Assessing the importance of demographic parameters for population dynamics using Bayesian integrated population modeling

Abstract

To successfully respond to changing habitat, climate or harvest, managers need to identify the most effective strategies to reverse population trends of declining species and/or manage harvest of game species. A classic approach in conservation biology for the last two decades has been the use of matrix population models to determine the most important vital rates affecting population growth rate (λ), that is, sensitivity. Ecologists quickly realized the critical role of environmental variability in vital rates affecting λ by developing approaches such as life-stage simulation analysis (LSA) that account for both sensitivity and variability of a vital rate. These LSA methods used matrix-population modeling and Monte Carlo simulation methods, but faced challenges in integrating data from different sources, disentangling process and sampling variation, and in their flexibility. Here, we developed a Bayesian integrated population model (IPM) for two populations of a large herbivore, elk (Cervus canadensis) in Montana, USA. We then extended the IPM to evaluate sensitivity in a Bayesian framework. We integrated known-fate survival data from radio-marked adults and juveniles, fecundity data, and population counts in a hierarchical population model that explicitly accounted for process and sampling variance. Next, we tested the prevailing paradigm in large herbivore population ecology that juvenile survival of neonates <90 d old drives λ using our Bayesian LSA approach. In contrast to the prevailing paradigm in large herbivore ecology, we found that adult female survival explained more of the variation in λ than elk calf survival, and that summer and winter elk calf survival periods were nearly equivalent in importance for λ. Our Bayesian IPM improved precision of our vital rate estimates and highlighted discrepancies between count and vital rate data that could refine population monitoring, demonstrating that combining sensitivity analysis with population modeling in a Bayesian framework can provide multiple advantages. Our Bayesian LSA framework will provide a useful approach to addressing conservation challenges across a variety of species and data types.

Roles of maternal condition and predation in survival of juvenile Elk in Oregon

“…Population growth rates of elk tend to be most sensitive to adult female survival followed by juvenile survival, and finally pregnancy rates (Raithel et al , Eacker et al ). Harvest of adult female elk has the greatest effect on elk population dynamics (Clark , Eacker et al , Lehman et al ), but in unhunted or lightly hunted populations, survival of adult female elk tends to be high and invariable (Brodie et al ).…”

“…Population growth rates of elk tend to be most sensitive to adult female survival followed by juvenile survival, and finally pregnancy rates (Raithel et al , Eacker et al ). Harvest of adult female elk has the greatest effect on elk population dynamics (Clark , Eacker et al , Lehman et al ), but in unhunted or lightly hunted populations, survival of adult female elk tends to be high and invariable (Brodie et al ). As wildlife managers reduced antlerless elk hunting to maintain elk populations (Brodie et al ), annual variation in juvenile survival and secondarily in pregnancy rates then have the greatest effect on population growth rates (Raithel et al , Eacker et al ).…”

“…Harvest of adult female elk has the greatest effect on elk population dynamics (Clark , Eacker et al , Lehman et al ), but in unhunted or lightly hunted populations, survival of adult female elk tends to be high and invariable (Brodie et al ). As wildlife managers reduced antlerless elk hunting to maintain elk populations (Brodie et al ), annual variation in juvenile survival and secondarily in pregnancy rates then have the greatest effect on population growth rates (Raithel et al , Eacker et al ). Using empirical data observed from field studies conducted in northeastern Oregon (e.g., this study, Johnson et al ), Clark () assessed the relative magnitude of observed effects of top‐down, surrogate measures of nutrition, and climate factors on elk population dynamics.…”

“…Consult Cook et al (,; 2004; 2013) for interpreting these metrics. If appropriate data sets exist, assess long‐term relationships between climate (e.g., winter weather severity, summer precipitation) and population parameters (e.g., juvenile to adult female ratios, yearling male harvest), which may help identify effects of annual variation in weather patterns on recruitment. Investigate trends between long‐term carnivore populations and measures of population performance (e.g., yearling male harvest, juvenile to adult female ratios) to determine the degree to which predation may be influencing recruitment. Assess juvenile to adult female ratios in autumn (Sep–Oct) and at end of winter to determine timing of juvenile mortality. Low juvenile to female ratios in late summer indicate that substantial mortality occurred (assuming high pregnancy rates) and resources should be targeted toward understanding low rates of summer survival. Using all of the above data, develop elk population models (Clark , Eacker et al , Lehman et al ) to assess factors affecting vital rates at the local scale to help guide management decisions.…”

Drivers and demographic consequences of seasonal mass changes in an alpine ungulate

“…At Ram Mountain, winter lamb survival increased with spring temperature in the year of birth (Portier et al 1998). Juvenile winter survival is often (but not always; Eacker et al 2017) one of the principal demographic parameters determining population growth of large mammals, including bighorn sheep (Coulson et al 1999(Coulson et al , 2005. Juvenile winter survival is often (but not always; Eacker et al 2017) one of the principal demographic parameters determining population growth of large mammals, including bighorn sheep (Coulson et al 1999(Coulson et al , 2005.…”