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The strong control that the emissions of carbon dioxide (CO2) have over Earth's climate identifies the need for accurate quantification of the emitted CO2 and its redistribution within the Earth system. The ocean annually absorbs more than a quarter of all CO2 emissions and this absorption is fundamentally altering the ocean chemistry. The ocean thus provides a fundamental component and powerful constraint within global carbon assessments used to guide policy action for reducing emissions. These carbon assessments rely heavily on satellite observations, but their inclusion is often invisible or opaque to policy. One reason is that satellite observations are rarely used exclusively, but often in conjunction with other types of observations, thereby complementing and expanding their usability yet losing their visibility. This exploitation of satellite observations led by the satellite and ocean carbon scientific communities is based on exciting developments in satellite science that have broadened the suite of environmental data that can now reliably be observed from space. However, the full potential of satellite observations to expand the scientific knowledge on critical processes such as the atmosphere-ocean exchange of CO2 and ocean acidification, including its impact on ocean health, remains largely unexplored. There is clear potential to begin using these observation-based approaches for directly guiding ocean management and conservation decisions, in particular in regions where in situ data collection is more difficult, and interest in them is growing within the environmental policy communities. We review these developments, identify new opportunities and scientific priorities, and identify that the formation of an international advisory group could accelerate policy relevant advancements within both the ocean carbon and satellite communities. Some barriers to understanding exist but these should not stop the exploitation and the full visibility of satellite ob

Dataset: FHLOO, To our knowledge, the FHL Ocean Observatory serves as the only multi-sensor array (~2 m from the surface) in the San Juan Islands archipelago that monitors for temperature, salinity, pH(total), carbon dioxide, dissolved oxygen, chlorophyll concentration, turbidity, and current velocity. In addition to the suite of ocean properties listed above, we also monitor the microplanktonic community using a camera system called the Imaging FlowCytoBot (IFCB). The IFCB is an automated imaging flow cytometer that is designed for the continuous monitoring of phytoplankton and microzooplankton. Using a laser-triggered, high-resolution camera, the IFCB generates images and optical data of individual plankton and other particles in the size range of >10-150 mm. Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global/regional climate system. This dataset includes pH, pCO2, temperature, salinity, and dissolved oxygen data recorded from 2018-2021. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/826798, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: FHLOO, To our knowledge, the FHL Ocean Observatory serves as the only multi-sensor array (~2 m from the surface) in the San Juan Islands archipelago that monitors for temperature, salinity, pH(total), carbon dioxide, dissolved oxygen, chlorophyll concentration, turbidity, and current velocity. In addition to the suite of ocean properties listed above, we also monitor the microplanktonic community using a camera system called the Imaging FlowCytoBot (IFCB). The IFCB is an automated imaging flow cytometer that is designed for the continuous monitoring of phytoplankton and microzooplankton. Using a laser-triggered, high-resolution camera, the IFCB generates images and optical data of individual plankton and other particles in the size range of >10-150 mm. Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global/regional climate system. This dataset includes pH, pCO2, temperature, salinity, and dissolved oxygen data recorded from 2018-2021. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/826798, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Assessing the status of ocean acidification across ocean and coastal waters requires standardized procedures at all levels of data collection, dissemination, and analysis. Standardized procedures for assuring quality and accessibility of ocean carbonate chemistry data are largely established, but a common set of best practices for ocean acidification trend analysis is needed to enable global time series comparisons, establish accurate records of change, and communicate the current status of ocean acidification within and outside the scientific community. Here we expand upon several published trend analysis techniques and package them into a set of best practices for assessing trends of ocean acidification time series. These best practices are best suited for time series capable of characterizing seasonal variability, typically those with sub-seasonal (ideally monthly or more frequent) data collection. Given ocean carbonate chemistry time series tend to be sparse and discontinuous, additional research is necessary to further advance these best practices to better address uncharacterized variability that can result from data discontinuities. This package of best practices and the associated open-source software for computing and reporting trends is aimed at helping expand the community of practice in ocean acidification trend analysis. A broad community of practice testing these and new techniques across different data sets will result in improvements and expansion of these best practices in the future.

