Integrative and Comparative Biology Integrative and Comparative Biology, volume 54, number 3, pp. 377–386 doi:10.1093/icb/icu088
Society for Integrative and Comparative Biology
SYMPOSIUM
Using Remote Biomonitoring to Understand Heterogeneity in Immune-Responses and Disease-Dynamics in Small, Free-Living Animals James S. Adelman,1 Sahnzi C. Moyers and Dana M. Hawley
From the symposium ‘‘Methods and Mechanisms in Ecoimmunology’’ presented at the annual meeting of the Society for Integrative and Comparative Biology, January 3–7, 2014 at Austin, Texas. 1
E-mail: [email protected]
Synopsis Despite the ubiquity of parasites and pathogens, behavioral and physiological responses to infection vary widely across individuals. Although such variation can have pronounced effects on population-level processes, including the transmission of infectious disease, the study of individual responses to infection in free-living animals remains a challenge. To fully understand the causes and consequences of heterogeneous responses to infection, research in ecoimmunology and disease-ecology must incorporate minimally invasive techniques to track individual animals in natural settings. Here, we review how several technologies, collectively termed remote biomonitoring, enable the collection of data on behavioral and physiological responses to infection in small, free-living animals. Specifically, we focus on the use of radiotelemetry and radio-frequency identification to study fever, sickness-behaviors (including lethargy and anorexia), and rates of inter-individual contact in the wild, all of which vary widely across individuals and impact the spread of pathogens within populations. In addition, we highlight future avenues for field studies of these topics using emerging technologies such as global positioning system tracking and tri-axial accelerometry. Through the use of such remote biomonitoring techniques, researchers can gain valuable insights into why responses to infection vary so widely and how this variation impacts the spread and evolution of infectious diseases.
Introduction The causes and consequences of heterogeneity in immunity lie at the core of the nascent fields of ecoimmunology and disease-ecology. Research into such variation has informed the study of life-history trade-offs, sexual selection, and can improve predictions of the dynamics of disease in natural systems (Zuk 1996; Martin et al. 2008; Hawley and Altizer 2011; Demas et al. 2012; Adelman forthcoming 2015). Methodological constraints, however, can limit progress in these endeavors, particularly when working with small, free-living animals that are challenging to capture multiple times, and for which current techniques of biomonitoring are strongly limited by restrictions on device weight. Numerous studies have dealt with such challenges by measuring immune defenses that require only one capture,
including constitutive defenses (those always present at appreciable levels), such as natural antibodies, complement, or antimicrobial peptides (Lee and Klasing 2004; Matson et al. 2005; Tieleman et al. 2005; Millet et al. 2007; Lee et al. 2008). Such techniques, however, cannot probe differences in induced immune defenses, those that become active only in response to infection. Measurement of such defenses is particularly important to the intersection of ecoimmunology and disease-ecology because induced defenses have high potential to shape the two components critical to the probability of transmission: the pathogen burden of a host and a host’s behavioral responses to infection (Hart 1988; Kluger et al. 1998; Dantzer 2004; Klasing 2004; Adelman and Martin 2009; Hawley and Altizer 2011; Iseri and Klasing 2013; Adelman forthcoming 2015).
Advanced Access publication June 20, 2014 ß The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: [email protected].
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Department of Biological Sciences, Virginia Tech, Derring Hall, Room 4020A (MC 0406), 1405 Perry Street, Blacksburg, VA 24061, USA
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between sickness-behaviors and inter-individual contacts is critical to revealing how directly-transmitted pathogens spread in the wild. To effectively understand the links among fever, sickness-behaviors, and inter-individual contact rates, we must incorporate minimally invasive techniques and technologies to study these responses in natural settings. Although there are a variety of options for monitoring such responses, this article highlights technologies that are small enough to be applied safely to small-bodied animals and require capturing individuals only once, as these should minimize the impacts on natural behaviors. Our initial discussion thus excludes technologies such as internal or external data loggers that are either too large to be applied to small-bodied, free-living animals or must be removed to analyze data (requiring multiple captures) (Kamerman et al. 2001; Prange et al. 2006; Hetem et al. 2008; Brown et al. 2012; Nathan et al. 2012; Hirsch et al. 2013). Rather, we focus principally on radiotelemetry and radio-frequency identification (RFID), briefly reviewing how these technologies function and discussing how they have been used to uncover patterns and consequences of variation in fever, sickness-behaviors, and rates of inter-individual contact in the wild. Finally, we highlight emerging biomonitoring technologies, including loggers that utilize global positioning system (GPS) technology and tri-axial accelerometers (Brown et al. 2012, 2013; Nathan et al. 2012; Bouten et al. 2013) that will further augment the remote collection of data on physiological and behavioral responses to infection in small-bodied, free-living animals.
Remote biomonitoring using radiotelemetry The basics of radiotelemetry Radiotelemetry involves the use of small transmitters placed on an animal to measure its position and/or aspects of its physiology (Fig. 1A). Wildlife radiotransmitters typically emit pulsed signals within the very high-frequency range (VHF: 30–300 MHz) that researchers can record via VHF receivers (Fig. 1B) (Millspaugh et al. 2012). This type of technology was first applied to biomonitoring during the early 1950s, when the US military used radio waves to transmit vital signs of fighter pilots (temperature, heart rate, and respiration) to physicians on the ground in real-time (Barr 1954). After this innovation, civilian physicians and wildlife biologists quickly followed suit, designing ingestible and implantable radiotransmitters that helped uncover patterns in animals’ home ranges, respiration, and
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Furthermore, covariation between induced behavioral and physiological defenses may have significant implications for how directly-transmitted pathogens spread (Hawley et al. 2011). In this review, we focus on techniques, collectively termed remote biomonitoring (Cooke et al. 2004), that facilitate multiple measurements of behavioral and physiological responses to infection in small-bodied, free-living animals. Such techniques are of particular value when assessing heterogeneities in responses such as fever, sickness-behaviors, and rates of contact among infected and uninfected individuals. As such, these techniques are ideal for exploring the growing intersection between ecoimmunology and disease-ecology. Fever and sickness-behaviors, including lethargy and anorexia, are immune-mediated responses that arise during diverse types of infections and among diverse taxa of animals (Hart 1988; Kluger 1991). Numerous authors have proposed that these responses are adaptive, aiding in the clearance of pathogens (Hart 1988; Exton 1997; Kluger et al. 1998; Owen-Ashley and Wingfield 2007; Adelman and Martin 2009). For instance, by increasing an animal’s thermoregulatory setpoint, fever creates a suboptimal thermal environment for pathogens while enhancing the efficacy of other immune-responses (Kluger 1991; Kluger et al. 1998). The sickness-behaviors of anorexia and lethargy could limit a pathogen’s access to micronutrients and conserve energy for use in other costly immune-responses, respectively (Hart 1988; Exton 1997). Although fever certainly enhances the clearance of pathogens and the survival of hosts in some cases (Bernheim and Kluger 1976; Kluger et al. 1998; Richards-Zawacki 2010), its role in other systems is more complicated. For instance, extreme or prolonged fever can damage a host’s own tissues (immunopathology), potentially offsetting its benefits (Kluger et al. 1998; Graham et al. 2005). In addition, in ectotherms, fever requires behavioral adjustments to seek out warmer environments, which can place animals in more conspicuous locations and at higher risk of predation (Otti et al. 2012). Moreover, the role of sickness-behaviors in fighting infection, while well established from a theoretical perspective, has been rarely tested experimentally, and never in the wild. Because fever and sicknessbehaviors could alter pathogen loads within wild animals, clarifying their roles in infection among free-living animals is critical to understanding the disease-dynamics of wildlife. Moreover, infectioninduced lethargy likely reduces direct contact between infectious and naı¨ve hosts (Adelman and Martin 2009; Hawley and Altizer 2011; Adelman forthcoming 2015). As such, elucidating the links
