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.

The increasing impact of human immunodeficiency virus infections, sexually transmitted diseases, and viral hepatitis in Durham County, North Carolina: a call for coordinated and integrated services.

BACKGROUND: Durham County, North Carolina, faces high rates of human immunodeficiency virus (HIV) infection (with or without progression to AIDS) and sexually transmitted diseases (STDs). We explored the use of health care services and the prevalence of coinfections, among HIV-infected residents, and we recorded community perspectives on HIV-related issues. METHODS: We evaluated data on diagnostic codes, outpatient visits, and hospitalizations for individuals with HIV infection, STDs, and/or hepatitis B or C who visited Duke University Hospital System (DUHS). Viral loads for HIV-infected patients receiving care were estimated for 2009. We conducted geospatial mapping to determine disease trends and used focus groups and key informant interviews to identify barriers and solutions to improving testing and care. RESULTS: We identified substantial increases in HIV/STDs in the southern regions of the county. During the 5-year period, 1,291 adults with HIV infection, 4,245 with STDs, and 2,182 with hepatitis B or C were evaluated at DUHS. Among HIV-infected persons, 13.9% and 21.8% were coinfected with an STD or hepatitis B or C, respectively. In 2009, 65.7% of HIV-infected persons receiving care had undetectable viral loads. Barriers to testing included stigma, fear, and denial of risk, while treatment barriers included costs, transportation, and low medical literacy. LIMITATIONS: Data for health care utilization and HIV load were available from different periods. Focus groups were conducted among a convenience sample, but they represented a diverse population. CONCLUSIONS: Durham County has experienced an increase in the number of HIV-infected persons in the county, and coinfections with STDs and hepatitis B or C are common. Multiple barriers to testing/treatment exist in the community. Coordinated care models are needed to improve access to HIV care and to reduce testing and treatment barriers.

The price of innovation: new estimates of drug development costs.

The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per new drug is 403 million US dollars (2000 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 11% yields a total pre-approval cost estimate of 802 million US dollars (2000 dollars). When compared to the results of an earlier study with a similar methodology, total capitalized costs were shown to have increased at an annual rate of 7.4% above general price inflation.

Innovation in the pharmaceutical industry: New estimates of R&D costs.

The research and development costs of 106 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug and biologics development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per approved new compound is $1395 million (2013 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 10.5% yields a total pre-approval cost estimate of $2558 million (2013 dollars). When compared to the results of the previous study in this series, total capitalized costs were shown to have increased at an annual rate of 8.5% above general price inflation. Adding an estimate of post-approval R&D costs increases the cost estimate to $2870 million (2013 dollars).

Large-area nanopatterning of self-assembled monolayers of alkanethiolates by interferometric lithography.

We demonstrate that interferometric lithography provides a fast, simple approach to the production of patterns in self-assembled monolayers (SAMs) with high resolution over square centimeter areas. As a proof of principle, two-beam interference patterns, formed using light from a frequency-doubled argon ion laser (244 nm), were used to pattern methyl-terminated SAMs on gold, facilitating the introduction of hydroxyl-terminated adsorbates and yielding patterns of surface free energy with a pitch of ca. 200 nm. The photopatterning of SAMs on Pd has been demonstrated for the first time, with interferometric exposure yielding patterns of surface free energy with similar features sizes to those obtained on gold. Gold nanostructures were formed by exposing SAMs to UV interference patterns and then immersing the samples in an ethanolic solution of mercaptoethylamine, which etched the metal substrate in exposed areas while unoxidized thiols acted as a resist and protected the metal from dissolution. Macroscopically extended gold nanowires were fabricated using single exposures and arrays of 66 nm gold dots at 180 nm centers were formed using orthogonal exposures in a fast, simple process. Exposure of oligo(ethylene glycol)-terminated SAMs to UV light caused photodegradation of the protein-resistant tail groups in a substrate-independent process. In contrast to many protein patterning methods, which utilize multiple steps to control surface binding, this single step process introduced aldehyde functional groups to the SAM surface at exposures as low as 0.3 J cm(-2), significantly less than the exposure required for oxidation of the thiol headgroup. Although interferometric methods rely upon a continuous gradient of exposure, it was possible to fabricate well-defined protein nanostructures by the introduction of aldehyde groups and removal of protein resistance in nanoscopic regions. Macroscopically extended, nanostructured assemblies of streptavidin were formed. Retention of functionality in the patterned materials was demonstrated by binding of biotinylated proteins.

Minding metals: tailoring multifunctional chelating agents for neurodegenerative disease.

Neurodegenerative diseases like Alzheimer's and Parkinson's disease are associated with elevated levels of iron, copper, and zinc and consequentially high levels of oxidative stress. Given the multifactorial nature of these diseases, it is becoming evident that the next generation of therapies must have multiple functions to combat multiple mechanisms of disease progression. Metal-chelating agents provide one such function as an intervention for ameliorating metal-associated damage in degenerative diseases. Targeting chelators to adjust localized metal imbalances in the brain, however, presents significant challenges. In this perspective, we focus on some noteworthy advances in the area of multifunctional metal chelators as potential therapeutic agents for neurodegenerative diseases. In addition to metal chelating ability, these agents also contain features designed to improve their uptake across the blood-brain barrier, increase their selectivity for metals in damage-prone environments, increase antioxidant capabilities, lower Abeta peptide aggregation, or inhibit disease-associated enzymes such as monoamine oxidase and acetylcholinesterase.

