Effects of White-Nose Syndrome on Bat Diets and Interspecific Competition

Derek Morningstar

A Thesis presented to the University of Guelph

In partial fulfilment of requirements for the degree of Masters of Science in Integrative Biology

Guelph, Ontario, Canada

Effects of White-Nose Syndrome on Bat Diets and Interspecific Competition

Derek Morningstar Advisor: University of Guelph, 2016 John Fryxell, Brock Fenton

Competition is commonly invoked to explain variation in abundance, activity patterns, and resource use, but is difficult to detect in nature. Introduction of white-nose syndrome

(WNS) in bats provides a natural experiment to test the impact of interspecific competition on bat communities. Acoustic monitoring at locations in Southern Ontario showed an increase in activity of Big Brown Bats (Eptesicus fuscus) and corresponding decline in the activity of Little

Brown Myotis (Myotis lucifugus), following the introduction of WNS. Next generation sequencing of bat stomachs and guano in Southern Ontario before and after WNS allowed for the characterization of diet changes of these species. As a function of competitive release, E. fuscus consumed a wider breadth of prey and many of the insect species once consumed by M. lucifugus, including several pest insects. These results suggest that interspecific competition has a detectable effect on bat communities in Southern Ontario.

ACKNOWLEDGEMENTS This work could not have been completed without the contributions, support and assistance from so many individuals. Most importantly, I would like to thank my family, especially my wife Vicky, my kids Owen and Mya and my parents Dave and Carol for tolerating my continued passion for research and my need to work on a “bat’s schedule” with a “bat’s stamina”. I appreciate the guidance and help from John Fryxell, Mehrdad Hajibabaei, Shadi

Shokrolla, Brock Fenton and the members of the Fryxell and Hajibabaei lab. Field assistance provided by Benoit Talbot, Lucas Greville, Alejandra Cebalos-Vasquez, Luke Owens, Al

Sandilands and review and technical advice from Gustavo Betini, Danielle Ethier, Eric McNeil,

Rebecca Viejou. Studies from Elizabeth Clare preceeded this research and laid the foundation upon which to build, along with guidance on methods and interpretation. The processing of

DNA data was conducted through the Hajibabaei lab at the University of Guelph. Allen

Kempert and Al Kurta helped to make connections and find roosts. Lenny Shirose and the

Canadian Wildlife Health Cooperative made bat carcasses available for this study. Golder

Associates Ltd. provided the flexibility to accomplish this work, the connection to pre-existing project data and technical equipment to collect new data. The landowners and data owners of the many acoustic monitoring and roost locations wish to remain anonymous, but their contribution won’t go unrecognized.

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Table of Contents

ABSTRACT ...... ii ACKNOWLEDGEMENTS ...... iii Table of Contents ...... iv LIST OF TABLES ...... v LIST OF FIGURES ...... vi INTRODUCTION ...... 1 METHODS ...... 7 Study system ...... 7

Acoustic Survey of Bat Activity ...... 8

Collection of Guano ...... 9

Collection of Stomachs ...... 11

Next Generation Sequencing Methods ...... 12

Statistical methods ...... 15

RESULTS ...... 17 Acoustics ...... 17

Results of Capture and Tracking ...... 18

Diet ...... 19

Pest Insects ...... 21

DISCUSSION ...... 23 REFERENCES ...... 31 TABLES AND FIGURES ...... 36 Appendix A: Bat Capture and Tracking in Dunnville Results ...... 49 Appendix B: Insects in bat diets that could be identified to the species level ...... 53

LIST OF TABLES Table 1: Direction of change in mean passes per night at each acoustic bat monitoring station ...... 46

Table 2: Species Richness in guano samples, based on the Chao estimator ...... 47

Table 3: Pest Insects Observed in Bat Diets ...... 48

LIST OF FIGURES Figure 1. Extent of confirmed WNS from winter assessment at bat hibernacula as of

September 3, 2014 ...... 36

Figure 2: Map of acoustic monitoring stations ...... 37

Figure 3: Map of roost locations for collection of E. fuscus guano ...... 37

Figure 4: Dunnville bat capture locations and roosts...... 38

Figure 5: Overall mean bat passes per night for M. lucifugus and E. fuscus ...... 39

Figure 6: Changes in mean bat passes per year for M. lucifugus at the Dun station40

Figure 7: Changes in mean bat passes per night for M. lucifugus ...... 40

Figure 8: Changes in mean bat passes per year for E. fuscus at the Dun station ... 41

Figure 9: Changes in mean bat passes per night for E. fuscus ...... 41

Figure 10: Percent richness by order for all E. fuscus roosts and the M. lucifugus roost

(SAND) ...... 42

Figure 11: AOTU's per insect order across E. fuscus roosts and one M. lucifugus roost

(SAND) ...... 43

Figure 12: Rarefaction curves for E. fuscus roosts ...... 44

Figure 13: Mean percent richness of AOTU's by order for stomachs ...... 44

Figure 14: Rarefaction curves for E. fuscus stomachs pre-WNS and post-WNS .. 45

INTRODUCTION Interspecific competition has long been posited as a driving mechanism in the diversification of species (Darwin, 1859) and continues to be an important topic of ecological study (Meyer and Kassen, 2007; Terborgh, 2015). For decades, competitive interactions have been investigated in theoretical and imperical studies and core in the training of ecology and wildlife management (Fryxell et al, 2014). It is described as the interactions between members of two or more different species to obtain essential resources that are in limited supply. This mechanism can be broken into two categories: exploitative competition and interference competition (Park, 1954; Faas and Weckerly, 2010). Interference competition refers to direct conflict between individuals, including aggression of physically excluding the opponent from access to resources. Under exploitative competition, such as the interaction in my study, each species has different means of obtaining the resources without direct combat, such as specialized abilities to pursue prey or access habitat. Exploitative competition is often difficult to study in nature because it can be hard to separate superior strategies of obtaining resources from other environmental factors.

Competition does not always drive one of the competitors to extinction. The Lotka-

Volterra model of competition predicts that it is possible under some conditions for competitors to coexist in nature (Schreiber et al, 2011; Amaresekare, 2002). Competitive coexistence has been demonstrated in bats in Europe (Ashrafi et al, 2011; Arlettaz, 1999) and in Mexico

(Salinas-Ramos et al, 2015). Salinas-Ramos (2015) showed that there is dietary flexibility and niche overlap in bats of the Pteronotus family, and suggested that this could also occur for other insectivorous bats.

Exploitative competition is hard to study in insectivorous bats because there is a dearth of information on the ecology and food selection of these bats, and it is obviously difficult to study competitive interactions by experimentally manipulating abundance of one competitor or the other in the wild. Sometimes, however, a natural experiment can be brought to bear on such problems.

Recent introduction of a novel and devastating disease in eastern North America called

WNS has caused significant declines in some bat species, but not on others (Frick et al, 2015).

These factors provide the opportunity for a natural experiment on interspecific exploitative competition in insectivorous bats.

WNS is caused by an infection of the bat skin by the fungus Pseudogymnoascus

destructans, and results in their death during winter hibernation (Wilcox et al, 2014). It was

first discovered in New York in 2006 and was likely transferred from an unknown source in

Europe (Leopardi et al, 2015). The expansion of areas infected by WNS has been tracked by

the United States Fish and Wildlife Service and the Canadian Wildlife Health Cooperative

(Figure 1). Confirmation of WNS infection is based on the observation of dead or infected bats

during their winter hibernation, but many areas have not been adequately surveyed. In

addition, bats can travel great distances from their winter hibernaculum to their summer

roosting areas (Norquay et al, 2013), which means that the distribution shown in Figure 1 is

likely an underestimate of the actual footprint of the effects of WNS. For this study, I

considered all of Southern Ontario to be within the range of the effects of WNS.

Mortality of hibernating bat colonies ranges from 90 - 100% which could lead to local

extirpation, and some remnant species may not recover to pre-WNS populations in the short

term under any management scenario (Russel et al, 2015). In particular, the Little Brown

Myotis (Myotis lucifugus) was once considered the most abundant and widespread bat in North

America (Harvey et al, 2011), but has been dramatically affected by WNS and may face local

extirpation in some areas (Russel et al, 2015). Alternatively, the Big Brown Bat (Eptesicus

fuscus) is also common in many of the same areas, can contract WNS, but appears to have a

higher survival rate and may have some resistance to the disease (Frank et al, 2014). WNS has

effectively removed one potential competitor from the system in areas affected by the disease.

Clare et al (2014) collected information on the diet of E. fuscus in advance of the effects of

WNS in Ontario, establishing a baseline from which the changes in diet can be detected in

response to the effects of WNS on bat species, and testing the competition theory.

If sympatric species require the same resource, a sudden population reduction of one species allows for a natural experiment to test for the strength of interspecific competition. The competition hypothesis predicts that the loss of one competitor should increase the availability of preferred resources for other competitors and accordingly result in increased population numbers. As a corollary, the competition hypothesis predicts that loss of a competitor should lead to expansion in the diet of the unaffected species.

M. lucifugus and E. fuscus have a similar distribution in North America and have similarities in their life history. Both are insectivorous, roost in trees or buildings in the summer, hibernate through the winter primarily in caves or mines (E. fuscus will also hibernate in buildings) and have few predators (Lima and O’Keefe, 2013). However, there are physiological and ecological differences between these species that may prevent competition from limiting either population. There is a clear difference in the physical size of these two species, with E. fuscus being much larger (Fraser et al, 2007), but differences in wing loading and maneuverability could favor the smaller bat for capturing prey (Kalcounis and Brigham, 1995).

M. lucifugus often prefers to feed over aquatic or wetland areas and sometimes within forest openings, whereas E. fuscus is frequently observed feeding over open fields and agricultural areas (Lacki et al, 2007), more terrestrial and open spaces, suggesting the potential for some partitioning of resources (indicating a competitive interaction) between these species (Mooseman et al, 2012).

Studying the behavior of bats and how they use these resources can be challenging because they emerge at night and normally do not make human-audible sounds. Specially designed acoustic recording devices (bat detectors) have been designed to allow for the recognition of bat vocalizations, often with the ability to identify the species of bat passing the detector. While these detectors cannot be used to assess absolute changes in population size, consistent monitoring over long time periods can provide repeatable measures of relative bat activity at a site, across sites or over time, as an indicator of their relative use of habitats.

Specifically, changes in bat detections can represent changes in relative use of an area, deemed as “relative abundance” for feeding, roosting or commuting and therefore a surrogate for population changes. When bats feed in a particular habitat type, they are likely to feed on insects that are closely associated with that habitat (Aldridge and Rautenbach, 1987) and therefore the loss of bats from a habitat could change the pressures on insect populations.

There is ongoing debate about whether bats specialize on certain insect groups such as

Coleoptera (beetles), certain prey sizes (i.e. bigger is better) or are opportunistic specialists, consuming whichever prey is most abundant, which changes throughout the year. It is often claimed that E. fuscus is more likely to consume hard bodied Coleoptera than other small insectivorous bat species, evidenced by stronger jaw musculature and bite force (Aguirre et al,

2003; Fraser and Fenton, 2007), and by the proportional representation of this order of insects in

4 their diet (Clare et al, 2014; Thomas et al, 2012; Feldhamer et al, 2009, Whitaker and Barnard,

2005; Agosta and Morton, 2003; Carter et al, 2003 but see Brigham, 1990 and Valdez and

O’Shea, 2014). Despite having an apparent affinity for Coleoptera, E. fuscus diets consistently also include prey items of Diptera (flies), Lepidoptera (moths), Ephemeroptera (mayflies),

Trichoptera (caddisflies) and to a lesser extend other insect orders and Arachnida (spiders) (Clare et al, 2014, Long et al, 2013, Mooseman et al, 2012, Feldhamer et al, 2009).

In contrast, M. lucifugus often consume a higher relative proportion of Lepidoptera and

Diptera (Clare et al, 2014; Thomas et al, 2012; Feldhamer et al, 2009; Carter et al, 2003), but still some proportion of each of the five main insect orders above (Mooseman et al, 2012, Clare et al, 2011), and so there is some overlap in the prey that these two bat species are consuming.

Each of these bats consume a wide variety of species within these orders, but the direct overlap of diet at the species level is less well understood.

