Hibernacula Microclimate and White-Nose Syndrome Susceptibility in the Little Rb Own Myotis (Myotis Lucifugus) Laura Grieneisen Bucknell University

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2011 Hibernacula Microclimate and White-nose Syndrome Susceptibility in the Little rB own Myotis (Myotis lucifugus) Laura Grieneisen Bucknell University

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Recommended Citation Grieneisen, Laura, "Hibernacula Microclimate and White-nose Syndrome Susceptibility in the Little rB own Myotis (Myotis lucifugus)" (2011). Master’s Theses. 12. https://digitalcommons.bucknell.edu/masters_theses/12

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TABLE OF CONTENTS

Acknowledgements……………………………………………………………………iii

List of Figures…………...……………………………………………………………..iv

List of Tables…………………………………………………………………………..vi

Abstract………………………………………………………………………………...2

Introduction…………………………………………………………………………….3

Study 1: Characterization of microclimate in typical bat roosts compared to the ‗WNS

shift zone‘……………………………………………………………………...29

Study 2: Thermal preferences of bats……………………………………………….....49

Study 3: The role of microclimate in survivability………………………………….....55

Conclusion……………………………………………………………………………..78

References…………………………………………………………………………...... 81

iii

ACKNOWLEDGEMENTS

I first and foremost want to thank my advisor, Dr. DeeAnn Reeder, for assistance in all aspects of this project. I also would like to thank the other members of my thesis committee, Dr. Warren Abrahamson and Dr. Ellen Herman, for their insight. The

National Speleological Society, McKenna Internship, Bucknell Biology Department, US

Fish & Wildlife Service, Woodtiger Foundation, and Bucknell University provided funding. I am grateful to the many people who worked with me. Greg Turner, Cal

Butchkoski, and other members of the Pennsylvania Game Commission assisted in collecting bats for studies and in deploying dataloggers. Cave and mine owners granted permission to access their sites. Constructing test equipment would not have been possible without the Bucknell physics shop: Moises Veloz, Jack Raup, and especially the late Dave Vayda. Dr. K.B. Boomer assisted with statistical analyses. The cavers and bat biologists who volunteered to deploy and collect TRH loggers include: Bill ‗Gator‘

Gates, Jennifer Pinkley, David Caudle, Steven Pitts, and Jimmy Romines from Alabama;

Cory Holliday and The Nature Conservancy in Tennessee; Al Kurta, S. M. Smith, and

Matt Portfleet from Michigan; and Marc-Andre Duval in Quebec. The Bucknell animal care staff includes Gretchen Long and Cindy Rhone. Field ―volunteers‖ include Morgan

Gilmour, Peter Riley, and Bradley Rhodes. I especially would like to thank all the members of the Batlab, who assisted with all parts of the project: Dr. Marianne Moore,

Sarah Brownlee, Morgan Furze, Cathy Meade, Chelsea McGorry, Chelsey Musante, Paul

Reamey, Hannah Rosen, and Megan Vodzak.

LIST OF FIGURES

Figure 1: Torpor and arousal patterns of a hibernating little brown myotis.

Figure 2: Simplified cave structures

Figure 3: Little brown myotis displaying physical signs of WNS

Figure 4: Major karst regions of the United States

Figure 5: Karst regions of the United States where caves are found and the

MAST-predicted southern extent of the growth range for Gd

Figure 6: The spread of WNS as of 1 June 2011

Figure 7: The disease triangle

Figure 8: Monthly mean temperature (+/- SEM) at the entrance versus historical

bat roost for eight hibernacula from October through March

Figure 9: Monthly coefficient of variation for temperature (+/- SEM) at the

entrance versus historical bat roost of hibernacula from October through

March

Figure 10: Temperature (ºC) at the entrance versus historical bat roost in Hubbard

Cave from 1 October 2010 to 1 April 2011

Figure 11: Monthly mean relative humidity (+/- SEM) at the entrance versus

historical bat roost at hibernacula from October through March

Figure 12: Monthly coefficient of variation for relative humidity (+/- SEM) at the

entrance versus historical bat roost at hibernacula from October through

March.

Figure 13: Relative humidity (%) at the entrance versus historical bat roost in

Hubbard Cave from 1 October 2010 to 1 April 2011.

Figure 14: Microclimate chamber

Figure 15: Temperature preferences of White-nose Syndrome-affected bats from

the entrance versus historical roosts of a cave

Figure 16: Modified microclimate chamber

Figure 17: Cumulative survival by WNS status and temperature

Figure 18: Cumulative survival by WNS status and sex

Figure 19: BMI by WNS status

Figure 20: Percent mortality by temperature and WNS status

Figure 21: BMI and survival

Figure 22: Torpid body temperature by WNS status and environmental chamber

temperature

Figure 23: Euthermic body temperature by WNS status and environmental

chamber temperature

Figure 24: Euthermic minus torpid body temperature (Teuthermic - Ttorpid) by WNS

status and environmental chamber temperature

Figure 25: Mean torpor bout length and survival

Figure 26: Mean torpor bout length and BMI

LIST OF TABLES

Table 1: Characterization of microclimate in typical bat roosts compared to the

‗WNS shift zone‘

Table 2: Variables in the final Cox regression model for survival

Table 3: Hazard ratios for the year 1 temperature study, as calculated from a Cox

regression

ABSTRACT

The objective of this project was to determine the relationship between hibernacula microclimate and White-nose Syndrome (WNS), an emerging infectious disease in bats.

Microclimate was examined on a species scale and at the level of the individual bat to determine if there was a difference in microclimate preference between healthy and

WNS-affected little brown myotis (Myotis lucifugus) and to determine the role of microclimate in disease progression. There is anecdotal evidence that colder, drier hibernacula are less affected by WNS. This was tested by placing rugged temperature and humidity dataloggers in field sites throughout the eastern USA, experimentally determining the response to microclimate differences in captive bats, and testing microclimate roosting preference. This study found that microclimate significantly differed from the entrance of a hibernaculum versus where bats traditionally roost. It also found hibernaculum temperature and sex had significant impacts on survival in WNS- affected bats. Male bats with WNS had increased survivability over WNS-affected female bats and WNS bats housed below the ideal growth range of the fungus that causes

WNS, Geomyces destructans, had increased survival over those housed at warmer temperatures. The results from this study are immediately applicable to (1) predict which hibernacula are more likely to be infected next winter, (2) further our understanding of

WNS, and (3) determine if direct mitigation strategies, such as altering the microclimate of mines, will be effective ways to combat the spread of the fungus.

INTRODUCTION

The concept of the disease triangle states that the interaction of a pathogen, host, and favorable environment is necessary for a disease to progress (McNew, 1960). In the case of White-nose Syndrome (WNS) in bats, the pathogen is the fungus Geomyces destructans, the hosts are hibernating North American bats, and the favorable environments are hibernacula (caves and mines) in the temperature and humidity range necessary for the fungus to grow. Because WNS is a disease that affects hibernating bats, it is important to understand the hibernation physiology of healthy bats and how WNS has the potential to alter this. Specifically, the goal of this study was to examine how microclimate (the temperature and humidity of hibernacula) affects hibernation behavior, survival, and energetic choices of WNS-affected bats.

Hibernation Physiology

Torpor

Many species of mammals utilize torpor, a metabolically reduced state, to conserve energy during energetically stressful times of the year. Mammals using daily torpor, such as lactating bats, can reduce energy expenditure by 20% to 58% (Vogt and

Lynn, 1982; Reynolds and Kunz, 2000). Torpor that is extended for several months, referred to as hibernation, is an adaptation to temporally avoid extended periods of low energy availability (Humphries et al., 2005). Hibernation is significantly and positively correlated with a longer lifespan in bats, possibly due to the decrease in exposure to

4 predators and adverse environmental conditions (South and Wilkinson, 2002). Of the 47 species of bats in North America, at least 25 have been observed to use some form of torpor. At least 21 of these use extended torpor (Cryan, 2010), and hibernation energetics have been studied in eight species (Geiser and Ruf, 1995).

The precise mechanism for entering torpor is highly debated, but it appears that long-term hibernators use metabolic inhibition combined with a drop in body temperature

(Tb) (Heller, 1979; Geiser 1988; Geiser, 2004). Torpid metabolic rate (TMR) may be

90% to 99% less than the resting metabolic rate (RMR) (Geiser, 2004; Matheson et al.,

o 2010). The change in metabolic rate per 10 C change in temperature (Q10) is inversely related to body mass, such that TMR at low temperatures is not significantly different among species with significantly different masses (Geiser, 1988). The median mass for hibernating mammals is 85g, with the majority ranging from 10 to 1000g (Geiser and

Ruf, 1995). Although the rate of metabolic reduction therefore varies greatly across all hibernators, hibernating bats typically range from 4g to less than 30g and so undergo similar metabolic changes. When metabolism drops, Tb falls from approximately 37ºC to within 0.5ºC of the ambient temperature (Ta). Tb is 2ºC – 12ºC in hibernating bats

(Thomas et al., 1990) but can be as low as -3ºC in arctic ground squirrels (Spermophilus parryii) (Barnes, 1989). It takes just under 12 hours for little brown myotis to enter deep hibernation (Thomas et al., 1990).

The drop in metabolic rate and body temperature sets off a cascade of other physiological changes that allow hibernators to tolerate hypothermia, hypoxia, and aglycemia (Frerichs and Hallenbeck, 1997). Rates of gene transcription are half of

5 euthermic rates (Martin and van Breuekelen, 2002). Digestion stops and the gut degenerates (Carey, 1992; Carey, 1995). Pancreatic amylase, a digestive enzyme, is reduced to 50% its summer concentrations in hibernating 13-lined ground squirrels

(Spermophilus tridecemlineatus) (Balslev-Clausen, 2003). Reduced protein kinase B

(Akt) activity in little brown myotis suggests that insulin response is lowered, which facilitates the use of fat reserves for fuel (Eddy and Storey, 2003). Oxidation of the lipids in brown adipose tissue becomes the primary source of energy (Dark, 2005). Euthermic biological rhythms are suspended as the molecular clock does not display daily oscillations (Revel et al., 2007). Corticosterone ceases to show its normal daily fluctuations (D. M. Reeder, unpublished) and the enzyme that generates melatonin rhythms in the pineal instead has a constant expression over 24 hours (Revel et al., 2007).

There are some physiological similarities between torpid mammals and euthermic mammals undergoing caloric restriction, specifically in hemoglobin oxygen affinity

(Spindler and Walford, 1997). The immune system is also down regulated (Carey et al.,

2003; Bouma et al. 2010). Hibernating mammals have fewer circulating white blood cells, specifically neutrophils and monocytes, which could lead to a reduced inflammation response (Szilagyi and Senturia, 1972; Bouma et al., 2010). Big brown bats

(Eptesicus fuscus) inoculated with Japanese B encephalitis did not make antibodies when maintained in a torpid state at 8ºC, but did when kept at euthermic temperatures (Sulkin et al., 1966).

In order to survive for several months without additional energy resources available, mammals either hoard food (e.g., chipmunks, Tamias striatus) or store their

6 energy in the form of body fat (e.g., bats). The energy budget for hibernation can be calculated as the amount of energy stored at the start of hibernation, minus the rate it is depleted and the length of winter (Humphries et al., 2005). Little brown myotis increase their mass from 7g to 10g when they enter hibernation by consuming enough insects to increase their fat from 7% of their mass to 38% (Kunz et al., 1998; Reynolds and Kunz,

2000). Much of this mass is gained in the last month before hibernation. From August to

September, adult male little brown myotis gain on average 2.3g (33% of their body mass) and adult female little brown myotis gain an average of 2.1g (30% of their body mass)

(Kunz et al., 1998). In a colony of Schreiber‘s bat (M. schreibersii) studied by Serra-

Cobo et al. (2000), bats increased their mass by 31.5% for the 29 days before the start of hibernation, and then dropped it by 23% over the first four months of hibernation. Female bats must lie down not only enough fat to survive hibernation, but also enough to ovulate upon spring emergence. Young-of-the-year are unable to put on as much mass as adults and subsequently have higher rates of mortality (Kunz et al., 1998; McGuire et al., 2009).

This is perhaps due to poorer foraging skills or allocation of resources to growth.

