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Microhabitat Selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the Central Appalachians
Corinne A. Diggins and W. Mark Ford

Northeastern Naturalist, Volume 24, Issue 2 (2017): 173–190

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Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 173 2017 NORTHEASTERN NATURALIST 24(2):173–190 Microhabitat Selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the Central Appalachians Corinne A. Diggins1,* and W. Mark Ford2 Abstract - Glaucomys sabrinus fuscus (Virginia Northern Flying Squirrel; VNFS) is a rare Sciurid that occurrs in the Allegheny Mountains of eastern West Virginia and northwest Virginia. Previous work on this subspecies has confirmed close associations with Picea rubens (Red Spruce) at the landscape and stand levels in the region. However, ongoing Red Spruce restoration actions using canopy-gap creation to release single or small groups of trees requires a better understanding of within-stand habitat selection of VNFS to assess potential short- and medium-term impacts. To address these questions, we conducted a microhabitat study using radio-collared squirrels in montane conifer and mixed conifer– hardwood stands. We used points obtained from telemetry surveys and randomly generated points within each squirrel’s home range to compare microhabitat variables for 13 individuals. We found that VNFS preferentially selected plots with conifer-dominant overstories and deep organic-soil horizons. VNFS avoided plots with dense Red Spruce regeneration in the understory in stands with hardwood-dominated overstories—the types of areas targeted for Red Spruce restoration. We also opportunistically searched for hypogeal fungi at telemetry points and found 3 species of Elaphomyces during our surveys. Our results indicate that microhabitat selection is associated with Red Spruce-dominant forests. Efforts to restore Red Spruce where hardwoods dominate in the central Appalachians may improve the connectivity and extent of habitat of VNFS. Introduction Glaucomys sabrinus fuscus Miller (Virginia Northern Flying Squirrel; VNFS) is a rare subspecies of G. sabrinus (Shaw) (Northern Flying Squirrel) found in montane conifer and conifer–northern hardwood forests in the central Appalachian Mountains of eastern West Virginia and western Virginia (Reynolds et al. 1999, Stihler et al. 1995). The preferred habitat of the VNFS is Picea rubens Sarg. (Red Spruce)-dominated forests (Ford et al. 2007, Menzel et al. 2006, Stihler et al. 1995). This forest type has been reduced from an estimated >200,000 ha in the late 1800s to less than 20,000 ha at present (Byers et al. 2013, Korstian, 1937, Newins 1931, Schuler et al. 2002) due to industrial clear-cut logging and subsequent fires during the early to mid-20th century (Clarkson 1964). Since that time, spruce forests have been further degraded by acid precipitation (Eagar and Adams 1992) and exotic pests (i.e., Adelges picea Ratzeburg [Balsam Woolly Adelgid]) and are projected to be highly vulnerable to future anthropogenic climate change (Beane and Rentch 1Department of Fisheries and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061. 2US Geological Survey, Virginia Cooperative Fish and Wildlife Research Unit, Blacksburg, VA, 24061. *Corresponding author - cordie1@vt.edu. Manuscript Editor: Thomas W. French Northeastern Naturalist 174 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 2015). Noss et al. (1995) listed Red Spruce-dominated forests of the region as one of the most critically endangered forested ecosystems in the US because of its reduced extent and recent degradation. Multiple studies indicated a positive relationship between the VNFS and Red Spruce forest at the landscape (Ford et al. 2010, Menzel et al. 2005, Odom et al. 2001) and stand level in the region (Ford et al. 2007; Menzel et al. 2004, 2006). In the Appalachians, past research indicated that denning habitat often has been associated with the northern hardwood–conifer ecotone (Hackett and Pagels 2003, Weigl et al. 1999). However, radio-collared VNFS in the central Appalachians and endangered G. s. coloratus Howell (Carolina Northern Flying Squirrel) in the southern Appalachians use Red Spruce as foraging habitat more than expected based on their availability (Diggins 2016; Ford et al. 2007, 2014; Menzel et al. 2006). This preference may be due to the greater abundance of important food items (i.e., hypogeal fungi; Mitchell 2001) for these subspecies in montane conifer versus northern hardwood forests (Loeb et al. 2000). Many nest-box locations for both subspecies are biasedly placed in the montane conifer–northern hardwood ecotone, where