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Multi-scale roost site selection by Rafinesque's big-eared bat (Corynorhinus rafinesquii) and Southeastern Myotis (Myotis austroriparius) in Mississippi.

INTRODUCTION

Rafinesque's big-eared bat (Corynorhinus rafinesquii; RBEB) and Southeastern myotis (Myotis austroriparius; SEM) are rare bats of the southeastern United States and considered species of concern throughout their range (Harvey el al., 2006). The current population statuses are unknown (Gooding and Langford, 9004; Harvey et al., 9006). Major threats to RBEB and SEM are habitat loss and degradation caused by urbanization and timber harvest (Clark, 1990; Cochran, 1999). Bottomland hardwood forests are important to SEM and RBEB (Clark et al., 1998; Cochran, 1999), providing roosting and foraging habitat (Tiner, 1984). Only 15-95% of precolonial bottomland hardwood forests remain in the southeastern United States; therefore, availability of roost trees for bats has decreased, likely leading to decreased abundance of SEM and RBEB in the region (Mississippi Museum of Natural Science, 2005).

Roosts are critical because of the role they serve in homeostasis and social interaction (Altringham, 1996). Tree cavity roosts are often considered limiting to bats and other wildlife, because their availability, varies temporally and suitable cavity trees are needed across seasons over multiple years (Kunz and Lumsden, 2003; Barclay and Kurta, 2007).

Roost tree availability can be limited by land-use practices including timber harvest (Campbell et al., 1996; Sedgeley and O'Donnell, 1999). Large tracts of bottomland hardwood forests with suitable large diametertrees are necessal-v to maintain populations of RBEB and SEM (Clark, 1990). Rafinesque's big-eared bat and SEM in Louisiana are usually found in bottomland hardwood forests containing baldcypress (Taxodium distichum) and water tupelo (Nyssa aquatica) (Menzel et al., 2001) with mean diameter at breast height (DBH) of 120-155 cm (Gooding and Langford, 2004). Mirowsky and Horner (1997) suggested the ratio of cavity opening size to inside cavity dimensions could be important for maintaining stable temperatures, and large cavity openings may allow bats to escape predators. Tree features, such as tree diameter (DBH 40 cm) and cavity chamber morphology, were selected for investigation due to reported influence of these metrics in roost tree use by RBEB and SEM (Gooding and Langford, 2004; Carver and Ashley, 2008).

Although roost tree characteristics can be important to tree roosting bats, landscape features may also influence use of roosting sites. Therefore, estimating landscape-level characteristics and their potential influence on bats can be important for understanding species-habitat associations. Limited information exists on seasonal use of trees by SEM or RBEB in relation to landscape characteristics for winter hibernacula and maternity sites (Barbour and Davis, 1969). Roost sites are often located within 1 km of permanent water which may increase humidity within roosts, foraging opportunities, and access to water (Rice, 1957). Southeastern myotis reportedly forage and roost near water (Harvey et al., 2006). Other factors, such as disturbance to the landscape surrounding the roost may influence use by SEM and RBEB (Clark, 1990). Although some bat species do not appear adversely affected by forest management, Clark (1990) reported RBEB usually abandon or reduce activity adjacent to logging operations. Landscape level features, including distance to nearest road, topographic elevations, and presence of surface water may influence roost tree use by RBEB and SEM (Rice, 1957; Clark, 1990; Harvey et al., 2006) and were selected a priori for model development.

Our objectives were to estimate the effects of tree and landscape characteristics on RBEB and SEM roost use as winter hibernacula and spring maternal sites. We hypothesized in spring and winter RBEB and SEM would use larger trees (DBH and internal cavity chamber) to allow more bats to cluster together to enhance metabolic regulation and social interactions (Barclay and Kurta, 2007; Brigham, 2007). We also hypothesized RBEB and SEM would use trees with larger cavity openings to escape predators (Mirowsky and Horner, 1997). We hypothesized bats would use areas close to rivers to provide water and foraging sites (Rice, 1957; Harvey et al., 2006) and areas away from roads to limit disturbance (Clark, 1990). Finally, we hypothesized that RBEB and SEM would be found in areas of low elevation and slope in response to tree species found in lower elevation bottomland hardwoods including baldcypress and water tupelo (Menzel el al., 2001).