Arousals

Although hibernating mammals spend over 99% of their time in torpor (Geiser,

2004), they use 83 – 90% of their stored energy during arousal bouts (Thomas et al.,

1990; Thomas and Cloutier, 1992), in which metabolism and Tb return to euthermic levels (~ 37ºC; Hayward and Ball, 1966) (See Fig. 1). In bats, each arousal bout costs an estimated 107.9mg of fat (Thomas et al., 1990). In little brown myotis this process can

7 take 45 minutes (Thomas et al.,

1990) and an arousal bout lasts 1-

2 hours (Reeder et al., in prep). In other species an arousal bout can last for a day or more (Thomas et

Figure 1: Torpor and arousal patterns of a al., 1990; Geiser, 2004). However, hibernating little brown myotis. These data were obtained by fitting the bat with a datalogger that the time it takes to arouse and the recorded its skin temperature, Tsk(ºC), from November through March. (Figure from Reeder et al, in prep). cost of an arousal bout depends on the bats torpid Tb. It takes less time to arouse from a warmer Ta or Tb than it does from a colder one (French, 1982; Utz et al., 2007). It also takes less heat energy to arouse from a higher Tb than from a lower Tb (Humphries et al., 2002; Dunbar and Tomasi, 2006;

Boyles et al., 2007; Utz et al., 2007). Bats do not arouse at regular intervals. Two studies by Twente et al. (1985a; 1985b) found that tricolored bats (Perimyotis subflavus), little brown myotis, and big brown bats all averaged 7-25 day torpor bouts, with some bouts lasting as long as 76 days. However, the upper estimates in these studies may be inaccurate: the studies defined an arousal bout as a change in location, but bats do not always switch roosts during arousal bouts. The duration of torpor bouts increase at colder temperatures (Geiser and Kenagy, 1988; Park et al., 2000; Jacob, 2009) which suggests the frequency of arousal is metabolically controlled (Twente et al., 1985a). Heat for arousals (thermogenesis) is generated by brown adipose tissue (BAT), the liver, muscles, and passive warming (Thomas et al., 1990; Geiser, 2004). Arousal bouts increase oxidative stress in BAT (Orr et al., 2009). Flying decreases the length of time to arouse

8 from torpor, which suggests that flight muscles may play a role in thermogenesis (Willis and Brigham, 2003).

There is not a precise delineation between euthermia and torpor. It is difficult to define because skin temperature (a standard measure of Tb) and metabolic rate are not consistently related in different species of bats (Willis and Brigham, 2003). Barclay et al.

(2001) suggested defining torpor for an individual by measuring its Tb when it is active

(flying) and assuming that a Tb less than that is torpor. It is often impractical or impossible to monitor individuals when they are active and torpid. Instead, researchers may attach dataloggers that track body temperature and define torpor based on relative changes in Tb. The Reeder lab defines arousal bouts as when Tb > Tb maximum - 10ºC, a definition that I used for my study. Other definitions include ―a rapid increase in temperature‖ (Dunbar and Tomasi, 2006), ―sustained increases in oxygen consumption and Tb‖ (Karpovich et al., 2009), or if Tb is above versus below 20ºC (Park et al., 2000).

The cause of arousal bouts is unknown, but there are several non-exclusive hypotheses to explain them. Dropping metabolism is physiologically costly; it is associated with an increase in reactive oxygen species (Buzadzic et al., 1990), immunosuppression (Burton and Reichman, 1999), and the risk of brain damage

(Frerichs and Hallenbeck, 1997). Arousals may help to minimize these costs by returning physiological systems to homeostasis (Humphries et al., 2003a). The ‗water balance hypothesis‘ suggests that bats arouse because they are dehydrated, which may be from excessive evaporative water loss from exposed wing membranes (Thomas and Cloutier,

1992; Cryan et al., 2010). Dehydration causes an ionic imbalance and poorer circulation

(Thomas and Geiser, 1997). Arousals may also allow the immune system to fight off any pathogens that were introduced while the hibernator was torpid. Golden mantled ground squirrels (Callospermophilus lateralis) injected with bacterial lipopolysaccharide (LPS) during hibernation did not display a fever until they aroused a few days later, when they underwent an unusually long arousal (Prendergast et al., 2002). Szilagyi and Senturia

(1972) posit that leukocytes may be stored for release during arousals, as high quantities of mature leukocytes are found in the bone marrow of hibernating woodchucks (Marmota monax) and thirteen-lined ground squirrels.

Additional arousals occur when bats are disturbed, e.g., from people or predators entering hibernacula. Bats arouse from sound, touch, and changes in temperature (Fenton and Barclay, 1980). A model by Boyles and Brack (2009), predicts that the survival rate of hibernating little brown myotis drops from 96% to 73% with human disturbances.

Survival rate likewise drops when bats are in easily preyed upon locations near the entrances of hibernacula (Kokurewicz, 2004). Predation upon hibernating bats is likely to be successful because it takes up to 45 minutes for bats to arouse (Thomas et al., 1990).

Great tits (Parus major) and eastern screech owls (Megascops asio) have been observed successfully preying upon hibernating common pipistrelle (Pipistrellus pipistrellus) and little brown myotis, respectively (Estok et al., 2010; pers. obs.).

Activities during arousals vary by species. Leaf litter and tree hibernators may arouse on warmer days to feed, while cave bats tend to be less active and spend their arousal bouts copulating and/or switching roosts in the hibernaculum (Tidemann 1982;

Park et al., 2000; Boyles et al., 2006). Bats that feed when aroused may do so to offset

10 some of the costs of an arousal bout; greater horseshoe bats (Rhinolophus ferrumequinum) arouse at dusk significantly more often than any other time of the day, presumably to forage (Park et al., 2000). Some will actually fly to a different hibernaculum (Serra-Cobo et al., 2000). Hibernating tricolored bats use winter emergence flights primarily to drink (Speakman and Racey, 1989) and hibernators sometimes sleep during arousal bouts (Daan et al., 1991).

The frequency of arousals varies by species, mass, and health status. Little brown myotis, big brown bats, and tricolored bats all average 10 to 20 days between arousal bouts, although the frequency of arousal bouts is positively correlated with Ta (Brack and

Twente, 1985; Dunbar, 2004; Dunbar and Tomasi, 2006; Boyles et al., 2007). More specifically, little brown myotis arouse every 12.9 to 19.7 days when the Ta is 5.6ºC

(Brack and Twente, 1985). Heavier animals or those that are artificially provided with additional food arouse more frequently than those that weigh less or do not have their diets supplemented (Humphries et al., 2003b; Reeder et al., in prep).

Roost location- physiology

Microclimate, specifically temperature and humidity, play an important role in which hibernacula bats utilize, where bats choose to hibernate within the hibernaculum, and if bats choose to roost in clumps or individually (Clawson et al., 1980). Bats rarely choose to hibernate at the entrances of hibernacula, as this area can be extremely cold and subject to greater predation and daily temperature fluctuations than deeper underground.

Rather, they choose to roost farther back in caves and mines. Some species prefer to hang

11 exposed, while others crawl in crevices (Zukal et al., 2005). Different species tend to hibernate primarily in clusters or primarily solitarily, although individuals within a species may choose either strategy. Solitary roosting can minimize spread of disease.

Parasites may move between clustered hosts and can thus spread disease through a torpid population, even if the hosts do not show symptoms until emergence (Bižanova and

Dobrokhotova, 2006). Roosting solitarily also may decrease chances of detection by a predator (Hwang et al., 2007).

Bats may employ communal roosting throughout the year to minimize heat loss

(Kunz, 1982). The arousal hypothesis, which proposes that bats cluster specifically during hibernation because it minimizes loss of body heat during arousal bouts, is supported by Boyles et al.‘s (2008) model where cluster size was most strongly predicted by ambient temperature and cluster size was negatively correlated with ambient temperature variation and body condition. This concurs with observations that little brown myotis hibernating in clusters tended to be in colder areas of the cave (3 to11ºC), while those hibernating solo tended to be in warmer areas (Henshaw, 1966). In addition, larger clusters correlate with colder substrate temperatures (Clawson et al., 1980). A model by Boyles and Brack (2009) predicted that little brown myotis would have >96% survival rate when bats cluster with no human disturbance for 90-200 day winters. For

200+ day winters, survival was 73% +/- 0.01 when bats didn‘t cluster. Clustering may also help to minimize energy expenditure when there are changes in ambient temperature

(Boyles et al., 2008).

Microclimate plays a major role in where bats roost. Because torpid body temperature can fall to within 1ºC of ambient temperature (Dunbar, 2004), it is best to roost at the ambient temperature at which torpid metabolic rate is most efficient. Arctic ground squirrels roost in outdoor burrows that can reach -40ºC (Barnes, 1989). Bats, however, have only been found to roost at ambient temperatures between -10ºC and

21ºC, with a mode of 6ºC for Vespertilionidae and 11°C for Rhinolophidae (Webb et al.,

1995). The most energetically efficient roosting temperature for hibernating bats is 2ºC

(McManus, 1974; Webb et al., 1995; Humphries et al., 2005; Boyles et al., 2007).

Thermogenic modeling predicts that for an average winter length of 193 days, a little brown myotis hibernating at 2ºC will use 1.2g of fat, but hibernating at any other temperature between -1ºC and 12ºC requires three times as much energy (Humphries et al., 2002, 2005). The relationship between metabolism (measured in oxygen consumption) and body temperature is curvilinear, such that a drop in body temperature from 35ºC to 30ºC saves more energy than a drop from 25ºC to 20ºC (Studier, 1981).

Little brown myotis hibernate 40% longer in southern Ontario than southern Missouri but require 26% less energy because hibernaculum temperatures are 6ºC colder on average

(9.5ºC and 3ºC, respectively) (Humphries et al., 2005). Sub-zero temperatures in particular require more energy because bats must raise their body temperature to above freezing (Dunbar and Tomasi, 2006). Hibernacula surveys have supported this model, with the highest percentage of bats in a mine choosing to roost in a tunnel segment that was 2.1ºC (McManus, 1974). However, a model by Boyles and McKechnie (2010) predicted that in hibernacula with fluctuating temperatures, bats should roost at slightly

13 above 2ºC so that temperature fluctuations would not drop below 2ºC. The best hibernation strategy may be to hibernate at the warmest possible temperature to arouse the most often while still having energy to survive the winter in order to minimize hibernation torpor costs (Boyles et al., 2007).

Humidity also plays in a role in hibernation. Bats have a lot of exposed skin because their patagiums are sparsely furred, which means that they are more susceptible to dehydration from evaporative water loss (Cryan et al., 2010). Water loss in laboratory trials for little brown myotis is 5.5 times greater at 4oC and 90% humidity than at 2oC and

98% humidity (Thomas and Cloutier, 1992). Water loss may also be reduced by clustering (Fenton, 1983). This may be why bats hibernate at high humidity. Brigham

(1993) predicted that bats in humid sites would arouse less frequently than those in drier sites.

There is a well-studied relationship between ambient temperature and mass. Little brown myotis roosting in warmer areas of hibernacula weighed significantly more than those in colder areas when examined in December, January, and February (Boyles et al.,

2007). This is most likely due to availability of fatty acids. Big brown bats placed in an artificial hibernaculum that provided a thermal gradient from 6.0ºC to 12.5ºC chose significantly colder roosts when their fatty acid availability was limited (Boyles et al.,

2007). Eastern chipmunks (Tamias striatus) provided with additional food before the start of hibernation had a minimum torpor body temperature of 5-10ºC warmer than controls

(Humphries et al., 2003b). Although roosting at a warmer temperature requires more energy as it incurs a higher metabolic rate, it has ecological and physiological benefits

14 such as lower costs of arousals (Humphries et al., 2002; Humphries et al., 2003b; Dunbar,

2004; Dunbar and Tomasi, 2006; Boyles et al., 2007; Utz et al., 2007; Matheson et al.,

2010). Because of the effects of arousals, animals less likely to survive the winter are the ones that roost at the coldest temperatures. Young-of-the-year, which are in poorer body condition than adults, roost at significantly colder temperatures than adult bats and have a higher rate of starvation (Kokurewicz, 2004).

Roost location- cave morphology

Although some species of bats hibernate under bark or in the leaf litter, most species have historically required caves for hibernation. With the advent of man-made structures, many bats now hibernate in mines, bunkers, abandoned buildings, and unheated attics. However, they are still considered trogloxenic because require a cave- like structure for part of their lifecycle. The precise cave morphology that hibernating bats prefer is poorly studied.

There are several types of caves. The most common kind is formed when water dissolves limestone or dolomite bedrock, creating solution caves and sinkholes that form a karst system (Palmer, 1991). Large portions of Appalachia contain karst formations, which accounts for the numerous caves throughout the region that bats utilize for hibernation. Caves formed by other processes, including sea caves, eolian caves, rock shelters, talus caves, and glacier caves (Duckeck, 2010) may also be utilized by bats.

