Water Boundaries, Tide and Shore Land Rights

Waterfront property, though extremely popular in Washington, presents problems of ownership with which few residents are familiar. The effect of transitory water boundaries upon the divisible proprietary interests is especially complex since the present status of such boundaries is uncertain under our court\u27s interpretation of the applicable statutes

Retrospective Analysis Of Midsummer Hypoxic Area And Volume In The Northern Gulf Of Mexico, 1985-2011

Robust estimates of hypoxic extent (both area and volume) are important for assessing the impacts of low dissolved oxygen on aquatic ecosystems at large spatial scales. Such estimates are also important for calibrating models linking hypoxia to causal factors, such as nutrient loading and stratification, and for informing management decisions. In this study, we develop a rigorous geostatistical modeling framework to estimate the hypoxic extent in the northern Gulf of Mexico from data collected during midsummer, quasi-synoptic monitoring cruises (1985-2011). Instead of a traditional interpolation-based approach, we use a simulation-based approach that yields more robust extent estimates and quantified uncertainty. The modeling framework also makes use of covariate information (i.e., trend variables such as depth and spatial position), to reduce estimation uncertainty. Furthermore, adjustments are made to account for observational bias resulting from the use of different sampling instruments in different years. Our results suggest an increasing trend in hypoxic layer thickness (p = 0.05) from 1985 to 2011, but less than significant increases in volume (p = 0.12) and area (p = 0.42). The uncertainties in the extent estimates vary with sampling network coverage and instrument type, and generally decrease over the study period

Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116353/1/eap2015252492.pd

Assessing the Causes and Severity of Gulf of Mexico Hypoxia Using Geostatistical and Mechanistic Modeling.

Hypoxia, typically defined by dissolved oxygen levels below 2 mg L-1, is an environmental problem common to many coastal systems. One particularly severe example of hypoxia is the large ‘dead zone’ that forms nearly every summer on the Louisiana-Texas shelf of the northern Gulf of Mexico. While there is considerable agreement about the primary causes of hypoxia, there remains substantial uncertainty regarding its spatial and temporal variability, such that it is difficult to predict how hypoxia will respond to management actions and other environmental changes. This research focuses on improving our understanding of Gulf hypoxia through three types of quantitative modeling. First, a geostatistical regression is developed to empirically model how water column stratification (a primary driver of hypoxia) affects bottom water dissolved oxygen (BWDO) concentrations, and to also infer the importance of other primary drivers, such as nutrient loading. Second, a geostatistical spatial estimation model is developed to simulate BWDO and hypoxic layer thickness across the Gulf shelf, providing estimates of hypoxic zone area and volume for a 27-year study period. Third, a mechanistic model, driven by nutrient loading, flow, and weather conditions is developed to predict hypoxic severity, as determined from the geostatistical model. As with all environmental models, the models developed in this dissertation are approximations of reality, tuned to limited observational and experimental information, such that they contain significant uncertainty. Because of this, all models are developed within statistical frameworks that quantify uncertainty and allow results to be presented as ranges of likely values. Overall, this works suggests there has been considerable variability in the mid-summer hypoxic extent over the last few decades, and this variability is explained, in large part, by both nutrient loading and oceanographic conditions (i.e., stratification). Relatively parsimonious models that account for these two main drivers explain at least 70% of the year-to-year variability in hypoxic area and mean BWDO. Also, this work indicates that over the past few decades, the Gulf has not become increasingly susceptible to hypoxia formation (independent of the biophysical drivers considered), at least in terms of hypoxic area and mean BWDO.PHDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/100085/1/obenour_1.pd

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico

A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from theMississippi River Basin andwater column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km(2) 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km(2). The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods

Ensemble Modeling Informs Hypoxia Management In The Northern Gulf Of Mexico

A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from theMississippi River Basin andwater column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km(2) 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km(2). The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods

Simulating algal dynamics within a Bayesian framework to evaluate controls on estuary productivity

