DOI: 10.5061/dryad.sn02v6xjw
title: Ecotone might provide key refugium for sky island mammals in the Southern Appalachian Mountains

description: Sky islands, ecosystems found on geographically isolated mountain peaks,
 are among the most biodiverse ecosystems in the world but face a
 disproportionately high threat from climate change. High‐elevation,
 montane ecosystems, which are already at their upper altitudinal limits,
 are predicted to severely contract in response to climate change. The
 identification and conservation of refugia is an increasingly important
 approach for protecting biodiversity associated with imperiled ecosystems.
 We explored the spruce‐fir–northern hardwood ecotone as a possible
 refugium for mammals in the Southern Appalachian red spruce (Picea
 rubens)‐Fraser fir (Abies fraseri) sky islands. We conducted livetrapping,
 camera trapping, and ultrasonic acoustic surveys to characterize mammal
 diversity across the spruce‐fir–northern hardwood forest gradient on
 Grandfather Mountain and Roan Mountain Highlands in western North
 Carolina, USA. We detected four out of the five spruce‐fir‐associated
 small mammal species in both spruce‐fir and ecotone habitats. Mammal
 species richness, alpha diversity, and bat activity tended to be higher in
 the ecotone than in the other forest types on both mountains. Next, the
 abundance of small mammals associated with spruce‐fir was higher in the
 spruce‐fir and ecotone forests for one of the three species we were able
 to estimate. Together, our results suggest that the spruce‐fir–northern
 hardwood ecotone might serve as refugium for mammal species that are
 associated with spruce‐fir sky islands in the Southern Appalachian
 Mountains and mammalian conservation efforts in this biodiversity hotspot
 should consider focusing on the ecotone in addition to the adjacent
 spruce‐fir ecosystem.
description: Study Area This study was conducted in the
 Southern Appalachian Mountains, in western North Carolina, USA. We
 surveyed mammal communities on two mountains: Grandfather Mountain
 (36°6′ N and 81°48′ W; 1812 m above sea level [asl]), and Roan Mountain
 Highlands (36°6′ N and 82°7′ W; 1916 m asl). On each mountain, we
 conducted surveys at three sites along an elevational gradient, each
 located within one of the following forest types: spruce‐fir,
 spruce‐fir–northern hardwood ecotone, and northern hardwood. We surveyed
 six sites in total. Mammal Surveys
 We surveyed mammals along an elevational gradient at each
 mountain, from 1324 to 1635 m asl on Grandfather Mountain and 1547 to
 1872 m asl in the Roan Mountain Highlands (Table S1 in Appendix S1). The
 peaks of Grandfather and Roan Mountains were approximately 27 km
 straight‐line distance from one another. We used three field survey
 techniques to document volant and non‐volant mammal species within each
 forest type on each mountain: live traps, remote camera traps, and
 ultrasonic acoustic recorders (Figure 2). All surveys occurred in June and
 July 2023 on the southern aspect of both mountains (Table S1 in
 Appendix S1). We surveyed a total of six sites (three forest types on each
 mountain) that were spaced by 0.6–1.9 km. Our protocol conformed to the
 guidelines outlined by the American Society of Mammalogists (Sikes et
 al. 2016) and was approved by the Appalachian State University
 Institutional Animal Care and Use Committee (permit #22‐12) with
 permissions from relevant management authorities.
