The global transport and deposition of anthropogenic nitrogen (N) to downwind ecosystems are significant and continue to increase. Indeed, atmospheric deposition can be a significant source of N to many watersheds, including those in remote, unpopulated areas. Bacterial denitrification in lake sediments may ameliorate the effects of N loading by converting nitrate (NO3-) to N2 gas. Denitrification also produces nitrous oxide (N2O), a potent greenhouse gas. The ecological effects of atmospheric N inputs in terrestrial ecosystems and the pelagic zone of lakes have been well documented; however, similar research in lake sediments is lacking. This project investigates the effects N of deposition on denitrification and N2O production in lakes. Atmospheric N inputs might alter the availability of NO3- and other key resources to denitrifiers. Such altered resources could influence denitrification, N2O production, and the abundance of denitrifying bacteria in sediments. The research contrasts these responses in lakes at the ends of gradients of N deposition in Colorado and Norway. Rates of denitrification and N2O production were elevated in the sediments of lakes subject to anthropogenic N inputs. There was no evidence, however, that N deposition has altered sediment resources or the abundance of denitrifiers. Further investigation into the dynamics of nitric oxide, N2O, and N2 during denitrification found no difference between deposition regions. Regardless of atmospheric N inputs, sediments from lakes in both Norway and Colorado possess considerable capacity to remove NO3- by denitrification. Catchment-specific properties may influence the denitrifying community more strongly than the rate of atmospheric N loading. In this regard, sediments appear to be insulated from the effects of N deposition compared to the water column. Lastly, surface water N2O concentrations were greater in high-deposition lakes compared to low-deposition lakes. To understand the potential magnitude of deposition-induced N2O production, the greenhouse gas inventory methodology of Intergovernmental Panel on Climate Change was applied to available datasets. Estimated emissions from lakes are 7-371 Gg N y-1, suggesting that lakes could be an important source of N2O.
Humans can influence wildlife populations and behavior through structural and behavioral disturbances, which can be particularly pronounced along the gradient of urbanization. Importantly, although anthropogenetic structural characteristics are relatively static along the gradient of urbanization for a given period of time, the presence of humans can be dynamic on daily and seasonal scales, which can affect wildlife activity patterns. The rapid onset of the COVID-19 pandemic created a unique opportunity to evaluate how a sudden change in human behavior can affect wildlife activity along the urbanization gradient. Specifically, we used a before-after-control-impact (BACI) study design to compare human presence and coyote daily activity patterns from before the COVID-19 pandemic to after COVID-19 stay-at-home orders and shutdowns were put in place in areas of low and high levels of urbanization. We predicted that human detection rates would increase in low levels of urbanization and decrease in high levels of urbanization due to the COVID-19 pandemic shutdowns. We also predicted that coyote daily activity patterns would shift in response to human detection rates, where coyotes would become more nocturnal in areas of low levels of urbanization where human presence was expected to increase and become more diurnal in areas of high levels of urbanization where human presence was expected to decrease. We used data from wildlife cameras across the gradient of urbanization from 2019 to 2020 within the Phoenix Valley of Arizona. Across 8 sites in low levels of urbanization and 12 sites in high levels of urbanization, we did not find a statistical difference in human detection rates or coyote activity patterns in response to the COVID-19 pandemic. However, low sample size likely led to low power to detect differences and next steps for this research (as part of my M.S. thesis project) will be incorporating additional wildlife camera locations and wildlife species (e.g., bobcat, cottontail rabbit, gray fox, etc.), into future analyses. This project and future studies can help us better understand how structural and behavioral characteristics of humans can shape wildlife populations along the gradient of urbanization, which has important conservation implications for wildlife and people.