Climate plays a role in whether bats use a cave as a summer roost or a winter hibernaculum. The mean annual surface temperature (MAST) of a region is the average

15 temperature over the course of a year. When MAST is 2ºC – 12ºC, caves in that region are good for hibernation. Caves with a MAST greater than 20ºC are good for maternity roosts, while those between 12ºC and 20ºC are too cold in the summer and too warm in the winter for bats to utilize them (Tuttle and Stevenson, 1978). A variety of additional factors make the bat use status of a cave not perfectly predictable by its MAST. These include elevation, if the cave is on a north- or south-facing slope, geothermal gradient

(how deep it goes), heat decay of rocks (i.e., uranium, granite), water flow, shape of the entrance, and air flow (Bodino, 2010; Perry, 2010). Air flow is in turn influenced by subterranean morphology and the number and direction of the entrances. The difference between air and substrate temperature can fluctuate from 3 or 4°C in either direction, depending on the distance from the entrance and air flow patterns (Tuttle and Stevenson,

1978). Bats hibernate deep in caves where air is often only 1ºC warmer than wall temperatures (Tuttle and Stevenson, 1978). A 1955 study by Twente noted that

―Differences between caverns and within a single cavern would seem to make a study of environmental habitat selection by cave bats a rewarding one.‖ Few studies since then have taken advantage of that ‗rewarding‘ field. Although descriptions of temperature and humidity preferences of some species are documented, there are modest data on the exact type of cave bats prefer. Tuttle and Stevenson (1978) subdivided caves used as hibernacula into seven structural types (See Fig. 2). These structural types are not congruent with how geologists classify caves (Palmer, 1991) and caves that form through completely different geological processes can meet Tuttle and Stevenson‘s (1978) definition of a good hibernaculum.

Figure 2: Simplified cave structures. Airflow indicated as occurring in ―winter‖ will generally occur when outside temperature is below mean annual surface temperature (MAST); flow marked ―summer‖ will occur when outside temperature is above MAST. Type 1: Breathes (as indicated by arrows) in winter; stores cold air in summer. Type 2: Undulation at A acts as dam inhibiting air flow; temperature relatively constant beyond dam. Type 3: ―Jug‖ shape often postulated to exhibit resonance; may have pulsing in and out air movement, especially when outside air deviates from MAST. Type 4: Strong air circulation from A to B in winter; stores cold air in summer. Type 5: The reverse of Type 1; warm air enter along ceiling in summer while air cooled by cave walls flows out along floor. No flow in winter. X is a warm air trap, Y stays at a relatively constant temperature. Type 6: Strong air flow from A to B in winter; equally strong air flow in opposite direction in summer. Type 7: Same as Type 6, with a warm air trap (X), cold air trap (Y), and an area of relatively constant temperature (Z). Distance between and elevational displacement of the entrances are critical factors in the air flow direction in these two cave types; the flow of air (cooled relative to outside temperatures by the cave walls) down in summer must be strong in order to overcome the tendency for warm outside air to rise into A. Similarly, in winter the ―negative pressure‖ created by air (now warmer than outside air due to the MAST effect of the cave walls) rising out of B must be strong enough to pull cold air up into A (Figure and text from Tuttle and Stevenson, 1978). Hibernating caves are usually type 1, 4, 6, or 7, with type 4 being the best (Fig. 2; Tuttle and Stevenson 1978). These types may be the most stable caves because structural complexity can contribute to thermal complexity, meaning that there is a range of microclimates over time (Tuttle and Stevenson 1978; Raesly and Gates 1987). There are

17 also thermal and humidity gradients in caves. Studies on vertical temperature gradients, or temperature sedimentation, found that a thermometer held 20m over the floor of the cave in a large chamber read 1.5ºC higher than one held at 1m above the floor (Badino,

2010; Villar et al., 2010). Cave entrances are colder than deeper areas and the floor is more humid than the ceiling (Kokurewicz, 2004). Because microclimate varies during hibernation—caves start warmer, cool down, then warm up again—complex caves help to minimize hibernation energy use (Raesly and Gates, 1987). Complex caves provide a broader diversity of microclimate choices, so they are more likely to meet the needs of several species. Complex caves also have a higher number of crevices, which have more stable microclimates than exposed areas. Bats in crevices can enter deeper bouts of torpor and stay torpid longer (Solick and Barclay, 2006).

Bats can be selective in the caves they choose. For example, grey bats (Myotis grisescens) occupy a maximum of 2.4% of 1,635 known caves in Alabama (Tuttle and

Stevenson, 1978). Bats also demonstrate a high site fidelity, which is not correlated with distance to the nearest appropriate summer habitat (Glover and Altringham, 2008). They may migrate several hundred kilometers between summer sites and hibernation sites

(Humphries et al., 2005). One reason why bats are not always found in what would be predicted to be the best caves for hibernation may be because of human disturbance, as some ideal bat caves are popular for recreational caving (Tuttle and Stevenson, 1978).

Bats may also leave when caves are gated, as this can significantly change ambient and substrate temperatures in the winter (Puckette et al., 2006).

White-nose Syndrome

Background

White-nose Syndrome (WNS) is an emerging infectious disease that has devastated insectivorous bat populations in the US since it first appeared in a cave in

New York State in 2006. In the first four years following discovery, WNS killed over one million bats

(Kunz and Tuttle, 2009). White-nose Syndrome was Figure 3: Little brown myotis displaying physical signs of WNS. named for the white fungus that grows on the muzzle Geomyces destructans, the causative agent of WNS, is a white fungus that grows on the nose, ears, and and/or on the ears and wing membranes of hibernating forearms. bats (See Fig. 3). Genetic sequencing has identified the fungus as a previously undescribed species, Geomyces destructans (Gd) (Blehert et al., 2008; Gargas et al.,

2009). Gd has since been found to grow on at least five species of bats in Europe, none of which have suffered mortality (Wibbelt, 2010). It is thought that Gd coevolved with

European bats and it was accidentally transported to North America via a human vector

(Wibbelt, 2010). The presence of Gd can be diagnosed by a rapid PCR test (Lorch et al.,

2010). Gd is a unique cutaneous fungus, as it invades living tissue rather than the dead surface skin cells that are the typical domain of dermatophytic fungi (Pedis et al., 2010).

Hyphae from Gd penetrate the epidermis and infect the connective tissue of the wing, nose, and ear. In addition, hyphae infect hair follicles, sebaceous glands, and apocrine glands (Meteyer et al., 2009), which could be interfering with heat exchange, evaporative

19 water loss, and secretion of protective moisturizers (Cryan et al., 2010). Despite this range of infected tissues, bats do not display inflammation associated with an immune response to fungal infection (Meteyer et al., 2009). This may be due to the immunosuppression that occurs during hibernation (Bouma et al., 2010). Gd is transmitted via physical contact and through the air (D.S. Blehert et al., in prep).

Gd is a psychrophilic fungus that thrives best between 5ºC and 14ºC, although it has been cultured on agar plates from 3ºC to 20ºC (Blehart et al., 2009). Because the fungus grows much more slowly at 3-4ºC and at 15-20ºC, it is likely that bats in hibernacula that fall outside of the 5ºC to 14ºC temperature range will be less susceptible to infection (Blehart et al., 2009). However, the caves and mines that bats use for winter hibernacula typically fall between 2ºC and 14ºC, making this fungus well-suited for infecting numerous species. As hibernacula temperatures are fairly constant year-round, there is also potential for fungus to survive in a hibernaculum from one winter to the next. The temperature and humidity ranges of the majority of bat hibernacula in North

America are unknown, making it difficult to predict which mines and caves may be more susceptible to hosting this fungus. In addition, there has not been a detailed study on the humidity level at which Gd thrives, although it can be predicted that, like most fungi, it thrives better at higher humidity.

Of the 47 species of bats in North America, nine have tested positive for the presence of Gd. These include little brown myotis, big brown bat, tricolored bat, northern long-eared myotis (Myotis septentrionalis), eastern small-footed myotis (Myotis leibii), cave myotis (Myotis velifer), southeastern myotis (Myotis austroriparius), and the

20 endangered Indiana bat and grey bat. WNS is associated with behavioral and physiological modifications, including depleted fat reserves (Blehert et al., 2009), a potentially reduced ability to arouse from deep torpor, an increase in number of arousal bouts (D.M. Reeder et al., in prep), and atypical behavior such as leaving hibernacula early during the winter. Healthy little brown myotis hibernate far back in hibernacula, where temperatures are warmer and more stable than near the entrance. Many White-

Nose researchers have observed that infected little brown myotis arouse, move to, and subsequently die near the entrances to hibernacula, which are presumably much colder and less stable than where healthy bats choose to hibernate. The different microclimate

(colder, potentially drier, and less thermally stable) near the entrances of hibernacula may alter thermoregulatory behavior, increase stress levels, affect rates of fungal growth, and contribute to premature death of infected bats. Storm and Boyles (2010) found that WNS- affected little brown myotis have significantly lower mass than unaffected bats. Mortality is presumed to result from starvation. In severely affected sites, WNS has a mortality rate of over 99% (Turner et al., 2011). Bats that survive the winter may die soon after emergence in the spring because their poor wing condition and low mass could make flying after prey extremely difficult (Reichard and Kunz, 2009; Cryan et al., 2010).

Attempts to mitigate the effects of WNS, such as through creation of artificial warm areas in caves for aroused bats to roost in, have been unsuccessful thus far (Boyles and Willis,

2010).

WNS has traveled over 2200km from where it was first identified in February

2006, and it is expected to continue to spread. Figure 4 shows the major karst regions of

21 the United States. Figure 5 illustrates mean annual surface temperature, a predictor of average cave temperature (Tuttle and Stevenson, 1978). It also shows the karst regions of the United States where cavernicolous bats hibernate and thus are the most susceptible to fungal spread. The map is overlaid with lines that show the predicted southern spread of the fungus based on its growth range, which suggest that the majority of the US, with the exception of California, the Southwest, Texas, Florida, and the Deep South could be susceptible. However, caves that do not follow MAST predictions almost definitely exist in these areas (Perry, 2010), so they may be susceptible. Figure 6 highlights the counties in the 19 states and four Canadian provinces where Gd has been documented on bats using PCR. From these maps, it is easy to predict that Missouri, Michigan, and northern

Georgia will be infected in the near future. It appears that hibernating bats in the western half of the US will not be affected for several years, as cave areas in the west are more diffuse and it may take longer for WNS to reach most of them. It is also unlikely that

WNS will affect the southwestern US because fewer species of bats hibernate there in large numbers. It is warm enough year-round in the Southwest that food is consistently available for bats and many choose to not hibernate (Geluso, 2007). However, because bats may migrate hundreds of kilometers from their summer roosts to winter hibernacula

(Humphries et al., 2005) and many of these hibernation patterns are unknown, the disease may spread more rapidly than predicted. Gd also is presumed to be transmitted by humans, as fungal spores may cling to cave gear and be transported to other caves. It is unknown if Gd can go dormant during the summer on bats that survive infection and re-emerge the next year, so the role of migrators in its spread is yet to be determined.

Figure 4: Major karst regions of the United States. Karst systems are most commonly formed when water dissolves dolomite or limestone, forming aquifers, caves, and sinkholes. The colored regions on the map indicate different karst types (see legend). Map from Veni, 2002.

Figure 5: Karst regions of the United States where caves are found and the MAST- predicted southern extent of the growth range for Gd. Dark areas indicate the major karst regions of the United States with caves utilized by hibernating bats. Mean annual surface temperature (MAST) roughly predicts cave temperature (Tuttle and Stevenson, 1978). This map is overlaid with lines that show the predicted southern spread of Gd based on its growth range, which suggest that the majority of the US could be susceptible. However, caves that do not follow MAST predictions almost definitely exist in these areas (Perry, 2010), so they may be susceptible. Figure by D.M. Reeder and P.T. Reamey, 2011.

Figure 6: The spread of WNS as of 1 June 2011. WNS was first seen in Schoharie County, NY in 2006. Since then it has spread to 19 US states and 4 Canadian provinces. Infected counties are shaded by year (see legend). Map by Cal Butchkoski, PAGC.

Interspecies variation in WNS susceptibility

Variation in WNS susceptibility can be viewed in context of the disease triangle, such that species-specific physiology and microclimate roosting preference likely have a major influence on how well different species fare (See Fig. 7). Raesly and Gates (1987) compared eight microclimate and structural variables in five different species of bats, and found that the biggest inter-species differences were in temperature and humidity.

Temperature and humidity were assumed to be the most important variables in determining if bats roost in a cave and where in the cave they choose, because these have

25 the greatest influence on the metabolic process during hibernation (Raesly and

Gates, 1987).

There is no thorough review on the hibernacula temperatures and humidities preferred by different species of hibernating bats. Although a review by Figure 7: The disease triangle Webb et al. (1996) lists hibernacula temperatures at which 34 species of bats have been found, the authors included the caveat that many of the studies from which they drew their data did not explicitly state that bats were torpid at the time. Temperature ranges were based on single observations, so they varied from -10oC to 21oC. Many accounts do not give sufficient detail to create a model. A study by Raesly and Gates (1987) noted that big brown bats tended hibernate in dry, cool, breezy passages near standing water while little brown myotis hibernated primarily on the side walls of wide, long passages with areas of low ambient temperature. Clawson et al. (1980) likewise recorded that all

Indiana bats caves had >77% relative humidity (RH), but percentage of RH above that did not appear to determine roost preference. This problem is further compounded by the fact that bats change location in the cave over the course of the winter, moving from farther back in the cave to colder sites closer to cave entrances and form larger clusters later in winter (Clawson et al., 1980).

Project objectives

This project addressed microclimate and WNS primarily in the little brown myotis, the most common species of bat in the US and one that has been so severely affected by WNS that is predicted to go extinct in the northeast in the next 15 years unless an effective way to combat the spread of the disease is found (Frick et al., 2010).

