Lower trophic level studies in the marginal sea-ice zone

Thesis (M.S.) University of Alaska Fairbanks, 198

A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GePandCO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll α, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015)

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications

Physical environments of the Caribbean Sea

The Caribbean Sea encompasses a vast range of physical environmental conditions that have a profound influence on the organisms that live there. Here we utilize a range of satellite and in situ products to undertake a region-wide categorization of the physical environments of the Caribbean Sea (PECS). The classification approach is hierarchical and focuses on physical constraints that drive many aspects of coastal ecology, including species distributions, ecosystem function, and disturbance. The first level represents physicochemical properties including metrics of satellite sea surface temperature, water clarity, and in situ salinity. The second level considers mechanical disturbance and includes both chronic disturbance from wind-driven wave exposure and acute disturbance from hurricanes. The maps have a spatial resolution of 1 km. An unsupervised neural network classification produced 16 physicochemical provinces that can be categorized into six broad groups: (1) low water clarity and low salinity and average temperatures; (2) low water clarity but average salinity and temperature, broadly distributed in the basin; (3) low salinity but average water clarity and temperature; (4) upwelling; (5) high latitude; and (6) offshore waters of the inner Caribbean. Additional mechanical disturbance layers impose additional pattern that operates over different spatial scales. Because physical environments underpin so much of coastal ecosystem structure and function, we anticipate that the PECS classification, which will be freely distributed as geographic information system layers, will facilitate comparative analyses and inform the stratification of studies across environmental provinces in the Caribbean basin

STRATEGIC GEOGRAPHIC POSITIONING OF SEA LEVEL GAUGES TO AID IN EARLY DETECTION OF TSUNAMIS IN THE INTRA-AMERICAS SEA

The potential impact of past Caribbean tsunamis generated by earthquakes and/or massive submarine slides/slumps, as well as the tsunamigenic potential and population distribution within the Intra-Americas Sea (IAS) is examined to help define the optimal location for coastal sea level gauges intended to serve as elements of a regional tsunami warning system. The goal of this study is to identify the minimum number of sea level gauge locations to aid in tsunami detection and provide the most warning time to the largest number of people. We identified 12 initial, prioritized locations for coastal sea level gauge installation. Our study area approximately encompasses 7oN, 59oW to 36oN, 98oW. The results of this systematic approach to assess priority locations for coastal sea level gauges will assist in developing a tsunami warning system (TWS) for the IAS by the National Oceanic and Atmospheric Administration (NOAA) and the Regional Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE-GOOS)

ENSO-Induced Co-Variability of Salinity, Plantkton Biomass and Coastal Currents in the Northern Gulf of Mexico

The northern Gulf of Mexico (GoM) is a region strongly influenced by river discharges of freshwater and nutrients, which promote a highly productive coastal ecosystem that host commercially valuable marine species. A variety of climate and weather processes could potentially influence the river discharges into the northern GoM. However, their impacts on the coastal ecosystem remain poorly described. By using a regional ocean-biogeochemical model, complemented with satellite and in situ observations, here we show that El Niño - Southern Oscillation (ENSO) is a main driver of the interannual variability in salinity and plankton biomass during winter and spring. Composite analysis of salinity and plankton biomass anomalies shows a strong asymmetry between El Niño and La Niña impacts, with much larger amplitude and broader areas affected during El Niño conditions. Further analysis of the model simulation reveals significant coastal circulation anomalies driven by changes in salinity and winds. The coastal circulation anomalies in turn largely determine the spatial extent and distribution of the ENSO-induced plankton biomass variability. These findings highlight that ENSO-induced changes in salinity, plankton biomass, and coastal circulation across the northern GoM are closely interlinked and may significantly impact the abundance and distribution of fish and invertebrates

A modern coastal ocean observing system using data from advanced satellite and in situ sensors – an example

Report of the Ocean Observation Research Coordination Network In-situ-Satellite Observation Working GroupThis report is intended to illustrate and provide recommendations for how ocean observing systems of the next decade could focus on coastal environments using combined satellite and in situ measurements. Until recently, space-based observations have had surface footprints typically spanning hundreds of meters to kilometers. These provide excellent synoptic views for a wide variety of ocean characteristics. In situ observations are instead generally point or linear measurements. The interrelation between space-based and in-situ observations can be challenging. Both are necessary and as sensors and platforms evolve during the next decade, the trend to facilitate interfacing space and in-situ observations must continue and be expanded. In this report, we use coastal observation and analyses to illustrate an observing system concept that combines in situ and satellite observing technologies with numerical models to quantify subseasonal time scale transport of freshwater and its constituents from terrestrial water storage bodies across and along continental shelves, as well as the impacts on some key biological/biogeochemical properties of coastal waters.Ocean Research Coordination Network and the National Science Foundatio

