara vs. Chara Milfoil vs Milfoil
Absent vs. Present p < 0.001 p = 0.05822 p = 0.99990
Across Species Comparison
Bass Odor Elodea vs. Chara Milfoil vs. Elodea Milfoil vs. Chara
Present vs. Present p = 0.99998 p < 0.001 p < 0.001
Notes. The top table displays within species p values from TukeyHSD multiple comparisons
following a linear mixed model analysis. These comparisons demonstrate changes in the
consumption of each macrophyte species between predator absent and predator present
conditions. The bottom table displays across species p values from TukeyHSD multiple
comparisons following a linear mixed model analysis. These comparisons demonstrate
changes in the relative percentage of each macrophyte species consumed under the influence
of the predator.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 29
Figure 4. Bass Odor Influence on Crayfish Foraging Behavior
Effects of bass absence (black) and presence (gray) on total foraging effort (mean ± SEM: p =
0.0518). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 30
Figure 5. Bass Odor Influence on Crayfish Sheltering Behavior
Effects of bass absence (black) and presence (gray) on total sheltering effort (mean ± SEM: p <
0.005). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 31
Discussion
Effect of Predator Odor on Macrophyte Consumption by Crayfish
The findings from this study clearly demonstrate that crayfish herbivory was heavily
modified by the presence of predatory cues. This is seen in the increased consumption of
macrophytes when fish were present in the trials. In addition, crayfish became more selective in
their herbivory when predatory cues were present. Crayfish consumed significantly greater
percentages of E. canadensis and Chara spp. biomass as opposed to M. exalbescens in trials when bass were present. The mechanism that underlies both the increased herbivory and change in selectivity of consumption appears to be alterations in foraging behavior. In the presence of predatory odor, crayfish significantly decreased their movements between resource zones, while increasing the amount of time spent in the foraging zone of the mesocosm. Crayfish also significantly decreased the time spent in the shelter zone when predator odors were present. The findings of increased foraging behaviors and decreased shelter use under threat are contrary to our hypotheses and contrast with many prior findings in the literature. However, the decrease in overall activity and the change in macrophyte preferences under threat were expected.
Animals responding to predatory threats are known to show elevated stress, evidenced by increased stress hormone levels (Barton, 2002; Pauwels et al., 2005; Sheriff et al., 2009). It is possible that the metabolic cost of stress responses requires an increase in food consumption
(Hawlena & Schmitz, 2010). Thus, crayfish could be feeding more because of the metabolic cost of physiologic stress imposed by the predator. Some animals respond to NCEs by altering their morphology to make themselves more difficult for predators to consume (Brönmark & Miner,
1992; Tollrian, 1995). Despite the time involved in morphological changes, this response can reduce the likelihood of predation in the future (Nilsson et al., 1995). Largemouth bass are gape- ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 32 limited predators and increased foraging in crayfish may be an attempt to accelerate growth in order to escape the gape limitation of a potential predator (Hambright, 1991; Urban, 2007).
Finally, the crayfish in our system are only being exposed to chemical stimuli. The presence of both mechanical and visual stimuli, along with chemical stimuli, may produce different foraging and shelter use results. Regardless of the mechanism driving changes in crayfish behavior, the differences in the increased foraging effort as well as the change in selectivity of the consumption of macrophytes could lead to changes in the macrophyte communities of streams.
Consequences for Aquatic Systems
Increased grazing pressure by crayfish under threat of predation will have a negative influence on the biomass of macrophytes in aquatic habitats. Macrophytes comprise the bulk of the diet in adult crayfish (Abrahamsson, 1966; Hogger, 1988) and the effects of increased grazing pressure from crayfish invasions are known to greatly reduce the biomass of macrophyte communities (Lodge & Lorman, 1987; Feminella & Resh, 1989; Gherardi & Acquistapace,
2007;). Similar losses of biomass might be expected if crayfish increase their consumption of macrophytes in response to predatory stimuli. Crayfish in the current study consumed nearly double the plant biomass when predators were present. Such significant reductions in macrophyte biomass would result in the loss of a key food resource for many herbivorous invertebrates, fish, and waterfowl as reviewed by Lodge (1991). Macrophytes also provide surface area for colonization by epiphytic algae, bacteria, and protists, which are key food resources for many aquatic invertebrates (Soszka, 1975). Decreased macrophyte abundance could change ecological interactions within the community of epiphyton feeding fauna (Gresens,
1995; Wallace & Webster, 1996; Brönmark, 1990). Reduced area for epiphyton grazing would increase competition between aquatic herbivores, which are known to compete through ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 33 exploitation and interference for epiphyton resources (Lamberti et al., 1987; Gresens, 1995).
Macrophyte losses that translate to reductions in macroinvertebrate abundance will have ripple effects throughout other trophic levels (Brönmark & Weisner, 1992). Populations of species using macrophytes for habitat and refuge may have to relocate to find suitable habitat elsewhere
(Wolcox & Meeker, 1992). In addition to increased grazing by crayfish, the present study found changes in selectivity of that grazing which produces changes in relative abundance that alter macrophyte community diversity.
Crayfish are known to be selective in the herbivory component of their diet (Chambers et al., 1991; Nystrom & Strand, 1996; Cronin et al., 2002). Uneven consumption of macrophytes under threat of predation may lead to shifts in relative abundances due to increased herbivory pressure on preferred species. Changes in macrophyte diversity have the potential to alter the effectiveness of ecosystem services provided by littoral zone macrophyte communities
(Carpenter & Lodge, 1986) especially through changes in spatial heterogeneity of macrophyte bed habitats. Spatial heterogeneity is an important component of habitat quality in aquatic environments, which contributes to the diversity of animals a habitat can support (Pianka, 1966;
Heck & Crowder, 1991). For example, benthic mats of Chara spp. often support a higher abundance of macroinvertebrates than vascular aquatic plants do (Waters & San Giovanni,
2002). These mats of vegetation grow in shallow water, are dense, and highly complex, thus providing a good refuge from predators while also allowing access to accumulated detritus and
Chara spp. tissue as food resources.
The observed changes in either macrophyte abundance or diversity are a result of a negative indirect effect of an aquatic predator on macrophyte communities. Typically, non- consumptive effects of predators have been found to reduce the impact of foraging by prey ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 34
(Lima & Dill, 1990; Turner & Mittelbach, 1990; Fortin et al., 2004). These reductions in foraging drive the indirect effects of predator presence on the plant community. For example, In coastal marine environments, the presence of predatory crabs (Carcinus maenas) in coastal marine environments has been shown to reduce grazing pressure on fucoid algae (Ascophyllum nodosum) by snails (Littorina littorea), allowing increased algal growth (Trussell et al., 2017).
However, in the present study, the direct observations of increased macrophyte consumption under threat of predation suggest that more complicated interactions may be at play, at least in this system.
The appearance of macrophyte preferences by crayfish under predation threat implies that the non-consumptive effect of the predator alters the perceived value of each macrophyte as a food resource. Other studies have found that prey will switch their food preferences under threat to either recoup energetic costs or reduce handling time (Hay & Fuller, 1981; Lima & Dill, 1990;
Schmitz et al., 1997). Although not directly measured here, changes in foraging choices may be based on differences in plant morphology, nutritional content, and/or buoyancy (Chambers et al.,
1991; Lodge, 1991; Cronin et al., 2002). Thus, handling time may carry more weight for crayfish foraging decisions under predation threats. Physiological changes, such as plant defensive chemicals, may also be involved in the choice. Crayfish are known to prefer plants with lower noxious chemical content (Chambers et al., 1991; Bolser et al., 1998; Cronin et al., 2002). In the present study, chemical analyses for total phenolic content were performed on a small subset of the macrophyte samples (n = 5). M. exalbescens showed significantly higher phenolic content in control treatments than either E. canadensis or Chara spp. Despite the lack of any systematic changes in plant phenolics in any of the bass or crayfish treatments, the greater loss of biomass ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 35 seen in the two plant species with lower phenolic content may be evidence that crayfish are using the concentration of phenolics to make foraging decisions in the presence of predatory odors.
Conclusions
The responses of prey species to predator stimuli are complex and difficult to predict.
The increase in foraging activity and plant consumption by crayfish in this study did not match our predictions. The results do provide insight into how the presence of aquatic predators can have indirect effects on macrophyte communities, thus linking two trophic levels that typically do not interact directly (Abrams, 1995). In streams where both crayfish and bass are present, the abundance of macrophytes is likely to be reduced, causing a loss in valuable food resources and refugia for other invertebrates, fishes, waterfowl, and mammals. However, reductions in macrophyte abundance may be beneficial to stream life if macrophyte stands become too large or too dense. The appearance of foraging preferences under threat of predation also changes the way that predators and prey interact with other species in the community. If a predatory threat causes crayfish to focus their foraging efforts on E. canadensis and Chara spp. in streams, the growth of other macrophyte species responding to the selective grazing might alter the diversity of the macrophyte community. Macrophyte diversity is especially important in stream environments because of the high degree of interconnectivity between species found there
(Brown et al., 2011). Crayfish function as keystone species in aquatic environments (Crandall &
Buhay, 2008) and can thus produce disproportionately large changes in community structure when their behavior or abundance is altered. Understanding the nuances of predator-prey interactions is vital to our ability to predict the outcome of human manipulations of stream environments and to better inform our conservation and management efforts. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 36
CHAPTER III: BIG AND BAD: HOW RELATIVE PREDATOR SIZE AND DIETARY
INFORMATION INFLUENCE CRAYFISH BEHAVIOR AND RESOURCE USE
DECISIONS.
This article was published in the Canadian Journal of Zoology, volume 98, issue 1,
January 2020. The journal had given permission for the work to be submitted as part of this
dissertation.
The nonlethal effects of predators on prey can alter behavior which can cascade to lower trophic levels. These trophic cascades can be important in structuring ecological communities
(Abrams 1995; Werner and Peacor 2003; Schmitz et al. 2015). The behavioral responses of prey to predators often involve changes in the time they spend foraging or in shelter (Gotceitas 1990;
Pirtle et al. 2012). Prey species may modify their mating activities under threatening conditions as well (Sih et al. 1990; Bierbach et al. 2011). Due to the complex nature of prey responses to predatory threats, Parsons et al. (2018) specifically called for future studies to examine multiple responses of prey which include simultaneous assessments of food consumption and video recordings of prey behavior. The foraging and shelter use behaviors of prey are of great interest to ecologists because changes in these behaviors can strongly influence interactions between prey and other species in the community (Preisser et al. 2005).
Trait mediated indirect interactions occur when the presence of predator cues cause prey to alter their behavior in a way that changes the abundance of other species (Abrams 1995). For example, in the intertidal zone, the presence of predatory green crabs (Carcinus maenas
Linnaeus, 1758) causes their dogwhelk (Nucella lapillus Linnaeus, 1758) prey to reduce consumption of barnacles (Semibalanus balanoides Linnaeus, 1767) which quickly results in encrustation of intertidal rocks by the accumulating barnacles (Matassa and Trussell 2011). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 37
Similarly, the presence of senorita fish (Oxyjulis californica Günther, 1861) can release the feather boa kelp (Egregia menziesii Areschoug, 1876) from grazing pressure exerted by the seaweed limpet (Discurria insessa Hinds, 1842) which leads to greater kelp density and increased cover availability for other species (Haggerty et al. 2018). Changes in shelter use can also drive trait mediated indirect interactions by altering how much time animals have available to forage and where they are foraging. Bernot and Turner (2001) found that Physa integra
Haldeman, 1841 snails increased their time under cover when they were exposed to predatory sunfish (Lepomis gibbosus Linnaeus, 1758) and migrated to the water’s surface in the presence of cues from predatory crayfish (Faxonius rusticus Girard, 1852). The snails exposed to fish grazed heavily on periphyton in covered habitats while those exposed to crayfish only influenced periphyton on surfaces near the water’s edge (Bernot and Turner 2001). Each of these examples demonstrates a prey response to a threatening predator which initiated indirect effects between the prey and other species. These prey responses are the result of risk assessment, a strategy prey use to estimate the threat associated with a predator in order to limit unnecessary predator avoidance behaviors (Hegab et al. 2015).
Predators in the environment represent a spectrum of threats for any given prey species.
The assessment of risk associated with each predator becomes a key decision-making point for prey. The stakes are high for prey animals because unnecessary antipredator responses waste energy and lead to missed resource acquisition opportunities, while failure to avoid a dangerous predator often results in death (Brown et al. 2006). However, prey have the ability to assess or calculate the risk posed by potential predators by extracting relevant information from cues generated by the predators (Helfman 1989). Thus, risk assessment begins with the detection of predator cues via visual, vibratory, chemical, or other sensory modalities (Lima and Dill 1990; ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 38
Weissburg et al. 2014). Factors which influence the degree of threat that can be contained in
predatory cues include the predator’s proximity to the prey, its hunting strategy, relative body
size, dietary preferences, and motivational state (Helfman 1989; Kats and Dill 1998, Parsons et
al. 2018).
The relative body size of predators is also an important piece of information for threat
assessment. Many predators as diverse as filter feeding plankton, reef fishes, and shore birds are
selective about the sizes of the prey they consume (Hansen et al. 1994; Holmes and McCormick
2010; Rose et al. 2016). The range of prey sizes that a predator consumes is influenced by the
food value of prey items contrasted against the effort required to capture them (MacArthur and
Pianka 1966; Turesson et al. 2002) as well as by the morphological limitations of the predator
(Wankowski 1979; Shine and Sun 2003; Inoue et al. 2016). Morphological limitations of
predators include characteristics like the gape size of the predator (Hambright 1991), shape or
strength of teeth (Whitenack et al. 2011), or even the functionality of a straining apparatus
(Werth and Potvin 2016). However, some of these morphological limitations can change with the
body size of the predator (Schmitt and Holbrook 1984; Scharf et al. 2000; Costa 2009). For
example, many predators that swallow whole prey have gape limitations which determine what
size prey they can consume (Nilsson and Brönmark 2000; Mihalitsis and Bellwood 2017). Hill et
al. (2004) determined that Largemouth Bass (Micropterus salmoides Lacépède, 1802) and peacock cichlids (Cichla ocellaris Bloch and Schneider, 1801) have very similar mouth geometry and gape to body size ratios. As these predators grow, the ratio of gape width to body length remains relatively constant within each species. Hill et al. (2004) also found that although these predators can consume prey up to 105% of their gape width, these species prefer to consume prey that are less than 96% of their gape width (Hill et al. 2004). Thus, for gape limited ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 39 predators, some prey are too small to be worth the capture effort, while others are too large to be consumed. It would be advantageous for prey to recognize the sizes of predators relative to themselves, so the prey can determine if they fall within an individual predator’s targeted size range. Some prey have adapted a response to gape limited predators which employs rapid growth to reach a size refuge where predators will not attempt to swallow them (Urban 2007).
Development of altered body morphologies to reach a size refuge has been observed in many taxa including mollusks, crustaceans, fishes, and amphibians (reviewed by Ferrari et al. 2010).
However, it is currently unknown how prey animals determine the relative size of a gape limited predator, to assess whether or not it poses a real threat of consumption. Prey could use information extracted from visual cues to discern the relative size of a predator, but many prey animals are nocturnal or live in visually complex or turbid environments where vision is of limited utility. However, a limited body of work suggests that prey can extract information about a predator’s relative size from chemical cues (Quirt and Lasenby 2002; Mathis 2003; Kusch et al.
2004).
Many prey animals rely heavily on chemoreception to obtain information from predator odors for risk assessment because much of the information about a predator is not easily conveyed by other stimuli (Ferrari et al. 2010). Chemical cues from predators enter the environment in the form of body odor, excrement, or territorial marking substances. These cues can have longer lasting impacts on prey behavior because chemical signals can linger within a habitat long after the predator has left (Turner and Montgomery 2003). In addition, the dispersion mechanics of chemical signals allow chemical signals to move where visual and acoustical signals may be blocked (i.e. dense foliage; Van Buskirk et al. 2014). The movements of predators and the distribution of their cues in the environment produce a sphere of influence, ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 40
where predator cues can impact the behavior of sensitive prey species (Turner and Montgomery
2003). The chemical cues generated by predators are based on the metabolism of the specific
predator and are dependent upon the recent diet of the predator (Weissburg et al. 2016). A robust
body of literature has demonstrated that prey animals are sensitive to dietary cues in predator
odors (Chivers and Mirza 2001a; Ferrari et al. 2010; Scherer and Smee 2016; Beattie and Moore
2018). Usually, prey show the strongest responses to dietary cues from predators that have
consumed conspecific prey animals (Chivers and Mirza 2001a). Yet, some prey animals respond
to dietary cues along a gradient of threat represented by the phylogenetic similarity between the
dietary cue and the prey (Schoeppner and Relyea 2005). Dietary cues are an important part of a
predator’s odor signature, but researchers too often focus solely on the dietary components of
odor. If other information like the predator’s relative body size is contained in odor cues, then
size and dietary information may interact to provide prey with a more precise estimate of risk.
Under Helfman’s (1989) threat-sensitive predator avoidance hypothesis, prey should consider multiple factors to determine the threat a predator poses during risk assessment, in order to take action with an appropriate intensity that matches the perceived risk. Currently, how prey integrate both dietary and relative size cues using chemical cues emanating from predators to assess threats in their environment is unknown. Here, we studied the responses of rusty crayfish
(F. rusticus) to the odors of Largemouth Bass (M. salmoides) that were fed different diets while also varying the ratio of body size between the test crayfish and the predatory bass. A macrophyte feeding assay was used to examine food consumption, while video recordings revealed the time crayfish spent foraging and the time they spent in shelters while under threat.
Crayfish are ideal for this kind of research because they are highly sensitive to predator odor cues and can detect subtle changes in dietary cues (Jurcak and Moore 2018; Wood et al. 2018; ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 41
Beattie and Moore 2018). Adult crayfish feed heavily on macrophytes in the wild (Momot et al.
1978; Hogger 1988) and are known to strongly impact macrophyte communities when their grazing is not limited by predatory threats (Feminella and Resh 1989; Lodge et al. 1994; Carriera et al. 2017). Largemouth Bass are gape limited predators that are common across North America.
Bass commonly occur in the same water bodies as many crayfish species and crayfish are an important food source in the bass’ diet. If crayfish are exposed to odors representing different combinations of predator body size cues and dietary cues, then crayfish would be expected to alter their macrophyte consumption, foraging behavior, and shelter use.
Methods
Collection and Housing of Animals and Plants
Five hundred form two (non-reproductive) female rusty crayfish (F. rusticus) were captured from Maple Bay of Burt Lake in Cheboygan County, Michigan (45.4873ºN,
84.7065ºW). Only healthy individuals with all appendages intact were used in the experiments.
Crayfish that had missing appendages were used as donors to produce dietary cues. All F. rusticus were stored in a steel cattle tank (200 x 60 x 60 cm: l x w x d) modified to allow a constant volume of flowing water. The tank was filled with 640 l of water from the Maple River.
The unfiltered river water provided a source of natural detritus for the crayfish to feed upon.
Clay pot halves were available as shelters within the crayfish storage tank. The post orbital carapace length and maximum carapace width of each crayfish was measured to the nearest 0.5 mm before use in a trial. Crayfish were marked with a symbol before each trial using a non-toxic correction pen (BIC® Wite-Out® 2 in 1 Correction Fluid) to allow for identification of individuals. Wite-Out does not alter the behavior of crayfish (Fero and Moore 2008; Martin and ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 42
Moore 2008; Jurcak and Moore 2018). Individual crayfish were not reused following a successful trial and were frozen according to protocols.
Two additional crayfish species, the virile crayfish (Faxonius virilis Hagen, 1870) and the northern clearwater crayfish (Faxonius propinquus Girard, 1852), were collected for use as a food source, along with the F. rusticus, for the different predator diet treatments. Fifty F. virilis of mixed sex were captured from Maple Bay of Burt Lake in Cheboygan County, Michigan.