Assessing the status of ocean acidification across ocean and coastal waters requires standardized procedures at all levels of data collection, dissemination, and analysis. Standardized procedures for assuring quality and accessibility of ocean carbonate chemistry data are largely established, but a common set of best practices for ocean acidification trend analysis is needed to enable global time series comparisons, establish accurate records of change, and communicate the current status of ocean acidification within and outside the scientific community. Here we expand upon several published trend analysis techniques and package them into a set of best practices for assessing trends of ocean acidification time series. These best practices are best suited for time series capable of characterizing seasonal variability, typically those with sub-seasonal (ideally monthly or more frequent) data collection. Given ocean carbonate chemistry time series tend to be sparse and discontinuous, additional research is necessary to further advance these best practices to better address uncharacterized variability that can result from data discontinuities. This package of best practices and the associated open-source software for computing and reporting trends is aimed at helping expand the community of practice in ocean acidification trend analysis. A broad community of practice testing these and new techniques across different data sets will result in improvements and expansion of these best practices in the future.

Estuaries are recognized as one of the habitats most vulnerable to coastal ocean acidification due to seasonal extremes and prolonged duration of acidified conditions. This is combined with co-occurring environmental stressors such as increased temperature and low dissolved oxygen. Despite this, evidence of biological impacts of ocean acidification in estuarine habitats is largely lacking. By combining physical, biogeochemical, and biological time-series observations over relevant seasonal-to-interannual time scales, this study is the first to describe both the spatial and temporal variation of biological response in the pteropod Limacina helicina to estuarine acidification in association with other stressors. Using clustering and principal component analyses, sampling sites were grouped according to their distribution of physical and biogeochemical variables over space and time. This identified the most exposed habitats and time intervals corresponding to the most severe negative biological impacts across three seasons and three years. We developed a cumulative stress index as a means of integrating spatial-temporal OA variation over the organismal life history. Our findings show that over the 2014–2016 study period, the severity of low aragonite saturation state combined with the duration of exposure contributed to overall cumulative stress and resulted in severe shell dissolution. Seasonally-variable estuaries such as the Salish Sea (Washington, U.S.A.) predispose sensitive organisms to more severe acidified conditions than those of coastal and open-ocean habitats, yet the sensitive organisms persist. We suggest potential environmental factors and compensatory mechanisms that allow pelagic calcifiers to inhabit less favorable habitats and partially offset associated stressors, for instance through food supply, increased temperature, and adaptation of their life history. The novel metric of cumulative stress developed here can be applied to other estuarine environ

Estuaries are recognized as one of the habitats most vulnerable to coastal ocean acidification due to seasonal extremes and prolonged duration of acidified conditions. This is combined with co-occurring environmental stressors such as increased temperature and low dissolved oxygen. Despite this, evidence of biological impacts of ocean acidification in estuarine habitats is largely lacking. By combining physical, biogeochemical, and biological time-series observations over relevant seasonal-to-interannual time scales, this study is the first to describe both the spatial and temporal variation of biological response in the pteropod Limacina helicina to estuarine acidification in association with other stressors. Using clustering and principal component analyses, sampling sites were grouped according to their distribution of physical and biogeochemical variables over space and time. This identified the most exposed habitats and time intervals corresponding to the most severe negative biological impacts across three seasons and three years. We developed a cumulative stress index as a means of integrating spatial-temporal OA variation over the organismal life history. Our findings show that over the 2014–2016 study period, the severity of low aragonite saturation state combined with the duration of exposure contributed to overall cumulative stress and resulted in severe shell dissolution. Seasonally-variable estuaries such as the Salish Sea (Washington, U.S.A.) predispose sensitive organisms to more severe acidified conditions than those of coastal and open-ocean habitats, yet the sensitive organisms persist. We suggest potential environmental factors and compensatory mechanisms that allow pelagic calcifiers to inhabit less favorable habitats and partially offset associated stressors, for instance through food supply, increased temperature, and adaptation of their life history. The novel metric of cumulative stress developed here can be applied to other estuarine environ