A greater understanding of influential factors in roost tree use and selection by RBEB and SEM could assist natural resource managers to develop forest management plans that integrate protection and recruitment of roost trees with forest management and silvicultural operations. Furthermore, development of predictive models based on field studies of roost tree use by RBEB and SEM could advance knowledge needed for conservation of these forest-dwelling bats.

METHODS

STUDY AREA

We conducted this study from Oct. 2009 to Feb. 2010 (winter) and Apr. 2010 to Jun. 2010 (spring) at Noxubee National Wildlife Refuge (NNWR; 19,425 ha), Tombigbee National Forest (TNF; 26,942 ha), and Legion State Park (LSP; 175 ha), Mississippi, USA (Fig. 1). Noxubee National Wildlife Refuge contains 6227 ha of bottomland hardwood forests (USFWS, 2009). Bottomland hardwood forests typically consist of sweetgum (Liquidambar styraciflua), black tupelo, baldcypress, American beech (Fagus grandifolia), mockernut and pignut hickory (Carya tomentosa and C. glauca), white oaks (e.g., Quercus michauxii, and Q. lyrata) and red oaks (e.g., Q. pagoda, Q. nigra, and Q. phellos; Stevenson, 2008). Tombigbee National Forest and LSP contain upland areas with oaks (Quercus spp.) and hickories (Carya spp.) mixed with loblolly pine (Pinus taeda), and some shortleaf pine (P. echinata). Trees typically seen on ravine slopes and near smaller streams ([less than or equal to] 2nd order) include oaks, hickories, cucumber magnolia (Magnolia acuminata), tulip poplar (Liriodendron tulipifera), American beech, and sweetgnm (McDaniel, 1992). Annual precipitation of study sites averaged 143.2 cm from 1971 to 2000 (Stevenson, 2008), with average winter (Nov.-Dec.) temperature of 9.1 C from 1998 to 2008 (NOAA, 2009) and elevations ranging from 190 to 550 m (MARIS, 2010).

SURVEY EFFORT DETERMINATION

We estimated survey effort using estimates of bat occupancy and detection probability following MacKenzie and Royle (2005). We first estimated number of roost trees to inspect and surveys we would conduct during winter (Jam-Feb. 2010) and spring (Apr.-Jun. 2010) using roost occupancy data for RBEB and SEM collected at NNWR during 2006-2008 (Stevenson, 2008). We included only those trees with basal cavities (Gooding and Langford, 2004; Carver and Ashley, 2008), had been surveyed at least twice (Mackenzie and Royle, 2005), and had DBH >40 cm because this size class criteria was previously determined to be used by these species (Stevenson, 2008). We used program PRESENCE (Hines, 2006) to estimate occupancy (Mackenzie et al., 2003).

We used a double-observer approach to estimate probability of detection for each bat species (Fletcher and Hutto, 2006). Thirty roost trees with DBH >40 cm previously documented at NNWR (Stevenson, 2008) were randomly selected and independently examined during Oct.-Nov. 2009 by two observers to determine species and number of bats present. We inspected each roost tree twice during each season as determined from Mackenzie and Royle (2005). For each roost inspection, we coded observations as: 1 = bat present or 0 = bat absent. The order in which an observer inspected each tree was determined randomly during each survey period. Inspections were conducted independently by observers to avoid bias associated with previous observer's findings. Each observer examined cavity chambers of each tree and recorded number of bats present by species.

From data collected during 2009-2010, probability (P) of detecting each species was estimated following Nichols et al. 2000 and Fletcher and Hutto (2006). Occupancy and detection probability were then used to determine allocation of survey effort (i.e., number of trees to inspect and number of surveys to conduct; Table 1) following Mackenzie and Royle (2005).