Fifty F. propinquus of mixed sex were captured from the East Branch of the Maple River in
Emmett County, Michigan (45.5644°N, 84.7514°W). These crayfish were frozen in the laboratory until they were needed as food. Freezing crayfish tissue does alter the chemistry of the chemical alarm cues present (Hazlett 1999), but crayfish still show measurable responses to these altered cues once they are released by a predator (Beattie and Moore 2018; Wood et al. 2018).
Largemouth Bass (M. salmoides) served as a source of predatory fish odor for the four different predator odor treatments. Fifty-six bass (123 to 183 mm total length) were divided evenly amongst three separate flow through steel cattle tanks (200 x 60 x 60 cm: l x w x d each) filled with 640 l of water from the Maple River. The water flowing into these tanks was filtered through 1 x 1 mm fiberglass mesh screening to prevent the introduction of crayfish or other large invertebrates. The screens over the bass tanks also protected the fish from avian predators. Bass were measured for total length to the nearest millimeter on a fish board. The exterior width of each fish’s maxillary bones was measured with their mouth closed using calipers as an assessment of gape width (Lawrence, 1958).
Samples of American waterweed (Elodea canadensis), muskgrass (Chara spp.), and northern watermilfoil (Myriophyllum exalbescens) were collected from South Fishtail Bay of
Douglas Lake, in Cheboygan County, Michigan (45.5618°N, 84.6762°W). These macrophyte ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 43
species were chosen because they co-occur with the animal species tested throughout northern
Michigan. A macrophyte sampling rake was used to collect plants by casting the rake into mats
of submerged vegetation. Once collected, all macrophytes were stored in three 100 l flow
through drums filled with water from the Maple River. The plant storage drums were placed in
open sunlight to avoid shading by trees or artificial structures. A surplus of plant samples was
maintained from June 25th, 2018 until all trials were complete on August 14th, 2018.
Experimental Design and Arenas
To test the influence of predator dietary cues and relative sizes of predators and prey on grazing by F. rusticus, a tri-trophic system was used: bass (predators), crayfish (consumers), and macrophytes (producers) composed the trophic system. The experiment consisted of 10 different treatments which included a predator free control and four different predator diets applied across two different size classes of prey (Table 2). The crayfish in a trial were classified as vulnerable if the average carapace width of the four individuals was less than 96% of the average gape width of the two bass in the trial. Crayfish in a trial were classified as invulnerable when their average carapace width exceeded 96% of the predators’ average gape width. The predator free control consisted of plants and crayfish without the presence of predators. The four bass diet conditions consisted of placing two bass into the mesocosm after they had been fed a diet of fish pellets, F. rusticus pellets, F. virilis pellets, or F. propinquus pellets (diet production described below).
Table 2 shows the number of trials completed in each treatment.
Experimental Mesocosms
A series of eight flow through stream mesocosms (200 x 60 x 25 cm: l x w x d) were
constructed from cinderblocks and were lined with 0.1 mm thick plastic sheeting. This same
construction technique was used successfully by Wood et al. (2018). Two 208 l plastic drums ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 44 were filled with water from the Maple River and served as constant head tanks for the eight mesocosms. Each drum fed four mesocosms with water from two 10 mm diameter garden hoses per mesocosm (0.18 ± 0.02 l s-1 [mean ± SEM]). Each mesocosm (Figure 6) was divided into an upstream predator section (80 x 60 x 25 cm: l x w x d) and a downstream crayfish/macrophyte section (100 x 60 x 25 cm: l x w x d). Water from the head tanks flowed into the predator section of each mesocosm before passing through a screened opening (28 x 12 cm opening with 1 x 1 mm screening) in a partial wall into the adjoining crayfish section. The water would exit from the far end of the crayfish section through another screened opening. In the crayfish section a piece of black weed control fabric (100 x 60 cm: l x w) served as substrate on the bottom of the mesocosm. This material provided a dark background against which the crayfish could be easily observed in video recordings. Four PVC half-pipe shelters (10 x 8.5 x 4 cm: l x w x h) were placed near the down current end of the crayfish section.
An infrared DVR camera (Zosi ZR08ZN10) was mounted to a wooden frame 1.5 m from the water’s surface above each mesocosm to record the nocturnal behaviors of the crayfish. The mesocosms were illuminated with one low intensity red light bulb (Great Value brand: Model
A19045 LED Lamp, 9 W, 145 mA, 120 V, 60 Hz, RED) per stream. A large black utility tarp
(12 x 9 m) was used as an awning over all eight mesocosms to prevent weather and water damage to the cameras and lighting equipment. The tarp was left open 1.5 m on the eastern and western ends of the mesocosms to allow sunlight into the system. The tarp also eliminated glare on the recordings from moonlight and starlight. The flow rate of water through the mesocosm is low enough that it does not produce any distortion that is visible on the video recordings beyond the movement of small particles floating on the water’s surface.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 45
Diet Production
All feeding occurred in the housing tanks which were separate from the mesocosms. The
bass in each tank were fed a different diet in order to produce different odor signatures for the
experimental treatments. Fish in one tank received a commercial fish food diet (Allied Aqua®
Tilapia Fingerling Pellets). In the other tanks, fish were fed pellets made from pulverized
crayfish. The pellets were made by freezing 0.5 ml portions of slurry produced by pulverizing
frozen crayfish (either F. rusticus, F. virilis, or F. propinquus) in a coffee grinder (Hamilton
Beach, Model: 80335R). Food was offered once daily at a rate of one frozen pellet per fish or
approximately 1g of fish food per individual. All fish were fed a given diet for at least 48 hours
before use in any trials to flush any previous dietary cues from their system (Beattie and Moore
2018).
Experimental Protocol
Trials began June 26th, 2018 and were concluded on August 14th, 2018. Trials were run
for a total of 24 hours. For bass trials, two bass were placed into the bass sections of each
mesocosm at 0900 each morning. Mesocosms that were running control trials had no fish in the
bass section. Plant samples were then selected from their respective storage drums. Only brightly
colored and crisp textured plant samples were chosen for use in feeding trials. Three stems of
each macrophyte species were selected per trial. The stems were surface dried in a salad spinner
(Farberware Basics, Item No. 5158683) before weighing to the nearest 0.001 g. After weighing,
the plant stems were attached to glass rods (255 x 6 mm: l x OD) with 26-gauge green painted
floral wire. The rods were then placed into three hardware cloth brackets (24 x 19 cm: l x w) which were designed to hold the plant samples in position for the duration of the feeding trial
(Figure 7). The arrangement of the three plant stems attached to each bracket were rotated across ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 46
trials. Three brackets/plant stems were placed within each mesocosm and the relative positions of
each bracket/plant stem within the mesocosm were systematically altered to prevent any feeding
bias caused by plant sample location within the mesocosm. After the plant samples were placed
into the crayfish sections of the mesocosms, four F. rusticus crayfish were selected for each stream. Crayfish were placed into the crayfish sections at least two hours after bass were placed into the predator sections to allow the crayfish section to be filled with water containing predator odors and to remove any stress-based bass odors caused by handling of the fish. Given the flow rate provided by the head tanks, the water in each mesocosm is replaced once every 25 minutes.
After addition of the crayfish, the screened openings between the predator and crayfish section and at the outflow from the crayfish section were brushed to remove any debris that might inhibit flow.
Beginning at 2300 the red lights illuminating the mesocosms would turn on via an automatic light timer. Then at 0000 the cameras above each mesocosm would begin recording
the nocturnal behaviors of the crayfish. The cameras would finish recording at 0400, and the
lights would switch off at 0500 to ensure adequate lighting throughout the video recording.
The following morning, all crayfish were removed first from the mesocosms. Any trials
that were impacted by crayfish deaths, escapes, molting, or immigration were discarded (28 trials
were discarded). Once the crayfish were removed, the plant samples were removed from each
mesocosm and were dried in the salad spinner again before weighing a second time. After use in
a trial, fish were replaced into their respective diet tanks, behind a divider which separated
recently used individuals from those that were awaiting use. Each fish was used three to four
times. Once a trial cycle was complete, the mesocosms were allowed to flush overnight (at least ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 47
12 hours) before a new trial cycle began the next morning. Over this duration, the water in the
mesocosms would be replaced approximately 29 times.
Data Collection
Four hours of video per trial were scored by a viewer blind to treatment for total time spent by all crayfish in the foraging and shelter zones of the mesocosm. It was not possible to determine when the crayfish were actually feeding because the feeding appendages of crayfish are located on the underside of their bodies. Thus, crayfish were scored as foraging whenever the entire marker on their carapace was inside the foraging zone of the mesocosm (Figure 6).
Similarly, crayfish were scored as using shelter whenever the entire marker on the animal’s carapace was within the shelter zone (Figure 6). The number of times crayfish transitioned into and out of the two resource zones was also recorded from the videos.
Total macrophyte consumption (g) was calculated by subtracting the total mass of all three plant species after the trial from the initial total mass of the plants before the trial. The resulting difference was then divided by the initial total mass of the plants and multiplied by 100 to obtain the percent of macrophyte biomass that was either consumed or destroyed by the crayfishes’ foraging activity. Which we defined as total macrophyte consumption.
Total Macrophyte Consumption = ((ΣWi – ΣWf) / ΣWi ) * 100
To calculate the gape limit percentage, the carapace widths of each of the four crayfish in a trial
were divided by the gape widths of each of the two bass present in the trial. The eight resulting
ratios were then averaged to produce the gape limit percentage for each trial. Foraging effort was
calculated as the percent of the total time that crayfish spent in the foraging zone of the
mesocosm. Shelter use was calculated as the percent of the total time that crayfish spent in the ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 48
shelter zone of the mesocosm. The number of transitions was used as an estimate of overall
crayfish activity.
Ethical Approval
Largemouth Bass were maintained and handled following established animal care and use procedures. The use of vertebrate animals was approved by the Institutional Care and Use
Committees at Bowling Green State University (Protocol: 856543‐9) and the University of
Michigan (Protocol: PRO00006840).
Statistical Analysis
The total consumption of macrophytes was assessed using the “contrasts” and “aov”
functions to run an ANCOVA in the statistical program R (R Core Team 2019). The total
macrophyte consumption model was constructed with full interactions using one categorical
factor (predator dietary cue) and one continuous variable (gape limit percentage). When
significant differences were found with the interaction terms, a regression of macrophyte
consumption against the gape limit percentage was plotted for each of the predator dietary
treatments to visualize the combined effects of predator diet and relative predator size on
macrophyte consumption. Following the same procedure, ANCOVAs were also performed on
the foraging effort, shelter use, and transitions measures of crayfish behavior.
Table 2.
Number of Trials Performed in each Treatment
Crayfish Vulnerability Pellet Diet F. propinquus Diet F.virilis Diet F. rusticus Diet
Invulnerable 8 4 5 17
Vulnerable 14 18 17 5 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 49
Figure 6. Flow Through Stream Mesocosm
Water enters the predator section through hoses on the left. Two bass (M. salmoides) release
odors from their skin and excretions into the water as it flows through a screened opening into
the crayfish section. Water containing bass odor flows past the crayfish (F. rusticus) as they feed on macrophytes (M. exalbescens, E. canadensis, and Chara spp.) attached to wire brackets or
occupy shelter. The water then exits the crayfish section through a screened opening on the right
(Flow rate = 0.18 ± 0.02 l s-1 [mean ± SEM]). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 50
Figure 7. Macrophyte Feeding Brackets
One of three possible arrangements of macrophyte samples is shown. Macrophytes were wired to glass stir rods which were then attached to hardware cloth brackets. The arrangement of macrophyte species on each bracket was rotated and the positions of the brackets were also rotated between trials ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 51
Results
Macrophyte Consumption
A significant overall interaction effect of predator diet and gape limit percentage was observed on macrophyte consumption (F(3,80, 0.05) = 3.4732, p = 0.01984, Table 3). The regression plot for the pellet diet treatment shows increasing macrophyte consumption as the crayfish become larger relative to the bass (Figure 8, Upper Left Panel). The plot for the F. rusticus diet treatment illustrates decreasing consumption as the crayfish become relatively larger (Figure 8,
Upper Right Panel). The F. virilis diet treatment shows no change in macrophyte consumption across the range of gape limit percentages tested (Figure 8, Lower Left Panel). Crayfish that were large relative to the predators in the F. propinquus diet treatment consumed less macrophyte biomass than relatively small crayfish did.
Foraging Effort
The percent of time crayfish spent foraging was significantly influenced by an interaction effect of predator diet and gape limit percentage (F(3, 80, 0.05) = 2.7511, p = 0.048055, Table 4).
Crayfish exposed to predators fed a pellet diet showed a slight decrease in foraging effort as their size relative to the predators increased (Figure 9, Upper Left Panel). The plot of crayfish responses to the F. rusticus diet treatment indicates that foraging effort decreased as their relative size increased (Figure 9, Upper Right Panel). The responses of crayfish exposed to the F. virilis diet treatment follow the trend of decreasing foraging with increasing relative size (Figure 9,
Lower Left Panel). The largest change in foraging effort occurred in the F. propinquus dietary treatment, which also follows the trend of decreased foraging effort with increased relative size
(Figure 9, Lower Right Panel).
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 52
Shelter Use
Crayfish significantly altered their shelter use in response to an interaction effect of
predator diet and gape limit percentage (F(3, 80, 0.05) = 3.7797, p = 0.01365, Table 5). The percent of time crayfish spent in shelter decreased with increasing relative size when they were exposed to pellet based dietary cues (Figure 10, Upper Left Panel). Crayfish exposed to F. rusticus dietary cues also decreased their shelter use with increasing size relative to their predators
(Figure 10, Upper Right Panel). The plot of responses to F. virilis dietary cues indicates that crayfish increased their shelter use with increasing relative size (Figure 10, Lower Left Panel).
When crayfish were exposed to F. propinquus dietary cues, they showed the greatest increase in
shelter use with increasing size relative to their predators (Figure 10, Lower Right Panel).
Transitions
There were no significant effects of predator dietary cues, gape limit percentage, or any
interaction effect on the number of transitions crayfish made into and out of the foraging and
shelter resource zones.
Table 3.
Effect of Predator Diet and Gape Percentage on Total Consumption of Macrophytes
Model Terms F Value p Value
Main Effects: Diet F(3,80) = 3.1224 0.03048
Interaction Effects: Gape x Diet F(3,80) = 3.4732 0.01984
Notes. ANCOVA model and statistical outputs for the effect of predator diet and gape
percentage on total consumption of macrophytes. The model included an interaction term
between predator diet and gape percentage.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 53
Figure 8. Macrophyte Consumption
Each panel represents changes in the total macrophyte consumption of crayfish exposed to a different predator dietary cue, along a gradient of crayfish relative size to their predators, represented as gape limitation percentage. Black squares represent individual responses, the dashed line indicates a linear fitted model, and the gray zone is a 95% confidence interval around the linear model. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 54
Table 4.
Effect of Predator Diet and Gape Percentage on Total Foraging Effort
Model terms F Value p Value
Main Effect: Diet F(3,80) = 3.5904 0.017196
Main Effect: Gape F(1,80) = 32.2587 < 0.0001
Interaction Effect: Gape x Diet F(3,80) = 2.7511 0.048055
Notes. ANCOVA model and statistical outputs for the effect of predator diet and gape percentage on total foraging effort. The model included an interaction term between predator diet and gape percentage.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 55
Figure 9. Foraging Effort
Each panel represents changes in the total foraging effort of crayfish exposed to a different predator dietary cue, along a gradient of crayfish relative size to their predators, represented as gape limitation percentage. Black squares represent individual responses, the dashed line indicates a linear fitted model, and the gray zone is a 95% confidence interval around the linear model. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 56
Table 5.
Effect of Predator Diet and Gape Percentage on Total Shelter Use
Model Terms F Value p Value
Main Effect: Diet F(3,80) = 3.5455 0.01816
Main Effect: Gape F(1,80) = 3.2808 0.07385
Interaction Effect: Gape x Diet F(3,80) = 3.7797 0.01365
Notes. ANCOVA model and statistical outputs for the effect of predator diet and gape percentage on total shelter use. The model included an interaction term between predator diet and gape percentage.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 57
Figure 10. Shelter Use
Each panel represents changes in the total shelter use of crayfish exposed to a different predator dietary cue, along a gradient of crayfish relative size to their predators, represented as gape limitation percentage. Black squares represent individual responses, the dashed line indicates a linear fitted model, and the gray zone is a 95% confidence interval around the linear model. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 58
Discussion
Chemical Components of Threat
An interaction between dietary cues and relative size cues from M. salmoides produced a variety of responses in the macrophyte consumption, foraging effort, and shelter use behaviors of
F. rusticus crayfish. This relationship suggests that predator size and dietary information are used by crayfish to assess threats. Thus, crayfish are extracting multiple pieces of information from chemical cues which are combined to form a threat assessment.
The altered behaviors of crayfish in this study were consistent with previous findings that prey animals respond strongly to odors from predators that have recently consumed conspecific prey items (Laurila et al. 1997; Hoefler et al. 2012). Crayfish responses to dietary cues from bass should be similar because bass are generalist predators and crayfish should respond to them regardless of their dietary constituents (Bryer et al. 2001; Scherer and Smee 2016). However, the crayfish showed different behaviors across the various predator diets tested. The crayfish differentiated amongst dietary cues representing three closely related congeneric species. This result is similar to behaviors in tadpoles which indicate that they can also differentiate amongst dietary cues from closely related species in odors produced by dragonfly larvae (Schoeppner and
Relyea 2005).
A growing body of evidence suggests that some prey are highly sensitive to subtle differences in predator dietary cues (Parsons et al. 2018). Large and Smee (2010) showed that
Nucella Roding, 1798 snails could differentiate between sympatric intertidal zone predators like green crabs (C. maenas) and visiting predators like rock crabs (Cancer irroratus Say, 1817) or
Jonah crabs (Cancer borealis Stimpson, 1859) from the subtidal zone. Beattie and Moore (2018) demonstrated that F. rusticus crayfish increased shelter use in the presence of odors from ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 59
predators that were fed conspecifics versus congeneric F. virilis crayfish, regardless of whether
the predators were a familiar species (M. salmoides) or not (Oreochromis aureus Steindachner,
1864 × Oreochromis niloticus Linnaeus, 1758). Turner (2008) demonstrated that the snails
Helisoma trivolvis Say, 1817 and Physa gyrina Say, 1821 respond more strongly to odor cues
from predators that have consumed conspecifics than they do to dietary cues from closely related
congeneric species (Helisoma anceps Menke, 1830 and Physa acuta Draparnaud,1805 respectively). Sullivan et al. (2005) showed that red-backed salamanders (Plethodon cinereus
Green, 1818) respond differently to garter snakes (Thamnophis sirtalis Linnaeus, 1758) that have fed on red-backed salamanders from distinct populations. Such specificity does not have to be innate; many prey species can also learn to recognize subtly different predator odors (Ferrari et al. 2005; Brown and Chivers 2005). Mechanistically, prey responding to dietary cues in predator odors are likely detecting differences in the mixture of compounds that comprise the odor cue
(Apfelbach et al. 2015; Weissburg et al. 2016). The current study further illustrates the finely tuned abilities of prey animals to detect differences in predator odor cues. Dietary odor cues provide information which alerts prey to the predator’s history of consuming similar organisms.
However, dietary cues alone do not allow prey animals to determine if an individual predator is large enough to consume them, just other individuals of the same species.
