ABSTRACT Snow is a major, climate-sensitive feature of the Earth’s surface and catalyst of fundamentally important ecosystem processes. Understanding how snow influences sentinel species in

rapidly changing mountain ecosystems is particularly critical. Whereas 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

characteristics of slow-growing populations of mountain-adapted animals. SIMILAR CONTENT BEING VIEWED BY OTHERS CLIMATE CHANGE AND ANTHROPOGENIC FOOD MANIPULATION INTERACT IN SHIFTING THE

DISTRIBUTION OF A LARGE HERBIVORE AT ITS ALTITUDINAL RANGE LIMIT Article Open access 07 April 2021 CLIMATE CHANGE INCREASES PREDATION RISK FOR A KEYSTONE SPECIES OF THE BOREAL FOREST Article

14 September 2020 SEASONAL VARIATION IN DAILY ACTIVITY PATTERNS OF SNOW LEOPARDS AND THEIR PREY Article Open access 15 December 2022 INTRODUCTION Climate change is occurring rapidly in

mountain environments1,2, imposing profound changes to sensitive ecological communities and processes. Multiple and novel stressors can harm species such as alpine ungulates, which have

specialized adaptations and narrow biophysical niches3,4,5. Questions remain, however, about potential demographic implications and their underlying mechanistic drivers5,6. Seasonal snow

conditions might play a central role, and can act as a primary influence on ungulate population dynamics7,8. Identified mechanisms are largely ecological and physiological, with changes in

snow depth and distribution altering energetic costs of locomotion, vulnerability to predation, and accessibility and quality of forage in both summer and winter9,10,11,12. We take a

different focus, showing here how snow avalanches act as a direct, physical process that cause high levels of mortality and strongly influence demography in mountain wildlife populations.

Mountain ungulates are behaviorally predisposed and morphologically adapted to steep, rugged terrain to avoid the risk of predation (Supplementary Fig. 1)13. Such specialization, however,

may carry other risks. Specifically, slopes that provide effective refugia from predators are also subject to frequent avalanching. Indeed, avalanche mortalities have been described for

several ungulate species14,15,16,17. However, the difficulties associated with systematically documenting avalanche fatalities, which requires marking and long-term monitoring of individuals

across broad geographies in dangerous mountain conditions, have precluded a definitive demographic assessment. To address this gap, we combined an extensive, individual-based mountain goat

field monitoring data set with spatially explicit avalanche terrain data to quantify how avalanches influence the population ecology of mountain wildlife. We collected data on mountain goats

and their environment in southeastern Alaska, USA. The area’s Coast Mountains are characterized by steep, rugged topography, with avalanche activity observed across the full vertical range

of habitat occupied by mountain goats (0 to >1500 m). To quantify mountain goat exposure to and mortality from avalanches, we affixed global positioning system (GPS) and very high

frequency (VHF) radio-collars to 421 animals from four populations over a 17-year period (_n_ = 1218 mountain goat years). The four populations inhabit a ~ 500 km domain characterized by a

broad range of biogeographic settings (Fig. 1a). RESULTS AVALANCHE MORTALITY IN MOUNTAIN GOATS To determine cause of mortality, we intensively monitored survival status and identified the

timing and location of mortality events. We found that avalanches comprise a major source of mortality, accounting for 23 to 65% (mean = 36%; _n_ = 93) of average annual mortality, depending

on population (_n_ = 258; Fig. 1b). Avalanches were a more common cause of mortality for females (41%, _n_ = 39) compared with males (33%, _n_ = 54). These mortalities predominantly (61%)

comprised prime-aged (4−9 yrs old) individuals for both females (54%) and males (67%), age classes that otherwise have the highest survival rates and reproductive contribution (Supplementary

Figs. 2 and 3)5,15,18. Avalanche mortality varied spatially and temporally across populations in relation to geographic, climatic, and ecological characteristics of regional study areas,

being highest on Baranof Island (65%, _n_ = 51), relative to Klukwan (39%, _n_ = 71), Cleveland Peninsula (29%, _n_ = 7), and Lynn Canal (23%, _n_ = 129; Fig. 1b). Avalanche mortalities

occurred across nine months of the year, and peaked when snow conditions were most unstable during early season snowpack development (October and November) and the spring melting period