Therefore, the objective of this study was to examine microclimate across species and at the level of the individual bat. Specifically, the goals were 1) to examine hibernacula microclimate at historical roosting areas (back of hibernacula) versus areas where WNS- affected bats roost (entrances of hibernacula); 2) to examine microclimate preferences of

WNS-affected versus unaffected little brown myotis to see if WNS-affected bats shift their roosts for microclimatic advantages; and 3) to determine the impact of microclimate on WNS disease progression, energy use, and mortality in the little brown myotis.

Impacts

Understanding how Gd changes bat behavior in respect to temperature preference is a key step in understanding why WNS results in so many mortalities. Seventeen of the

25 hibernating bat species in North America are endangered or a species of concern

(Cryan, 2010). Other species will soon join this list. The majority of bat species have one pup per year, so even assuming that some individuals have an inherited immunity to

WNS, it will take decades (if ever) to restore populations to pre-WNS levels.

A lactating bat can eat its body mass in insects (4-8g) every night during the summer (Anthony and Kunz, 1977; Kurta et al., 1989; Encarnacao and Dietz, 2006),

27 which means that the extinction of the little brown myotis could affect the vital ecosystem services that bats provide. For example, Pennsylvania has naturally high bat populations due to the over 1000 hibernacula (mines and caves) dispersed throughout the state and one-to-two million bats likely live in Pennsylvania (D. M. Reeder, pers. comm.). These one-to-two million bats eat 630-1259 metric tons of insects each year

(Kunz and Tuttle, 2009). Consequences of the loss of bats and thus increase in insects

(and associated ecosystem perturbations) could include an increase in pesticide use and mosquito-borne illnesses as the insect population rises. A model by Boyles et al. (2011) predicted that the decrease in bats due to WNS could cost the agriculture industry at least

$3.7 billion each year, with an upper estimate of $53 billion each year. Bats are an important part of the environment and this study has shed more light on how they fit in and how they can be better protected.

In addition, this project addressed the following questions, which were identified as Priority Research Gaps at the 2009 White Nose Syndrome Science Strategy Meeting

II. The goal of the WNS strategy meetings are to discuss what is known about WNS and where research should go next. The 2009 Priority Research Gaps included:

1. Can the dispersal of WNS be predicted?

This study recorded the microclimate profiles for WNS-affected and unaffected

hibernacula. These can be used to predict which caves will be likely to host WNS-

affected bats next winter, allowing ample time for conservation efforts. If

microclimate is a major predictor of WNS prevalence, direct mitigation strategies

such as altering mine microclimate to make it less conducive to fungal growth could

28 be used to slow the spread of the disease. Although some mines are too physically complex for mediation of microclimate to be practical, there are many small, simple mines (e.g., Shindle Iron Mine in Pennsylvania) where altering microclimate would be very feasible. Caves that are less likely to harbor Gd can be made first priorities to be gated. Gating a cave refers to installing an iron gate across the entrance such that people cannot enter the cave but bats are able to fly freely. Because humans are presumed to have greatly contributed to the initial spread of WNS by not cleaning gear between sites, gating a site prevents anthropogenic spread of WNS.

2. Can WNS-affected bats survive?

The observation of bats in artificial hibernacula in captivity not only allowed us to determine if WNS-affected bats are able to survive the disease, but also if the hibernaculum temperature influenced their survival. In addition, understanding how

G. destructans changes bat behavior in respect to temperature preference is a key step in understanding why WNS results in so many mortalities. Results from this study may be utilized to predict which caves will be likely to host WNS-affected bats next winter so that steps can be taken to lessen the impact of disease.

STUDY 1: CHARACTERIZATION OF MICROCLIMATE IN TYPICAL BAT

ROOSTS COMPARED TO THE ‘WNS SHIFT ZONE’

Study background and hypotheses

Microclimate plays a major role in where bats roost. Bats rarely choose to hibernate at the entrances of hibernacula. Rather, they choose to roost farther back in caves and mines. There is anecdotal evidence that bats with WNS roost at the entrances of hibernacula, which presumably presents hibernating bats with a more variable environment than do historical hibernation areas in the back of caves. The goals of this study were to assess the microclimatic difference between the entrances of hibernacula and historical hibernation areas. I hypothesized that historical roosting areas of bats would be more thermally stable, more humid, and not as cold in midwinter as the entrances to hibernacula. This was assessed by deploying temperature and relative humidity data loggers to hibernacula throughout the eastern half of the US and Canada.

In addition, I researched historical data on microclimate preference species of bats in

WNS-affected regions of the US to see what factors may predict degree of susceptibility.

Assessing interspecies variation in WNS susceptibility

Temperature and humidity roosting preferences are presumed to be important variables in determining if a species is more or less susceptible to WNS, based on the Gd fungus‘ growth range. Gd thrives best between 5ºC and 14ºC (Blehart et al., 2009) and it is presumed to grow best at high levels of humidity because most fungi require high amounts of moisture to complete their life processes. Other influences on species

30 susceptibility are likely related to clustering, amount of body fat, and wing membrane physiology. Gd is part of a family of soil-dwelling fungi (Gargas et al., 2009), so it is unlikely to spread to tree-roosting or tree-hibernating bats. In addition, tree-hibernators are more active in the winter than most cave-hibernators (Boyles et al., 2006). WNS- infected bats that are aroused and kept at a warm temperature for the duration of the winter (such as at bat rehabilitation clinics) are able to survive the infection (G. R.

Turner, unpublished). It can therefore be assumed that bats that frequently arouse and forage, such as tree bats, will be less susceptible to infection. Because Gd is most likely spread through physical contact, bats that cluster should be more susceptible than those that roost solitarily. However, big brown bats and tricolored bats both roost solitarily, but tricolored bats appear to have high mortality (>85%) while big brown bats are relatively unaffected (Turner et al., 2011). Size difference may be a factor because the greater surface area of a big brown bat may increase the time it takes to reach a certain level on infection. In addition, big brown bats have a smaller surface area: volume ratio than tricolored bats, which means that they lose heat and thus burn energy at a slower rate than smaller species. Microclimate likely plays a larger role. Big brown bats prefer to hibernate at cold temperatures in drier areas (Kurta and Baker, 1990), while tricolored bats prefer sites with at least 80% humidity and temperatures in the 9-12oC range (Fujita and Kunz, 1984; Briggler and Prather, 2003). This is a comparison between only two species, but it suggests that large bats with microclimate and solitary roosting preferences similar to big brown bats will have increased survivability versus those with preferences closer to tricolored bats. For example, the eastern small-footed myotis has similar

31 hibernation preferences to the big brown bat, and it has an overall decrease in population due to WNS of only 12% (Turner et al., 2011). Similar predictions can be made about other species in Table 1.

Table 1: A sample of North American hibernating bats. Asterisks indicate data modified from a chart by D.M. Reeder. Blank spaces indicate that data are unavailable. All WNS mortality estimates are from Turner et al., 2011.

Species Mass Cave Cave Cluster Additional Hibernation Info WNS Citation (g) Temp. Humidity status (oC) (% RH) 91% Little brown 7 to Nearly always cluster in large Fenton and 5 to 8 >70% Y population myotis * 10 groups (5-100s). Barclay, 1980 decline Hibernate solitarily or in small clusters (sometimes Northern 98% Caceres and clusters with M. lucifugus); long-eared 5 to 9 2 to 13 rarely population Barclay, 2000; May hibernate in deep myotis * decline Layne, 1958 crevices or move between hibernacula in the winter. 9 to 12, Hibernate solitarily in deeper Fujita and but parts of caves with stable 75% Kunz, 1984; Tricolored bat * 4 to 8 range >80% N temps; highest hibernacula population Briggler and from 5 site fidelity. First to enter decline Prather, 2003 to 16 hibernacula and last to leave. Last to enter hibernacula and first to leave, prefer colder <5 in drier, more exposed locations 41% 11 to Kurta and Big brown bat * captive N with higher air flow within population 23 Baker, 1990 studies hibernacula than other decline species; nearly always solitary. 33

Have been found hibernating singly and up to groups of 30. Found in caves and mines, in narrow crevices, wall, ceiling, or tucked between rocks on low RH the floor. Often found in Eastern 12% 3.8 to subject to 'drafty open mines and Best and small-footed 4 to 11 Y population 5.5 great caves… near the entrance Jennings, 1997 myotis * decline fluctuation where T drops below freezing.' Conditions similar to E. fuscus, but not as tolerant of cold and dry. Last in, first out. Move between sites during winter. Tend towards site fidelity, 3.5 to 66% - cluster size is inverse to T, 72% 10; 95% Thomson, Indiana bat * 2 to 5 Y called "the cluster bat". Tend population mean (mean 1982 to be easily aroused by decline 6.4 87%) disturbances. Select coldest caves versus other Myotis in its range. Decher and Summer maternity caves have Choat, 1995; Presence of 7 to 6.7 to 66 - 95% humidity. Winter Howell, 1909; Grey bat * Y Gd 16 10 caves may have several Bat confirmed hundred thousand individuals. Conservation 95% of population hibernates International in 8 caves. high RH; Found in clusters in cracks Presence of Fitch et al., 9 to Cave myotis * 0 to 10 55% to Y and crevices in caves. Tend Gd 1981; Allen, 12 100% towards site fidelity. confirmed 1890

Mauk- In the northern part of its F 5.2 Cunningham range (when T < 40) in to 8.1 Presence of and Jones, Southeastern 4.5 to winter, will hibernate up to 7 Y Gd 2003; Jones myotis 20 months. Clump in groups of M 5.1 confirmed and Manning ~50. Active in winter in to 6.8 1989; Rice southern part of range. 1957 Depending on the latitude/elevation, may be Nagorsen et M. californicus active, hibernating, or use No al., 1993; 3.3 to 10.7 to Y extended torpor bouts in the evidence of Bogan, 2003; California 5.4 14.4 winter. Hibernate solitarily or WNS Reeder, 1949; myotis in small groups. Some roost in Dalquest, 1947 caves, mines in summer. F 7.9 Corynorhinus to Hibernate in the northern part rafinesquii No Jones, 1977; 13.6 of range, and either hibernate evidence of Lynch and or goes into extensive torpor Rafinesque‘s WNS Jones 2003 M 7.9 in the southern part. big-eared bat to 9.5 Females form maternity colonies in caves/mines C. townsendii during the summer. In winter, Kunz and both sexes hibernate in caves. No 5 to 8.9 to Martin, 1982; Townsend‘s 86 to 93% N Arouse frequently. Prefer evidence of 13 9.4 Clark et al., (Ozark) cold, thermally stable areas WNS 2002 big-eared bat over warm areas. Move between neighboring caves. Roost solitarily.

Observed roosting in caves, mines, hollow trees, houses, Lasionycteris under bark in winter. Thought noctivagans No 8 to 1 to 13, to hibernate in northern parts Kunz , 1982; evidence of 11 5 mean of range, use daily torpor in Pearson, 1962 Silver-haired WNS other parts. Migrate north in bat spring, based on seasonal abundance changes. Sometimes hibernate in caves; more often trees, leaf litter. Saugey et al., L. borealis No 7 to Change roosts often during 1998; Shump evidence of 13 hibernation. Migrate far. and Shump, Red bat WNS Assumed to hibernate in 1982 southern states. M. evotis Use caves, mines, rocks, for Manning and No summer day roosts. Found Jones, 1989; Western 5 to 8 N evidence of hibernating singly in caves, Perkins et al., long-eared WNS mines. 1990 myotis Prefer cool, moist hibernacula. May hibernate 8 Person, 1962; M. keenii to 9 months in northern part No 1.5 to Fitch & 4 to 6 69% Y of range. Hibernate in groups, evidence of 13 Shump, 1979; Keen‘s myotis often mixed species. Roost in WNS Shump, 1993 caves, buildings in the summer. O‘Farrel, 1999; Summer roosts in caves, M. thysanodes No Farrel and 6 to mines, buildings, trees. Some evidence of Studier 1980; 12 migrate short distances. Fringed myotis WNS Rasheed et al., Hibernate in caves, mines. 1995

Migrate locally for seasonal Czaplewski, M. volans habitat shifts. Can fly with No 1999; Warner 5 to low body temperatures, evidence of and Long-legged 10 presumably to delay entry into WNS Czaplewski, myotis hibernation. Hibernate in 1984 caves and mine tunnels. Occasionally use mine tunnels for day roosting. Have been netted year-round in TX, Parastrellus although in much greater No Sidner, 1999; hesperus 2 to 6 numbers in the summer. Has evidence of Farrel and

been hibernated for up to 2 WNS Bradley, 1970 Canyon bat weeks in a lab. May utilize daily or extensive torpor in cold months.