SURVEY SITE SELECTION

We selected study sites on public lands based on the following criteria: forest age class (>65 y of age), contiguous forest patch size (>20 ha) or patch associated with a stream order [less than or equal to] 2, and forest stand composition dominated by deciduous hardwood species (Dickson and Sheffield, 2001). Study sites were in bottomland hardwood forests or riparian forests and could not be harvested during the study period. We defined bottomland hardwood forests as a deciduous hardwood forest in lowland floodplains along larger rivers and lakes, characterized by sweetgum, oaks, tupelo, and baldcypress (Fredrickson, 2005). We defined riparian forests as hardwood forests adjacent to intermittent and small-order streams ([less than or equal to] 2) associated with ravine hardwood forests (Strahler, 1957). We selected roost trees from a complete survey of trees within the 20 ha study site at LSP and TNF. At NNWR we selected areas that met criteria and used roost trees previously recorded by Stevenson (2008) that were not inundated with water from Green Tree Reservoir (GTR) management during the study. Green Tree Reservoirs are areas designed to inundate bottomland hardwood forests with 0.4-0.6 m of water during winter (~Nov.-Mar.) to provide waterfowl habitat (USFWS, 2009). Criteria for inclusion of roost trees included presence of a basal cavity and DBH >40 cm (Stevenson, 2008). Potential roost trees were marked with flagging and unique identification numbers and locations recorded using a handheld global positioning system (GPS) with 10 m accuracy. We divided the calculated number of trees to survey proportionally among potential roost trees found at each study site using random number generator. This calculation was done twice; once for each season surveyed [Jan.-Feb. 2010 (winter) and Apr.-Jun. 2010 (spring)]. We surveyed 118 (NNWR), 26 (TNF), and 11 (LSP) trees in winter and 128 (NNWR), 28 (TNF), and 12 (LSP) trees in spring.

For all surveys we estimated presence and abundance of RBEB and SEM in roost tree with basal cavities using a flashlight. When cavity openings were too small for direct observation, we used a mirror to reflect light from the flashlight into the cavity. In four cavity trees at NNWR, rectangular openings were constructed with a chainsaw at breast height (Stevenson, 2008). We removed cut-outs to search for bats, then replaced and sealed each with sediment to minimize changes in cavity microclimate (Stevenson, 2008). One abandoned well was surveyed but included only in landscape analysis.

We recorded number and species of bats detected, cavity chamber volume, area of cavity opening, and DBH for each tree. Species identification of bats followed Barbour and Davis (1969). We estimated cavity volume by multiplying the cavity's height, depth, and width. Height was measured from the ground to the top of the cavity; depth and width were measured at top of the cavity opening to avoid the wider buttress. We estimated cavity opening area by measuring height and width across the midpoint of the cavity's opening. Because of the low number of cavity trees in which RBEB and SEM were detected (n [less than or equal to] 9 for each species/season), we used descriptive statistics and 95% confidence intervals (CIS) to compare characteristics of trees used and not used by each species during winter and spring.

For each roost tree location we estimated distance to nearest stream (perennial streams layer; MARIS, 2010) and road (county roads and designated highway layers; MARIS, 2010) using the euclidean distance tool in ArcMAP (ESRI, 2011). We estimated elevation and slope from United States Geological Survey (USGS) digital elevation model (DEM; Jaberg and Guisan, 2001). All layers used in analyses had 10-m resolution. Landscape metrics were estimated using ArcGIS (ESRI, 2011). To increase sample sizes, we included roost trees used by RBEB or SEM during the same months (Jan.-Feb. and Apr.-Jun.) as reported by Stevenson (2008). We considered this approach pragmatic because edaphic factors, such as slope, elevation, distance to roads and water, had not changed since trees were surveyed in 2006.

