Feeding Strategies of the Little Brown Bat Myotis Lucifugus in Southernnewhampshire

Abstract

Characterizing habitat use is a key component to quantifying the niche, ecological interactions, and conservation needs of a species. Habitat selection is the disproportionate use of habitat types, whereby animals select higher-quality habitats within a landscape mosaic. For insectivorous bats, selection of foraging habitat is likely due to variation between habitat types in the distribution and abundance of prey, as well as differences in how effectively bats can move through, and forage in, different landscapes. Due to their cryptic nature and rapid nocturnal flight, detailed knowledge about fine-scale habitat selection of bat species is lacking. We used data-logging telemetry receivers to assess selection of foraging habitat by the little brown bat, Myotis lucifugus, in the Badlands and Missouri River Valley of North Dakota. Bats were captured at maternity roosts, fitted with radiotransmitters, and tracked for 11 nights at each site. Habitat selection was assessed based on selection ratios of used and available proportions of habitat, which were characterized in terms of both composition and structure. Eigenanalysis of selection ratios was used to further evaluate individual variation in habitat selection. Foraging female M. lucifugus primarily selected edge habitats and nearby water sources. Pregnant bats selected edges bordering grass or herbaceous habitats. Lactating bats selected water and edge habitat within close proximity to the roost. Selection of nearby water resources by lactating bats under the constraints of nursing is consistent with previous studies. While there were ecologically consistent trends across bats, individuals varied in some aspects of their habitat selection.

For effective conservation and management of wildlife populations, detailed information is needed about habitat use of a species. This information is also key for understanding ecological interactions and evolutionary implications of species' behavior. Habitat composition and structure are important components of ecological niches and foraging behavior (Arlettaz 1999; Sattler et al. 2007). Here, we define habitat composition as categorical land cover attributes (e.g., evergreen forest, grassland) and habitat structure as a description of vegetation density (e.g., cluttered forest, edge or gap, or open habitat) or canopy cover. Measures of habitat use in terms of composition or structure are particularly valuable for assessing the importance of specific habitat types or conditions to a given species.

Habitat composition plays a key role in the distribution of insect prey and foraging strategies of bats, as well as the partitioning of resources by sympatric bat species (Arlettaz 1999; Bergeson et al. 2013). For example, Arlettaz (1999) found that sympatric sister species, Myotis myotis and Myotis blythii, spatially segregate when foraging based on differences in habitat requirements of preferred prey. Similarly, Bergeson et al. (2013) found that sympatric Myotis sodalis and Myotis lucifugus partition foraging resources behaviorally and through variation in selection of land cover.

In addition to habitat composition, habitat structure has also been studied in bats, with a strong focus on understanding how morphological features and physiological states of a given species impact the type of habitat structure in which they are primarily found. For example, Kalcounis and Brigham (1995) found that heavier M. lucifugus with greater wing loading foraged in lower-clutter habitat. Similarly, Adams (1996) found that juvenile M. lucifugus with higher wing aspect ratios and lower wing loading exploit more diverse and cluttered habitat compared to other juveniles. Further, a large body of work has focused on classifying bats into functional groups based on echolocation call structure, morphology, and flight behavior as they correlate with habitat structure and habitat use (Aldridge and Rautenbach 1987; Schnitzler and Kalko 2001; Schnitzler et al. 2003). However, resource use may not be predictable by echolocation or morphology alone (Arlettaz 1999; Davidson-Watts et al. 2006), and combining data for such functional groups, guilds, or even sexes may yield ambiguous or spurious results in studies of selection (Broders et al. 2006). Overall, studies of habitat use by bats are abundant in the ecological literature, yet detailed habitat characterizations are often limited, and knowledge of foraging habitat selection of many bat species is lacking.

Habitat selection is the decision-making process through which animals choose resources relative to their availability or accessibility (Johnson 1980; Garshelis 2000). It is presumed that species should select habitats that best meet their ecological and behavioral needs. A variety of study designs have been developed to investigate habitat selection (Garshelis 2000; Manly et al. 2002). The use-availability design identifies habitat selection as occurring when habitats are used disproportionately to their availability (Garshelis 2000; Manly et al. 2002). A significant challenge in habitat selection studies is defining habitats so that they are ecologically relevant and appropriately partitioned so that selection can be measured for a given species (Garshelis 2000).

The volant, nocturnal nature and relatively small size of bats make them particularly problematic for assessing habitat selection (Henry et al. 2002; Gannon et al. 2003). With recent advances in spatial analysis of habitat via GIS, habitat selection studies have progressed. However, the majority of such research on bats includes limited habitat characterizations, using only land cover attributes available in GIS datasets, which are not necessarily reflective of habitat structures that are important to foraging bats. Also, such GIS land cover datasets typically represent coarse landscape features that may lack the detail required for ecologically meaningful assessments of habitat use (Brambilla et al. 2009). Fewer studies have incorporated habitat structure, with those studies generally separating analysis of habitat structure from composition (Napal et al. 2010, 2013; Buckley et al. 2013; Arrizabalaga-Escudero et al. 2014; Ripperger et al. 2015). Further, most studies do not evaluate individual variation in habitat selection (Hillen et al. 2011), and therefore selection may not be detectable at the population level if individuals or sexes exhibit alternative selection strategies (Garshelis 2000).

