Quantifying effects of snow depth on caribou winter range selection and movement in Arctic Alaska

Abstract

Background Caribou and reindeer across the Arctic spend more than two thirds of their lives moving in snow. Yet snow-specific mechanisms driving their winter ecology and potentially influencing herd health and movement patterns are not well known. Integrative research coupling snow and wildlife sciences using observations, models, and wildlife tracking technologies can help fill this knowledge void. Methods Here, we quantified the effects of snow depth on caribou winter range selection and movement. We used location data of Central Arctic Herd (CAH) caribou in Arctic Alaska collected from 2014 to 2020 and spatially distributed and temporally evolving snow depth data produced by SnowModel. These landscape-scale (90 m), daily snow depth data reproduced the observed spatial snow-depth variability across typical areal extents occupied by a wintering caribou during a 24-h period. Results We found that fall snow depths encountered by the herd north of the Brooks Range exerted a strong influence on selection of two distinct winter range locations. In winters with relatively shallow fall snow depth (2016/17, 2018/19, and 2019/20), the majority of the CAH wintered on the tundra north of the Brooks Range mountains. In contrast, during the winters with relatively deep fall snow depth (2014/15, 2015/16, and 2017/18), the majority of the CAH caribou wintered in the mountainous boreal forest south of the Brooks Range. Long-term (19 winters; 2001–2020) monitoring of CAH caribou winter distributions confirmed this relationship. Additionally, snow depth affected movement and selection differently within these two habitats: in the mountainous boreal forest, caribou avoided areas with deeper snow, but when on the tundra, snow depth did not trigger significant deep-snow avoidance. In both wintering habitats, CAH caribou selected areas with higher lichen abundance, and they moved significantly slower when encountering deeper snow. Conclusions In general, our findings indicate that regional-scale selection of winter range is influenced by snow depth at or prior to fall migration. During winter, daily decision-making within the winter range is driven largely by snow depth. This integrative approach of coupling snow and wildlife observations with snow-evolution and caribou-movement modeling to quantify the multi-facetted effects of snow on wildlife ecology is applicable to caribou and reindeer herds throughout the Arctic.

Winters are changing: snow effects on Arctic and alpine tundra ecosystems

“…Snow conditions, including spatial patterns, the onset and duration of winter snow cover, and thawing events during winter can influence plant-herbivore-predator interactions in a number of ways. First, snow distribution directly affects food accessibility to herbivores, which will influence their distribution (Berg et al 2008;Pedersen et al 2021). For example, during winter, muskoxen and reindeer/caribou prefer areas with thin snow cover where food is more easily accessible (Schaefer and Messier 1995;Riseth et al 2011;Pedersen et al 2021), while lemmings favour areas with deeper and more persistent snowpack that protects them from temperature extremes and predators (Gilg et al 2009;Duchesne et al 2011;Reid et al 2012).…”

“…First, snow distribution directly affects food accessibility to herbivores, which will influence their distribution (Berg et al 2008;Pedersen et al 2021). For example, during winter, muskoxen and reindeer/caribou prefer areas with thin snow cover where food is more easily accessible (Schaefer and Messier 1995;Riseth et al 2011;Pedersen et al 2021), while lemmings favour areas with deeper and more persistent snowpack that protects them from temperature extremes and predators (Gilg et al 2009;Duchesne et al 2011;Reid et al 2012). Which habitats become available (snow-free) earlier in the season will also affect the spatial distribution of herbivores and their population dynamics (Layton-Matthews et al 2020).…”

“…Snow cover is spatially and temporally heterogeneous and, in particular, snowmelt and snow accumulation patterns can vary across landscapes with varied topography (Marsh et al 1997;Aalstad et al 2020;Pedersen et al 2021). Recently, drones have successfully been used for recording and seasonal monitoring of ecosystem properties even in climatically challenging tundra environments (Fraser et al 2016;Assmann et al 2020;Siewert and Olofsson 2020).…”

“…Recently, drones have successfully been used for recording and seasonal monitoring of ecosystem properties even in climatically challenging tundra environments (Fraser et al 2016;Assmann et al 2020;Siewert and Olofsson 2020). Drones and highresolution satellite imagery can resolve small scale variability in snow extent, often measured as fractional snow-covered area (fSCA) (Liang et al 2017;Aalstad et al 2020), or snow thickness (Grünberg et al 2020;Harder et al 2020) or snow depth (Pedersen et al 2018;Pedersen et al 2021). Snow cover can be coupled with hydrological analyses, for example by estimating the snow water equivalent Dozier et al 2016;Niedzielski et al 2019), or to understand the impact of snowbeds on vegetation productivity (Borner et al 2008;Siewert and Olofsson 2020).…”

Collaborative wildlife–snow science: Integrating wildlife and snow expertise to improve research and management

“…The physical properties of snow, and their spatial distribution and temporal evolution, influence many ecological processes (Figure 1). For wildlife, snow properties can impact individuals by affecting movements and behaviors (Balkenhol et al, 2020; Berman et al, 2019; Boelman et al, 2017; Chimienti et al, 2020; Coady, 1974; Droghini & Boutin, 2018; Mahoney et al, 2018; Oliver et al, 2018; Oliver et al, 2020; Pedersen et al, 2021); predator–prey interactions (Horne et al, 2019; Nelson & Mech, 1986; Peers et al, 2020; Sirén et al, 2021); energetics related to foraging (Dumont et al, 2005; Fancy & White, 1985), locomotion (Fancy & White, 1987; Gurarie et al, 2019; Lundmark & Ball, 2008; Parker et al, 1984), and thermoregulation (Karniski, 2014; Pruitt Jr., 1957; Thompson III & Fritzell, 1988); forage accessibility (Hupp & Braun, 1989; Takatsuki et al, 1995; Visscher et al, 2006; White et al, 2009); as well as ground (Boelman et al, 2016) and subnivean habitat use (Bilodeau et al, 2013; Glass et al, 2021; Petty et al, 2015). Additionally, the effects of snow on individual survival (Hurley et al, 2017; Reinking et al, 2018; Shipley et al, 2020) and reproduction (Apollonio et al, 2013; Barnowe‐Meyer et al, 2011; Liston et al, 2016; Schmidt et al, 2019) can ultimately alter population‐level demographics (Apollonio et al, 2013; Berteaux et al, 2017; Boelman et al, 2019; Cosgrove et al, 2021; Desforges et al, 2021; Van de Kerk et al, 2018; Van de Kerk et al, 2020).…”