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thermoregulation, and the coordination of avian flight (Mackay and Jacobson 1957; Le Munyan et al. 1959; Lord et al. 1962; Southern 1964; Craighead and Craighead 1965). Although the lightest of these early devices weighed nearly 40 g, newer transmitters can weigh less than 0.5 g (e.g., Fig. 1A), facilitating use on small-bodied animals (Lord et al. 1962; Wikelski et al. 2006; Adelman et al. 2010). Moreover, telemetry can enable collection of data over considerable distances as long as a clear line of sight can be established between transmitter and receiver, which is often achieved by positioning receivers on higher ground (Millspaugh et al. 2012). Although radiotransmitters can relay a variety of physiological data by varying the amplitude or frequency of a radio wave, here we focus on two ways in which this technology can encode data on an animal’s movement and temperature. Researchers can deduce an animal’s activity patterns by utilizing transmitters that emit pulses of constant amplitude (Fig. 1B) and calculating the extent to which this signal’s amplitude varies over time at the receiver. Specifically, if an animal remains inactive, the amplitude of the signal at the receiver remains relatively constant; if an animal becomes active, the amplitude of the signal at the receiver will fluctuate, as the radio waves are no longer emitted in a constant direction and, as such, reflect off of surfaces in the environment in different ways, attenuating or amplifying the original signal’s amplitude (Fig. 1C) (Cochran and Lord 1963; Bisson et al. 2009; Lambert et al. 2009; Bridge et al. 2011). As
some baseline level of fluctuation in amplitude will appear even when animals are immobile, researchers must perform validation studies for their species of interest to calculate rules that differentiate between activity and inactivity. A slightly more complex class of transmitter encodes information about an animal’s temperature in addition to its movement. Such transmitters still emit pulses of constant amplitude, but vary the interval between pulses with temperature. Typically these transmitters produce shorter inter-pulse-intervals at higher temperatures (Fig. 1D). Because the precise relationship between pulse-interval and temperature will vary across individual transmitters, manufacturers or researchers must calibrate each transmitter separately. Furthermore, when affixing temperature-sensing transmitters externally, researchers should calibrate skin temperature with core-body temperature and/or quantify fever using change in skin temperature rather than via absolute skin temperature (Adelman et al. 2010). Radiotelemetry, fever, and sickness-behaviors in the wild Despite a long history of radiotelemetry in ecological and biomedical studies (Taffe 2011; Millspaugh et al. 2012), few researchers have utilized this technique to measure responses to infection in free-living wild animals. Although several studies have utilized implantable data loggers to opportunistically monitor fever and sickness-behavior in the wild, such techniques required recapture of the animals to surgically
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Fig. 1 Radiotelemetry can generate data on activity (sickness-behaviors) and body temperature (fever). When transmitters (A, e.g., on a song sparrow) emit pulses of constant amplitude (B), receivers will detect different levels of variation in the amplitude of these pulses, depending upon whether the animal and transmitter are moving (Active) or remain in a constant position (Inactive) (C). Additionally, transmitters can encode variation in temperature by varying the time between pulses, or inter-pulse-interval, in a predictable manner (D). Photograph (A) by Kamiel Spoelstra.
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on an ecoimmunologist’s budget. At the time of writing, temperature-sensing transmitters can cost between $200 and $300 US each, and automated receiving units typically cost several thousand US dollars. Such costs may become prohibitive, particularly if transmitters are difficult to recover (either once they fall off a tagged organism, or through repeated captures). However, researchers have been constructing radiotransmitters themselves for decades, and such practices can help minimize costs (Cochran and Lord 1963). In addition, although technological advances have produced increasingly lightweight transmitters (some 50.3 g), this may still be too heavy to infer normal behavioral patterns in very small animals, including some insects (but see Wikelski et al. 2007). Furthermore, even if transmitter weights fall within accepted best practices of 3–5% of the study organism’s mass (MacDougald and Burant 2007), a meta-analysis by Barron et al. (2010) suggests that affixing transmitters can negatively impact reproduction and survival (though estimates of survival in this meta-analysis may have been confounded by emigration or dispersal). Battery life is also an important logistical consideration when using radiotelemetry on small-bodied species. Currently, batteries in transmitters that weigh less than 1 g can last on the order of days to weeks, which works well in short-term studies with immune challenges (e.g., LPS), but may not be ideal for long-term studies or those including true pathogens. Finally, the data generated during a telemetry study can prove cumbersome to analyze. With automated receivers, researchers can record many datapoints per minute over periods ranging from days to weeks. Such voluminous datasets require some knowledge of computer programming for appropriate extraction of data (e.g., filtering out data-points that fall below a detection threshold) and can introduce patterns that are problematic for basic statistical techniques (e.g., temporal autocorrelation and missing data-points). Although mixed effects models offer solutions to these statistical challenges and most statistical programs now incorporate these techniques, including freely available programs such as R (Pinheiro and Bates 2000; Zuur et al. 2009; R Development Core Team 2014), these issues, coupled with concerns about transmitters’ weights and costs, may have deterred potential telemetry users in recent years. Still, when researchers require fine-scaled data on induced immune-responses in the wild, radiotelemetry remains a valuable technique for wildlife systems. As costs will inevitably decrease and the miniaturization of transmitters will inevitably continue, this
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remove the loggers and download the relevant data, limiting their application across groups of animals and in different field settings (Kamerman et al. 2001; Hetem et al. 2008). Although newer technologies, including GPS tags and tri-axial accelerometers, have improved upon such loggers by allowing for remote upload of activity data, these technologies are still too large for application to many smallbodied animals (Brown et al. 2012, 2013; Nathan et al. 2012). Thus, radiotransmitters are currently one of the only accessible technologies for remotely monitoring sickness-behavior and fever in small, free-living animals. For instance, Adelman et al. (2010) used radiotelemetry to assess fever and sickness-behaviors among free-living song sparrows (Melospiza melodia) following injection with lipopolysaccharide (LPS), a bacterial cell-wall component that cannot replicate within the host. This study revealed several details about fever and sickness-behaviors not observable through repeated captures or behavioral observations alone. First, prior field experiments that used territorial aggression alone as a proxy for lethargy showed no effect, or inconsistent effects, of LPS treatment on sickness-behaviors during the breeding season (Owen-Ashley and Wingfield 2006; Adelman et al. 2010). Telemetry showed, however, that sparrows did express sickness-behaviors during the breeding season (Adelman et al. 2010), reducing the amount of time they spend active to 30–50% of control levels. Moreover, both fever and lethargy were more pronounced in the more southern of two populations, consistent with predictions based on life-history trade-offs and apparent selective-pressures from pathogens (Adelman et al. 2010). These results highlight several advantages of using radiotelemetry to measure induced immune-responses, and their behavioral consequences, in the wild. First, unlike implantable data loggers, the transmitters used in the study by Adelman et al. (2010) were affixed to the skin of the animal, yielding metrics that correlated well with implantable alternatives while not requiring surgery. In addition, by utilizing automated receiving units, the authors extracted data in real-time, eliminating the need for repeated captures and surgeries. Finally, continuously monitoring behavioral responses to infection revealed differences in lethargy that were not observed using single timepoint territorial assays, illustrating that telemetry can uncover patterns other methodologies likely miss. Despite these advantages, few studies have utilized radiotelemetry to measure fever or sickness-behavior in the wild. Several drawbacks to radiotelemetry may help explain this pattern. First, telemetry is expensive
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technique is poised to expand in utilization to a range of new species and contexts.