denning was thought to exclusively occur (Ford et al. 2010), although recent research suggests these subspecies readily den in Red Spruce-dominated stands (Diggins 2016, Diggins et al. 2015, Ford et al. 2010, 2014). Habitat use by this subspecies has been studied on larger scales, but within-stand habitat associations are not well-defined. VNFS was listed as endangered under the Endangered Species Act in 1985 (USFWS 1985), and subsequently delisted in 2013 (USFWS 2013). The delisting occurred because the majority (63%) of VNFS habitat is protected on public land, and nest-box occupancy rates were indicative of long-term persistence, as determined from long-term nest-box monitoring data (Ford et al. 2010, Menzel et al. 2005). Paradoxically, the delisting of this subspecies has allowed more-flexible habitat management strategies to improve habitat quality and connectivity than when it was listed, including ecological restoration of Red Spruce forests using canopy-gap creation (Rentch et al. 2007, 2010, 2016; Schuler et al. 2002). Presently, the VNFS is a focal rationale for Red Spruce restoration in the central Appalachians because these activities are designed to increase the extent and connectivity of the squirrel’s habitat. However, biologists and land managers are still debating what constitutes the preferred habitat of this subspec ies. This discussion centers on determining which habitat type is more important to the VNFS: montane conifer forests (i.e., Red Spruce, and Tsuga canadensis [L.] Carr. [Eastern Hemlock]) or high-elevation northern hardwood forests dominated by Betula alleghaniensis Britton (Yellow Birch), Fagus grandifolia Ehrh. (American Beech) and other species (i.e., forest types adjacent to Red Spruce stands that may be designated for restoration treatments). Red Spruce, a shade-tolerant species, has been increasing in extent as understory regeneration in areas where northern hardwoods became dominant following logging and burning in the past 100 years (Mayfield and Hicks 2010, Rollins et al. 2010). This process may reflect signs of natural recovery of Red Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 175 Spruce forests (Nowacki et al. 2010), although natural recovery is gradual due to the slow establishment characteristics of Red Spruce (Rentch et al. 2010, Smith and Nicholas 1999, White et al. 1985). Spodic soils with deep organic horizons are correlated with Red Spruce forests, and evidence of these soil types may still be present under forests that regenerated as hardwoods after industrial logging (Nauman et al. 2015). Restoration using single-canopy gap to small-group selection cuts permit suppressed mid- and understory Red Spruce to be released for eventual accession to the overstory at a faster rate than natural recovery through successional trajectories (Rentch et al. 2016). Accelerating the process allows Red Spruce to regain its status as a foundation species that drives the structure and processes within the ecosystem (Ellison et al. 2005). Priority sites for Red Spruce restoration are determined by comparing current Red Spruce cover to its historic extent (i.e., Byers et al. 2013, Korstian 1937, Nauman et al. 2015), and efforts are underway to identify important habitat patches and corridors for other Red Spruce-associated wildlife (Rentch et al. 2007). Currently, little research, beyond anecdotal observations, has examined microhabitat selection by the VNFS, thereby limiting effective prioritization of future forest-restoration actions for this subspecies (Ford et al. 2004, Odom et al. 2001). Our objective was to determine variables that influence within-stand microhabitat selection by the VNFS in the central Appalachians. We used squirrel locations obtained from telemetry data of radio-collared individuals, and compared microhabitat characteristics for selected sites with available sites within a squirrel’s home range. We hypothesized that VNFS would preferentially select microhabitats associated with montane conifer forests (i.e., deep organic-soil horizons, and conifer dominance in overstory and/or understory). Field-site Description We conducted our study in Pocahontas and Randolph counties, WV, in the Allegheny Mountains and Plateau sub-physiographic region of the central Appalachian Mountains. The region is characterized by broad plateau-like ridges, steep slopes, and narrow valleys (Byers et al. 2010, Fenneman 1938). The mountains of the region are capped with Pennsylvanian siltstones and sandstones characterized by frigid silt or sandy loam soils that are rocky , highly acidic, and low in produc - tivity (Allard and Leonard 1952, Flegal 1999, Pyle et al. 1982). Our study sites included Kumbrabow