The goal of this study was to assess selection of foraging habitat by pregnant and lactating female little brown bats, M. lucifugus. We radiotracked bats using autonomous telemetry data-logging receivers, which allow for simultaneous, long-term data collection on multiple bats with minimal researcher input. While this type of autonomous telemetry has been used to assess bat migration (McGuire et al. 2012) and various aspects of spatial ecology in other taxa (Bridger et al. 2001; Drewe et al. 2012; Ryder et al. 2012), it has not previously been used to study habitat selection by bats. Our specific objectives were to: 1) assess selection of foraging habitat by M. lucifugus in terms of habitat composition and structure in tandem, and 2) assess individual variation in habitat selection by M. lucifugus.

Materials and Methods

Study species.

The little brown bat is an insectivorous bat (6–11 g—van Zyll deJong 1985) widely distributed throughout most of North America (Fenton and Barclay 1980). M. lucifugus feed on a variety of small insects (3–10 mm long—Anthony and Kunz 1977), often in cluttered habitats near or over water (Fenton and Bell 1979; Fenton and Barclay 1980; Kalcounis and Brigham 1995; Adams 1996; Adams and Thibault 2006). Maternity colonies vary in size, ranging from a few to over a thousand individuals. Roosts are often found in man-made structures such as old buildings (Fenton and Barclay 1980; Anthony et al. 1981), and are usually near bodies of water (Kunz et al. 1995).

Study sites.

Data were collected at 2 nursery colonies of M. lucifugus: 1) a picnic shelter in the North Unit of Theodore Roosevelt National Park (TRNP; 47°35′41.72″N, 103°20′11.79″W), North Dakota, United States, containing ~50 adult female bats, and 2) a bat house at Cross Ranch State Park (CRSP; 47°12′44.07″N, 100°59′57.87″W), North Dakota, United States, containing ~40 adult female bats. The TRNP site consisted of cottonwood (Populus deltoides) dominated riparian forest surrounded by badlands. The CRSP site consisted of cottonwood-dominated riparian forest surrounded by upland prairie, pasture, and agricultural fields. The habitat of both sites was relatively similar in composition and structure at the scale of sampling in this study. Sites were approximately 112 miles apart and were selected based on previous work identifying these areas as sites of higher abundance of M. lucifugus in North Dakota (Nelson et al. 2015).

Telemetry.

Bats were captured using mist nets (Kunz and Parsons 2009) placed at roost entrances. The species, sex, age, mass, and forearm length were assessed for all captured animals. Trapping and tracking of bats was avoided around the time parturition was expected, which occurs mid-late June to early July (Farrrell and Studier 1973; Barclay 1982; Kunz et al. 1983). Bats selected for radiotracking were fitted with digitally encoded transmitters (Lotek NTQB-1 Nano Tags, Lotek Wireless Inc., Newmarket, Ontario, Canada) attached to trimmed mid-dorsal hair over the scapulae using surgical skin adhesive. Each transmitter has a unique digital identification (ID) signature, although all transmitters emit the same frequency; this allows for simultaneous monitoring of multiple transmitters, which is not possible with traditional radiotelemetry systems. Transmitters weighed 0.29 g (< 5% of the bat's body mass—Aldridge and Brigham 1988) and had a pulse rate of 2 s, resulting in a battery life of approximately 12 days.

Upon release, bats were tracked using a telemetry array of 3 automated receiving towers. Each tower consisted of a data-logging receiver (SRX DL, Lotek Wireless Inc.) connected to an antenna tower affixed with a pair of 5-element Yagi antennas raised ~5 m in the air. Antennas were monitored on alternating 4-s cycles, which ensures detection if transmitters are within detectable range. The data loggers continuously recorded all transmitter detections and logged the transmitter ID, date and time of detection, antenna number, and signal strength. Calibration tests of line-of-sight detection gave a maximum detection range of approximately 400 m in the direction an individual antenna was oriented and 150 m to the side and rear. Telemetry arrays were strategically positioned so that the sampling range encompassed as much of the available area near the roost as possible. Each antenna was oriented to monitor a separate portion of the sampling area, although some overlap occurred (Fig. 1). To ensure continuous monitoring, the operational status of each data logger was regularly checked and data from periods of time when batteries failed were excluded from analysis.

Fig. 1.

A) Map of Theodore Roosevelt National Park in North Dakota, United States, showing locations of bat roost (bat symbol), data loggers (black dots), and sampling areas (outlined in black) overlaid on digitized habitat types. B) Map of Cross Ranch State Park in North Dakota, United States, showing locations of bat roost (bat symbol), data loggers (black dots), and sampling areas (outlined in black) overlaid on digitized habitat types.

A) Map of Theodore Roosevelt National Park in North Dakota, United States, showing locations of bat roost (bat symbol), data loggers (black dots), and sampling areas (outlined in black) overlaid on digitized habitat types. B) Map of Cross Ranch State Park in North Dakota, United States, showing locations of bat roost (bat symbol), data loggers (black dots), and sampling areas (outlined in black) overlaid on digitized habitat types.

