Our work in population ecology broadly encompasses assessment of the sources of population growth and decline. This research involves a range of methods and systems to estimate survival and productivity, as well as analysis of population time series towards understanding patterns of numerical growth and regulation.
Patterns of density dependence
It is well understood that animal populations are regulated by density dependent forces, but there are different patterns by which density dependence can be manifest on population growth. Currently, there is considerable controversy regarding appropriate statistical models to describe growth and regulation in single-species populations. Moreover, it is not clear how density dependence may vary in space and time in populations inhabiting complex environments. Using breeding waterfowl survey data, we are examining why patterns of density dependence in numbers of breeders has varied fundamentally through time. We suspect that environmental change promoting increased nest predation by generalist predators is driving the waterfowl system to a state of increased stochasticity. We are extending this work to gauge whether large-scale changes in landscape or climate features contribute to variability in density dependence, population asynchrony, and numerical stability. We are further developing this area of research using algae grown in experimental microcosms, to test in a more controlled manner questions addressing population responses to perturbation and density-dependent regulation.
It is well understood that animal populations are regulated by density dependent forces, but there are different patterns by which density dependence can be manifest on population growth. Currently, there is considerable controversy regarding appropriate statistical models to describe growth and regulation in single-species populations. Moreover, it is not clear how density dependence may vary in space and time in populations inhabiting complex environments. Using breeding waterfowl survey data, we are examining why patterns of density dependence in numbers of breeders has varied fundamentally through time. We suspect that environmental change promoting increased nest predation by generalist predators is driving the waterfowl system to a state of increased stochasticity. We are extending this work to gauge whether large-scale changes in landscape or climate features contribute to variability in density dependence, population asynchrony, and numerical stability. We are further developing this area of research using algae grown in experimental microcosms, to test in a more controlled manner questions addressing population responses to perturbation and density-dependent regulation.
Vital rate estimation
Demographic rates are the metrics by which populations grow and decline, and it is important not only to estimate these rates accurately but also to understand the sources of their variability. We work on questions related to vital rate estimation in a range of mammal species, and we assess the role of biotic and abiotic factors in causing changes in those rates. Of particular interest is the estimation of survival and competing risks in species such as wolves and snowshoe hares, and towards this end we have been at altthe forefront of adapting time-to-event statistical methods to analyze survival data obtained from wildlife telemetry data. Among the novel inferences made available via these analytical methods are whether anthropogenic factors play an additive or compensatory effect on mortality patterns, and how different predator species may select unique types of individuals from the prey population.
Demographic rates are the metrics by which populations grow and decline, and it is important not only to estimate these rates accurately but also to understand the sources of their variability. We work on questions related to vital rate estimation in a range of mammal species, and we assess the role of biotic and abiotic factors in causing changes in those rates. Of particular interest is the estimation of survival and competing risks in species such as wolves and snowshoe hares, and towards this end we have been at altthe forefront of adapting time-to-event statistical methods to analyze survival data obtained from wildlife telemetry data. Among the novel inferences made available via these analytical methods are whether anthropogenic factors play an additive or compensatory effect on mortality patterns, and how different predator species may select unique types of individuals from the prey population.