State Forest (KSF; 38°37'10''N, 80°6'25''W), Snowshoe Ski Resort (SSR; 38°24'50'' N, 79°59'52''W), and the Greenbrier Ranger District (GRD; 38°41'15''N, 79°44'11''W) in the Monongahela National Forest (Fig. 1). The site on SSR was dominated by Red Spruce, whereas sites on GRD were dominated by Red Spruce, Red Spruce–Eastern Hemlock, and northern hardwood forests composed of Prunus serotine Ehrh. (Black Cherry), Yellow Birch, and Acer rubrum L. (Red Maple). Sites on KSF were dominated by planted Picea abies (L.) H. Karst. (Norway Spruce)–Eastern Hemlock and northern hardwood forests. All sites were second-growth stands, all had been cutover at least once in the preceding 100 years, and many had experienced multiple reentries to harvest Northeastern Naturalist 176 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 merchantable, high-value timber such as Black Cherry. Elevation at the study sites ranges from 930 m to 1450 m. Climatic conditions were cool and moist with frequent fog, high annual precipitation (120–150 cm distributed throughout the year, with >350 cm of average annual snowfall in the winter months), and mean annual temperature ranging from 6.7 °C to 9.4 °C with the possibility of freezing temperatures all year (Byers et al. 2010, Rentch et al. 2007, Stephenson 1993). Methods We captured VNFS using a combination of nest-box and live-trap surveys. We coordinated nest-box surveys with the annual spring and fall checks conducted by the West Virginia Division of Natural Resources and the GRD staff (C. Stihler, WVDNR, Elkins, WV, unpubl. data). We placed nest boxes (33.0 x 12.7 x 12.7 cm with a 4.4–5.7 cm opening) in single transects per site ranging from 15 to 30 nest boxes spaced at 30–50-m intervals ([S. Jones, US Forest Service, Barstow, WV, pers. comm.; Stihler et al. 1987). We mounted nest boxes 4–5 m from the ground on the trunks of trees and used a ladder to access them during checks . We supplemented nest-box checks with live trapping using Tomahawk 201 live traps (14 cm Figure 1. Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) microhabitat- survey sites during 2013 and 2014 in the central Appalachian Mountains of West Virginia. Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 177 x 14 cm x 41 cm, Tomahawk Live Trap Co., Hazelhurst, WI) baited with a slice of apple rolled in a peanut butter–molasses–bacon grease–oatmeal mixture. To reduce trap stress and potential hypothermic effects of trapping, we placed polyfill batting in each of the traps and partially covered the traps with plastic and duct tape. We set traps on the ground and on tree boles to increase captures of flying squirrels (Loeb et al. 1999). We opened traps at dusk and checked them at dawn. We closed all traps between sunrise and sunset to reduce capture of diurnal species. We distinguished Virginia Northern Flying Squirrels from sympatric G. volans L. (Southern Flying Squirrel) by coloration of ventral fur and hind-foot measurement (Wells-Gosling and Heaney 1984). We recorded sex, age, reproductive condition, and mass of all VNFS captures. Individuals were tagged with uniquely numbered ear tags (No. 1005-1, National Band and Tag Company, Newport, MA). We radio-collared all adult VNFS captures using 3.4-g and 4.0-g PD-2C radiocollars (Holohil Systems Ltd., Carp, ON, Canada), which represented ≤5% of their total body weight. Capture and tagging methods were approved by the Virginia Tech Institutional Animal Care and Use Committee (permit #11-120-FIW). We radio-tracked individuals and surveyed flying squirrel telemetry locations during May—July 2013, October 2013, and May–June 2014. To determine home ranges, we tracked radio-collared flying squirrels for a minimum of 5 nights or until the radio-collar signal was lost. We used Wildlife Materials TR4-2000S receivers (Wildlife Materials, Carbondale, IL) and 3-element folding yagi antennas to determine the location of flying squirrels. Before each nighttime telemetry session, we located each flying squirrel’s diurnal den to determine the best location for telemetry stations that night. We obtained telemetry points using close-range (less than 0.4 km) biangulation by manning 2 fixed stations to take telemetry points simultaneously to minimize temporal error, with the assumption that animal movements would not influence telemetry error rates (Schmutz and White 1990). For each survey night, telemetry stations were located >50 m apart to minimize bearings taken at less than 90°-angles (White 1985). Close-range biangulation is a common technique used for arboreal squirrels (Ford et al. 2014, Koprowski et al. 2008, Menzel et al. 2006, Shanley et al. 2013), because these animals are small-bodied, highly mobile, and