All research on live animals followed guidelines for the use of wild mammals in research approved by the American Society of Mammalogists (Sikes et al. 2011) and was approved by the North Dakota State University Institutional Animal Care and Use Committee (Protocol # A15032).

Habitat selection.

Locations of data loggers and antenna detection ranges were mapped using GIS (ArcMap, ArcGIS version 10.3). Habitat types were designated using 20 categories based on habitat composition and structure (Table 1). Habitat within detection range was manually digitized as a set of polygons using georeferenced aerial imagery corroborated by manual inspection of habitats done during sampling (Fig. 1). From these data, the proportional area of each habitat type within each antenna's sampling range could be determined. Telemetry data were filtered to only include detections during a window of 2 h after sunset, as this corresponds with the primary peak in foraging activity of M. lucifugus (Anthony and Kunz 1977; Anthony et al. 1981; Henry et al. 2002). We assumed that animals were selected independently with equal probability from a single population. Therefore, the animals can provide the needed replication to make inferences at the population level without concern for autocorrelation of location estimates (Otis and White 1999).

Table 1.

Habitat type Description
Mixed forest Mixed-species forest; highly cluttered understory
Cottonwood forest Cottonwood-dominated forest; more sparsely distributed than mixed forest; medium clutter
Grass and herb Open grassland and herbaceous vegetation
Crops Open areas of agriculturally converted land cover
Mowed Open areas of mowed grass; predominately in campground areas
Barren Open-ground areas; characteristic of river sandbars and banks or badland bluff faces
Shrubs Highly vegetated but lacking canopy cover
Marsh Seasonal wetlands associated with drainages or streams
Grass and herb edge Edge habitats formed from distinct boundaries between forest and associated open habitats; water edge (water) is predominately associated with river habitat
Water edge
Crop edge
Developed or mowed edge
Corridor
Marsh edge
River Aquatic habitats assigned by appropriate definitions
Pond
Stream
Buildings Including picnic shelters
Roadway Either paved or gravel roads
Developed other Miscellaneous anthropogenic structures
Habitat type Description
Mixed forest Mixed-species forest; highly cluttered understory
Cottonwood forest Cottonwood-dominated forest; more sparsely distributed than mixed forest; medium clutter
Grass and herb Open grassland and herbaceous vegetation
Crops Open areas of agriculturally converted land cover
Mowed Open areas of mowed grass; predominately in campground areas
Barren Open-ground areas; characteristic of river sandbars and banks or badland bluff faces
Shrubs Highly vegetated but lacking canopy cover
Marsh Seasonal wetlands associated with drainages or streams
Grass and herb edge Edge habitats formed from distinct boundaries between forest and associated open habitats; water edge (water) is predominately associated with river habitat
Water edge
Crop edge
Developed or mowed edge
Corridor
Marsh edge
River Aquatic habitats assigned by appropriate definitions
Pond
Stream
Buildings Including picnic shelters
Roadway Either paved or gravel roads
Developed other Miscellaneous anthropogenic structures

Table 1.

Habitat type Description
Mixed forest Mixed-species forest; highly cluttered understory
Cottonwood forest Cottonwood-dominated forest; more sparsely distributed than mixed forest; medium clutter
Grass and herb Open grassland and herbaceous vegetation
Crops Open areas of agriculturally converted land cover
Mowed Open areas of mowed grass; predominately in campground areas
Barren Open-ground areas; characteristic of river sandbars and banks or badland bluff faces
Shrubs Highly vegetated but lacking canopy cover
Marsh Seasonal wetlands associated with drainages or streams
Grass and herb edge Edge habitats formed from distinct boundaries between forest and associated open habitats; water edge (water) is predominately associated with river habitat
Water edge
Crop edge
Developed or mowed edge
Corridor
Marsh edge
River Aquatic habitats assigned by appropriate definitions
Pond
Stream
Buildings Including picnic shelters
Roadway Either paved or gravel roads
Developed other Miscellaneous anthropogenic structures
Habitat type Description
Mixed forest Mixed-species forest; highly cluttered understory
Cottonwood forest Cottonwood-dominated forest; more sparsely distributed than mixed forest; medium clutter
Grass and herb Open grassland and herbaceous vegetation
Crops Open areas of agriculturally converted land cover
Mowed Open areas of mowed grass; predominately in campground areas
Barren Open-ground areas; characteristic of river sandbars and banks or badland bluff faces
Shrubs Highly vegetated but lacking canopy cover
Marsh Seasonal wetlands associated with drainages or streams
Grass and herb edge Edge habitats formed from distinct boundaries between forest and associated open habitats; water edge (water) is predominately associated with river habitat
Water edge
Crop edge
Developed or mowed edge
Corridor
Marsh edge
River Aquatic habitats assigned by appropriate definitions
Pond
Stream
Buildings Including picnic shelters
Roadway Either paved or gravel roads
Developed other Miscellaneous anthropogenic structures

Because the exact location of a bat within an antenna's sampling range cannot be accurately determined, habitat use was assigned by dividing the number of detections for an antenna proportionally among the habitats available within that sampling range. The counts per habitat were then summarized across all of the antennas as a representation of habitat use for that bat. The drawback of this method is that the strength of relative selection for or against any particular habitat type is diminished because habitat use is inevitably assigned to habitat types that may not actually be used, but are co-located with habitat types for which there is positive selection. Despite this feature, selection is still detectable as long as the proportions of habitat are not uniform across all antenna sampling ranges. An additional complicating factor is that the antenna sampling ranges had some level of overlap, especially antennas attached to the same data logger. The nature of the detection system means that bats cannot be simultaneously detected on shared antennas, as the data logger systematically switches between monitoring each of the antennas individually. Hence, a bat's location cannot be confidently narrowed down to the overlapped habitat, and habitat use can only be assigned to each antenna individually. To address this issue, we used the proportions of habitat within each individual antenna's sampling range, summarized across all antennas, as the available habitat for analysis.

