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North E.W.,University of Cambridge | Adams E.E.,Massachusetts Institute of Technology | Thessen A.E.,Data Detektiv | Thessen A.E.,Ronin Institute for Independent Scholarship | And 5 more authors.
Environmental Research Letters | Year: 2015

A better understanding of oil droplet formation, degradation, and dispersal in deep waters is needed to enhance prediction of the fate and transport of subsurface oil spills. This research evaluates the influence of initial droplet size and rates of biodegradation on the subsurface transport of oil droplets, specifically those from the Deepwater Horizon oil spill. A three-dimensional coupled model was employed with components that included analytical multiphase plume, hydrodynamic and Lagrangian models. Oil droplet biodegradation was simulated based on first order decay rates of alkanes. The initial diameter of droplets (10-300 μm) spanned a range of sizes expected from dispersant-treated oil. Results indicate that model predictions are sensitive to biodegradation processes, with depth distributions deepening by hundreds of meters, horizontal distributions decreasing by hundreds to thousands of kilometers, and mass decreasing by 92-99% when biodegradation is applied compared to simulations without biodegradation. In addition, there are two- to four-fold changes in the area of the seafloor contacted by oil droplets among scenarios with different biodegradation rates. The spatial distributions of hydrocarbons predicted by the model with biodegradation are similar to those observed in the sediment and water column, although the model predicts hydrocarbons to the northeast and east of the well where no observations were made. This study indicates that improvement in knowledge of droplet sizes and biodegradation processes is important for accurate prediction of subsurface oil spills. © 2015 IOP Publishing Ltd. Source

Baguskas S.A.,University of California at Santa Barbara | Baguskas S.A.,University of California at Santa Cruz | Still C.J.,University of California at Santa Barbara | Still C.J.,Oregon State University | And 5 more authors.
Oecologia | Year: 2016

Fog water inputs can offset seasonal drought in the Mediterranean climate of coastal California and may be critical to the persistence of many endemic plant species. The ability to predict plant species response to potential changes in the fog regime hinges on understanding the ways that fog can impact plant physiological function across life stages. Our study uses a direct metric of water status, namely plant water potential, to understand differential responses of adult versus sapling trees to seasonal drought and fog water inputs. We place these measurements within a water balance framework that incorporates the varying climatic and soil property impacts on water budgets and deficit. We conducted our study at a coastal and an inland site within the largest stand of the regionally endemic bishop pine (Pinus muricata D. Don) on Santa Cruz Island. Our results show conclusively that summer drought negatively affects the water status of sapling more than adult trees and that sapling trees are also more responsive to changes in shallow soil moisture inputs from fog water deposition. Moreover, between the beginning and end of a large, late-season fog drip event, water status increased more for saplings than for adults. Relative to non-foggy conditions, we found that fog water reduces modeled peak water deficit by 80 and 70 % at the inland and coastal sites, respectively. Results from our study inform mechanistically based predictions of how population dynamics of this and other coastal species may be affected by a warmer, drier, and potentially less foggy future. © 2016 Springer-Verlag Berlin Heidelberg Source

Thessen A.E.,The Data Detektiv | Thessen A.E.,Ronin Institute for Independent Scholarship | Fertig B.,Ronin Institute for Independent Scholarship | Fertig B.,Versar Inc. | And 2 more authors.
Estuaries and Coasts | Year: 2016

Holistic understanding of estuarine and coastal environments across interacting domains with high-dimensional complexity can profitably be approached through data-centric synthesis studies. Synthesis has been defined as “the inferential process whereby new models are developed from analysis of multiple data sets to explain observed patterns across a range of time and space scales.” Examples include ecological—across ecosystem components or organization levels, spatial—across spatial scales or multiple ecosystems, and temporal—across temporal scales. Though data quantity and volume are increasingly accessible, infrastructures for data sharing, management, and integration remain fractured. Integrating heterogeneous data sets is difficult yet critical. Technological and cultural obstacles hamper finding, accessing, and integrating data to answer scientific and policy questions. To investigate synthesis within the estuarine and coastal science community, we held a workshop at a coastal and estuarine research federation conference and conducted two case studies involving synthesis science. The workshop indicated that data-centric synthesis approaches are valuable for (1) hypothesis testing, (2) baseline monitoring, (3) historical perspectives, and (4) forecasting. Case studies revealed important weaknesses in current data infrastructures and highlighted opportunities for ecological synthesis science. Here, we list requirements for a coastal and estuarine data infrastructure. We model data needs and suggest directions for moving forward. For example, we propose developing community standards, accommodating and integrating big and small data (e.g., sensor feeds and single data sets), and digitizing ‘dark data’ (inaccessible, non-curated, non-archived data potentially destroyed when researchers leave science). © 2015, Coastal and Estuarine Research Federation. Source

Thessen A.E.,Ronin Institute for Independent Scholarship | Bunker D.E.,New Jersey Institute of Technology | Buttigieg P.L.,Alfred Wegener Institute for Polar and Marine Research | Cooper L.D.,Oregon State University | And 17 more authors.
PeerJ | Year: 2015

Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments. © 2015 Thessen et al. Source

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