Bats have been credited on many occasions for providing an invaluable service due to insect control (Tuttle, 2015; Maine and Boyles, 2015; Long et al, 2013). There are many anecdotal accounts of a bat “eating its weight in mosquitos in a night,” and some evidence of mosquito control by bats (Reiskind and Wund, 2009) while other researchers suggest that bats are likely to eat very few mosquitoes in favor of larger, more nutritious prey (Gonsalves et al,

2013). A recent study has successfully excluded bats from crop fields and demonstrated that the insect control from bats does, in fact improve crop growth and quality (Maine and Boyles, 2015), while another study has shown that the apple orchard pests which were expected to be consumed by bats were not actually part of bat diets (Long et al, 2013). The importance of insect control by bats has dramatically heightened due to the advent of WNS in North America and the observed and predicted loss of so many bats in the landscape (Alves et al, 2014; Frick et al,

2010). In other systems, bats are known to consume pest insects of pecans (Brown et al¸2015), walnuts (Long et al, 1998) and cotton (Fredrico et al, 2008). Whether bats consume particular pest insects, have group-level preferences or are generalists, their contribution to the ecosystems they live in is of paramount importance (Kunz et al, 2011). Further research on the specific prey items they eat, the abundance of those prey consumed and how that relates to insect control or ecosystem balance is urgently needed. The loss of one or more species of bats could have a change on the pressures that bats have on insect populations, but modeling this is complicated if there are competitive interactions and an alternate species is compensating for the loss of another.

Insects are not always pests. There are some insects which which provide benefits, such as plant pollination, predation on other insects or parasites that kill other insects. A list of some of these species is provided by the Ontario Ministry of Agriculture, Food and Rural Affairs

(OMAFRA, 2009) and descriptions of some beneficial insects are described in Marshall (2006).

In contrast to the pest hypothesis, if E. fuscus is known to consume beneficial insects then an increase in the abundance of E. fuscus could result in reducing the abundance of beneficial insects.

Traditional diet studies on bats have used morphological identification methods to classify the contents of bat guts or guano (feces), but often are not suitable for species-level classification and some softer-bodied insects are likely undetectable using these methods

(Belwood and Fenton, 1976). The methods were adequate, however, for quantifying the proportion of each identified group within the sample. More recent techniques for diet classification involve next generation sequencing of the guts or guano to amplify the DNA for subsequent comparison with libraries of known species DNA. As those libraries, such as the

Barcode of Life Database (BOLD) and Genbank continue to be developed and improved, so too does the accuracy of next generation sequencing techniques and the use of new frameworks for

DNA metabarcode identification (Fahner et al, 2016).

Exploitative competition theory leads to the prediction that competitive release due to the loss of M. lucifugus, will lead to an increase in the abundance of E. fuscus and expansion in their dietary breadth. Hence, M. lucifugus should be recorded less frequently and E. fuscus should be recorded more frequently following the introduction of WNS, as a result of competitive release.

The competition hypothesis also leads to the prediction that the diet of E. fuscus should expand to include broader species richness, more overlap with prey items that were also consumed by M. lucifugus, and an increase in the frequency of pest insects in the diets of E. fuscus individuals.

METHODS I first assessed the relative activity of bats on the landscape as a measure of their resource use by using bat detectors positioned at 13 locations in Southern Ontario. The survey stations were located within areas which are either known to have been infected by WNS at the time (Figure

2), or just outside the infected area and where both E. fuscus and M. lucifugus are known to exist.

Bats are known to travel several hundred kilometers from winter to summer habitat (Norquay et al, 2013), so all of Southern Ontario was considered to be affected. All of the stations were surveyed before the decline of bats was observed in Ontario (pre-2012) and then sampled again after WNS, and one station had consistent monitoring through all years.

Study system

Although WNS was first confirmed in New York in 2006 and in Ontario in 2009, the decline of bats was not observed until the summer of 2012 (Lesley Hale, pers. comm., Dunnville

7 site (pers. obs.)). Therefore, for the purpose of this study I have characterized pre-WNS as 2011 or earlier. The acoustic monitoring stations were selected from the data that was available based on the habitat type where the detectors had been stationed on previous studies (Figure 2). Guano was collected from locations known to have roosting bats or sites where bats had been found roosting through capture and tracking, but generally occur over a similar geographic region as the acoustic monitoring stations (Figure 3). E. fuscus stomachs were extracted from all suitable bat carcasses submitted to the Canadian Wildlife Health Cooperative at the University of Guelph.

In general, samples were from Southern Ontario, west of the Niagara Escarpment.

Acoustic Survey of Bat Activity

Station Hald was placed outside of a building that was known as a nursery roost for E. fuscus, but as a large building it could also have provided a roost for M. lucifugus. All other stations were placed at or near suspected roosting areas, feeding areas or commuting corridors for bats in a variety of habitat types across the landscape.

Pre-WNS data were collected in 2009-2011 during time periods when bats would be active on the landscape. The study period for each station was replicated with data collected at the same station, post-WNS in 2014. The Dun station was installed in spring of 2009 and remained at the site, recording nightly for all years through 2015.

At each monitoring station, an AR125 microphone (Binary Acoustic Technology ®) was paired with an FR125 recorder (Binary Acoustic Technology ®); collectively called the BAT detector. The BAT detector recorded nightly from at least 30 minutes before sunset to at least 30 minutes after sunrise. It was set to trigger a recording when a sound within the range of 15 to 90 kHz with an intensity of at least 18 dB was detected. When triggered, the BAT detector would

8 continue recording for at least 5 seconds and then stop recording if there were at least 5 seconds of no sounds in this range or a maximum recording length of 15 seconds. Sound files were recorded in wavpack (.WV) format, later converted to wave (.WAV) using a decompression package, and were sorted into a folder for each night of recording (a night includes the following morning). Nights on which all or some of the night was not recorded because of power failure or other circumstances were excluded from further analysis.

The data was filtered using the program SCAN’R (Binary Acoustics Technology ®, version 1.7.3) to remove non-bat files and then converted to WAV format and passed through a second filter program called Scrubber (Sonobat ®, version 5.2), to further remove noise files. A subset of the files removed by both filters were reviewed manually and it was estimated that less than 1% of removed files contained recognizable bat calls, but even these files were very poor quality and likely could not be identified to the species level. Species classification of the files was conducted using the Sonobat NNE package (Sonobat ®, version 3.2.1). The resulting species classifications were tallied by night using the BatData program (Golder Associates Ltd.), and then analyzed using Microsoft Excel and R (R Core Team, 2015).

Collection of Guano

Roosts were identified through contact with bat specialists, bat eviction companies, church managers and through a capture and tracking program in Dunnville. In the Dunnville area where I have the most consistent, long-term acoustic data, no local roosts were known. So a capture and tracking program was initiated to find roosts where bat guano could be collected in this area (Figure 4).

The capture and handling of specially protected wildlife in Ontario (including bats) must be done under an approved Wildlife Scientific Collector Permit (WSCP), with an approved

Animal Care Protocol (ACP), and the activity must be registered with the Ministry of Natural

Resources and Forestry (MNRF) for disturbance to an Endangered Species Act protected species for scientific purposes (17(c) permit). WSCP number 1076739 was issued through the Guelph

District MNRF. The ACP was adopted from the Animal Utilization Protocol (#2917) obtained through the University of Guelph. The activity was registered with the MNRF under

Registration Confirmation Number M-102-5401875496. A permit for scientific studies on

Grand River Conservation Authority (GRCA) property was also granted by the GRCA. All animals were handled carefully and ethically in accordance with these permits. All capture and handling followed accepted WNS decontamination protocols. There was no mortality or severe injury of the bats handled.

The capture program was conducted from July 5 to 12, 2014. Capture events were carried out at Byng Conservation Area (July 5, 2014), the Morningstar Cottage (July 6 to 9,

2014), Dunnville Marsh Area 1 (July 10, 2014), Dunnville Marsh Area 2 (July 11, 2014) and

Rock Point Provincial Park (July 12, 2014). Full netting times, weather and details are listed in

Appendix A (Table A-1).

At each site, I installed three to five mist net sets. These included one, 12 m wide by 8 m high (three nets stacked), one 9 m wide by 8 m high, at least one 6 m wide by 5 m high (two nets stacked) and some single nets (3 m high) of various widths. Netting effort was calculated based on one 6 m wide single net for one hour = 1 net-hour. Total netting effort is listed in Appendix

A (Table A-1). The nets were opened at 30 minutes past sunset to avoid incidental capture of birds and were checked on a 10-minute frequency. Once a bat was found within the net, it was carefully extracted and placed into a paper bag for processing. During processing, I identified the species, sex, age (adult or juvenile), physical size measurements and indicators of health and

10 a bat band (Porzana) of the appropriate size was placed on the forearm of the bat with a unique identification number (Appendix A, Table A-2).

Upon capture of an E. fuscus individual, a VHF radio transmitter was glued to the bat using Skin Bond ® surgical cement. The following day and for at least 3 days after, the bat was located at its roost using the truck-mounted and handheld receivers (Advanced Telemetry

Systems). Once the roost was identified and permission was granted by the landowner, it was added to the list of roosts at which guano samples could be collected.

Once roosts were identified at all locations, paper was placed under the bat roosts at the start of the sampling period (typically the start of each month). In each sampling period, 4 – 20 subsamples were collected at each roost from on top of the collection sheets, taking care not to cross-contaminate between subsamples. New collection sheets were placed for subsequent sampling periods. These subsamples were labeled according the location and period from which they were collected and stored in ethanol at -20oC prior to processing for molecular analysis.

Samples from the E. fuscus roosts in the Cambridge area were pooled (CAMB) because there were not enough samples from each individual roost, and samples from the E. fuscus roosts in

Dunnville were also pooled for analysis (DUNN). The Sandilands roost (SAND), south of

Cambridge was not grouped with other Cambridge roosts because it was for M. lucifugus.

Collection of Stomachs Bat carcasses of several species (including E. fuscus) have been collected from wind farm monitoring projects in Ontario and submitted to the Canadian Wildlife Health Cooperative at the

University of Guelph prior to the beginning of this project. From these samples, 44 E. fuscus were available from 2011 or earlier (pre-WNS), and 46 were available from 2012 to 2014 (post-

WNS). Each of these bats were dissected to extract the stomach and intestine (collectively

11 referred to as stomach contents). The equipment was sterilized between dissections of each bat.

The stomach was placed in ethanol and stored at -20oC until molecular processing.

Next Generation Sequencing Methods

Despite the recent improvements in molecular sampling techniques and the ability for highly accurate species-level classification, there is still debate whether the number of sequences of a particular AOTU obtained within each sample is representative of abundance (Deagle et al,

2013; Pompanon et al, 2012). Therefore, I did not use the number of sequences as an indicator of abundance, but rather quantified abundance based on the “frequency of occurrence” of that

AOTU across multiple samples.

From each guano subsample, the guano was dried in an air circulating incubator set at

56oC. Stomachs were pulverized using a 5.8” drill bit spun at 400 revolutions per minute for a period of 30 seconds in forward and 30 seconds in reverse. A 1.2 mL Lysing matrix tube was filled with guano (approximately 4-8 pellets of E. fuscus, or 10-15 pellets of M. lucifugus depending on pellet size) or stomach tissue and 760 μL of buffer T1 and 75 μL of Proteinase K

(from the NucleoSpin® Tissue Kit). Thereafter, all samples were treated the same. The lysing matrix tube was placed in a shaker at 6.0 m/s for a period of 40 seconds to homogenize and liquefy the sample. The DNA extraction was conducted using a NucleoSpin® Tissue kit

(Macherey-Nagel), following instructions for the standard protocol for human or animal tissue and cultured cells. The final step where pure water was eluted from the filter was conducted using 30 μL of molecular biology grade water heated at 70oC to elute the DNA, rather than 100

μL of buffer BE (as described in the instruction manual). The extracted DNA was then stored at

-20oC until Polymerase Chain Reaction (PCR) and DNA sequencing.

Two mini-barcode fragments within the standard COI DNA barcode region were amplified with two primer sets in a two-step PCR amplification regime (Hajibabaei et al., 2011).