Dataset: FHLOO, To our knowledge, the FHL Ocean Observatory serves as the only multi-sensor array (~2 m from the surface) in the San Juan Islands archipelago that monitors for temperature, salinity, pH(total), carbon dioxide, dissolved oxygen, chlorophyll concentration, turbidity, and current velocity. In addition to the suite of ocean properties listed above, we also monitor the microplanktonic community using a camera system called the Imaging FlowCytoBot (IFCB). The IFCB is an automated imaging flow cytometer that is designed for the continuous monitoring of phytoplankton and microzooplankton. Using a laser-triggered, high resolution camera, the IFCB generates images and optical data of individual plankton and other particles in the size range of >10-150 mm. Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global/regional climate system. This dataset includes pH, pCO2, temperature, salinity, and dissolved oxygen data recorded from 2018-2020. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/826798, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Dissolved Oxygen, Dissolved oxygen (O2) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808629, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: FHLOO, To our knowledge, the FHL Ocean Observatory serves as the only multi-sensor array (~2 m from the surface) in the San Juan Islands archipelago that monitors for temperature, salinity, pH(total), carbon dioxide, dissolved oxygen, chlorophyll concentration, turbidity, and current velocity. In addition to the suite of ocean properties listed above, we also monitor the microplanktonic community using a camera system called the Imaging FlowCytoBot (IFCB). The IFCB is an automated imaging flow cytometer that is designed for the continuous monitoring of phytoplankton and microzooplankton. Using a laser-triggered, high resolution camera, the IFCB generates images and optical data of individual plankton and other particles in the size range of >10-150 mm. Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global/regional climate system. This dataset includes pH, pCO2, temperature, salinity, and dissolved oxygen data recorded from 2018-2020. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/826798, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: FHLOO, To our knowledge, the FHL Ocean Observatory serves as the only multi-sensor array (~2 m from the surface) in the San Juan Islands archipelago that monitors for temperature, salinity, pH(total), carbon dioxide, dissolved oxygen, chlorophyll concentration, turbidity, and current velocity. In addition to the suite of ocean properties listed above, we also monitor the microplanktonic community using a camera system called the Imaging FlowCytoBot (IFCB). The IFCB is an automated imaging flow cytometer that is designed for the continuous monitoring of phytoplankton and microzooplankton. Using a laser-triggered, high resolution camera, the IFCB generates images and optical data of individual plankton and other particles in the size range of >10-150 mm. Data produced by this project may be of interest to chemical and biological oceanographers, and climate scientists interested in the role of biogeochemistry in the global/regional climate system. This dataset includes pH, pCO2, temperature, salinity, and dissolved oxygen data recorded from 2018-2020. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/826798, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Temperature and Salinity, Temperature and salinity recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811788, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pH, pH (total hydrogen scale) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811757, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pCO2, pCO2 and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808567, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Dissolved Oxygen, Dissolved oxygen (O2) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808629, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Temperature and Salinity, Temperature and salinity recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811788, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pCO2, pCO2 and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808567, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pH, pH (total hydrogen scale) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811757, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Temperature and Salinity, Temperature and salinity recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811788, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pCO2, pCO2 and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808567, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: Dissolved Oxygen, Dissolved oxygen (O2) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808629, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

Dataset: pH, pH (total hydrogen scale) and temperature recorded from 2018-2020 from a sensor array that measures pH, pCO2, temperature, salinity, dissolved oxygen, chlorophyll, turbidity, and current velocity at Friday Harbor Laboratories Ocean Observatory (FHLOO). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/811757, NSF Division of Biological Infrastructure (NSF DBI) FSML-1418875

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sutton, A. J., Feely, R. A., Maenner-Jones, S., Musielwicz, S., Osborne, J., Dietrich, C., Monacci, N., Cross, J., Bott, R., Kozyr, A., Andersson, A. J., Bates, N. R., Cai, W., Cronin, M. F., De Carlo, E. H., Hales, B., Howden, S. D., Lee, C. M., Manzello, D. P., McPhaden, M. J., Melendez, M., Mickett, J. B., Newton, J. A., Noakes, S. E., Noh, J. H., Olafsdottir, S. R., Salisbury, J. E., Send, U., Trull, T. W., Vandemark, D. C., & Weller, R. A. Autonomous seawater pCO(2) and pH time series from 40 surface buoys and the emergence of anthropogenic trends. Earth System Science Data, 11(1), (2019):421-439, doi:10.5194/essd-11-421-2019., Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural, We gratefully acknowledge the major funders of the pCO2 and pH observations: the Office of Oceanic and Atmospheric Research of the National Oceanic and Atmospheric Administration, US Department of Commerce, including resources from the Ocean Observing and Monitoring Division of the Climate Program Office (fund reference number 100007298) and the Ocean Acidification Program. We rely on a long list of scientific partners and technical staff who carry out buoy maintenance, sensor deployment, and ancillary measurements at sea. We thank these partners and their funders for their continued efforts in sustaining the platforms that support these long-term pCO2 and pH observations, including the following institutions: the Australian Integrated Marine Observing System, the Caribbean Coastal Ocean Observing System, Gray's Reef National Marine Sanctuary, the Marine and Freshwater Research Institute, the Murdock Charitable Trust, the National Data Buoy Center, the National Science Foundation Division of Ocean Sciences, NOAA–Korean Ministry of Oceans and Fisheries Joint Project Agreement, the Northwest Association of Networked Ocean Observing Systems, the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (i.e., RAMA), the University of Washington, the US Integrated Ocean Observing System, and the Washington Ocean Acidification Center. The open ocean sites are part of the OceanSITES program of the Global Ocean Observing System and the Surface Ocean CO2 Observing Network. All sites are also part of the Global Ocean Acidification Observing Network. This paper is PMEL contribution number 4797.