We used logistic regression to assess effects of landscape metrics on bat presence for each species and season ([alpha] = 0.10; Schauber and Edge, 1999). We designated a = 0.10 a priori, which has been used in field studies with small sample sizes, (i.e., n < 30; Tacha et al., 1982). We tested our models for lack of fit using the Hosmer and Lemeshow Goodness-of-fit test ([alpha] = 0.05; Schauber and Edge, 1999)

Candidate models using all parameter combinations were constructed to assess ability of landscape variables to predict presence of RBEB and SEM. We used Akaike's Information Criterion corrected for small samples sizes (AICc) to identify competing models of bat presence (Burnham and Anderson, 2002). We ranked competing models from least to greatest AICc value and calculated the difference between the best model and other models ([increment of x). We calculated respective Akaike weights ([w.sub.i]) for all models with [increment of x] < 2 (Burnham and Anderson, 2002). When models contained more than one parameter, relative importance of individual parameters was estimated using model averaging and summing Akaike weights (Quinn and Keough, 2002).

For each bat species and season, we integrated final models from logistic regression into ArcGIS Model Builder (ESRI, 2011) to spatially model probability of use across bottomland hardwood forests and riparian forests in the study area (Jaberg and Guisan, 2001). Forest type was determined (i.e., bottomland or riparian hardwood) using forest survey data (Hines, 2006; MARIS, 2010).

RESULTS

TREE METRICS

We detected [greater than or equal to] 1 bat of either species in 10 and 17 trees during winter and spring, respectfully. During winter, three individual RBEBs were found in one American sycamore (Platanus occidentalis), one eastern cottonwood (Populus deltoids) and one in a covered well. Southeastern myotis were detected in cavity chambers of three black tupelo and one each baldcypress, white oak, sweetgum, and eastern cottonwood. In spring, RBEBs were found in four black tupelo, two American beech, two sweetgum, one American sycamore, and one swamp chestnut oak (Quercus michauxii). Southeastern myotis were found in cavities of three black tupelo, two American beech, and one each of sweetgum, ash (Fraxinus sp.) and American sycamore. The number of Rafinesque's big-eared bats and southeastern myotis detected in a single cavity tree ranged from one individual to colonies of approximately 300.

During winter, mean DBH of trees with cavities where RBEB and SEM were detected were about 1.7 and 1.4 times larger than DBH of trees with cavities where RBEB and SEM were not detected, respectively (Table 2). However, RBEB and SEM occurred in cavities during spring comparable in DBH to unoccupied cavities. Rafinesque's big-eared bat and SEM used cavities with openings similar in size to openings of unoccupied cavities during each season.

In winter, RBEB and SEM occurred in cavities about 3 and 4.6 times larger than cavities without RBEB and SEM, respectively. During spring, volumes of cavity chambers of roost trees used by SEM and RBEB and unoccupied roost trees were similar (Table 2).

LANDSCAPE METRICS

During winter, RBEB and SEM were located in 21 and 19 roosts, respectively. During spring, RBEB and SEM were located in 27 and 33 roosts, respectively (Table 3). The best-supported models for RBEB during winter and spring included only elevation (Table 4). Similarly, the best supported model for SEM in winter included elevation only. The best supported models for SEM during spring included distance to nearest road, elevation and slope. In spring and winter there was increased likelihood of RBEB presence in roost trees at decreasing elevation. Ninety and 100% of occupied roosts were at 200-235 m elevation during spring and winter, respectfully. Unoccupied roosts ranged from 200-533 m elevation. Southeastern myotis occupied roosts >0.5 km and >1 km from nearest roads 82% and 70% of the time, respectfully. Distance from the nearest road was three times more important than elevation or slope and best predicted SEM presence during spring (Table 5).

Green Tree Reservoirs at NNWR were moderate probability use areas for RBEB and SEM (Fig. 2). Legion State Park and TNF had <5% estimated probability of use by either species.

DISCUSSION

TREE METRICS

Rafinesque's big-eared bat and SEM both used several tree species as reported previously (Clark, 1990; Hurst and Lacki, 1999; Mirowsky et al., 2004; Mendlin and Risch, 2008). Variation in tree species used as roosts suggests that cavity presence and size may be of greater importance than tree species. However, in other studies water tupelo, black gum, swamp tupelo, baldcypress, and water hickory were reported as important species for bats in bottomland hardwood forests (Clark, 2003; Gooding and Langford, 2004; Mirowsky et al., 2004). The tendency for cavity development as trees attain greater age and size may vary among tree species and influence suitability as roosts. For example, species such as baldcypress and tupelo gum are more likely to develop heart rot which facilitates cavity formation (Mirowsky and Hornet, 1997).