The size of a predator influences the size of the prey they can consume. According to optimal foraging theory, for a given predator there exists a prey size class that can be captured efficiently and also provides sufficient calories to justify the pursuit (MacArthur and Pianka
1966). Large prey are energetically costly to subdue and may pose considerable risk of harm to a predator when the prey defend themselves. For example, juvenile blind snakes (Ramphotyphlops nigrescens Gray, 1845) consume a variety of ants, but they avoid bulldog ants (Myrmecia gulosa ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 60
Fabricius, 1775) until adulthood because these ants can kill or injure juvenile snakes (Webb and
Shine 1993). Similarly, predatory cod (Gadus macrocephalus Tilesius, 1810) are more likely to be attacked by one-year old red king crabs (Paralithodes camtschaticus Tilesius, 1815) than by young of the year crabs during predation attempts (Pirtle et al. 2012). Thus, predators should follow a size dependent functional response, where predators focus their efforts on prey that are the largest that they can safely handle and consume (Aljetlawi et al. 2004). Gape limitation is a characteristic of many predators that determines the upper size limit of the prey they can consume (Hambright 1991; Webb and Shine 1993). When a predator is gape limited, prey that possess an intermediate body dimension greater than the predator’s gape width are usually excluded from the predator’s diet and have reached a size refuge (Persson et al. 1996; Karpouzi and Stergiou 2003). However, the gape limitations of individual predators changes as they grow and increase in size (Luczkovich et al. 1995; Hill et al. 2004). Prey also grow over time and represent a moving target for gape limited predators. Thus, prey that grow faster than their predators have the advantage of staying ahead of the predator’s gape limitation (Nowlin et al.
2006). It is well known from research on Daphnia Müller, 1785 (Grant and Bayly 1981; Tollrain
1995) and many fish species including perch (Perca fluviatilis Linnaeus, 1758; Persson et al.
1996) and Crucian Carp (Carassius carassius Linnaeus, 1758; Brönmark and Miner 1992), that prey can alter their body morphology as they develop to reach a size refuge from predation.
However, behavioral and especially morphological responses are energetically costly to prey animals (Lima and Dill 1990; DeWitt 1998). Thus, there is selective pressure for individual prey to differentiate predators with gapes large enough to pose a real threat from those of smaller individuals that feed on similar prey species. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 61
The differences in crayfish behavior observed across a relative size gradient within each dietary treatment indicate that crayfish responses to predator cues depend on the size of the bass and crayfish concerned. In most cases, crayfish that were small relative to their predators consumed plants differently or used the foraging and shelter resource zones differently than crayfish that were large relative to their predators. Prey animals could determine the relative size of a predator using the concentration of odor cues, or differences in the chemical composition of the cue. In an aquatic system, a larger predator may release a greater quantity of odor into a given volume of water over the same time period, than a smaller predator would (Kusch et al.
2004). Odor concentration responses have been documented in rats, which increase their freezing responses as the concentration of TMT, a synthetic fear inducing chemical, is increased in their environment (Wallace and Rosen 2000). Kusch et al. (2004) demonstrated that minnows
(Pimephales promelas Rafinesque, 1820) increased the intensity of their response to pike (Esox lucius Linnaeus, 1758) odor as the concentration of pike odor was increased. Hegab et al. (2014) demonstrated that Brandt’s voles (Lasiopodomys brandtii Radde, 1861) were more averse to samples of fresh cat feces than they were to samples that had been aged one, two, or four days
(the aging reduces the concentration of odor presented by the sample). The rate at which predators consume prey changes as predators grow and their metabolic demands change
(Mittelbach 1981; Brown et al. 2004). Thus, predators at different life history stages or different sizes present different levels of threat (Simonis 2013).
Currently, whether the crayfish were responding to differences in the concentration of predator kairomones or if bass of different sizes produce unique chemical signals is unknown, but the crayfish appear to use relative size ratios to assess threats. Similarly, Johnson and Smee
(2012) found that small oysters produce less soft tissue and thicker shells in response to mud ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 62 crabs, but large oysters show no response to mud crabs. The prey in both scenarios seem to recognize odors of predators that are large enough to consume them as threatening and respond.
Regardless of the mechanism, the crayfish in the current study clearly have a finely tuned ability to assess predatory threats using odor cues. However, because the crayfish have this ability, they are subjected to non-consumptive effects of the predator’s presence, caused by the odor cues the predator produces. These NCEs have a number of ecologically important implications, especially because crayfish function as keystone species in many freshwater environments (Crandall and
Buhay 2007). Crayfish populations impact many different species in freshwater communities directly through predation and herbivory but also indirectly by altering organic matter processing rates, influencing habitat structure (via herbivory on aquatic plants) and the effects of bioturbation of sediments (Momot et al. 1978; Parkyn et al. 1997; Reynolds et al. 2013). As previous work has shown, NCEs in crayfish can cascade to produce trait-mediated indirect effects of the predator on community dynamics (Wood et al. 2018).
In a recent review by Parsons et al. (2018), the authors specifically highlight the need for future studies which examine prey responses to predator odor cues using video recordings of prey behavior combined with analysis of food consumption by the prey under threat conditions.
The current study is a positive step towards that goal, and our hope is that other researchers will adopt and further develop this model, as this method is a powerful tool for capturing prey responses to predator odors in a complicated multi-dimensional response space. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 63
Conclusions
Crayfish extract information from predator odors about the relative size of the predator and the contents of the predator’s diet. Then, crayfish use this information to assess the threat posed by the predator to change their behavior. Changes in the behavior of crayfish resulted in measurable impacts to the macrophyte community. The findings of this study and other recent works (Chivers et al. 2001b; Ferrari et al. 2009; Ferrari et al. 2010; Parsons et al. 2018) suggest that ecologists need to look beyond predator presence or absence in the environment to obtain a better understanding of threats from the prey’s perspective. Prey are sensitive to the various components of predator odor signatures, and changes in these components influence a finely tuned ability to assess threats, which in turn, elicits altered prey behavior (Parsons et al. 2018).
This concept is important because of the consequences that arise, not only for the predators and prey, but also for other species in the community that are influenced by the interaction. When predator cues cause prey to alter their behavior, the predator induces trait mediated indirect effects on other species in the community that interact with the prey (Abrams 1995; Werner and
Peacor 2003). A large body of work has explored the size dependent interactions between predators and prey, with much focus on the predator’s perspective. If we are to gain a more complete understanding of predator-prey interactions and their influence on community dynamics, then we must undertake significant efforts to increase our knowledge of threat assessments by prey, especially in the realm of size ratios between predators and prey. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 64
CHAPTER IV: FINE-TUNED RESPONSES TO CHEMICAL LANDSCAPES: CRAYFISH
USE PREDATOR ODOR TO ASSESS THREATS BASED ON RELATIVE SIZE RATIOS
This revised article was resubmitted to Ecosphere, March 2020.
Prey animals extract relevant information about predatory threats from the sensory landscape within their environment (Lima and Dill 1990; Wisenden 2000). This information is contained in a variety of sensory cues that are dispersed in a spatially and temporally heterogeneous fashion throughout their habitat (Brown et al. 1999; Laundré et al. 2001). The distribution of these sensory cues is a result of the movement of the predator and the physical processes that serve to move stimuli through habitats (Smee and Weissburg 2006). As a result of the detection of these stimuli, prey respond by altering their physiology, behavior, morphology, or life history (Lima and Dill 1990). Prey animals live in an ever-changing landscape filled with predator cues. The combination of the sensory landscape and the prey’s response to the information within that landscape has been termed the landscape of fear (Laundré et al. 2010).
In the conceptual theory of the landscape of fear, locations in the environment where sensory cues indicate a high degree of threat have greater risks and are avoided by prey (Lima and Bednekoff 1999). Other regions, where predatory cues indicate lower degrees of threat are frequently used by prey. Thus, the spatial distribution of predatory cues can cause shifts in prey locations within environments (Wirsing et al. 2010). In the classic example, wolf reintroductions into Yellowstone National Park (USA) caused elk to shift their foraging activities away from the lowlands into more upland habitats to avoid the risk of wolf predation (Ripple and Beschta
2003). The distribution of predator cues in space is determined largely by the terrain and complexity of the environment (Gaynor et al. 2019). Temporal variation in cue availability arises from the activity patterns of the predators (Palmer et al. 2017) and the persistence of cues ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 65
(especially of odors) in the environment (Turner and Montgomery 2003). Some prey animals
respond to temporal variation in predator cues by seeking shelter when the perceived risk of
predation is high and by taking advantage of periods of relative safety to forage and be active
(Lima and Bednekoff 1999). Under the risk allocation hypothesis, perceived risk is highest when
the predator is present and able to hunt effectively. However, for most predators, there are times
when the predator’s hunting effectiveness or activity is reduced in which prey can afford to take
risks to access resources. Ultimately, prey that change their behavior may avoid some predation
risk, but there are costs to being afraid.
Antipredator responses require that prey trade off time they could use to forage or find
mates in favor of vigilance behaviors or maneuvers to avoid predator encounters (Laundré et al.
2001). Prey also expend energy resources to escape predators and through the development of
defenses (Lima 1998). The benefit of safety leads to costs for prey including reduced growth or
reproductive output and missed opportunities to access resources (Preisser and Bolnick 2008).
Morphological defenses are often costly to produce and maintain (Steiner and Pfeiffer 2006). For instance, in crucian carp (Carassius carassius), a shallow streamlined body is the normal phenotype, while a deep body morphology confers a defense against gape limited pike (Esox lucius) (Brönmark and Miner 1992). However, under conditions of limited food availability, deep bodied carp only gain half as much mass over time as their shallow bodied competitors
(Pettersson and Brönmark 1997). Behavioral responses to predators are likewise costly for prey.
Daphnia exposed to fish odors use diel vertical migration to avoid predation. However, migrating Daphnia only grow a third as much as non-migrating populations that are not exposed to fish odors (Dawidowicz and Loose 1992). Foraging activity is also frequently traded for increased vigilance to improve awareness of potential threats. Increased vigilance is known, for ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 66 example, to reduce the feeding efficiencies of house sparrows (Passer domesticus), mallards
(Anas platyrhynchos) and African ungulates amongst other species (Studd et al. 1983; Illius and
Fitzgibbon 1994; Fritz et al. 2002). Thus, animals should use costly defensive strategies only when the benefits of survival outweigh the costs of lost foraging or mating opportunities. The ability to identify and respond to threatening predators while ignoring those that do not pose a threat, reduces the chance of unnecessary antipredator responses in prey (Kats and Dill, 1998).
Through risk assessment, prey can minimize the cost of defenses by adjusting their responses to the level of threat posed by individual predators (Helfman 1989; Lima and
Bednekoff 1999). For example, Western Mosquitofish (Gambusia affinis) respond in an additive fashion to Green Sunfish (Lepomis cyanellus) dietary and satiation cues (Smith and Belk 2001).
On a fine spatial scale, Trinidadian Guppies (Poecilia reticulata) performing predator inspection behaviors avoid the heads but not the bodies of their predators to reduce the chance of being ingested (Magurran and Seghers 1990). Such graded responses to predation risk require that prey extract more than just presence or absence information from predator cues (Lee et al. 2013).
The additional information prey use to assess the level of threat posed by a predator includes factors like predator identity, predator diet, predator size, etc. (Bishop and Brown 1992;
Chivers and Mirza 2001; Henry et al. 2010). The identity of a predator is important to prey because different predators employ attack strategies that carry different levels of risk. Miller et al. (2014) demonstrated that grasshoppers (Melanoplus femurrubrum) showed unique changes in their activity and habitat use in response to six species of spiders which use three different hunting modes. Prey use predator dietary cues to determine what the predator has eaten recently.
Predators that have recently consumed conspecifics or other closely related prey are often perceived as greater threats (Chivers and Mirza 2001). Tadpoles (Rhacophorus arboreus) ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 67 showed increased investment in antipredator defenses to dietary odors from predatory newts
(Cynops pyrrhogaster) that had been fed a diet of tadpoles when compared to odors from newts fed fish (Ramamonjisoa and Mori 2019). The size of predators also influences prey perceptions of risk. In Helfman’s (1989) classic study, he demonstrated that damselfish (Stegastes planifrons) avoided large predator models more than small models and the damselfish were more likely to continue non-avoidance behaviors in the presence of the smaller predator models. In several of the examples above, specific predator information is being extracted from predator odor cues. Animals that can use predator odors as a source of detailed information about the predator can obtain better assessments of risk.
Several characteristics of odor cues make them useful in risk assessments. Olfactory cues persist in the environment for extended periods of time and offer detailed predator information long after the predator has moved off (Bradbury and Vehrencamp 1998; Dusenbery 1992).
Variation in the mixture of chemicals in an odor cue can communicate information beyond predator presence (Wyatt 2010). For example, snails (Physella gyrina) can differentiate between predator species like sunfish (Lepomis gibbosus) and crayfish (Faxonius rusticus) using only odor cues (Turner et al. 1999). Predators of different sizes may also smell different and larger predators may be perceived as more threatening than small ones (Chivers et al. 2001). Cue concentration can also be an indicator of predator size (Hill and Weissburg 2014). Each of these types of predator information represents a gradient of threat posed by the predators that left them behind.
Prey that can respond to gradients of risk are able to fine tune their landscape of fear to only include predators that pose a potentially lethal threat. Since predator-prey encounters occur along a continuum of relative size, prey should only respond to predators that are potentially ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 68 lethal; especially when predators have morphological features that limit the sizes of prey they can capture and consume. Hill et al. (2004) found that predatory fishes like Largemouth Bass
(Micropterus salmoides) and Peacock Cichlids (Cichla oscillaris) prefer prey that are smaller than 96% of their gape width. However, prey that are large enough to exceed the capture limits of the predator do not need to deploy their defensive mechanisms. In fact, both small Brook
Sticklebacks (Culaea inconstans) and small Swordtails (Xiphophorus helleri) will alter their behavior in the presence of a predator, but large fish of either species do not modify their behavior for predators of the same size (Abrahams 1995; DiSciullo and Basolo 2019). However, we do not know whether prey animals are able to estimate the threat posed by a gape limited predator relative to their own body size. Although many robust experiments have evaluated threat-specific responses in a variety of prey animals, few studies have considered the relationship that exists between gradients of prey size and predator size communicated through odor cues.
Therefore, we studied the effects of odor cues from two species of gape limited predatory fishes on the macrophyte consumption, foraging behavior, shelter use, and activity of crayfish along a gradient of relative size relationships defined by fish gape width and crayfish carapace width. Largemouth Bass were chosen because they are a gape limited predatory fish that occurs throughout much of North America and across the world via introductions for recreational fishing. Rainbow Trout (Oncorhynchus mykiss) were chosen as the second predatory fish species because their gape widths are smaller when compared to bass of the same total length. Using two different predatory fish species with different gape to total length ratios allowed us to eliminate the size of the predator as the only factor influencing the crayfish’s behavior. Rusty crayfish
(Faxonius rusticus) were selected as prey because they live throughout the bass’s native range ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 69
and are a preferred food for bass. Trout also consume crayfish, but the native ranges of O. mykiss
and F. rusticus do not overlap. Crayfish range widely in size and grow in a step wise manner by molting several times per year. Since crayfish often live in highly turbid flowing water or in the dark depths of lakes, they rely primarily on their extraordinary chemical sensitivity to detect
predators. Under conditions where visual cues are unavailable, crayfish may be able to extract
predator size information from olfactory cues to contrast with an estimate of their own size to
determine the level of threat.
Previous studies of crayfish responses to bass odors found that crayfish increase their
macrophyte consumption and nocturnal foraging effort under threat. This counterintuitive result
could be driven by crayfish increasing their foraging activity at night to avoid exposure to
diurnal predators (Lima and Bednekoff 1999). Crayfish exposed to bass odors consumed more
biomass of Elodea canadensis and Chara spp. than crayfish that were not exposed (Wood et al.
2018). The predator-exposed crayfish also increased the time that they spent foraging and reduced the time they spent in shelter. In a second experiment, crayfish were exposed to odors from bass of different sizes that were fed four different diets consisting of fish food pellets and three types of crayfish (Wood and Moore 2020). The responses of crayfish to the relative predator size gradient were dependent upon the predator’s diet. Overall, the combination of dietary cues and relative predator size significantly altered macrophyte consumption, foraging effort, and shelter use behaviors of the exposed crayfish. Based on these prior results, we expected to find similar increases in macrophyte consumption and time spent foraging by the crayfish when predators are large relative to the size of the prey.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 70
Methods
Collection and Housing of Animals
One hundred form two (non-reproductive) female rusty crayfish (F. rusticus) were
captured from Maple Bay of Burt Lake in Cheboygan County, Michigan, USA (45.4873ºN,
84.7065ºW). The crayfish used had all their appendages intact. All F. rusticus were stored in a
flow through steel cattle tank (200 x 60 x 60 cm: l x w x d). Unfiltered water from the East
Branch of the Maple River flowed into the tank from a PVC delivery pipe and exited the tank via
a standpipe which kept the water depth at approximately 60 cm. Crayfish fed on natural detritus
that was contained within the river water. Shelters made from clay pot halves were available in
the storage tank. The post orbital carapace length and maximum carapace width of each crayfish
was measured to the nearest 0.5 mm before use in a trial. Crayfish were marked with a one
square centimeter white patch on their carapace before each trial using a non-toxic correction pen
(BIC® Wite-Out® 2 in 1 Correction Fluid) to improve visibility for tracking in video recordings.
The behavior of crayfish is not altered by the presence of Wite-Out application (Fero and Moore
2008; Martin and Moore 2008; Jurcak and Moore 2018). Each crayfish, used only once, was
frozen after a successful trial (due to the non-native status of F. rusticus in Michigan).
Sixty Largemouth Bass (M. salmoides) and 60 Rainbow Trout (O. mykiss) served as sources of predatory fish odors. The fish were purchased from Harrietta Hills Trout Farm,
Harrieta Michigan, USA. Thirty bass and 30 trout were stored singly in a large flow through flume (1600 x 100 x 32 cm: l x w x d) constructed from cinderblocks and lined with plastic sheeting. The flume was filled with a mixture of water from the Maple River and well water. The addition of well water cooled the river water to approximately 11°C which was suitable for both bass and trout. Hardware cloth barricades divided the flume into 60 equal sections to provide ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 71
each fish with its own space (25 x 100 x 32 cm: l x w x d). The large flume was covered with
orange plastic snow fencing to filter the sunlight and provide protection from avian predators.
Before being loaded into the flume, each fish was measured for total length to the nearest
millimeter on a fish board. The exterior width of each fish’s maxillary bones was measured with
their mouth closed using calipers as an assessment of gape width (Lawrence, 1958). Each fish’s
flume section was marked with a number so that individuals could be selected based on their size
characteristics. Fish in the flume were fed a diet of pellets made from frozen pulverized F. rusticus to enhance the responses of crayfish to conspecific dietary cues released by the fish
(Beattie and Moore 2018; Wood et al. 2018). Once all the singly housed fish in the flume had
been used, a new set of fish were loaded into the flume from the stock tanks. All the fish and
crayfish were kept outdoors under the natural temperature and daylight/darkness regime.
Two additional flow through steel cattle tanks (one for bass and one for trout: 200 x 60 x
60 cm: l x w x d each) were filled with 640 l of water from the East branch Maple River (for
bass) and well water (for trout). The fishes stored in these tanks were kept in reserve to replace
previously used individuals in the flume storage system. The trout were kept in well water to
reduce the temperature of their holding water. River water ranged from 12°C to 24°C and well
water was 9°C. The tanks were covered with 1 x 1 mm fiberglass mesh to protect the fish from
avian predators, diffuse sunlight, and to filter the water to prevent the introduction of crayfish or
other large invertebrates. The fish in the storage tanks were fed a diet of commercial fish food
pellets (Sportsman’s Choice™ Trophy Fish Feed High Protein Multi-Species Fish Formula).
Diet Production
The F. rusticus crayfish used for food were frozen, then pulverized in a coffee grinder
(Hamilton Beach, Model: 80335R) to produce a slurry. Pellets were made by freezing 0.5 ml ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 72 portions of crayfish slurry. Each fish was fed a single pellet once per day. The fish were fed crayfish pellets in the holding flume for at least 48 hours before use in any trials to flush any previous dietary cues from their system (Beattie and Moore 2018). Fish were never fed in the experimental mesocosms or during trials.
