Nearly half of the population of the United States lives in coastal regions, and millions of visitors from across the nation and world enjoy the coasts every year. Coastal and marine areas provide for recreation, economic activities essential for the financial health of the nation, and vital ecological services. As they provide so many benefits to the U.S., it is vital to protect and preserve the coastal and ocean areas from the increasing, competing demands they are facing. In order to protect and preserve these complex systems, a comprehensive approach incorporating science, engineering, humanities, and social sciences should be taken; this approach is commonly referred to as Ecosystem-Based Management. This dissertation focuses on developing a framework that can be used to identify appropriate sub-regions in Northern Gulf of Mexico coastal and marine environments for the purposes of Ecosystem-Based Management. Through this work, the roles of three management protocols used for managing coastal areas – coastal and marine spatial planning, ecosystem-based management, and integrated ecosystem assessment – were examined individually as well as their integrations with each other. Biological, ecological, physical, human, and economic indicators for partitioning an ecosystem were developed and weighted for each management protocol using the analytic hierarchy process and expert elicitation. Using the weighted indicators, a framework for identifying sub-regions and estuarine classification system was developed. The framework and classification system were applied to five estuaries within the Northern Gulf of Mexico: Barataria, Galveston, Mobile, and Perdido Bays and Mississippi Sound. Initial results from this work show that: 1. Sub-regions can be identified as associated to each other based upon indicator data values and not upon physical location. 2. Even though the weights calculated for the management protocols vary significantly, for systems that were not highly homogeneous in indicator data values, the different weights did not produce the vastly different cluster maps expected. 3. The scale work indicates that to identify appropriate sub-regions using the developed framework, a larger grid size produces more consistent results for larger systems whereas a smaller grid size produces more consistent results for smaller systems. Recommendations for further research are also presented.

[pt] O oceano é um ecossistema fundamental para a sobrevivência dos humanos e não humanos. Todavia, vem sendo explorado de forma desordenada e sufocado com poluição plástica, como demonstram diagnósticos recentes, elaborados na Década do Oceano, inclusive em relação ao cenário brasileiro. Nesse período, pretende-se alavancar ações para alcançar um oceano saudável e produtivo, entre outros atributos, mediante integração e colaboração entre diversos atores, inclusive as instituições financeiras, que dispõem de recursos para financiar sua execução. O presente trabalho objetiva demonstrar como o Planejamento Espacial Marinho, cujo estudo para implementação do Projeto-Piloto na região sul do país será apoiado pelo Banco Nacional de Desenvolvimento Econômico e Social (BNDES), poderá, além de servir de base para a adequada regulação do uso sustentável do oceano, também acelerar o combate à poluição plástica nesse ecossistema, induzindo a ampliação de ações voltadas à gestão de resíduos sólidos, nele planejadas. Esse efeito adicional poderá ser alcançado porque esse planejamento será desenvolvido com base ecossistêmica e observando a integração entre as políticas públicas marinhas e terrestres já existentes, além de considerar todas as questões que afetam o oceano. A Convenção das Nações Unidas sobre Diversidade Biológica definiu a base ecossistêmica como uma estratégia para a gestão integrada da terra, da água e dos recursos vivos, que promove a conservação e o uso sustentável, de um modo equitativo. No âmbito do referido financiamento, deverão ser produzidos cadernos técnicos setoriais, entre os quais sobre meio ambiente e mudança do clima, analisando, inclusive, a poluição marinha e como esse problema ambiental e social pode afetar o uso econômico do oceano. Assim, aliando essa iniciativa a outras que já são apoiadas, em linha com sua missão socioambiental, o BNDES irá induzir transformações relevantes, ao colaborar para a efetividade da Política Nacional de Resíduos Sólidos, necessária para o desenvolvimento da Economia Azul e a consequente sustentabilidade do oceano. / [en] The ocean is a fundamental ecosystem for the survival of humans and non-humans. However, it has been exploited in a disorderly way and suffocated with plastic pollution, as shown by recent diagnoses, elaborated in the Ocean Decade, including in relation to the Brazilian scenario. During this period, the intention is to leverage actions to achieve a healthy and productive ocean, among other attributes, through integration and collaboration between different actors, including financial institutions, which have resources to finance its execution. This work aims to demonstrate how the Marine Spatial Planning, whose study for the implementation of the Pilot Project in the southern region of the country will be supported by the National Bank for Economic and Social Development (BNDES), may, in addition to providing for the regulation of ocean use, also accelerate the combat against plastic pollution in this ecosystem, inducing the expansion of actions aimed at solid waste management in Brazil. This additional effect can be achieved because this planning will be developed based on ecosystem and observing the integration between existing marine and terrestrial public policies, in addition to considering all issues that affect the ocean. The United Nations Convention on Biological Diversity defined the ecosystem base as a strategy for the integrated management of land, water and living resources that promotes conservation and sustainable use in an equitable way. In this financing, should be produced a sectoral notebook about the environmental and climate change, including analyzing marine pollution and how this environmental and social problem can affect the economic use of the ocean. Thus, combining this initiative with others that are already supported, in line with its socio-environmental mission, the BNDES will induce relevant transformations, by collaborating for the effectiveness of the National Solid Waste Policy, necessary for the development of the Blue Economy and the consequent sustainability of the ocean.

