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Dennis Murray

Publications and source records attributed to Dennis Murray.

3 recordsLinked to original sources

Demographic mechanisms of snowshoe hare population cycles in Yukon, Canada

One hundred years have elapsed since Charles Elton (1924) described the periodic fluctuations in North American snowshoe hare abundance, yet mechanisms underlying 9–11-year population cycles in snowshoe hares continue to be debated. We applied multistate capture–mark–recapture models to long-term field data (1977–2020) based on >20,000 captures of >7000 unique snowshoe hares ( Lepus americanus ) from Kluane Lake, Yukon, Canada, to estimate and model state-specific demographic parameters. Juveniles had the lowest and reproductive adult females the highest apparent survival. Apparent survival of all sex-age classes was highest during the mid- and late-breeding seasons and was generally better during the increase phase. Conditional probability of females transitioning from non-reproductive to reproductive state, and reproductive females remaining in the reproductive state, increased substantially as the population transitioned from low to increase phase throughout the breeding season. Analysis of stage-structured matrix population models revealed that population-dynamic characteristics were strongly phase-specific, and also varied across seasons, with the increase phases being characterized by high monthly asymptotic population growth rate. Snowshoe hares experienced short stage-specific generation time during the early breeding season across all phases; they experienced relatively long generation time during the increase and low phase of the mid-breeding season, and the increase and peak phase of the late breeding season. Elasticity analyses showed that asymptotic population growth rate was proportionately most sensitive to changes in survival of adult females across all phases and seasons. However, retrospective life table response experiment analysis showed that rapid growth of the snowshoe hare populations during the increase phase was due to improvements in reproductive transitions and pre-weaning survival, whereas population declines are caused primarily by reduced survival (primarily, pre-weaning survival), with reduced reproductive transitions and smaller litter sizes playing a secondary role. Our results suggest that cyclic populations of snowshoe hares are characterized by complex demographic and population-dynamic patterns, depending on phase of the cycle and reproductive season, and that different demographic mechanisms underlie rapid population growth during the increase phase, and swift population declines as the population transitions from the peak to the decline phase. Because our study represents the first comprehensive demographic and population-dynamic study of a cyclic population, similar studies would be needed to test the generalities of our conclusions. Whereas density-dependent predation has been shown to be the primary cause of phase-related changes in survival, future research should focus on identifying mechanisms underlying phase-related changes in reproductive parameters.

Yukon

Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore

Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator–prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability and predator space use, we examined patterns of black bear ( Ursus americanus ) predation of caribou ( Rangifer tarandus ) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per‐capita rate at which bears killed calves followed a type‐I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time‐scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator–prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore.

Journal of Animal Ecology

Moving forward in circles: Challenges and opportunities in modeling population cycles

Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research.

Ecology Letters