Toxicity and Contamination in Bear Creek Sediment: Spatial Analysis and Implications for Risk Assessment

The sediments of Bear Creek near Baltimore, Maryland demonstrate substantial toxicity to benthic organisms, and contain a complex mixture of organic and inorganic contaminants. The present study maps the spatial extent and depth profile of toxicity and contamination in Bear Creek, and explores correlations between heavy metals, organic contaminants, and toxic responses. Two novel analytical techniques ��� handheld XRF and an antibody-based PAH biosensor ��� were applied to samples from the site to quantify total metals and total PAHs in sediments. By comprehensively assessing toxicity in Bear Creek, the present study provides data to inform future risk assessments and management decisions relating for the site, while demonstrating the benefits of applying joint biological assays and chemical assessment methods to sediments with complex contaminant mixtures.

Geography and Genetics of Ecological Speciation in Pea Aphids

During ecological speciation, divergent natural selection drives evolution of ecological specialization and genetic differentiation of populations on alternate environments. Populations diverging onto the same alternate environments may be geographically widespread, so that divergence may occur at an array of locations simultaneously. Spatial variation in the process of divergence may produce a pattern of differences in divergence among locations called the Geographic Mosaic of Divergence. Diverging populations may vary in their degree of genetic differentiation and ecological specialization among locations. My dissertation examines the pattern and evolutionary processes of divergence in pea aphids (Acyrthosiphon pisum) on alfalfa (Medicago sativa) and clover (Trifolium pretense). In Chapter One, I examined differences among North American aphid populations in genetic differentiation at nuclear, sequence-based markers and in ecological specialization, measured as aphid fecundity on each host plant. In the East, aphids showed high host-plant associated ecological specialization and high genetic differentiation. In the West, aphids from clover were genetically indistinguishable from aphids on alfalfa, and aphids from clover were less specialized. Thus, the pattern of divergence differed among locations, suggesting a Geographic Mosaic of Divergence. In Chapter Two, I examined genomic heterogeneity in divergence in aphids on alfalfa and clover across North America using amplified fragment length polymorphisms (AFLPs). The degree of genetic differentiation varied greatly among markers, suggesting that divergent natural selection drives aphid divergence in all geographic locations. Three of the same genetic markers were identified as evolving under divergent selection in the eastern and western regions, and additional divergent markers were identified in the East. In Chapter Three, I investigated population structure of aphids in North America, France, and Sweden using AFLPs. Aphids on the same host plant were genetically similar across many parts of their range, so the evolution of host plant specialization does not appear to have occurred independently in every location. While aphids on alfalfa and clover were genetically differentiated in most locations, aphids from alfalfa and clover were genetically similar in both western North America and Sweden. High gene flow from alfalfa onto clover may constrain divergence in these locations.

DYNAMICS OF THE SHORT TERM AND LONG TERM AVIAN DISTRIBUTIONS IN NORTH AMERICA - THE ROLES OF VEGETATION HEIGHT HETEROGENEITY AND CLIMATIC FACTORS

Understanding how biodiversity spatially distribute over both the short term and long term, and what factors are affecting the distribution, are critical for modeling the spatial pattern of biodiversity as well as for promoting effective conservation planning and practices. This dissertation aims to examine factors that influence short-term and long-term avian distribution from the geographical sciences perspective. The research develops landscape level habitat metrics to characterize forest height heterogeneity and examines their efficacies in modelling avian richness at the continental scale. Two types of novel vegetation-height-structured habitat metrics are created based on second order texture algorithms and the concepts of patch-based habitat metrics. I correlate the height-structured metrics with the richness of different forest guilds, and also examine their efficacies in multivariate richness models. The results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of two forest bird guilds. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. The second and the third projects focus on analyzing centroids of avian distributions, and testing hypotheses regarding the direction and speed of these shifts. I first showcase the usefulness of centroids analysis for characterizing the distribution changes of a few case study species. Applying the centroid method on 57 permanent resident bird species, I show that multi-directional distribution shifts occurred in large number of studied species. I also demonstrate, plain birds are not shifting their distribution faster than mountain birds, contrary to the prediction based on climate change velocity hypothesis. By modelling the abundance change rate at regional level, I show that extreme climate events and precipitation measures associate closely with some of the long-term distribution shifts. This dissertation improves our understanding on bird habitat characterization for species richness modelling, and expands our knowledge on how avian populations shifted their ranges in North America responding to changing environments in the past four decades. The results provide an important scientific foundation for more accurate predictive species distribution modeling in future.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or ���greendown���, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar ��13C (proxy for intrinsic water use efficiency), but foliar ��13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change