To assess habitat selection, selection ratios (w i ) of used versus available habitat were calculated (Manly et al. 2002). In the absence of selection, a ratio equal to 1 is expected, while selection ratios greater than 1 reflect positive selection for that habitat. Habitats are subsequently ranked according to their selection ratio. There are 3 types of use-availability designs for assessing habitat selection: design I = animals are pooled and habitat use and availability are measured at the population level; design II = habitat use is measured for each animal and habitat availability is measured at the population level; design III = habitat use and availability are measured for each animal (Manly et al. 2002). Since bats at each site shared a roost and could potentially share foraging sites, analysis of study design II or III could be applied to our data by simply using the same habitat availability for all animals under the design III framework. We conducted both analyses on our data so that nonrandom habitat use could be tested at both the population and individual level. Following Manly et al. (2002), chi-square goodness-of-fit tests were used to test for identical use of habitat by all animals, habitat selection by individuals, and independence of habitat use and availability (overall habitat selection). To assess selection of individual habitats, Bonferroni confidence intervals were constructed for individually estimated proportions of habitat use and availability. Pairwise comparisons between selection ratios were then evaluated for statistical significance based on Bonferroni confidence intervals. For all tests, α was set to 0.05, and the confidence intervals were computed at the 95% level. To run all habitat selection analyses, we used the package "adehabitat" for R software (Calenge 2006) with R Studio version 0.98.1028 (RStudio Team 2015).

Because all animals may not exhibit the same patterns of habitat selection, we also analyzed our data at the individual level. To evaluate individual variation in habitat selection, we conducted eigenanalysis of selection ratios (Calenge and Dufour 2006), which is useful for this purpose when there is a high number of animals and habitat types. This analysis undertakes an additive linear partitioning of the White and Garrott (1990) statistic, maximizing the difference between habitat use and availability on the 1st factorial axis (Calenge and Dufour 2006). If all animals select the same habitat types, then the majority of variation in selection is explained on the 1st axis. However, when there is high variability in selection, the explained variation is distributed across multiple axes (Calenge and Dufour 2006). Therefore, variation on 1 factorial axis may reveal differing intensities of selection for the same habitat types, while variation on 2 or more axes may reveal separate modes of selection or that selection strategies differ across animals.

Results

Bat captures.

At TRNP, we captured bats on 24 July 2014 and tagged 11 adult female M. lucifugus. We were able to gather sufficient data for analysis of 7 individuals over the subsequent 11 nights. At CRSP, we captured bats on 4 June 2015 and tagged 18 adult female M. lucifugus, with sufficient data being gathered from 17 of these animals over an 11-night period. Given the capture dates combined with visual inspection of the bats and roosts, sampling corresponded with mid-gestation in CRSP and mid- to late-lactation in TRNP.

Habitat selection.

Tests of overall habitat selection were highly significant under both design II and III frameworks. For simplicity, we report results under design II for the test of overall habitat selection. At both sites, bats did not use habitat in equal proportion to availability (TRNP: χ2 = 1115.5, d.f. = 98, P < 0.001; CRSP: χ2 = 20,189.5, d.f. = 306, P < 0.001) and there were significant differences in selection between habitat types (Supplementary Data SD1 and SD2). Only 1 of 24 bats in our study did not exhibit statistically significant habitat selection (bat ML173 from TRNP; χ2 = 4.6, d.f. = 14, P = 0.09).

In TRNP, bats selected marsh, mixed forest, shrubs, and stream habitat, as well as edge habitat bordering roadways and mowed grass (Fig. 2). In CRSP, bats showed strong selection of edge habitat bordering un-mowed grass and herb habitat (Fig. 3). Barren habitat was also selected at both sites but this habitat type likely lacks ecological relevance to bats (see "Discussion"). Despite trends in selection at each site, bats did not exhibit identical use of habitat (TRNP: χ2 = 305.4, d.f. = 84, P < 0.001; CRSP: χ2 = 6584.3, d.f. = 288, P < 0.001). Most notably, there was an overall trend toward selection of river and river edge habitat at both TRNP and CRSP, but selection of these habitats was highly variable between individuals (Figs. 2 and 3). Results of eigenanalysis revealed that the majority of individual variation in habitat selection was accounted for on the 1st factorial axis (79.3% at TRNP and 84.3% at CRSP). Adding a 2nd factor increased the variance explained to 97.6% at TRNP and 99.5% at CRSP.

Fig. 2.