Cavity trees with >75 cm DBH were most often used by both RBEB and SEM similar to previous studies (Mirowsky and Horner, 1997; Trousdale and Beckett, 2005; Carver and Ashley, 2008). In our study, larger trees (DBH >70 cm) typically exhibited greater cavity volumes. Rafinesque's big-eared bats and SEM both occurred more often in trees with large internal cavity volumes (>1.0 [m.sup.3]), especially during winter. These larger trees developed large cavities that could support more occupants, potentially enhancing behavioral thermoregulation by clustering (Barclay and Kurta, 2007). Furthermore, insulative properties of greater wood biomass of larger trees could produce more stable microclimate conditions including insulation against extreme minimum temperatures and reduction in temperature fluctuations (Sedgeley, 2001; Kurtz and Lumsden, 2003; Barclay and Kurta, 2007). Larger trees may extend above the canopy thereby being more exposed to solar radiation, which could also contribute to cavity warming (Kurtz and Lumsden, 2003; Barclay and Kurta, 2007). Increased roost warmth and thermal stability should reduce energetic demands during hibernation and pup rearing (Racey and Swift, 1981; Kunz, 1982). Types and quality' of shelter may affect individual fitness through physiological stresses, such as energy expenditure for thermoregulation. These stresses can be especially critical for bats during winter torpor due to potential temperature extremes and low food availability (Birks et al., 2005). Therefore, size and cavity volume of tree roosts used by RBEB and SEM may be very important in survival and population recruitment especially under extreme weather conditions (Birks et al., 2005).

Area of cavity opening did not influence presence of either RBEB or SEM during either season, similar to other studies (Carver and Ashley, 2008; Gooding and Langford, 2004). Mirowsky and Horner (1997) suggested large cavity openings may allow bats to escape predators. However, our unintentional size criterion of a cavity opening adequate for insertion of a flashlight and mirror (minimum 20 x 20 [cm.sup.2]) may have biased results.

LANDSCAPE METRICS

Rafinesque's big-eared bat in winter and spring used roost trees at lower elevations, perhaps in response to proximity to water (Rice, 1957), such as forested wetlands (sloughs and oxbows) and the Noxubee River channel. Larger tree size was associated with lower elevations; past protection of trees within streamside corridors can influence forest stand characteristics and suitability for forest dwelling bats, such as SEM and RBEB (Clark, 2000). Protection of streamside management zones and cavity trees in public forests like NNWR allow forests to reach older age classes in riparian areas (Dickson and Sheffield, 2001). Consequently, larger acres of suitable hardwood forests were available to forest-dwelling bats and much of this habitat was within the floodplain at lower elevations of NNWR. That RBEB used mature cavity trees in lower elevations of bottomland hardwood forests may be a combination of timber management practices and ecological characteristics including older age forests, larger forest patch sizes, and proximity of roost trees to surface water (Rice, 1957; Harvey et al., 2006).

Elevations within floodplain forests of NNWR where most RBEB and SEM were detected in roost trees ranged from 200-235 m whereas unoccupied roosts ranged from 200-533 m. Small elevation changes within active floodplain forests of the southeastern U.S. can affect soil texture, structure, drainage, and hydroperiod (Hodges, 1997). Soil characteristics also influence forest stand development, site index, and species composition with lower elevations typically supporting obligative wetland trees, such as baldcy-press and water tupelo (Hodges, 1997). Thus, forest stand composition appeared to influence roost tree use by RBEB in that these bats were often found in tupelo trees (Stevenson, 2008).

Southeastern myotis selected roost trees further from roads during spring, similar to Clark (1990). Clark (2000) reported a similar response of RBEB to disturbance associated with forest management activities. Disturbance at roosting sites is considered the most important factor in decline of North American bat populations, particularly for bats that do not roost in anthropogenic structures (Racey and Swift, 1981; Humphrey and Kunz, 1976). For example, human disturbance can cause abandonment of young and increased energetic expenditures by adult females as colony size declines (Mohr, 1972; McCracken, 1989).