typically inhabit small home-ranges (less than 20 ha). We tracked each flying squirrel for at least 2 h after civil twilight and typically ended surveys before or at midnight, when flying squirrel activity drastically decreased (Ford et al. 2007, Menzel et al. 2006). We obtained bearings on individual flying squirrels every 5–10 min to determine frequent movements associated with nocturnal activity. All personnel were tested for telemetry bias by using known locations of transmitters hidden in the field and actual bearings from telemetry stations to the location of the transmitter (White and Garrott 1990). We calculated our mean telemetry bearing error to be 3° ± 1° (White and Garrott 1990). Microhabitat points and home range We entered locations of stations and biangulation bearings into the software program LOCATE II (Pacer Co., Truro, NS, Canada) to obtain locations of individual squirrels. Using all locations for each VNFS, we estimated home ranges Northeastern Naturalist 178 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 using 100% minimum convex polygon (MCP) function in Biotas 2.0 (Ecological Software Solutions LLC, www.ecostats.com/web/Biotaswww.ecostats.com/web/ Biotaswww.ecostats.com/web/Biotas; Figs. 2, 3). We selected MCP because this estimator assumes use across the home range is continuous; thus, it does not explicitly depict high- and low-use areas (Getz and Wilmers 2004, Mitchell and Powell 2008). Our primary use of MCP was simply to define an area of potential habitat available to a squirrel in proximity to known flying squirrel locations. As denoted by other home-range estimators, high-use areas may include higher-quality habitat and random points may not fall in lower-quality habitat, thereby biasing microhabitat-comparison data. Home-range shapefiles obtained from Biotas were imported into ArcMap 10.0 GIS (Environmental Systems Research Institute, Inc., Redlands, CA. We used ArcMap to randomly generate 20 points within each home range of all VNFS with ≥30 points, to serve as random points during microhabitat surveys. We also randomly selected 20 locations obtained from telemetry surveys (hereafter, telemetry points) for each individual with the stipulation that randomly selected telemetry fixes must be ≥30 consecutive minutes apart from one another. Using telemetry points allowed us to compare points selected by a flying squirrel with random points within the flying squirrel’s home range (Fig. 3). Figure 2. 100% maximum convex polygon home-range of male Glaucomys sabrinus fuscus (Virginia Northern Flying Squirrel) at Greenbrier Ranger District in summer 2014 on the Monongahela National Forest, WV. The original telemetry-point locations. Picea rubens (Red Spruce) cover from Byers et al. 2013. Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 179 Microhabitat surveys We surveyed microhabitat variables at random points and telemetry points for individual Virginia Northern Flying Squirrels. All subspecies of Northern Flying Squirrels are preferential mycophagists (Maser et al. 1985, 2008); therefore, we tailored microhabitat plots to specifically look at factors that might influence hypogeal fungi. At each point, we chose a plot center and established a 10-m diameter circular plot. We placed a 1 m x 1-m vegetation sampling frame on the plot center to measure ground vegetation. We followed the microhabitat-measurement protocol provided by Castleberry et al. (2002) for Neotoma magister Baird (Allegheny Woodrat) in the Allegheny Mountains as modified based on previous habitat-association studies on VNFS and Carolina Northen Flying Squirrel (Ford et al. 2004, 2014, 2015; Menzel et al. 2006; Payne et al. 1989). At each random point and telemetry point, we qualitatively assessed dominant and co-codominant tree species within the circular plot. Hypogeal fungi form an obligatory symbiotic relationship with the roots of certain tree species, aiding host trees in absorption of nutrients and water from the soil (Harley and Smith 1983); these relationships are critical to tree and forest health (Amaranthus 1998). Therefore, we measured the distance to the nearest tree within Figure 3. 