 Livetrapping We live‐trapped non‐volant small
 mammal species using Sherman traps (3″ × 3.5″ × 9″; H.B. Sherman Traps,
 Tallahassee, FL, USA). Each survey site consisted of 36 traps arranged in
 a 6 × 6 grid with 20 m spacing between traps (Figure 2). We set traps at
 sunset and checked and closed them at sunrise. Each trapping session
 consisted of four consecutive trap nights for a total of 144 trap nights
 per each 100 m<sup>2</sup> survey site. We baited traps with
 sunflower seeds, oats, and mealworms, and placed a cotton ball into each
 trap to help animals thermoregulate during colder nights. We placed traps
 at grid intersections in proximity to woody debris, trees, or rocks
 (Converse et al. 2006). For each captured rodent, we
 measured weight, hind foot length, body length, and tail length for
 species identification (Stephens et al. 2014; Berl et al. 2017), and
 determined sex, age class (adult or juvenile), and external reproductive
 status (Steele and Powell 1999; Polyakov et al. 2021). We uniquely marked
 each adult rodent in the right ear with an ear tag (Style 1005‐1L1,
 National Band & Tag Company, Newport, KY, USA; McCain 2004) and
 used surgical scissors to take ear tissue samples from
 <em>Peromyscus</em> for molecular species assignment (see
 “Molecular species assignment and discriminant function analysis” section
 below). Shrews were weighed, sexed, and identified to species. We used a
 permanent ink pen to mark juvenile rodents and all shrews with a unique
 symbol on the stomach or tail. All animals were released at their capture
 location. Molecular Species Assignment and Discriminant
 Function Analysis Morphology‐based identification is
 often unreliable for the two <em>Peromyscus</em> species in
 the region, the cloudland deer mouse (<em>P. maniculatus
 nubiterrae</em>) and the white‐footed mouse
 (<em>P. leucopus</em>) (Choate 1973; Stephens et al. 2014;
 Berl et al. 2017). We extracted DNA from the collected
 <em>Peromyscus</em> ear tissue samples via Qiagen DNeasy blood
 and tissue kits (Qiagen, Germantown, MD, USA). A random subset of the DNA
 extracts (<em>n</em> = 48) was analyzed at the North Carolina
 Museum of Natural Sciences for identification to species using the
 cytochrome b mitochondrial gene (primers: MTCB‐F and R; Naidu et
 al. 2012). For DNA sequencing, polymerase chain
 reactions (PCR) occurred in 10 μL volumes consisting of 5–10 ng of
 extracted DNA, 10 nM of forward and reverse primer, 2.0 mM of
 MgCl<sub>2</sub>, 5.0 μL of 1:5 mix of Takara Taq Polymerase
 and Promega GoTaq MasterMix, and 2.9 μL nuclease‐free water. PCRs began
 with initiation at 95°C for 2 min, then 35 cycles of denaturing at 95°C
 for 15 s, annealing at 52°C for 30 s, and extension at 72°C for 1 min with
 a final 10‐min extension at 72°C. We sequenced the forward primer for
 cytochrome b as it yields sufficient power to discern
 <em>Peromyscus</em> species (~600 bp of cytochrome b).
 Sequencing reactions initiated at 96°C for 3 min, then underwent 30 cycles
 at 96°C for 10 s, 50°C for 5 s, and 60°C for 2.5 min. We used the ethanol
 precipitation method to clean sequencing reactions (Latch and Rhodes 2005)
 and then sequenced them on a 3500 Genetic Analyzer (Applied Biosystems,
 Foster City, CA, USA). We aligned all sequences in Geneious Prime (Kearse
 et al. 2012) and uploaded them to GenBank (Accession Numbers
 PV487868–PV487919). Finally, to identify the remaining
 live‐trapped <em>Peromyscus</em> individuals to species, we
 used a linear discriminant function analysis model in the “mda” 0.5‐4
 package (Hastie et al. 2023) in R 4.3.2 (R Core Team 2023). The model
 function was built using four body measurements (weight, hind foot length,
 body length, and tail length). Analysis of variance tests confirmed that
 each body measurement differed significantly between the two species
 (<em>p</em> &lt; 0.01). The model correctly assigned
 species identity for 93.9% of the 48 individuals previously identified by
 DNA analysis, and we used it to predict the species of the remaining
 captured individuals (<em>n</em> = 100).