Selection ratios (wi) for habitats used by little brown bats (Myotis lucifugus), with Bonferroni confidence intervals for each habitat, in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014. Habitats are ranked in descending order from left to right by selection ratio. Gray line at wi = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Selection ratios (w i ) for habitats used by little brown bats (Myotis lucifugus), with Bonferroni confidence intervals for each habitat, in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014. Habitats are ranked in descending order from left to right by selection ratio. Gray line at w i = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Fig. 3.

Selection ratios (wi) for habitats used by little brown bats (Myotis lucifugus), with Bonferroni confidence intervals for each habitat, in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015. Habitats are ranked in descending order from left to right by selection ratio. Gray line at wi = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Selection ratios (w i ) for habitats used by little brown bats (Myotis lucifugus), with Bonferroni confidence intervals for each habitat, in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015. Habitats are ranked in descending order from left to right by selection ratio. Gray line at w i = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

For TRNP, eigenanalysis confirmed the overall trends in habitat selection found in the analysis of selection ratios (Fig. 4). All but 1 individual bat exhibited similar patterns of habitat selection. However, as previously noted, habitat selection by this individual (bat ML173) was not significant (Fig. 5). As confirmed by individual selection ratios (Fig. 5), eigenanalysis showed that the remaining bats exhibited varying intensities of selection between river, water edge, corridor, and stream habitats (Fig. 4). Specifically, most individuals selected stream habitat but 2 individuals did not select the river and corridor habitats (Fig. 5).

Fig. 4.

Results of the eigenanalysis of selection ratios highlighting habitat selection by 7 little brown bats (Myotis lucifugus) in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014. Top: habitat type loadings on the first 2 factorial axes. Bottom: positions of individual bats on the factorial plane.

Results of the eigenanalysis of selection ratios highlighting habitat selection by 7 little brown bats (Myotis lucifugus) in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014. Top: habitat type loadings on the first 2 factorial axes. Bottom: positions of individual bats on the factorial plane.

Fig. 5.

Selection ratios (wi) of individual little brown bats (Myotis lucifugus) in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014, for all habitat types connected by lines to highlight trends in habitat selection. Bat ML173, which exhibited nonsignificant habitat selection, is represented by the bold black line. All other individuals represented by gray lines. Black line located at wi = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Selection ratios (w i ) of individual little brown bats (Myotis lucifugus) in Theodore Roosevelt National Park, North Dakota, United States, 24 July–6 August 2014, for all habitat types connected by lines to highlight trends in habitat selection. Bat ML173, which exhibited nonsignificant habitat selection, is represented by the bold black line. All other individuals represented by gray lines. Black line located at w i = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Similarly, for CRSP, eigenanalysis confirmed the overall trends in selection found in the analysis of selection ratios and revealed variation among individuals in selection of river, water edge, and corridor habitat (Fig. 6). All bats selected grass and herb edge habitat. The majority of bats (14 individuals) selected the river and its associated edge habitat. However, as confirmed by individual selection ratios (Fig. 7), 3 individuals strongly selected corridor and used the river and water edge in lesser proportion than available, resulting in the division across axes seen in the eigenanalysis (Fig. 6).

Fig. 6.

Results of the eigenanalysis of selection ratios highlighting habitat selection by 17 little brown bats (Myotis lucifugus) in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015. Top: habitat type loadings on the first 2 factorial axes. Bottom: positions of individual bats on the factorial plane.

Results of the eigenanalysis of selection ratios highlighting habitat selection by 17 little brown bats (Myotis lucifugus) in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015. Top: habitat type loadings on the first 2 factorial axes. Bottom: positions of individual bats on the factorial plane.

Fig. 7.

Selection ratios (wi) of individual little brown bats (Myotis lucifugus) in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015, for all habitat types connected by lines to highlight trends in habitat selection. Bats ML16, ML161, and ML162 are represented by bold black lines. All other individuals represented by gray lines. Black line located at wi = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Selection ratios (w i ) of individual little brown bats (Myotis lucifugus) in Cross Ranch State Park, North Dakota, United States, 4–16 June 2015, for all habitat types connected by lines to highlight trends in habitat selection. Bats ML16, ML161, and ML162 are represented by bold black lines. All other individuals represented by gray lines. Black line located at w i = 1 indicates that habitat is being used in proportion to its availability (neutral selection).

Discussion

Bats at both TRNP and CRSP exhibited selection of edge habitats as well as selection (with significant variation) of the river and its associated edge habitat. Barren habitat was also positively selected; however, in TRNP, this habitat was spatially limited and roughly equally distributed between portions of the river embankment and sand bars, and bluff faces (Fig. 1A) while in CRSP this habitat was limited solely to small portions of the river embankment (Fig. 1B). Therefore, selection of barren habitat is likely attributed to its association with other positively selected habitats, such as the river.

In TRNP, selection of marsh and shrub habitat seemed initially counter-intuitive, but inspection of the spatial distribution of these habitat types provides insight into this pattern. The majority of these habitats were spatially associated with a portion of the stream. Together, the marsh and stream habitats represent the water sources closest to the roost in TRNP. The relatively weaker selection of stream habitat may also be explained by its spatial distribution. Specifically, the primary stream passes through roughly one-half of the sampling area, so measurable selection for this habitat type may have been limited by its relative abundance across less-used portions of the sampling area.