Remote biomonitoring using RFID Basics of RFID
RFID, fever, sickness-behaviors, and rates of contact in the wild Few studies in ecoimmunology have yet made use of RFID techniques to measure fever. However, specialized PIT-tags fitted with thermistors can measure and transmit temperature data based on fluctuations in electrical resistance. For example, cattle farmers have incorporated such technologies to monitor the health of herds (Small et al. 2008; Reid and Fried 2012). Recently, Nord et al. (2013) utilized RFID to monitor febrile responses of aviary-housed great tits (Parus major) in response to simulated bacterial infection. In this study, researchers placed antennas in nest boxes, where birds roosted at night, enabling fine-scaled measurements of body temperature (Nord et al. 2013). Similar techniques could easily be applied to nest boxes or other such refugia in the field, enabling similar studies in a variety of free-living animals.
Fig. 2 RFID involves the use of PIT-tags (arrow in A, e.g., on a house finch). Upon entering the magnetic field emitted by a RFID reader (B), PIT-tags transmit unique identifying codes, which can then be logged at specified intervals of time. Photograph (A) by Greg Fisk.
Although no field studies have yet explicitly examined sickness-behaviors using RFID, this technology can track patterns of movement and foraging, albeit in a spatially limited manner. For example, RFIDequipped devices placed in high-traffic areas can record general levels of activity based on the number of times an individual passes a particular reader. Schielke et al. (2012) used this approach to track activity among Ansell’s mole-rats, placing readers throughout colony tunnel systems. In addition, RFID presents a convenient way to measure targeted behaviors such as rates and patterns of foraging. For example, Bonter et al. (2013) affixed PIT-tags to four species of North American songbirds and, using RFID-equipped bird feeders, logged the frequency of individuals’ visits to the feeders as a proxy for foraging rates. Such techniques, when applied in the context of experimental immune challenges could easily record variation in anorexia and lethargy.
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RFID uses electromagnetic fields to transfer data from a transponder either affixed to, or implanted in, an animal to a battery-powered reader (Bonter and Bridge 2011). The basic components of an RFID reader include an antenna, microprocessor, a memory card, and a battery (Bridge and Bonter 2011). In the context of animal studies, RFID systems typically operate in the low-frequency range (125–150 kHz), that is, at much lower frequencies than radiotelemetry discussed above (Bonter and Bridge 2011). Readers communicate with passive integrated transponder (PIT) tags, which each have a unique ID and do not require a power source. These PIT-tags, which can be the size of a grain of rice and as light as 0.1 g (Fig. 2A), have been used on species as small as hummingbirds, ants, and bees (Bonter and Bridge 2011; Brewer et al. 2011; Decourtye et al. 2011; Moreau et al. 2011). When a PIT-tag enters the magnetic field surrounding a reader’s antenna (typically a range of centimeters to meters), it utilizes the energy of the field to transmit a unique identification code, which is then logged at the reader (Fig. 2B). Due to its convenient size and capacity to track the location of tagged objects or individuals, RFID technology has been utilized in many contexts such as manufacturing, healthcare, and animal behavior (Gibbons and Andrews 2004; Glover and Himanshu 2006).
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infection and immunity. Similar to radiotelemetry, RFID techniques require only single captures to generate long-term data on foraging habits, inter-individual interactions in the wild, as well as physiological metrics such as body temperature. Additionally, the small size and minimal weight of PIT-tags, which do not require an internal battery, makes their use feasible in a wider range of species than almost all other remote biomonitoring techniques. Moreover, the use of PIT-tags likely has fewer adverse effects on fitness than do larger devices, such as transmitters, in small animals. For example, great tits implanted with PIT-tags showed no differences in breeding success and survival when compared with control animals (Nicolaus et al. 2008). Finally, researchers can implement RFID technology at much lower costs than radiotelemetry. Standard PIT-tags cost roughly $3 US and researchers can build their own readers for less than $50 US (Bridge and Bonter 2011). Despite these advantages, the use of RFID involves several important limitations. Most importantly, the passive nature of PIT-tags comes with spatial constraints to communication between RFID readers and transponders. In order for a reader to log the presence of a transponder, the transponder must be within close proximity to the reader’s antenna. Thus, behavior of tagged animals can only be logged at specific RFID reader-equipped checkpoints such as roosting or foraging sites, and cannot be monitored continuously. Increasing the effective range can be expensive, with commercially available units costing thousands of dollars (Bridge and Bonter 2011). Additionally, most RFID readers can only read one transponder at a time, meaning that the presence of two tagged animals at the same time cannot be logged. As such, researchers must often choose locations of the readers carefully, considering high-traffic areas and targeted behaviors such as foraging, as well as locations that preclude the simultaneous presence of multiple tagged individuals at a single antenna. Given these limitations, the use of RFID tracking in ecoimmunology or disease-ecology is best suited to species with small, predictable home ranges rather than widely-ranging animals or those with highly erratic movement patterns.