The BR5 fragment (~330 bp) was amplified using the following primers, previously optimized for use with a broad range of arthropod orders: B CCIGAYATRGCITTYCCICG (Hajibabaei et al., 2011), and R5 GTRATIGCICCIGCIARIAC (Gibson et al., 2014). The second fragment

F230 (~230 bp) is at the 5’ end of the standard bar-coding region and is amplified using F

GGTCAACAAATCATAAAGATATTGG (Folmer et al., 1994) and F230_R

CTTATRTTRTTTATICGIGGRAAIGC (Gibson et al., 2015). The first PCR used COI specific primers and the second PCR involved Illumina-tailed primers. The PCR reactions were assembled in 25μL volumes. Each reaction contained 2μL DNA template, 17.5μL molecular biology grade water, 2.5μL 10X reaction buffer (200mM Tris HCl, 500mM KCl, pH 8.4), 1μL

MgCl2 (50mM), 0.5μL dNTPs mix (10mM), 0.5μL forward primer (10mM), 0.5μL reverse primer (10mM), and 0.5μL Invitrogen’s Platinum Taq polymerase (5 U/μL). The PCR conditions were initiated with heated lid at 95°C for 5min, followed by a total of 30 cycles of 94°C for 40s,

46°C (for both primer sets) for 1min, and 72°C for 30s, and a final extension at 72°C for 5min, and held at 4°C. Amplicons from each sample were purified using Qiagen’s MiniElute PCR purification columns and eluted in 30μL molecular biology grade water. The purified amplicons from the first PCR were used as templates in the second PCR with the same amplification condition used in the first PCR with the exception of using Illumina-tailed primers in a 30-cycle amplification regime. All PCRs were done using Eppendorf Mastercycler ep gradient S thermalcyclers and negative control reactions (no DNA template) were included in all experiments. PCR products were visualized on a 1.5% agarose gel to check the amplification success. All generated amplicons were dual indexed, pooled and sequenced on multiple Illumina

MiSeq flowcells using V2 MiSeq sequencing kits (250 × 2)(FC-131-1002 and MS-102-2003).

All sequencing data generated will be submitted to Dryad for access by the scientific community after publication of this data.

For all 257 samples, Illumina reads were generated from both COI fragments (BE and

F230). For each sample, the forward and reverse raw reads for the BE fragment and the F230 fragment were merged with SEQPREP software (https://github.com/jstjohn/SeqPrep) requiring a minimum overlap of 25bp and no mismatches. All Illumina paired-end reads were filtered for quality using PRINSEQ software and a minimum length of 100bp. USEARCH v6.0.307 with the UCLUST algorithm was used to dereplicate and cluster the remaining sequences using a 98% sequence similarity cutoff. This was done to denoise any potential sequencing errors prior to further processing. Chimera filtering was performed using USEARCH with the ‘de novo

UCHIME’ algorithm. At each step, cluster sizes were retained, singletons were retained, and only putatively non-chimeric reads were retained for further processing. All filtered, non- chimeric reads from all 257 samples were pooled and clustered at 98% similarity. For those clusters including at least 100 sequences, membership in each cluster for each sample was recorded as an operational tatanomic unit (OTU) sequence abundance matrix.

An OTU was defined as a cluster of at least 10 sequences in each sample with a minimum of 98% similarity to any CO1 reference sequence in the Genbank and BOLD databases. Assigned operational taxonomic units (AOTUs) are clusters of sequences which all assigned to the same taxonomic classification (haplotypes), which could be at the genus, family, or order level. If there were more than one cluster of sequences assigned to the same taxa, these were pooled together.

Only those AOTU’s within the class Insecta were carried forward for further analysis, excluding other orders such as Arachnida and any bacterial, fungal or plant DNA. The number of sequences of each AOTU was not considered for further analysis, but this was converted to the AOTU being present if there were at least 10 sequences in a particular sample and absent if there were less than 10 sequences.

Since guano from pre-WNS was not available, I used the raw sequence data from Clare et al (2011) and Clare et al (2013) for M. lucifugus and Clare et al (2014) for E. fuscus. The sequences underwent a BLAST (Basic Local Alignment Search Tool) against BOLD and

Genbank and followed the same criteria for AOTU presence as the guano or stomach samples.

The data from each of these was pooled so as to determine if each prey AOTU was present or absent in the diet of bats from each study, rather than frequency of occurance in samples.

A list was developed of the frequency of occurrence of each AOTU within the samples of each of the following groups: pre-WNS stomach (n=44, E. fuscus), post-WNS stomach (n=46, E. fuscus), Clare et al (2011) (n=1 (due to pooled dataset of M. lucifugus)), Clare et al (2013) (n=1

(pooled dataset of M. lucifugus)), Clare et al (2014) (n=1 (pooled dataset of E. fuscus)), NORF

(n=20, E. fuscus roost subsamples), HALD (n=23, E. fuscus roost subsamples), DUNN (n=37, E. fuscus roost subsamples combined from various roosts), CAMB (n=22, E. fuscus roost subsamples combined from various roosts), GREY (n=18, E. fuscus roost subsamples), BRU

(n=23, E. fuscus roost subsamples) and SAND (n=24, M. lucifugus roost subsamples).

Statistical methods After analysis of the acoustic data, only the files classified as E. fuscus and M. lucifugus were carried forward, excluding files with other species or ambiguous species identity. All data were pooled for pre-WNS and post-WNS for each of these two species to quantify overall

15 changes in bat activity. Boxplots were created of the mean passes per night across the survey period between pre-WNS and post-WNS for each species. A Tukey test was then conducted to determine if there were significant differences among stations with respect to the mean number of bat passes per night of each species. For the Dun station with data across three years of pre-

WNS and four years of post-WNS, the data from those years was pooled for comparison. The mean bat passes per year was also plotted for each of the seven years at Dun for each species to look at annual changes and a Tukey test was then conducted to test whether differences were significant.

For the diet data, the mean number of AOTU’s within each of the major insect orders was calculated to compare differences between stomachs pre-WNS and post-WNS and between each of the post-WNS E. fuscus roosts. A rarefaction curve was created from AOTU’s using the iNext package (Hsieh et al, 2015) and the Chao function (Chao et al, 2014; Cayuela et al, 2015) in R (R Core Team, 2015). Through this analysis, the overall AOTU richness was calculated where the rarefaction curve reaches an asymptote (estimated total diet AOTU richness) and has a

95% confidence interval. The difference between the estimated richness of stomachs pre-WNS was compared with post-WNS. The same analysis was conducted to describe differences in estimated richness from the guano at the different E. fuscus roosts.

I then created lists of insect taxa identified to the species level for all guano and stomach samples for both species of bat and the lists created from corss-referencing the sequences from

Clare et al (2011), Clare et al (2014) and Clare et al (2013). I checked these lists against lists of known pest insects, totalling 242 pest insect species from OMAFRA (2015), and 67 mosquito species from Giordano et al (2015) and Cywinska et al (2006). Several other insect species are herbivores on plants that humans use, but these were not included in the pest list unless they

16 occurred in OMAFRA (2016). I also compared the list of species identified in the diet of bats to the species in OMAFRA (2009) to determine which species or families of beneficial insects are being consumed. From these data, I was able to quantify which species of insect pests and beneficial insects were found within the diet of each of the bats species and whether these changed from pre-WNS to post-WNS.

RESULTS

Acoustics Throughout the study, across thirteen stations, a total of 960 nights of data were

collected pre-WNS and 1187 nights of data were collected post-WNS. The station at which the

most data were collected was the Dun station, where 395 nights (across three years) of data

pre-WNS and 601 nights (across four years) of data post-WNS provided a strong dataset from

which to draw conclusions.

Overall, the decline of M. lucifugus pre- to post-WNS across all stations was 81.72%

(Figure 5), and 84.6% at the Dun station. At Dun, there was 99.9% decline of M. lucifugus

between 2010 (highest mean activity) and 2014 or 2015 (lowest activity, Figure 6). Significant

decline in M. lucifugus was observed across twelve of the fifteen stations, with decline ranging

from 56.0-98.7% (Table 1, Figure 7). The decline was not significant at Hur1, and where this

species was not frequently observed pre-WNS at Lam1 and Lam2 (Figure 7).

The mean activity level of E. fuscus from pre-WNS to post-WNS increased by 27.5%

overall (Figure 5), and by 78.2% at Dun. Although there was an overall increase in E. fuscus

activity at Dun, the changes were variable across years, with 2012 actually showing a decrease

in activity during the first year of M. lucifugus decline, but significant increase in activity

levels in 2013 and 2015 (Figure 8). When investigating the differences in mean nightly bat

passes at each station for E. fuscus, the trend was inconsistent (Figure 9). The predicted

increase in E. fuscus activity was statistically significant (P < 0.05) at seven of the thirteen

stations and considered biologically significant (0.05 < P < 0.10) at one station (Bru3, Table 1).

The change was not significant at four stations. In contrast to the prediction, E. fuscus

experienced a significant decline at three stations (Mid, Grey and Bru1). At station Hald which

is set outside of a known nursery roost of E. fuscus, the activity levels of this species declined

(although not significantly, P = 0.132) despite the significant decline of M. lucifugus at this

location.

Results of Capture and Tracking

Bat capture and tracking in 2014 was carried out in Dunnville, one of which capture locations corresponding to the Dun acoustic station. In total, thirteen bats were captured, all of which were E. fuscus (Table A-2). Of the thirteen bats, three were adult male, six were adult female, four were juvenile male and none were juvenile female. All bats were photographed and released at the site of capture with no evidence of harm. None of the bats showed wing damage that could have resulted from WNS infection (all were Reichard’s Wing Score of 0 (Reichard,

2009)). Four of these bats, captured at four different locations were tracked to their roost. The distance between the capture site and the roost for these bats was approximately 360, 830, 1080 and 2700 m. Two of the roosts were accessible, in which there was a large accumulation of guano and several bats observed (although most bats were hiding within the roof), indicating that the colony was well established at these locations. At the other two roosts, the bat was identified at the building due to the VHF tag response, but the population and guano samples were not collected because the roost could not be accessed.

Diet

Monthly collection of guano was conducted at all 7 roosts or roost areas, including

Sandilands. There was less guano available at the individual roosts in Dunnville in the early part of the season (prior to capture and tracking), so these roosts were pooled for the Dunnville samples. Similarly, guano accumulation at the individual Cambridge roosts was lower at the end of the season, so Cambridge area roosts were also pooled. Of 345 guano samples collected across all roosts, 167 were processed through next generation sequencing, which included a subset of samples from each month at each roost area. Overall, 543 AOTU’s were identified across all samples taken from E. fuscus roosts, with each site ranging from 100 (GREY) to 277

(DUNN) AOTU’s.

The mean percent of the number of AOTU’s within each insect order at each of the roosts is provided in Figure 10, including SAND. Coleoptera was in very low proportion for M. lucifugus (Sandilands) as expected, but the proportion of Coleoptera varied across E. fuscus roosts with the lowest at Demarce and Burke. In Figure 11, the proportion of AOTU’s per insect order for E. fuscus is transposed to show how the relative proportion varied across roosts. In

Figure 12, the lower proportion of Coleoptera is apparent at Demarce and Burke, but these are still within one standard deviation from other roosts, and therefore the difference is not statistically significant. Diptera were also in lower proportion at Demarce, Burke and

Cambridge (the most northern roosts), and these three roosts had the highest proportion of

Ephemeroptera and Trichoptera, most similar to Sandilands.

The number of AOTU’s identified at a particular roost is not an exhaustive list of all insects consumed by the bats at that roost. Therefore, rarefaction curves were created to determine the total richness of insects consumed (Figure 12). Associated with the rarefaction curves is a calculation of the total estimated richness of prey items, provided in Table 2. HALD

(365 AOTU’s (95% CI [300, 473]) and DUNN (482 AOTU’s (95% CI [373, 666]) showed high estimated richness relative to BRU (254 AOTU’s (95% CI [195, 360]), GREY (209 AOTU’s

(95% CI [152, 323]), CAMB (258 AOTU’s (95% CI [210, 346]) and NORF (242 AOTU’s (95 %

CI [176, 379]).

Of all AOTU’s classified to the species level, observed in M. lucifugus (total 253 species), seven were recorded pre-WNS in E. fuscus in Clare et al (2014) and 37 were observed in pre-WNS stomachs. However, 58 of these species from M. lucifugus diets were observed in post-WNS E. fuscus stomachs and 97 were observed in at least one of the post-WNS roost diets.

Of the stomach samples extracted from E. fuscus, 44 were from pre-WNS and 46 were from post-WNS. The mean proportion of insects eaten by order was not significantly different between pre-WNS and post-WNS samples (Figure 13). Using rarefaction curves (Figure 14), there is a significant difference in the overall richness within the samples, with the estimated richness greater for post-WNS samples (627 AOTU’s (95% CI [532, 769]), than for pre-WNS samples (560 AOTU’s (95% CI [458, 718]), Table 3). These data suggest that E. fuscus showed an increased richness of diet after the introduction of WNS, potentially due to the increased abundance of food items previously consumed by other bats. Using the estimated richness value, the samples were ranked as follows:

Richness: Highest  Lowest

Stomachs Stomachs Post- DUNN HALD SAND CAMB BRU NORF GREY Pre-WNS WNS

The AOTU richness of stomach samples was higher than that of guano samples, suggesting that sampling from stomachs is more sensitive in detecting dietary breadth.