Variability of Surface Pigment Concentrations in the South Atlantic Bight

A 1‐year time sequence (November 1978 through October 1979) of surface pigment images from the South Atlantic Bight (SAB) was derived from the Nimbus 7 coastal zone color scanner. This data set is augmented with in situ observations of hydrographic parameters, freshwater discharge, sea level, coastal winds, and currents for the purpose of examining the coupling between physical processes and the spatial and temporal variability of the surface pigment fields. The SAB is divided into three regions: the east Florida shelf, the Georgia‐South Carolina shelf and the Carolina Capes. Six‐month seasonal mean pigment fields and time series of mean values within subregions were generated. While the seasonal mean isopleths were closely oriented along isobaths, significant differences between seasons in each region were found to exist. These differences are explained by correlating the pigment time series with physical parameters and processes known to be important in the SAB. Specifically, summertime concentrations between Cape Romain and Cape Canaveral were greater than those in winter, but the opposite was true north of Cape Romain. It is suggested that during the abnormally high freshwater discharge in the winter‐spring of 1979, Cape Romain and Cape Fear were the major sites of cross‐shelf transport, while the cross‐shelf exchange during the fall of 1979 occurred just north of Cape Canaveral. Finally, the alongshore band of high pigment concentrations increased in width throughout the year in the vicinity of Charleston, but near Jacksonville it exhibited a minimum width in the summer and a maximum width in the fall of 1979

Carbon regeneration in the Cariaco Basin, Venezuela

The carbon regeneration in the water column of the Cariaco Basin (Venezuela) was investigated using a regression model of total alkalinity (TA) and the concentration of total inorganic carbon (TCO2). Primary productivity (PP) was determined from the inorganic carbon fraction assimilated by phytoplankton and the variation of the 22 and 23ºC isotherm was used as an indicator of coastal upwelling. The results indicate that CO2 levels were lowest (1962 µmol/kg) at the surface and increased to 2451 µmol/kg below the oxic-anoxic redox interface. The vertical regeneration distribution of carbon was dominated (82%) by organic carbon originating from the soft tissue of photosynthetic organisms, whereas 18% originated from the dissolution of biogenic calcite. The regeneration of organic carbon was highest in the surface layer in agreement with the primary productivity values. However, at the oxic-anoxic interface a second more intense maximum was detected (70-80%), generated by chemotrophic respiration of organic material by microorganisms. The percentages in the anoxic layers were lower than in the oxic zone because aerobic decomposition occurs more rapidly than anaerobic respiration of organic material because more labile fractions of organic carbon have already been mineralized in the upper layers

Robots Versus Humans: Automated Annotation Accurately Quantifies Essential Ocean Variables of Rocky Intertidal Functional Groups and Habitat State

Standardized methods for effectively and rapidly monitoring changes in the biodiversity of marine ecosystems are critical to assess status and trends in ways that are comparable between locations and over time. In intertidal and subtidal habitats, estimates of fractional cover and abundance of organisms are typically obtained with traditional quadrat-based methods, and collection of photoquadrat imagery is a standard practice. However, visual analysis of quadrats, either in the field or from photographs, can be very time-consuming. Cutting-edge machine learning tools are now being used to annotate species records from photoquadrat imagery automatically, significantly reducing processing time of image collections. However, it is not always clear whether information is lost, and if so to what degree, using automated approaches. In this study, we compared results from visual quadrats versus automated photoquadrat assessments of macroalgae and sessile organisms on rocky shores across the American continent, from Patagonia (Argentina), Galapagos Islands (Ecuador), Gorgona Island (Colombian Pacific), and the northeast coast of the United States (Gulf of Maine) using the automated software CoralNet. Photoquadrat imagery was collected at the same time as visual surveys following a protocol implemented across the Americas by the Marine Biodiversity Observation Network (MBON) Pole to Pole of the Americas program. Our results show that photoquadrat machine learning annotations can estimate percent cover levels of intertidal benthic cover categories and functional groups (algae, bare substrate, and invertebrate cover) nearly identical to those from visual quadrat analysis. We found no statistical differences of cover estimations of dominant groups in photoquadrat images annotated by humans and those processed in CoralNet (binomial generalized linear mixed model or GLMM). Differences between these analyses were not significant, resulting in a Bray-Curtis average distance of 0.13 (sd 0.11) for the full label set, and 0.12 (sd 0.14) for functional groups. This is the first time that CoralNet automated annotation software has been used to monitor “Invertebrate Abundance and Distribution” and “Macroalgal Canopy Cover and Composition” Essential Ocean Variables (EOVs) in intertidal habitats. We recommend its use for rapid, continuous surveys over expanded geographical scales and monitoring of intertidal areas globally.Fil: Bravo, Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Biología de Organismos Marinos; ArgentinaFil: Moity, Nicolas. Charles Darwin Foundation Santa Cruz; EcuadorFil: Londoño-Cruz, Edgardo. Universidad del Valle; ColombiaFil: Muller-Karger, Frank. University of South Florida St. Petersburg; Estados UnidosFil: Bigatti, Gregorio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Biología de Organismos Marinos; Argentina. Universidad Espíritu Santo; EcuadorFil: Klein, Eduardo. Universidad Simón Bolívar; VenezuelaFil: Choi, Francis. Northeastern University; Estados Unidos. University Northeastern; Estados UnidosFil: Parmalee, Lark. Northeastern University; Estados Unidos. University Northeastern; Estados UnidosFil: Helmuth, Brian. Northeastern University; Estados Unidos. University Northeastern; Estados UnidosFil: Montes, Enrique. University of South Florida St. Petersburg; Estados Unido