Future directions: biomonitoring at the intersection of ecoimmunology and disease-ecology Remote biomonitoring has the potential to contribute significantly to the growing intersection of ecoimmunology and disease-ecology by linking
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The use of RFID can also offer valuable insights into spatial distributions of animals and heterogeneity in inter-individual contacts, both of which can influence the spread of parasites and pathogens. The spatial distribution of individuals can be measured by tracking the presence or absence of certain individuals across RFID readers placed at different locations. Rates of contact between individuals can then be inferred based on the presence of multiple individuals within a very close spatial or temporal proximity. For instance, Moreau et al. (2011) measured ants’ spatial structure by introducing tagged ants into an artificial nest equipped with RFID readers at many different spatial domains (Moreau et al. 2011). Given the small spatial scale (i.e., within an ant nest) of their RFID set-up, Moreau et al. (2011) defined inter-individual contact as any time two ants came within 14 mm of one another. At larger spatial scales, the distances among readers and the inability of one reader to simultaneously log multiple individuals at once can complicate such endeavors. In this case, researchers can monitor inter-individual contacts as the presence of more than one individual at one location within a brief period of time, typically on the order of seconds. For instance, using bird feeders equipped with RFID readers, Aplin et al. (2013) quantified rates of contact among PIT-tagged great tits based on temporal proximity, and were able to incorporate this information into analyses of these animals’ social network. Similarly, Clay et al. (2009) used RFID to track contacts among PIT-tagged deer mice and test a fundamental theory in disease-ecology, termed the 20/80 rule. This theory suggests that in numerous infectious diseases, 20% of individuals are responsible for 80% of the transmission of the pathogen (Woolhouse et al. 1997). By defining contacts as any instance when two unique PIT-tags were logged at the same RFID reader within 15 s, Clay et al. (2009) found that contact rates closely matched the 20/80 rule: 17.5% of tagged individuals generated 75.4% of recorded contacts. This research also raises an important caveat to using RFID to estimate inter-individual contacts: choosing the time-interval between successive logs of PIT-tags to define as a contact requires calibration for each species studied (which Clay et al. [2009] achieved using video trials), and the relevant interval will likely depend on the type of contact of interest for the transmission of a particular disease (e.g., aggressive interactions; use of the same feeding station in close succession). The studies highlighted in this section illustrate a number of advantages of RFID in monitoring behavioral and physiological responses relevant to
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could also record individual foraging behaviors and the rates of contact among marked individuals. Although standard limitations of RFID would apply to such systems (see above), this technology nevertheless offers immediate functionality for remotely monitoring links among infection, behavior, interindividual contact, and pathogen-transmission. Second, recent advances in automated radiotelemetry have the potential to remotely monitor disease-status, additional physiological responses to infection, and rates of contact, all with improved spatial coverage within a landscape. Large-scale telemetric grids, spanning hundreds of hectares, can monitor activity, location, and physiological status (e.g., heart rate, energy expenditure, blood pressure, and body temperature) (Bowlin and Wikelski 2008; Bisson et al. 2009, 2011; Kays et al. 2011; US Army Corps of Engineers 2013). By incorporating data from multiple receivers, such systems triangulate signals from individual radiotransmitters, potentially yielding information on location, activity, and fever (disease-status) for multiple marked animals simultaneously. Using these data, researchers can extract information not only on individual responses to infection, but also on rates of contact among marked animals. Although such systems require significant initial capital and ongoing collaborations among engineers, computer scientists, and biologists, the ability to continuously monitor contacts across entire landscapes will vastly improve our ability to estimate behaviors relevant to the spread of disease in the wild. Third, satellite-based tracking has considerable potential for tracking contacts and disease-status. Several existing types of satellite tags have been applied to disease-relevant systems and can monitor an animal’s location using GPS, offloading data periodically to remote servers (e.g., Cui et al. 2011; Smith et al. 2011; Ratanakorn et al. 2012). Such tags could prove ideal for monitoring contacts and diseasestatus at broad spatial scales for a wide variety of species, particularly those that undertake expansive migratory movements. Unfortunately, the current size and expense of such tags limit both the types of species and the number of individuals that researchers can monitor. However, several research groups are developing new satellite technologies capable of detecting much smaller tags (Wikelski et al. 2007; icarusinitiative.org). Finally, devices that incorporate both GPS technology and tri-axial accelerometers will likely prove invaluable in linking disease-ecology and ecoimmunology across an array of spatial scales. Such tags can store detailed information on an animal’s location,
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within-host processes (e.g., replication of pathogens; immune-responses) and between-host processes (e.g., rates of contact) in free-living animals (Alizon and van Baalen 2008; Hawley and Altizer 2011). Because infectious diseases represent an increasing threat to biodiversity (Daszak et al. 2000; Fisher et al. 2012), remote biomonitoring can also tie ecoimmunology and disease-ecology to the emerging discipline of conservation physiology (Wikelski and Cooke 2006). As one key example, the way in which individuals behave during infection by pathogens is arguably one of the most critical determinants of whether and how directly-transmitted pathogens will spread (Hawley et al. 2011). Although numerous studies have examined such patterns from the perspective of parasite-induced changes in hosts’ behaviors, immune-mediated behavioral changes and the ecological factors that mediate them have received little, to no, attention in disease-ecology (Moore 2002; Thomas et al. 2005; Hawley and Altizer 2011). Instead, most work to date on behavior and disease-transmission has focused on behavioral predictors of infection (e.g., group size, foraging behavior, and social status) (Coˆte´ and Poulin 1995; Altizer et al. 2003; Ezenwa 2004). If we consider transmission as a mathematical function in a classic susceptible–infected–recovered model (Anderson and May 1979), rates of contact are modeled as a function of the density or frequency of susceptible and infected individuals, with the implicit assumption that the behavior of both classes is similar. Understanding the behavior of infectious individuals, and how that behavior might vary with within-host processes such as pathogen-load or activation of the immune system, is a key missing link in revealing how pathogens spread in free-living populations. Interest in linking within- and between-host processes, however, is growing (Alizon and van Baalen 2008; Mideo et al. 2008; Day et al. 2011; Hawley and Altizer 2011; Hawley et al. 2011; Adelman forthcoming 2015), and several advances in remote biomonitoring are likely to clarify the links among the behavior of infected individuals, rates of contact with healthy individuals, and spread of disease in the wild. First, temperature-sensing PIT-tags and RFID provide an immediate avenue for simultaneously monitoring individual behavior, infection, and rates of contact. Such PIT-tags are not significantly larger than standard PIT-tags and can be implanted subcutaneously or in the body cavity of animals as small as 10 g songbirds (Nord et al. 2013). For infections that induce fever, body temperature could then be monitored at RFID-enabled feeding or roosting stations and used as a proxy for infection. Such RFID units
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Acknowledgments The authors thank the organizers, participants, and attendees of the symposium ‘‘Methods and Mechanisms in Ecoimmunology,’’ held at the 2014 annual meeting of the Society for Integrative and Comparative Biology for their suggestions and engaging discussions. They also thank Karen Mabry for insightful discussions about automated telemetry and two anonymous reviewers for their valuable suggestions on a prior version of this article.
Funding This work was supported by the National Science Foundation [grant number IOS-1054675 to D.M.H.]. This paper was part of the symposium ‘‘Methods and Mechanisms in Ecoimmunology,’’ supported by the Divisions of Animal Behavior, Comparative Endocrinology, and Comparative Physiology and Biochemisty within the Society for Integrative and Comparative Biology, and the Research Coordination Network for Ecoimmunology funded by the National Science Foundation [grant number IOS-0947177 to Lynn B. Martin, D.M.H., and Daniel R. Ardia].
