<p>Anthropogenic contributions to global reactive N pools have more than doubled since the agricultural and industrial revolutions. Although N is an essential plant nutrient, enrichment of reactive N in air pollution can initiate a cascade of deleterious effects including increased smog and haze, ecosystem acidification, increased invasion of non-native grasses, and reduced biodiversity. However, the ecological impacts of N deposition in historically N-limited, semi-arid regions are not well understood. Here, I report the findings from field studies of automobile pollution in Grand Canyon National Park (GCNP; Study 1) and long-range N deposition from the nearest coal-fired power plant, the Navajo Generating Station (NGS; Study 2). To identify potential indicators of N enrichment, I measured four different metrics of N pollution: 1) atmospheric nitrogen oxides (NO_x) with Ogawa passive air samplers, 2) natural abundance &delta;¹⁵N signatures of soil and foliage of pinyon pine (<i>Pinus edulis</i>), 3) spectral analysis of pinyon pine foliar nitrogen, and 4) leaf area on pinyon pine branches. </p><p> In both studies, the amount of NO_x measured by the Ogawa samplers decreased significantly with increasing distance from N-source. In heavily trafficked sites in GCNP, atmospheric NO_x was 52% higher at the roadside compared to 30 m away from the road. Atmospheric NO_x on the Paria Plateau was 54% higher 25 km from NGS compared to 50 km away from the coal-fired power plant. Across both study areas, &delta;¹⁵N values in plant tissues reflected inputs from emission sources. According to our data, the biggest ground level N inputs in GCNP are from vehicular emissions, not NGS. Although I detected patterns in terrestrial responses to both small and larger-scale N deposition gradients, future field studies focused on plant community composition and sensitive biological indicators are needed to determine ramifications of elevated N inputs caused by pollution from motor vehicles and power plants. </p>

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008. / Source: Dissertation Abstracts International, Volume: 69-05, Section: B, page: 2881. Adviser: Anton G. Endress. Includes bibliographical references. Available on microfilm from Pro Quest Information and Learning.

<p>Amphibian populations have been declining at higher rates than bird and mammal populations. Agriculture, urbanization, including roads, and resource extraction continue to put pressure on all species. Roads in particular, are major sources of mortality. The Santa Cruz long-toed salamander (<i> Ambystoma macrodactylum croceum</i>), one of the most critically endangered species in the US, is one amphibian that is declining as a result of anthropogenic impacts, especially habitat loss and fragmentation due to urban development. Migration across roads puts these salamanders at risk from road-related death. This thesis quantified the rate of road mortality to these salamanders and other common amphibians during two A. m. croceum breeding-migration seasons in 2011&ndash;13 in a portion of the subspecies' range. Vehicular traffic was a major source of mortality to the salamander. Through traffic doubled the overall vehicle load on roads where the <i>A. m. croceum</i> migrated to and from breeding ponds. The Pacific chorus frog was also killed on the roads. This common species can be used as an indicator of road mortality risk for rarer amphibians. This study indicated that measures to reduce road mortality to the Santa Cruz long-toed salamander could include restricting vehicular traffic on roads adjacent to salamander ponds by limiting traffic to residential use only during breeding migrations, installing structures to protect <i>A. m. croceum</i> while crossing roads, and potentially assisting animals crossing roads at nighttime during the breeding migrations. </p>

<p> A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. <i>Every</i> location has a unique and constantly changing climate so that <i>any</i> distribution <i> could</i> be explained by some aspect of climate. </p><p> Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. </p><p> Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. </p><p> In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. </p><p> Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. </p><p> Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.) </p>

No description available.

Thesis (Ph.D.)--University of California, Berkeley, 2003. / (UnM)AAI3206946. Adviser: Wayne M. Getz. Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0060.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-07, Section: A, page: 2700. Adviser: Bruce M. Hannon. Includes bibliographical references (leaves 167-184) Available on microfilm from Pro Quest Information and Learning.