Plant Collection and Storage
Samples of American waterweed (Elodea canadensis), muskgrass (Chara spp.) and northern watermilfoil (Myriophyllum exalbescens) were collected from North Fishtail Bay of
Douglas Lake, in Cheboygan County, Michigan, USA (45.5618°N, 84.6762°W). A macrophyte sampling rake was cast into mats of submerged vegetation to collect the aquatic plants. The macrophyte species used were selected because their secondary metabolic contents and handling characteristics create a gradient of preference amongst crayfish (Lodge 1991; Cronin et al. 2002;
Wood et al. 2018). Chara spp. is generally preferred by crayfish because of its fine texture, low buoyancy, and lack of noxious secondary metabolites. E. canadensis is more buoyant than Chara spp. and has slightly higher phenolic content. M. exalbescens should be the least preferred because it is buoyant enough to float and contains more secondary metabolic compounds (Wood et al. 2018). Previous studies have shown that crayfish choose macrophytes based primarily on their lack of chemical and structural defenses, not based on nutritional value (Bolser et al. 1998).
The collected macrophytes were stored in three flow through streams filled with water from the
East branch of the Maple River. The plant storage streams were lined with sand and located in open sunlight to mimic their natural environment. A surplus of plant samples was maintained from June 18th, 2019 until all trials were complete on August 12th, 2019.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 73
Experimental Design
Crayfish and fish were size matched for each trial using the ratio between the crayfish’s
carapace width and the fish’s gape width. To calculate the gape ratio, the carapace widths of the
crayfish in a trial were divided by the gape width of the predator present in the trial. The
influence of gape ratio was tested along a continuous gradient which ranged from 0.57 to 1.88.
Crayfish ranged in carapace width from 0.90 cm to 2.40 cm. The gape width ranges of the bass
(1.40 cm to 2.35 cm) and trout (1.15 cm to 1.75 cm) were different. The total length (distance
from snout to tip of caudal fin with fin squeezed together) ranges were nearly identical for bass
(16.8 cm to 23.1 cm) and trout (16.1 cm to 23.1 cm). A total of 90 trials were run consisting of
45 with bass and 45 with trout odor cues. Trials that were impacted by crayfish, escapes,
molting, immigration, or deaths were discarded (19 trials were discarded).
Experimental Mesocosms
Cinderblocks were used to frame eight flow through stream mesocosms (160 x 40 x 24
cm: l x w x d) which were lined with 0.1 mm thick plastic sheeting (Figure 11 left panel). Each
mesocosm had two sections. The predator section of each mesocosm measured 80 x 40 x 24 cm
(l x w x d), and the crayfish sections were the same size. The crayfish sections were lined with sand substrate which accumulated fine detrital material and provided a dark background against which the crayfish could be easily observed in video recordings. This same construction technique was used successfully in previous experiments (Ludington and Moore 2017, Neal and
Moore 2017, Wood et al. 2018). A pair of 208 l plastic drums served as constant head tanks for the eight mesocosms and were filled with water from the Maple River. The Maple River is part of a watershed that contains populations of both M. salmoides and O. mykiss. Each plastic drum
fed four mesocosms with water from one 10 mm diameter garden hose per mesocosm (flow rate ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 74
= 0.086 ± 0.003 l s-1 [mean ± SEM]). Water flowed into the upstream predator section of each mesocosm before overflowing through a screened opening (28 x 12 cm opening with 1 x 1 mm screening) in a partial wall into the downstream crayfish section. The water overflowing through the screened opening did not exceed 5mm in depth, which is inadequate for crayfish to see into the predator section of the arena. The water would then exit from the downstream end of the mesocosm through another screened opening. A single PVC half-pipe shelter (10 x 8.5 x 4 cm: l x w x h) was placed near the down current end of the crayfish section.
A wooden frame held an infrared DVR camera (Zosi ZR08ZN10) 1.5 m above the water’s surface of each mesocosm to record the crayfish’s nocturnal behaviors. One low intensity red light bulb (Great Value brand: Model A19045 LED Lamp, 9 W, 145 mA, 120 V, 60 Hz,
RED) was used to illuminate each mesocosm from above. An awning made from a black utility tarp (9 x 6 m) covered all eight mesocosms to prevent weather and water damage to the electrical equipment. The awning also eliminated glare from moonlight and starlight from the recordings.
Sunlight could enter the system through 1.5 m openings on the on the eastern and western ends of the mesocosms. Water flow through the mesocosms was slow enough that it did not produce any visible surface distortion in the video recordings.
Experimental Protocol
Trials began July 1st, 2019 and were concluded on August 12th, 2019. Each trial was run for 24 hours. A trial cycle began at 0830 with selection of plant samples from the plant storage streams. Single stems of each macrophyte species (weighing approximately 1 g) were selected for each trial. Excess surface water was removed from plant samples using a salad spinner
(Farberware Basics, Item No. 5158683) before weighing to the nearest 0.001 g. The plant stems were then attached to glass rods (255 x 6 mm: l x OD) with 26-gauge green painted floral wire. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 75
The loaded rods were placed into a hardware cloth bracket (24 x 19 cm: l x w) which held the plant samples in position during the feeding trial (Figure 11 right panel). The arrangement of the three plant stems were rotated on the brackets across trials to prevent any selection bias caused by the location of plant samples in the mesocosm. After the plant samples were placed into the crayfish sections of the mesocosms, a single F. rusticus crayfish was selected for each stream. A single fish was placed into the predator section of each mesocosm at 1100 each morning. After addition of the fish, the screened openings between the predator and crayfish section and at the outflow from the crayfish section were brushed to remove any debris that might inhibit water/odor flow.
Beginning at 2300 an automatic light timer activated the red lights to illuminate the mesocosms. At 0000 the cameras above each mesocosm started recording the nocturnal behaviors of the crayfish. The cameras shut down at 0400 when behavioral recordings were complete. All crayfish were removed from the mesocosms first on the following morning. The plant samples were then removed from each mesocosm and were surface dried in the salad spinner again before weighing a second time. After use in a trial, fish were replaced into their species-specific stock tanks. Once a trial cycle was complete, the mesocosms were flushed overnight (at least 12 hours) before a new trial cycle began the following morning. The water in the mesocosms was replaced approximately 24 times during the flush period.
Data Collection
A viewer blind to treatment scored four hours of video per trial for the total time spent by each crayfish in the foraging and shelter zones of the mesocosm. Because the feeding appendages of crayfish are located on the underside of their bodies, it was not possible to determine when the crayfish were actually feeding. Thus, whenever the entire marker on the ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 76 carapace was inside the foraging zone of the mesocosm crayfish were scored as foraging (Figure
11 left panel). Similarly, crayfish were scored as using shelter whenever the entire marker on the animal’s carapace was within the shelter zone (Figure 11 left panel).
Foraging effort was calculated by dividing the time (s) that crayfish spent in the foraging zone of the mesocosm by 14400 s (4 hours in seconds), then the quotient was multiplied by 100.
The resulting percentage represents the percent of the four-hour video recording that was spent foraging. Shelter use was calculated the same way, using time (s) spent in shelter as the numerator. The movements of crayfish into and out of the two resource zones were recorded as the number of transitions and used as a proxy for overall activity.
Consumption of M. exalbescens (g) was calculated by subtracting the mass of M. exalbescens remaining after the trial from the initial mass of M. exalbescens before the trial. The resulting difference was then divided by the initial mass M. exalbescens and multiplied by 100 to obtain the percent of M. exalbescens biomass that was either consumed or destroyed by the crayfishes’ foraging activity. Which we defined as M. exalbescens consumption.
Macrophyte Consumption = ((Mi – Mf) / Mi ) * 100
This calculation was repeated for E. canadensis and Chara spp. as well to obtain the proportions of each of these species that were consumed. Since the plants are offered to the crayfish in approximately equal masses and at the same time, variation in consumption of each macrophyte species is a useful measure of choice under different threat conditions (Chambers et al. 1990;
Lodge 1991). The goal of these measures was to assess the influence of foraging choices on the macrophyte community. Macrophyte consumption was not normalized against crayfish biomass, in alignment with the convention in this field (Feminella and Resh 1989; Cronin et al. 2002).
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 77
Ethical Approval
Largemouth Bass were maintained and handled following established animal care and use procedures. The use of vertebrate animals was approved by the Institutional Care and Use
Committee at University of Michigan (Protocol: PRO00008892).
Relative Size Analyses
Carapace widths of the crayfish were plotted against the gape widths of the fish used in each trial to check for possible trends as a result of the pairing fish and crayfish across a relative size gradient (Figure 12). A linear model was run on the data using the “lm” function in the statistical program R to verify that there was no relationship between the crayfish carapace widths and the gape widths of each fish species (R Core Team 2019). No significant relationship was detected between crayfish carapace width and fish gape width (F(1, 68, 0.05) = 0.298, p = 0.587,
Figure 12) in the data. Due to the lack of a relationship between these two measures, further analysis is focused on gape ratio as the driving factor for the results.
The total lengths of the bass and trout used in the trials were compared using a box and whisker plot (Figure 13 red boxes). Gape ratios were also compared for the two fish species with a box and whisker plot (Figure 13 blue boxes). A MANOVA test in R was used to check for differences in fish total length and gape ratio related to fish species (R Core Team 2019). The total lengths of the fish, and the gape ratios were not different between trials using bass and trout
(F(2, 69, 0.05) = 2.579, p = 0.083, Figure 13).
Macrophyte Consumption Analysis
The consumption of each macrophyte species was assessed using a linear mixed effects model by running the “lmer” function from the “lmerTest” package in R (Kuznetsova et al. 2017;
R Core Team 2019). Each macrophyte consumption model was constructed with full interactions ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 78
using one categorical factor (fish species), one continuous variable (gape ratio) and a random
effects term (mesocosm). Following model construction, the outputs were extracted using the
“anova” function from the “car” package in R (Fox and Weisburg 2019). When significant interactions between gape ratio and fish species were detected, simplified linear mixed effects models were run for each fish species. Each species-specific model assessed the effect of gape ratio on macrophyte consumption with mesocosm as a random factor.
Crayfish Behavioral Analysis
Following the same statistical procedure as the macrophyte consumption analysis, linear mixed effects models using the “lmer” function from the “lmerTest” package in R were also performed on the foraging effort, shelter use, and transitions measures of crayfish behavior using fish species as a categorical variable, gape ratio as a continuous variable, and mesocosm as the random effects term (Kuznetsova et al. 2017). Again, the outputs were extracted using the
“anova” function in the “car” package in R (Fox and Weisburg 2019).
Comparison of Gape Ratio and Total Length Models
It is possible that any behavioral or foraging changes could be a result of an increase in total chemical stimulus by using larger animals within a trial. To test for a simple size effect on the results, a second series of linear mixed effects models were constructed using the same procedure described above which replaced gape ratio with predator total length. The Akaike information criterion was used to determine whether the linear mixed effects models incorporating gape ratio or total length were a better fit to each of the crayfish response variables. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 79
Figure 11. Artificial Stream Mesocosm and Macrophyte Feeding Bracket
The left panel displays the stream mesocosm. Water flows into the predator section through a hose on the left. A single largemouth bass (Micropterus salmoides) or rainbow trout
(Oncorhynchus mykiss) releases odors from its skin and excretions into the water. The water containing predator odor cues then flows through a screened opening into the crayfish section.
The predator odors are presented to a rusty crayfish (Faxonius rusticus) as it feeds on macrophytes (northern watermilfoil (Myriophyllum exalbescens), American waterweed (Elodea canadensis), and muskgrass (Chara spp.)) attached to wire brackets or occupies shelter. The water then exits the crayfish section through a screened opening on the right (flow rate = 0.086 ±
0.003 l s-1 [mean ± SEM]).The right panel shows an expanded view of the feeding bracket. The
position of each macrophyte species was rotated between trials. Approximately one gram of each
macrophyte species were wired to glass stir rods that were then attached to a hardware cloth
bracket. One bracket was used per trial per stream. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 80
Figure 12. Fish Gape Widths Against Crayfish Carapace Widths
Red circles indicate pairings in trials using bass odor cues. Pink shading represents a 95% confidence interval around the sizes of paired bass and crayfish. Blue triangles represent pairings in trials using trout odor cues. Light blue shading represents a 95% confidence interval around the sizes of paired trout and crayfish. The nearly flat slopes of the regression lines indicate that there is no relationship between crayfish carapace width and the gape widths of either species of fish.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 81
Figure 13. Total Lengths and Gape Ratios of Fish Used for Odor Generation
Boxes with red shading represent fish total lengths. Blue shading represents gape ratios. White filled circles indicate individual trials. Total length of the fish is measured as the distance from the end of the snout to the tip of the caudal fin with the caudal fin depressed. Gape ratio is equal to crayfish carapace width divided by the gape width of the fish in the trial. The bold lines indicate medians. The box indicates the interquartile range between the first quartile (bottom of box) and the third quartile (top of box). Whiskers indicate the overall ranges tested. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 82
Results
Macrophyte Consumption by Crayfish
M. exalbescens Consumption and Gape Ratio
Crayfish significantly decreased their consumption of M. exalbescens as gape ratio
increased (F(1, 58.51, 0.05) = 15.441, p < 0.001, Table 6, Figure 14 top panel). Fish species had a
marginally significant effect on M. exalbescens consumption (F(1, 58.63, 0.05) = 3.411, p = 0.070).
The interaction between gape ratio and fish species also had a marginally significant effect on M.
exalbescens consumption (F(1, 59.09, 0.05) = 3.731, p = 0.058).
Chara spp. Consumption and Gape Ratio
Crayfish consumption of Chara spp. was influenced significantly by gape ratio (F(1, 64) =
7.100, p = 0.010, Table 6, Figure 14 bottom panel). As gape ratio increased, the amount of
Chara spp. consumed decreased. Fish species had no effect on Chara spp. consumption (F(1, 64,
0.05) = 0.666, p = 0.418). There was no significant effect of the interaction between gape ratio and
fish species on Chara spp. consumption (F(1, 64, 0.05) = 0.288, p = 0.593).
E. canadensis Consumption and Gape Ratio
The consumption of E. canadensis by crayfish was not significantly influenced by fish
species or the gape ratio between prey body size and predator gape width.
Crayfish Behavioral Responses
Foraging Behavior and Gape Ratio
The crayfish spent significantly less time foraging as gape ratio increased (F(1, 64, 0.05) =
18.334, p < 0.001, Table 6, Figure 15 top panel). The species of fish did not influence foraging
time (F(1, 64, 0.05) = 1.155, p = 0.287). There was no interaction effect of gape ratio and fish
species on the time crayfish spent foraging (F(1, 64, 0.05) = 0.522, p = 0.473). ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 83
Shelter Use and Gape Ratio
The time crayfish spent in the shelter increased significantly as gape ratio increased (F(1,
60.21, 0.05) = 18.002, p < 0.001, Table 6, Figure 15 middle panel). There was no effect of fish
species on shelter time (F(1.60.59, 0.05) = 0.068, p = 0.795). Gape ratio and fish species did not have an interacting effect on the time crayfish spent in shelter (F(1, 61.30, 0.05) = 0.383, p = 0.538).
Transitions and Gape Ratio
The crayfish moved across the resource zone boundaries fewer times as gape ratio increased (F(1, 60.35, 0.05) = 5.953, p = 0.018, Table 6, Figure 15 bottom panel). Fish species did not
affect the number of transitions (F(1, 60.57, 0.05) = 0.097, p = 0.756). There was no interaction
effect of gape ratio and fish species on the number of transitions made by the crayfish across the
resource zone boundaries (F(1, 61.11, 0.05) = 0.184, p = 0.669).
Comparison of Gape Ratio and Total Length Models
The fish total length showed no significant effects on any of the macrophyte consumption
or crayfish behavior variables (Table 6). In addition, all models based on gape ratio produced
lower AIC values (difference > 2) than models based on fish total length (Table 6).
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 84
Table 6.
Comparison of Gape Ratio and Fish Total Length Effects on Crayfish Response Variables
Gape Ratio Effects Total Length Effects
F Model F Model Response Variable p Value p Value Value AIC Value AIC
M. exalbescens 15.441 <0.001 -101.67 0.534 0.468 -70.20 Consumption
Chara spp. Consumption 7.100 0.010 29.54 0.684 0.411 50.98
Foraging Time 18.334 <0.001 1196.57 1.029 0.314 1230.98
Shelter Time 18.002 <0.001 1247.39 0.076 0.784 1280.11
Transitions 5.953 0.018 569.16 1.446 0.234 590.34
Notes. Outputs are from linear mixed effects models run independently on each response variable. Linear mixed effects models incorporating gape ratio were run separately from models incorporating fish total length, then the two models for each response variable were compared using AIC.
ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 85
Figure 14. Influence of Gape Ratio on Macrophyte Consumption by Crayfish
The top panel displays the consumption of Myriophyllum exalbescens by crayfish under threat.
The bottom panel displays the consumption of Chara spp. by crayfish. In both panels, the red circles represent macrophyte consumption in the presence of bass odors. Pink shading represents a 95% confidence interval around the predicted response to bass odors. Blue triangles represent macrophyte consumption in the presence of trout odors. Light blue shading represents a 95% confidence interval around the predicted response to trout odors. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 86
Figure 15. Behavior of Crayfish Responding to Gape Ratio
The top panel displays the time crayfish spent foraging under threat. The middle panel displays the time crayfish spent in shelter. The bottom panel displays the number of transitions crayfish made across the resource zone boundaries. In all three panels, red circles represent the time crayfish spent foraging in the presence of bass odors. Pink shading represents a 95% confidence interval around the predicted response to bass odors. Blue triangles represent the time crayfish spent foraging in the presence of trout odors. The light blue shading represents a 95% confidence interval around the predicted response to trout odors. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 87
Discussion
Crayfish that were small relative to their predators consumed more macrophyte biomass
(Figure 14), spent more time foraging (Figure 15 top panel), decreased shelter use (Figure 15
middle panel), and transitioned between sections more often (Figure 15 bottom panel) in the
mesocosms than crayfish that were large relative to their predators. All these significant effects
from gape ratio and the lack of fish species or general size effects supports the hypothesis that
crayfish use relative predator size to assess the threat posed by the predator and alter their
behavior. Given the design of the experiment, these results support the conclusion that this
measurement of threat as indicated by gape ratio comes solely from chemical cues. These results
are consistent with findings from previous studies on predatory threat assessment in crayfish.
The first demonstrated that crayfish increased macrophyte consumption and showed altered
macrophyte species preferences in the presence of predatory fish odors (Wood et al. 2018). The
other studies showed that crayfish could assess the threat posed by a predatory fish using dietary
cues and size information extracted from the fish’s odor (Beattie and Moore 2018; Wood and
Moore 2020). The current study demonstrates that individual crayfish assess threats posed by
fish of different sizes relative to their own body size and alter their behavior accordingly.
However, threat assessment is not a one-dimensional process. The crayfish are integrating multiple types of predator information including predator presence/absence, predator diet, predator species, and predator size while also considering their own size relative to the predator before making resource use decisions.
The design of the mesocosms used in this experiment limits the predatory stimuli available to the crayfish to only odor cues carried by the flowing water. So, the size information the crayfish are using to make resource use decisions must be extracted from the predator odor. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 88
These odor cues are a cocktail of many different chemicals released through the predator’s skin,
gills, and excretory system (Brown et al., 1995; Evans et al. 2005; Glover et al. 2013). Although
the mechanism by which crayfish determine the size of the predator from odor cues is not
known, there are several possibilities that could provide an explanation. Larger predators have
greater surface area, greater mass, and lower metabolic rates than smaller predators of the same
species (Killen et al. 2010). The release of greater quantities of body odor and waste excretions,
larger predators could be producing a more intense odor plume which reveals their size (Kusch et
al. 2004; Hill and Weissburg 2013). The chemical composition of a predator’s odor could also
change as they grow larger and age. Through ontogenetic effects on metabolism and physiology,
larger predators could be releasing different chemical mixtures that prey can use to estimate size
(Pilati and Vanni 2007). Possibly, the chemical cocktails released by predators of different sizes
contain the same compounds but in different proportions or different concentrations (Pilati and
Vanni 2007). Prey animals could then assess predator size using the relative concentrations of
different chemicals in the predator’s odor plume. Whatever the mechanism of predator size
recognition, our evidence shows that crayfish are comparing predator size information with an
estimate of their own size to perform a risk assessment.