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enabling researchers to map inter-individual contacts across large ranges, along with fine-scaled data on an individual’s acceleration in three dimensional space (Nathan et al. 2012; Brown et al. 2013). Several types of algorithms can match unique patterns of acceleration to distinct behaviors, yielding much more detailed information on activity than can radiotelemetry (Brown et al. 2012, 2013; Nathan et al. 2012). In addition, these tags can utilize either cellular communication networks or radiotransmissions to offload data remotely, eliminating the need for multiple captures (Brown et al. 2012, 2013; Nathan et al. 2012; Bouten et al. 2013). Although the size and weight of such tags have decreased rapidly in recent years, including some weighing nearly 10 g (Bouten et al. 2013), their utility for animals under 200 g remains limited. However, as these, and other, technologies improve, remote biomonitoring will continue to make great strides in linking individual responses to infection with population-level disease processes, not only at local or regional scales, but at a global level.
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Society for Integrative and Comparative Biology
SYMPOSIUM
Using Remote Biomonitoring to Understand Heterogeneity in Immune-Responses and Disease-Dynamics in Small, Free-Living Animals James S. Adelman,1 Sahnzi C. Moyers and Dana M. Hawley
From the symposium ‘‘Methods and Mechanisms in Ecoimmunology’’ presented at the annual meeting of the Society for Integrative and Comparative Biology, January 3–7, 2014 at Austin, Texas. 1
E-mail: [email protected]
Synopsis Despite the ubiquity of parasites and pathogens, behavioral and physiological responses to infection vary widely across individuals. Although such variation can have pronounced effects on population-level processes, including the transmission of infectious disease, the study of individual responses to infection in free-living animals remains a challenge. To fully understand the causes and consequences of heterogeneous responses to infection, research in ecoimmunology and disease-ecology must incorporate minimally invasive techniques to track individual animals in natural settings. Here, we review how several technologies, collectively termed remote biomonitoring, enable the collection of data on behavioral and physiological responses to infection in small, free-living animals. Specifically, we focus on the use of radiotelemetry and radio-frequency identification to study fever, sickness-behaviors (including lethargy and anorexia), and rates of inter-individual contact in the wild, all of which vary widely across individuals and impact the spread of pathogens within populations. In addition, we highlight future avenues for field studies of these topics using emerging technologies such as global positioning system tracking and tri-axial accelerometry. Through the use of such remote biomonitoring techniques, researchers can gain valuable insights into why responses to infection vary so widely and how this variation impacts the spread and evolution of infectious diseases.
Introduction The causes and consequences of heterogeneity in immunity lie at the core of the nascent fields of ecoimmunology and disease-ecology. Research into such variation has informed the study of life-history trade-offs, sexual selection, and can improve predictions of the dynamics of disease in natural systems (Zuk 1996; Martin et al. 2008; Hawley and Altizer 2011; Demas et al. 2012; Adelman forthcoming 2015). Methodological constraints, however, can limit progress in these endeavors, particularly when working with small, free-living animals that are challenging to capture multiple times, and for which current techniques of biomonitoring are strongly limited by restrictions on device weight. Numerous studies have dealt with such challenges by measuring immune defenses that require only one capture,
including constitutive defenses (those always present at appreciable levels), such as natural antibodies, complement, or antimicrobial peptides (Lee and Klasing 2004; Matson et al. 2005; Tieleman et al. 2005; Millet et al. 2007; Lee et al. 2008). Such techniques, however, cannot probe differences in induced immune defenses, those that become active only in response to infection. Measurement of such defenses is particularly important to the intersection of ecoimmunology and disease-ecology because induced defenses have high potential to shape the two components critical to the probability of transmission: the pathogen burden of a host and a host’s behavioral responses to infection (Hart 1988; Kluger et al. 1998; Dantzer 2004; Klasing 2004; Adelman and Martin 2009; Hawley and Altizer 2011; Iseri and Klasing 2013; Adelman forthcoming 2015).
Advanced Access publication June 20, 2014 ß The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: [email protected].
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Department of Biological Sciences, Virginia Tech, Derring Hall, Room 4020A (MC 0406), 1405 Perry Street, Blacksburg, VA 24061, USA
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between sickness-behaviors and inter-individual contacts is critical to revealing how directly-transmitted pathogens spread in the wild. To effectively understand the links among fever, sickness-behaviors, and inter-individual contact rates, we must incorporate minimally invasive techniques and technologies to study these responses in natural settings. Although there are a variety of options for monitoring such responses, this article highlights technologies that are small enough to be applied safely to small-bodied animals and require capturing individuals only once, as these should minimize the impacts on natural behaviors. Our initial discussion thus excludes technologies such as internal or external data loggers that are either too large to be applied to small-bodied, free-living animals or must be removed to analyze data (requiring multiple captures) (Kamerman et al. 2001; Prange et al. 2006; Hetem et al. 2008; Brown et al. 2012; Nathan et al. 2012; Hirsch et al. 2013). Rather, we focus principally on radiotelemetry and radio-frequency identification (RFID), briefly reviewing how these technologies function and discussing how they have been used to uncover patterns and consequences of variation in fever, sickness-behaviors, and rates of inter-individual contact in the wild. Finally, we highlight emerging biomonitoring technologies, including loggers that utilize global positioning system (GPS) technology and tri-axial accelerometers (Brown et al. 2012, 2013; Nathan et al. 2012; Bouten et al. 2013) that will further augment the remote collection of data on physiological and behavioral responses to infection in small-bodied, free-living animals.