(April and May; Supplementary Fig. 4). The high levels of mortality highlight the challenges mountain ungulates face in mitigating avalanche risk. Avalanche formation involves the

interaction among meteorological conditions, snowpack, and terrain. Exposure to avalanche hazard depends largely on topography and the prevalence of structural weaknesses in the snowpack

that vary in space and time19. While we did not explicitly test whether mountain goats select specific terrain types to avoid avalanches during risky periods, the complex and dynamic

physical interactions that create avalanche vulnerability are likely difficult to detect among wildlife, minimizing opportunity for development of behavioral strategies to avoid avalanche

hazards in areas and periods of snowpack instability. Thus, compared to mortality mechanisms such as predation (for which most attempts end in prey escape) and winter starvation that can be

mitigated by learning and behavioral adaptations, avalanches may represent a ‘wicked problem’; that is, there are limited opportunities for trial-and-error learning due to the catastrophic

outcomes that follow initial exposure20,21. By extension, opportunities for and pace of fine-scale behavioral adaptation may be constrained because risk perception of such cryptic and

stochastic processes is likely weak and not strongly linked to heritable variation of behavioral responses22. COSTS OF LIVING DANGEROUSLY We hypothesized that putatively stochastic avalanche

mortality events would be linked, in aggregate and across populations, with the amount of time mountain goats spend in avalanche terrain during months with snow cover. Accordingly, we

modeled the potential release area locations23 and the maximum spatial extent of simulated individual avalanches within the geographic range of the study populations using Rapid Mass

Movement Simulation (RAMMS), a numerical dynamic avalanche simulation model24. Delineating avalanche hazard zones allowed us to quantify prevalence and use of avalanche terrain in winter for

individual mountain goats, assess the physical setting of avalanche mortality sites, and, in some cases, track the precise locations of avalanche entrainment and burial of killed

individuals (Fig. 2). We then evaluated whether exposure to avalanche hazard varied seasonally by intersecting temporally referenced GPS radio-collar locations (_n_ = 801,410 locations, 367

individuals) with the avalanche hazard spatial data layer (Fig. 2). Mountain goat use of avalanche terrain was widespread and linked to mortality. Avalanche release areas and paths

constitute most (62%) of the alpine and subalpine footprint across the winter range. There was little variability in the proportion of avalanche terrain in the three largest study areas,

which ranged from 57% in Lynn Canal to 67% in Klukwan; however, in the smallest study area, Cleveland Peninsula, avalanche terrain comprised only 17% of the wintering area (Supplementary

Table 1). Across all months and populations, mountain goats that died in avalanches exhibited significantly higher use of avalanche terrain (67 ± 3%, _n_ = 85) than those that did not die in

avalanches (54 ± 2%, _n_ = 282, _t_ = 3.643, _P_ < 0.01), a pattern that we likewise observed in finer-scale temporal analyses (i.e., for each individual month during the snow period;

Fig. 3 and Supplementary Table 2). Use of avalanche terrain varied substantially among populations, helping to explain observed spatial differences in avalanche mortality. Lynn Canal and

Cleveland Peninsula, where animals used avalanche terrain less than 40% of the time in winter months, had the lowest proportion of avalanche mortalities. The Klukwan and Baranof populations,

where animals occupied avalanche terrain more than 70% of the time in winter, had avalanche mortality rates roughly double those of the other areas (Fig. 1b and Supplementary Fig. 5). A NEW

VIEW OF SNOW AND MOUNTAIN UNGULATE POPULATION DYNAMICS Avalanche mortality patterns scaled up to reveal population-level implications. Estimated from radio-marked individuals, the

proportion of the population that died from avalanches averaged 8% annually over the study (_n_ = 43 population-years) and showed substantial spatial and temporal variation (Fig. 4). Three

populations had at least one year where more than 15% of the population died in avalanches, with peak annual avalanche mortality of over 22% of the Baranof population. Yet, we also

documented years without avalanche mortalities in all four populations. Such variation suggests a complex relationship between snow and ungulate population ecology. In particular, the

prevailing ecologically-focused view that snow depth and coverage is the primary snow-related control on ungulate fitness7 may not hold true for populations exposed to substantial avalanche

hazard. Instead, intra-seasonal variability in winter weather, which controls the amount of snowfall and the formation of weak layers in the snowpack19, may serve as a key physical driver of

population-level mortality. That population-level mortality from avalanches can exceed 20% in a single year highlights the role of stochastic environmental processes in the viability of

inherently vulnerable alpine wildlife. Stochastic predation events in mountain bighorn sheep, for example, can precipitate acute population declines resulting in demographic restructuring