 Remote Camera Trapping We used remote camera
 traps to detect small to large non‐volant mammal species. We installed
 four remote cameras (Spec Ops Elite HP5, Browning, Morgan, UT, USA) at
 each survey site within each forest type so that cameras were at a minimum
 of 150–200 m apart (Figure 2). We mounted each camera at 30–50 cm on the
 bole of a tree following standard methodology to survey for small to large
 mammals (Evans and Mortelliti 2022; Rooney et al. 2025) near animal
 trails, rock outcrops, logs, and other desirable habitat features to
 increase the probability of detection (Trolle et al. 2008; Gebert et
 al. 2019; Hofmeester et al. 2021). We set cameras to take five‐image photo
 bursts every 5 s when motion was detected. We considered all images taken
 of the same species at the same camera within an hour as one detection
 (Hegerl et al. 2017; Gebert et al. 2019). We set the cameras at each site
 for 31 days, for a total of 372 trap nights per mountain. We uploaded,
 sorted, and manually identified species in all camera images on Wildlife
 Insights (https://www.wildlifeinsights.org/; Ahumada et al. 2020). Ultrasonic Acoustic Monitoring We used ultrasonic acoustic detectors (SM4, Wildlife Acoustics Inc., Maynard, MA, USA) to record vocalizations and quantify bat activity and species richness, and the activity of American flying squirrels (Carolina northern flying squirrel and southern flying squirrel; Diggins et al. 2016, 2020) across the forest types. We installed two acoustic detectors at each trap grid in the same location as the camera traps (Figure 2). To detect bats and American flying squirrels while minimizing the detection of nontarget species, we set detectors to record sounds with a minimum frequency of 16 kHz and minimum length of 1.5 ms from 30 min before sunset to 30 min after sunrise for 10 days (Gilley et al. 2019; U.S. Fish and Wildlife Service 2024). We attached detectors to tree trunks 1.5 m off the ground, facing the direction with the least amount of clutter to improve recording quality (Diggins et al. 2016, 2020). We conducted acoustic recording for a total of 10 consecutive nights per survey site. We used SonoBat software (SonoBat 4.4.5, DND Design, Arcata, CA, USA) to sort and identify flying squirrel calls. We confirmed all species identifications using two observers. A total of 845 calls were identified as American flying squirrels. We were able to identify four flying squirrel call types: chirps, trills, upsweeps, and crows (Gilley et al. 2019). We identified bat passes to species using Kaleidoscope Pro Analysis Software (Kaleidoscope 4.4, Wildlife Acoustics Inc., Maynard, MA, USA). Each bat pass had to match a species identification accuracy of at least 60% or the pass was classified as a “no ID” (Li and Kalcounis‐Rueppell 2018; Schimpp et al. 2018; Parker et al. 2019). We estimated bat species activity at each site as the mean number of bat passes recorded per night over the 10‐night survey period. We identified a total of 6436 bat passes to species. Vegetation Surveys We conducted vegetation surveys at every survey site to characterize each forest type. We established a circular 400 m<sup>2</sup> plot centered at each live‐trap grid. In every plot, all live trees (≥ 1.4 m height) were identified to species and measured at diameter at breast height. In addition, we counted the number of tree snags. Within each 400 m<sup>2</sup> plot, we established a 40 m<sup>2</sup> subplot where all live saplings (&lt; 1.4 m height) were identified to species and dead saplings counted (Kalies et al. 2012). We used the line interception method (Canfield 1941) along four perpendicular transects within the subplot to identify shrubs and herbaceous plant species. We calculated plant species richness as the total number of species detected at each survey site, including tree, shrub, and herbaceous species. We also calculated the percentage of trees that consisted of Fraser fir, red spruce, and northern hardwood species. Finally, we measured slope and aspect at the center of each plot.
description: # Ecotone might provide key refugium for sky island mammals in the
 Southern Appalachian Mountains ### DESCRIPTION OF THE DATA AND FILE
 STRUCTURE The dataset is located in the file