Remote biomonitoring using radiotelemetry The basics of radiotelemetry Radiotelemetry involves the use of small transmitters placed on an animal to measure its position and/or aspects of its physiology (Fig. 1A). Wildlife radiotransmitters typically emit pulsed signals within the very high-frequency range (VHF: 30–300 MHz) that researchers can record via VHF receivers (Fig. 1B) (Millspaugh et al. 2012). This type of technology was first applied to biomonitoring during the early 1950s, when the US military used radio waves to transmit vital signs of fighter pilots (temperature, heart rate, and respiration) to physicians on the ground in real-time (Barr 1954). After this innovation, civilian physicians and wildlife biologists quickly followed suit, designing ingestible and implantable radiotransmitters that helped uncover patterns in animals’ home ranges, respiration, and
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Furthermore, covariation between induced behavioral and physiological defenses may have significant implications for how directly-transmitted pathogens spread (Hawley et al. 2011). In this review, we focus on techniques, collectively termed remote biomonitoring (Cooke et al. 2004), that facilitate multiple measurements of behavioral and physiological responses to infection in small-bodied, free-living animals. Such techniques are of particular value when assessing heterogeneities in responses such as fever, sickness-behaviors, and rates of contact among infected and uninfected individuals. As such, these techniques are ideal for exploring the growing intersection between ecoimmunology and disease-ecology. Fever and sickness-behaviors, including lethargy and anorexia, are immune-mediated responses that arise during diverse types of infections and among diverse taxa of animals (Hart 1988; Kluger 1991). Numerous authors have proposed that these responses are adaptive, aiding in the clearance of pathogens (Hart 1988; Exton 1997; Kluger et al. 1998; Owen-Ashley and Wingfield 2007; Adelman and Martin 2009). For instance, by increasing an animal’s thermoregulatory setpoint, fever creates a suboptimal thermal environment for pathogens while enhancing the efficacy of other immune-responses (Kluger 1991; Kluger et al. 1998). The sickness-behaviors of anorexia and lethargy could limit a pathogen’s access to micronutrients and conserve energy for use in other costly immune-responses, respectively (Hart 1988; Exton 1997). Although fever certainly enhances the clearance of pathogens and the survival of hosts in some cases (Bernheim and Kluger 1976; Kluger et al. 1998; Richards-Zawacki 2010), its role in other systems is more complicated. For instance, extreme or prolonged fever can damage a host’s own tissues (immunopathology), potentially offsetting its benefits (Kluger et al. 1998; Graham et al. 2005). In addition, in ectotherms, fever requires behavioral adjustments to seek out warmer environments, which can place animals in more conspicuous locations and at higher risk of predation (Otti et al. 2012). Moreover, the role of sickness-behaviors in fighting infection, while well established from a theoretical perspective, has been rarely tested experimentally, and never in the wild. Because fever and sicknessbehaviors could alter pathogen loads within wild animals, clarifying their roles in infection among free-living animals is critical to understanding the disease-dynamics of wildlife. Moreover, infectioninduced lethargy likely reduces direct contact between infectious and naı¨ve hosts (Adelman and Martin 2009; Hawley and Altizer 2011; Adelman forthcoming 2015). As such, elucidating the links
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thermoregulation, and the coordination of avian flight (Mackay and Jacobson 1957; Le Munyan et al. 1959; Lord et al. 1962; Southern 1964; Craighead and Craighead 1965). Although the lightest of these early devices weighed nearly 40 g, newer transmitters can weigh less than 0.5 g (e.g., Fig. 1A), facilitating use on small-bodied animals (Lord et al. 1962; Wikelski et al. 2006; Adelman et al. 2010). Moreover, telemetry can enable collection of data over considerable distances as long as a clear line of sight can be established between transmitter and receiver, which is often achieved by positioning receivers on higher ground (Millspaugh et al. 2012). Although radiotransmitters can relay a variety of physiological data by varying the amplitude or frequency of a radio wave, here we focus on two ways in which this technology can encode data on an animal’s movement and temperature. Researchers can deduce an animal’s activity patterns by utilizing transmitters that emit pulses of constant amplitude (Fig. 1B) and calculating the extent to which this signal’s amplitude varies over time at the receiver. Specifically, if an animal remains inactive, the amplitude of the signal at the receiver remains relatively constant; if an animal becomes active, the amplitude of the signal at the receiver will fluctuate, as the radio waves are no longer emitted in a constant direction and, as such, reflect off of surfaces in the environment in different ways, attenuating or amplifying the original signal’s amplitude (Fig. 1C) (Cochran and Lord 1963; Bisson et al. 2009; Lambert et al. 2009; Bridge et al. 2011). As
some baseline level of fluctuation in amplitude will appear even when animals are immobile, researchers must perform validation studies for their species of interest to calculate rules that differentiate between activity and inactivity. A slightly more complex class of transmitter encodes information about an animal’s temperature in addition to its movement. Such transmitters still emit pulses of constant amplitude, but vary the interval between pulses with temperature. Typically these transmitters produce shorter inter-pulse-intervals at higher temperatures (Fig. 1D). Because the precise relationship between pulse-interval and temperature will vary across individual transmitters, manufacturers or researchers must calibrate each transmitter separately. Furthermore, when affixing temperature-sensing transmitters externally, researchers should calibrate skin temperature with core-body temperature and/or quantify fever using change in skin temperature rather than via absolute skin temperature (Adelman et al. 2010). Radiotelemetry, fever, and sickness-behaviors in the wild Despite a long history of radiotelemetry in ecological and biomedical studies (Taffe 2011; Millspaugh et al. 2012), few researchers have utilized this technique to measure responses to infection in free-living wild animals. Although several studies have utilized implantable data loggers to opportunistically monitor fever and sickness-behavior in the wild, such techniques required recapture of the animals to surgically
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Fig. 1 Radiotelemetry can generate data on activity (sickness-behaviors) and body temperature (fever). When transmitters (A, e.g., on a song sparrow) emit pulses of constant amplitude (B), receivers will detect different levels of variation in the amplitude of these pulses, depending upon whether the animal and transmitter are moving (Active) or remain in a constant position (Inactive) (C). Additionally, transmitters can encode variation in temperature by varying the time between pulses, or inter-pulse-interval, in a predictable manner (D). Photograph (A) by Kamiel Spoelstra.
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on an ecoimmunologist’s budget. At the time of writing, temperature-sensing transmitters can cost between $200 and $300 US each, and automated receiving units typically cost several thousand US dollars. Such costs may become prohibitive, particularly if transmitters are difficult to recover (either once they fall off a tagged organism, or through repeated captures). However, researchers have been constructing radiotransmitters themselves for decades, and such practices can help minimize costs (Cochran and Lord 1963). In addition, although technological advances have produced increasingly lightweight transmitters (some 50.3 g), this may still be too heavy to infer normal behavioral patterns in very small animals, including some insects (but see Wikelski et al. 2007). Furthermore, even if transmitter weights fall within accepted best practices of 3–5% of the study organism’s mass (MacDougald and Burant 2007), a meta-analysis by Barron et al. (2010) suggests that affixing transmitters can negatively impact reproduction and survival (though estimates of survival in this meta-analysis may have been confounded by emigration or dispersal). Battery life is also an important logistical consideration when using radiotelemetry on small-bodied species. Currently, batteries in transmitters that weigh less than 1 g can last on the order of days to weeks, which works well in short-term studies with immune challenges (e.g., LPS), but may not be ideal for long-term studies or those including true pathogens. Finally, the data generated during a telemetry study can prove cumbersome to analyze. With automated receivers, researchers can record many datapoints per minute over periods ranging from days to weeks. Such voluminous datasets require some knowledge of computer programming for appropriate extraction of data (e.g., filtering out data-points that fall below a detection threshold) and can introduce patterns that are problematic for basic statistical techniques (e.g., temporal autocorrelation and missing data-points). Although mixed effects models offer solutions to these statistical challenges and most statistical programs now incorporate these techniques, including freely available programs such as R (Pinheiro and Bates 2000; Zuur et al. 2009; R Development Core Team 2014), these issues, coupled with concerns about transmitters’ weights and costs, may have deterred potential telemetry users in recent years. Still, when researchers require fine-scaled data on induced immune-responses in the wild, radiotelemetry remains a valuable technique for wildlife systems. As costs will inevitably decrease and the miniaturization of transmitters will inevitably continue, this
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remove the loggers and download the relevant data, limiting their application across groups of animals and in different field settings (Kamerman et al. 2001; Hetem et al. 2008). Although newer technologies, including GPS tags and tri-axial accelerometers, have improved upon such loggers by allowing for remote upload of activity data, these technologies are still too large for application to many smallbodied animals (Brown et al. 2012, 2013; Nathan et al. 2012). Thus, radiotransmitters are currently one of the only accessible technologies for remotely monitoring sickness-behavior and fever in small, free-living animals. For instance, Adelman et al. (2010) used radiotelemetry to assess fever and sickness-behaviors among free-living song sparrows (Melospiza melodia) following injection with lipopolysaccharide (LPS), a bacterial cell-wall component that cannot replicate within the host. This study revealed several details about fever and sickness-behaviors not observable through repeated captures or behavioral observations alone. First, prior field experiments that used territorial aggression alone as a proxy for lethargy showed no effect, or inconsistent effects, of LPS treatment on sickness-behaviors during the breeding season (Owen-Ashley and Wingfield 2006; Adelman et al. 2010). Telemetry showed, however, that sparrows did express sickness-behaviors during the breeding season (Adelman et al. 2010), reducing the amount of time they spend active to 30–50% of control levels. Moreover, both fever and lethargy were more pronounced in the more southern of two populations, consistent with predictions based on life-history trade-offs and apparent selective-pressures from pathogens (Adelman et al. 2010). These results highlight several advantages of using radiotelemetry to measure induced immune-responses, and their behavioral consequences, in the wild. First, unlike implantable data loggers, the transmitters used in the study by Adelman et al. (2010) were affixed to the skin of the animal, yielding metrics that correlated well with implantable alternatives while not requiring surgery. In addition, by utilizing automated receiving units, the authors extracted data in real-time, eliminating the need for repeated captures and surgeries. Finally, continuously monitoring behavioral responses to infection revealed differences in lethargy that were not observed using single timepoint territorial assays, illustrating that telemetry can uncover patterns other methodologies likely miss. Despite these advantages, few studies have utilized radiotelemetry to measure fever or sickness-behavior in the wild. Several drawbacks to radiotelemetry may help explain this pattern. First, telemetry is expensive
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technique is poised to expand in utilization to a range of new species and contexts.