Pest Insects

A list of 242 insects, including 67 mosquito species were cross-checked against those species identified in the guano and stomachs of E. fuscus and M. lucifugus, including those reported in Clare et al (2011), Clare et al (2014) and Clare et al (2013) (each study was pooled for presence or absence of species). A total of 37 insect pest species were identified in guano and stomachs across all samples, with 14 of these being consumed by M. lucifugus and 35 being consumed by E. fuscus overall (Table 3). Of these, only two leaf-miner species, Argyresthia canadensis, and Argyresthia thuiella were consumed by M. lucifugus, but not found in E. fuscus.

Of the 35 species identified in the diet of E. fuscus, 20 were identified from pre-WNS (Clare et al

(2013) or stomachs), and 33 were identified from post-WNS (stomachs or roosts). Only two of the 35 pest species observed in E. fuscus were not observed in post-WNS diets: the Western

Bean Cutworm (Striacosta albicosta) and a Mosquito (Culiseta inornata), both of which were found in only one sample of E. fuscus pre-WNS. Of the 14 species identified in the diet of M. lucifugus, 8 were consumed by E. fuscus pre-WNS and 9 were consumed by E. fuscus post-

WNS. A mosquito species (Culiseta inornata), was found in M. lucifugus and one E. fuscus stomach pre-WNS, but was not found in any sample post-WNS. Another mosquito species

(Aedes vexans) was observed in M. lucifugus diets and all E. fuscus diets, suggesting that it is

21 frequently consumed by either bat species. Pest insects consumed by M. lucifugus and found only in post-WNS samples of E.fuscus include the following:

1) A fruit tree leaf-roller (Archips argyrospila) was found in one guano sample at HALD;

2) Redbanded leaf-roller (Argrotaenia velutinana) was found in guano samples at HALD and BRU;

3) Onion maggot (Delia antiqua) was found in post-WNS stomachs, NORF, DUNN and

CAMB; and,

4) June Beetle (Phyllophaga futilis) was found at all E. fuscus guano roosts, but not in post-WNS stomachs.

One species of plant bug (Miridae) was identified called the tarnished plant bug (Lygus lineolaris) was found in all E. fuscus guano sampling sites except GREY and in both pre-WNS and post-WNS stomachs, but was not found in any sample from or study on M. lucifugus. This species is considered to be an important native agricultural pest in Ontario (Broadbent et al,

2006).

Beneficial Insects

Twenty-two species were listed in OMAFRA (2009) which are considered beneficial to apple orchards. None of those species were identified in the list of insects consumed by bats in this study, and no bees were identified. However, OMAFRA (2009) suggest that there are several other beneficial insects in various insect families. In particular, two lacewing species

(Neuroptera family) were idenfified in the bat diets; Hemerobius atrifrons and H. stigma. Both of these insects are considered to be predatory on other insects, but neither were found in

22 stomachs or guano sampled here (Appendix B). One parasitic fly species, Actia interrupta was found in the guano of M. lucifugus at SAND, but not from any E. fuscus sample. This species is a parasite of the Obliquebanded Leafroller (Choristoneura rosaceana), which was found at

SAND, but also at five E. fuscus roosts and post-WNS E. fuscus guano. The A. interrupta may not have been the target prey of M. lucifugus, but within the C. rosaceana that it consumed.

Most notably, ground beetles in the family Carabidae are considered to be caterpillar hunters.

Although the species listed in OMAFRA (2009) were not found in any bat diet, other species within this family were identified (see Appendix B). The species most frequently identified are

Stenolophus comma, a predator on codling moth larvae and apple maggot pupae (Hagley et al,

1982) which was not identified in M. lucifugus diet, and Stenolophus ochropezus, found in all sampling groups for M. lucifugus and E. fuscus except SAND and BRU. The remaining insect species found in the diet of E. fuscus and M. lucifugus re provided in Appendix B.

DISCUSSION

The overall trend for E. fuscus in response to the decline of M. lucifugus was significantly positive and it was significantly or biologically positive at 8 of the 13 stations, which supports the prediction of a competitive interaction, in that E. fuscus was recorded more frequently where there was a significant decline of M. lucifugus. The stomach samples collected throughout southern Ontario showed an increase in diet richness following the introduction of WNS, supporting the predictions arising from the competition hypothesis of an increase in richness of

E. fuscus prey items following competitive release. This conclusion is further supported by an increase in the presence of insect pests in E. fuscus diet following the introduction of WNS.

The capture and tracking of bats was a successful method to find roosts for this species at which guano could be collected. All bats tracked were found on the first day of tracking with relatively little effort and all of these bats stayed within the roosts for at least three consecutive days, and no alternate roosts were discovered. All of the roosts were buildings (residences where people also live), which is typical for this species, although they will sometimes roost in trees.

The timing of this capture and tracking program did not allow for collection of guano in the early parts of the season (May or June), but the two roosts used afterwards had large colonies of bats at which a significant amount of guano was available for collection.

One key observation of the capture program was that only one species was ever captured on any night (E. fuscus). These netting techniques are somewhat biased towards species which will fly low enough to be captured, but many other bat species would also meet this criteria.

Previous netting efforts in 2013 at these locations has also captured Eastern Red Bat (Lasiurus borealis) and M. lucifugus (pers. obs). Fortunately, E. fuscus was the target species for the project but the capture rate of this species was also less than on previous efforts (pers. obs). The results of the capture also support the hypothesis that M. lucifugus have declined significantly in this area since the introduction of WNS. It also corresponds with the acoustic data showing a reduction in the activity of E. fuscus in 2014 from 2013, although there is no explanation for this observation.

Replicated acoustic monitoring and especially long-term stationary acoustic monitoring provide an effective means to track long-term changes in bat activity as a surrogate for bat population abundance. While this data could have some degree of auto-correlation because stations were re-sampled in different years, a repeated measures calculation was not conducted.

The detectors and automated species classification programs have limitations in their ability to

24 discriminate bats in files with multiple individuals, because of poor sound quality or atypical search-phase calls (Adams et al, 2012). This bias was consistent across the entire study, so is considered to be a minor nuisance rather than a confounding factor. It seems to be more repeatable than manual classification techniques, which can have similar biases and considerable errors in taxonomic assignment due to human subjectivity (Skowronski and Fenton, 2009).

There is potential that additional passes of these species were recorded and classified to a higher level (i.e. Myotis spp.), or misclassified as another species (i.e. E. fuscus being misclassified as

Lasionycteris noctivagans), but those recordings were consistently excluded from the dataset for this analysis and therefore the effect of this exclusion should be consistent. There is also the potential that other species were misclassified as E. fuscus or M. lucifugus, but this should also be uncommon and consistent across the analysis. There could be other environmental factors which change the activity measures, and overall population of bats over time. These could be things like climate change, roost availability or anthropogenic disturbance to bats. However, those were considered to be consistent pre-WNS to post-WNS in this dataset and within the variation of both estimates. Since the effects of WNS on M. lucifugus has happened very rapidly, the change in bat activity is considered to be reflective mostly of those effects from

WNS, rather than other environmental conditions.

These data provide evidence that M. lucifugus in Southern Ontario declined following the introduction of WNS, based on summer activity patterns, as predicted by the competition hypothesis. Importantly from a conservation and species management perspective, the decline of summer activity of this species was observed in locations that are outside of where WNS has been confirmed – demonstrating that the ecological footprint of the disease is greater than that shown on spread maps.

Rates of bat population decline are not likely to equal the potential rates of recovery – all bats can die quickly, but females of both these two species typically only have one pup per year, and it is not known whether they reproduce each year or for how many years in total one female can reproduce. However, one individual could become more active in the absence of sympatric bats (indicated by more time flying and echolocating on the landscape), so activity levels (passes per night) may not accurately index population abundance.

E. fuscus activity levels increased overall, but not consistently across all locations. The significant decline of E. fuscus at Mid, Grey and Bru1 were opposite to the general trend. These locations may have suffered local disturbances (i.e. roost eviction) with opposite effects than those due to competitive release, or there could have been less competitive interactions to begin with at some stations. Dun showed a lower level of activity in 2012 and 2014 when the data at all other stations was collected, but significantly higher activity in 2013 and 2015, suggesting that there could be significant inter-annual variation in local bat activity, which could explain some inconsistency in the results across stations.

Three stations (Cam, Lam2 and Bru4) all had low levels of activity of M. lucifugus pre-

WNS (Table 1). Two stations (Lam1 and Lam2) are in mostly agricultural landscapes that are not expected to have a high abundance of M. lucifugus. Despite the low activity level of M. lucifugus, there was still a significant decline at Cam and Bru3 and a corresponding significant increase of E. fuscus at Camb, Bru3 and Lam1. Where no M. lucifugus were observed either pre-

WNS or post-WNS at Lam2, the change in E. fuscus was not significant. In contrast, the M. lucifugus activity level at Hur1 declined by only 14.5 percent, which was not considered a significant decline, but the activity level of E. fuscus still increased significantly, by 330%.

At the known E. fuscus roost (Hald), there was a significant decline of M. lucifugus, but also a small decline of E. fuscus (though not statisticaly significant). This is a large building, which could have also served as a roost for M. lucifugus although none were physically observed within the building. The detector was set back approximately 10 m from the building, so not all bats recorded were necessarily roosting within the building. These data do not explain why E. fuscus activity declined at this location. It is possible that E. fuscus may have chosen to use other roosts for this year or spent less time in close proximity to the roost (resulting in less acoustic activity). There could also have been a direct impact on the bats in this roost such as bat exclusion or extermination attempts (i.e. a pail of water was found within the roost that had two dead bats) or local landscape disturbance (i.e. wind power facilities have been developed in the general area of this roost).

Collection of bat guano and DNA processing was an effective method to develop a comprehensive list of taxa consumed by these bats, but despite a significant number of samples collected and processed, the total AOTU’s did not approach the estimated total richness calculated through rarefaction curves. Next generation sequencing of DNA has proven superior to traditional methods of morphological prey identification for the determination of prey richness, but DNA processing methods are still not suitable for quantifying the abundance of prey items in the bat diet. Therefore, future studies should focus on ways to calculate the volume of each prey item, which can then be extrapolated to determine the impact of bat feeding on the insect biomas. Greater insect prey richness was found in bat stomachs, likely because the contents of the stomachs have been less digested and degraded than in guano. This indicates that bats have a considerably broad insect diet, although many taxa could be consumed rarely.

Proportional representation of insect orders varied considerably across roosts, indicating that the breadth of the diet of bats is locally driven, as suggested in Clare et al (2011).

DUNN and HALD had the highest estimated richness, all of which are on the southern end of the study area. NORF was also in the southern end of the study area and had one of the lowest estimated richness’. The diet of bats at all E. fuscus roosts continued to have a high proportion of Coleoptera (supporting the conclusions of Clare et al (2014)) relative to the M. lucifugus roost, although this was lower at GREY and BRU (the two most northerly roosts). In contrast, GREY and BRU had the highest relative proportion of Ephemeroptera of all roosts, also similar to M. lucifugus at Sandilands. GREY and BRU are also the roosts in closest proximity to the earliest confirmation of WNS in Ontario (Grey County, See Figure 1). These two roosts have two of the lowest richness of AOTU’s of all E. fuscus roosts, in contrast to my predictions, but most closely resemble the diet assemblage of M. lucifugus at the insect order level. It’s possible that although GREY and BRU have lower diet richness than other roosts, this richness could be greater than was the case for those roosts before the loss of M. lucifugus.

This data does not account for the availability of insect prey on the landscape. The assumption is that prey was equally available to these bats over time pre-WNS to post-WNS. The same is considered across roosts for data collected in 2014 where it is assumed that the richness of insect prey available is the same. Future studies could be conducted to test the abundance of insects on the landscape and how they have changed over time. More importantly, a change in insect abundance of those species which are prey of bats could indicate the strength of population pressure of bats on insects and how that may have changed as a result of the loss of bats from

WNS.

To compare species consumption overlap between M. lucifugus and E. fuscus, the most comparable samples are pre-WNS and post-WNS stomachs of E. fuscus, in which there was an increase from 37 to 58 species in common with M. lucifugus. Clare et al (2014) found only seven species from the list generated for M. lucifugus, while 97 insect species were identified in the diet of E. fuscus across all post-WNS roosts. These data support the prediction that there is an increase in the overlap of prey items between E. fuscus and M. lucifugus in response to the decline of M. lucifugus. Further analysis could use radio isotopes of the guano samples to characterize differences in the places where each species of bat are eating based on differences in isotope ratios for insects which feed over terrestrial landscapes versus aquatic landscapes.

