Beth E. Ross

An Accessible Method for Implementing Hierarchical Models with Spatio-Temporal Abundance Data

A common goal in ecology and wildlife management is to determine the causes of variation in population dynamics over long periods of time and across large spatial scales. Many assumptions must nevertheless be overcome to make appropriate inference about spatio-temporal variation in population dynamics, such as autocorrelation among data points, excess zeros, and observation error in count data. To address these issues, many scientists and statisticians have recommended the use of Bayesian hierarchical models. Unfortunately, hierarchical statistical models remain somewhat difficult to use because of the necessary quantitative background needed to implement them, or because of the computational demands of using Markov Chain Monte Carlo algorithms to estimate parameters. Fortunately, new tools have recently been developed that make it more feasible for wildlife biologists to fit sophisticated hierarchical Bayesian models (i.e., Integrated Nested Laplace Approximation, ‘INLA’). We present a case study using two important game species in North America, the lesser and greater scaup, to demonstrate how INLA can be used to estimate the parameters in a hierarchical model that decouples observation error from process variation, and accounts for unknown sources of excess zeros as well as spatial and temporal dependence in the data. Ultimately, our goal was to make unbiased inference about spatial variation in population trends over time.

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potentil interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding. conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

ABSTRACT Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

Effects of prairie vole runways on tallgrass prairie

Abstract Disturbances by large mammals influence plant populations and ecosystem processes. In contrast, impacts on ecosystem processes at local scales by small herbivorous rodents are relatively unknown. To examine effects of the runways of prairie voles (Microtus ochrogaster) on soil nitrogen, we collected soil cores from under runways, along the runway edges and at 0.25 and 2 m away from runways. Plant samples (both current and previous years growth) were clipped from microsites at edges of runways and at 0.25 and 2 m away from runways. Concentrations of soil nitrate were highest along runway edges and lowest 2 m away, whereas those of ammonium were highest 0.25 m away from runways and lowest under runways and along runway edges. Biomass of plants from previous growth (litter) was higher along edges of runways than at 0.25 and 2 m from runway edges. In contrast to differences in soil nitrate and ammonium concentrations and in litter biomass among microsites, carbon: nitrogen (C:N) ratios of big bluestem and live plant biomass were similar among the three microsites. Our data suggest that prairie voles do affect nutrient dynamics and plant litter at a local scale in tallgrass prairie.