One issue with creating detailed hibernation profiles is that little is known about the precise microclimate preferences of different species. Many studies that note substrate temperatures of cave roosting bats in winter do not record if the bats roosting there are hibernating or just utilizing daily torpor. For example, one early study described the hibernation location of little brown bats as ―cooler parts…drafty places generally avoided.‖ (Twente, 1955). Another issue is that species may employ different overwintering strategies in different parts of their range. Big brown bats living in

Michigan, for example, hibernate while those living farther south in Alabama stay active throughout the winter and only use daily torpor (Dunbar and Brigham, 2010). Even within one region, members of the same species may engage in activities that increase or decrease their risk for WNS transmission. Potential risk factors include clustering, roosting in an area that is within the temperature growth range for Gd, and starting the winter with a lower BMI. The data in Table 1 suggest that most species of hibernating bats in the USA are at some degree of risk and that learning more about the hibernation habits of USA bats would be a useful future endeavor.

Methods

In July 2010, temperature and relative humidity (T/RH) data loggers specifically calibrated for low temperature and high humidity (N.I.S.T. certified TransitempII-RH,

Madgetech, Warner, New Hampshire, USA) were deployed to 14 hibernacula in

Pennsylvania. In addition, loggers were sent to four sites in Tennessee, four sites in

Michigan, four sites in Alabama, and one site in Quebec. To minimize disturbance, data 38 loggers were deployed before bats went into hibernation or when incursions for other reasons were already planned. Data loggers were set to record every 30 minutes. In each hibernaculum, one data logger was placed at the entrance (no more than 100m inside the hibernaculum) and two were placed where bats historically had been observed hibernating in midwinter. Hibernacula that had been devastated by WNS, those that had not been affected, and sites that had some mortality but to which bats were still expected to return were examined. Cavers were instructed to deploy data loggers to hibernacula of four different microclimate types: cold/low relative humidity, cold/ high relative humidity, warm/ low relative humidity, and warm/ high relative humidity. Data loggers remained in the sites until the bats emerged from hibernation in April 2011. The initial plan was to collect them in April and May 2011 for data download.

Twenty-six functioning TRH data loggers were retrieved from caves in Alabama,

Tennessee, Kentucky, Michigan, and Pennsylvania in early April. Data loggers from

Pennsylvania have not yet been analyzed. The original goal was to compare the entrance data logger with a logger in a historical roosting area at each cave, but theft and equipment malfunction meant that only eight hibernacula were used in this analysis.

These include New Mammoth Cave (KY), Cornstarch Cave (TN), Adventure Mine (MI),

Hubbard‘s Cave (TN), Cave Springs Cave (AL), Fern Cave (AL), Key Cave (AL), and

Great Expectations cave (TN). When a hibernaculum had more than one logger in the back, the logger placed by the largest group of hibernating bats was used. If the notes by the cavers who placed the loggers did not suggest which site had more bats, the logger to use was chosen by flipping a coin. Temperature and relative humidity were averaged for

39 each data logger for each month from October through March. The mean coefficient of variation (CV) for temperature and for relative humidity were calculated for each logger for each month in order to determine how microclimatically stable each site was. CV for temperature is energetically important because a torpid bat maintains its body temperature within 1ºC of ambient temperature (Dunbar, 2004). If ambient temperature shows high variance, it would require more energy for a bat to maintain a constant torpid body temperature than if the ambient temperature showed little variance (Ruel and Ayers,

1999).

The data were analyzed with SPSS statistical software. A 6x2 repeated measures

ANOVA was run on temperature, CV for temperature, relative humidity, and CV for relative humidity for all eight hibernacula to test if the microclimate variables significantly changed over the course of the winter (as delineated by months) and to see if entrances showed different patterns than historical roosting areas. Time (October through

March) and location (entrance and historical roosting area) were within subject factors.

When Mauchly‘s test indicated that the assumption of sphericity was violated, degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity. If the repeated measures ANOVA showed significant differences, paired t-tests were run to elucidate the differences.

Results

A 6x2 repeated-measures ANOVA was run on the temperature data. Mauchly‘s test indicated that the assumption of sphericity was violated for time (χ2 = 44.4, p<0.05)

40 and time*location (χ2 = 54.5, p<0.05). Therefore, degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (epsilon = 0.26 for location; epsilon =

0.40 for time*location). The results showed that time, location, and time*location had a significant influence on temperature, F1. 3, 9.0 = 32.63, p < 0.001 for time; F1, 7 = 5.59, p =

0.05 for location; F 2.021, 14.150 = 4.42, p = 0.032 for time*location (See Fig. 8). Paired t- tests revealed that the entrance of the cave was significantly colder than the historical roost in December (t = 2.49, p = 0.042), January (t = 2.60, p = 0.036), and February (t =

2.40, p = 0.048), but not so in October, November, and March.

10 * * * 8

6 bat roost entrance

4 Mean temperature (ºC) temperature Mean 2

0 Oct Nov Dec Jan Feb Mar Time (months)

Figure 8: Monthly mean temperature (+/- SEM) at the entrance versus historical bat roost at hibernacula from October through March. It was significantly colder at the entrances than at historical bat roosts for December (t = 2.49, p = 0.042), January (t = 2.60, p = 0.036), and February (t = 2.40, p = 0.048). The entrances also had greater standard error. Asterisks indicate significant differences between the entrance and bat roost.

A 6x2 repeated-measures ANOVA was run on the CV for temperature data, with time and location as within subject factors. Mauchly‘s test indicated that the assumption

41 of sphericity was violated for time (χ2=126.1, p<0.05) and time*location (χ2 = 132.7, p<0.05). Therefore, degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (epsilon = 0.23 for location; epsilon = 0.23 for time*location).

There was no significant effect of time, location, or time*location on CV for temperature but observed power was low (1-β = 0.20 for time, 1-β = 0.32 for location, and 1-β = 0.19 for time*location) (See Fig. 9). This was surprising, as a graph comparing temperatures at the different locations showed much more extreme oscillations for the logger at the entrance of the cave than at the bat roost area (See Fig. 10). In addition, the entrance data loggers had greater standard error than the historical bat roost data loggers for both temperature and CV for temperature (See Figs. 8 and 9).

6 bat roost entrance 4

CV for tempertature (%) tempertature for CV 2

0 Oct Nov Dec Jan Feb Mar Time (months)

Figure 9: Monthly CV for temperature (+/- SEM) at the entrance versus historical bat roost of hibernacula from October through March. There were no significant differences between the entrance and bat roost for any months, although the entrance had greater standard error than the bat roosts.

entrance

bat roost Temperature (ºC) Temperature

1-Oct 1-Nov 1-Dec 1-Jan 1-Feb 1-Mar 1-Apr

Figure 10: Temperature (ºC) at the entrance versus historical bat roost in Hubbard Cave from 1 October 2010 to 1 April 2011.

A 6x2 repeated measures ANOVA was run on the relative humidity data, with time and location as within subject factors. Mauchly‘s test indicated that the assumption of sphericity was violated for time (χ2 = 57.1, p<0.05) and time*location (χ2 = 30.7, p<0.05). Therefore, degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (epsilon = 0.28 for time; epsilon = 0.47 for time*location). The results show that time had a significant influence on relative humidity, with F1.4, 9.8 =

4.75, p = 0.046. Location (1-β = 0.28) and time*location (1-β = 0.13) were not significant. For both the entrances and historical roosting areas, humidity started high in

October, decreased until December, and increased again through March (See Fig. 11).

100

98 96 94 92 90 bat roost 88 entrance 86 84

Mean relative (%) humidity relative Mean 82 80 Oct Nov Dec Jan Feb Mar Time (months)

Figure 11: Monthly mean relative humidity (+/- SEM) at the entrance versus historical bat roost at hibernacula from October through March. There were no significant differences in mean relative humidity between the entrance versus bat roost for any months.

A 6x2 repeated-measures ANOVA was run on the CV for relative humidity data, with time and location as within subject factors. Mauchly‘s test indicated that the assumption of sphericity was violated for time (χ2 = 57.3, p<0.05) and time*location (χ2 =

45.9, p<0.05). Therefore, degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (epsilon = 0.290 for location; epsilon = 0.381 for time*location).

The results show that time and location had a significant influence on CV for relative humidity, with F1.4, 10.1= 4.95, p = 0.040 for time and with F1, 7= 5.60, p = 0.050 for location. CV for relative humidity was significantly higher for the entrance than for historical bat roosts. Specifically, paired t-tests revealed that CV for relative humidity was significantly higher for the entrance than historical bat roosts for October (t = -2.74,

44 p = 0.029), November (t = -2.40, p = 0.047), and February (t = -2.41, p = 0.047). It was still higher at the entrance, although not significantly so, in December, January, or March.

Time*location was not significant (See Fig. 12). A graph of the relative humidity for one cave, Hubbard‘s Cave, from 1 October 2010 to 1 March 2011 showed this relationship

(See Fig. 13).

0.12 *

0.1 * * 0.08

0.06 bat roost 0.04 entrance

0.02

CV for relative (%) humidity relative for CV 0 Oct Nov Dec Jan Feb Mar Time (months)

Figure 12: Monthly CV for relative humidity (+/- standard error bars) at the entrance versus historical bat roost at hibernacula from October through March. RH CV was significantly higher for the entrance than the historical roost in October (t = -2.74, p = 0.029), November (t = -2.40, p = 0.047), and February (t = -2.41, p = 0.047). Asterisks indicate significant differences between the entrance and bat roost.

entrance

bat roost Relative humidity (%) humidity Relative

1-Oct 1-Nov 1-Dec 1-Jan 1-Feb 1-Mar 1-Apr

Figure 13: Relative humidity (%) at the entrance versus historical bat roost in Hubbard Cave from 1 October 2010 to 1 April 2011.

Discussion

The change in cave temperature over the course of the winter and the differences between the entrance and historical roost areas were, for the most part, consistent with my hypotheses. Although I did not specifically predict that temperature differences between the entrance and the historical roost would be significant from December to

February but not in October, November, and March, these results were not surprising.

The mean temperature of a cave can be loosely predicted by surface temperature of the surrounding area over the course of a year (mean annual surface temperature, or

‗MAST‘) (Perry, 2010). Spring and autumn months are closer to the average temperature of a region than winter months are. The internal temperature of a cave does not change as quickly as the entrance temperature, so the steeper decrease in temperature from

November to December for the entrance of the cave was consistent with its greater

46 exposure to environmental conditions. The difference between the temperature at the entrance of the cave and the historical roost also is influenced by properties of the entrance. For caves with multiple entrances at different elevations, upper cave entrances are generally warmer than lower cave entrances (Badino, 2010).

The variability (as indexed by CV) of recorded temperature was not significantly different between the entrance and historical roost. This was not consistent with my hypothesis that the historical root sites in a hibernaculum are more thermally stable. I predicted that temperature would have more extreme fluctuations at the entrance of a hibernaculum than at the historical roost of a hibernaculum, which appears to be the case in Fig. 10. One study that placed temperature loggers at the entrance of a cave and multiple locations inside the cave found that over the course of a year, internal cave temperature was more stable than the temperature at the entrance (Dominguez-Villar et al., 2010). One explanation is that TRH entrance loggers were not deployed to uniform locations. The exact placement of a logger depended on if the site was gated, entrance morphology (e.g., a sinkhole that cavers have to repel down versus a walk-in tourist cave), and where cavers deploying the loggers judged was the least likely place for the logger to be stolen. The exact location of a TRH logger in the back of a cave also may have influenced temperature CV. The biggest factor was likely cave morphology. Internal morphology can create air traps, making warm and cold pockets throughout the cave and air flow can shift temperature throughout the winter (Badino, 2010).

In my dataset, humidity started high in the fall, dropped in winter, and increased again in spring for both the entrance and historical roost of hibernacula. While it

47 appeared that the historical roosts had consistently higher levels of humidity than the entrances did (Fig. 11), they were not statistically. These data were not consistent with my prediction that traditional roosting areas are more humid than the entrances of hibernacula, but the power was low different (1-β = 0.28 for location and 1-β = 0.13 for time*location). RH CV was significantly higher for the entrance than the historical roosts in October, November, and February, which supported my hypothesis that the historical roost of the cave is more microclimatically stable (at least with regards to humidity) than the entrance.

These data indicate that moving to the entrance of a hibernaculum, as WNS- affected bats do, may provide some thermal benefits. Hibernating at colder temperatures is less energetically costly than hibernating at warmer temperatures, so moving to the entrance of a hibernaculum could be a last-resort energetic strategy by bats that have severely depleted fat reserves from WNS (Humphries et al., 2002; 2005). However, other studies show that the entrances of hibernacula are more thermally variable than deeper in the caves, suggesting that bats that seek colder temperatures may spend more energy trying to maintain a steady body temperature during extreme temperature fluctuations

(Boyles and McKechnie, 2010). One study found that in March, subadult Daubenton‘s bat (Myotis daubentonii) weighed significantly less than adults and roosted in colder areas close to the entrance than adult bats did. It also found that subadults roosted in areas of higher humidity (Kokurewicz, 2004). These subadults were more likely to starve to death before the end of hibernation, suggesting that they moved closer to the entrance to minimize energetic costs.