Patterns of selection at TRNP may be at least partially attributed to the reproductive condition of bats at the time of study. During sampling, ~2-week-old pups were captured at the roost, and the sampling date corresponds to mid-to-late lactation (Farrrell and Studier 1973; Fenton and Barclay 1980; Anthony et al. 1981; Henry et al. 2002). Energy demands are highest during lactation for M. lucifugus (Fenton and Barclay 1980; Kurta et al. 1989a; Kunz et al. 1995) and lactation represents a substantial strain on maintaining water balance (Kurta et al. 1989b; Kunz et al. 1995). Also, M. lucifugus exhibit a substantial decrease in home range size during lactation (~50%), making frequent trips back to the roost to nurse (Barclay 1982; Henry et al. 2002). Given that aquatic habitats provide not only drinking water but a high abundance of insect prey that M. lucifugus regularly exploit (Anthony and Kunz 1977; Fenton and Bell 1979; Fenton and Barclay 1980), it is not surprising that lactating M. lucifugus in our study selected such habitat in close proximity to the maternity roost.

In contrast with CRSP, bats in TRNP selected edge bordering roads or mowed grass. In TRNP, the campground roads and mowed camp sites have formed notably more edge habitat (of this type), relative to CRSP, in close proximity to the roost. One factor potentially contributing to these selection differences stems from prey availability. Insect control measures are typically conducted in campground areas of CRSP but not in TRNP. This could potentially drive foraging away from campground areas in CRSP, at a time when prey is a limiting factor for pregnant M. lucifugus (Anthony and Kunz 1977; Anthony et al. 1981; Henry et al. 2002). Despite these differences, bats in TRNP and CRSP clearly exhibited strong selection of edge habitats. Also, bats at both sites selected their respective rivers and associated edge habitats, although individuals exhibited a great deal of variation in selection of these habitats.

Previous studies have investigated variation in habitat use or selection between groups of individuals classified by factors such as age, sex, reproductive condition, or morphology (Aldridge and Rautenbach 1987; Kalcounis and Brigham 1995; Adams 1996; Hillen et al. 2011). However, little attention has been paid to variation among individuals (Hillen et al. 2011). We found that inconsistencies in overall habitat selection can be accounted for by differing intensities of selection of specific habitats. In these cases, differing selection among individuals can be explained by bats using different subsets of ecologically similar habitat. Edge habitats and water resources were strongly selected by M. lucifugus, with variation at the microhabitat scale delineating potential individual preferences for specific edge compositions and water habitats. For example, all bats in CRSP selected grass and herb edge, yet only 3 individuals selected corridor habitat. Also, all bats in TRNP selected water resources, yet 2 individuals selected stream over river while their cohorts used both habitats.

Overall, we found that female M. lucifugus selected edge habitats and water resources, which is consistent with previous observations and findings (Fenton and Bell 1979; Kalcounis and Brigham 1995; Bergeson et al. 2013). We found that bats exhibited habitat selection on a microhabitat scale when habitats are characterized by both composition and structure in tandem; specifically, not all edge habitats or water resources were selected equally, with the composition of edge habitat influencing patterns of selection. Future studies of habitat selection by bats should consider the relationship between habitat composition and structure to avoid overlooking important microhabitat associations. Further work about habitat selection by male bats, verification of selection differences based upon reproductive state, and individual variation in habitat selection would also be of value for gaining a better understanding of how bats use the landscape.

Supplementary Data

Supplementary Data SD1.—Habitat type matrix for Theodore Roosevelt National Park (TRNP) in North Dakota, United States, indicating whether a habitat in a given row was selected more or less (sign + or −) than habitats in the corresponding columns. A triple sign (+++, −−−) indicates significant (P < 0.05) selection.

Supplementary Data SD2.—Habitat type matrix for Cross Ranch State Park (CRSP) in North Dakota, United States, indicating whether a habitat in a given row was selected more or less (sign + or −) than habitats in the corresponding columns. A triple sign (+++, −−−) indicates significant (P < 0.05) selection.

Acknowledgments

We would like to acknowledge P. Barnhart for invaluable assistance in field data collection. We thank the wildlife managers from the North Dakota Game and Fish Department, National Park Service, and North Dakota Parks and Recreation, who provided logistical assistance and permits for this project. This research was funded by a North Dakota Game and Fish Department State Wildlife Grant (SWG T2-5-R) and the National Science Foundation under NSF ND EPSCoR Track 1 Grant Award IIA-1355466.

Literature Cited

Adams

R. A

.

1996

.

Size-specific resource use in juvenile little brown bats, Myotis lucifugus (Chiroptera: Vespertilionidae): is there an ontogenetic shift?

Canadian Journal of Zoology

74

:

1204

1210

.

Adams

R. A.

Thibault

K. M.

.

2006

.

Temporal resource partitioning by bats at water holes

.

Journal of Zoology

270

:

466

472

.

Aldridge

H. D. J. N.

Brigham

R. M.

.

1988

.

Load carrying and maneuverability in an insectivorous bat: a test of the 5% "rule" of radio-telemetry

.

Journal of Mammalogy

69

:

379

382

.

Aldridge

H. D. J. N.

Rautenbach

I. L.

.

