Pittsburgh air quality study overview

Ambient sampling for the Pittsburgh Air Quality Study (PAQS) was conducted from July 2001 to September 2002. The study was designed (1) to characterize particulate matter (PM) by examination of size, surface area, and volume distribution, chemical composition as a function of size and on a single particle basis, morphology, and temporal and spatial variability in the Pittsburgh region; (2) to quantify the impact of the various sources (transportation, power plants, biogenic sources, etc.) on the aerosol concentrations in the area; and (3) to develop and evaluate the next generation of atmospheric aerosol monitoring and modeling techniques. The PAQS objectives, study design, site descriptions and routine and intensive measurements are presented. Special study days are highlighted, including those associated with elevated concentrations of daily average PM2.5 mass. Monthly average and diurnal patterns in aerosol number concentration, and aerosol nitrate, sulfate, elemental carbon, and organic carbon concentrations, light scattering as well as gas-phase ozone, nitrogen oxides, and carbon monoxide are discussed with emphasis on the processes affecting them. Preliminary findings reveal day-to-day variability in aerosol mass and composition, but consistencies in seasonal average diurnal profiles and concentrations. For example, the seasonal average variations in the diurnal PM2.5 mass were predominately driven by the sulfate component. © 2004 Elsevier Ltd. All rights reserved.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Biological and Physical Factors Affecting the Natural History and Evolution of Encapsulated Development

The evolution of reproductive strategies involves a complex calculus of costs and benefits to both parents and offspring. Many marine animals produce embryos packaged in tough egg capsules or gelatinous egg masses attached to benthic surfaces. While these egg structures can protect against environmental stresses, the packaging is energetically costly for parents to produce. In this series of studies, I examined a variety of ecological factors affecting the evolution of benthic development as a life history strategy. I used marine gastropods as my model system because they are incredibly diverse and abundant worldwide, and they exhibit a variety of reproductive and developmental strategies.

The first study examines predation on benthic egg masses. I investigated: 1) behavioral mechanisms of predation when embryos are targeted (rather than the whole egg mass); 2) the specific role of gelatinous matrix in predation. I hypothesized that gelatinous matrix does not facilitate predation. One study system was the sea slug Olea hansineensis, an obligate egg mass predator, feeding on the sea slug Haminoea vesicula. Olea fed intensely and efficiently on individual Haminoea embryos inside egg masses but showed no response to live embryos removed from gel, suggesting that gelatinous matrix enables predation. This may be due to mechanical support of the feeding predator by the matrix. However, Haminoea egg masses outnumber Olea by two orders of magnitude in the field, and each egg mass can contain many tens of thousands of embryos, so predation pressure on individuals is likely not strong. The second system involved the snail Nassarius vibex, a non-obligate egg mass predator, feeding on the polychaete worm Clymenella mucosa. Gel neither inhibits nor promotes embryo predation for Nassarius, but because it cannot target individual embryos inside an egg mass, its feeding is slow and inefficient, and feeding rates in the field are quite low. However, snails that compete with Nassarius for scavenged food have not been seen to eat egg masses in the field, leaving Nassarius free to exploit the resource. Overall, egg mass predation in these two systems likely benefits the predators much more than it negatively affects the prey. Thus, selection for environmentally protective aspects of egg mass production may be much stronger than selection for defense against predation.

In the second study, I examined desiccation resistance in intertidal egg masses made by Haminoea vesicula, which preferentially attaches its flat, ribbon-shaped egg masses to submerged substrata. Egg masses occasionally detach and become stranded on exposed sand at low tide. Unlike adults, the encased embryos cannot avoid desiccation by selectively moving about the habitat, and the egg mass shape has high surface-area-to-volume ratio that should make it prone to drying out. Thus, I hypothesized that the embryos would not survive stranding. I tested this by deploying individual egg masses of two age classes on exposed sand bars for the duration of low tide. After rehydration, embryos midway through development showed higher rates of survival than newly-laid embryos, though for both stages survival rates over 25% were frequently observed. Laboratory desiccation trials showed that >75% survival is possible in an egg mass that has lost 65% of its water weight, and some survival (<25%) was observed even after 83% water weight lost. Although many surviving embryos in both experiments showed damage, these data demonstrate that egg mass stranding is not necessarily fatal to embryos. They may be able to survive a far greater range of conditions than they normally encounter, compensating for their lack of ability to move. Also, desiccation tolerance of embryos may reduce pressure on parents to find optimal laying substrata.

The third study takes a big-picture approach to investigating the evolution of different developmental strategies in cone snails, the largest genus of marine invertebrates. Cone snail species hatch out of their capsules as either swimming larvae or non-dispersing forms, and their developmental mode has direct consequences for biogeographic patterns. Variability in life history strategies among taxa may be influenced by biological, environmental, or phylogenetic factors, or a combination of these. While most prior research has examined these factors singularly, my aim was to investigate the effects of a host of intrinsic, extrinsic, and historical factors on two fundamental aspects of life history: egg size and egg number. I used phylogenetic generalized least-squares regression models to examine relationships between these two egg traits and a variety of hypothesized intrinsic and extrinsic variables. Adult shell morphology and spatial variability in productivity and salinity across a species geographic range had the strongest effects on egg diameter and number of eggs per capsule. Phylogeny had no significant influence. Developmental mode in Conus appears to be influenced mostly by species-level adaptations and niche specificity rather than phylogenetic conservatism. Patterns of egg size and egg number appear to reflect energetic tradeoffs with body size and specific morphologies as well as adaptations to variable environments. Overall, this series of studies highlights the importance of organism-scale biotic and abiotic interactions in evolutionary patterns.

Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors

Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

Role of Hydrological Process Representation on Erosion, Deposition, and Sediment Yield Estimate

Soil erosion by water is a major driven force causing land degradation. Laboratory experiments, on-site field study, and suspended sediments measurements were major fundamental approaches to study the mechanisms of soil water erosion and to quantify the erosive losses during rain events. The experimental research faces the challenge to extent the result to a wider spatial scale. Soil water erosion modeling provides possible solutions for scaling problems in erosion research, and is of principal importance to better understanding the governing processes of water erosion. However, soil water erosion models were considered to have limited value in practice. Uncertainties in hydrological simulations are among the reasons that hindering the development of water erosion model. Hydrological models gained substantial improvement recently and several water erosion models took advantages of the improvement of hydrological models. It is crucial to know the impact of changes in hydrological processes modeling on soil erosion simulation.

This dissertation work first created an erosion modeling tool (GEOtopSed) that takes advantage of the comprehensive hydrological model (GEOtop). The newly created tool was then tested and evaluated at an experimental watershed. The GEOtopSed model showed its ability to estimate multi-year soil erosion rate with varied hydrological conditions. To investigate the impact of different hydrological representations on soil erosion simulation, a 11-year simulation experiment was conducted for six models with varied configurations. The results were compared at varied temporal and spatial scales to highlight the roles of hydrological feedbacks on erosion. Models with simplified hydrological representations showed agreement with GEOtopSed model on long temporal scale (longer than annual). This result led to an investigation for erosion simulation at different rainfall regimes to check whether models with different hydrological representations have agreement on the soil water erosion responses to the changing climate. Multi-year ensemble simulations with different extreme precipitation scenarios were conducted at seven climate regions. The differences in erosion simulation results showed the influences of hydrological feedbacks which cannot be seen by purely rainfall erosivity method.