I have demonstrated that both E. fuscus and M. lucifugus consumed insect pest species, although these data cannot be used to quantify the abundance of these species in the diet or the overall effect on the population of these insect pests. More insect pest species appeared in the diet of E. fuscus post-WNS than pre-WNS. Also, of the insect pests consumed by M. lucifugus, there was an increase in the number of these consumed by E. fuscus in response to the decline of

M. lucifugus. These data support the prediction of the competition hypothesis of an increase in the number of pest insects species consumed by E. fuscus, suggesting that diet expansion by E. fuscus due to competitive release could help to fill the niche of insect pest control that was previously afforded by M. lucifugus, implying an important rescue effect relevant to pest control efforts. Very few beneficial insects were identified in the deit of E. fuscus with the exception of

Carabid beetles, particularly S. comma and S. ochropezus. However, the ecology of many of the insects consumed by bats is not well known. Spiders (Arachnida) were not evaluated from these samples, but there were spiders observed in the diets. Whether these insectivorous spiders could be considered beneficial based on the insects they are cosuming is a topic suitable for further

29 research. Therefore, the changes in bat polulations could have effects on insects and then agricultural crops in both positive and negative ways.

Further research is needed to quantify the overall ecological effect of WNS on the bat community assemblage, considering the effects of exploitative interspecific competition. This will be critical in modelling the potential for population recovery of M. lucifugus and other species, if they are able to overcome the direct effects of WNS. Changes in the impact bats have on insect populations and their contribution to the ecosystem are obviously important to understand. This study provides an extensive list of insect species which could be affected by changes in predation, but further research is needed to understand the overall impact on those insect populations, especially with respect to insect pests. Although bar-coding studies cannot currently quantify the magnitude of insect consumption, it nonetheless demonstrates that bats play a potential role in the control of insect pests and possible effects on beneficial insects. As described above, futher research is needed on the biomas of each of these insects in the environment and how much of that biomas is actually consumed by bats to determine if there is an actual population control service provided by bats and how that has changed with differences in the proportion of different bat species on the landscape.

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TABLES AND FIGURES

Figure 1: Extent of confirmed WNS from winter assessment at bat hibernacula as of September 3, 2014 (note, light grey is from 2011-2012)

Figure 2: Map of acoustic monitoring stations

Figure 3: Map of roost locations for collection of E. fuscus guano

Figure 4: Dunnville bat capture locations (red) and roost locations (blue), prepared using the Grand River Conservation Authority’s GRIN online service.

Mean bat Mean passes per night

Figure 5: Overall mean bat passes per night for M. lucifugus and E. fuscus (both statistically significant).

Figure 6: Changes in mean bat passes per year for M. lucifugus at the Dun station

Figure 7: Changes in mean bat passes per night for M. lucifugus (See Table 1 for which of these are significant changes)

Figure 8: Changes in mean bat passes per year for E. fuscus at the Dun station

Figure 9: Changes in mean bat passes per night for E. fuscus (See Table 1 for which of these are significant changes)

Mean AOTU's per Order 25

15 Other Insecta Trichoptera Lepidoptera Ephemeroptera Diptera

Mean AOTU's MeanAOTU's perorder 10 Coleoptera

0 NORF HALD DUNN CAM BRU GREY SAND

Figure 10: Percent richness by order for all E. fuscus roosts and the M. lucifugus roost (Sandilands)

Mean AOTU's per Order for each Roost 14

8 NORF HALD DUNN

6 CAM

Mean AOTU MeanAOTU perorder BRU GREY SAND 4

Figure 11: AOTU's per insect order across E. fuscus roosts and one M. lucifugus roost (SAND) (brackets are one standard deviation from the mean)

AOTU

Figure 12: Rarefaction curves for E. fuscus roosts where species diversity represents AOTU richness

Mean Percent Richness of AOTU's in the stomachs of Big Brown Bats in each Insect Order 70

PreWNS MeanAOTU's 20 PostWNS 10

Figure 13: Mean percent richness of AOTU's by order for stomachs

AOTU

Figure 14: Rarefaction curves for E. fuscus stomachs pre-WNS and post-WNS (the difference between estimated species richness is statistically significant), where species diversity represents AOTU richness

Table 1: Direction of change in mean passes per night at each acoustic bat monitoring station

E. fuscus M. lucifugus Station Pre- Post- Direction P-value % Pre- Post- Direction P-value % WNS WNS change WNS WNS change Mean Mean Mean Mean Cam 1.40 13.82 + <0.001* 886.3 0.21 0.09 - 0.029* -56.0 Lam1 9.92 57.80 + 0.012* 482.5 0.08 0.00 - 0.337 -100.0 Lam2 19.54 15.00 - 0.487 -23.2 0.00 0.00 0 n/a n/a Hur1 9.30 40.03 + <0.001* 330.5 3.85 3.29 - 0.660 -14.5 Hur2 30.88 24.06 - 0.390 -22.1 60.77 6.11 - 0.003* -89.9 Mid 67.83 28.93 - 0.006* -57.3 3.88 0.04 - <0.001* -99.1 Hald 40.87 24.17 - 0.132 -40.9 7.53 0.10 - <0.001* -98.7 Grey 14.08 0.86 - <0.001* -93.9 48.02 0.70 - <0.001* -98.5 Bru1 3.43 0.53 - <0.001* -84.4 5.67 0.05 - <0.001* -99.2 Bru2 30.37 37.57 + 0.420 23.7 190.46 76.40 - 0.001* -59.9 Bru3 4.13 19.81 + 0.070** 379.5 1.00 0.14 - 0.006* -86.1 Bru4 29.78 79.22 + 0.004* 166.0 6.87 2.59 - 0.001* -62.2 Dun 11.66 20.79 + <0.001* 78.2 45.99 5.28 - <0.001* -88.5 * - statistically significant change (p<0.05) ** - biologically significant change (p<0.10)

Table 2: AOTU Richness in guano and stomach samples, based on the Chao estimator

Total Observed AOTU Est_S.E. 95% 95% Subsamples Richness Lower Upper Estimator NORF 20 112 242.421 49.425 175.611 379.401 HALD 23 200 365.052 43.193 299.665 473.336 DUNN 37 214 482.18 72.732 373.096 666.058 CAMB 22 152 258.028 33.617 209.807 346.475 GREY 18 99 208.587 41.526 152.453 323.672 BRU 23 127 253.51 40.536 195.553 360.468 SAND 24 154 334.188 54.665 254.728 476.328 Stomachs 44 277 560.13 65.171 458.376 718.969 Pre-WNS Stomachs 46 339 627.629 59.382 532.655 769.182 Post-WNS

Table 3: Pest Insects Observed in Bat Diets. Number values are how many samples in which the species was identified from the total samples in that sampling group.

Little Brown Myotis (M. lucifugus) Big Brown Bat (E. fuscus) Clare (2013) Clare (2011) Sandilands Clare (2014) Stomach pre-WNS Stomach post-WNS NORF HALD DUNN CAMB GREY BRU Total Samples Processed  Pooled Pooled 24 Pooled 44 46 20 23 37 22 18 23 Common Name Species Mosquito Aedes sp. (incorrectly classified as Aedes togoi) 0 0 1 0 3 7 0 1 0 0 0 0 Mosquito Aedes vexans Yes 0 1 0 4 11 4 5 2 1 1 2 Mosquito Culex restuans 0 0 1 0 2 6 1 1 0 0 0 0 Mosquito Culiseta inornata Yes 0 0 0 1 0 0 0 0 0 0 0 Green stink bugs Acrosternum hilare 0 0 0 0 10 17 8 10 16 8 4 2 Fruit tree leafroller Archips argyrospila Yes 0 0 0 0 0 0 1 0 0 0 0 Redbanded leafroller Argyrotaenia velutinana 0 0 1 0 0 0 0 1 0 0 0 1 Obliquebanded leafroller Choristoneura roseceana 0 0 0 0 7 6 0 7 3 2 0 2 Onion maggot Delia antiqua 0 Yes 0 0 0 1 1 0 1 1 0 0 Corn Rootworm Diabrotica barberi 0 0 0 0 5 1 0 0 0 0 0 0 Corn Rootworm Diabrotica virgifera 0 0 0 0 4 1 0 0 0 0 0 0 Wireworms Eaeolus millilus 0 0 0 0 3 4 0 3 0 0 0 0 Wireworms Ampedus melsheimeri 0 0 0 0 0 0 0 0 0 1 0 0 Wireworms Hemicrepidius brevicollis 0 0 0 0 0 1 0 2 3 4 3 2 Wireworms Hemicrepidius memnonius 0 0 0 0 3 1 1 9 9 12 0 0 Wireworms Melanotus communis 0 0 0 0 1 1 0 0 0 0 0 0 Wireworms Melanotus cribulosus 0 0 0 0 0 4 0 0 5 3 3 0 Wireworms Melanotus dietrichi 0 0 0 0 1 3 1 0 9 0 0 0 Wireworms Menlanotus similis 0 0 0 0 2 3 0 2 5 3 3 0 Potato leafhopper Empoasca fabae 0 0 0 0 0 2 0 0 0 0 0 0 Tarnished plant bug Lygus lineolaris 0 0 0 0 8 22 1 9 2 2 0 1 Aster leafhopper Macrosteles quadrilineatus 0 0 0 0 0 1 0 0 0 0 0 0 Eastern tent caterpillar Malacosoma americanum Yes 0 0 Yes 0 0 0 0 0 1 0 2 Apple budmoth Platynota idaeusalis Yes 0 0 0 1 0 0 3 0 0 0 0 Diamondback moth Plutella xylostella 0 0 0 0 3 6 1 1 2 0 0 1 Western Bean Cutworm Striacosta albicosta 0 0 0 0 1 0 0 0 0 0 0 0 Twig Pruner Anelaphus villosus formerly Elaphidionoides 0 0 0 0 0 0 0 0 0 1 0 0 Cedar (Arborvitae) Leafminers Argyresthia canadensis Yes 0 0 0 0 0 0 0 0 0 0 0 Cedar (Arborvitae) Leafminers Argyresthia thuiella Yes 0 0 0 0 0 0 0 0 0 0 0 Spruce Budworm Choristoneura fumiferana Yes 0 0 Yes 0 1 0 3 0 3 0 0 Forest Tent Caterpillar Malacosoma disstria Yes Yes 0 Yes 0 1 0 1 0 1 0 1 June Beetle Phyllophaga balia 0 0 0 0 0 0 0 1 0 0 0 0 June Beetle Phyllophaga fusca 0 0 0 0 0 0 1 0 0 0 1 0 June Beetle Phyllophaga futilis 0 Yes 0 0 0 0 1 4 4 5 1 2 June Beetle Phyllophaga knochii 0 0 0 0 0 0 0 0 1 0 0 0 June Beetle Phyllophaga pearliae 0 0 0 0 0 0 0 0 0 1 0 0 Willow Leaf Beetle Plagiodera versicolora 0 0 0 0 0 0 1 0 0 0 0 0 total 7 3 1 0 13 18 9 15 12 15 6 9