Crayfish may also be using chemical signals to gauge their own size against the size of
the predator. The literature on social behavior in crayfish demonstrates that crayfish use urine- like excretions released from orifices on their heads called nephropores as a form of chemical communication during social interactions (Breithaupt 2010). These signals are used by crayfish to recognize previously encountered individuals and to discern the size of their opponents (Pavey and Fielder 1996; Seebacher and Wilson 2007). Previous work has suggested that crayfish may be sampling their own urinary signals as a measure of their own social status (Zulandt-Schneider ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 89 et al. 2001). If so, some estimate of their own size may be contained within these signals.
Comparing the information in the predatory odors with the information contained within urinary signals may provide crayfish with relative size estimates. While the relative size assessment mechanism in use remains unknown, future work aimed at testing this odor comparison strategy would be beneficial to our understanding of risk assessment and the exchange of information between predators and prey.
The behavioral responses of crayfish to the varying threats posed by predators of different relative sizes illustrate a non-consumptive effect of the predators on crayfish behavior.
Crayfish in trials with small gape ratios consumed greater quantities of macrophytes and increased the time they spent foraging. This result seems counterintuitive considering that most prey animals decrease their foraging efforts when faced with predatory threats (Lima and Dill
1990; Peckarsky et al., 2008). However, both bass and trout are gape limited predators of crayfish (Shave et al. 1994; Huskey and Turingan 2001). Many prey species respond to gape limited predators by altering their body morphology to make themselves more difficult to swallow. Some species of Daphnia grow enlarged helmets, neckteeth, or spines when exposed to predator odors (Weiss 2019). Although the morphology of F. rusticus crayfish is not as plastic on a short temporal scale, crayfish could increase their overall body size through promoting faster growth between molts. By increasing their foraging effort, crayfish could be altering their growth rate to reach a size beyond the predator’s gape limitation.
Prey animals that can increase their growth rates have an advantage when faced with a threat from a gape limited predator (Olson 1996). Under the paradigm of relative size effects, the goal for prey is not to reach a certain size which is “safe” from predators, but rather to outpace the size of the predatory size limitation. In bass and trout, this is their gape. For example, spot ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 90
(Leiostomus xanthurus) that grow rapidly experience half as much mortality from southern flounder (Paralichthys lethostigma) predation compared to slow growing spot populations (Craig et al. 2006). However, prey must consume greater quantities of resources in order to increase their growth rate. In the experiments by Craig et al. (2006), the accelerated growth rates of the spot fish in rapid growth treatments were achieved by increasing food availability. Thus, in natural systems, prey animals that are growing to outpace their predators size limitation need to seek additional food resources through increased foraging activity and greater food consumption.
Threat assessment is important in this context because prey must expose themselves to predation risk in order to procure the additional resources they need for rapid growth.
However, the behavioral patterns of crayfish in the current study could be further explained by temporal variation in the crayfish’s perception of risk. Both predator species used in this study (M. salmoides and O. mykiss) are visually oriented, diurnal foragers (Angradi and
Griffith 1990; McMahon and Holanov 1995). The video recordings of crayfish behavior were only conducted at night from 0000 to 0400. During this dark period, the crayfish may perceive a reduction in predation risk from visually oriented predators. Thus, the videos may have captured the crayfish using a period of relative safety to forage more even though the odor of the predator was present. The behaviors of crayfish that were too large to be consumed by their predators is also consistent with the risk allocation hypothesis (Lima and Bednekoff 1999). The lack of nocturnal foraging effort and activity that was observed in the crayfish that were large relative to their predators makes sense considering that the predators pose no real threat. Thus, the crayfish can spread their activity throughout the day. There is also no urgency to increase growth if the crayfish are already too large to be consumed, which helps explain their low macrophyte consumption. Crayfish of all sizes exhibited differences in their responses to predators dependent ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 91
on the size ratio between predator and prey. A similar behavior has been observed in the elk
(Cervus canadensis) in Yellowstone National Park, responding to temporal variation in wolf predation risk. The elk in the park are more vigilant and occupy safer regions during the crepuscular periods of the day when wolves tend to hunt; and are more active and occupy riskier areas during the daylight hours when wolves are less active (Kohl et al. 2018).
In the current study, the relationship between crayfish size and predator size should not be viewed as a cutoff where some individuals that are small are vulnerable while other bigger crayfish are invulnerable to specific predators. While this mechanism seems tidy, a bimodal distribution of responses on either side of a relative size threat threshold would be needed to support this conclusion. However, the data show here present a smooth, albeit variable, gradient of responses to differences in the ratio between predator gape width and prey body size. Thus, the responses of prey to variation in threats presented by predators of different relative sizes is well described as a continuous phenomenon. While there is some possibility that crayfish which
are relatively large show an increased fear response to predators because their make them more
conspicuous, this would not be very advantageous from a resource allocation perspective.
Following this idea, large crayfish who show fear responses to predators across the relative size
spectrum would incur considerable costs in lost opportunities to access resources, during the time
when they are most reproductively viable. Thus, the best response is one that is fine tuned to
allow prey to only respond to predators that present a real threat under current conditions.
Threat assessment allows prey to fine tune the landscape of fear and minimize the impact
of non-consumptive predator effects. Under classical landscape of fear theory, prey animals
reduce encounters with predators by detecting predator cues in the environment and avoiding
areas where predators are or have been in the past (Laundré et al. 2001, 2010). The perceived ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 92
risk in these locations comes from the predator’s current or past presence at a specific locale.
Prey animals incorporate information about more than just predator presence as they move
through the landscape. Factors like predator identity, dietary components, satiation state, and
activity patterns are known to influence prey responses (Turner et al. 1999; Chivers and Mirza
2001; Bell et al. 2006; Kohl et al. 2018). Prey use this additional information about their predators to decide if a predator poses a real threat to them (Ferrari et al. 2010). The literature is rich with information about the size-dependent prey selection by predators, but comparatively little is known about the size-dependent avoidance of predators by prey. Until now, the field has largely overlooked the influence of predator size relative to prey size in size-limited predators as sources of information that could be used in risk assessment.
In situations where predator-prey size ratios favor the prey, the perceived risk is lower, while size ratios that favor the predator heighten the perception of risk (Puttlitz et al. 1999). Thus predator-prey relative size as opposed to predator size provides a refined landscape of fear concept. Prey can ignore cues from juvenile predators or relatively small individuals because these predators do not pose a threat, while reserving their antipredator strategies for potentially lethal predators that need to be avoided (Helfman 1989). Wahle (1992) showed that small lobsters (Homarus americanus) spent more time in shelter in the presence of predatory sculpins
(Myoxocephalus anaeus), while large lobsters confronted the predator with aggressive displays.
Thus, prey animals are sensitive to the predatory limitations of their predators. However, previous studies have only tested the responses of prey along a size gradient to a few predators of very similar sizes. The conclusion that prey are sensitive to predator size cannot be reached without considering relative sizes of the predator and prey. Thus, prey may be responding to the ratio of size in addition to or instead of just size of the predator. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 93
The crayfish responded to the relative size ratio between their carapace width and the gape of their predators and adjusted their resource use behaviors to set themselves on a growth trajectory to get beyond the predator’s gape limitation. Considering Helfman’s (1989) threat- sensitive predator avoidance hypothesis in light of the current study, we see that prey can determine the level of threat posed by the predator and use this information to make resource use decisions. Incorporating the threat-sensitivity of prey to relative predator size into the background level of risk refines the landscape of fear concept (Brown et al. 2006). The numerous species interactions that occur within an ecosystem are governed by a highly complex system of risk assessments and decisions made by individuals within a spatially and temporally dynamic landscape of predatory cues (Ferrari et al. 2009, Gaynor et al. 2019). The fully integrated landscape of fear would involve prey assessing multiple aspects of predator cues beyond their presence in the landscape to determine which predators present a legitimate threat. A deeper understanding of risk assessments in prey reveals how altered prey behavior impacts biological communities and informs our perspective on the top down influence of predators. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 94
CHAPTER V: SUMMARY AND IMPACTS
The study of ecology has long been concerned with understanding the ways organisms
interact with each other in biological communities, and with the abiotic components of the
environment. Early on, predator-prey interactions were recognized as important in shaping
ecological structure. Since the 1920s, the focus on density-dependent interactions and
consumptive effects guided progress in the field (Volterra, 1926; Lotka, 1927; Holling, 1959;
MacArthur & Pianka, 1966). However, these early models failed to explain a large amount of the
variation we observe in natural communities. This is largely because non-lethal predator-prey
interactions had been overlooked by many ecologists. Beginning in the 1980s, the importance of
informational interactions between predators and their prey were realized (Sih, 1980; Lima &
Dill, 1990; Werner & Peacor, 2003). Since then, we have found that non-consumptive effects
(NCEs) and behaviorally mediated trophic cascades (BMTCs) may account for a larger portion of the variation in natural communities than consumptive effects do (Abrams, 1990; Schmitz et al., 1997).
NCEs naturally lead to BMTCs through changes in prey behavior. However, there is a significant gap in knowledge concerning the use of predator information by prey which links these two subfields of trophic ecology together. The literature on NCEs has shown the diversity of effects of different types of predator information on prey. Similarly, the literature on BMTCs shows the types of changes that can follow in the community. The unanswered question is whether community change occurs when prey respond to differences in cues from similar predators or to similar cues from different predators in unique ways. The three experiments in this dissertation have examined how subtle changes in predator information lead to differences in prey behavior, which produce unique and measurable impacts on the community. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 95
The first experiment demonstrated that odors from predatory fish could induce NCEs in
crayfish. When the threatening cue was present in their environment, crayfish spent more time
foraging and less time in shelter. Crayfish also increased their consumption of aquatic plants
when predator cues were present, which indicated that a BMTC had occurred. Interestingly,
crayfish only increased consumption of two of the three aquatic plants which suggests a shift in
preference for those two species under threat of predation. The reason why the crayfish may have
preferred Elodea canadensis and Chara spp. over Myriophyllum exalbescens is unclear, but our
chemical analyses suggest that the total phenolic content of M. exalbescens was higher than in the other two species. Phenolic compounds are often toxic or at least unpalatable and are thought to deter herbivory (Lodge, 1991; Bolser et al., 1998). This experiment showed that prey animals used predator information, extracted from chemical cues, to alter their behavior. These behavioral changes, driven by altered resource use decisions, had measurable impacts on the controlled plant community we studied and has thus demonstrated an NCE facilitated BMTC.
The findings from the first study are contrary to many other studies regarding the non- consumptive effects of predators on prey behavior. Most examples of NCEs in the literature show reduced foraging effort, increased shelter use, and reduced resource consumption by prey
(Lima & Dill, 1990; Peckarsky et al., 2008; Ferrari et al, 2010). Following the results of the first experiment, a second study was conducted to see if the crayfish would show the same behavioral responses to a gradient of threats represented by different predator dietary cues. In addition to the behavioral observations, the second experiment also tested whether crayfish were increasing their plant consumption to offset the increased metabolic demands of stress imposed by the threat of predation. In place of direct measures of crayfish metabolism, hemolymph samples were ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 96 collected from crayfish and analyzed for serotonin levels, a known indicator of stress in crayfish
(Fossat et al., 2015).
The predatory bass were fed diets consisting of commercial fish food pellets, pulverized allopatric Faxonius propinquus crayfish, pulverized sympatric Faxonius virilis crayfish, and pulverized conspecific Faxonius rusticus crayfish. There are many examples in the literature of conspecific dietary cues from a variety of predators eliciting the greatest threat responses from an array of different prey species (Chivers & Mirza, 2001; Scherer & Smee, 2016). Few relationships were found upon the first analysis of the dietary threat gradient experiment. After controlling for several random effects including date and mesocosm, I suspected that there was another factor involved in the predator odor that might confound the results. When I included the average size relationship between the two predators and four crayfish present in each trial in the analysis, significant trends emerged within each of the dietary treatments. The data suggest that crayfish are sensitive to predator size and that their response to size cues is modulated by the predator’s diet. The serotonin content of the hemolymph samples within each dietary treatment were highly variable, even though we pooled the hemolymph samples for the four crayfish present in each trial into a single sample. Thus, there were no significant differences in the serotonin concentrations in the crayfish hemolymph, despite the similarity of behavioral responses of crayfish to predator cues in the first and second experiments. Although testing serotonin content for evidence of stress was inconclusive, there could be another mechanism which involves the relative size relationships between predators and prey.
The second experiment demonstrated that crayfish which are small relative to their predators show different behavioral responses to predator odor than crayfish that are large relative to their predators, while the responses of both groups are modulated by predator diet. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 97
This was interesting, considering that largemouth bass are gape limited (Hill et al., 2004). Bass can only swallow prey that are small enough to fit into their mouth. As a bass grows and the size of its mouth increases, so does the size of the prey the bass can consume. Meanwhile, crayfish grow in a stepwise manner by shedding their exoskeleton every few months (Aiken & Waddy,
1992). Thus, a single molting event can put a crayfish that is near the gape limit of a predator temporarily beyond the predator’s consumptive ability. Crayfish could increase the frequency of molting events by consuming more resources to promote growth and potentially reach a size refuge from predation. Crayfish growth responses to predators were not studied directly because we first needed to know if crayfish are sensitive enough to gradients of relative predator size to differentiate threatening and non-threatening predators.
If crayfish are sensitive to differences in predator gape relative to their own body size and increase their foraging behaviors when they are small relative to their predators, then the proposed growth mechanism could explain the inverse foraging results observed in the first two studies, relative to other studies on NCEs. Thus, the third experiment in this dissertation was designed to test the sensitivity of individual crayfish to relative size relationships along a gradient of variation in individual crayfish body size and individual predator gape size. The crayfish were tested against two different predator species; largemouth bass (Micropterus salmoides) and rainbow trout (Oncorhynchus mykiss) to separate the effects of predator gape size and predator body size. Bass and trout of similar body size have gape sizes that are quite different, enough in fact that crayfish who are safe from trout predation may be threatened by a bass of the same body size.
Crayfish in the third study showed increased foraging behavior, plant consumption, and overall activity, while reducing shelter use when the crayfish were small relative to the size of ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 98 their predators. Lower foraging effort, plant consumption, overall activity, and increased shelter use were observed in crayfish that were large relative to their predators. These results are largely consistent with the findings from the first and second experiments which indicated that under high threat conditions, F. rusticus crayfish forage more, eat more plants, and spend less time in shelter. While this relationship does not confirm the hypothesis that crayfish increase their foraging effort to accelerate growth towards a size refuge from predation, these data lend support to the idea.
Alternatively, large crayfish might be less active because they are more conspicuous than small ones and need to hide more to avoid detection by predators. However, the third experiment did not simply test small vs. large crayfish, because the study was based on relative size. Thus, some large crayfish exposed to even larger predators foraged more than some small crayfish that were exposed to predators too small to eat them. The results are not directly caused by fish size either, because analyses based only on predator size produced no significant relationships.
These experiments provide a strong test of the threat sensitive predator avoidance hypothesis (Helfman, 1989) and demonstrate that prey animals are highly sensitive to subtle variation in predator odor cues that can change prey behavior. Together, these experiments combine behavioral analysis from video recordings with direct assessments of behaviorally mediated trophic cascades on other members of an aquatic community to provide a more complete picture of the effects arising from predator-prey interactions. Within my study system,
I have shown that crayfish alter their behavior when exposed to predator odors and that the shift in prey behavior produces a measurable impact on the aquatic community. Crayfish are sensitive to the gape limitations of their predators relative to their own body size and they can extract this information from predator odor cues. The responses of crayfish to predator size information are ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 99 also modulated by the recent constituents of the predator’s diet, again communicated through chemical cues released by the predator.
When prey integrate all the information gathered from predator cues, the prey can assess threats and make decisions to alter their future behavior. Changes in information availability like the presence or absence of a predator cue can have profound effects on prey behavior, which also translate to impacts on the larger community. Subtle changes like shifts in predator diet can also alter the character of cues which leads to different prey behaviors. Even the variation in relative size relationships between predators and prey tells prey which predators need to be avoided and which ones pose little threat. Once prey change their behavior, then their interactions with other species change as well. These indirect effects have large impacts on community structure and diversity. My hope for this research, is that the direct observational approach I have developed inspires and advances the methodology of future studies in the field of trophic ecology.
Furthermore, my work has shown that prey base their decisions on multiple threat factors beyond presence or absence of the predator. Prey animals do not respond to all predators to the same degree. They use threat assessment to refine the complex and dynamic landscape of fear to limit the costly influence of non-threating predators. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 100
REFERENCES
Abrahams, M. V. (1995). The interaction between antipredator behaviour and antipredator
morphology: Experiments with fathead minnows and brook sticklebacks. Canadian
Journal of Zoology, 73(12), 2209-2215. DOI: 10.1139/z95-261
Abrahamsson, S. A. A. (1966). Dynamics of an isolated population of the crayfish Astacus
astacus Linné. Oikos, 17(1), 96-107. DOI: 10.2307/3564784
Abrams, P. A. (1990). The evolution of anti-predator traits in prey in response to evolutionary
change in predators. Oikos, 59(2), 147-156. DOI: 10.2307/3545529
Abrams, P. A. (1995). Implications of dynamically variable traits for identifying, classifying, and
measuring direct and indirect effects in ecological communities. The American
Naturalist, 146(1), 112-134. DOI: 10.1086/285789
Abrams, P. A., Menge, B. A., Mittelbach, G. G., Spiller, D. A., & Yodzis, P. (1996). The role of
indirect effects in food webs. In G. A. Polis & K. O. Winemiller (Eds.), Food Webs (pp.
371-395). Springer.
Aiken, D. E., & Waddy, S. L. (1992). The growth process in crayfish. Reviews in Aquatic
Science, 6(3, 4), 335-381.
Aljetlawi, A. A., Sparrevik, E., & Leonardsson, K. (2004). Prey–predator size‐dependent
functional response: Derivation and rescaling to the real world. Journal of Animal
Ecology, 73(2), 239-252. DOI: 10.1111/j.0021-8790.2004.00800.x
Angradi, T. R., & Griffith, J. S. (1990). Diel feeding chronology and diet selection of rainbow
trout (Oncorhynchus mykiss) in the Henry's Fork of the Snake River, Idaho. Canadian
Journal of Fisheries and Aquatic Sciences, 47(1), 199-209. DOI: 10.1139/f90-022 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 101
Anholt, B. R., & Werner, E. E. (1995). Interaction between food availability and predation
mortality mediated by adaptive behavior. Ecology, 76(7), 2230-2234. DOI:
10.2307/1941696
Apfelbach, R., Parsons, M. H., Soini, H. A., & Novotny, M. V. (2015). Are single odorous
components of a predator sufficient to elicit defensive behaviors in prey species?
Frontiers in Neuroscience, 9, 263. DOI: 10.3389/fnins.2015.00263
Atema, J. (1988). Distribution of chemical stimuli. In J. Atema, R. R. Fay, A. N. Popper, & W.
N. Tavolga (Eds.), Sensory Biology of Aquatic Animals (pp. 29-56). Springer.
Barton, B. A. (2002). Stress in fishes: A diversity of responses with particular reference to
changes in circulating corticosteroids. Integrative and Comparative Biology, 42(3), 517-
525. DOI: 10.1093/icb/42.3.517
Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models
using lme4. Journal of Statistical Software, 67(1), 1-48. DOI:10.18637/jss.v067.i01.