100% maximum convex polygon home-range of male Glaucomys sabrinus fuscus (Virginia Northern Flying Squirrel) at Greenbrier Ranger District in summer 2014 on the Monongahela National Forest, WV. Randomly selected telemetry plots and randomly generated random plots where microhabitat surveys were conducted. Picea rubens (Red Spruce) cover from Byers et al. (2013). Northeastern Naturalist 180 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 10 m from the center of the plot and recorded its species and diameter at breast height (DBH) to determine if host species for hypogeal fungi were located closer to foraging points than non-host species. We used a spherical densitometer to measure percent canopy cover at the plot center. We assessed percent groundcover within the subplot using the following variables: herbaceous vegetation, bare soil/rock, woody debris/ roots, moss/lichen, and duff (i.e., leaf/needle litter). In each plot, we also measured and averaged 4 systematically sampled soil plugs to determine the depth of the forest floor (i.e., organic horizon) within the plot. The fruiting bodies of hypogeal fungi are subterranean (e.g., truffles) and rely on small mammals, such as Northern Flying Squirrels, for dispersal throughout the forest (Fogel 1976, Fogel and Trappe 1978, Johnson 1996, Maser et al. 1978). Home ranges of Northern Flying Squirrels are larger than those of other small mammals that consume hypogeoal fungi (e.g., Myodes gapperi Vigors (Southern Red-backed Vole; Orrock and Pagels 2002), and, therefore, the squirrels may have a greater ecological role in dispersing fungi across the landscape (Loeb et al. 2000). Although the VNFS has a generalist diet that includes lichens and tree buds (Mitchell 2001), in West Virginia, they also consume the fruiting bodies of hypogeal fungi; thus, the location of host trees for hypogeal fungi may influence microhab itat selection. For telemetry points, we assessed if there were any signs of small-mammal digging activity in the subplot to indicate foraging for the fruiting bodies of hypogeal fungi. We recorded 2 types of small-mammal fungal-foraging types: digs and scratches. We defined a dig or scratch as fresh if there were no debris (i.e., leaf fragments, needles) or spider webs covering it (Castellano et al. 1999, 2003). We opportunistically excavated digs within telemetry points and searched for hypogeal fungi for ≤5 min within 0.5 m2 area of the dig. We destructively sampled, placed specimens in wax bags, and later identified all hypogeal fungi to species in the lab. Data analysis We employed a Spearman’s rank correlation in the R program (version 3.1; R Development Core Team 2015) to determine if any of our variables were highly correlated. No variables were significantly correlated and we retained all variables for subsequent analysis. We compared differences between variables at telemetry and random points averaged across all individual squirrels. Our data were not normally distributed; thus, we analyzed data using a permutated multivariate analysis of variance (PerMANOVA; Anderson 2001). Assumptions of analysis of variance are not generally met by most biological data, which tend to be highly skewed or aggregated. The PerMANOVAs use a permutation procedure to assess significance without requiring that data be normally distributed (Anderson 2001). We ran PerMANOVAs based on a Euclidean distance matrix with 9999 permutations per run using package ‘vegan’ (Dixon 2003, Oksanen et al. 2009). We assessed closest overstory tree by comparing the distance from the plot center to the tree and tree type (i.e., conifer versus hardwood species). For dominant overstory trees, we assessed percent conifer presence (i.e., Red Spruce, Norway Spruce, Eastern Hemlock) averaged across all sites. For understory conifers, we determined if pole or seedling Red Spruce or Eastern Hemlock trees were present in the understory, Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 181 including regeneration thickets, and averaged the presence across all sites. We ran a PerMANOVA to compare soil depth at telemetry points with hypogeal fungi versus telemetry points without hypogeal fungi. Results We captured 28 VNFS (21 adults, 7 juveniles) during 746 nest-box checks and ~1300 trap nights. We fitted 19 adult flying squirrels with radio-collars. Of these flying squirrels, we conducted microhabitat surveys on 13 individuals (7 males, 6 females). We gathered a total of 802 telemetry locations (average = 62 ± 5 locations per flying squirrel) for these 13 VNFS. Mean MCP home ranges were 4.2 ± 1.0 ha (mean male MCP = 5.8 ± 1.6 ha, mean female = 2.3 ± 0.5 ha). The 3 most-important explanatory habitat variables were organic soil horizon depth, dominant overstory tree, and presence of understory Red Spruce. The mean organic soil horizon depth was greater at telemetry points than at random points (Table 1). Montane conifers were the dominant overstory trees at 73.5% of telemetry points versus 57.7% of random points. Of the telemetry points with a dominant hardwood overstory, 69.6% had some conifer component in the overstory and 4% had Red Spruce regeneration present in the understory. Understory Red Spruce was greater in random points than in telemetry points (Table 1), and Red Spruce