DOI: 10.5061/dryad.xsj3tx9ms
title: Long-term individual-based records of mountain goat mortality and terrain use in relation to avalanches in coastal Alaska during 2005-2022

description: Snow is a major, climate-sensitive feature of the Earth’s surface and a
 catalyst of fundamentally important ecosystem processes. Understanding how
 snow influences sentinel species in rapidly changing mountain ecosystems
 is particularly critical. Whereas the effects of snow on food
 availability, energy expenditure, and predation are well documented, we
 report how avalanches exert major impacts on an ecologically significant
 mountain ungulate - the coastal Alaskan mountain goat (Oreamnos
 americanus). Using long-term GPS data and field observations across four
 populations (421 individuals over 17 years), we show that avalanches
 caused 23-65% of all mortality, depending on area. Deaths varied
 seasonally and were directly linked to spatial movement patterns and
 avalanche terrain use. Population-level avalanche mortality, 61% of which
 comprised reproductively important prime-aged individuals, averaged 8%
 annually and exceeded 22% when avalanche conditions were severe. Our
 findings reveal a widespread but previously undescribed pathway by which
 snow can elicit major population-level impacts and shape demographic
 characteristics of slow-growing populations of mountain-adapted animals.
description: <strong>Study system.</strong> Mountain goats were
 studied in four separate areas across a broad geographic range in coastal
 Alaska (5537 km<sup>2</sup>; Fig. 1 and Supplementary Table 1)
 from 2005-2022. This area is within the Coast Mountains biogeographic
 region (<em>56</em>). Mean monthly temperatures range from -2
 to 14°C and mean annual precipitation is 1400 mm in Juneau
 (<em>57</em>), the area’s most populous city. Across the
 region, annual precipitation ranges from 1 to &gt;8 m and winter
 snowfall ranges from 0.5 to &gt; 3 m of snow water equivalent
 (<em>58</em>). During the study period, annual snowfall at sea
 level in Juneau averaged 233 cm with a range of 89-501 cm.
 The region is part of the world’s largest contiguous coastal
 temperate rainforest and is composed primarily of Sitka spruce-western
 hemlock (<em>Picea sitchensis-Tsuga heterophylla</em>) forests
 at lower elevations (below 450-750 m). At higher elevations, subalpine and
 alpine habitats dominated by krummholtz forest, low-growing herbaceous
 meadows, and ericaceous heathlands are widespread and persist to
 elevations of about 1400 m. The geologic terrain is complex and strongly
 influenced by terrain accretion and uplift processes
 (<em>59</em>). The resulting landscape is highly fractured and
 dominated by steep, rugged topography that is fragmented by active
 glaciers, icefields, high-volume river systems, and marine waters
 (<em>59</em>). The avalanche paths in this study extend from
 sea level to 2000 m and include a variety of aspects as a result of the
 complex topography of the Coast Mountains. Mountain
 goats in this region are widespread and occur at low to moderate
 densities, typical of northern coastal areas inhabited by the species
 (<em>55</em>, <em>60</em>). Populations exhibit a
 high degree of local-scale population genetic differentiation, with
 limited movement among geographically discrete mountain complexes
 (<em>29</em>, <em>61</em>,
 <em>62</em>). Mountain goats are habitat specialists and
 select steep, rugged terrain near cliffs and exhibit seasonal variation in
 altitudinal distribution (<em>33</em>,
 <em>62</em>, <em>63</em>). Mountain goats are
 partially migratory, with some individuals, depending on the study area,
 residing in alpine and subalpine habitats throughout the year
 (<em>64</em>, <em>65</em>). However, most
 individuals conduct short-distance (5-10 km), seasonal migrations
 involving annual movements between high-elevation alpine summer habitats
 and forested, low-elevation wintering areas
 (<em>63</em>–<em>65</em>). Downslope migrations
 tend to correspond with the first major snowfall events at high elevation
 (i.e., mid-October), while upslope migrations are timed with the onset of
 the spring snow ablation and pre-parturition period (i.e., early May)
 (<em>63</em>). Individuals in Lynn Canal are highly migratory
 and, like mountain goats on the Cleveland Peninsula, primarily use
 low-elevation forested habitat during winter months, while individuals in
 Klukwan and Baranof more frequently employ mixed-migration strategies,
 more often utilizing higher-elevation subalpine and alpine habitats where
 avalanche exposure is greater (<em>63</em>,
 <em>64</em>, <em>66</em>)(Supplementary Fig. 5).
 Impacts of human development and activity in the study area are,
 generally, minimal. Nonetheless, low-intensity or localized activities do
 occur and include regulated hunting, ground- and air-based recreational
 tourism, timber harvest, and mining (<em>29</em>,
 <em>33</em>, <em>64</em>). The large mammal
 predator-prey communities in this area are intact and, in addition to
 mountain goats, key species include moose (<em>Alces
 alces</em>), Sitka black-tailed deer (<em>Odocoileus hemionus
 sitkensis</em>), wolves (<em>Canis lupus</em>), coyotes
 (<em>Canis latrans</em>), black bears (<em>Ursus
 americanus</em>), brown bears (<em>Ursus arctos</em>)
 and wolverines (<em>Gulo gulo</em>); though local variation
 occurs relative to species distribution and abundance
 (<em>63</em>, <em>67</em>). 