Appendix A: Bat Capture and Tracking in Dunnville Results

Table A-1: Net Placement, Effort and Weather

Project Name Date Weather Summary Net Location (UTM Net Nets Nets Total Net Net Net Total Net Area Description NAD83, Zone 17) Configuration Opened Closed hours Effort Location Name Bats (1nH Caught = 6m net X 1hr) Byng 5-Jul-14 Clear sky, low wind, 16-19C 610606, 4750460 9m, 3H 21:30 2:30 5 7.5 1 A 0 Near fence to Lagoon Byng 5-Jul-14 Clear sky, low wind, 16-19C 610606, 4750460 9m, 3H 21:30 2:30 5 7.5 1 B 0 Near fence to Lagoon Byng 5-Jul-14 Clear sky, low wind, 16-19C 610606, 4750460 9m, 3H 21:30 2:30 5 7.5 1 C 0 Near fence to Lagoon Byng 5-Jul-14 Clear sky, low wind, 16-19C 610562, 4750392 12m, 3H 21:30 2:30 5 10 2 A 0 Entrance to trail near pavilion Byng 5-Jul-14 Clear sky, low wind, 16-19C 610562, 4750392 12m, 3H 21:30 2:30 5 10 2 B 1 Entrance to trail near pavilion Byng 5-Jul-14 Clear sky, low wind, 16-19C 610562, 4750392 12m, 3H 21:30 2:30 5 10 2 C 0 Entrance to trail near pavilion Byng 5-Jul-14 Clear sky, low wind, 16-19C 610524, 4750402 6m, 1H 21:30 2:00 4.5 4.5 3 A 0 Across trail within forest Byng 5-Jul-14 Clear sky, low wind, 16-19C 610513, 4750422 9m, 1H 21:30 2:00 4.5 6.75 4 A 1 Near pond within forest Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615775, 4748900 12m, 3H 21:30 1:00 3.5 7 1 A 0 Porch to dock, near river Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615775, 4748900 12m, 3H 21:30 1:00 3.5 7 1 B 0 Porch to dock, near river Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615775, 4748900 12m, 3H 21:30 1:00 3.5 7 1 C 0 Porch to dock, near river Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615761, 4748889 6m, 1H 21:30 1:08 3.5 3.5 2 A 0 Over driveway Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615754, 4748841 9m, 3H 21:30 1:00 3.5 5.25 3 A 0 Back field between oaks Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615754, 4748841 9m, 3H 21:30 1:00 3.5 5.25 3 B 0 Back field between oaks Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615754, 4748841 9m, 3H 21:30 1:00 3.5 5.25 3 C 0 Back field between oaks Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615762, 474829 9m, 1H 21:30 1:00 3.5 5.25 4 A 0 Edge of creek Morningstar Cottage 6-Jul-14 Sky clear and calm, becoming cloudy and high wind 615693, 4748824 9m, 1H 21:30 1:00 3.5 5.25 5 A 0 Edge of pond Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615775, 4748900 12m, 3H 21:30 2:30 5 10 1 A 0 Porch to dock, near river Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615775, 4748900 12m, 3H 21:30 2:30 5 10 1 B 0 Porch to dock, near river Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615775, 4748900 12m, 3H 21:30 2:30 5 10 1 C 0 Porch to dock, near river Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615761, 4748889 6m, 1H 21:30 2:30 5 5 2 A 0 Over driveway Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615754, 4748841 9m, 3H 21:30 2:30 5 7.5 3 A 0 Back field between oaks Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615754, 4748841 9m, 3H 21:30 2:30 5 7.5 3 B 0 Back field between oaks Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615754, 4748841 9m, 3H 21:30 2:30 5 7.5 3 C 0 Back field between oaks Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615762, 474829 9m, 1H 21:30 2:30 5 7.5 4 A 0 Edge of creek Morningstar Cottage 7-Jul-14 Sky cloudy and moderate wind, intermittent rain, 19-23C 615693, 4748824 9m, 1H 21:30 2:30 5 7.5 5 A 0 Edge of pond Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615775, 4748900 12m, 3H 21:30 1:30 4 8 1 A 0 Porch to dock, near river Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615775, 4748900 12m, 3H 21:30 1:30 4 8 1 B 0 Porch to dock, near river Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615775, 4748900 12m, 3H 21:30 1:30 4 8 1 C 0 Porch to dock, near river Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615761, 4748889 6m, 1H 21:30 1:30 4 4 2 A 0 Over driveway Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615754, 4748841 9m, 3H 21:30 1:30 4 6 3 A 0 Back field between oaks Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615754, 4748841 9m, 3H 21:30 1:30 4 6 3 B 0 Back field between oaks Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615754, 4748841 9m, 3H 21:30 1:30 4 6 3 C 0 Back field between oaks Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615762, 474829 9m, 1H 21:30 1:30 4 6 4 A 0 Edge of creek Morningstar Cottage 8-Jul-14 Sky cloudy and low wind clearing later, 15-20C 615693, 4748824 9m, 1H 21:30 1:30 4 6 5 A 0 Edge of pond Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615775, 4748900 12m, 3H 21:30 2:30 4 8 1 A 0 Porch to dock, near river Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615775, 4748900 12m, 3H 21:30 2:30 4 8 1 B 0 Porch to dock, near river Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615775, 4748900 12m, 3H 21:30 2:30 4 8 1 C 0 Porch to dock, near river Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615761, 4748889 6m, 1H 21:30 2:30 4 4 2 A 0 Over driveway Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615754, 4748841 9m, 3H 21:30 2:30 4 6 3 A 0 Back field between oaks

Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615754, 4748841 9m, 3H 21:30 2:30 4 6 3 B 0 Back field between oaks Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615754, 4748841 9m, 3H 21:30 2:30 4 6 3 C 0 Back field between oaks Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615762, 474829 9m, 1H 21:30 2:30 4 6 4 A 1 Edge of creek Morningstar Cottage 9-Jul-14 Clear, calm, 13-15C 615693, 4748824 9m, 1H 21:30 2:30 4 6 5 A 0 Edge of pond Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615455, 4750352 9m, 1H 21:10 2:10 5 7.5 1 A 0 Within woodland, across ATV trail Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615441, 4750221 6m, 1H 21:00 2:15 5 5 2 A 0 Across driveway near railroad Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615484, 4750225 9m, 1H 21:25 2:30 5 5 3 A 0 Across driveway within woodland Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615466, 4750200 9m, 3H 21:20 2:30 5 7.5 4 A 0 Across parking lot at edge of woodland Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615466, 4750200 9m, 3H 21:20 2:30 5 7.5 4 B 1 Across parking lot at edge of woodland Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615466, 4750200 9m, 3H 21:20 2:30 5 7.5 4 C 0 Across parking lot at edge of woodland Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615415, 4750106 12m, 3H 21:25 2:30 5 10 5 A 0 Across trail at edge of forest and field Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615415, 4750106 12m, 3H 21:25 2:30 5 10 5 B 0 Across trail at edge of forest and field Dunnville Marsh 1 10-Jul-14 Clear, calm, ~17C 615415, 4750106 12m, 3H 21:25 2:30 5 10 5 C 0 Across trail at edge of forest and field Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617841, 4748810 9m, 1H 20:35 2:05 5.5 8.25 1 A 0 Trail Corridor Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617878, 4748817 12m, 3H 21:20 2:30 5 10 2 A 0 Confluence of two trails Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617878, 4748817 12m, 3H 21:20 2:30 5 10 2 B 0 Confluence of two trails Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617878, 4748817 12m, 3H 21:20 2:30 5 10 2 C 4 Confluence of two trails Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617943, 4748755 9m, 3H 21:25 2:25 5 7.5 3 A 0 Edge of pond Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617943, 4748755 9m, 3H 21:25 2:25 5 7.5 3 B 0 Edge of pond Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617943, 4748755 9m, 3H 21:25 2:25 5 7.5 3 C 0 Edge of pond Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617930, 4748730 6m, 1H 20:55 2:10 5 5 4 A 0 Trail Corridor Dunnville Marsh 2 11-Jul-14 Clear, Calm, ~15C 617959, 4748704 9m, 1H 20:50 2:00 5 7.5 5 A 0 Trail Corridor Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617636, 4745385 9m, 3H 21:15 1:15 4 6 1 A 0 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617636, 4745385 9m, 3H 21:15 1:15 4 6 1 B 0 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617636, 4745385 9m, 3H 21:15 1:15 4 6 1 C 0 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617647, 4745359 6m, 1H 21:15 1:15 4 4 2 A 0 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617638, 4745280 12m, 3H 21:15 1:15 4 8 3 A 0 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617638, 4745280 12m, 3H 21:15 1:15 4 8 3 B 2 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617638, 4745280 12m, 3H 21:15 1:15 4 8 3 C 2 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617603, 4745272 9m, 1H 21:15 1:15 4 6 4 A 1 Across old road Rock Point 12-Jul-14 Light wind, overcast, storm rolling in later, 23-24C 617659, 4745208 6m, 1H 21:15 1:15 4 4 5 A 0 Across old road

Table A-2: Capture Results of the Bat Capture Program in Dunnville Ontario

Date Location Capture Net Set Species Band Band # Sex Age Reproductive Weight Forearm Reichard's Notes Time Size Condition (g) length Wing (mm) Score 5-Jul-14 Byng 22:05 2B Epfu 4.2 100529 Male Adult Unknown 15 45 0 Tracked bat to Sieman house 5-Jul-14 Byng 00:30 4 Epfu 4.2 100530 Male Adult Unknown 18.8 44 0 9-Jul-14 Morningstar 22:00 4 Epfu 4.2 100543 Male Juvenile Non- 14.5 45 0 Tracked bat to Fraser house. Cottage reproductive 10-Jul-14 Dunnville Marsh 1 21:45 4B Epfu 4.2 100531 Female Adult Lactating 23.6 48 0 Many ticks. Tracked to McFerson house 11-Jul-14 Dunnville Marsh 2 21:20 2C Epfu 4.2 100514 Female Adult Lactating 15.5 44 0 Tracked to King house recap 11-Jul-14 Dunnville Marsh 2 21:55 2C Epfu 4.2 100532 Male Juvenile Non- 14.4 45 0 reproductive 11-Jul-14 Dunnville Marsh 2 0:00 2C Epfu 4.2 100533 Male Juvenile Non- 13.5 43 0 reproductive 11-Jul-14 Dunnville Marsh 2 0:00 2C Epfu 4.2 100534 Male Juvenile Non- 12.5 43 0 reproductive 12-Jul-14 Rock Point 21:30 3C Epfu 4.2 100535 Male Adult Unknown 17.5 44 0 12-Jul-14 Rock Point 21:30 3B Epfu 4.2 100536 Female Adult Unknown 18.7 44 0 12-Jul-14 Rock Point 21:25 4 Epfu 4.2 100537 Female Adult Lactating 17 46 0 12-Jul-14 Rock Point 23:40 3B Epfu 4.2 100538 Female Adult Lactating 17.8 45 0 12-Jul-14 Rock Point 2:30 3C Epfu 4.2 100539 Female Adult Lactating 19.8 43 0

Appendix B: Insects in bat diets that could be identified to the species level

Little Brown Myotis (Myotis lucifugus) Big Brown Bat (Eptesicus fuscus) pre-WNS post_WNS preWNS post-WNS

Epfu Epfu Clare Clare Clare et Stomach Stomach et al et al al Pre- Post- (2013) (2011) SAND (2014) WNS WNS NORF HALD DUNN CAM GREY BRU Total samples processed --> pooled pooled 24 pooled 44 46 20 23 37 22 18 23 Order Family Genus Species Coleoptera Carabidae Agonum Agomum placidum - - - Present 5 13 - - 1 - - - Coleoptera Carabidae Amara Amara apricaria - - - Present - 4 - 1 - - - - Coleoptera Carabidae Calosoma Calosoma frigidum - - - Present ------Coleoptera Carabidae Harpalus Harpalus pennsylvanicus - - - Present ------Coleoptera Carabidae Notiobia Notiobia terminata - - - Present ------Coleoptera Carabidae Ophonus Ophonus puncticeps - - - Present ------Coleoptera Carabidae Platynus Platynus cincticollis - - - Present ------Coleoptera Carabidae Peocilus Poecilus lucublandus - - - Present ------Coleoptera Carabidae Selenophorus Selenophorus opalinus - - - Present ------Coleoptera Carabidae Stenolophus Stenolophus comma - - - Present 4 5 1 5 1 3 - 3 Coleoptera Carabidae Stenolophus Stenolophus ochropezus Present Present - Present 1 14 3 11 9 3 1 - Coleoptera Carabidae Trichotichnus Trichotichnus vulpeculus - - - Present - 1 ------Coleoptera Cerambycidae Ecyrus Ecyrus dasycerus - - - Present ------Coleoptera Cerambycidae Graphisurus Graphisurus fasciatus - - - Present ------Coleoptera Cerambycidae Momochamus Monochamus notalus - - - Present ------Coleoptera Cleridae Cymatodera Cymatodera bicolor - - - Present ------Coleoptera Curculionidae Hypera Hypera seriata Present - - - - 1 ------Coleoptera Curculionidae Polydrusus Polydrusus formosus Present ------1 - - - Coleoptera Curculionidae Polydrusus Polydrusus sericeus Present Present ------1 - - - Coleoptera Curculionoidea Phyllobius Phyllobius oblongus - Present ------1 - - - Coleoptera Dermestidae Attagenus Attagenus unicolor - Present ------Coleoptera Elateridae Ampedus Ampedus semicintus - - - Present ------Coleoptera Elateridae Melanotus Melanotus similis - - - Present 2 3 - 2 5 3 3 - Coleoptera Leiodidae Catops Catops luridipennis Present ------Coleoptera Scarabaeidae Amphimallon Amphmallon majalis - Present - - - 3 1 1 6 9 5 4 Coleoptera Scarabaeidae Aphodius Aphodius distinctus - - 1 ------Coleoptera Scarabaeidae Digitonthophagus Digitonthophagus gazella Present ------Coleoptera Scarabaeidae Phyllophaga Phyllophaga futilis - Present - - - - 1 4 4 5 1 2 Coleoptera Scirtidae Cyphon Cyphon laevipennis - Present ------Coleoptera Silphidae Nicrophorus Nicrophorus pustulatus - - - Present ------Coleoptera Staphylinidae Oxytelus Oxytelus sculptus - - 1 ------Diptera Anthomyiidae Delia Delia antiqua - Present - - 1 2 1 - 1 1 - - Diptera Calliphoridae Pollenia Pollenia pediculata - - 1 - 1 2 - 2 - - 2 - Diptera Chironomidae Ablabesmyia Ablabesmyia americana Present - - Present ------