1987

.

Morphology, echolocation and resource partitioning in insectivorous bats

.

Journal of Animal Ecology

56

:

763

778

.

Anthony

E. L. P.

Kunz

T. H.

.

1977

.

Feeding strategies of the little brown bat, Myotis lucifugus, in southern New Hampshire

.

Ecology

58

:

775

786

.

Anthony

E. L. P.

Stack

M. H.

Kunz

T. H.

.

1981

.

Night roosting and the nocturnal time budget of the little brown bat, Myotis lucifugus: effects of reproductive status, prey density, and environmental conditions

.

Oecologia

51

:

151

156

.

Arlettaz

R

.

1999

.

Habitat selection as a major resource partitioning mechanism between the two sympatric sibling bat species Myotis Myotis and Myotis blythii

.

Journal of Animal Ecology

68

:

460

471

.

Arrizabalaga-Escudero

A.

Napal

M.

Aihartza

J.

Garin

I.

Alberdi

A.

Salsamendi

E.

.

2014

.

Can pinewoods provide habitat for a deciduous forest specialist? A two-scale approach to the habitat selection of Bechstein's bat

.

Mammalian Biology

79

:

117

122

.

Barclay

R. M. R

.

1982

.

Night roosting behavior of the little brown bat, Myotis lucifugus

.

Journal of Mammalogy

63

:

464

474

.

Bergeson

S. M.

Carter

T. C.

Whitby

M. D.

.

2013

.

Partitioning of foraging resources between sympatric Indiana and little brown bats

.

Journal of Mammalogy

94

:

1311

1320

.

Brambilla

M.

et al.  .

2009

.

GIS-models work well, but are not enough: habitat preferences of Lanius collurio at multiple levels and conservation implications

.

Biological Conservation

142

:

2033

2042

.

Bridger

C. J.

Booth

R. K.

McKinley

R. S.

Scruton

D. A.

Lindstrom

R. T.

.

2001

.

Monitoring fish behaviour with a remote, combined acoustic/radio biotelemetry system

.

Journal of Applied Ichthyology

17

:

126

129

.

Broders

H. G.

Forbes

G. J.

Woodley

S.

Thompson

I. D.

.

2006

.

Range extent and stand selection for roosting and foraging in forest-dwelling northern long-eared bats and little brown bats in the Greater Fundy Ecosystem, New Brunswick

.

The Journal of Wildlife Management

70

:

1174

1184

.

Buckley

D. J.

et al.  .

2013

.

The spatial ecology of the whiskered bat (Myotis mystacinus) at the western extreme of its range provides evidence of regional adaptation

.

Mammalian Biology - Zeitschrift für Säugetierkunde

78

:

198

204

.

Calenge

C

.

2006

.

The package "adehabitat" for the R software: a tool for the analysis of space and habitat use by animals

.

Ecological Modelling

197

:

516

519

.

Calenge

C.

Dufour

A. B.

.

2006

.

Eigenanalysis of selection ratios from animal radio-tracking data

.

Ecology

87

:

2349

2355

.

Davidson-Watts

I.

Walls

S.

Jones

G.

.

2006

.

Differential habitat selection by Pipistrellus pipistrellus and Pipistrellus pygmaeus identifies distinct conservation needs for cryptic species of echolocating bats

.

Biological Conservation

133

:

118

127

.

Drewe

J. A.

et al.  .

2012

.

Performance of proximity loggers in recording intra- and inter-species interactions: a laboratory and field-based validation study

.

PLoS ONE

7:e39068, 1–9

.

Farrrell

M. J. O.

Studier

E. H.

.

1973

.

Reproduction, growth, and development in Myotis thysanodes and Myotis lucifugus (Chiroptera: Vespertilionidae)

.

Ecology

54

:

18

30

.

Fenton

M. B.

Barclay

R. M. R.

.

1980

.

Myotis lucifugus

.

Mammalian Species

142:

1

8

.

Fenton

M. B.

Bell

G. P.

.

1979

.

Echolocation and feeding behaviour in four species of Myotis (Chiroptera)

.

Canadian Journal of Zoology

57

:

1271

1277

.

Gannon

W. L.

Sherwin

R. E.

Haymond

S.

.

2003

.

On the importance of articulating assumptions when conducting acoustic studies of habitat use by bats

.

Wildlife Society Bulletin

31

:

45

61

.

Garshelis

D. L

.

2000

.

Delusions in habitat evaluation: measuring use, selection, and importance

. Pp.

111

164

in

Research techniques in animal ecology: controversies and consequences

( L. Boitani and T. K. Fuller , eds.).

Columbia University Press

,

New York

.

Henry

M.

Thomas

D. W.

Vaudry

R.

Carrier

M.

.

2002

.

Foraging distances and home range of pregnant and lactating little brown bats (Myotis lucifugus)

.

Journal of Mammalogy

83

:

767

774

.

Hillen

J.

et al.  .

2011

.

Sex-specific habitat selection in an edge habitat specialist, the western Barbastelle bat

.

Annales Zoologici Fennici

48

:

180

190

.

Johnson

D. H

.

1980

.

The comparison of usage and availability measurements for evaluating resource preference

.

Ecology

61

:

65

71

.