Environmental and genetic determinants of colony morphology in yeast.

Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs.

Information programs for technology adoption: The case of energy-efficiency audits

We analyze technology adoption decisions of manufacturing plants in response to government-sponsored energy audits. Overall, plants adopt about half of the recommended energy-efficiency projects. Using fixed effects logit estimation, we find that adoption rates are higher for projects with shorter paybacks, lower costs, greater annual savings, higher energy prices, and greater energy conservation. Plants are 40% more responsive to initial costs than annual savings, suggesting that subsidies may be more effective at promoting energy-efficient technologies than energy price increases. Adoption decisions imply hurdle rates of 50-100%, which is consistent with the investment criteria small and medium-size firms state they use. © 2003 Elsevier B.V. All rights reserved.

Cost of innovation in the pharmaceutical industry.

The research and development costs of 93 randomly selected new chemical entities (NCEs) were obtained from a survey of 12 U.S.-owned pharmaceutical firms. These data were used to estimate the pre-tax average cost of new drug development. The costs of abandoned NCEs were linked to the costs of NCEs that obtained marketing approval. For base case parameter values, the estimated out-of-pocket cost per approved NCE is $114 million (1987 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a 9% discount rate yielded an average cost estimate of $231 million (1987 dollars).

Learning from falling.

Walkers fall frequently, especially during infancy. Children (15-, 21-, 27-, 33-, and 39-month-olds) and adults were tested in a novel foam pit paradigm to examine age-related changes in the relationship between falling and prospective control of locomotion. In trial 1, participants walked and fell into a deformable foam pit marked with distinct visual cues. Although children in all 5 age groups required multiple trials to learn to avoid falling, the number of children who showed adult-like, 1-trial learning increased with age. Exploration and alternative locomotor strategies increased dramatically on learning criterion trials and displays of negative affect were limited. Learning from falling is discussed in terms of the immediate and long-term effects of falling on prospective control of locomotion.

Indexed Regulation

Seminal work by Weitzman (1974) revealed prices are preferred to quantities when marginal benefits are relatively flat compared to marginal costs. We extend this comparison to indexed policies, where quantities are proportional to an index, such as output. We find that policy preferences hinge on additional parameters describing the first and second moments of the index and the ex post optimal quantity level. When the ratio of these variables' coefficients of variation divided by their correlation is less than approximately two, indexed quantities are preferred to fixed quantities. A slightly more complex condition determines when indexed quantities are preferred to prices. Applied to climate change policy, we find that the range of variation and correlation in country-level carbon dioxide emissions and GDP suggests the ranking of an emissions intensity cap (indexed to GDP) compared to a fixed emission cap is not uniform across countries; neither policy clearly dominates the other.

Suppression of DNA-damage checkpoint signaling by Rsk-mediated phosphorylation of Mre11.

Ataxia telangiectasia mutant (ATM) is an S/T-Q-directed kinase that is critical for the cellular response to double-stranded breaks (DSBs) in DNA. Following DNA damage, ATM is activated and recruited by the MRN protein complex [meiotic recombination 11 (Mre11)/DNA repair protein Rad50/Nijmegen breakage syndrome 1 proteins] to sites of DNA damage where ATM phosphorylates multiple substrates to trigger cell-cycle arrest. In cancer cells, this regulation may be faulty, and cell division may proceed even in the presence of damaged DNA. We show here that the ribosomal s6 kinase (Rsk), often elevated in cancers, can suppress DSB-induced ATM activation in both Xenopus egg extracts and human tumor cell lines. In analyzing each step in ATM activation, we have found that Rsk targets loading of MRN complex components onto DNA at DSB sites. Rsk can phosphorylate the Mre11 protein directly at S676 both in vitro and in intact cells and thereby can inhibit the binding of Mre11 to DNA with DSBs. Accordingly, mutation of S676 to Ala can reverse inhibition of the response to DSBs by Rsk. Collectively, these data point to Mre11 as an important locus of Rsk-mediated checkpoint inhibition acting upstream of ATM activation.