Diptera Chironomidae Axarus Axarus sp. varvestris Present ------Diptera Chironomidae Chironomus Chironomus acidophilus Present - 3 - - 2 - 1 - - - - Diptera Chironomidae Chironomus Chironomus atroviridis Present - - - 4 ------Diptera Chironomidae Chironomus Chironomus decorus - Present - - 22 18 16 17 28 3 1 - Diptera Chironomidae Chironomus Chironomus dilutus - Present 6 - 6 1 - - - - - 2 Diptera Chironomidae Chironomus Chironomus entis - Present - - 14 11 19 11 2 2 2 5 Diptera Chironomidae Chironomus Chironomus maturus - - 3 - - 2 - - 1 - - - Diptera Chironomidae Dicrotendipes Dicrotendipes tritomus Present - - Present 1 2 ------Diptera Chironomidae Microtendipes Microtendipes pedellus Present - 2 ------Diptera Chironomidae Parachironomus Parachironomus delinificus Present ------Diptera Chironomidae Paracladopelma Paracladopelma winnelli - - - Present ------Diptera Chironomidae Polypedilum Polypedilum convictum - - 1 - - 1 ------Diptera Chironomidae Tanytarsus Tanytarsus mendax - - - Present ------Diptera Chironomidae Xenochironomus Xenochironomus zenolabis - - - Present ------Aedes sp. (incorectly classfied as Aedes Diptera Culicidae Aedes togoi) - - 1 - 3 7 - 1 - - - - Diptera Culicidae Aedes Aedes vexans Present - 1 - 4 11 4 5 2 1 1 2 Diptera Culicidae Anopheles Anopheles quadrimaculatus Present - 1 ------Diptera Culicidae Coquillettidia Coquillettidia perturbans Present - 2 - - 1 ------Diptera Culicidae Culex Culex pipiens - - - Present 1 4 ------Diptera Culicidae Culex Culex quinquefasciatus Present - - - - 1 ------Diptera Culicidae Culex Culex restuans - - 1 - 2 6 1 1 - - - - Diptera Culicidae Culiseta Culiseta inornata Present - - - 1 ------Diptera Culicidae Culiseta Culiseta minnesotae Present - - - - 1 2 1 3 - - - Diptera Culicidae Culiseta Culiseta morsitans Present ------Diptera Culicidae Ochlerotatus Ochlerotatus implicatus Present ------Diptera Culicidae Ochlerotatus Ochlerotatus provocans Present - 1 ------Diptera Culicidae Ochlerotatus Ochlerotatus punctor Present ------Diptera Culicidae Ochlerotatus Ochlerotatus sticticus Present ------Diptera Culicidae Ochlerotatus Ochlerotatus stimulans Present - 1 - - 3 - 1 3 - - 1 Diptera Drosophilidae Chymomyza Chymomyza amoena - Present - - - 1 ------Diptera Drosophilidae Drosophila Drosophila affinis - - 1 - - 1 ------Diptera Ephydridae Pelina Pelina canadensis - - 1 - 2 - - 3 - - - 2 Diptera Fanniidae Fannia Fannia canicularis - - 1 ------Diptera Hybotidae Platypalpus Platypalpus major - - 1 ------Diptera Limoniidae Helius Helius flavipes Present - 2 - 1 1 7 - 2 - 1 1 Diptera Muscidae Musca Musca autumnalis Present ------Diptera Muscidae Muscina Muscina pascuorum Present ------Diptera Muscidae Spilogona Spilogona suspecta Present ------Diptera Psychodidae Psychoda Psychoda alternata - - 1 ------Diptera Psychodidae Psychoda Psychoda trinodulosa Present ------Diptera Sciaridae Bradysia Bradysia hilaris Present ------Diptera Sepsidae Sepsis Sepsis punctum Present ------Diptera Simuliidae Simulium Simulium gouldingi - - - Present ------Diptera Simuliidae Simulium Simulium murmanum Present ------55

Diptera Simuliidae Simulium Simulium vittatum - - 1 ------Diptera Tabanidae Hybomitra Hybomitra epistates Present ------Diptera Tachinidae Actia Actia interrupta - - 2 ------Diptera Tipulidae Nephrotoma Nephrotoma ferruginea - - 1 - 3 9 - 1 6 1 2 4 Diptera Tipulidae Tipula Tipula furca - - - Present ------Diptera Tipulidae Tipula Tipula paludosa Present - - - 3 1 - 2 2 1 1 3 Ephemeroptera Baetidae Acentrella Acentrella parvula - - 6 ------Ephemeroptera Baetidae Cloeon Cloeon dipterum - - 1 - - 3 ------Ephemeroptera Baetidae Iswaeon Iswaeon anoka - - 3 ------Ephemeroptera Caenidae Caenis Caenis amica Present - 2 - 4 2 5 - 3 4 1 1 Ephemeroptera Caenidae Caenis Caenis anceps - - 1 ------Ephemeroptera Caenidae Caenis Caenis latipennis Present Present 3 - 1 1 3 2 7 4 4 - Ephemeroptera Caenidae Caenis Caenis punctata - - 1 - - - 3 - - - - - Ephemeroptera Caenidae Caenis Caenis youngi Present Present - Present - - 2 - - 1 - - Ephemeroptera Ephemerellidae Eurylaphella Eurylaphella temporalis Present Present ------Ephemeroptera Ephemeridae Hexagenia Hexagenia atrocaudata - - - Present - - - - 1 3 - 8 Ephemeroptera Ephemeridae Hexagenia Hexagenia limbata Present Present - Present 4 5 - 3 8 2 1 - Ephemeroptera Heptageniidae Leucrocuta Leocrocuta maculipennis - - - Present - - - - 2 - - - Ephemeroptera Heptageniidae Maccaffertium Maccaffertium mediopunctatum Present Present 3 Present 1 - 1 1 2 4 15 13 Ephemeroptera Heptageniidae Maccaffertium Maccaffertium modestum - - 4 - - - - - 1 3 4 1 Ephemeroptera Heptageniidae Maccaffertium Maccaffertium pudicum - - 1 ------2 - Ephemeroptera Heptageniidae Maccaffertium Maccaffertium pulchellum - - 1 - - - 1 2 3 5 6 2 Ephemeroptera Heptageniidae Maccaffertium Maccaffertium terminatum - - 6 - - 1 - - - 1 - - Ephemeroptera Heptageniidae Maccaffertium Maccaffertium vicarium Present ------1 2 - Ephemeroptera Heptageniidae Stenacron Stenacron interpunctatum Present Present 16 - - 1 - 1 8 11 11 9 Ephemeroptera Heptageniidae Stenonema Stenonema femoratum - Present 2 - 1 - - 3 - 2 2 2 Ephemeroptera Isonychiidae Isonychia Isonychia bicolor Present Present - Present - - - - - 1 1 - Ephemeroptera Isonychiidae Isonychia Isonychia rufa - - - Present - 2 ------Ephemeroptera Potamanthidae Anthopotamus Anthopotamus verticis - - 3 - - - - - 1 - - - Hemiptera Aphrophoridae Philaenus Philaenus spumarius - - 1 - - - - 2 - 1 - 2 Hemiptera Flatidae Metcalfa Metcalfa pruinosa - - 1 - 11 13 - 4 4 - 1 1 Hemiptera Miridae Lygus Lygus lineolaris - - - Present 8 22 1 9 2 2 - 1 Hemiptera Notonectidae Notonecta Notonecta kirbyi Present ------Hemiptera Pentatomidae Nezara Nezara antennata - - 1 ------Hymenoptera Formicidae Formica Formica ulkei - Present ------Hymenoptera Formicidae Lasius Lasius claviger - - 1 - - 1 - - - - 1 - Hymenoptera Formicidae Temnothorax Temnothorax ambiguus - - 1 ------1 - 1 Hymenoptera Formicidae Tetramorium Tetramorium caespitum - Present - - - 2 - 2 1 4 - - Lepidoptera Argyresthiidae Argyresthia Argyresthia alternatella Present ------Lepidoptera Argyresthiidae Argyresthia Argyresthia canadensis Present ------Lepidoptera Argyresthiidae Argyresthia Argyresthia thuiella Present ------Lepidoptera Batrachedridae Batrachedra Batrachedra praeangusta Present ------Lepidoptera Blastobasidae Blastobasis Blastobasis floridella Present - - - 1 ------Lepidoptera Blastobasidae Holcocera Holcocera chalcofrontella Present - 2 - - - - 1 - - - - Lepidoptera Blastobasidae Holcocera Holcocera immaculella - - - Present ------56

Lepidoptera Castniidae Paysandisia Paysandisia archon Present ------Lepidoptera Coleophoridae Blastobasis Blastobasis glandulella - 1 - - - - - 1 - - - - Lepidoptera Coleophoridae Coleophora Coleophora gaylussaciella - - 1 ------Lepidoptera Coleophoridae Coleophora Coleophora limosipennella Present ------Lepidoptera Coleophoridae Coleophora Coleophora pruniella Present - 1 ------Lepidoptera Coleophoridae Coleophora Coleophora serratella Present ------Lepidoptera Coleophoridae Coleophora Coleophora versurella - - - Present ------Lepidoptera Cosmopterigidae Limnaecia Limnaecia phragmitella Present - - - - 1 - 2 2 - - - Lepidoptera Crambidae Agriphila Agriphila straminella - - 1 ------Lepidoptera Crambidae Crambus Crambus agitatellus - Present - - - - - 1 - - - - Lepidoptera Crambidae Elophila Elophila obliteralis - - 1 - - 2 ------Lepidoptera Crambidae Herpetogramma Herpetogramma phaeopteralis - - - Present ------Lepidoptera Crambidae Ostrinia Ostrinia obumbratalis Present ------Lepidoptera Crambidae Ostrinia Ostrinia penitalis Present ------Lepidoptera Crambidae Palpita Palpita magniferalis Present ------Lepidoptera Crambidae Petrophila Petrophila bifascialis - - - Present ------Lepidoptera Dalceridae Dalcerides Dalcerides gugelmanni Present ------Lepidoptera Elachistidae Agonopterix Agonopterix pulvipennella - - 1 ------Lepidoptera Elachistidae Agonopterix Agonopterix robinella - - - Present - - 1 - - - - - Lepidoptera Elachistidae Machimia Machimia tentoriferella - - 2 ------Lepidoptera Elachistidae Machimia Machimia tentoriferella Present ------Lepidoptera Elachistidae Semioscopis Semioscopis packardella Present ------Lepidoptera Erebidae Aglaonice Aglaonice hirtipalpis Present ------Lepidoptera Erebidae Aristaria Aristaria theroalis Present ------Lepidoptera Erebidae Ctenucha Ctenucha virginica Present ------Lepidoptera Erebidae Idia Idia aemula Present ------Lepidoptera Erebidae Xenogenes Xenogenes gloriosa Present ------Lepidoptera Erebidae Zanclognatha Zanclognatha laevigata Present ------Lepidoptera Gelechiidae Aristotelia Aristotelia fungivorella Present ------Lepidoptera Gelechiidae Carpatolechia Carpatolechia fugitivella Present ------1 Lepidoptera Gelechiidae Carpatolechia Carpatolechia proximella Present ------Lepidoptera Gelechiidae Chionodes Chionodes mediofuscella Present ------Lepidoptera Gelechiidae Coleotechnites Coleotechnites atrupictella Present ------Lepidoptera Gelechiidae Coleotechnites Coleotechnites piceaella Present - - Present ------Lepidoptera Gelechiidae Coleotechnites Coleotechnites quercivorella Present ------Lepidoptera Gelechiidae Ezoteleia Ezoteleia dodecella - - - Present ------Lepidoptera Gelechiidae Filatima Filatima pseudacaciella - - - Present ------Lepidoptera Gelechiidae Metzneria Metzneria lappella Present ------1 - - - Lepidoptera Gelechiidae Scrobipalpa Scrobipalpa acuminatella Present ------Lepidoptera Gelechiidae Scrobipalpa Scrobipalpa atiplicella - Present - - - 2 ------Lepidoptera Gelechiidae Telphusa Telphusa longifasciella Present ------1 - - Lepidoptera Gelechiidae Xenolechia Xenolechia ontariensis Present ------1 1 - - - Lepidoptera Geometridae Hydriomena Hydriomena impluviata Present - - Present ------Lepidoptera Geometridae Lomographa Lomographa vestaliata - - 1 ------Lepidoptera Geometridae Lycia Lycia ursaria Present ------57