However, past studies on WNS-affected bats suggest that roosting at a colder temperature may not be the best energetic strategy. WNS-affected bats arouse more frequently than unaffected bats (D.M. Reeder, in prep). WNS-affected bats may fare better at warmer temperatures, as these require a lower cost for arousals (Humphries et al., 2002; Humphries et al., 2003; Dunbar, 2004; Dunbar and Tomasi, 2006; Boyles et al.,

2007; Utz et al., 2007; Matheson et al., 2010). A mathematical model by Boyles and

Willis (2010) supported the hypothesis that WNS-affected bats provided with warm areas to roost in during arousal bouts would have increased survivorship over those who roost at 2°C.

Although past studies of cave microclimate have compared the microclimate at the entrances of caves to internal areas, this is the first study to compare traditional roosting areas of bats with the zone where they relocate when they are WNS-affected. A follow-up study on these data could be to compare the results from these hibernacula with hibernacula that have been affected by WNS. TRH dataloggers from WNS-affected sites in Pennsylvania are yet to be analyzed. These data can be compared to unaffected sites to determine if hibernacula that are below the ideal temperature range for Gd growth (5º to

14ºC (Gargas et al., 2009)), and that have low levels of humidity will have fewer WNS- affected bats and bats whose health is less impacted. Additional attributes of individual sites, such as cave morphology and which species are present, would be useful to incorporate into future analyses. Understanding the relationship between hibernacula microclimate and prevalence and progression of the disease in WNS-affected bats is a key to predicting which hibernacula are most likely to be affected next.

STUDY 2: THERMAL PREFERENCE OF BATS

Background and hypotheses

Because the results from the first study showed that there were microclimatic differences between the entrances of hibernacula and historical roosting areas of bats, the goal of this second study was to assess if WNS-affected bats were moving to the entrances of hibernacula to utilize these differences. Individual microclimate preferences of bats from the entrance of a WNS-affected hibernaculum versus bats from historical roosting areas of a WNS-affected hibernaculum were compared in the first year of this study. I hypothesized that in a temperature choice apparatus bats from the entrance of a

WNS-affected hibernaculum would choose to hibernate at colder temperatures than bats from historical roosts of the hibernaculum. I next assessed the individual microclimate preferences of bats from a first year WNS-affected hibernaculum displaying physical signs of WNS versus bats that lacked physical signs of WNS. I hypothesized that bats displaying physical signs of WNS would choose to hibernate at colder temperatures than presumed unaffected bats. I tested microclimate preference by placing bats individually in a microclimate gradient chamber for several hours, which allowed them to choose at which temperature they wanted to hibernate.

Methods: WNS-affected bats from the entrance vs. historical roosting areas

The individual microclimate preferences of bats from a WNS-affected site were tested in February 2010 to see if bats were moving to the entrances of hibernacula for thermal benefits. A total of 30 WNS-affected bats (15 roosting at the entrance of the cave and 15 roosting far back where bats have historically been observed to roost) were collected from the Woodward Cave hibernaculum in Pennsylvania and transported to

Bucknell University. Five bats were collected per each of six trips. Each bat was removed from it roost, had standard measurements taken, and was fitted with a WeeTag Lite temperature datalogger (Alpha Mach Inc, Mont-St-Hilaire, Quebec, Canada) to track its body temperature every five minutes. The substrate temperature where each bat was roosting was recorded with an infrared thermometer (Extech; Waltham, MA). During transport to Bucknell

University, bats were held in individual small paper bags (ULINE; S-

115358 1# Kraft

Grocery Bag) that are standard use in bat research. During Figure 14: Microclimate chamber. A bat was placed in the chamber and the lid was closed so that the box was dark. The bat could then crawl transport bats were kept on the mesh bottom or hang on the cloth-lined sides and ceiling to hibernate at its preferred temperature. euthermic at

51 approximately 28oC, near their thermoneutral zone (Willis et al., 2005; Boyles and Willis,

2010), to assure that they would not expend extra energy. Upon arrival, each bat was removed from its paper bag and placed in a ‗microclimate chamber‘, or ‗thermobox‘, in which a 2oC to 12oC temperature gradient had been set up. The microclimate chamber was a highly modified version of one used by Boyles et al. (2007) (See Fig. 14). Five microclimate chambers were built and placed in a walk-in cold room in the Bucknell

University biology building so that five bats could be tested at once. The temperature gradient in all microclimate chambers was verified over several weeks before bats were tested in them. Each bat remained in the chamber for 12 hours, at which time the location of the torpid bat and the substrate temperature it chose were noted. After the bats were removed from all five chambers, they were returned to Woodward Cave and the next group of 5 was collected. Although the original plan was to test bats from this cave in late spring in addition to in the winter, this site was severely impacted by WNS and there were not enough bats remaining in the cave in the late spring to run another round of testing.

Results: WNS-affected bats from the entrance versus historical roosting areas

Two bats, one from each group, were not included in the analysis due to equipment issues. There were no significant differences between bats from historical roosts (n=14) and the entrance bats (n=14) for the following variables: initial BMI, post- testing BMI, change in BMI, the length of time to pick a stable torpid temperature, the presence of a second arousal bout, the length of time of time before a second arousal

52 bout, the total percentage of time aroused, and mean body temperature. There was a significant difference in the roosting temperatures in the cave of the entrance versus historical root bats (t = 7.31, p < 0.001), but there was no significant difference in the roosting temperature bats chose in the thermobox (See Fig. 15).

(14) (14) * Methods: WNS-affected versus (14) presumed unaffected bats

(14) The individual microclimate

preferences of bats from a first-

year WNS affected site were

Figure 15: Temperature preferences of WNS bats from tested. Thirty bats from Snowtop the entrance versus historical roosts of a cave. WNS- infected bats from the entrance of the cave roosted at Mushroom Mine were tested significantly different temperatures in the cave than bats from historical roosts (t=7.31, p < 0.001, but there were no from 16 to 25 February 2011. To significant differences in the temperature the groups chose to hibernate at in the thermobox. Bracketed numbers are assess WNS status, each bat was sample sizes. Asterisks indicate significant differences. checked for physical signs of

WNS during processing. This included visual examination for fungal growth on the muzzle and forearms, as well as examining the wings under UV light. Gd fluoresces as yellow under UV light, so examining bat wings under UV allows for an in-field analysis of WNS status (J. Gumbs et al., in prep). Bats that fluoresced and/or had white fungal growth were counted as WNS-affected. Those with neither were counted as presumed unaffected, although is possible they were early stage infected. A similar protocol to the entrance versus historical roost study was used, except that each bat was individually

placed in a thermobox for 36 hours to assure that deep hibernation was achieved. In

addition, the thermoboxes were modified so that they could be transported and set up in

the field. This minimized the stress of transport for the bats. A cooling plate and

temperature feedback regulator also were installed at the opposite end of the thermobox

from the heat tape, allowing the thermobox to maintain a 2oC to 12oC gradient regardless

of the outside temperature (See Fig. 16).

Figure 16: Modified microclimate chamber. A cold plate was installed at the opposite end of the aluminum plate from the heat tape so that the thermobox could be used at a variety of ambient temperatures. A rheostat was attached so that the thermobox could self-regulate to maintain a 2ºC to 12ºC temperature gradient regardless of fluctuations in external temperatures.

Results: WNS-affected versus presumed unaffected bats

A univariate ANOVA was run on WNS affected (n=8) versus presumed

unaffected (n=6) bats with thermobox substrate temperature as the dependent variable,

WNS status as a fixed factor, and initial BMI and percent time torpid as covariates. There

were no significant differences between the two groups.

Discussion

The results of the thermobox studies did not support my hypotheses. The data from the study on bats roosting in historical locations at the back of hibernacula versus those roosting at the entrance indicated no differences in the selected roost temperature. It is thus possible that, in affected caves, bats are not moving to the entrance of the cave for thermal benefits. Rather, they may be prematurely staging to emerge from the cave in the spring. However, an alternate explanation is that the 12-hour testing period was too short for the bats to reach deep torpor (Thomas et al., 1990; Tuttle, pers. comm.). Nevertheless, the warmer temperature selected by both groups of bats would allow the bats to arouse to euthermic temperatures using less energy than if they selected a colder temperature

(Humphries et al., 2002; Dunbar and Tomasi, 2006; Utz et al., 2007; Boyles et al., 2007).

In order to correct for the potential effect of only hibernating bats for 12 hours, in the next thermobox experiment, bats were left in the boxes for 36 hours. In this experiment, the thermal preferences of bats with visible fungus and/or UV fluorescent evidence of skin infection compared to bats with no visible evidence of infection were tested. There were no significant differences in thermal preferences between these groups. The precise progression of WNS in these bats was unknown, so it may be that the bats without visible signs of WNS were still infected or that early versus later stage infection does not correlate with differences in temperature preference. Unfortunately, although the original sample size of this study was 15 bats per group, equipment problems resulted in a sample size of only 8 WNS-confirmed bats and 6 bats with no visible infection. This likely limited our ability to detect differences between the groups.

In addition, it is possible that little brown myotis do not respond the same way to thermobox testing as big brown bats. My study was modeled after that of Boyles et al.

(2007), in which big brown bats were tested in a similar thermobox and chose significantly different temperatures in relation to BMI. Additionally, Musante et al. (in prep)‘s recently completed study of big brown bats, using my thermoboxes, found that the range bats chose to roost from was 0.7ºC to 11.3ºC, with a mean of 6.8ºC ± 2.4.

Although thermoboxes are a useful tool for testing roosting temperature preferences in big browns, it seems that little brown myotis does not do well in such a testing situation.

This likely reflects natural differences in roosting preferences and behavioral tendencies between little brown myotis and big brown bats. Little brown myotis in my study consistently roosted on the walls and in the corners of the thermoboxes, while the big brown bats in Musante‘s study roosted on the floors, wall, and ceiling. In the wild, little brown myotis cluster and roost in crevices and big brown bats hang solitarily in exposed locations. A future study that narrowed the thermoboxes to a width more natural for little brown moytis would elucidate if the results in this study are valid.

STUDY 3: THE ROLE OF MICROCLIMATE IN SURVIVABILITY

Study background and hypotheses

Hibernacula microclimate plays a significant role in how bats budget their energy throughout hibernation and if they even survive hibernation. The goal of this study was to determine the impact that microclimate has on the progression and rate of mortality of

WNS. WNS-affected and presumed unaffected bats were hibernated at different temperatures and humidities. Each bat‘s body temperature was recorded over the course of hibernation to document its arousal and torpor patterns. Because fungi prefer damp conditions and Geomyces destructans (Gd) grows best between 5 and 14ºC (Gargas et al.,

2009), I hypothesized that WNS-affected bats housed at colder temperatures would exhibit a slower progression of the disease and increased survival rates over those housed in the warmer environmental chambers. I further hypothesized that WNS-affected bats housed at colder, drier temperatures would fare better than those housed at warmer, more humid temperatures. Bats affected with WNS have been shown to have altered torpor and arousal patterns (Reeder et al., in prep), and the influence of hibernacula temperature on these patterns is unknown. The second goal of this study was to record the body temperature of bats throughout the duration of hibernation to examine the relationship between WNS, hibernacula temperature, and thermal patterns. I hypothesized that WNS bats would have more frequent arousal bouts than presumed unaffected bats.

Methods: Year 1, the role of temperature

Sixty presumably unaffected and 60 WNS-affected little brown myotis from both

WNS-affected and unaffected sites were collected from hibernacula in Pennsylvania and transported to the Bucknell University Bat Vivarium in January 2010. Bats were taken from hibernacula, had standard measurements taken, were fitted with WeeTag body temperature trackers (Alpha-Mach, Quebec, CA) and transported back to Bucknell

University. During transportation bats were held in individual small paper bags placed within a portable refrigerator maintained at 4ºC. Upon arrival, bats were induced to

57 hibernate by transferring them into darkened environmental chambers in the animal facilities. Twenty healthy bats and 20 affected bats were placed into each chamber (one chamber each set at 4ºC, 7ºC, and 10ºC) to see how hibernaculum temperature affected survival rate. At this time of year (with sufficient body fat) bats will enter hibernation in response to low ambient temperatures. Within the temperature-controlled environmental chambers (Conviron; model E8; Winnipeg, Manitoba, CA), the bats were placed in a wire-mesh cage (46 cm x 46cm x 61cm); one for presumed unaffected bats, one for

WNS-affected bats) with humidity maintained at or near saturation (similar to what they are exposed to in their natural environment). Although it is possible that unaffected bats could have become infected with WNS, Gd spores are not frequently spread via air and the mesh cages were not immediately next to each other. Water dishes were mounted in the mesh cages so bats could drink ad libitum. Hibernating bats can be successfully housed under these conditions for 5-6 months (their normal period of hibernation). Every week the environmental chambers were checked for mortality and dead bats were removed.