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sutton, A. J., Feely, R. A., Maenner-Jones, S., Musielwicz, S., Osborne, J., Dietrich, C., Monacci, N., Cross, J., Bott, R., Kozyr, A., Andersson, A. J., Bates, N. R., Cai, W., Cronin, M. F., De Carlo, E. H., Hales, B., Howden, S. D., Lee, C. M., Manzello, D. P., McPhaden, M. J., Melendez, M., Mickett, J. B., Newton, J. A., Noakes, S. E., Noh, J. H., Olafsdottir, S. R., Salisbury, J. E., Send, U., Trull, T. W., Vandemark, D. C., & Weller, R. A. Autonomous seawater pCO(2) and pH time series from 40 surface buoys and the emergence of anthropogenic trends. Earth System Science Data, 11(1), (2019):421-439, doi:10.5194/essd-11-421-2019., Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural, We gratefully acknowledge the major funders of the pCO2 and pH observations: the Office of Oceanic and Atmospheric Research of the National Oceanic and Atmospheric Administration, US Department of Commerce, including resources from the Ocean Observing and Monitoring Division of the Climate Program Office (fund reference number 100007298) and the Ocean Acidification Program. We rely on a long list of scientific partners and technical staff who carry out buoy maintenance, sensor deployment, and ancillary measurements at sea. We thank these partners and their funders for their continued efforts in sustaining the platforms that support these long-term pCO2 and pH observations, including the following institutions: the Australian Integrated Marine Observing System, the Caribbean Coastal Ocean Observing System, Gray's Reef National Marine Sanctuary, the Marine and Freshwater Research Institute, the Murdock Charitable Trust, the National Data Buoy Center, the National Science Foundation Division of Ocean Sciences, NOAA–Korean Ministry of Oceans and Fisheries Joint Project Agreement, the Northwest Association of Networked Ocean Observing Systems, the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (i.e., RAMA), the University of Washington, the US Integrated Ocean Observing System, and the Washington Ocean Acidification Center. The open ocean sites are part of the OceanSITES program of the Global Ocean Observing System and the Surface Ocean CO2 Observing Network. All sites are also part of the Global Ocean Acidification Observing Network. This paper is PMEL contribution number 4797.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

Harmful algal blooms (HABs) produce local impacts in nearly all freshwater and marine systems. They are a problem that occurs globally requiring an integrated and coordinated scientific understanding, leading to regional responses and solutions. Given that these natural phenomena will never be completely eliminated, an improved scientific understanding of HAB dynamics coupled with monitoring and ocean observations, facilitates new prediction and prevention strategies. Regional efforts are underway worldwide to create state-of-the-art HAB monitoring and forecasting tools, vulnerability assessments, and observing networks. In the United States, these include Alaska, Pacific Northwest, California, Gulf of Mexico, Gulf of Maine, Great Lakes, and the United States Caribbean islands. This paper examines several regional programs in the United States, European Union, and Asia and concludes that there is no one-size-fits-all approach. At the same time, successful programs require strong coordination with stakeholders and institutional sustainability to maintain and reinforce them with new automating technologies, wherever possible, ensuring integration of modeling efforts with multiple regional to national programs. Recommendations for scaling up to a global observing system for HABs can be summarized as follows: (1) advance and improve cost-effective and sustainable HAB forecast systems that address the HAB-risk warning requirements of key end-users at global and regional levels; (2) design programs that leverage and expand regional HAB observing systems to evaluate emerging technologies for Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) in order to support interregional technology comparisons and regional networks of observing capabilities; (3) fill the essential need for sustained, preferably automated, near real-time information from nearshore and offshore sites situated in HAB transport pathways to provide improved, advanced HAB warnings

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.

Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 92-107, doi:10.5670/oceanog.2015.34., Coastal ocean ecosystems have always served human populations—they provide food security, livelihoods, coastal protection, and defense. Ocean acidification is a global threat to these ecosystem services, particularly when other local and regional stressors combine with it to jeopardize coastal health. Monitoring efforts call for a coordinated global approach toward sustained, integrated coastal ocean health observing networks to address the region-specific mix of factors while also adhering to global ocean acidification observing network principles to facilitate comparison among regions for increased utility and understanding. Here, we generalize guidelines for scoping and designing regional coastal ocean acidification observing networks and provide examples of existing efforts. While challenging in the early stages of coordinating the design and prioritizing the implementation of these observing networks, it is essential to actively engage all of the relevant stakeholder groups from the outset, including private industries, public agencies, regulatory bodies, decision makers, and the general public. The long-term sustainability of these critical observing networks will rely on leveraging of resources and the strength of partnerships across the consortium of stakeholders and those implementing coastal ocean health observing networks, National Science Foundation, National Aeronautics and Space Administration, and the National Oceanic and Atmospheric Administration

Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 226-228, doi:10.5670/oceanog.2015.45., Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

Coastal ocean ecosystems have always served human populations—they provide food security, livelihoods, coastal protection, and defense. Ocean acidification is a global threat to these ecosystem services, particularly when other local and regional stressors combine with it to jeopardize coastal health. Monitoring efforts call for a coordinated global approach toward sustained, integrated coastal ocean health observing networks to address the region-specific mix of factors while also adhering to global ocean acidification observing network principles to facilitate comparison among regions for increased utility and understanding. Here, we generalize guidelines for scoping and designing regional coastal ocean acidification observing networks and provide examples of existing efforts. While challenging in the early stages of coordinating the design and prioritizing the implementation of these observing networks, it is essential to actively engage all of the relevant stakeholder groups from the outset, including private industries, public agencies, regulatory bodies, decision makers, and the general public. The long-term sustainability of these critical observing networks will rely on leveraging of resources and the strength of partnerships across the consortium of stakeholders and those implementing coastal ocean health observing networks

Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 226-228, doi:10.5670/oceanog.2015.45., Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.

In 2002 National Oceanographic Partnership Program funded a partnership of a university, federal, state and local government agencies, and a private non-profit corporation who share a common interest and concern about a body of water -- Puget Sound, Washington. Designated as the Puget Sound Marine Environmental Modeling (PSMEM) partnership, the objectives of the partnership were to conduct scientific research aimed at developing fundamental understanding of the Sound's working, as well as addressing practical questions raised by the regional community concerning management of the Sound and its resources. The partnership is a new kind of collaborative effort between academia, government and a private nonprofit organization -- one that capitalizes on existing strength of each and respects the different mandate that each organization carries., Prepared in cooperation with Ocean Inquiry Project, Seattle, WA; Washington Department of Ecology, Olympia, WA; and King County Department of Natural Resources and Parks, Seattle, WA. Prepared in collaboration with Space and Naval Warfare Systems Center, Bremerton, WA, and San Diego, CA.

Puget Sound, Washington, is both the largest fjord in the lower forty-eight states and closest to the substantial urban centers of Seattle, Tacoma, Everett and surrounding communities. The sound has seasonally high annual phytoplankton standing stock and primary production, and they support several economically valuable fisheries. Our long-term goals are to develop quantitative understanding of the Sound's circulation and marine ecosystem, and of the sensitivity of the physical and the biological system to natural and human perturbations; and to develop models of Puget Sound that can aid agencies with responsibilities for environmental management in making informed decisions and serve as marine science education tools.

The PSNERP Nearshore Science Team has developed a Conceptual Model framework to aid in assessing restoration and preservation measures for nearshore ecosystems in Puget Sound. This model was designed primarily as a synthesis tool to better understand nearshore ecosystem processes and the response of nearshore ecosystems to different stressors or, alternatively, restoration actions. We have designed this model as a framework from which additional, more explicit `submodels' can be consistently developed that relate to specific nearshore stressors, landscape segments, functions, or restoration designs., Puget Sound Nearshore Partnership Report No. 2006-03. Prepared in cooperation with the School of Oceanography, University of Washington, Seattle, WA; National Marine Fisheries Service, National Oceanic and Atmosheric Administration; and the Washington (State) Department of Ecology. Published by Washington Sea Grant Program, University of Washington, Seattle, Washington. The original document contains color images.