Species distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina), have overlapping ranges but contrasting population dynamics around the UK; whilst grey seals have generally increased, harbour seals have shown significant regional declines. A robust analytical methodology was developed to produce maps of grey and harbour seal usage estimates with corresponding uncertainty, and scales of spatial partitioning between the species were found. Throughout their range, both grey and harbour seals spend the majority of their time within 50 km of the coast. The scalability of the analytical approach was enhanced and environmental information to enable spatial predictions was included. The resultant maps have been applied to inform consent and licensing of marine renewable developments of wind farms and tidal turbines. For harbour seals around Orkney, northern Scotland, distance from haul out, proportion of sand in seabed sediment, and annual mean power were important predictors of space-use. Utilising seal usage maps, a framework was produced to allow shipping noise, an important marine anthropogenic stressor, to be explicitly incorporated into spatial planning. Potentially sensitive areas were identified through quantifying risk of exposure of shipping traffic to marine species. Individual noise exposure was predicted with associated uncertainty in an area with varying rates of co-occurrence. Across the UK, spatial overlap was highest within 50 km of the coast, close to seal haul outs. Areas identified with high risk of exposure included 11 Special Areas of Conservation (from a possible 25). Risk to harbour seal populations was highest, affecting half of all SACs associated with the species. For 20 of 28 animals in the acoustic exposure study, 95% CI for M-weighted cumulative Sound Exposure Levels had upper bounds above levels known to induce Temporary Threshold Shift. Predictions of broadband received sound pressure levels were underestimated on average by 0.7 dB re 1μPa (± 3.3). An analytical methodology was derived to allow ecological maps to be quantitatively compared. The Structural Similarity (SSIM) index was enhanced to incorporate uncertainty from underlying spatial models, and a software algorithm was developed to correct for internal edge effects so that loss of spatial information from the map comparison was limited. The application of the approach was demonstrated using a case study of sperm whales (Physeter macrocephalus, Linneaus 1758) in the Mediterranean Sea to identify areas where local-scale differences in space-use between groups and singleton whales occurred. SSIM is applicable to a broad range of spatial ecological data, providing a novel tool for map comparison.

For the west coast of North America, from northern California to southern Washington, a habitat suitability prediction framework was developed to support wave energy device siting. Concern that wave energy devices may impact the seafloor and benthos has renewed research interest in the distribution of marine benthic invertebrates and factors influencing their distribution. A Bayesian belief network approach was employed for learning species-habitat associations for Rhabdus rectius, a tusk-shaped marine infaunal Mollusk. Environmental variables describing surficial geology and water depth were found to be most influential to the distribution of R. rectius. Water property variables, such as temperature and salinity, were less influential as distribution predictors. Species-habitat associations were used to predict habitat suitability probabilities for R. rectius, which were then mapped over an area of interest along the south-central Oregon coast. Habitat suitability prediction models tested well against data withheld for crossvalidation supporting our conclusion that Bayesian learning extracts useful information available in very small, incomplete data sets and identifies which variables drive habitat suitability for R. rectius. Additionally, Bayesian belief networks are easily updated with new information, quantitative or qualitative, which provides a flexible mechanism for multiple scenario analyses. The prediction framework presented here is a practical tool informing marine spatial planning assessment through visualization of habitat suitability. / Graduation date: 2012