Green Tree Reservoirs at NNWR were moderately selected areas for both RBEB and SEM (Fig. 2). Historically, GTR management resulted in forest inundation for extended periods on annual or biennial cycles. Frequency and duration of flooding used with GTR management does not mimic natural hydrologic regimes of alluvial floodplain forests which would have alternating wet and dry periods following seasonal flooding (Fredrickson, 2005). In Illinois, a colony of SEM abandoned a baldcypress roost with a basal entrance when water levels rose after a heavy rain, but returned to the tree when the water subsided (Hofmann et al., 1999). Extended inundation would not allow bats to return and cause basal cavities to be unavailable. Additionally, rapid flood events can cause suffocation of colonies by flooding entrances to trees before bats can depart (Gooding and Langford, 2004), especially during winter when bats are in torpor and less mobile. Forest management approaches that retain and recruit quality roost trees dispersed across different elevations of the floodplain, such as upper terraces and ridges, could provide alternate roost tree sites for bats during periods of prolonged flooding.

Both species in this study used roost trees with large DBH and cavity volumes, located in areas of lower elevation. Further, SEM demonstrated avoidance of roost trees near roads during spring. We recommend retention of mature and young cavity-producing trees (e.g., baldcypress, American sycamore, and tupelo spp.) in bottomland hardwood forests and minimizing disturbance in these areas during the maternal season (Mar.-Jun.). Protecting roost sites and reducing human disturbance would likely benefit Rafinesque's big-eared bat and southeastern myotis and ensure their long-term persistence.

Acknowledgments.--We thank the United States Fish and Wildlife Service for funding this project and Mississippi State Department of Fisheries, Wildlife and Aquacuhure for their support. Special thanks to E. O'Donnell, T. Harris, S. Fleming, J. Fogarty, E. Fogarty, C. Smith, A. Posner, K. Edwards, W. Howell, and E. Andrews for field assistance.

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UNITED STATES FISH AND WILDLIFE SERVICE. 2009. Noxubee National Wildlife Refuge. <http://www.fws. gov/noxubee/> Accessed 6 Apr. 2009.

SUBMITTED 19 JULY 2011

ACCEPTED 27 APRIL 2012

HEATHER L. FLEMING (1) AND JEANNE C. JONES

Department of Fisheries, Wildlife and Aquaculture, Mississippi State University, Mississippi State 39762

JERROLD L. BELANT

Carnivore Ecology Laboratory, Forest and Wildlife Research Center, Mississippi State University, Box 9690,

Mississippi State 39762

AND

DAVID M. RICHARDSON

Noxubee National Wildlife Refuge, Brooksville, Mississippi 39739

(1) Corresponding author: e-mail: hlf47@msstate.edu


TABLE 1.--Seasonal occupancy, detection probability, number of
surveys, and number of trees surveyed for Rafinesque's big-eared bat
(RBEB) and southeastern myotis (SEM) in bottomland and riparian
hardwood forests, Mississippi, 2009-2010

                                   Detection     No. of
Season    Species    Occupancy    probability   surveys

Winter    RBEB          0.08          0.8          2
          SEM           0.08          0.8          2
Spring    RBEB          0.10          0.8          2
          SEM           0.09          0.8          2

                      No. of      No. of
                     trees to      trees
Season    Species     survey     surveyed

Winter    RBEB          146         155
          SEM            63         155
Spring    RBEB          160         168
          SEM            86         168

TABLE 2.--Characteristics and associated 95% confidence intervals
(Cls) of trees used seasonally by Rafinesque's big-eared bat (RBEB)
and southeastern  myotis (SEM) in bottontland and riparian hardwood
forests, Mississippi, 2009-2010