 <strong>Mountain goat monitoring.</strong> Adult male
 and female mountain goats were captured using standard helicopter darting
 techniques (<em>68</em>). During handling all animals were
 fitted with mortality-sensing very high frequency (VHF) and/or global
 positioning system (GPS) radio-collars (Telonics Inc., Mesa, AZ). GPS
 radio-collars were programmed to acquire a GPS location at 6-hour
 intervals; ancillary activity sensor and temperature measurements were
 collected over a 15-minute evaluation period commencing at the initiation
 of the GPS location acquisition attempt. The age of animals was determined
 by counting horn annuli (<em>69</em>, <em>70</em>)
 and, in some cases, cross-validated by examination of tooth eruption
 patterns (for young animals) (<em>70</em>) and/or cementum
 analysis of incisors (for deceased animals; Matson’s Laboratory, Milltown,
 MT). Capture and handling procedures complied with all relevant ethical
 regulations for animal use and were approved by the Alaska Department of
 Fish and Game Institutional Animal Care and Use Committee (protocols
 05‐11, 2016‐25, 0078‐2018‐68, 0039‐2017‐39) and followed the American
 Society of Mammalogists guidelines (<em>71</em>).
 Following capture, animals were typically monitored at least once
 per month (often multiple times per month) via aerial telemetry to
 determine whether animals were alive or dead. Survival status was also
 determined via examination of GPS radio-collar location, activity, and
 temperature sensor data, an approach that often enabled temporal
 determination of death within a 6-hour time window. In cases where animals
 were determined to have died, an initial fixed-wing aerial reconnaissance
 of the site was conducted and followed up with a ground-based examination
 to determine the context and causes of death, to the extent possible. Due
 to safety and logistic considerations, ground-based examinations were
 typically conducted after initial aerial reconnaissance and determination
 of death. Due to the delay, it was not always possible to definitively
 distinguish between non-avalanche related causes of death (i.e. due to
 scavenging of carcasses). However, avalanche-caused mortality
 determinations were definitive and associated with carcasses being buried
 under, or associated with, avalanche debris and located within active
 avalanche paths.  <strong>Avalanche simulations
 and mapping.</strong> Avalanche hazard indication maps were
 developed from terrain analysis, downscaled climate model reanalysis, and
 numerical simulations of avalanche runout dynamics. Object-based image and
 terrain analyses were used with a digital terrain model (DTM; 5-m
 resolution) to determine avalanche potential release areas outside of
 closed canopy, conifer forest areas (<em>23</em>,
 <em>72</em>). Dynamically downscaled climate reanalysis (4-km
 resolution)(<em>73</em>) was used to calculate the maximum
 snow depth increase over three days in the 1981-2010 climatology, which
 was used to determine the avalanche release depth for each potential
 release area. We recognize that biologically meaningful avalanche activity
 can occur within closed-canopy forests but maintain that such events are
 very uncommon in southeast Alaska relative to avalanche activity in alpine
 areas. As such, for this large-scale approach, we assumed that closed
 canopy, conifer forest areas were not prone to significant avalanche
 activity and restricted our automated mapping of potential release areas
 to landcover types outside this designation.  Potential release areas and
 release depths were then used in the numerical dynamic avalanche model
 Rapid Mass Movement Simulations (RAMMS)(<em>24</em>) to
 simulate millions of individual avalanches within the study areas and map
 avalanche hazard following the large-scale hazard indication modelling
 approach developed by Bühler et al. (2022)(<em>74</em>).
 Mapped avalanche hazard zones were further used to confirm that all
 mortalities classified as avalanche-related were located in avalanche
 hazard zones. <strong>Mountain goat spatial
 analyses.</strong> Mountain goat GPS radio-collar location data were
 compiled and subsequently filtered, using methods described by D’Eon et
 al. (2002)(<em>75</em>) and D’Eon and Delparte
 (2005)(<em>76</em>), to ensure geolocational accuracy. Using a
 geographical information system (GIS), mountain goat GPS location data
 were intersected with avalanche hazard indication maps to determine the
 relative proportion of time each mountain goat spent in avalanche terrain
 during months when avalanche mortalities occurred (Oct-May). We defined
 avalanche terrain as avalanche potential release areas and runout paths
 combined, as both features comprised equivalent risk to mountain goats.