Our long-term goals are to develop quantitative understanding of the Sound's circulation and marine ecosystem, and of the sensitivity of the physical and the biological system to natural and human perturbations; and to develop models of Puget Sound that can aid agencies with responsibilities for environmental management in making informed decisions and serve as marine science education tools. Our partnership will develop, maintain and operate a suite of flexibly linked simulation models of Puget Sound's circulation and ecosystem, a data management system for archiving and exchanging oceanographic data and model results that are accessible to all members of the partnership as well as to the regional and oceanographic community, and an effective delivery interface for the model results and observational data for research, education and policy formulation. Our partnership will conduct scientific research aimed at developing fundamental understanding of the Sound's working, as well as addressing practical questions raised by the regional community concerning management of the Sound and its resources. Our partnership will function as an estuarine research node within the NOPP Ocean Information Commons., A National Oceanographic Partnership Program Award. Prepared in cooperation with University of Washington, Dept. of Education, Seattle, WA; Space and Naval Warfare Systems Center, San Diego, CA; Ocean Inquiry Project, Seattle, WA; Washington Dept. of Ecology, Olympia, WA; and King County Department of Natural Resources and Parks, Seattle, WA.

Puget Sound, Washington, is both the largest fjord in the lower forty-eight states and closest to the substantial urban centers of Seattle, Tacoma, Everett and surrounding communities. The sound has seasonally high annual phytoplankton standing stock and primary production, and they support several economically valuable fisheries. This partnership's long-term goals are to develop quantitative understanding of the Sound's circulation and marine ecosystem, and of the sensitivity of the physical and the biological system to natural and human perturbations; and to develop models of Puget Sound that can aid agencies with responsibilities for environmental management in making informed decisions, and serve as marine science education tools. The partnership will develop, maintain and operate a suite of flexibly linked simulation models of Puget Sound's circulation and ecosystem, a data management system for archiving and exchanging oceanographic data, and model results that are accessible to all members of the partnership as well as to the regional and oceanographic community, and an effective delivery interface for the model results and observational data for research, education and policy formulation. This partnership will conduct scientific research aimed at developing fundamental understanding of the Sound's working, as well as addressing practical questions raised by the regional community concerning management of the Sound and its resources. This partnership will function as an estuarine research node within the NOPP Ocean Information Commons. Collectively, the partners are operating or developing four dynamically based, predictive models of the Sound's aquatic environment, each with a different spatial coverage (and a fifth module for biogeochemistry), and their goal is to integrate these modeling efforts into a coordinated whole., A National Oceanographic Partnership Program Award. The original document contains color images. Prepared in collection with Space and Naval Warfare Systems Center, Bremerton, WA., Space and Naval Warfare Systems Center, San Diego, CA., Ocean Inquiry Project, Seattle, WA., Environmental Assessment Program, Olympia, WA., King County Department of Natural Resources and Park, Seattle, WA.

This document provides guidance on the development, selection, and evaluation of projects designed to support recovery of the nearshore ecosystems of Puget Sound. It is an interim product that reflects our current state of knowledge about the nearshore and represents a first step in a longer-term, evolving process. While developed for the Nearshore Partnership, we believe the guidance provided in this document can be useful to other restoration practitioners. Includes bibliography., Puget Sound Nearshore Partnership Report No. 2004-02. Prepared in cooperation with the School of Oceanography, University of Washington, Seattle, WA; National Marine Fisheries Service, National Oceanic and Atmosheric Administration; U.S. Geological Survey; U.S. Fish and Wildlife Service; the Washington (State) Department of Natural Resources and the Washington (State) Department of Ecology. Published by Washington Sea Grant Program, University of Washington, Seattle, Washington. The original document contains color images.

Puget Sound, Washington, is both the largest fjord in the lower forty-eight states and closest to the substantial urban centers of Seattle, Tacoma, Everett and surrounding communities. The sound has seasonally high annual phytoplankton standing stock and primary production, and they support several economically valuable fisheries. Our long-term goals are to develop quantitative understanding of the Sound's circulation and marine ecosystem, and of the sensitivity of the physical and the biological system to natural and human perturbations; and to develop models of Puget Sound that can aid agencies with responsibilities for environmental management in making informed decisions and serve as marine science education tools., A National Oceanographic Partnership Program Award. The original document contains color images.