Date of Award

Fall 2024

Project Type

Dissertation

Program or Major

Natural Resources and Environmental Studies

Degree Name

Doctor of Philosophy

First Advisor

Rebecca J. Rowe

Second Advisor

Adrienne Kovach

Third Advisor

Elizabeth Burakowski

Abstract

Rodent populations at northern latitudes undergo cyclic dynamics characterized by high amplitude interannual fluctuations every 3-5 years. Population cycles have puzzled mammalogists for over a century and disentangling their drivers remains a central goal. Understanding which factors drive rodent populations and how these dynamics might change with warming is essential for predicting the impacts of climate change on arctic ecosystems as herbivore pressure shapes plant community composition, soil nutrient availability and carbon concentrations. My research focused on potential drivers of brown lemming (Lemmus trimucronatus) and tundra vole (Microtus oeconomus) population fluctuations in Arctic Alaska. I combined field techniques with laboratory analyses of stress hormone levels and took advantage of long-term monitoring programs and museum specimens from historical field collections. As the Arctic warms, large scale disturbances such as fire and thawing permafrost are becoming more frequent and severe. In Chapter 1, I examine the impact of post-fire successional changes in vegetation structure and composition on tundra vole abundance and herbivory rates in response to a large and unprecedented fire in northern Alaskan tussock tundra. I found that mid-successional changes in vegetation (a decade after the fire) enhance habitat suitability for tundra voles through a combination of increases in food quality, quantity, and cover. These changes resulted in a tenfold increase in tundra vole densities, which in turn, increased rates of herbivory and tussock mortality. These findings suggest the subsequent increase in herbivore pressure could disrupt graminoid recovery and promote the competitive release of less palatable shrub species. Stress hormones (cortisol and corticosterone) are critical for allowing animals to cope with changes and challenges in their environment and can affect individual survival and reproductive success. Further, chronic exposure to stressors, with transgenerational consequences (through maternal effects) can result in the delayed density dependent changes in reproduction required to generate population cycles. In Chapter 2, I used hair samples from capture-mark-recapture surveys (2018–2022) to examine potential mechanisms (both intrinsic and extrinsic) driving brown lemming populations, and in particular, the linkage between stress and cyclicity in Utqiaġvik (formerly Barrow) Alaska. I found a positive relationship between brown lemming stress hormone levels and population density, and that patterns in stress hormone levels across the population cycle were consistent with delayed density dependent maternal effects. Colder winter temperatures and warmer summer temperatures were positively associated with stress hormone levels, suggesting that changing environmental conditions may influence lemming stress hormone levels, potentially resulting in both more tolerable and more challenging conditions. In Chapter 3, I sampled brown lemming museum specimens from historical field collections from the same site over multiple population cycles (1951–1963) to assess the influence of cycle phase and environmental conditions on stress hormone levels. I also compared the natural range of variability in the historical samples to modern samples (2018–2022). I found that stress hormone levels did not show consistent trends with cycle phases. Winter conditions (temperature and snow depth) were significantly associated with historical brown lemming stress hormone levels, such that colder temperatures and deeper snow depths were associated with higher stress hormone levels. The modern-historical comparison showed modern lemming populations have similar average stress hormone levels, but significantly greater variation relative to the historical period, potentially reflecting increased variability in environmental conditions.

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