                                                    Without bats

Season   Species   Variable        Units          n     Mean     SE

Winter   RBEB      DBH             cm            151    64.3     2.0
                   Opening Area    [m.sup.2]     151     0.2     0.0
                   Cavity Volume   [m.sup.3]     151    11.9     0.2
         SEM       DBH             cm            147    63.7     1.9
                   Opening Area    [m.sup.2]     147     0.2     0.0
                   Cavity Volume   [m.sup.3]     147     0.8     0.2
Spring   RBEB      DBH             cm            156    65.5     2.1
                   Opening Area    [m.sup.2]     156     0.2     0.0
                   Cavity Volume   [m.sup.3]     156     0.9     0.2
         SEM       DBH             cm            157    65.7     2.1
                   Opening Area    [m.sup.2]     157     0.2     0.0
                   Cavity Volume   [m.sup.3]     157     0.9     0.2

                                           Without bats

                                                      95% CI

Season   Species   Variable           Range      Lower    Upper

Winter   RBEB      DBH             40.6-177.8     60.4     68.2
                   Opening Area     0.0-1.9        0.1      0.2
                   Cavity Volume   0.03-19.1       0.5      1.6
         SEM       DBH             30.5-162.6     59.9     67.5
                   Opening Area     0.0-1.9        0.1      0.2
                   Cavity Volume    0.0-19.1       0.5      1.1
Spring   RBEB      DBH             40.6-177.8     61.4     69.6
                   Opening Area     0.0-1.9        0.1      0.2
                   Cavity Volume    0.0-19.1       0.6      1.3
         SEM       DBH             30.5-177.8     61.6     69.7
                   Opening Area     0.0-1.9        0.1      0.2
                   Cavity Volume    0.0-19.1       0.6      1.3

                                              With bats

Season   Species   Variable             n         Mean      SE

Winter   RBEB      DBH                  3        104.6     19.3
                   Opening Area         3          0.2      0.1
                   Cavity Volume        3          2.7      0.9
         SEM       DBH                  7         92.0     16.2
                   Opening Area         7          0.4      0.3
                   Cavity Volume        7          3.7      2.4
Spring   RBEB      DBH                  9         77.1      6.2
                   Opening Area         9          0.2      0.0
                   Cavity Volume        9          1.6      0.4
         SEM       DBH                  8         74.9     10.2
                   Opening Area         8          0.3      0.1
                   Cavity Volume        8          1.1      0.5

                                              With bats

                                                 95% CI

Season   Species   Variable           Range      Lower    Upper

Winter   RBEB      DBH             78.7-142.2     71.9    137.2
                   Opening Area     0.1-0.5        0.0      0.8
                   Cavity Volume    1.5-4.4        0.0      6.4
         SEM       DBH             50.8-177.8     92.0     92.5
                   Opening Area     0.0-1.9        0.0      1.0
                   Cavity Volume    0.4-18.1       1.2      9.6
Spring   RBEB      DBH             49.5-106.7     56.6     85.4
                   Opening Area     0.0-0.5        0.1      0.3
                   Cavity Volume    0.1-4.1        0.6      2.6
         SEM       DBH             49.5-142.2     50.7     99.1
                   Opening Area     0.1-0.8        0.1      0.5
                   Cavity Volume    0.1-4.4        0.0      2.3

TABLE 3.--Landscape characteristics of roost trees used seasonally by
Rafinesque's big-eared bat (RBEB) and southeastern myotis (SEM) in
bottomland  and riparian hardwood forests, Mississippi, 2009-2010

                                                    Trees without bats

Season   Species   Variable             Units      n      Mean     SF

Winter   RBEB      Distance to Road     m          142    925.0    60.2
                   Distance to Stream   m          142    245.0    29.0
                   Slope                degrees    142      5.2     0.8
                   Elevation            m          142    276.6     8.0
         SEM       Distance to Road     m          144    912.0    58.8
                   Distance to Stream   m          144    244.0    30.3
                   Slope                degrees    144      5.3     0.7
                   Elevation            m          144    275.4     7.9
Spring   RBEB      Distance to Road     m          145    970.0    61.6
                   Distance to Stream   m          145    254.0    30.0
                   Slope                degrees    145      5.2     0.7
                   Elevation            m          145    275.3     7.9
         SEM       Distance to Road     m          139    897.0    59.8
                   Distance to Stream   m          139    256.0    31.0
                   Slope                degrees    139      5.3     0.8
                   Elevation            m          139    275.5     8.2