Kalcounis

M. C.

Brigham

R. M.

.

1995

.

Intraspecific variation in wing loading affects habitat use by little brown bats (Myotis lucifugus)

.

Canadian Journal of Zoology

73

:

89

95

.

Kunz

T. H., R.

Hodgkison

Weise

C.

.

2009

.

Methods of capturing and handling bats

.

Pp. 3–35 in Ecological and behavioral methods for the study of bats (T. H. Kunz and S. Parsons, eds.). 2nd edition. The Johns Hopkins University Press, Baltimore, Maryland

.

Kunz

T. H.

Oftedal

O. T.

Robson

S. K.

Kretzmann

M. B.

Kirk

C.

.

1995

.

Changes in milk composition during lactation in three species of insectivorous bats

.

Journal of Comparative Physiology B

164

:

543

551

.

Kunz

T. H.

Stack

M. H.

Jennes

R.

.

1983

.

A comparison of milk composition in Myotis lucifugus and Eptesicus fuscus (Chiroptera: Vespertilionidae)

.

Biology of Reproduction

28

:

229

234

.

Kurta

A.

Bell

G. P.

Nagy

K. A.

Kunz

T. H.

.

1989

a.

Energetics of pregnancy and lactation in freeranging little brown bats (Myotis lucifugus)

.

Physiological Zoology

62

:

804

818

.

Kurta

A.

Bell

G. P.

Nagy

K. A.

Kunz

T. H.

.

1989

b.

Water balance of free-ranging little brown bats (Myotis lucifugus) during pregnancy and lactation

.

Canadian Journal of Zoology

67

:

2468

2472

.

Manly

B. F. J.

McDonald

L. L.

Thomas

D. L.

McDonald

T. L.

Erickson

W. P.

.

2002

.

Resource selection by animals

.

Kluwer Academic Publishers, Dordrecht, The Netherlands

.

McGuire

L. P.

Guglielmo

C. G.

Mackenzie

S. A.

Taylor

P. D.

.

2012

.

Migratory stopover in the long-distance migrant silver-haired bat, Lasionycteris noctivagans

.

The Journal of Animal Ecology

81

:

377

385

.

Napal

M.

Garin

I.

Goiti

U.

Salsamendi

E.

Aihartza

J.

.

2010

.

Habitat selection by Myotis bechsteinii in the southwestern Iberian Peninsula

.

Annales Zoologici Fennici

47

:

239

250

.

Napal

M.

Garin

I.

Goiti

U.

Salsamendi

E.

Aihartza

J.

.

2013

.

Past deforestation of Mediterranean Europe explains the present distribution of the strict forest dweller Myotis bechsteinii

.

Forest Ecology and Management

293

:

161

170

.

Nelson

J. J.

Barnhart

P. R.

Gillam

E. H.

.

2015

.

Distribution and occurrence of bat species in North Dakota

.

The Prairie Naturalist

47

:

84

93

.

Otis

D. L.

White

G. C.

.

1999

.

Autocorrelation of location estimates and the analysis of radiotracking data

.

Journal of Wildlife Management

63

:

1039

1044

.

Ripperger

S. P.

Kalko

E. K. V.

Rodríguez-Herrera

B.

Mayer

F.

Tschapka

M.

.

2015

.

Frugivorous bats maintain functional habitat connectivity in agricultural landscapes but rely strongly on natural forest fragments

.

PLoS ONE

10

:

e0120535

.

RStudio Team

.

2015

.

RStudio: integrated development for R

.

RStudio

,

Boston, Massachusetts

. http://www.rstudio.com/. Accessed 1 February 2016.

Ryder

T. B.

Horton

B. M.

van den Tillaart

M.

De Dios Morales

J.

Moore

I. T.

.

2012

.

Proximity data-loggers increase the quantity and quality of social network data

.

Biology Letters

8

:

917

920

.

Sattler

T.

Bontadina

F.

Hirzel

A. H.

Arlettaz

R.

.

2007

.

Ecological niche modelling of two cryptic bat species calls for a reassessment of their conservation status

.

Journal of Applied Ecology

44

:

1188

1199

.

Schnitzler

H.-U.

Kalko

E. K. V.

.

2001

.

Echolocation by insect-eating bats

.

Bioscience

51

:

557

569

.

Schnitzler

H.-U.

Moss

C. F.

Denzinger

A.

.

2003

.

From spatial orientation to food acquisition in echolocating bats

.

Trends in Ecology & Evolution

18

:

386

394

.

Sikes

R. S.

Gannon

W. L.

, and

the Animal Care and Use Committee of the American Society of Mammalogists

.

2011

.

Guidelines of the American Society of Mammalogists for the use of wild mammals in research

.

Journal of Mammalogy

92

:

235

253

.

White

G.

Garrott

R.

.

1990

.

Analysis of wildlife radio-tracking data

.

Academic Press, San Diego, California

.

van Zyll deJong

C. G

.

1985

.

Handbook of Canadian mammals 2

.

National Museums of Canada

,

Ottawa, Ontario, Canada

.

Author notes

Associate Editor was Jorge Ortega.

thomaswass1974.blogspot.com

Source: https://academic.oup.com/jmammal/article/98/1/222/2698909

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