Remote biomonitoring using RFID Basics of RFID
RFID, fever, sickness-behaviors, and rates of contact in the wild Few studies in ecoimmunology have yet made use of RFID techniques to measure fever. However, specialized PIT-tags fitted with thermistors can measure and transmit temperature data based on fluctuations in electrical resistance. For example, cattle farmers have incorporated such technologies to monitor the health of herds (Small et al. 2008; Reid and Fried 2012). Recently, Nord et al. (2013) utilized RFID to monitor febrile responses of aviary-housed great tits (Parus major) in response to simulated bacterial infection. In this study, researchers placed antennas in nest boxes, where birds roosted at night, enabling fine-scaled measurements of body temperature (Nord et al. 2013). Similar techniques could easily be applied to nest boxes or other such refugia in the field, enabling similar studies in a variety of free-living animals.
Fig. 2 RFID involves the use of PIT-tags (arrow in A, e.g., on a house finch). Upon entering the magnetic field emitted by a RFID reader (B), PIT-tags transmit unique identifying codes, which can then be logged at specified intervals of time. Photograph (A) by Greg Fisk.
Although no field studies have yet explicitly examined sickness-behaviors using RFID, this technology can track patterns of movement and foraging, albeit in a spatially limited manner. For example, RFIDequipped devices placed in high-traffic areas can record general levels of activity based on the number of times an individual passes a particular reader. Schielke et al. (2012) used this approach to track activity among Ansell’s mole-rats, placing readers throughout colony tunnel systems. In addition, RFID presents a convenient way to measure targeted behaviors such as rates and patterns of foraging. For example, Bonter et al. (2013) affixed PIT-tags to four species of North American songbirds and, using RFID-equipped bird feeders, logged the frequency of individuals’ visits to the feeders as a proxy for foraging rates. Such techniques, when applied in the context of experimental immune challenges could easily record variation in anorexia and lethargy.
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RFID uses electromagnetic fields to transfer data from a transponder either affixed to, or implanted in, an animal to a battery-powered reader (Bonter and Bridge 2011). The basic components of an RFID reader include an antenna, microprocessor, a memory card, and a battery (Bridge and Bonter 2011). In the context of animal studies, RFID systems typically operate in the low-frequency range (125–150 kHz), that is, at much lower frequencies than radiotelemetry discussed above (Bonter and Bridge 2011). Readers communicate with passive integrated transponder (PIT) tags, which each have a unique ID and do not require a power source. These PIT-tags, which can be the size of a grain of rice and as light as 0.1 g (Fig. 2A), have been used on species as small as hummingbirds, ants, and bees (Bonter and Bridge 2011; Brewer et al. 2011; Decourtye et al. 2011; Moreau et al. 2011). When a PIT-tag enters the magnetic field surrounding a reader’s antenna (typically a range of centimeters to meters), it utilizes the energy of the field to transmit a unique identification code, which is then logged at the reader (Fig. 2B). Due to its convenient size and capacity to track the location of tagged objects or individuals, RFID technology has been utilized in many contexts such as manufacturing, healthcare, and animal behavior (Gibbons and Andrews 2004; Glover and Himanshu 2006).
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infection and immunity. Similar to radiotelemetry, RFID techniques require only single captures to generate long-term data on foraging habits, inter-individual interactions in the wild, as well as physiological metrics such as body temperature. Additionally, the small size and minimal weight of PIT-tags, which do not require an internal battery, makes their use feasible in a wider range of species than almost all other remote biomonitoring techniques. Moreover, the use of PIT-tags likely has fewer adverse effects on fitness than do larger devices, such as transmitters, in small animals. For example, great tits implanted with PIT-tags showed no differences in breeding success and survival when compared with control animals (Nicolaus et al. 2008). Finally, researchers can implement RFID technology at much lower costs than radiotelemetry. Standard PIT-tags cost roughly $3 US and researchers can build their own readers for less than $50 US (Bridge and Bonter 2011). Despite these advantages, the use of RFID involves several important limitations. Most importantly, the passive nature of PIT-tags comes with spatial constraints to communication between RFID readers and transponders. In order for a reader to log the presence of a transponder, the transponder must be within close proximity to the reader’s antenna. Thus, behavior of tagged animals can only be logged at specific RFID reader-equipped checkpoints such as roosting or foraging sites, and cannot be monitored continuously. Increasing the effective range can be expensive, with commercially available units costing thousands of dollars (Bridge and Bonter 2011). Additionally, most RFID readers can only read one transponder at a time, meaning that the presence of two tagged animals at the same time cannot be logged. As such, researchers must often choose locations of the readers carefully, considering high-traffic areas and targeted behaviors such as foraging, as well as locations that preclude the simultaneous presence of multiple tagged individuals at a single antenna. Given these limitations, the use of RFID tracking in ecoimmunology or disease-ecology is best suited to species with small, predictable home ranges rather than widely-ranging animals or those with highly erratic movement patterns.