and long recovery times25. Avalanches may have similar implications for mountain goats. Growth rates of mountain goat populations are particularly low. For example, modeling from this and

other areas—that has not incorporated the higher end of variation in annual mortality reported here—suggests that populations are able to sustain only limited annual removals such as by

harvest (1−4% annually)26,27,28. In this context, avalanche-driven mortality, which is dominated by prime aged individuals (Supplementary Fig. 2), is capable of eliciting major demographic

impacts and may underlie previously documented population declines and extirpation events in fundamentally tenuous mountain ungulate populations26,28,29,30,31. DISCUSSION Understanding

mountain goat use of dangerous, avalanche-prone terrain requires broader consideration of how avalanches might influence multiple components of fitness. Mountain goats utilize steep terrain

to mitigate predation-risk, with optimally selected slope angles (36−58°)32 closely corresponding with the most avalanche prone slopes (30−45°)33 (Supplementary Fig. 1). Additionally,

scouring by avalanches provides nutritional benefits by generating and maintaining accessibility of forage rich, early-successional habitats during winter and spring (Fig. 5)34,35. Yet,

given sufficient exposure, avalanche terrain might manifest as a form of ecological trap. Ecological traps have traditionally been described in contexts where rapid and direct human-induced

landscape change (i.e., habitat modification) results in ecological and evolutionary mismatch such that animals, in apparent error, select certain habitats associated with low fitness36.

Avalanches may thus represent a novel form of ecological trap that is linked to similarly imperceptible seasonal changes in the structure of snow cover blanketing mountain environments.

Whether and how climate change might lurk behind the pronounced avalanche-caused mortality we observed is unknown. If mountain goats evolved with similar snow conditions, the benefits of

using avalanche-prone terrain must be extraordinarily high for populations to offset such high mortality (in proportion and magnitude). Population-level variability in avalanche mortality

highlights the role of migratory and wintering strategies in exposing mountain ungulates to avalanche hazard. Mountain goats in Lynn Canal are highly migratory and primarily use low

elevation forested habitat during winter months, while individuals in Klukwan and Baranof employ mixed-migration strategies, often remaining at higher-elevation during winter to forage in

subalpine habitats and on wind-scoured alpine ridges (Supplementary Fig. 5, “Methods – Study System”). Other mountain ungulate species exhibit comparable variation in partially migratory

behavior, with a fraction of individuals residing year-round at high elevation while others migrate to low-elevation ranges during winter37,38. Partial migration is taxonomically widespread,

especially among ungulates39. Accordingly, our findings have broad implications, given that selection imposed by avalanches may reduce the prevalence of risk-prone higher-elevation resident

strategies. Over time, climate-driven variation in avalanche hazard40 may alter fitness trade-offs among migratory phenotypes and, ultimately, the occurrence of partial migration in

mountain systems. Regardless of details yet unknown, climate change impacts on snow characteristics will loom large in the future of mountain ungulates. It will shift the spatial and

temporal occurrence of avalanches41,42, with implications for exposure and entrapment. Warming will intensify extreme precipitation during winter43 and increase the occurrence of

rain-on-snow events44,45, both of which contribute to snowpack instability and avalanche release46. Avalanche character will also shift from dry-snow dominated to wet slides41, with

potentially increased avalanche mortality rates47. At the same time, future increases in snowline elevation in mountain environments may decrease avalanche hazard at lower altitudes42. Yet,

the demographic influence of avalanches on mountain ungulate populations is likely to persist into the future because both avalanche hazard42 and mountain ungulate ranges5,48 are expected to

shift upward in elevation as climate warms. The high rates of avalanche mortality we document might be widespread among mountain wildlife, and if so carry important cultural and ecological

implications. Mountain environments with avalanche hazard currently cover about 6% of Earth’s land area and occur on all continents49, with 32 mountain ungulate species across 70 countries

inhabiting a substantial fraction of this range50. Ungulate carcasses provide critical nutritional benefits to a diversity of avian and mammalian scavenging specialists (Supplementary Fig. 

6)51, and are particularly important in mountain food webs characterized by low ungulate biomass52. Moreover, Indigenous hunters have relied on mountain ungulate populations for millennia, a

relationship involving important subsistence and cultural traditions including use of wool for weaving ceremonial robes and other regalia53,54,55. Mountain ungulates are also highly

regarded among contemporary sport hunters and recreational wildlife-viewers worldwide. Thus, recognition that the persistence of ecologically and culturally important mountain ungulate

populations relates to climate-linked phenomena in more diverse ways than previously acknowledged has far-reaching conservation and cultural implications for mountain ecosystems and people.

