Online enhancements: appendixes. Dryad data: http://dx.doi.org/10.5061/dryad.3hr2c. abstract:The forage-maturation hypothesis (FMH) states that herbivores migrate along a phenological gradient of plant development in order to maximize energy intake. Despite strong support for the FMH, the actual relationship between plant phenology and ungulate movement has remained enigmatic. We linked plant phenology (MODISnormalized difference vegetation index [NDVI] data) and space use of 167 migratory and 78 resident red deer (Cervus elaphus), using a space-time-time matrix of "springness," defined as the instantaneous rate of green-up. Consistent with the FMH, migrants experienced substantially greater access to early plant phenology than did residents. Deer were also more likely to migrate in areas where migration led to greater gains in springness. Rather than "surfing the green wave" during migration, migratory red deer moved rapidly from the winter to the summer range, thereby "jumping the green wave." However, migrants and, to a lesser degree, residents did track phenological green-up through parts of the growing season by making smaller-scale adjustments in habitat use. Despite pronounced differences in their life histories, we found only marginal differences between male and female red deer in this study. Those differences that we did detect pointed toward additional constraints on female space-use tactics, such as those posed by calving and caring for dependent offspring. We conclude that whereas in some systems migration itself is a way to surf the green wave, in others it may simply be a means to reconnect with phenological spring at the summer range. In the light of ubiquitous anthropogenic environmental change, understanding the relationship between the green wave and ungulate space use has important consequences for the management and conservation of migratory ungulates and the phenomenon of migration itself.

Animals selecting habitats often have to consider many factors, e.g., food and cover for safety. However, each habitat type often lacks an adequate mixture of these factors. Analyses of habitat selection using resource selection functions (RSFs) for animal radiotelemetry data typically ignore trade-offs, and the fact that these may change during an animal's daily foraging and resting rhythm on a short-term basis. This may lead to changes in the relative use of habitat types if availability differs among individual home ranges, called functional responses in habitat selection. Here, we identify such functional responses and their underlying behavioral mechanisms by estimating RSFs through mixed-effects logistic regression of telemetry data on 62 female red deer (Cervus elaphus) in Norway. Habitat selection changed with time of day and activity, suggesting a trade-off in habitat selection related to forage quantity or quality vs. shelter. Red deer frequently used pastures offering abundant forage and little canopy cover during nighttime when actively foraging, while spending much of their time in forested habitats with less forage but more cover during daytime when they are more often inactive. Selection for pastures was higher when availability was low and decreased with increasing availability. Moreover, we show for the first time that in the real world with forest habitats also containing some forage, there was both increasing selection of pastures (i.e., not proportional use) and reduced time spent in pastures (i.e., not constant time use) with lowered availability of pastures within the home range. Our study demonstrates that landscape-level habitat composition modifies the trade-off between food and cover for large herbivorous mammals. Consequently, landscapes are likely to differ in their vulnerability to crop damage and threat to biodiversity from grazing.

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Partial migration is common in ungulates living in highly seasonal environments. Typically, at higher latitudes, this involves movement between high elevation summer areas used during breeding and lowland areas with less snow used during winter. Snow depth is regarded the main cause of migration to low elevation, but it is less clear why deer migrate to high elevation in spring. The forage maturation hypothesis explains the upward migration due to plant phenology. We here present also an alternative and non‐exclusive hypothesis, that deer migrate uphill in summer to escape competition due to the high density in winter areas (the competition avoidance hypothesis). We also suggest that social fences may play a role at high population density. Based on a unique study of 141 GPS‐marked red deer from seven regions covering the main distribution in Norway, we found that the proportion of migrants in the populations varied from 38% to 100%. Migration was more common in areas with a diverse topography, i.e. for areas with access to high elevation. Further, we found evidence that migration was negatively density dependent, and that fall migration was delayed at high density. We suggest that a combination of avoidance of competition in high density winter ranges, social fencing during summer in addition to the forage maturation and predation risk avoidance hypotheses, is needed to explain migration patterns of northern ungulates.

The cumulative effects of climate warming on herbivore vital rates and population dynamics are hard to predict, given that the expected effects differ between seasons. In the Arctic, warmer summers enhance plant growth which should lead to heavier and more fertile individuals in the autumn. Conversely, warm spells in winter with rainfall (rain-on-snow) can cause 'icing', restricting access to forage, resulting in starvation, lower survival and fecundity. As body condition is a 'barometer' of energy demands relative to energy intake, we explored the causes and consequences of variation in body mass of wild female Svalbard reindeer (Rangifer tarandus platyrhynchus) from 1994 to 2015, a period of marked climate warming. Late winter (April) body mass explained 88% of the between-year variation in population growth rate, because it strongly influenced reproductive loss, and hence subsequent fecundity (92%), as well as survival (94%) and recruitment (93%). Autumn (October) body mass affected ovulation rates but did not affect fecundity. April body mass showed no long-term trend (coefficient of variation, CV = 8.8%) and was higher following warm autumn (October) weather, reflecting delays in winter onset, but most strongly, and negatively, related to 'rain-on-snow' events. October body mass (CV = 2.5%) increased over the study due to higher plant productivity in the increasingly warm summers. Density-dependent mass change suggested competition for resources in both winter and summer but was less pronounced in recent years, despite an increasing population size. While continued climate warming is expected to increase the carrying capacity of the high Arctic tundra, it is also likely to cause more frequent icing events. Our analyses suggest that these contrasting effects may cause larger seasonal fluctuations in body mass and vital rates. Overall our findings provide an important 'missing' mechanistic link in the current understanding of the population biology of a keystone species in a rapidly warming Arctic.