Future directions: biomonitoring at the intersection of ecoimmunology and disease-ecology Remote biomonitoring has the potential to contribute significantly to the growing intersection of ecoimmunology and disease-ecology by linking
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The use of RFID can also offer valuable insights into spatial distributions of animals and heterogeneity in inter-individual contacts, both of which can influence the spread of parasites and pathogens. The spatial distribution of individuals can be measured by tracking the presence or absence of certain individuals across RFID readers placed at different locations. Rates of contact between individuals can then be inferred based on the presence of multiple individuals within a very close spatial or temporal proximity. For instance, Moreau et al. (2011) measured ants’ spatial structure by introducing tagged ants into an artificial nest equipped with RFID readers at many different spatial domains (Moreau et al. 2011). Given the small spatial scale (i.e., within an ant nest) of their RFID set-up, Moreau et al. (2011) defined inter-individual contact as any time two ants came within 14 mm of one another. At larger spatial scales, the distances among readers and the inability of one reader to simultaneously log multiple individuals at once can complicate such endeavors. In this case, researchers can monitor inter-individual contacts as the presence of more than one individual at one location within a brief period of time, typically on the order of seconds. For instance, using bird feeders equipped with RFID readers, Aplin et al. (2013) quantified rates of contact among PIT-tagged great tits based on temporal proximity, and were able to incorporate this information into analyses of these animals’ social network. Similarly, Clay et al. (2009) used RFID to track contacts among PIT-tagged deer mice and test a fundamental theory in disease-ecology, termed the 20/80 rule. This theory suggests that in numerous infectious diseases, 20% of individuals are responsible for 80% of the transmission of the pathogen (Woolhouse et al. 1997). By defining contacts as any instance when two unique PIT-tags were logged at the same RFID reader within 15 s, Clay et al. (2009) found that contact rates closely matched the 20/80 rule: 17.5% of tagged individuals generated 75.4% of recorded contacts. This research also raises an important caveat to using RFID to estimate inter-individual contacts: choosing the time-interval between successive logs of PIT-tags to define as a contact requires calibration for each species studied (which Clay et al. [2009] achieved using video trials), and the relevant interval will likely depend on the type of contact of interest for the transmission of a particular disease (e.g., aggressive interactions; use of the same feeding station in close succession). The studies highlighted in this section illustrate a number of advantages of RFID in monitoring behavioral and physiological responses relevant to
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could also record individual foraging behaviors and the rates of contact among marked individuals. Although standard limitations of RFID would apply to such systems (see above), this technology nevertheless offers immediate functionality for remotely monitoring links among infection, behavior, interindividual contact, and pathogen-transmission. Second, recent advances in automated radiotelemetry have the potential to remotely monitor disease-status, additional physiological responses to infection, and rates of contact, all with improved spatial coverage within a landscape. Large-scale telemetric grids, spanning hundreds of hectares, can monitor activity, location, and physiological status (e.g., heart rate, energy expenditure, blood pressure, and body temperature) (Bowlin and Wikelski 2008; Bisson et al. 2009, 2011; Kays et al. 2011; US Army Corps of Engineers 2013). By incorporating data from multiple receivers, such systems triangulate signals from individual radiotransmitters, potentially yielding information on location, activity, and fever (disease-status) for multiple marked animals simultaneously. Using these data, researchers can extract information not only on individual responses to infection, but also on rates of contact among marked animals. Although such systems require significant initial capital and ongoing collaborations among engineers, computer scientists, and biologists, the ability to continuously monitor contacts across entire landscapes will vastly improve our ability to estimate behaviors relevant to the spread of disease in the wild. Third, satellite-based tracking has considerable potential for tracking contacts and disease-status. Several existing types of satellite tags have been applied to disease-relevant systems and can monitor an animal’s location using GPS, offloading data periodically to remote servers (e.g., Cui et al. 2011; Smith et al. 2011; Ratanakorn et al. 2012). Such tags could prove ideal for monitoring contacts and diseasestatus at broad spatial scales for a wide variety of species, particularly those that undertake expansive migratory movements. Unfortunately, the current size and expense of such tags limit both the types of species and the number of individuals that researchers can monitor. However, several research groups are developing new satellite technologies capable of detecting much smaller tags (Wikelski et al. 2007; icarusinitiative.org). Finally, devices that incorporate both GPS technology and tri-axial accelerometers will likely prove invaluable in linking disease-ecology and ecoimmunology across an array of spatial scales. Such tags can store detailed information on an animal’s location,
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within-host processes (e.g., replication of pathogens; immune-responses) and between-host processes (e.g., rates of contact) in free-living animals (Alizon and van Baalen 2008; Hawley and Altizer 2011). Because infectious diseases represent an increasing threat to biodiversity (Daszak et al. 2000; Fisher et al. 2012), remote biomonitoring can also tie ecoimmunology and disease-ecology to the emerging discipline of conservation physiology (Wikelski and Cooke 2006). As one key example, the way in which individuals behave during infection by pathogens is arguably one of the most critical determinants of whether and how directly-transmitted pathogens will spread (Hawley et al. 2011). Although numerous studies have examined such patterns from the perspective of parasite-induced changes in hosts’ behaviors, immune-mediated behavioral changes and the ecological factors that mediate them have received little, to no, attention in disease-ecology (Moore 2002; Thomas et al. 2005; Hawley and Altizer 2011). Instead, most work to date on behavior and disease-transmission has focused on behavioral predictors of infection (e.g., group size, foraging behavior, and social status) (Coˆte´ and Poulin 1995; Altizer et al. 2003; Ezenwa 2004). If we consider transmission as a mathematical function in a classic susceptible–infected–recovered model (Anderson and May 1979), rates of contact are modeled as a function of the density or frequency of susceptible and infected individuals, with the implicit assumption that the behavior of both classes is similar. Understanding the behavior of infectious individuals, and how that behavior might vary with within-host processes such as pathogen-load or activation of the immune system, is a key missing link in revealing how pathogens spread in free-living populations. Interest in linking within- and between-host processes, however, is growing (Alizon and van Baalen 2008; Mideo et al. 2008; Day et al. 2011; Hawley and Altizer 2011; Hawley et al. 2011; Adelman forthcoming 2015), and several advances in remote biomonitoring are likely to clarify the links among the behavior of infected individuals, rates of contact with healthy individuals, and spread of disease in the wild. First, temperature-sensing PIT-tags and RFID provide an immediate avenue for simultaneously monitoring individual behavior, infection, and rates of contact. Such PIT-tags are not significantly larger than standard PIT-tags and can be implanted subcutaneously or in the body cavity of animals as small as 10 g songbirds (Nord et al. 2013). For infections that induce fever, body temperature could then be monitored at RFID-enabled feeding or roosting stations and used as a proxy for infection. Such RFID units
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Acknowledgments The authors thank the organizers, participants, and attendees of the symposium ‘‘Methods and Mechanisms in Ecoimmunology,’’ held at the 2014 annual meeting of the Society for Integrative and Comparative Biology for their suggestions and engaging discussions. They also thank Karen Mabry for insightful discussions about automated telemetry and two anonymous reviewers for their valuable suggestions on a prior version of this article.
Funding This work was supported by the National Science Foundation [grant number IOS-1054675 to D.M.H.]. This paper was part of the symposium ‘‘Methods and Mechanisms in Ecoimmunology,’’ supported by the Divisions of Animal Behavior, Comparative Endocrinology, and Comparative Physiology and Biochemisty within the Society for Integrative and Comparative Biology, and the Research Coordination Network for Ecoimmunology funded by the National Science Foundation [grant number IOS-0947177 to Lynn B. Martin, D.M.H., and Daniel R. Ardia].
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