Beattie, M. C., & Moore, P. A. (2018). Predator recognition of chemical cues in crayfish: Diet
and experience influence the ability to detect predation threats. Behaviour, 155(6), 505-
530. DOI: 10.1163/1568539X-00003501
Bell, R. D., Rypstra, A. L., & Persons, M. H. (2006). The effect of predator hunger on
chemically mediated antipredator responses and survival in the wolf spider Pardosa
milvina (Araneae: Lycosidae). Ethology, 112(9), 903-910. DOI: 10.1111/j.1439-
0310.2006.01244.x
Bergman, D. A., & Moore, P. A. (2005). Prolonged exposure to social odours alters subsequent
social interactions in crayfish (Faxonius rusticus). Animal Behaviour, 70(2), 311-318.
DOI: 10.1016/j.anbehav.2004.10.026 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 102
Bernot, R. J., & Turner, A. M. (2001). Predator identity and trait-mediated indirect effects in a
littoral food web. Oecologia, 129(1), 139-146. DOI: 10.1007/s004420100705
Bierbach, D., Schulte, M., Herrmann, N., Tobler, M., Stadler, S., Jung, C. T., ... & Indy, J. R.
(2011). Predator-induced changes of female mating preferences: Innate and experiential
effects. BMC Evolutionary Biology, 11(1), 190. DOI: 10.1186/1471-2148-11-190
Bishop, T. D., & Brown, J. A. (1992). Threat-sensitive foraging by larval threespine sticklebacks
(Gasterosteus aculeatus). Behavioral Ecology and Sociobiology, 31(2), 133-138. DOI:
10.1007/BF00166346
Bolser, R. C., Hay, M. E., Lindquist, N., Fenical, W., & Wilson, D. (1998). Chemical defenses of
freshwater macrophytes against crayfish herbivory. Journal of Chemical Ecology, 24(10),
1639-1658. DOI: 10.1023/A:1020816511924
Bouwma, P., & Hazlett, B. A. (2001). Integration of multiple predator cues by the crayfish
Faxonius propinquus. Animal Behaviour, 61(4), 771-776. DOI: 10.1006/anbe.2000.1649
Bradbury, J. W., & Vehrencamp, S. L. (1998). Principles of Animal Communication. Sinauer.
Breithaupt, T. (2010). Chemical communication in crayfish. In T. Breithaupt, & M. Thiel (Eds.),
Chemical Communication in Crustaceans (pp. 257-276). Springer.
Brönmark, C. (1990). How do herbivorous freshwater snails affect macrophytes?--A comment.
Ecology, 71(3), 1212-1215. DOI: 10.2307/1937391
Brönmark, C., & Hansson, L. A. (2000). Chemical communication in aquatic systems: An
introduction. Oikos, 88(1), 103-109. DOI: 10.1034/j.1600-0706.2000.880112.x
Brönmark, C., & Miner, J. G. (1992). Predator-induced phenotypical change in body
morphology in crucian carp. Science, 258(5086), 1348-1350. DOI:
10.1126/science.258.5086.1348 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 103
Brönmark, C., & Weisner, S. (1992). Indirect effects of fish community structure on submerged
vegetation in shallow, eutrophic lakes - An alternative mechanism. Hydrobiologia,
243(1), 293-301. DOI: 10.1007/BF00007045
Brower, L. P. (1988). Avian predation on the monarch butterfly and its implications for mimicry
theory. The American Naturalist, 131, S4-S6. DOI: 10.1086/284763
Brown, G. E., & Chivers, D. P. (2005). Learning as an adaptive response to predation. In P.
Barbosa & I. Castellanos (Eds.), Ecology of Predator–Prey Interactions (pp. 34-54).
Oxford University Press.
Brown, G. E., Chivers, D. P., & Smith, R. J. F. (1995). Localized defecation by pike: A response
to labelling by cyprinid alarm pheromone?. Behavioral Ecology and Sociobiology, 36(2),
105-110. DOI: 10.1007/BF00170715
Brown, G. E., Rive, A. C., Ferrari, M. C., & Chivers, D. P. (2006). The dynamic nature of
antipredator behavior: Prey fish integrate threat-sensitive antipredator responses within
background levels of predation risk. Behavioral Ecology and Sociobiology, 61(1), 9-16.
DOI: 10.1007/s00265-006-0232-y
Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage, & G. B. West. (2004). Towards a
metabolic theory of ecology. Ecology, 85(7), 1771–1789. DOI: 10.1890/03-9000
Brown, J. S. (1999). Vigilance, patch use and habitat selection: Foraging under predation risk.
Evolutionary Ecology Research, 1(1), 49-71.
Brown, J. S., Laundré, J. W., & Gurung, M. (1999). The ecology of fear: Optimal foraging, game
theory, and trophic interactions. Journal of Mammalogy, 80(2), 385-399. DOI:
10.2307/1383287 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 104
Brown, L. E., Edwards, F. K., Milner, A. M., Woodward, G., & Ledger, M. E. (2011). Food web
complexity and allometric scaling relationships in stream mesocosms: Implications for
experimentation. Journal of Animal Ecology, 80(4), 884-895. DOI: 10.1111/j.1365-
2656.2011.01814.x
Bryer, P. J., Mirza, R. S., & Chivers, D. P. (2001). Chemosensory assessment of predation risk
by slimy sculpins (Cottus cognatus): Responses to alarm, disturbance, and predator cues.
Journal of Chemical Ecology, 27(3), 533-546. DOI: 10.1023/A:1010332820944
Carpenter, S. R., & Lodge, D. M. (1986). Effects of submersed macrophytes on ecosystem
processes. Aquatic Botany, 26, 341-370. DOI: 10.1016/0304-3770(86)90031-8
Carreira, B. M., Dias, M. P., & Rebelo, R. (2014). How consumption and fragmentation of
macrophytes by the invasive crayfish Procambarus clarkii shape the macrophyte
communities of temporary ponds. Hydrobiologia, 721(1), 89-98. DOI: 10.1007/s10750-
013-1651-1
Carreira, B. M., Segurado, P., Laurila, A., & Rebelo, R. (2017). Can heat waves change the
trophic role of the world’s most invasive crayfish? Diet shifts in Procambarus clarkii.
PloS One, 12(9), e0183108. DOI: 10.1371/journal.pone.0183108
Chambers, P. A., Hanson, J., Burke, J. M., & Prepas, E. E. (1990). The impact of the crayfish
Faxonius virilis on aquatic macrophytes. Freshwater Biology, 24(1), 81-91. DOI:
10.1111/j.1365-2427.1990.tb00309.x
Chambers, P. A., Hanson, J. M., & Prepas, E. E. (1991). The effect of aquatic plant chemistry
and morphology on feeding selectivity by the crayfish, Faxonius virilis. Freshwater
Biology, 25(2), 339-348. DOI: 10.1111/j.1365-2427.1991.tb00496.x ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 105
Chibucos, K., Wofford, S. J., & Moore, P. A. (2015). Hierarchical decision making: Resource
distribution exhibits stronger effect on crayfish dominance relationships and shelter
occupation than prior social experience and resource ownership. Behaviour, 152(7-8),
1063-1082. DOI: 10.1163/1568539X-00003292
Chivers, D. P., & Mirza, R. S. (2001). Predator diet cues and the assessment of predation risk by
aquatic vertebrates: A review and prospectus. In A. Marchlewska-Koj, J. J. Lepri, & D.
Müller-Schwarze (Eds.), Chemical Signals in Vertebrates 9 (pp. 277-284). Springer.
Chivers, D. P., Mirza, R. S., Bryer, P. J., & Kiesecker, J. M. (2001). Threat-sensitive predator
avoidance by slimy sculpins: Understanding the importance of visual versus chemical
information. Canadian Journal of Zoology, 79(5), 867-873. DOI: 10.1139/z01-049
Chivers, D. P., Wisenden, B. D., & Smith, R. J. F. (1996). Damselfly larvae learn to recognize
predators from chemical cues in the predator's diet. Animal Behaviour, 52(2), 315-320.
DOI: 10.1006/anbe.1996.0177
Clark, J. L., & Moore, P. A. (2018). The role of sensory modalities in producing nonconsumptive
effects for a crayfish–bass predator–prey system. Canadian Journal of Zoology, 96(7),
680-691. DOI: 10.1139/cjz-2017-0109
Costa, G. C. (2009). Predator size, prey size, and dietary niche breadth relationships in marine
predators. Ecology, 90(7), 2014-2019. DOI: 10.1890/08-1150.1
Craig, J. K., Burke, B. J., Crowder, L. B., & Rice, J. A. (2006). Prey growth and size‐dependent
predation in juvenile estuarine fishes: Experimental and model analyses. Ecology, 87(9),
2366-2377. DOI: 10.1890/0012-9658(2006)87[2366:PGASPI]2.0.CO;2 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 106
Crandall, K. A., & Buhay, J. E. (2007). Global diversity of crayfish (Astacidae, Cambaridae, and
Parastacidae—Decapoda) in freshwater. In E.V. Balian, C. Lévêque, H. Segers, K.
Martens (Eds.), Freshwater Animal Diversity Assessment (pp. 295-301). Springer.
Cronin, G., Lodge, D. M., Hay, M. E., Miller, M., Hill, A. M., Horvath, T., …, & Wahl, M.
(2002). Crayfish feeding preferences for freshwater macrophytes: The influence of plant
structure and chemistry. Journal of Crustacean Biology, 22(4), 708-718. DOI:
10.1651/0278-0372(2002)022[0708:CFPFFM]2.0.CO;2
Dall, S. R., Giraldeau, L. A., Olsson, O., McNamara, J. M., & Stephens, D. W. (2005).
Information and its use by animals in evolutionary ecology. Trends in Ecology &
Evolution, 20(4), 187-193. DOI: 10.1016/j.tree.2005.01.010
Dawidowicz, P., & Loose, C. J. (1992). Metabolic costs during predator‐induced diel vertical
migration of Daphnia. Limnology and Oceanography, 37(8), 1589-1595. DOI:
10.4319/lo.1992.37.8.1589
Derby, C. D., & Sorensen, P. W. (2008). Neural processing, perception, and behavioral
responses to natural chemical stimuli by fish and crustaceans. Journal of Chemical
Ecology, 34(7), 898-914. DOI: 10.1007/s10886-008-9489-0
DeWitt, T. J. (1998). Costs and limits of phenotypic plasticity: Tests with predator‐induced
morphology and life history in a freshwater snail. Journal of Evolutionary Biology, 11(4),
465-480. DOI: 10.1046/j.1420-9101.1998.11040465.x
DiSciullo, R. A., & Basolo, A. L. (2020). Body size, but not age‐at‐maturation or context, affects
the expression of predator‐induced behavioural plasticity in female green swordtails
(Xiphophorus hellerii). Ethology, 126(3), 320-332. DOI: 10.1111/eth.12974 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 107
Dorn, N. J., & Wojdak, J. M. (2004). The role of omnivorous crayfish in littoral communities.
Oecologia, 140(1), 150-159. DOI: 10.1007/s00442-004-1548-9
Dusenbery, D. B. (1992). Sensory ecology: How Organisms Acquire and Respond to
Information. WH Freeman.
Evans, D. H., Piermarini, P. M., & Choe, K. P. (2005). The multifunctional fish gill: Dominant
site of gas exchange, osmoregulation, acid-base regulation, and excretion of nitrogenous
waste. Physiological Reviews, 85(1), 97-177. DOI: 10.1152/physrev.00050.2003
Feminella, J. W., & Resh, V. H. (1989). Submersed macrophytes and grazing crayfish: An
experimental study of herbivory in a California freshwater marsh. Ecography, 12(1), 1-8.
DOI: 10.1111/j.1600-0587.1989.tb00815.x
Fenton, M. B., & Fullard, J. H. (1979). The influence of moth hearing on bat echolocation
strategies. Journal of Comparative Physiology, 132(1), 77-86. DOI:
10.1007/BF00617734
Ferland-Raymond, B., & Murray, D. L. (2008). Predator diet and prey adaptive responses: Can
tadpoles distinguish between predators feeding on congeneric vs. conspecific prey?.
Canadian Journal of Zoology, 86(12), 1329-1336. DOI: 10.1139/Z08-117
Ferner, M. C., & Weissburg, M. J. (2005). Slow-moving predatory gastropods track prey odors
in fast and turbulent flow. Journal of Experimental Biology, 208(5), 809-819. DOI:
10.1242/jeb.01438
Fero, K., & Moore, P. A. (2008). Social spacing of crayfish in natural habitats: What role does
dominance play? Behavioral Ecology and Sociobiology, 62(7), 1119-1125. DOI:
10.1007/s00265-007-0540-x ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 108
Ferrari, M. C., Trowell, J. J., Brown, G. E., & Chivers, D. P. (2005). The role of learning in the
development of threat-sensitive predator avoidance by fathead minnows. Animal
Behaviour, 70(4), 777-784. DOI: 10.1016/j.anbehav.2005.01.009
Ferrari, M. C., Sih, A., & Chivers, D. P. (2009). The paradox of risk allocation: A review and
prospectus. Animal Behaviour, 78(3), 579-585. DOI: 10.1016/j.anbehav.2009.05.034
Ferrari, M. C., Wisenden, B. D., & Chivers, D. P. (2010). Chemical ecology of predator–prey
interactions in aquatic ecosystems: A review and prospectus. Canadian Journal of
Zoology, 88(7), 698-724. DOI: 10.1139/Z10-029
Folin, O., & Ciocalteu, V. (1927). On tyrosine and tryptophane determinations in proteins.
Journal of Biological Chemistry, 73(2), 627-650.
Fortin, D., Boyce, M. S., Merrill, E. H., & Fryxell, J. M. (2004). Foraging costs of vigilance in
large mammalian herbivores. Oikos, 107(1), 172-180. DOI: 10.1111/j.0030-
1299.2004.12976.x
Fossat, P., Bacqué-Cazenave, J., De Deurwaerdère, P., Cattaert, D., & Delbecque, J. P. (2015).
Serotonin, but not dopamine, controls the stress response and anxiety-like behavior in the
crayfish Procambarus clarkii. Journal of Experimental Biology, 218(17), 2745-2752.
DOI: 10.1242/jeb.120550
Fox, J. & Weisberg, S. (2019). An R Companion to Applied Regression (3rd edition). Sage.
Fritz, H., Guillemain, M., & Durant, D. (2002). The cost of vigilance for intake rate in the
mallard (Anas platyrhynchos): An approach through foraging experiments. Ethology
Ecology & Evolution, 14(2), 91-97. DOI: 10.1080/08927014.2002.9522748 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 109
Garvey, J. E., Stein, R. A., & Thomas, H. M. (1994). Assessing how fish predation and
interspecific prey competition influence a crayfish assemblage. Ecology, 75(2), 532-547.
DOI: 10.2307/1939556
Gaynor, K. M., Brown, J. S., Middleton, A. D., Power, M. E., & Brashares, J. S. (2019).
Landscapes of fear: Spatial patterns of risk perception and response. Trends in Ecology &
Evolution, 34(4), 355-368. DOI: 10.1016/j.tree.2019.01.004
Gherardi, F., & Acquistapace, P. (2007). Invasive crayfish in Europe: The impact of
Procambarus clarkii on the littoral community of a Mediterranean lake. Freshwater
Biology, 52(7), 1249-1259. DOI: 10.1111/j.1365-2427.2007.01760.x
Gherardi, F., Mavuti, K. M., Pacini, N. I. C., Tricarico, E., & Harper, D. M. (2011). The smell of
danger: Chemical recognition of fish predators by the invasive crayfish Procambarus
clarkii. Freshwater Biology, 56(8), 1567-1578. DOI: 10.1111/j.1365-2427.2011.02595.x
Glover, C. N., Bucking, C., & Wood, C. M. (2013). The skin of fish as a transport epithelium: A
review. Journal of Comparative Physiology B, 183(7), 877-891. DOI: 10.1007/s00360-
013-0761-4
Gotceitas, V. (1990). Foraging and predator avoidance: A test of a patch choice model with
juvenile bluegill sunfish. Oecologia, 83(3), 346-351. DOI: 10.1007/BF00317558
Grabowski, J. H. (2004). Habitat complexity disrupts predator–prey interactions but not the
trophic cascade on oyster reefs. Ecology, 85(4), 995-1004. DOI: 10.1890/03-0067
Grant, J. W. G., & Bayly, I. A. E. (1981). Predator induction of crests in morphs of the Daphnia
carinata King complex. Limnology & Oceanography, 26(2): 201-218. DOI:
10.4319/lo.1981.26.2.0201 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 110
Gresens, S. E. (1995). Grazer diversity, competition and the response of the periphyton
community. Oikos, 73(3), 336-346. DOI: 10.2307/3545957
Haggerty, M. B., Anderson, T. W., & Long, J. D. (2018). Fish predators reduce kelp frond loss
via a trait‐mediated trophic cascade. Ecology, 99(7), 1574-1583. DOI: 10.1002/ecy.2380
Hambright, K. D. (1991). Experimental analysis of prey selection by largemouth bass: Role of
predator mouth width and prey body depth. Transactions of the American Fisheries
Society, 120(4), 500-508. DOI: 10.1577/1548-8659(1991)120<0500:EAOPSB>2.3.CO;2
Hansen, B., Bjornsen, P. K., & Hansen, P. J. (1994). The size ratio between planktonic predators
and their prey. Limnology & Oceanography, 39(2), 395-403. DOI:
10.4319/lo.1994.39.2.0395
Hasson, O. (1991). Pursuit-deterrent signals: Communication between prey and predator. Trends
in Ecology & Evolution, 6(10), 325-329. DOI: 10.1016/0169-5347(91)90040-5
Hawlena, D., & Schmitz, O. J. (2010). Physiological stress as a fundamental mechanism linking
predation to ecosystem functioning. The American Naturalist, 176(5), 537-556. DOI:
10.1086/656495
Hay, M. E., & Fuller, P. J. (1981). Seed escape from heteromyid rodents: The importance of
microhabitat and seed preference. Ecology, 62(5), 1395-1399. DOI: 10.2307/1937304
Hay, M. E., & Kubanek, J. (2002). Community and ecosystem level consequences of chemical
cues in the plankton. Journal of Chemical Ecology, 28(10), 2001-2016. DOI:
10.1023/A:1020797827806
Hazlett, B. A., & Schoolmaster, D. R. (1998). Responses of cambarid crayfish to predator odor.
Journal of Chemical Ecology, 24(11), 1757-1770. DOI: 10.1023/A:1022347214559 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 111
Hazlett, B. (1999). Responses to multiple chemical cues by the crayfish Orconectes virilis.
Behaviour, 136(2), 161-177. DOI: 10.1163/156853999501261
Heck, K. L., & Crowder, L. B. (1991). Habitat structure and predator—prey interactions in
vegetated aquatic systems. In S. S. Bell, E. D. McCoy, & H. R. Mushinsky (Eds.),
Habitat Structure (pp. 281-299). Springer.
Hegab, I. M., Jin, Y., Ye, M., Wang, A., Yin, B., Yang, S., & Wei, W. (2014). Defensive
responses of Brandt’s voles (Lasiopodomys brandtii) to stored cat feces. Physiology &
Behavior, 123, 193-199. DOI: 10.1016/j.physbeh.2013.10.030
Hegab, I. M., Kong, S., Yang, S., Mohamaden, W. I., & Wei, W. (2015). The ethological
relevance of predator odors to induce changes in prey species. Acta Ethologica, 18(1), 1-
9. DOI: 10.1007/s10211-014-0187-3
Helfman, G. S. (1989). Threat-sensitive predator avoidance in damselfish-trumpetfish
interactions. Behavioral Ecology and Sociobiology, 24(1), 47-58. DOI:
10.1007/BF00300117
Henry, L. M., Bannerman, J. A., Gillespie, D. R., & Roitberg, B. D. (2010). Predator identity and
the nature and strength of food web interactions. Journal of Animal Ecology, 79(6), 1164-
1171. DOI: 10.1111/j.1365-2656.2010.01723.x
Hernández, L., & Laundré, J. W. (2005). Foraging in the ‘landscape of fear’and its implications
for habitat use and diet quality of elk Cervus elaphus and bison Bison bison. Wildlife
Biology, 11(3), 215-220. DOI: 10.2981/0909-6396(2005)11[215:FITLOF]2.0.CO;2
Hill, A. M., & Lodge, D. M. (1995). Multi-trophic-level impact of sublethal interactions between
bass and omnivorous crayfish. Journal of the North American Benthological Society,
14(2), 306-314. DOI: 10.2307/1467782 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 112
Hill, J. E., Nico, L. G., Chichra, C. E., & Gilbert, C. R. (2004). Prey vulnerability to peacock
cichlids and largemouth bass based on predator gape and prey body depth. In
Proceedings of the Southeastern Association of Fish and Wildlife Agencies, 58, 47-56.