Lepidoptera Geometridae Metarranthis Metarranthis indeclinata Present ------Lepidoptera Geometridae Operophtera Operophtera bruceata Present ------Lepidoptera Geometridae Perizoma Perizoma alchemillatum Present ------Lepidoptera Gracillariidae Caloptilia Caloptilia negundella Present ------Lepidoptera Gracillariidae Caloptilia Caloptilia packardella Present ------Lepidoptera Hepialidae Korscheltellus Korscheltellus gracilis Present ------Lepidoptera Hepialidae Korscheltellus Korscheltellus lupulinus - Present ------1 - - - Lepidoptera Lasiocampidae Malacosoma Malacosoma americanum Present ------1 - 2 Lepidoptera Lasiocampidae Malacosoma Malacosoma disstria Present Present - Present - 1 - 1 - 1 - 1 Lepidoptera Limacodidae Euclea Euclea delphinii Present - - - - 1 ------Lepidoptera Limacodidae Lithacodes Lithacodes fasciola Present Present - Present - - - - 1 - - - Lepidoptera Momphidae Mompha Mompha brevivittella Present ------Lepidoptera Momphidae Mompha Mompha epilobiella Present ------Lepidoptera Noctuidae Achaea Achaea janata Present ------Lepidoptera Noctuidae Apamea Apamea devastator Present ------Lepidoptera Noctuidae Avitta Avitta discipuncta Present ------Lepidoptera Noctuidae Corgatha Corgatha omopis Present ------Lepidoptera Noctuidae Feltia Feltia jaculifera Present ------Lepidoptera Noctuidae Hypena Hypena sordidula - Present ------Lepidoptera Noctuidae Mythimna Mythimna turca Present ------Lepidoptera Noctuidae Pseudohermonassa Pseudohermonassa bicarnea - - 1 ------Lepidoptera Noctuidae Zale Zale galbanata - - - Present ------Lepidoptera Notodontidae Schizura Schizura ipomoeae Present ------Lepidoptera Oecophoridae Cosmaresta Cosmaresta charaxias Present ------Lepidoptera Oecophoridae Epicallima Epicallima argenticinctella - - 1 - - - - 2 - - - - Lepidoptera Oecophoridae Parocystola Parocystola holodryas Present ------Lepidoptera Oecophoridae Stereocheta Stereocheta sciocrossa Present ------Lepidoptera Oecophoridae Trichomoeris Trichomoeris amphichrysa Present ------Lepidoptera Pterophoridae Geina Geina sheppardi Present - 1 - - - - - 1 - - - Lepidoptera Pterophoridae Hellinsia Hellinsia homodactylus - Present ------Lepidoptera Pyralidae Sciota Sciota virgatella - - - Present ------Lepidoptera Sphingidae Amorpha Amorpha juglandis Present - - Present - - - 1 - - - - Lepidoptera Sphingidae Deidamia Deidamia inscriptum Present Present ------Lepidoptera Tineidae Diachorisia Diachorisia velatella - Present ------Lepidoptera Tineidae Homosetia Homosetia fasciella Present ------Lepidoptera Tineidae Praeacedes Praeacedes atomosella Present ------Lepidoptera Tischeriidae Coptotriche Coptotriche citrinipennella Present - - - 1 ------Lepidoptera Tortricidae Acleris Acleris chalybeana Present - - Present ------Lepidoptera Tortricidae Acleris Acleris curvalana Present ------Lepidoptera Tortricidae Acleris Acleris flavivittana Present ------Lepidoptera Tortricidae Acleris Acleris forbesana Present ------Lepidoptera Tortricidae Acleris Acleris forsskaleana Present - 1 - - 1 ------Lepidoptera Tortricidae Acleris Acleris negundana Present ------Lepidoptera Tortricidae Adoxophyes Adoxophyes negundana Present ------Lepidoptera Tortricidae Ancylis Ancylis divisana Present ------58

Lepidoptera Tortricidae Archips Archips argyrospila Present ------1 - - - - Lepidoptera Tortricidae Archips Archips purpurana - - 1 ------Lepidoptera Tortricidae Argyrotaenia Argyrotaenia alisellana - - 1 ------Lepidoptera Tortricidae Argyrotaenia Argyrotaenia juglandana Present ------Lepidoptera Tortricidae Argyrotaenia Argyrotaenia mariana Present - - - - - 1 - - 1 - - Lepidoptera Tortricidae Argyrotaenia Argyrotaenia quercifoliana Present - 1 - - - - 1 - - - - Lepidoptera Tortricidae Argyrotaenia Argyrotaenia velutinana - - 1 - - - - 1 - - - 1 Lepidoptera Tortricidae Catastega Catastega aceriella Present - - - - - 1 - - - - 1 Lepidoptera Tortricidae Choristoneura Choristoneura fractivittana Present - - - - 1 ------Lepidoptera Tortricidae Choristoneura Choristoneura fumiferana Present - - - - 1 - 3 - 3 - - Lepidoptera Tortricidae Choristoneura Choristoneura rosaceana - - 4 - 7 6 - 7 3 2 - 2 Lepidoptera Tortricidae Clepsis Clepsis clemensiana - - - Present ------Lepidoptera Tortricidae Clepsis Clepsis melaleucana Present ------1 - Lepidoptera Tortricidae Clepsis Clepsis virescana Present ------Lepidoptera Tortricidae Cnephasia Cnephasia geitalana - - - Present ------Lepidoptera Tortricidae Cnephasia Cnephasia stephensiana Present - - - - 2 - 2 - - 1 2 Lepidoptera Tortricidae Eana Eana osseana Present ------Lepidoptera Tortricidae Epinotia Epinotia indecorana Present ------Lepidoptera Tortricidae Epinotia Epinotia nisella Present ------Lepidoptera Tortricidae Epinotia Epinotia transmissana Present ------Lepidoptera Tortricidae Epinotia Epinotia trigonella Present - - - 1 ------Lepidoptera Tortricidae Eucosma Eucosma cataclystiana - Present ------Lepidoptera Tortricidae Eucosma Eucosma comatulana Present - - - 1 1 ------Lepidoptera Tortricidae Eucosma Eucosma derelecta Present Present - Present ------Lepidoptera Tortricidae Eucosma Eucosma tocullionana Present ------Lepidoptera Tortricidae Metendothenia Metendothenia separatana Present - - - - 1 ------Lepidoptera Tortricidae Olethreutes Olethreutes baccatana - - 2 - - 1 ------Lepidoptera Tortricidae Olethreutes Olethreutes glaciana Present ------Lepidoptera Tortricidae Pandemis Pandemis limitata Present - - - 4 5 - 4 1 2 - 1 Lepidoptera Tortricidae Phtheochroa Phtheochroa birdana - - - Present ------Lepidoptera Tortricidae Platynota Platynota exasperatana Present ------Lepidoptera Tortricidae Platynota Platynota idaeusalis Present - - - 1 - - 3 - - - - Lepidoptera Tortricidae Proteoteras Proteoteras aesculana - - 1 - - 1 3 2 4 - - - Proteoteras Lepidoptera Tortricidae willingana Proteoteras willingana - - 1 ------Lepidoptera Tortricidae Pseudoexentra Pseudoexentra cressoniana - - - Present ------Lepidoptera Tortricidae Pseudoexentra Pseudoexentra marcana - - - Present ------Lepidoptera Tortricidae Sparganothis Sparganothis diluticostana - - 2 - 1 - 1 - - - - - Lepidoptera Tortricidae Sparganothis Sparganothis pettitana Present Present - Present - - - 1 - - - - Lepidoptera Tortricidae Spilonota Spilonota laricana Present - - - - 1 ------Lepidoptera Tortricidae Syndemis Syndemis afflictana - - 1 ------Lepidoptera Tortricidae Zeiraphera Zeiraphera canadensis Present ------1 - - - Mantodea Mantidae Mantis Mantis regiosa - - - Present - 1 ------Neuroptera Hemerobiidae Hemerobius Hemerobius atrifrons Present ------Neuroptera Hemerobiidae Hemerobius Hemerobius stigma - - - Present ------59

Orthoptera Gryllidae Gryllus Gryllus pennsylvanicus - - - Present ------Trichoptera Glossosomatidae Glossosoma Glossosoma intermedium Present ------Trichoptera Helicopsychidae Helicopsyche Helicopsyche borealis Present Present - Present ------1 Trichoptera Helicopsychidae Macrostemum Macrostemum zebratum - - - Present - - - - - 1 - - Trichoptera Hydropsychidae Arctopsyche Arctopsyche ladogensis Present ------Trichoptera Hydropsychidae Ceratopsyche Ceratopsyche bronta - - 11 - - 2 - - - 8 3 7 Trichoptera Hydropsychidae Ceratopsyche Ceratopsyche morosa - Present 1 - - 1 - - - - 1 2 Trichoptera Hydropsychidae Ceratopsyche Ceratopsyche morosa - - 1 - - 1 - - - - 1 2 Trichoptera Hydropsychidae Ceratopsyche Ceratopsyche sparna - - 4 ------1 - - Trichoptera Hydropsychidae Cheumatopsyche Cheumatopsyche analis - - 1 - 1 - - - - 1 - - Trichoptera Hydropsychidae Cheumatopsyche Cheumatopsyche campyla - - 1 Present - - - 1 - 3 - 2 Trichoptera Hydropsychidae Hydropsyche Hydropsyche betteni - - 3 ------4 - 1 Trichoptera Hydropsychidae Hydropsyche Hydropsyche cuanis - - 1 ------Trichoptera Hydropsychidae Hydropsyche Hydropsyche phalerata - - 12 - 1 1 - 2 - 6 - - Trichoptera Hydropsychidae Hydropsyche Hydropsyche placoda - - 1 ------1 - - Trichoptera Hydropsychidae Hydropsyche Hydropsyche scalaris - - 2 - - 1 - - - 1 - - Trichoptera Hydropsychidae Hydropyche Hydropyche betteni - Present 2 ------4 - 1 Trichoptera Hydropsychidae Triaenodes Triaenodes commatus - Present ------Trichoptera Hydropsychidae Triaenodes Triaenodes injustus - Present ------Trichoptera Hydropsychidae Triaenodes Triaenodes tardus - Present ------Trichoptera Leptoceridae Ceraclea Ceraclea transversa - - - Present ------Trichoptera Leptoceridae Mystacides Mystacides interjectus - - 1 ------Trichoptera Leptoceridae Nectopsyche Nectopsyche albida Present ------Trichoptera Leptoceridae Oecetis Oecetis cinerascens Present - - - 1 - 3 - - 1 - - Trichoptera Leptoceridae Triaenodes Triaenodes injustus Present - - - 1 2 7 4 - - - - Trichoptera Leptoceridae Triaenodes Triaenodes tardus Present - 1 - 1 2 1 - - - - 1 Trichoptera Limnephilidae Anabolia Anabolia binaculata - Present ------Trichoptera Limnephilidae Limnephilus Limnephilus externus - - 1 ------Trichoptera Limnephilidae Limnephilus Limnephilus indivisus - - 2 - - - - 5 7 2 3 3 Trichoptera Limnephilidae Limnephilus Limnephilus submonilifer - - 1 - 1 9 - 1 2 1 2 6 Trichoptera Limnephilidae Nemotaulius Nemotaulius hostilis - Present ------1 - Trichoptera Limnephilidae Pycnopsyche Pycnopsyche guttifera - - 1 ------4 - Trichoptera Philopotamidae Chimarra Chimarra obscura - - 8 ------4 - - Trichoptera Phryganeidae Agrypnia Agrypnia colorata Present ------Trichoptera Phryganeidae Agrypnia Agrypnia deflata Present ------Trichoptera Phryganeidae Agrypnia Agrypnia vestita - Present 1 - 1 - - 3 3 1 1 1 Trichoptera Phryganeidae Phryganea Phryganea cinerea Present - - - 2 - - - 1 - - - Trichoptera Phryganeidae Phryganea Phryganea sayi - - 1 - - - - - 2 - - - Trichoptera Polycentropodidae Neureclipsis Neureclipsis crepuscularis - - 1 - - 1 ------Trichoptera Polycentropodidae Polycentropus Polycentropus cinereus Present ------Trichoptera Polycentropodidae Polycentropus Polycentropus pentus Present ------