Statistical analyses were run with SPSS statistical software. Although all of the bats in this study died, checking the environmental chambers weekly gave a relative death date and survival could thus be calculated using a Cox regression.

Results: Year 1, the role of temperature

Although 120 bats were collected for the study, the final numbers used in the analysis were as follows: n=19 for 10ºC unaffected, n=16 for 10ºC WNS-affected, n=19

for 7ºC unaffected, n=16 for 7ºC WNS- Table 2: Variables in the final Cox regression model for survival. WNS status, temperature the bats were housed at, and WNS status X sex were all significant affected, n= 21 for 4ºC unaffected, and predictors of survival in the year 1 temperature study.

n=17 for 4ºC WNS-affected. Because Effect Chi-Square P-value WNS status* 11.70 <0.001 almost all of the WeeTags failed, I could Sex 0.10 0.75 WNS status X sex* 4.26 0.04 not include any thermal data in the Temperature* 11.17 0.004 BMI initial 3.07 0.08 analysis. Rather, a Cox regression was run on the following variables for all of the bats

(n=108): WNS status, environmental chamber temperature, sex, initial BMI, and death

date (See Table 2). A Cox regression is a survival analysis that can include continuous

variables. The output is read in terms of hazard ratios, or what is the risk that a bat with

certain characteristics will die before a bat with different characteristics (See Table 3). A

hazard ratio close to 1.0 indicates that the two groups did not have significantly different

chances of dying.

Table 3: Hazard ratios for the year 1 temperature study, as calculated from a Cox regression. A hazard ratio of 1.986 indicates that bats housed at 7ºC had a 198.6% higher risk of death than bats housed at 4ºC. .Parameter Group with higher Hazard 95% Confidence risk of death ratio interval lower upper Bats housed at 7ºC No significant 0.872 0.537 1.416 vs. bats housed at 10ºC difference Bats housed at 7ºC Bats housed at 7ºC 1.986 1.204 3.274 vs. bats housed at 4ºC Bats housed at 4ºC Bats housed at 10ºC 2.276 1.36 3.81 vs. bats housed at 10ºC WNS male bats WNS female bats 0.468 0.253 0.866 vs. WNS female bats Unaffected male bats No significant 1.090 0.647 1.837 vs. unaffected female bats difference Unaffected female bats WNS female bats 0.152 0.080 0.287 vs. WNS female bats Unaffected male bats WNS male bats 0.353 0.195 0.641 vs. WNS male bats

Bats with WNS had significantly lower survival than unaffected bats (χ2 = 11.70, p < 0.001). BMI did not have a significant impact on survival, nor was BMI significantly different between WNS-affected and unaffected bats. Temperature had a significant effect on the survival of bats (χ2 = 11.17, p = 0.004) (See Fig. 17). Bats held at 7C had nearly two times (1.986, 95%CI 1.204, 3.274) the risk of death as bats held at 4C. Bats held at 10C were over 2.25 times (2.276, 95% CI 1.36, 3.81) as likely as bats held at 4C to die. There was no difference in hazard rates for bats held at 7C or 10C (95% CI

0.537, 1.416).

Figure 17: Cumulative survival by WNS status and temperature. The graph on the left represents WNS-affected bats. WNS-affected bats housed at 4ºC had exactly the same mortality as WNS bats housed at 10ºC, so the lines overlap exactly on the graph. The graph on the right represents unaffected bats. Temperature and WNS-status played a significant role in survival in Year 1. Bats with WNS had significantly lower survival than unaffected bats (Cox regression; χ2 = 11.70, p<0.001). Bats housed at 7ºC or 10ºC had significantly higher survival than bats housed at 4ºC (Cox regression; χ2 = 11.17, p = 0.004). Numbers in brackets are sample sizes. There was a significant interaction between site and sex (χ2 = 4.26, p = 0.04) (See

Fig. 18). Among male bats, unaffected bats had approximately 35% the risk of death as did WNS-affected bats (95% CI 0.195, 0.641). Among female bats, unaffected bats had

60 approximately 15% the risk of death of WNS-affected bats (95% CI 0.080, 0.287).

Among unaffected bats, there was no difference in risk of death between male and

healthy female bats (95% CI

0.647, 1.837). Among WNS-

affected bats, the risk of death for

females was 2.14 times higher

than that for males, even though

female bats had a significantly

higher initial BMI than male bats

Figure 18: Cumulative survival by WNS status (t = -2.32, p = 0.023). and sex. Female bats with WNS had a higher risk of death than male bats with WNS in Year 1 (Cox regression; p = 0.04). Numbers in brackets are sample sizes.

Methods: Year 2, the role of temperature and humidity

This experiment was similar to Year 1, except that the role of humidity in survivability also was addressed. Eighty-three bats were collected from a presumed unaffected site in Kentucky and 80 bats were collected from a WNS-affected site in western Pennsylvania on 15 December and 21 December 2010, respectively. Although collecting bats from similar geographic regions would have been preferred, there were no

WNS-unaffected hibernacula in Pennsylvania available to use. Bats were transported in individual muslin bags in coolers kept at ~24ºC with soaked sponges in the bottom to maximize humidity. Upon arrival at Bucknell University, each bat was dry swabbed on one wing to test for PCR presence of Gd. Each bat was then weighed, sexed, had standard

61 measurements taken, and was fitted with a BUTT (Bucknell University Temperature

Tracker) data logger to track its body temperature. Bats were then placed in a wire-mesh cage (46 cm x 46cm x 61cm); one for healthy bats, one for affected bats) in their appropriate environmental chambers. Each wire-mesh cage included a water device so that bats could drink ad libitum. Twenty WNS-affected bats and 20 presumed unaffected bats were housed at each of the following four conditions: 4ºC at 90% relative humidity

(RH), 4ºC at 60% RH, 10ºC at 90% RH, and 10ºC at 60% RH. Because mortality was high the first winter, possibly from frequent disturbances, bats remained undisturbed until

23 March 2011. Dead bats were removed and live bats were allowed to continue to hibernate until 4 April 2011, when all survivors were weighed, had temperature data loggers removed, and were banded and integrated into the Bucknell University captive colony. Statistical analyses were run with SPSS statistical software.

Analyzing temperature data loggers:

Temperature data loggers were downloaded and duration, time, and average temperature of torpor bouts and arousal bouts, as well as the date of last arousal bout, were noted. The method for measuring the start of an arousal bout is not standardized across bat or squirrel literature. Definitions may be as vague as ―a sudden increase in temperature‖ (Dunbar and Tomasi, 2006). For this study, torpor was defined as when the bat‘s body temperature was below 10ºC less than the maximum arousal temperature

(torpor < Tmax – 10), i.e. a bat whose maximum arousal temperature was 24ºC would be noted as torpid if its body temperature was at 13.9ºC or below. The accuracy of the

62 temperature data loggers was ascertained by running twelve through a one week temperature test to determine if there was a delay in when a bat started to change its body temperature and when the temperature data logger measured that change. The test results showed that temperature data loggers accurately measured temperature and there was not a delay in their perception of temperature, making their results accurate.

Results: Year 2, the role of temperature and humidity

Due to serious equipment malfunction, only bats housed in the 4ºC 90% RH and

10ºC 90% RH environmental chambers were included in the analysis. Because I did not want to risk disturbing more bats than necessary to get equal sex ratios, sex was too heavily male-biased to include as a variable in the analysis. Out of 163 bats brought in to captivity, only 38 were female (22 WNS-affected and 16 unaffected). Therefore, the relationship between only the following variables was analyzed for all bats (n = 80): temperature, WNS status, and initial BMI. A univariate general linear model was run with BMI as the dependent variable and WNS-status and temperature as the fixed variables in order to describe the relationship between these three variables. WNS- affected bats had significantly lower BMI than presumed unaffected bats (univariate general linear model, F1,76 = 17.6; p < 0.001) (See Fig. 19).

(40) (40)

Figure 19: BMI by WNS status. WNS-affected bats started with significantly lower initial BMI than unaffected bats in the year 2 survival study (univariate general linear model, F1,76 = 17.6; p < 0.001). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Numbers in brackets are sample sizes.

20 Mortality (%)Mortality 10

0 4°C WNS 4°C 10°C WNS 10°C (20) unaffected (20) unaffected (20) (20) Temperature and WNS status

Figure 20: Percent mortality by temperature and WNS status. In the year 2 survival study, WNS-affected bats had significantly higher mortality than unaffected bats, regardless of the environmental chamber temperature they

were housed at (univariate general linear regression; F1,76 = 5.19, p = 0.026). Numbers in brackets are sample sizes.

A binary logistic regression was run to analyze how these variables predicted mortality

(defined as whether a bat lived or died). BMI initial was the only significant predictor of mortality. Bats with a higher BMI survived longer than those with a lower BMI (binary logistic regression; Wald‘s χ2 = 11.39, p < 0.001) (See Fig. 21).

(40) (40) Figure 21: BMI and survival status. BMI was the only significant predictor of survival in the year 2 survival study. Bats that died were more likely to have a lower BMI than bats that survived (binary logistic regression; Wald‘s χ2 = 11.39, p < 0.001). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Boxes designated by the same letter are significantly different from each other. Numbers in brackets are sample sizes.

It was surprising that WNS status did not have a significant influence on mortality in this model. A univariate general linear model run with mortality as the dependent variable and WNS-status and temperature as the fixed variables showed that significantly more

WNS-affected bats died (F1,76 = 5.19, p = 0.026).

There were thermal data for a subset of bats (n=63 total; n=13 unaffected bats at

4°C, n=13 unaffected bats at 10°C, n=19 WNS bats at 4°C, and n=18 WNS bats at 10°C) whose temperature dataloggers functioned. Thermal variables, including mean torpor bout length, mean torpid temperature (Ttorpid), mean euthermic temperature (Teuthermic), and Teuthermic - Ttorpid, were incorporated into the model. Average arousal bout length was

66 not included in the analysis because temperature dataloggers were programmed to read every 30 minutes and obtaining an accurate measure of arousal bout length at that interval is questionable (Reeder et al., in prep). Past studies have shown that WNS status and hibernaculum temperature impact the thermal choices bats make. A univariate general linear model was run on each thermal variable, with the thermal variable as the dependent variable and WNS status and temperature as fixed factors. When Levene‘s test for equality of variance showed unequal variance, two-sample t-tests with correction for unequal variance (and a Bonferroni correction if necessary) were used.

There was no significant relationship between torpor bout length and temperature and/or WNS status. WNS- affected bats had a significantly higher Ttorpid than did unaffected bats at 4°C (t = 7.46, p < 0.001) and at 10°C (t = 5.72, p < 0.001) (See Fig.

22).

Figure 22: Torpid body temperature by WNS status and environmental chamber temperature. WNS-affected bats had a significantly higher mean torpid

body temperature (Ttorpid) than did unaffected bats at 4°C (two sample t-test; t = 7.46, p < 0.001) and at 10°C (two sample t-test; t = 5.72, p < 0.001). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Boxes designated by different letters are significantly different from each other. Numbers in brackets are sample sizes.

WNS-affected bats had a significantly lower Teuthermic at 4ºC than did unaffected bats

(two-sample t-test with Bonferroni correction; t = -5.47, p = 0.002) but there was no significant difference between the groups at 10°C. WNS-affected bats had a significantly higher Teuthermic at 10ºC than at 4ºC (two-sample t-test with Bonferroni correction; t =

2.84, p = 0.022), while unaffected bats showed the opposite pattern (two-sample t-test with Bonferroni correction; t = -2.72, p = 0.022) (See Fig. 23).

a c

° ° ° °

Figure 23: Euthermic body temperature by WNS status and environmental chamber temperature. WNS-affected bats had a significantly higher euthermic

body temperature (Teuthermic) at 10ºC than at 4ºC (two-sample t-test with Bonferroni correction; t = 2.84, p = 0.022), while unaffected bats showed the opposite pattern (two-sample t-test with Bonferroni correction; t = -2.72, p = 0.022). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Boxes designated by different letters are significantly different from each other. Numbers in brackets are sample sizes.

This meant that WNS-affected bats had significantly smaller Teuthermic - Ttorpid than did unaffected bats (univariate general linear model; F1,59 = 43.37, p < 0.001) (See Fig.

24).

Figure 24: Euthermic minus torpid body temperature (Teuthermic - Ttorpid) by WNS status and environmental chamber temperature. WNS-affected

bats had significantly smaller Teuthermic - Ttorpid than did unaffected bats

(univariate general linear model; F1,59 = 43.4, p < 0.001). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Numbers in brackets are sample sizes.

The incorporation of thermal variables— Teuthermic - Ttorpid and mean torpor bout length—into the binary logistic regression changed the model slightly. Initial BMI

(binary logistic regression; Wald‘s χ2 = 8.60, p = 0.003) and torpor bout length (Wald‘s

χ2 = 13.94; p < 0.001) became the two significant predictors of survival. Bats that survived had longer torpid bouts and a higher BMI than bats that died (See Fig. 25).