METHODS STUDY SYSTEM Mountain goats were studied in four separate areas across a broad geographic range in coastal Alaska (5537 km2; Fig. 1 and Supplementary Table 1) from 2005 to 2022. This

area is within the Coast Mountains biogeographic region56. Mean monthly temperatures range from −2 to 14 °C and mean annual precipitation is 1400 mm in Juneau57, the area’s most populous

city. Across the region, annual precipitation ranges from 1 to >8 m and winter snowfall ranges from 0.5 to >3 m of snow water equivalent58. 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 composed primarily of Sitka

spruce-western hemlock (_Picea sitchensis-Tsuga heterophylla_) 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 processes59. 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 waters59. 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 species55,60. Populations exhibit a high degree of

local-scale population genetic differentiation, with limited movement among geographically discrete mountain complexes28,61,62. Mountain goats are habitat specialists and select steep,

rugged terrain in close proximity to cliffs and exhibit seasonal variation in altitudinal distribution32,62,63. Mountain goats are partially migratory, with some individuals, depending on

study area, residing in alpine and subalpine habitats throughout the year64,65. 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 areas63,64,65. Downslope migrations tend to correspond with the first major snowfall events at high

elevation (i.e., mid-October), while upslope migrations are timed with onset of the spring snow ablation and pre-parturition period (i.e., early-May)63. 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 greater63,64,66(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 mining28,32,64. The large mammal predator-prey communities in this area are intact and, in addition to mountain goats, key species include: moose

(_Alces alces_), Sitka black-tailed deer (_Odocoileus hemionus sitkensis_), wolves (_Canis lupus_), coyotes (_Canis latrans_), black bears (_Ursus americanus_), brown bears (_Ursus arctos_)

and wolverines (_Gulo gulo_); though local variation occurs relative to species distribution and abundance63,67. MOUNTAIN GOAT MONITORING Adult male and female mountain goats were captured

using standard helicopter darting techniques68. During handling all animals were fitted with mortality-sensing VHF and/or GPS radio-collars (Telonics Inc., Mesa, AZ). GPS radio-collars were

programmed to acquire a GPS location at 6-h intervals; ancillary activity sensor and temperature measurements were collected over a 15-min evaluation period commencing at the initiation of

the GPS location acquisition attempt. Age of animals was determined by counting horn annuli69,70 and, in some cases, cross validated by examination of tooth eruption patterns (for young

animals)70 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

American Society of Mammalogists guidelines71. 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 to within a 6-h 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 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. AVALANCHE SIMULATIONS AND MAPPING 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 areas23,72. Dynamically downscaled climate reanalysis (4-km resolution)73 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 RAMMS24 to simulate millions of

individual avalanches within the study areas and map avalanche hazard following the large scale hazard indication modeling approach developed by ref. 74. Mapped avalanche hazard zones were

further used to confirm that all mortalities classified as avalanche-related were located in avalanche hazard zones. MOUNTAIN GOAT SPATIAL ANALYSES Mountain goat GPS radio-collar location

data were compiled and subsequently filtered, using methods described by refs. 75,76, to ensure geolocational accuracy. Using a geographical information system, mountain goat GPS location

data were intersected with avalanche hazard indication maps to determine relative proportion of time each individual 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.

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 was analyzed in relation to fate using paired students _t_ tests, with _P_ < 0.05 denoting statistical significance. MOUNTAIN GOAT MORTALITY AND

SURVIVAL ESTIMATION 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 estimator77. 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 ref. 78). 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 individuals79. On average, 11% of study populations were

marked and monitored each year (based on mark-resight aerial survey sightability estimation)60; a large proportion and overall sample size (_n_ = 421 individuals) for deriving reliable

estimates of avalanche-related survival80. STATISTICS AND REPRODUCIBILITY All statistical and summary analyses (described above) including visualizations were performed using Program R

v4.3.1 and Microsoft Excel (v. 2019). Map visualizations were performed using ArcMap (v. 10.8). REPORTING SUMMARY Further information on research design is available in the Nature Portfolio