Summary1. Most studies of intraspecific variation in home range size have investigated only a single or a few factors and often at one specific scale. However, considering multiple spatial and temporal scales when defining a home range is important as mechanisms that affect variation in home range size may differ depending on the scale under investigation. 2. We aim to quantify the relative effect of various individual, forage and climatic determinants of variation in home range size across multiple spatiotemporal scales in a large browsing herbivore, the moose (Alces alces), living at the southern limit of its distribution in Norway. 3. Total home range size and core home range areas were estimated for daily to monthly scales in summer and winter using both local convex hull (LoCoH) and fixed kernel home range methods. Variance in home range size was analysed using linear mixed-effects models for repeated measurements. 4. Reproductive status was the most influential individual-level factor explaining variance in moose home range size, with females accompanied by a calf having smaller summer ranges across all scales. Variation in home range size was strongly correlated with spatiotemporal changes in quantity and quality of natural food resources. Home range size decreased with increasing browse density at daily scales, but the relationship changed to positive at longer temporal scales. In contrast, browse quality was consistently negatively correlated with home range size except at the monthly scale during winter when depletion of high-quality forage occurs. Local climate affected total home range size more than core areas. Temperature, precipitation and snow depth influenced home range size directly at short temporal scales. 5. The relative effects of intrinsic and extrinsic determinants of variation in home range size differed with spatiotemporal scale, providing clear evidence that home range size is scale dependent in this large browser. Insight into the behavioural responses of populations to climatic stochasticity and forage variability is essential in view of current and future climate change, especially for populations with thermoregulatory restrictions living at the southern limit of their distribution.

One predicted consequence of global warming is an increased frequency of extreme weather events, such as heat waves, droughts, or heavy rainfalls. In parts of the Arctic, extreme warm spells and heavy rain-on-snow (ROS) events in winter are already more frequent. How these weather events impact snow-pack and permafrost characteristics is rarely documented empirically, and the implications for wildlife and society are hence far from understood. Here we characterize and document the effects of an extreme warm spell and ROS event that occurred in High Arctic Svalbard in January-February 2012, during the polar night. In this normally cold semi-desert environment, we recorded above-zero temperatures (up to 7°C) across the entire archipelago and record-breaking precipitation, with up to 98 mm rainfall in one day (return period of >500 years prior to this event) and 272 mm over the two-week long warm spell. These precipitation amounts are equivalent to 25 and 70% respectively of the mean annual total precipitation. The extreme event caused significant increase in permafrost temperatures down to at least 5 m depth, induced slush avalanches with resultant damage to infrastructure, and left a significant ground-ice cover (∼5-20 cm thick basal ice). The ground-ice not only affected inhabitants by closing roads and airports as well as reducing mobility and thereby tourism income, but it also led to high starvation-induced mortality in all monitored populations of the wild reindeer by blocking access to the winter food source. Based on empirical-statistical downscaling of global climate models run under the moderate RCP4.5 emission scenario, we predict strong future warming with average mid-winter temperatures even approaching 0°C, suggesting increased frequency of ROS. This will have far-reaching implications for Arctic ecosystems and societies through the changes in snow-pack and permafrost properties.

The theory of predation risk effects predicts behavioral responses in prey when risk of predation is not homogenous in space and time. Prey species are often faced with a tradeoff between food and safety in situations where food availability and predation risk peak in the same habitat type. Determining the optimal strategy becomes more complex if predators with different hunting mode create contrasting landscapes of risk, but this has rarely been documented in vertebrates. Roe deer in southeastern Norway face predation risk from lynx, as well as hunting by humans. These two predators differ greatly in their hunting methods. The predation risk from lynx, an efficient stalk-and-ambush predator is expected to be higher in areas with dense understory vegetation, while predation risk from human hunters is expected to be higher where visual sight lines are longer. Based on field observations and airborne LiDAR data from 71 lynx predation sites, 53 human hunting sites, 132 locations from 15 GPS-marked roe deer, and 36 roe deer pellet locations from a regional survey, we investigated how predation risk was related to terrain attributes and vegetation classes/structure. As predicted, we found that increasing cover resulted in a contrasting lower predation risk from humans and higher predation risk from lynx. Greater terrain ruggedness increased the predation risk from both predators. Hence, multiple predators may create areas of contrasting risk as well as double risk in the same landscape. Our study highlights the complexity of predator-prey relationship in a multiple predator setting.