Oregon's ocean waters are a potential source of wind, wave, and tidal energy; of interest to renewable energy entrepreneurs and to the U.S. government as it seeks to bolster energy security. In order to install technology to capture this energy, however, it may be necessary to mitigate conflict with existing ocean space users. The objective of this research was to construct a conflict analysis model in a GIS to answer the following research questions: (1) Within the study area off the coast of Oregon, where are stakeholders currently using ocean space and how many uses overlap? (2) To what extent might existing ocean space use present potential for conflict with renewable energy development? (3) How do various types of uncertainty affect analysis results? (4) What are the implications of these findings for ecosystem based management of the ocean? All available spatial information on ocean space usage by commercial fishing, commercial non-fishing, recreational, Native American, and scientific communities was gathered. Stakeholder outreach with these communities was used to vet the collected data and allow each to contribute knowledge not previously available through GIS data clearinghouses maintained by government or interest groups. The resulting data were used as inputs to a conflict visualization model written in Python and imported to an ArcGIS tool. Results showed extensive coverage and overlap of existing ocean space uses; specifically that 99.7% of the 1-nm² grid cells of the study area are occupied by at least 6 different categories of ocean space use. The six uses with the greatest coverage were: Fishing – Trolling, Habitat, Military, Fishing - Closure Areas, Protected, and Marine Transportation - Low Intensity. An uncertainty analysis was also completed to illustrate the margin for error and therefore the necessity of appropriate stakeholder outreach during the renewable energy siting process, as opposed to relying only on a GIS. Ranking of each category by its potential for conflict with renewable energy development demonstrated which areas of the ocean may be particularly contentious. Because rankings are subjective, a tool was created to allow users to input their own rankings. For the purpose of this report, default rankings were assigned to each as justified by the literature. Results under these assumptions showed that space use and potential for conflict were highest between the coast and approximately 30 nm at sea. This is likely because certain space use is limited by depth (e.g., recreational use); there is increased shipping density as vessels approach and depart major ports; and increased fuel costs associated with traveling further from shore. Two potential applications of model results were demonstrated. First, comparison with existing wave energy permit sites highlighted relative potential for conflict among the sites and the input data detailed the specific uses present. Second, comparison with areas determined most suitable for development by the wave energy industry illustrated that areas of high suitability often also had high rankings for potential for conflict. It appeared that the factors that determined development suitability were often the same factors that drew current ocean space users to those locations. Current support at the state, regional and federal level under the National Ocean Policy for the use of marine spatial planning as a tool to implement ecosystem based management of the oceans requires that tools such as the one developed in this research are used, to ensure that all components of the marine ecosystem are considered prior to implementation of a management plan. The addition of renewable energy to the current social landscape of the ocean will reduce the resource base for many categories of ocean space use. Model results demonstrated that mitigation of conflict between development and existing space use is not merely a best practice supported by current policy, but a necessity. Results presented a visualization of the social landscape of the ocean that could help managers determine which stakeholders to engage during the initial stage of choosing a site for development. / Graduation date: 2012

As competing uses of our coastlines increase, natural resource agencies are employing marine spatial planning (MSP) to designate areas for different uses or activities in order to reduce conflicts while achieving ecological, economic and social objectives. A central challenge of implementing MSP is development of a rigorous approach for analyzing tradeoffs across the provision of ecosystem services (i.e., the benefits humans receive from nature). This study develops an operational approach to this problem that is founded on community-based methods, ecological production theory, and multi-criteria decision analysis (MCDA). The approach merges ecological models with surveys to identify marine ecosystem services for use in tradeoff analysis. The approach allows for a single set of marine ecosystem services to at once be valued by local stakeholders and measured by biologists, thus connecting social and biological monitoring efforts. To develop the approach in a real-world context, I examined ecosystem services associated with nearshore marine ecosystems in Oregon, where marine reserves are being introduced for biodiversity conservation. I worked with stakeholder focus groups in three Oregon communities to identify 24 marine ecosystem services. I then linked the ecosystem services with ecological indicators, which I then consolidated to derive 11 items for use in a survey-based tradeoff analysis exercise. I administered the survey to a nonrandom sample of stakeholders in Oregon (n=31), from which their relative preferences and preference weights for ecosystem services were derived. The weights and preference measures may then be used in MSP decision-making. Furthermore, I grouped the stakeholder survey data in three ways: by location of residence (coastal vs. non-coastal), by eight categories of affiliation (e.g., business owners, conservationists, commercial and recreational fishers, etc.), and by resource use patterns. I then analyzed the various groupings of stakeholders for within- and between-group homogeneity of preferences. Results of the analyses showed that there are statistically significant variations in preferences within and between most groupings. Capturing the variations in stakeholder preferences is important when developing policies that affect different stakeholder groups. Thus, when implementing the survey instrument, I suggest random sampling of stakeholders stratified by location, affiliation, and resource use. This study provides one of the first examples of a systems-based approach to ecosystem service valuation operationalized to inform MSP, and novel features of the approach have a number of implications for advancing marine research and management. First, by using stakeholders to identify ecosystem services, the approach allows for a tailored implementation of ecosystem-based management at the community level. Second, by integrating ecological and economic information on the provision and value of ecosystem services, the approach provides relevant data for MSP decision-making during the siting, evaluation, and monitoring stages. And third, by applying both stated-preference and MCDA methods, the approach may capture the array of values represented by diverse stakeholder groups. / Graduation date: 2013