Hill, J. M., & Weissburg, M. J. (2013). Predator biomass determines the magnitude of non-
consumptive effects (NCEs) in both laboratory and field environments. Oecologia,
172(1), 79-91. DOI: 10.1007/s00442-012-2488-4
Hill, J. M., & Weissburg, M. J. (2014). Crabs interpret the threat of predator body size and
biomass via cue concentration and diet. Animal Behaviour, 92, 117-123. DOI:
10.1016/j.anbehav.2014.03.025
Hoefler, C. D., Durso, L. C., & McIntyre, K. D. (2012). Chemical‐mediated predator avoidance
in the European house cricket (Acheta domesticus) is modulated by predator diet.
Ethology, 118(5), 431-437. DOI: 10.1111/j.1439-0310.2012.02028.x
Hogger, J. B. (1988). Ecology, population biology and behaviour. In D. M. Holdich & R. S.
Lowery (Eds.), Freshwater Crayfish: Biology, Management and Exploitation (pp. 114-
144). Croom Helm Ltd.
Holling, C. S. (1959). The components of predation as revealed by a study of small-mammal
predation of the European pine sawfly. The Canadian Entomologist, 91(5), 293-320.
DOI: 10.4039/Ent91293-5
Holmes, T. H., & McCormick, M. I. (2010). Size-selectivity of predatory reef fish on juvenile
prey. Marine Ecology Progress Series, 399, 273-283. DOI: 10.3354/meps08337
Holomuzki, J. R., & Hatchett, L. A. (1994). Predator avoidance costs and habituation to fish
chemicals by a stream isopod. Freshwater Biology, 32(3), 585-592. DOI: 10.1111/j.1365-
2427.1994.tb01149.x ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 113
Hothorn, T., Bretz, F., & Westfall, P. (2008). Simultaneous Inference in General Parametric
Models. Biometrical Journal, 50(3), 346-363. DOI: 10.1002/bimj.200810425
Huskey, S. H., & Turingan, R. G. (2001). Variation in prey-resource utilization and oral jaw
gape between two populations of largemouth bass, Micropterus salmoides.
Environmental Biology of Fishes, 61(2), 185-194. DOI: 10.1023/A:1011095526939
Illius, A. W., & Fitzgibbon, C. (1994). Costs of vigilance in foraging ungulates. Animal
Behaviour, 47(2), 481–484. DOI: 10.1006/anbe.1994.1067
Inoue, N., Satoh, J., Mekata, T., Iwasaki, T., & Mori, K. (2016). Maximum prey size estimation
of longtooth grouper, Epinephelus bruneus, using morphological features, and predation
experiments on juvenile cannibalism. Aquaculture Research, 47(2), 605-611. DOI:
10.1111/are.12519
Johnson, K. D., & Smee, D. L. (2012). Size matters for risk assessment and resource allocation
in bivalves. Marine Ecology Progress Series, 462, 103-110. DOI: 10.3354/meps09804
Jurcak, A. M., & Moore, P. A. (2014). Behavioral decisions in sensory landscapes: Crayfish use
chemical signals to make habitat use choices. Journal of Crustacean Biology, 34(5), 559-
564. DOI: 10.1163/1937240X-00002266
Jurcak, A. M., & Moore, P. A. (2018). Sensory signals and the reaction space in predator–prey
interactions. Hydrobiologia, 816(1), 137-152. DOI: 10.1007/s10750-018-3574-3
Karpouzi, V. S., & Stergiou, K. I. (2003). The relationships between mouth size and shape and
body length for 18 species of marine fishes and their trophic implications. Journal of Fish
Biology, 62(6), 1353-1365. DOI: 10.1046/j.1095-8649.2003.00118.x
Kats, L. B., & Dill, L. M. (1998). The scent of death: Chemosensory assessment of predation risk
by prey animals. Ecoscience, 5(3), 361-394. DOI: 10.1080/11956860.1998.11682468 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 114
Keller, T. A., Tomba, A. M., & Moore, P. A. (2001). Orientation in complex chemical
landscapes: Spatial arrangement of chemical sources influences crayfish food‐finding
efficiency in artificial stream. Limnology and Oceanography, 46(2), 238-247. DOI:
10.4319/lo.2001.46.2.0238
Kennedy, D., & Bruno, M. S. (1961). The spectral sensitivity of crayfish and lobster vision. The
Journal of General Physiology, 44(6), 1089-1102. DOI: 10.1085/jgp.44.6.1089
Killen, S. S., Atkinson, D., & Glazier, D. S. (2010). The intraspecific scaling of metabolic rate
with body mass in fishes depends on lifestyle and temperature. Ecology Letters, 13(2),
184-193. DOI: 10.1111/j.1461-0248.2009.01415.x
Kohl, M. T., Stahler, D. R., Metz, M. C., Forester, J. D., Kauffman, M. J., Varley, N., ... &
MacNulty, D. R. (2018). Diel predator activity drives a dynamic landscape of fear.
Ecological Monographs, 88(4), 638-652. DOI: 10.1002/ecm.1313
Kusch, R. C., Mirza, R. S., & Chivers, D. P. (2004). Making sense of predator scents:
Investigating the sophistication of predator assessment abilities of fathead minnows.
Behavioral Ecology and Sociobiology, 55(6), 551-555. DOI: 10.1007/s00265-003-0743-8
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in
linear mixed effects models. Journal of Statistical Software, 82(13). DOI:
10.18637/jss.v082.i13
Lamberti, G. A., Ashkenas, L. R., Gregory, S. V., & Steinman, A. D. (1987). Effects of three
herbivores on periphyton communities in laboratory streams. Journal of the North
American Benthological Society, 6(2), 92-104. DOI: 10.2307/1467219
Lampert, W. (1989). The adaptive significance of diel vertical migration of zooplankton.
Functional Ecology, 3(1), 21-27. DOI: 10.2307/2389671 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 115
Lampert, W. (1993). Ultimate causes of diel vertical migration of zooplankton: New evidence for
the predator-avoidance hypothesis. Archiv für Hydrobiologie–BeiheftErgebnisse der
Limnologie, 39, 79-88.
Large, S. I., & Smee, D. L. (2010). Type and nature of cues used by Nucella lapillus to evaluate
predation risk. Journal of Experimental Marine Biology and Ecology, 396(1), 10-17.
DOI: 10.1016/j.jembe.2010.10.005
Laska, M., Fendt, M., Wieser, A., Endres, T., Salazar, L. T. H., & Apfelbach, R. (2005).
Detecting danger—or just another odorant? Olfactory sensitivity for the fox odor
component 2, 4, 5-trimethylthiazoline in four species of mammals. Physiology &
Behavior, 84(2), 211-215. DOI: 10.1016/j.physbeh.2004.11.006
Laughlin, S. B. (2011). Energy, information, and the work of the brain. In R. Levin, S. Laughlin,
C. De La Rocha & A. Blackwell (Eds.), Work Meets Life (pp. 39-67). MIT Press.
Laundré, J. W., Hernández, L., & Altendorf, K. B. (2001). Wolves, elk, and bison:
Reestablishing the" landscape of fear" in Yellowstone National Park, USA. Canadian
Journal of Zoology, 79(8), 1401-1409. DOI: 10.1139/z01-094
Laundré, J. W., Hernández, L., & Ripple, W. J. (2010). The landscape of fear: Ecological
implications of being afraid. Open Ecology Journal, 3, 1-7. DOI:
10.2174/1874213001003030001
Laurila, A., Kujasalo, J., & Ranta, E. (1997). Different antipredator behaviour in two anuran
tadpoles: Effects of predator diet. Behavioral Ecology and Sociobiology, 40(5), 329-336.
DOI: 10.1007/s002650050349 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 116
Lawrence, J. M. (1958). Estimated sizes of various forage fishes largemouth bass can swallow.
Proceedings of the Annual Conference of the Southeastern Association of Game and Fish
Commissioners, 11, 220–225.
Lee, S. I., Hwang, S., Joe, Y. E., Cha, H. K., Joo, G. H., Lee, H. J., Kim, J. W., & Jablonski, P.
G. (2013). Direct look from a predator shortens the risk-assessment time by prey. PLoS
One, 8(6). DOI: 10.1371/journal.pone.0064977
Lima, S. L., & Dill, L. M. (1990). Behavioral decisions made under the risk of predation: A
review and prospectus. Canadian Journal of Zoology, 68(4), 619-640. DOI: 10.1139/z90-
092
Lima, S. L. (1998). Nonlethal effects in the ecology of predator-prey interactions. Bioscience,
48(1), 25-34. DOI: 10.2307/1313225
Lima, S. L., & Bednekoff, P. A. (1999). Temporal variation in danger drives antipredator
behavior: The predation risk allocation hypothesis. The American Naturalist, 153(6),
649-659. DOI: 10.1086/303202
Lodge, D. M. (1991). Herbivory on freshwater macrophytes. Aquatic Botany, 41(1-3), 195-224.
DOI: 10.1016/0304-3770(91)90044-6
Lodge, D. M., & Lorman, J. G. (1987). Reductions in submersed macrophyte biomass and
species richness by the crayfish Faxonius rusticus. Canadian Journal of Fisheries and
Aquatic Sciences, 44(3), 591-597. DOI: 10.1139/f87-072
Lodge, D. M., Kershner, M. W., Aloi, J. E., & Covich, A. P. (1994). Effects of an omnivorous
crayfish (Faxonius rusticus) on a freshwater littoral food web. Ecology, 75(5): 1265-
1281. DOI: 10.2307/1937452 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 117
Loose, C. J., & Dawidowicz, P. (1994). Trade‐offs in diel vertical migration by zooplankton: The
costs of predator avoidance. Ecology, 75(8), 2255-2263. DOI: 10.2307/1940881
Lotka, A. (1927). Fluctuations in the Abundance of a Species considered Mathematically.
Nature, 119, 12. DOI: 10.1038/119012a0
Luczkovich, J. J., Norton, S. R., & Gilmore, R. G. (1995). The influence of oral anatomy on prey
selection during the ontogeny of two percoid fishes, Lagodon rhomboides and
Centropomus undecimalis. Environmental Biology of Fishes, 44(1-3), 79-95. DOI:
10.1007/BF00005908
Ludington, T. S., & Moore, P. A. (2017). The degree of impairment of foraging in crayfish
(Faxonius virilis) due to insecticide exposure is dependent upon turbulence dispersion.
Archives of Environmental Contamination and Toxicology, 72(2), 281-293. DOI:
10.1007/s00244-016-0341-1
Luecke, C., Vanni, M. J., Magnuson, J. J., Kitchell, J. F., & Jacobson, P. T. (1990). Seasonal
regulation of Daphnia populations by planktivorous fish: Implications for the spring
clear‐water phase. Limnology and Oceanography, 35(8), 1718-1733. DOI:
10.4319/lo.1990.35.8.1718
Luttbeg, B., & Trussell, G. C. (2013). How the informational environment shapes how prey
estimate predation risk and the resulting indirect effects of predators. The American
Naturalist, 181(2), 182-194. DOI: 10.1086/668823
MacArthur, R. H., & Pianka, E. R. (1966). On optimal use of a patchy environment. The
American Naturalist, 100(916), 603-609. DOI: 10.1086/282454 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 118
Magurran, A. E., & Seghers, B. H. (1990). Population differences in predator recognition and
attack cone avoidance in the guppy Poecilia reticulata. Animal Behaviour, 40(3), 443-
452. DOI: 10.1016/S0003-3472(05)80524-X
Martin III, A. L., & Moore, P. A. (2008). The influence of dominance on shelter preference and
eviction rates in the crayfish, Faxonius rusticus. Ethology, 114(4), 351-360. DOI:
10.1111/j.1439-0310.2008.01473.x
Matassa, C. M., & Trussell, G. C. (2011). Landscape of fear influences the relative importance of
consumptive and nonconsumptive predator effects. Ecology, 92(12), 2258-2266. DOI:
10.1890/11-0424.1
Mathis, A. (2003). Use of chemical cues in detection of conspecific predators and prey by newts,
Notophthalmus viridescens. Chemoecology, 13(4), 193-197. DOI: 10.1007/s00049-003-
0248-y
Maynard Smith, J. (1982). Do animals convey information about their intentions?. Journal of
Theoretical Biology, 97(1), 1-5. DOI: 10.1016/0022-5193(82)90271-5
McMahon, T. E., & Holanov, S. H. (1995). Foraging success of largemouth bass at different
light intensities: Implications for time and depth of feeding. Journal of Fish Biology,
46(5), 759-767. DOI: 10.1111/j.1095-8649.1995.tb01599.x
McNeely, D. L., Futrell, B. N., & Sih, A. (1990). An experimental study on the effects of
crayfish on the predator-prey interaction between bass and sculpin. Oecologia, 85(1), 69-
73. DOI: 10.1007/BF00317344
Mihalitsis, M., & Bellwood, D. R. (2017). A morphological and functional basis for maximum
prey size in piscivorous fishes. PLoS One, 12(9), e0184679. DOI:
10.1371/journal.pone.0184679 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 119
Miller, J. R., Ament, J. M., & Schmitz, O. J. (2014). Fear on the move: predator hunting mode
predicts variation in prey mortality and plasticity in prey spatial response. Journal of
Animal Ecology, 83(1), 214-222. DOI: 10.1111/1365-2656.12111
Mittelbach, G. G. (1981). Foraging efficiency and body size: A study of optimal diet and habitat
use by bluegills. Ecology, 62(5), 1370-1386. DOI: 10.2307/1937300
Momot, W. T. (1995). Redefining the role of crayfish in aquatic ecosystems. Reviews in
Fisheries Science, 3(1), 33-63. DOI: 10.1080/10641269509388566
Momot, W. T., Gowing, H., & Jones, P. D. (1978). The dynamics of crayfish and their role in
ecosystems. The American Midland Naturalist, 99(1), 10-35. DOI: 10.2307/2424930
Moore, P. A., & Atema, J. (1991). Spatial information in the three-dimensional fine structure of
an aquatic odor plume. The Biological Bulletin, 181(3), 408-418. DOI: 10.2307/1542361
Moore, P. A., & Bergman, D. A. (2005). The smell of success and failure: The role of intrinsic
and extrinsic chemical signals on the social behavior of crayfish. Integrative and
Comparative Biology, 45(4), 650-657. DOI: 10.1093/icb/45.4.650
Moore, P., & Crimaldi, J. (2004). Odor landscapes and animal behavior: Tracking odor plumes
in different physical worlds. Journal of Marine Systems, 49(1-4), 55-64. DOI:
10.1016/j.jmarsys.2003.05.005
Moore, P. A., & Grills, J. L. (1999). Chemical orientation to food by the crayfish Faxonius
rusticus: Influence of hydrodynamics. Animal Behaviour, 58(5), 953-963. DOI:
10.1006/anbe.1999.1230
Moore, P. A., Fortino, C. P., Stamplis, Z., & Steffler, M. (2012). Aquatic Vegetation Survey
2012 for Douglas Lake. ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 120
Moretto, A. S., & Distel, R. A. (1999). Effects of selective defoliation on the competitive
interaction between palatable and unpalatable grasses native to a temperate semi-arid
grassland of Argentina. Journal of Arid Environments, 42(3), 167-175. DOI:
10.1006/jare.1999.0510
Murray, D. L., & Jenkins, C. L. (1999). Perceived predation risk as a function of predator dietary
cues in terrestrial salamanders. Animal Behaviour, 57(1), 33-39. DOI:
10.1006/anbe.1998.0986
Neal, A. E., & Moore, P. A. (2017). Mimicking natural systems: Changes in behavior as a result
of dynamic exposure to naproxen. Ecotoxicology and Environmental Safety, 135, 347-
357. DOI: 10.1016/j.ecoenv.2016.10.015
Nelson, E. H., Matthews, C. E., & Rosenheim, J. A. (2004). Predators reduce prey population
growth by inducing changes in prey behavior. Ecology, 85(7), 1853-1858. DOI:
10.1890/03-3109
Nilsson, P. A., Brönmark, C., & Pettersson, L. B. (1995). Benefits of a predator-induced
morphology in crucian carp. Oecologia, 104(3), 291-296.
Nilsson, P. A., & Brönmark, C. (2000). Prey vulnerability to a gape‐size limited predator:
behavioural and morphological impacts on northern pike piscivory. Oikos, 88(3), 539-
546. DOI: 10.1034/j.1600-0706.2000.880310.x
Nowlin, W. H., Drenner, R. W., Guckenberger, K. R., Lauden, M. A., Alonso, G. T., Fennell, J.
E., & Smith, J. L. (2006). Gape limitation, prey size refuges and the top–down impacts of
piscivorous largemouth bass in shallow pond ecosystems. Hydrobiologia, 563(1), 357-
369. DOI: 10.1007/s10750-006-0024-4 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 121
Nyström, P., & Strand, J. (1996). Grazing by a native and an exotic crayfish on aquatic
macrophytes. Freshwater Biology, 36(3), 673-682. DOI: 10.1046/j.1365-2427.1996.d01-
508.x
Ohgushi, T., Schmitz, O., & Holt, R. D. (Eds.). (2012). Trait-Mediated Indirect Interactions:
Ecological and Evolutionary Perspectives. Cambridge University Press.
Olson, M. H. (1996). Predator-prey interactions in size-structured fish communities: Implications
of prey growth. Oecologia, 108(4), 757-763. DOI: 10.1007/BF00329052
Palmer, M. S., Fieberg, J., Swanson, A., Kosmala, M., & Packer, C. (2017). A ‘dynamic’
landscape of fear: Prey responses to spatiotemporal variations in predation risk across the
lunar cycle. Ecology Letters, 20(11), 1364-1373. DOI: 10.1111/ele.12832
Parkyn, S. M., Rabeni, C. F., & Collier, K. J. (1997). Effects of crayfish (Paranephrops
planifrons: Parastacidae) on in‐stream processes and benthic faunas: A density
manipulation experiment. New Zealand Journal of Marine and Freshwater Research,
31(5), 685-692. DOI: 10.1080/00288330.1997.9516798
Parsons, A. J., Harvey, A., & Johnson, I. R. (1991). Plant-animal interactions in a continuously
grazed mixture. II. The role of differences in the physiology of plant growth and of
selective grazing on the performance and stability of species in a mixture. Journal of
Applied Ecology, 28(2), 635-658.