 The proportional use of avalanche terrain was calculated for each
 individual and coded based on whether the individual did or did not die in
 an avalanche. Monthly and seasonal differences in proportional use
 avalanche terrain were analyzed in relation to fate using paired
 student's t-tests, with <em>P</em> &lt; 0.05 denoting
 statistical significance.  <strong>Mountain goat
 mortality and survival estimation.</strong> As described above,
 causes of mortality were ascertained for every deceased individual. All
 causes of mortality were summarized as either being caused by an avalanche
 or other, non-avalanche related cause(s), including unknown (Supplementary
 Table 3). Cause-specific mortality was summarized for each population
 across all years of study as well as by month and study area. Survival of
 radio-collared animals was calculated for the annual cycle (June-May), at
 monthly time steps, using the Kaplan-Meier estimator
 (<em>77</em>). This method allows for staggered entry and exit
 of newly captured or deceased animals, respectively. While post-capture
 effects were not evident in our study, we implemented a conservative
 approach and excluded mountain goats for survival analysis for three days
 after capture (following Wagler et al. 2022)(<em>78</em>).
 Survival was estimated using only avalanche-caused mortality cases in
 order to determine the proportion of radio-marked animals that died due to
 avalanches (i.e. population-level mortality) for each year and study area.
 To ensure our sample was representative of the overall adult population,
 we conducted annual capture events to compensate for mortality losses, and
 maintain balanced sex and age classes in our sample of marked individuals
 (<em>79</em>). On average, 11% of study populations were
 marked and monitored each year (based on mark-resight aerial survey
 sightability estimation)(<em>60</em>); a large proportion and
 overall sample size (n = 421 individuals) for deriving reliable estimates
 of avalanche-related survival (<em>80</em>).
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description: Data files are deposited in .csv file format and are readily
 accessible using standard software programs. 
description: # Long-term individual-based records of mountain goat mortality and
 terrain use in relation to avalanches in coastal Alaska during 2005-2022
 Summary: These data were used to derive the analytical results described
 in the manuscript: Snow avalanches comprise a leading cause of mortality
 for mountain ungulates. Upon publication, a DOI will be added. This data
 archive includes field-based records collected from individually
 radio-marked and monitored mountain goats in relation to spatiotemporal
 patterns of mortality, with specific emphasis on avalanche-caused
 mortality. In addition, records describing temporal patterns of avalanche
 terrain use for each GPS-collared individual mountain goat are included.
 These data should not be used before reading the associated publication
 and corresponding with the authors to ensure proper interpretation and
 resolve any questions that may arise. ## Description of the data and file
 structure This data archive includes four independent files (.csv file
 format): 1) timing, spatial distribution, and cause of individual mountain
 goat mortalities, 2) proportion of time spent in avalanche terrain by
 individual, month, and fate, 3) proportion of population killed by
 avalanches by area and year, and 4) average proportion of a population
 killed by avalanche by area. Key fields and file structure are described
 in detail below. Individual mountain goat mortality data (mtn
 goat_individual mortality_db_final_2023_0625) #Avalanche_Mort denotation
 of whether an individual died in an avalanche (code = 1), or died from
 non-avalanche related causes (code = 0) #ID unique identifier for each
 animal #Area name of study area #Sex sex status of individual animal
 #Age_Capture age (years) at the time of capture #Age_Death age (years) at
 the time of death #Date_Capture date of capture #Year_Death biological
 year when the death occurred (the biological year began on June 1 and
 ended May 31, the following calendar year) #Month_Death month when the
 death occurred #Date_Death date when the death occurred Individual
 mountain goat use of avalanche terrain (mtn goat_avalanche terrain
 use_mortality_db_final_2023_0625) #ID unique identifier for each animal
 #Month month of year #Avy_Mort - denotation of whether an individual died
 in an avalanche (code = 1), or died from non-avalanche related causes
 (code = 0) #Prop_Avy proportion of time (i.e., GPS locations collected at
 equal intervals) an individual mountain goat spent in avalanche terrain
 per month. Population-level mountain goat mortality caused by avalanches
 (mtn goat_avalanche_pop level mortality_area by year_final_2023_0625)
 #Area - the name of study area #Area_Year - biological year of assessment
 (the biological year began on June 1 and ended May 31, the following
 calendar year) #n_at_risk total number of individuals monitored during the
 biological year #n\_ avy_morts number of individuals that died in
 avalanches during the biological year #Mortality_avy proportion of the
 population (i.e. total number of monitored individuals) that died due to
 avalanches in a given year. Mortality (the inverse of survival) was
 calculated for the biological year at monthly time steps using the
 Kaplan-Meier estimator, and allowed for staggered entry and exit of newly
 captured or deceased animals, respectively. Population-level mountain goat
 mortality caused by avalanches, mean by study area (mtn goat_avalanche_pop
 level mortality_mean by area_final_2023_0625) #Area - the name of the
 study area #mean_avy_at_risk average proportion of a population (i.e.
 total number of monitored individuals) that died due to avalanches per
 year #total_at_risk total number of mountain goat years for which
 avalanche mortality was assessed during the duration of the study. A
 mountain goat year is defined as monitoring one mountain goat during a
 biological year. #n\_ avy_morts total number of individual mountain goats
 that died due to avalanches per area across all years. ## Sharing/Access
 Information NA