 "Mallinoff_et_al_Southern_Appalachian_mammals_Ecology_and_Evolution.xlsx". This dataset contains the following variables: 'live trapping - Roan' & 'live trapping - Grandfather': Live-trapping results from Roan Mountain Highlands and Grandfather Mountain * Date: Date of capture. * Trap Grid: Forest type of livetrap location (spruce-fir, ecotone, northern hardwood). * Trap Number: Individual identifier for each livetrap based on location within 6x6 trap grid. * N/R: New capture or recapture with unique number assigned to each captured animal. 'N' indicates new capture and 'R' indicates recapture. Numbers match the ear tag number or permanent marker symbol drawn on underside of animal's tail. 'CBE' indicates trap was closed but empty (false positive). * Species: Abbreviation for small mammal species captured. * Age: Age class of captured animals. 'A' = Adult and 'J' or 'Juv' = Juvenile. * Animal Weight in Bag: Weight of animal and the bag that animal was held in (grams). * Bag weight: Weight of the animal holding bags (grams). * Animal Weight: Animal weight (grams). * Body Length: Length of animal from tip of nose to base of tail (millimeters). * Tail Length: Length of tail from base to tip (millimeters). * Body Length - Tail Length: Tail length subtracted from body length (millimeters). * HFL: Hind foot length from tip of longest toe to back of heel (millimeters). * Sex: Animal sex ('F' = female, 'M' - male). * Repro Status: Reproductive status of the animal. 'NR' = nonreproductive, 'R' = reproductive, 'P' = pregnant, 'P?' = maybe pregnant, 'L' = lactating, 'S' = scrotal. * DNA: Ear tissue sample taken for DNA analysis 'Y' (yes) or 'N' (no). * Ecto: Ecoparasite sample taken if parasites are present (e.g., ticks or fleas) 'Y' (yes) or 'N' (no). * Fecal: Fecal sample taken if feces is present 'Y' (yes) or 'N' (no). 'acoustics - flying squirrels': Ultrasonic acoustic recording results of American flying squirrels (Glaucomys volans and G. sabrinus coloratus) * Site: Location of acoustic detector. * Recorder ID: Unique identification number of each detector. * Date: Date that call was recorded. * Time: Time of recording. * Species: Species identified. 'SFS' = southern flying squirrel (G. volans), 'NFS' = northern flying squirrel (G. sabrinus coloratus), 'FS' = flying squirrel species unknown. * Type: Call type. 'acoustics - bats': Ultrasonic acoustic recording results of bats from Kaleidoscope Pro output. * INDIR: File location. * SITE: Location of detector (Grandfather or Roan). * REGION: Forest type location of detector (spruce-fir, ecotone, northern hardwoods) * DURATION: Call duration in seconds. * DATE: Datestamp of the recording. * TIME: Timestamp of the recording. * HOUR: Hour (from time) of the recording. * DATE-12: Datestamp of recording less 12 hours. * TIME-12: Timestamp of recording less 12 hours. * SPECIES: Bat species identified. * ID: Bat species identified. * PULSES: Number of pulses detected in the file. * MATCHING: Number of pulses matching the auto classification result. * MATCH RATIO: The ratio of MATCHING over PULSES. * MARGIN: CLassification margin (uncalibrated confidence score, higher values are more confident than lower). * ALTERNATE 1: First alternate. * ALTERNATE 2: Second alternate. * N: Total number of pulses detected. * Fc: Average characteristic frequency (kHz). * Sc: Average characteristic slope (octaves per second). * Dur: Average duration (ms) of call. * Fmax: Average maximum frequency (kHz). * Fmin: Average minimum frequency (kHz). * Fmean: Average mean frequency (kHz). * TBC: Average time between calls (ms). * Fk: Average frequency of the knee (kHz). * Tk: Average time to the knee (kHz). * S1: Average initial slope (octaves per second). * Tc: Average time to characteristic (ms). * Qual: Average call quality (%). * FILES: The number 1, indicating one file. * INPATHMD5: Unique identification used internally by Kaleidoscope Pro corresponding to the input file. 'cameras': Remote camera trapping results, output from Wildlife Insights ([https://www.wildlifeinsights.org/](https://www.wildlifeinsights.org/)). * project_id: Unique project ID assigned by Wildlife Insights. * deployment_id: Location of camera (mountain and forest type). * mtn: Mountain location (Grandfather or Roan). * image_id: Unique image ID. * filename: Unique file name. * location: File location. * is_blank: 0 * identified_by: Name of human identifier. * wi_taxon_id: Unique ID assigned by Wildlife Insights for taxa. * class: Organism's class. * order: Organism's order. * family: Organism's family. * genus: Organism's genus. * species: Organism's species. * common_name: Organism's common name. * timestamp: Date and timestamp of photo. * date: Datestamp of photo. * time: Timestamp of photo. 'vegetation - Roan trees' & 'vegetation - GFM trees': Vegetation survey results of trees (trees were identified as being greater than or equal to 1.4 m height). * Date: Date tree was surveyed. * Trap Grid: Forest type where tree is located (spruce-fir, ecotone, northern hardwood). * Quadrant: Location of tree within surveyed area (split into four quadrants). * Species: Abbreviation of identified tree species. * DBH (cm): Diameter at breast height (cm). * Total DBH (cm): Total sum of DBH of tree if it had multiple trunks. 'vegetation - saplings': Vegetation survey results of saplings (saplings were identified as trees of height less than 1.4 m). * Date: Date sapling was surveyed. * Mountain: Location of sapling (Roan or Grandfather). * Trap Grid: Forest type where sapling is located (spruce-fir, ecotone, northern hardwood). * Species: Abbreviation of identified sapling species. * Notes: Additional comments. 