The Neuse River Estuary (North Carolina, USA) is a valuable ecosystem that has been affected by the expansion of agricultural and urban watershed activities over the last several decades. Eutrophication, as a consequence of enhanced anthropogenic nutrient loadings, has promoted high phytoplankton biomass, hypoxia, and fish kills. This study compares and contrasts three models to better understand how nutrient loading and other environmental factors control phytoplankton biomass, as chl-a, over time. The first model is purely statistical, while the second model mechanistically simulates both chl-a and nitrogen dynamics, and the third additionally simulates phosphorus. The models are calibrated to a multi-decadal dataset (1997–2018) within a Bayesian framework, which systematically incorporates prior information and accounts for uncertainties. All three models explain over one third of log-transformed chl-a variability, with the mechanistic models additionally explaining the majority of the variability in bioavailable nutrients (R2 > 0.5). By disentangling the influences of riverine nutrient concentrations, flows, and loadings on estuary productivity we find that concentration reductions, rather than total loading reductions, are the key to controlling estuary chl-a levels. The third model indicates that the estuary, even in its upstream portion, is rarely phosphorus limited, and will continue to be mostly nitrogen limited even under a 30% phosphorus reduction scenario. This model also predicts that a 10% change in nitrogen loading (flow held constant) will produce an approximate 4.3% change in estuary chl-a concentration, while the statistical model suggests a larger (10%) effect. Overall, by including a more detailed representation of environmental factors controlling algal growth, the mechanistic models generate chl-a forecasts with less uncertainty across a range of nutrient loading scenarios. Methodologically, this study advances the use of Bayesian methods for modeling the eutrophication dynamics of an estuarine system over a multi-decadal period

Mapping the spatial distribution of the biomass and filter‐feeding effect of invasive dreissenid mussels on the winter‐spring phytoplankton bloom in Lake Michigan

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115963/1/fwb12653.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115963/2/fwb12653_am.pd

Temporal and spatial dynamics of large lake hypoxia: Integrating statistical and three‐dimensional dynamic models to enhance lake management criteria

Hypoxia or low bottom water dissolved oxygen (DO) is a world‐wide problem of management concern requiring an understanding and ability to monitor and predict its spatial and temporal dynamics. However, this is often made difficult in large lakes and coastal oceans because of limited spatial and temporal coverage of field observations. We used a calibrated and validated three‐dimensional ecological model of Lake Erie to extend a statistical relationship between hypoxic extent and bottom water DO concentrations to explore implications of the broader temporal and spatial development and dissipation of hypoxia. We provide the first numerical demonstration that hypoxia initiates in the nearshore, not the deep portion of the basin, and that the threshold used to define hypoxia matters in both spatial and temporal dynamics and in its sensitivity to climate. We show that existing monitoring programs likely underestimate both maximum hypoxic extent and the importance of low oxygen in the nearshore, discuss implications for ecosystem and drinking water protection, and recommend how these results could be used to efficiently and economically extend monitoring programs.Key Points:We modeled seasonal and spatial dynamics of Lake Erie hypoxiaWe showed hypoxia starts nearshore and can persist after traditional monitoring programs endWe recommend monitoring adjustments and explore impacts of different hypoxia definitionsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/133547/1/wrcr22074.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133547/2/wrcr22074-sup-0001-2015WR018170-s01.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/133547/3/wrcr22074_am.pd

Ozone and PM(2.5) Exposure and Acute Pulmonary Health Effects: A Study of Hikers in the Great Smoky Mountains National Park

To address the lack of research on the pulmonary health effects of ozone and fine particulate matter (≤ 2.5 μm in aerodynamic diameter; PM(2.5)) on individuals who recreate in the Great Smoky Mountains National Park (USA) and to replicate a study performed at Mt. Washington, New Hampshire (USA), we conducted an observational study of adult (18–82 years of age) day hikers of the Charlies Bunion trail during 71 days of fall 2002 and summer 2003. Volunteer hikers performed pre- and posthike pulmonary function tests (spirometry), and we continuously monitored ambient O(3), PM(2.5), temperature, and relative humidity at the trailhead. Of the 817 hikers who participated, 354 (43%) met inclusion criteria (nonsmokers and no use of bronchodilators within 48 hr) and gave acceptable and reproducible spirometry. For these 354 hikers, we calculated the posthike percentage change in forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV(1)), FVC/FEV(1), peak expiratory flow, and mean flow rate between 25 and 75% of the FVC and regressed each separately against pollutant (O(3) or PM(2.5)) concentration, adjusting for age, sex, hours hiked, smoking status (former vs. never), history of asthma or wheeze symptoms, hike load, reaching the summit, and mean daily temperature. O(3) and PM(2.5) concentrations measured during the study were below the current federal standards, and we found no significant associations of acute changes in pulmonary function with either pollutant. These findings are contrasted with those in the Mt. Washington study to examine the hypothesis that pulmonary health effects are associated with exposure to O(3) and PM(2.5) in healthy adults engaged in moderate exercise