(31) (32) Figure 25: Mean torpor bout length and survival. In Year 2, torpor bout length and BMI were the two significant predictors of survival in a binary logistic regression. Bats that survived were significantly more likely to have longer torpor bouts than bats that 2 died (binary logistic regression; Wald‘s χ = 13.94; p < 0.001). Boxes represent the first and third quartiles, the line within the box indicates the median, whiskers mark 1.5*interquartile range, and circles indicate outliers. Numbers in brackets are sample sizes.

It was surprising that WNS status was not a significant part of the final model because unaffected bats had increased torpor bout length and higher BMI than WNS- affected bats. However, BMI and torpor bout length have been shown in past studies to correlate with each other. A general linear model was run with dependent variable BMI, covariate mean torpor bout length, with fixed factors WNS and temperature. (See Fig.

26). Torpor bout and BMI did not significantly covary, but the observed power was low

(1-β = 0.094).

Figure 26: Mean torpor bout length and BMI. In Year 2, torpor bout length (TBL) and BMI were the two significant predictors of survival in a binary logistic regression. TBL and BMI did not significantly covary, but the observed power was low (1-β = 0.094).

Discussion

The results from Year 1 were consistent with my hypotheses that 1) WNS- affected bats housed at colder temperatures would have increased survivability over those housed at temperatures within the Gd growth range and 2) presumably unaffected bats would have increased survivability over WNS-affected bats. However, the data did not entirely support my subsequent predictions. Bats hibernated at 7ºC and 10ºC had nearly two times the risk of death as bats at 4ºC, regardless of WNS status. This suggests that although temperature played an important role in survival in all bats, WNS augmented its importance. Hibernating at warmer temperatures is energetically more costly than

72 hibernating at colder temperatures (McManus, 1974; Webb et al., 1995; Humphries et al.,

2005; Boyles et al., 2007; Boyles and Willis, 2010). Initial BMI did not significantly differ between WNS-affected and unaffected bats, so although WNS-affected bats may have burned through fat more quickly than unaffected bats while in captivity they started at equal mass. The increased fungal growth at warmer temperatures may have augmented energetic effects on the bats, perhaps by increasing the amount of time spent grooming off the fungus (S.A. Brownlee, in prep). Increasing the quantity of pores and glands in the wings invaded by hyphae may in turn inhibit water exchange, increase dehydration, and decrease flight maneuverability (Meteyer et al., 2009; Cryan et al., 2010; Brownlee et al., in prep). Observing behavioral differences between bats hibernating at these different temperatures would be extremely useful in determining why the change in temperature has such an effect on survival. It also would be illuminating to repeat this study and take

UV photographs of wings of bats at different temperatures each week to track rate of fungal growth, although the added handling disturbance would hinder application of the results.

The Year 1 survivability study added a novel piece to the WNS puzzle: the role of sex in survival. This is the first study to show that there are sex differences in WNS survival and that female bats have a greater risk of dying than male bats. Sex distribution between temperature and WNS status groups was equal. Females started with a higher

BMI than males, which should have biased females towards increased survivability.

These results are not congruent with what would be expected sex differences in survival based on differences in energy distribution between males and females. Little brown

73 myotis copulate during the few weeks before hibernation. Females store sperm until they emerge from hibernation, when they ovulate and become pregnant if they have sufficient fat reserves. Healthy female bats start hibernation fatter than males, because female must have sufficient fat reserved upon spring emergence to ovulate and become pregnant. Past studies in other species of bats have found that females lose more mass during hibernation than males do (Johnson et al., 1998; Caire and Loucks, 2010). If female little brown myotis burn energy at a similarly elevated rate, a disease that causes loss of mass would make them much more susceptible than males. However, other studies show that female little brown myotis start and end hibernation with higher BMIs than males

(Jonasson and Willis, 2011; Storm and Boyles, 2011). Because dead bats were removed from the chambers every few days, it was not possible to obtain an accurate BMI at death to determine if WNS-affected females lost more mass than WNS-affected males. WNS- affected bats have smaller fat reserves than unaffected bats and are presumed to die from starvation (Blehart et al., 2009), so it can be presumed that WNS causes females but not males to burn fat at a faster rate.

This does not bode well for the continuation of the little brown moytis species. If females are more severely affected by WNS, as the data in this study suggest, those that survive hibernation are unlikely to have the excess fat necessary to reproduce. Most

WNS-affected species of bats only have one pup per year. Little brown myotis pups have less than a 50% survival (Frick et al., 2010), so removing a significant portion of the female population and inhibiting the ability of most of the survivors to reproduce may make bat populations irrecoverable.

All of the bats in the Year 1 study died. However, there were confounding factors in Year 1. Bats were disturbed every few days to remove dead bats. Several bats were removed from the environmental chamber for twelve hours of additional testing, which likely increased energy loss. All tested groups were disturbed equally, so these extra factors did not bias the results. The relationship between sex and survival, without confounding factors, is a particularly important one to assess in future studies.

It was impossible to run a sex analysis on the Year 2 survivability analysis because only 23% of the bats brought in to captivity were female. When bats were collected for captivity, they were collected in a random fashion to minimize the total number of bats disturbed. The extreme sex bias in Year 2 suggests that either bats were clustering by sex and females were roosting elsewhere at both sites, or that WNS may be causing a decrease in the number of female bats. Past studies have found that sex ratios in

Indiana myotis, eastern red bats (Lasiurus borealis), and Yuma myotis (Myotis yumanensis) may vary at different locations at different times of the year, but there is no evidence that populations show a sex bias (Brigham and Milligan 1993; Ford et al., 2002;

Johnson et al., 1998).

The results from Year 2 were somewhat incongruent with those from Year 1 and did not support my hypotheses. I hypothesized that WNS-affected bats in Year 2 would have shorter torpor bout lengths (more frequent arousals) and lower survivability than unaffected bats, and would have lower survivability at 10ºC than at 4ºC. In Year 1, WNS status, temperature, and WNS*sex were significant predictors of survival and BMI was not, although it was part of the final model. In Year 2, BMI was the only one of these

75 factors that significantly predicted survival. Survival in Year 2 was defined differently from Year 1. It was not possible to look at body temperature logger thermal profiles of individual bats and calculate precise date of death. Instead, survival in Year 2 was defined simply as mortality any time during the winter (if a bat lived or died). WNS status and temperature did not appear to play a significant role in if bats died, but without data on day of death it is impossible to state their role in survivability. It was surprising that WNS status did not have a significant influence on mortality in this model, as 65% of the WNS-affected bats died in each group, while only 30% of the unaffected bats at 4ºC and 50% of the unaffected bats at 10ºC died. In addition, WNS-affected bats had significantly lower BMIs than unaffected bats, which is consistent with a past study

(Storm and Boyles, 2011). A more detailed analysis of the data could clarify these relationships.

When data from the body temperature loggers were included in the year 2 survival analysis, torpor bout length became an additional predictor of mortality.

Survivors had longer torpor bouts (less frequent arousals). Torpor bout length and BMI did not covary, but since the observed power was low the model may not have been able to accurately test their relationship. Although other thermal variables were not significant predictors of mortality, they still were significantly different between WNS-affected and unaffected bats. WNS-affected bats had significantly higher Ttorpid. This is consistent with a past study that found that WNS-affected little brown myotis had significantly warmer body temperatures relative to substrate temperature than unaffected Indiana bats (Storm and Boyles, 2011). Maintaining a higher torpid temperature uses more energy

(Humphries et al., 2002; Dunbar and Tomasi, 2006; Boyles et al., 2007; Utz et al., 2007;

Boyles and Willis, 2010), which may account for the significantly higher initial BMI in unaffected versus WNS-affected bats. WNS-affected bats in my study may have been trying to minimize energy expenditure despite maintaining a higher Ttorpid; they had a significantly smaller Teuthermic - Ttorpid than unaffected bats. In addition, at 4°C, unaffected bats aroused to a significantly warmer euthermic temperature than WNS-affected bats did, but there was no significant difference between the two groups at 10°C. WNS- affected bats housed at 4°C may have aroused to a lower temperature to try to save energy, but it may not have been worth it to do so at 10°C. It is also possible that WNS- affected bats have trouble thermoregulating. Future studies that track body temperature also should incorporate a respirometer to measure oxygen consumption and thus metabolic rate. Comparing thermal data with metabolic data would further our understanding of the physiological changes that WNS causes.

There were confounding factors in the year 1 and 2 survival studies that may have influenced the results. Bats were in the ‗unaffected‘ group were collected each year in

December at supposedly unaffected sites (year 1 from Snowtop Mushroom Mine in

Pennsylvania, year 2 from Kentucky). In each case, by the end of the hibernation season,

WNS-positive bats were identified in those sites. It is therefore possible that the

‗unaffected‘ bats in these studies were actually early stage infected bats. When dead bats were removed from the environmental chamber in Year 2 in March, they were in a state of decomposition that made it impossible to examine them for fungal growth or swab them for PCR confirmation of the fungus.

Another potentially confounding factor in the year 2 survival study was where the study animals were from. The differences between the WNS-affected bats from

Pennsylvania and the unaffected bats from Kentucky could be due to geography rather than Gd. Bats from the Pennsylvania hibernaculum may have been exposed to different pre-hibernation conditions than those in the Kentucky hibernaculum. However, little brown myotis migrate between their summer and winter roosts so there may have been as great of variation in pre-hibernation conditions between individuals at the same hibernaculum as between hibernacula. A past that compared latitudinal differences in behavior did not have congruent results with my study. Dunbar and Brigham (2010) compared thermoregulatory behavior in big brown bats across a latitudinal gradient in

North America. They found that hibernating bats from Michigan were significantly heavier, maintained significantly lower body temperatures during torpor, and had significantly different metabolic rates than bats from Alabama. These are opposite the results that I found when comparing bats from Pennsylvania versus Kentucky, which suggest that there are not consistent regional differences in thermoregulatory behavior.

Studies that compare summer behavior of bats from different latitudes have found that basal metabolic rates do not differ by region and that regardless of ambient temperatures bats will roost at similar temperatures throughout their range (Speakman and Thomas,

2003; Richardson et al., 2009). It would be ideal to repeat this study with bats from more similar latitudes, but I do not think that geographic differences discount the conclusions made.

CONCLUSION

In ecology, the concept of the disease triangle states that three factors—host, pathogen, and environment—must interact in a specific way to allow for disease progression to occur (McNew, 1960). For White-nose Syndrome, the three sides of the triangle are hibernating bats, the fungal pathogen Geomyces destructans, and hibernacula microclimate. The goal of this project was to assess the role of microclimate in WNS susceptibility. These data showed that the temperature at which WNS-affected bats roosted, as modified by their BMI, sex, and torpor patterns, had a great impact on their survival. WNS-affected bats had altered torpor patterns that indicated changes in their energy use, which in turn may have been why they died mid-winter. WNS-affected bats maintain a higher Ttorpid than unaffected bats and in the year 2 study there were not differences in mortality between those housed at 4°C and 10°C. This suggests that artificially altering the microclimate of hibernacula or providing bats with thermal refugia would not be an efficient way to slow the spread of WNS. A future survivability study should experimentally inoculate unaffected bats with WNS in a laboratory setting to see exactly how long it takes from initial exposure to Gd until energy-use changes are evident. In addition, future studies should incorporate flow-through respirometry to calculate metabolic differences between WNS-affected and unaffected bats held at different temperatures.

This project found that there are few detailed studies on microclimate preference of different species of hibernating bats. Winter banding studies in the 1950‘s resulted in such severe mortality that the attitude for the last forty years has been to disturb

79 hibernating bats as little as possible (Tinkle and Patterson 1965; Keen and Hitchcock,

1980; Daan 1980). Studies that compare microclimate at the entrances of caves versus in the back exist in the caving literature, but this is the first study that has specifically examined microclimate in historical roosting sites of bats versus where WNS bats roost at the entrances of caves. It is crucial to examine microclimate in hibernacula that have been infected by WNS and those that have not to tease apart microclimatic differences that can be used to predict which hibernacula are more likely to be infected in the future and how severely moving to the entrance of hibernacula will affect bats‘ energy budget.

The relationship between sex and survival is a particularly important one to assess in future studies. Female bats ovulate and become pregnant if they have sufficient fat reserves upon emergence from hibernation. If they are more severely affected by WNS, as the data in this study suggest, not only are fewer surviving hibernation but those that do may be in too poor of body condition to reproduce. Most WNS-affected species of bats only have one pup per year, so removing a significant portion of the female population and inhibiting the ability of most of the survivors to reproduce could make bat populations irrecoverable.

However, it appears that bat populations in New York have stabilized, which suggests that at least some species may be able to persist at drastically reduced numbers.

Transmission of WNS appears to have a density dependence component, such that less physical contact between bats (in the form of clustering or a low population) is associated with a lower risk of WNS (Wilder et al., 2011). Unfortunately, once populations reach a low enough level that North American bats may survive WNS they may also be below

80 the viable population size and will thus go extinct. A positive outcome for White-nose

Syndrome is therefore unlikely.

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