Parsons, M. H., Apfelbach, R., Banks, P. B., Cameron, E. Z., Dickman, C. R., Frank, A. S., ... &
Sparrow, E. E. (2018). Biologically meaningful scents: A framework for understanding
predator–prey research across disciplines. Biological Reviews, 93(1), 98-114. DOI:
10.1111/brv.12334 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 122
Patek, S. N., & Caldwell, R. L. (2005). Extreme impact and cavitation forces of a biological
hammer: Strike forces of the peacock mantis shrimp Odontodactylus scyllarus. Journal of
Experimental Biology, 208(19), 3655-3664. DOI: 10.1242/jeb.01831
Pauwels, K., Stoks, R., & De Meester, L. (2005). Coping with predator stress: Interclonal
differences in induction of heat‐shock proteins in the water flea Daphnia magna. Journal
of Evolutionary Biology, 18(4), 867-872. DOI: 10.1111/j.1420-9101.2005.00890.x
Pavey, C. R., & Fielder, D. R. (1996). The influence of size differential on agonistic behaviour in
the freshwater crayfish, Cherax cuspidatus (Decapoda: Parastacidae). Journal of Zoology,
238(3), 445-457. DOI: 10.1111/j.1469-7998.1996.tb05405.x
Payne, R., & Webb, D. (1971). Orientation by means of long range acoustic signaling in baleen
whales. Annals of the New York Academy of Sciences, 188(1), 110-141. DOI:
10.1111/j.1749-6632.1971.tb13093.x
Peacor, S. D., Peckarsky, B. L., Trussell, G. C., & Vonesh, J. R. (2013). Costs of predator-
induced phenotypic plasticity: a graphical model for predicting the contribution of
nonconsumptive and consumptive effects of predators on prey. Oecologia, 171(1), 1-10.
DOI: 10.1007/s00442-012-2394-9
Peacor, S. D., & Werner, E. E. (2001). The contribution of trait-mediated indirect effects to the
net effects of a predator. Proceedings of the National Academy of Sciences, 98(7), 3904-
3908. DOI: 10.1073/pnas.071061998
Peckarsky, B. L., Abrams, P. A., Bolnick, D. I., Dill, L. M., Grabowski, J. H., Luttbeg, B., ... &
Trussell, G. C. (2008). Revisiting the classics: Considering nonconsumptive effects in
textbook examples of predator–prey interactions. Ecology, 89(9), 2416-2425. DOI:
10.1890/07-1131.1 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 123
Persons, M. H., & Rypstra, A. L. (2001). Wolf spiders show graded antipredator behavior in the
presence of chemical cues from different sized predators. Journal of Chemical Ecology,
27(12), 2493-2504. DOI: 10.1023/A:1013679532070
Persson, L., Andersson, J., Wahlstrom, E., & Eklov, P. (1996). Size‐specific interactions in lake
systems: Predator gape limitation and prey growth rate and mortality. Ecology, 77(3),
900-911. DOI: 10.2307/2265510
Pettersson, L. B., & Brönmark, C. (1997). Density‐dependent costs of an inducible
morphological defense in crucian carp. Ecology, 78(6), 1805-1815. DOI: 10.1890/0012-
9658(1997)078[1805:DDCOAI]2.0.CO;2
Pianka, E. R. (1966). Latitudinal gradients in species diversity: A review of concepts. The
American Naturalist, 100(910), 33-46. DOI: 10.1086/282398
Pilati, A., & Vanni, M. J. (2007). Ontogeny, diet shifts, and nutrient stoichiometry in fish. Oikos,
116(10), 1663-1674. DOI: 10.1111/j.0030-1299.2007.15970.x
Pirtle, J. L., Eckert, G. L., & Stoner, A. W. (2012). Habitat structure influences the survival and
predator prey interactions of early juvenile red king crab Paralithodes camtschaticus.
Marine Ecology Progress Series, 465, 169-184. DOI: 10.3354/meps09883
Power, M. E., & Matthews, W. J. (1983). Algae-grazing minnows (Campostoma anomalum),
piscivorous bass (Micropterus spp.), and the distribution of attached algae in a small
prairie-margin stream. Oecologia, 60(3), 328-332. DOI: 10.1007/BF00376847
Preisser, E. L., & Bolnick, D. I. (2008). The many faces of fear: Comparing the pathways and
impacts of nonconsumptive predator effects on prey populations. PLoS One, 3(6). DOI:
10.1371/journal.pone.0002465 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 124
Preisser, E. L., Bolnick, D. I., & Benard, M. F. (2005). Scared to death? The effects of
intimidation and consumption in predator–prey interactions. Ecology, 86(2), 501-509.
DOI: 10.1890/04-0719
Puttlitz, M. H., Chivers, D. P., Kiesecker, J. M., & Blaustein, A. R. (1999). Threat‐sensitive
predator avoidance by larval Pacific treefrogs (Amphibia, Hylidae). Ethology, 105(5),
449-456. DOI: 10.1046/j.1439-0310.1999.00416.x
Quirt, J., & Lasenby, D. (2002). Cannibalism and ontogenetic changes in the response of the
freshwater shrimp Mysis relicta to chemical cues from conspecific predators. Canadian
Journal of Zoology, 80(6), 1022-1025. DOI: 10.1139/z02-084
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria.
Ramamonjisoa, N., & Mori, A. (2019). Temporal variation in behavioral responses to dietary
cues from a gape‐limited predator in tadpole prey: A test of the phylogenetic relatedness
hypothesis. Ethology, 125(9), 628-634. DOI: 10.1111/eth.12914
Reynolds, J., Souty-Grosset, C., & Richardson, A. (2013). Ecological roles of crayfish in
freshwater and terrestrial habitats. Freshwater Crayfish, 19(2): 197-218.
Ripple, W. J., & Beschta, R. L. (2003). Wolf reintroduction, predation risk, and cottonwood
recovery in Yellowstone National Park. Forest Ecology and Management, 184(1-3), 299-
313. DOI: 10.1016/S0378-1127(03)00154-3
Ripple, W. J., & Beschta, R. L. (2006). Linking wolves to willows via risk-sensitive foraging by
ungulates in the northern Yellowstone ecosystem. Forest Ecology and Management,
230(1-3), 96-106. DOI: 10.1016/j.foreco.2006.04.023 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 125
Ripple, W. J., & Beschta, R. L. (2007). Restoring Yellowstone’s aspen with wolves. Biological
Conservation, 138(3-4), 514-519. DOI: 10.1016/j.biocon.2007.05.006
Rodríguez, C. F., Bécares, E., Fernández-Aláez, M., & Fernández-Aláez, C. (2005). Loss of
diversity and degradation of wetlands as a result of introducing exotic crayfish.
Biological Invasions, 7(1), 75. DOI: 10.1007/s10530-004-9636-7
Roeder, K. D. (1962). The behaviour of free flying moths in the presence of artificial ultrasonic
pulses. Animal Behaviour, 10(3-4), 300-304. DOI: 10.1016/0003-3472(62)90053-2
Rose, M., Pollock, L., & Nol, E. (2016). Diet and prey size selectivity of Semipalmated Plovers
(Charadrius semipalmatus) in coastal Georgia. Canadian Journal of Zoology, 94(10),
727-732. DOI: 10.1139/cjz-2016-0039
Scharf, F. S., Juanes, F., & Rountree, R. A. (2000). Predator size-prey size relationships of
marine fish predators: Interspecific variation and effects of ontogeny and body size on
trophic-niche breadth. Marine Ecology Progress Series, 208, 229-248.
DOI:10.3354/meps208229
Scherer, A. E., & Smee, D. L. (2016). A review of predator diet effects on prey defensive
responses. Chemoecology, 26(3), 83-100. DOI: 10.1007/s00049-016-0208-y
Schmitt, R. J., & Holbrook, S. J. (1984). Gape-limitation, foraging tactics and prey size
selectivity of two microcarnivorous species of fish. Oecologia, 63(1), 6-12. DOI:
10.1007/BF00379778
Schmitz, O. J. (1998). Direct and indirect effects of predation and predation risk in old-field
interaction webs. The American Naturalist, 151(4), 327-342. DOI: 10.1086/286122 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 126
Schmitz, O. J., Beckerman, A. P., & O’Brien, K. M. (1997). Behaviorally mediated trophic
cascades: Effects of predation risk on food web interactions. Ecology, 78(5), 1388-1399.
DOI: 10.1890/0012-9658(1997)078[1388:BMTCEO]2.0.CO;2
Schmitz, O. J., Krivan, V., & Ovadia, O. (2004). Trophic cascades: The primacy of trait‐
mediated indirect interactions. Ecology Letters, 7(2), 153-163. DOI: 10.1111/j.1461-
0248.2003.00560.x
Schmitz, O. J., Buchkowski, R. W., Burghardt, K. T., & Donihue, C. M. (2015). Functional traits
and trait-mediated interactions: Connecting community-level interactions with ecosystem
functioning. In S. Pawar, G. Woodward, & A. I. Dell (Eds.), Advances in Ecological
Research (Vol. 52, pp. 319-343). Academic Press.
Schoeppner, N. M., & Relyea, R. A. (2005). Damage, digestion, and defense: The roles of alarm
cues and kairomones for inducing prey defenses. Ecology Letters, 8(5), 505-512. DOI:
10.1111/j.1461-0248.2005.00744.x
Seebacher, F., & Wilson, R. S. (2007). Individual recognition in crayfish (Cherax dispar): The
roles of strength and experience in deciding aggressive encounters. Biology Letters, 3(5),
471-474. DOI: 10.1098/rsbl.2007.0289
Shave, C. R., Townsend, C. R., & Crowl, T. A. (1994). Anti-predator behaviours of a freshwater
crayfish (Paranephrops zealandicus) to a native and an introduced predator. New
Zealand Journal of Ecology, 1-10.
Sheriff, M. J., Krebs, C. J., & Boonstra, R. (2009). The sensitive hare: Sublethal effects of
predator stress on reproduction in snowshoe hares. Journal of Animal Ecology, 78(6),
1249-1258. DOI: 10.1111/j.1365-2656.2009.01552.x ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 127
Shine, R., & Sun, L. X. (2003). Attack strategy of an ambush predator: Which attributes of the
prey trigger a pit‐viper’s strike? Functional Ecology, 17(3), 340-348. DOI:
10.1046/j.1365-2435.2003.00738.x
Sih, A. (1980). Optimal behavior: can foragers balance two conflicting demands?. Science,
210(4473), 1041-1043.
Sih, A. (1982). Foraging strategies and the avoidance of predation by an aquatic insect,
Notonecta hoffmanni. Ecology, 63(3), 786-796. DOI: 10.2307/1936799
Sih, A., Krupa, J., & Travers, S. (1990). An experimental study on the effects of predation risk
and feeding regime on the mating behavior of the water strider. The American Naturalist,
135(2), 284-290. DOI: 10.1086/285044
Simonis, J. L. (2013). Predator ontogeny determines trophic cascade strength in freshwater rock
pools. Ecosphere, 4(5), 1-25. DOI: 10.1890/ES13-00019.1
Smee, D. L., & Weissburg, M. J. (2006). Clamming up: Environmental forces diminish the
perceptive ability of bivalve prey. Ecology, 87(6), 1587-1598. DOI: 10.1890/0012-
9658(2006)87[1587:CUEFDT]2.0.CO;2
Smith, M. E., & Belk, M. C. (2001). Risk assessment in western mosquitofish (Gambusia
affinis): Do multiple cues have additive effects?. Behavioral Ecology and Sociobiology,
51(1), 101-107. DOI: 10.1007/s002650100415
Soszka, G. J. (1975). Ecological relations between invertebrates and submerged macrophytes in
the lake littoral. Ekologia Polska, 23, 393-415.
Stein, R. A., & Magnuson, J. J. (1976). Behavioral response of crayfish to a fish predator.
Ecology, 57(4), 751-761. DOI: 10.2307/1936188 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 128
Steiner, U. K., & Pfeiffer, T. (2007). Optimizing time and resource allocation trade-offs for
investment into morphological and behavioral defense. The American Naturalist, 169(1),
118-129. DOI: 10.1086/509939
Stevens, M. (2013). Sensory Ecology, Behaviour, and Evolution. Oxford University Press.
Studd, M., Montgomerie, R. D., & Robertson, R. J. (1983). Group size and predator surveillance
in foraging house sparrows (Passer domesticus). Canadian Journal of Zoology, 61(1),
226-231. DOI: 10.1139/z83-028
Sullivan, A. M., Picard, A. L., & Madison, D. M. (2005). To avoid or not to avoid? Factors
influencing the discrimination of predator diet cues by a terrestrial salamander. Animal
Behavior, 69(6), 1425-1433. DOI: 10.1016/j.anbehav.2004.08.017
Taniguchi, H., Nakano, S., & Tokeshi, M. (2003). Influences of habitat complexity on the
diversity and abundance of epiphytic invertebrates on plants. Freshwater Biology, 48(4),
718-728. DOI: 10.1046/j.1365-2427.2003.01047.x
Tollrian, R. (1995). Predator‐induced morphological defenses: Costs, life history shifts, and
maternal effects in Daphnia pulex. Ecology, 76(6), 1691-1705. DOI: 10.2307/1940703
Trussell, G. C., Ewanchuk, P. J., & Bertness, M. D. (2003). Trait‐mediated effects in rocky
intertidal food chains: Predator risk cues alter prey feeding rates. Ecology, 84(3), 629-
640. DOI: 10.1890/0012-9658(2003)084[0629:TMEIRI]2.0.CO;2
Turesson, H., Persson, A., & Brönmark, C. (2002). Prey size selection in piscivorous pikeperch
(Stizostedion lucioperca) includes active prey choice. Ecology of Freshwater Fish, 11(4),
223-233. DOI: 10.1034/j.1600-0633.2002.00019.x ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 129
Turner, A. M. (2008). Predator diet and prey behaviour: Freshwater snails discriminate among
closely related prey in a predator’s diet. Animal Behavior, 76(4), 1211-1217. DOI:
10.1016/j.anbehav.2008.06.005
Turner, A. M., Fetterolf, S. A., & Bernot, R. J. (1999). Predator identity and consumer behavior:
Differential effects of fish and crayfish on the habitat use of a freshwater snail.
Oecologia, 118(2), 242-247. DOI: 10.1007/s004420050724
Turner, A. M., & Mittelbach, G. G. (1990). Predator avoidance and community structure:
Interactions among piscivores, planktivores, and plankton. Ecology, 71(6), 2241-2254.
DOI: 10.2307/1938636
Turner, A. M., & Montgomery, S. L. (2003). Spatial and temporal scales of predator avoidance:
Experiments with fish and snails. Ecology, 84(3), 616-622. DOI: 10.1890/0012-
9658(2003)084[0616:SATSOP]2.0.CO;2
Turner, A. M., & Peacor, S. D. (2012). Scaling up infochemicals: Ecological consequences of
chemosensory assessment of predation risk. In C. Brönmark & L.-A. Hansson (Eds.),
Chemical Ecology in Aquatic Systems (pp. 140-157). Oxford University Press.
Urban, M. C. (2007). The growth–predation risk trade‐off under a growing gape‐limited
predation threat. Ecology, 88(10), 2587-2597. DOI: 10.1890/06-1946.1
Van Buskirk, J., Krügel, A., Kunz, J., Miss, F., & Stamm, A. (2014). The rate of degradation of
chemical cues indicating predation risk: An experiment and review. Ethology, 120(9),
942-949. DOI: 10.1111/eth.12266
Volterra, V. (1926). Fluctuations in the Abundance of a Species considered Mathematically.
Nature, 118, 558–560. DOI: 10.1038/118558a0 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 130
Wahle, R. A. (1992). Body-size dependent anti-predator mechanisms of the American lobster.
Oikos, 65(1), 52-60. DOI: 10.2307/3544887
Wallace, K. J., & Rosen, J. B. (2000). Predator odor as an unconditioned fear stimulus in rats:
Elicitation of freezing by trimethylthiazoline, a component of fox feces. Behavioral
Neuroscience, 114(5), 912. DOI: 10.1037/0735-7044.114.5.912
Wallace, J. B., & Webster, J. R. (1996). The role of macroinvertebrates in stream ecosystem
function. Annual Review of Entomology, 41(1), 115-139. DOI:
10.1146/annurev.en.41.010196.000555
Wankowski, J. W. J. (1979). Morphological limitations, prey size selectivity, and growth
response of juvenile Atlantic salmon, Salmo salar. Journal of Fish Biology, 14(1), 89-
100. DOI: 10.1111/j.1095-8649.1979.tb03498.x
Warfe, D. M., & Barmuta, L. A. (2006). Habitat structural complexity mediates food web
dynamics in a freshwater macrophyte community. Oecologia, 150(1), 141-154. DOI:
10.1007/s00442-006-0505-1
Waters, N. M., & San Giovanni, C. R. (2002). Distribution and diversity of benthic
macroinvertebrates associated with aquatic macrophytes. Journal of Freshwater Ecology,
17(2), 223-232. DOI: 10.1080/02705060.2002.9663890
Webb, J. K., & Shine, R. (1993). Prey-size selection, gape limitation and predator vulnerability
in Australian blindsnakes (Typhlopidae). Animal Behavior, 45(6), 1117-1126. DOI:
10.1006/anbe.1993.1136
Weiss, L. C. (2019). Sensory ecology of predator-induced phenotypic plasticity. Frontiers in
Behavioral Neuroscience, 12, 330. DOI: 10.3389/fnbeh.2018.00330 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 131
Weissburg, M., Smee, D. L., & Ferner, M. C. (2014). The sensory ecology of nonconsumptive
predator effects. The American Naturalist, 184(2), 141-157. DOI: 10.1086/676644
Weissburg, M., Poulin, R. X., & Kubanek, J. (2016). You are what you eat: A metabolomics
approach to understanding prey responses to diet-dependent chemical cues released by
predators. Journal of Chemical Ecology, 42(10), 1037-1046. DOI: 10.1007/s10886-016-
0771-2
Weissburg, M. J., & Zimmer-Faust, R. K. (1994). Odor plumes and how blue crabs use them in
finding prey. Journal of Experimental Biology, 197(1), 349-375.
Werner, E. E., & Peacor, S. D. (2003). A review of trait‐mediated indirect interactions in
ecological communities. Ecology, 84(5), 1083-1100. DOI: 10.1890/0012-
9658(2003)084[1083:AROTII]2.0.CO;2
Werth, A. J., & Potvin, J. (2016). Baleen hydrodynamics and morphology of cross-flow filtration
in balaenid whale suspension feeding. PLoS One, 11(2), e0150106. DOI:
10.1371/journal.pone.0150106
Whitenack, L. B., Simkins Jr, D. C., & Motta, P. J. (2011). Biology meets engineering: The
structural mechanics of fossil and extant shark teeth. Journal of Morphology, 272(2),
169-179. DOI: 10.1002/jmor.10903
Wirsing, A. J., Cameron, K. E., & Heithaus, M. R. (2010). Spatial responses to predators vary
with prey escape mode. Animal Behaviour, 79(3), 531-537. DOI:
10.1016/j.anbehav.2009.12.014
Wisenden, B. D. (2000). Olfactory assessment of predation risk in the aquatic environment.
Philosophical Transactions of the Royal Society of London. Series B: Biological
Sciences, 355(1401), 1205-1208. DOI: 10.1098/rstb.2000.0668 ECOLOGICAL EFFECTS OF PREDATOR INFORMATION 132
Wolcox, D. A., & Meeker, J. E. (1992). Implications for faunal habitat related to altered
macrophyte structure in regulated lakes in northern Minnesota. Wetlands, 12(3), 192-203.
DOI: 10.1007/BF03160609
Wood, T. C., Kelley, R. E., & Moore, P. A. (2018). Feeding in fear: Indirect effects of predatory
fish on macrophyte communities mediated by altered crayfish foraging behaviour.
Freshwater Biology, 63(12), 1523-1533. DOI: 10.1111/fwb.13181
Wood, T. C., & Moore, P. A. (2020). Big and bad: How relative predator size and dietary
information influence rusty crayfish (Faxonius rusticus) behavior and resource-use
decisions. Canadian Journal of Zoology, 98(1), 62-72. DOI: 10.1139/cjz-2019-0089
Wyatt, T. D. (2010). Pheromones and signature mixtures: Defining species-wide signals and
variable cues for identity in both invertebrates and vertebrates. Journal of Comparative
Physiology A, 196(10), 685-700. DOI: 10.1007/s00359-010-0564-y
Zulandt-Schneider, R. A., Huber, R., & Moore, P. A. (2001). Individual and status recognition in
the crayfish, Faxonius rusticus: The effects of urine release on fight dynamics.
Behaviour, 138(2), 137-153. DOI: 10.1163/15685390151074348