Season   Species   Variable             Range

Winter   RBEB      Distance to Road       0.0-2229.1
                   Distance to Stream     0.0-1614.2
                   Slope                  0.0-41.4
                   Elevation            206.1-532.7
         SEM       Distance to Road       0.0-2205.1
                   Distance to Stream     0.0-1614.2
                   Slope                  0.0-41.4
                   Elevation            202.1-532.7
Spring   RBEB      Distance to Road       0.0-2597.9
                   Distance to Stream     0.0-1614.2
                   Slope                  0.0-41.4
                   Elevation            202.1-532.7
         SEM       Distance to Road       0.0-2325.6
                   Distance to Stream     0.0-1614.2
                   Slope                  0.0-732.5
                   Elevation            202.1-532.7

                                            Trees with bats

Season   Species   Variable             n     Mean     SE

Winter   RBEB      Distance to Road     21    958.3   144.4
                   Distance to Stream   21    178.3    84.5
                   Slope                21      2.9     0.6
                   Elevation            21    216.1     2.2
         SEM       Distance to Road     19   1066.4   170.0
                   Distance to Stream   19    176.7    52.5
                   Slope                19      1.5     0.4
                   Elevation            19    218.3     2.0
Spring   RBEB      Distance to Road     27   1166.4   158.2
                   Distance to Stream   27    195.6    43.3
                   Slope                27      1.5     0.4
                   Elevation            27    220.5     1.7
         SEM       Distance to Road     33   1441.2   142.3
                   Distance to Stream   33    196.6    39.7
                   Slope                33      1.9     0.5
                   Elevation            33    229.8     5.3

                                        Trees with bats

Season   Species   Variable             Range

Winter   RBEB      Distance to Road      36.1-2300.0
                   Distance to Stream     0.0-1613.1
                   Slope                  0.2-9.2
                   Elevation            202.1-245.7
         SEM       Distance to Road     151.3-2300.0
                   Distance to Stream     0.0-882.3
                   Slope                  0.1-5.5
                   Elevation            206.1-235.3
Spring   RBEB      Distance to Road     150.0-2500.0
                   Distance to Stream     0.0-882.3
                   Slope                  0.1-6.2
                   Elevation            210.1-235.2
         SEM       Distance to Road      90.0-2597.9
                   Distance to Stream    10.0-892.0
                   Slope                  0.0-11.7
                   Elevation            209.9-390.4

TABLE 4.--Top AlCc candidate model s ([[DELTA]i < 2) for landscape
variables of roost tree locations used  seasonally by Rafmesque's big-
eared bat (RBEB) and southeastern myotis (SEM) in bottomland and
riparian hardwood forests, Mississippi, 2009-2010

Season   Species  Model            K   AICc     w    Rank  [R.sup.2]

Winter   RBEB     Elevation        2  113.36  0.53    1      0.115
         SEM      Elevation        2  112.43  0.55    1      0.077
Spring   RBEB     Elevation        2  142.45  0.53    1      0.084
         SEM      Road, Elevation  3  161.84  0.29    1      0.102
                  Road, Slope      3  162.17  0.25    2      0.100
                  Road             2  162.42  0.22    3      0.077

TABLE 5.--Logistic regression results for model averaged landscape
parameters of locations of roost  trees used by southeastern myotis in
bottomland and riparian hardwood forests, Mississippi, spring 2010

                                                        95% CI
             Importance
Parameter      weight     Estimate    SE         Lower      Upper

Intercept                 -1.18       1.053      -2.91      0.55
Road            0.76       0.00067    0.00027     0.00023   0.00029
Elevation       0.29      -0.0087     0.0073     -0.021     0.0033
Slope           0.25      -0.086      0.072      -0.2       0.032
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Author:Fleming, Heather L.; Jones, Jeanne C.; Belant, Jerrold L.; Richardson, David M.
Publication:The American Midland Naturalist
Article Type:Report
Geographic Code:1USA
Date:Jan 1, 2013
Words:6501
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