Reporting Summary linked to this article. DATA AVAILABILITY Data needed to reproduce the findings are publicly archived in the Dryad data repository81. Mountain goat location data are

administered by the Alaska Department of Fish and Game, Division of Wildlife Conservation and are not freely available due to conservation concerns [Alaska Statute 16.05.815(d)] but may be

requested by qualified parties through a data sharing agreement. CODE AVAILABILITY The code for the statistical analysis in the current study are available from the corresponding author on

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https://doi.org/10.5061/dryad.xsj3tx9ms (2024). Download references ACKNOWLEDGEMENTS We thank N. Barten, A. Crupi, J. Jemison, D. Larsen, K. McCoy, C. Rice, S. Sell, B. Seppi and Y. Shakeri

for field support. Expert fixed-wing and helicopter services were provided by Lynn Bennett, Chuck Schroth and Temsco Helicopters (M. Horton, R. Madrid, C. Kolden, E. Main, T. Buhler and A.

Hermansky). We thank A. Crupi, C. Cunningham, T. Graves, T. Levi, C. Magirl and two anonymous reviewers for their insightful feedback. Funding for this work was provided by the Alaska

Climate Adaptation Science Center, Alaska Department of Fish and Game, Federal Aid in Wildlife Restoration Program grant AKW-10 Project 12.01, Alaska Department of Transportation and Public

Facilities, Alaska Division of Geological and Geophysical Surveys, Bureau of Land Management, City of Sitka, Coeur Alaska, Federal Highway Administration, and Wild Sheep Foundation. We thank

the Alaska Department of Fish and Game, Division of Wildlife Conservation for providing a data sharing agreement and use of mountain goat monitoring data. Any use of trade, firm, or product

names is for descriptive purposes only and does not imply endorsement by the U.S. Government. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Natural Sciences, Program on the

Environment, University of Alaska Southeast, Juneau, AK, 99801, USA Kevin S. White & Eran Hood * Department of Geography, University of Victoria, Victoria, BC, V8W 2Y2, Canada Kevin S.

White & Chris T. Darimont * Division of Wildlife Conservation (ret.), Alaska Department of Fish and Game, Juneau, AK, 99811, USA Kevin S. White * Alaska Division of Geological and

Geophysical Surveys, Climate and Cryosphere Hazards Program, Fairbanks, AK, 99709, USA Gabriel J. Wolken * Alaska Climate Adaptation Science Center, University of Alaska Fairbanks,

Fairbanks, AK, 99775, USA Gabriel J. Wolken & Katreen Wikstrom Jones * U.S. Geological Survey, Northern Rocky Mountain Science Center, West Glacier, Montana, MT, 59936, USA Erich H.

Peitzsch * WSL Institute for Snow and Avalanche Research SLF, Davos CH-7260, Davos, Switzerland Yves Bühler * Climate Change, Extremes and Natural Hazards in Alpine Regions Research Centre

CERC, Davos CH-7260, Davos, Switzerland Yves Bühler Authors * Kevin S. White View author publications You can also search for this author inPubMed Google Scholar * Eran Hood View author

publications You can also search for this author inPubMed Google Scholar * Gabriel J. Wolken View author publications You can also search for this author inPubMed Google Scholar * Erich H.

Peitzsch View author publications You can also search for this author inPubMed Google Scholar * Yves Bühler View author publications You can also search for this author inPubMed Google

Scholar * Katreen Wikstrom Jones View author publications You can also search for this author inPubMed Google Scholar * Chris T. Darimont View author publications You can also search for

this author inPubMed Google Scholar CONTRIBUTIONS Conceptualization: K.S.W., E.H., E.H.P., G.J.W.; Methodology: K.S.W., G.J.W., Y.B., E.H., E.H.P., K.W.J.; Investigation: K.S.W., G.P.W.;

Visualization: K.S.W., E.H., G.P.W., E.H.P.; Funding acquisition: K.S.W., E.H., G.P.W., E.H.P.; Project administration: K.S.W., E.H., G.P.W.; Supervision: E.H., G.P.W., C.T.D.; Writing –

original draft: K.S.W., E.H.; Writing – review & editing: All Authors. CORRESPONDING AUTHOR Correspondence to Kevin S. White. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare

no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Communications Biology_ thanks Calum Cunningham and other anonymous reviewer(s) for their contribution to the peer review of this

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climate-linked driver of mountain ungulate populations. _Commun Biol_ 7, 423 (2024). https://doi.org/10.1038/s42003-024-06073-0 Download citation * Received: 03 October 2023 * Accepted: 19

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