regeneration at random points occurred in both conifer- and hardwood-dominant plots (48.5% and 9.2%, respectively). Other microhabitat variables (i.e., variables quantifying ground cover and canopy cover) were not significantly different between telemetry and random points (Table 1). Species that occurred as the closest overstory tree included Red Spruce (25.8% and 20% of telemetry and random points, respectively), Red Maple (25.0% and 29.2%), Yellow Birch (17.3% and 22.7%), Norway Spruce (11.9% and 6.5%), Black Cherry (7.3% and 8.5%), American Beech (3.5% and 4.2%), Eastern Hemlock (3.1% and 2.7%), and Betula lenta L. (Sweet Birch; 2.7% and 0.4%). Other species documented at a small number of plots were Tilia americana L. (American Table 1. Mean (± SE) and PerMANOVA results of microhabitat variables averaged across all individual Glaucomys sabrinus fuscus (Virginia Northern Flying Squirrel) sample points, 2013–2014, Allegheny Mountains, WV. Telemetry Random F-statistic Habitat vVariable plots plots (df = 1, 24) P Organic matter depth (cm) 12.0 ± 1.3 8.6 ± 0.8 4.686 0.043 % bare ground 0.5 ± 0.4 0.7 ± 0.3 0.190 0.705 % moss cover 5.6 ± 1.4 5.2 ± 1.1 0.049 0.850 % duff cover 77.5 ± 2.6 74.9 ± 2.8 0.490 0.483 % woody debris 5.5 ± 0.5 4.7 ± 0.6 0.908 0.097 % herbaceous cover 11.0 ± 1.6 14.3 ± 2.4 1.362 0.350 % Canopy cover 76.4 ± 3.9 77.4 ± 2.3 0.050 0.838 Distance to closest overstory tree 2.2 ± 0.2 2.8 ± 0.3 3.302 0.080 Closest overstory tree (% plots with conifer) 40.8 ± 0.04 30.4 ± 0.04 3.388 0.066 Dominant overstory conifer (%) 73.5 ± 0.05 57.7 ± 0.06 4.105 0.048 Understory Red Spruce (% plots with regeneration) 22.3 ± 0.03 83.1 ± 0.07 59.040 less than 0.001 Northeastern Naturalist 182 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 Basswood), Pinus strobus L. (White Pine), Acer pensylvanicum L. (Striped Maple), A. saccharum Marshall (Sugar Maple), Magnolia acuminata L. (Cucumber Magnolia), and M. fraseri Walter (Fraser Magnolia). At telemetry points, the closest overstory trees were 59.2% hardwood species and 40.8% conifer species. The closest overstory trees at random points were 70.0% hardwood species and 29.2% conifer species, and 0.8% of plots had no tree within 10 m of the plot center. The average distance to closest tree was 2.2 m in telemetry points and 2.8 m in random points, although this was not significantly dif ferent (Table 1). Of the 260 telemetry points surveyed, we found hypogeal fungi digs and scratches in 25.4% of the subplots and approximately half of those subplots contained hypogeal fungi. We documented 3 species of hypogeal fungi: Elaphomyces americanum Castellano, E. verruculosus Castellano, and E. macrosporus Castellano and Trappe. We found the majority of digs during the spring seasons (86.4%), likely because leaf deposition in mixed forests during the fall season made locating digs difficult. Montane conifers were the closest overstory trees at 61.8% of plots where hypogeal fungi were present, and all plots with hypogeal fungi had either Red Spruce, Norway Spruce, or Eastern Hemlock as a dominant overstory tree (88.2%) or these species were present in the midstory (11.8%). Soils were significantly deeper at telemetry points with hypogeal fungi (mean = 12.5 ± 0.5) than telemetry points without hypogeal fungi (8.6 ± 1.0; F259 = 8.888, P = 0.003). Discussion Small-mammal microhabitat studies typically obtain data from capture–no capture sites in live-trapping grids (e.g., Jorgensen 2004, Meyer et al. 2007, Pyare and Longland 2002, Rossell and Rossell 1999), but these data can be misleading because baited-capture sites do not necessarily indicate microhabitat selection (Trainor et al. 2005), especially of foraging habitat. Although there is error associated with VHF telemetry (White and Garrott 1990), we measured our error rate and corrected for potential bias by using a larger plot size. The majority of the radio-collared individuals were obtained from nest boxes placed along the conifer–northern hardwood ecotone. Trapping and placing next boxes along the ecotone is associated with high capture rates of Northern Flying Squirrels in the Appalachians (Hackett and Pagels 2003, Weigl et al. 1999); however, ecotonal habitat is more closely associated with nesting habitat than foraging habitat (Diggins 2016, Ford et al. 2007, Loeb et al. 2000, Menzel et al. 2006). Our use of telemetry data reduced the bias effects of baited-trap sites or selectively placed nest boxes on potential foraging habitat. Macrohabitat conditions are typically considered better predictors of smallmammal habitat selection than microhabitat characteristics (e.g., Coppeto et al. 2006, Morris 1987, Orrock et al. 2000) because microhabitat partitioning is usually constrained by macrohabitat (Jorgensen and Demarais 1999). This limit may be dependent on average home-range size of the species in question (e.g., Castleberry et al. 2002). VNFS are highly mobile and can sometimes have home ranges > 20 ha (Ford et al. 2007, Menzel et al. 2006); we found the majority of withinstand habitat variables measured did not differ between selected and random sites. Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 183 Canopy cover and herbaceous cover are known to influence Northern Flying Squirrel microhabitat selection (Meyer et al. 2005, Pyare and Longland 2002, Smith et al. 2004) because Northern Flying Squirrels may be more vulnerable to predation in open stands (Carey et al. 1992). Urban (1988) found that fern cover was positively correlated within VNFS core-activity areas versus low-activity areas, whereas canopy cover was negatively correlated. However, neither variable influenced microhabitat selection in our study. We posit that this finding is explained by the fact that herbaceous cover was generally low at most sites we surveyed (Table 1) and virtually absent from plots with hypogeal fungi. Canopy cover was similar between telemetry and random points, regardless of whether plots were dominated by hardwoods (75.1% ± 1.2 canopy cover) or montane conifers (78.8% ± 0.9 canopy cover); thus, we detected no difference in overstory cover between telemetry and random points. Three habitat variables were significantly different between telemetry and random plots: organic-soil horizon depth, dominant overstory tree, and presence of understory Red Spruce. VNFS selected for deep organic-soil horizons that are typically associated with conifer stands and may be linked to selection of hypogeal fungi at foraging sites. Deeper organic-soil horizons also may be associated with higher abundances of hypogeal fungi (Meyer et al. 2007), although we found hypogeal fungi at telemetry points with shallower soils than telemetry points without hypogeal fungi. Our exploration of hypogeal fungi was opportunistic and we employed limited-time searches; thus, our searches for hypogeal fungi were incomplete at most telemetry points, and further assessment needs to be made in regards to soil depth and hypogeal fungi presence. Elaphomyces spp. occur in high proportions in VNFS diets (Mitchell 2001). All 3 species of hypogeal fungi we found are associated with Red Spruce or other conifers, such as Norway Spruce and Eastern Hemlock (Castellano et al. 2012; M. Castellano, US Forest Service, Corvallis, OR, pers. comm.). In a study of the Carolina Northern Flying Squirrel’s habitats in the southern Appalachians, Red Spruce was considered the most important tree species in plots with hypogeal fungi (Loeb et al. 2000). In our study, the majority of digs (62%) were located within 2 m of a conifer, the zone near the host tree where most hypogeal fungi occur (Fogel 1976). Presence of downed coarse woody debris is considered an important indicator to flying squirrels for hypogeal fungi detection (Pyare and Longland 2001), but coarse woody debris itself does not influence squirrel occurrence (Meyer et al. 2007, Pyare and Longland 2002). We did not measure coarse woody debris due to the low abundance observed throughout our study sites. Although we only opportunistically sampled for hypogeal fungi, our success in obtaining hypogeal fungi was much higher than a previous study on the VNFS in the central Appalachians (Ford et al. 2004), likely because that study was based on survey plots proximate to nest-box sites, which were not necessarily related to foraging sites. Similar to studies at the landscape and stand-level for Northern Flying Squirrels in the central and southern Appalachians, we found that VNFS microhabitat selection was linked to forests dominated by Red Spruce or other conifer surrogates Northeastern Naturalist 184 C.A. Diggins and W.M. Ford 2017 Vol. 24, No. 2 (Ford et al. 2004, 2007, 2014; Menzel et al. 2004, 2005, 2006; Payne et al. 1989). Pyare and Longland (2002) suggested that flying squirrel microhabitat selection may be hierarchical, but our results indicate that presence of Red Spruce or a conifer surrogate is more important in predicting microhabitat selection of VNFS than other habitat features, such as herbaceous cover. Northern Flying Squirrel home ranges are smaller in pure montane conifer stands than stands on the conifer– northern hardwoods ecotone (Diggins and Ford, unpubl. data; Ford et al. 2014; Menzel et al. 2006), suggesting that conifer stands have higher-quality habitat than ecotonal stands. Menzel et al. (2006) found that radio-collared VNFS selectively chose Red Spruce-dominant stands and mixed stands, and