'vegetation - snags': Vegetation survey results for number of dead trees and saplings (snags). * Date: Date dead trees were counted. * Moutain: Location of dead trees (Roan or Grandfather). * Trap Grid: Forest type where dead trees are located (spruce-fir, ecotone, northern hardwood). * Large Tree Snags: Number of large dead trees. 'Large' is a subjective description but indicates snags that were once overstory trees. * Small Tree Snags: Number of small dead trees. 'Small' is a subjective description but indicates snags that were once midstory or understory trees. * Sapling snags: Number of dead saplings. 'vegetation - shrubs & herbs': Vegetation survey results for shrub and herbaceous plant species. * Date: Date of vegetation survey. * Mountain: Location of plant (Roan or Grandfather). * Trap Grid: Forest type where plant is located (spruce-fir, ecotone, northern hardwood). * Dominant Species Present: Abbreviation for identified plant species. * Notes: Common name of plant species. 'survey site info': Additional data collected at each survey site. We surveyed six sites total, one in each forest type on each mountain. * Date: Date additional survey site information was collected. * Mountain: Location of survey site (Roan or Grandfather). * Trap Grid: Forest type of survey site (spruce-fir, ecotone, northern hardwood). * Aspect: Aspect of survey site in degrees (all sites were on south-facing slopes). * Slope: Slope of survey site in degrees. * Center Coordinates: Location of the center of the live trap grid where vegetation survey also took place. ### DESCRIPTION OF R SCRIPTS R code for alpha diversity estimates and the discriminant function analysis are located in the file "Mallinoff_et_al_R_code.txt". We used R 4.3.2 for the discriminant function analysis with the ‘mda’ 0.5-4 package (Hastie et al., 2023) and files titled "DNA.csv" and "species_to_predict.csv". For diversity estimates, we used R 4.3.2 and the Community Ecology Package ‘vegan’ 2.6-4 (Oksanen et al., 2022) with the data file "diversity_cameras.csv". The files contain the following variables: "DNA.csv": Data collected from a random subset of captured *Peromyscus* individuals that were identified to species using DNA sequencing. Body measurements from these individuals were used to build the discriminant function analysis to identify other captured *Peromyscus* to species. * DNA_ID: Unique identification number assigned to each *Peromyscus* individual that received DNA sequencing analysis. * Year: Year the animal was captured and DNA sample (ear tissue) was taken. * Animal_ID: Unique ear tag number assigned to each captured animal. 'NA' = Not Assigned; animal did not receive an ear tag because of it's small body size and instead received a unique permanent marker symbol drawn on it's tail. * Species: *Peromyscus maniculatus* or *leucopus.* * Mtn: Mountain where animal was captured ('G' = Grandfather, 'R' = Roan). * Grid: Forest type where animal was captured (spruce-fir, ecotone, northern hardwood). * Weight: Animal weight (grams). * Body: Length of animal from tip of nose to base of tail (millimeters). * Tail: Length of tail from base to tip (millimeters). * Body_Tail: Tail length subtracted from body length (millimeters). * HFL: Hind foot length from tip of longest toe to back of heel (millimeters). * Age: Age class of captured animals. 'A' = Adult and 'J' = Juvenile. * Sex: Animal sex ('0' = female, '1' = male). "species_to_predict.csv": This file was entered in the discriminant function analysis to predict the species of the remaining *Peromyscus* individuals that were not identified using DNA sequencing. * Species: Generated output of Discriminant Function Analysis will go in this column. * Weight: Animal weight (grams). * Body: Length of animal from tip of nose to base of tail (millimeters). * Tail: Length of tail from base to tip (millimeters). * HFL: Hind foot length from tip of longest toe to back of heel (millimeters). "diversity_cameras.csv": Total number of unique detections of mammal species at each survey site. Columns indicate the species and rows indicate the location of the survey site. * Row 1 Columns A-L = Species captured in remote camera images in the following order left to right: 1 American_black_bear, 2 Bobcat, 3 Coyote, 4 Eastern_chipmunk, 5 Eastern_gray_squirrel, 6 Long_tailed_weasel, 7 Northern_raccoon, 8 Red_squirrel, 9 Striped_skunk, 10 Sylvilagus_species, 11 Virginia_opossum, 12 White_tailed_deer * Rows 2-7 = Location of the survey site as follows from top to bottom: 2 gfm spruce, 3 gfm eco, 4 gfm hardwood, 5 roan spruce, 6 roan eco, 7 roan hardwood. ('gfm' = Grandfather, 'roan' = Roan, 'spruce' = spruce-fir, 'eco' = ecotone, 'hardwood' = northern hardwood.)