Regulation of DNA Double Strand Break Response

To ensure genomic integrity, dividing cells implement multiple checkpoint pathways during the course of the cell cycle. In response to DNA damage, cells may either halt the progression of the cycle (cell cycle arrest) or undergo apoptosis. This choice depends on the extent of damage and the cell's capacity for DNA repair. Cell cycle arrest induced by double-stranded DNA breaks relies on the activation of the ataxia-telangiectasia (ATM) protein kinase, which phosphorylates cell cycle effectors (e.g., Chk2 and p53) to inhibit cell cycle progression. ATM is an S/T-Q directed kinase that is critical for the cellular response to double-stranded DNA breaks. Following DNA damage, ATM is activated and recruited to sites of DNA damage by the MRN protein complex (Mre11-Rad50-Nbs1 proteins) where ATM phosphorylates multiple substrates to trigger a cell cycle arrest. In cancer cells, this regulation may be faulty and cell division may proceed even in the presence of damaged DNA. We show here that the RSK kinase, often elevated in cancers, can suppress DSB-induced ATM activation in both Xenopus egg extracts and human tumor cell lines. In analyzing each step in ATM activation, we have found that RSK disrupts the binding of the MRN complex to DSB DNA. RSK can directly phosphorylate the Mre11 protein at Ser 676 both in vitro and in intact cells and can thereby inhibit loading of Mre11 onto DSB DNA. Accordingly, mutation of Ser 676 to Ala can reverse inhibition of the DSB response by RSK. Collectively, these data point to Mre11 as an important locus of RSK-mediated checkpoint inhibition acting upstream of ATM activation.

The phosphorylation of Mre11 on Ser 676 is antagonized by phosphatases. Here, we screened for phosphatases that target this site and identified PP5 as a candidate. This finding is consistent with the fact that PP5 is required for the ATM-mediated DNA damage response, indicating that PP5 may promote DSB-induced, ATM-dependent DNA damage response by targeting Mre11 upstream of ATM.

Explanatory Model for the Use of Traditional Medicines in Kilimanjaro, Tanzania

Introduction: Traditional medicines are one of the most important means of achieving total health care coverage globally, and their importance in Tanzania extends beyond the impoverished rural areas. Their use remains high even in urban settings among the educated middle and upper classes. They are a critical component healthcare in Tanzania, but they also can have harmful side effects. Therefore we sought to understand the decision-making and reasoning processes by building an explanatory model for the use of traditional medicines in Tanzania.

Methods: We conducted a mixed-methods study between December 2013 and June 2014 in the Kilimanjaro Region of Tanzania. Using purposive sampling methods, we conducted focus group discussions (FGDs) and in-depth interviews of key informants, and the qualitative data were analyzed using an inductive Framework Method. A structured survey was created, piloted, and then administered it to a random sample of adults. We reported upon the reliability and validity of the structured survey, and we used triangulation from multiple sources to synthesize the qualitative and quantitative data.

Results: A total of five FGDs composed of 59 participants and 27 in-depth interviews were conducted in total. 16 of the in-depth interviews were with self-described traditional practitioners or herbal vendors. We identified five major thematic categories that relate to the decision to use traditional medicines in Kilimanjaro: healthcare delivery, disease understanding, credibility of the traditional practices, health status, and strong cultural beliefs.

A total of 473 participants (24.1% male) completed the structured survey. The most common reasons for taking traditional medicines were that they are more affordable (14%, 12.0-16.0), failure of hospital medicines (13%, 11.1-15.0), they work better (12%, 10.7-14.4), they are easier

to obtain (11%, 9.48-13.1), they are found naturally or free (8%, 6.56-9.68), hospital medicines have too many chemical (8%, 6.33-9.40), and they have fewer side effects (8%, 6.25-9.30). The most common uses of traditional medicines were for symptomatic conditions (42%), chronic diseases (14%), reproductive problems (11%), and malaria and febrile illnesses (10%). Participants currently taking hospital medicines for chronic conditions were nearly twice as likely to report traditional medicines usage in the past year (RR 1.97, p=0.05).

Conclusions: We built broad explanatory model for the use of traditional medicines in Kilimanjaro. The use of traditional medicines is not limited to rural or low socioeconomic populations and concurrent use of traditional medicines and biomedicine is high with frequent ethnomedical doctor shopping. Our model provides a working framework for understanding the complex interactions between biomedicine and traditional medicine. Future disease management and treatment programs will benefit from this understanding, and it can lead to synergistic policies with more effective implementation.

Peace and war: trajectories of posttraumatic stress disorder symptoms before, during, and after military deployment in Afghanistan.

In the study reported here, we examined posttraumatic stress disorder (PTSD) symptoms in 746 Danish soldiers measured on five occasions before, during, and after deployment to Afghanistan. Using latent class growth analysis, we identified six trajectories of change in PTSD symptoms. Two resilient trajectories had low levels across all five times, and a new-onset trajectory started low and showed a marked increase of PTSD symptoms. Three temporary-benefit trajectories, not previously described in the literature, showed decreases in PTSD symptoms during (or immediately after) deployment, followed by increases after return from deployment. Predeployment emotional problems and predeployment traumas, especially childhood adversities, were predictors for inclusion in the nonresilient trajectories, whereas deployment-related stress was not. These findings challenge standard views of PTSD in two ways. First, they show that factors other than immediately preceding stressors are critical for PTSD development, with childhood adversities being central. Second, they demonstrate that the development of PTSD symptoms shows heterogeneity, which indicates the need for multiple measurements to understand PTSD and identify people in need of treatment.