avoided pure northern hardwood stands. Ford et al. (2014) and Diggins (2016) found that radio-collared Carolina Northern Flying Squirrels selected Red Spruce more than expected based on availability at both the between-stand level and within-stand level in the southern Appalachians. Variation in microhabitat in Red Spruce stands, such as stand maturity and tree condition, may influence the frequency of use at a site, but we did not specifically address this question in the current study . Understory Red Spruce was significantly lower at telemetry points versus random points. Red Spruce regeneration, not herbaceous understory, was associated with higher amounts of absolute understory cover, although we did not specifically quantify density of regeneration over all of our study sites. In southeast Alaska, Smith et al. (2004) found that conifer regeneration was lower at trap sites that produced captures of flying squirrels than sites with no captures. However, other research has indicated that increased understory vegetation might be important for cover from predators, especially when foraging and handling food items (Longland and Price 1991, Pyare and Longland 2002). Increased understory cover may also hinder mobility on the ground (Carey 2000), which is considered a less-efficient form of locomotion for flying squirrels (Scheibe et al. 2006). We found that Red Spruce regeneration was significantly higher in random plots and hardwood dominated forests. Microhabitat selection was not associated with hardwood-dominant stands, regardless of the presence of Red Spruce regeneration in the understory. Our findings link VNFS microhabitat selection to deep organic-soil horizons and overstories comprised of montane conifer-dominated stands. Although adjacent hardwood stands may provide denning opportunities (Hackett and Pagels 2003, Menzel et al. 2004), our data suggest that conifer stands were more important foraging habitat. The expansion of Red Spruce regeneration into adjacent hardwood stands is indicative of ecological recovery of this forest type (Mayfield and Hicks 2010, Nowacki et al. 2010, Rollins et al. 2010), and should be a high priority for restoration. Girdling, stem-injection herbiciding, or felling of hardwoods to mimic natural canopy gaps (Rentch et al. 2010) would release single or small groups of suppressed Red Spruce to the overstory and potentially provide a near-term increase in potential den sites in newly created snags (Rentch et al. 2016). Although Northern Flying Squirrels are sensitive to silvicultural treatments (Carey 2000, Holloway and Smith 2011, Holloway et al. 2012), Red Spruce restoration occurs on a relatively small scale within the forest compared to more common forestharvest methods (i.e., clearcutting, green-tree retention). Restoration treatments Northeastern Naturalist Vol. 24, No. 2 C.A. Diggins and W.M. Ford 2017 185 are currently occurring in northern hardwood-dominant stands with suppressed Red Spruce in the understory or midstory. The restoration treatments may not strongly impact VNFS because they tend not to select these habitats. However, a better understanding of VNFS response to Red Spruce restoration treatments is necessary to understand short-term impacts of the treatments on this subspec ies. Ours is the first microhabitat selection study of Northern Flying Squirrels in the Appalachian Mountains and it may provide information pertinent to habitat management of this subspecies. Denning habits of Northern Flying Squirrels in the Appalachians may be plastic (Diggins et al. 2015, Hackett and Pagels 2003) and foraging habitat could be a more important indicator of habitat occupancy of VNFS. Red Spruce is predicted to decline in extent due to anthropogenic climate change, potentially leading to the extirpation of this species from the central Appalachians (Beane and Rentch 2015). Links to Red Spruce and other conifer surrogates on the landscape-, stand-, and microhabitat-level should help managers prioritize areas for habitat management and Red Spruce restoration to increase or retain as much of this threatened habitat type as possible. Restoration will help increase the extent, connectivity, and quality of the VNFS habitat, increasing the potential for population persistence into an uncertain future climate within the central Appalachians. Acknowledgments We thank P. Curtin, L. Schablein, W. Thompson, K. Parker, and H.B. Hound for field assistance. M. Castellano provided truffle identification. We are grateful to C. Stihler, S. Jones, J. Wallace, R. Doyle, B. Sargent, E. Galford, J. Teets, M.B. Adams, J. Tribble, T. Kuntz, D. Mitchell, S. Connelly, P. Weigl, D. 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