Natural variability of surface oceanographic conditions in the offshore Gulf of Mexico

AbstractThis work characterizes patterns of temporal variability in surface waters of the central Gulf of Mexico. We examine remote-sensing based observations of sea surface temperature (SST), wind speed, sea surface height anomaly (SSHA), chlorophyll-a concentration (Chl-a) and Net Primary Production (NPP), along with model predictions of mixed layer depth (MLD), to determine seasonal changes and long-term trends in the central Gulf of Mexico between the early 1980s and 2012. Specifically, we examine variability in four quadrants of the Gulf of Mexico (water depth >1000m). All variables show strong seasonality. Chl-a and NPP show positive anomalies in response to short-term increases in wind speed and to cold temperature events. The depth of the mixed layer (MLD) directly and significantly affects primary productivity throughout the region. This relationship is sufficiently robust to enable real-time estimates of MLD based on satellite-based estimates of NPP. Over the past 15–20years, SST, wind speed, and SSHA show a statistically significant, gradual increase. However, Chl-a and NPP show no significant trends over this period. There has also been no trend in the MLD in the Gulf of Mexico interior. The positive long-term trend in wind speed and SST anomalies is consistent with the warming phase of the Atlantic Multidecadal Oscillation (AMO) that started in the mid-90s. This also coincides with a negative trend in the El Niño/Southern Oscillation Multivariate ENSO Index (MEI) related to an increase in the frequency of cooler ENSO events since 1999–2000. The results suggest that over decadal scales, increasing temperature, wind speed, and mesoscale ocean activity have offsetting effects on the MLD. The lack of a trend in MLD anomalies over the past 20years explains the lack of long-term changes in chlorophyll concentration and productivity over this period in the Gulf. Understanding the background of seasonal and long-term variability in these ocean characteristics is important to interpret changes in ocean health due to episodic natural and anthropogenic events and long term climate changes or development activities. With this analysis we provide a baseline against which such changes can be measured

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 calibratio

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Applications 28 (2018): 749-760, doi: 10.1002/eap.1682.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 <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) 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.National Center for Ecological Analysis and Synthesis (NCEAS); National Aeronautics and Space Administration (NASA) Grant Numbers: NNX16AQ34G, NNX14AR62A; National Ocean Partnership Program; NOAA US Integrated Ocean Observing System/IOOS Program Office; Bureau of Ocean and Energy Management Ecosystem Studies program (BOEM) Grant Number: MC15AC0000

Influence Of The Environment On The Distribution And Relative Apparent Abundance Of Juvenile Atlantic Bluefin Tuna Along The United States East Coast

The preferred thermal habitat for juvenile Atlantic bluefin tuna (Thunnus thynnus thynnus), ages 1 - 4, has been determined from analyses of behavioral, hydrographic, and catch data derived from bluefin (ABT) fisheries in the Middle Atlantic Bight (MAB) from 1976 through 1982. The data indicate that both inter-seasonal and intra-seasonal changes in catchability (availability and vulnerability) are affected by the dynamics of the preferred habitat and that catch-per-unit effort (CPUE) data are valid indices of ABT concentration or catchability. Use of CPUE with constant or random catchability results in biased estimates of ABT stock abundance, especially when environmental conditions vary. Inter-seasonal changes in the geographic location of the center of apparent abundance and duration of the various fisheries for ABT from North Carolina to Rhode Island has been interpreted as being a function of the location and condition of the preferred temperature habitat. It appears that relatively cool summers favor the southern fisheries of Virginia and North Carolina and that relatively warm summers favor the northern fisheries of New Jersey, New York and Rhode Island. Since sea surface temperature (SST) is a proxy indicator for the location of the sub-surface preferred habitat, one can monitor the habitat from satellite infrared (IR) data and use the IR and other data to derive models which result in forecasts of the onset, location, and duration of the various ABT fisheries in the MAB.Daily changes in the distribution, concentration, and CPUE of juvenile ABT in the Virginia Beach, Virginia fishery followed the ephemeral changes in the off-shore location, history, and temperature gradients of the Chesapeake Bay plume frontal zone. The effect of bottom topographic features and SST fronts on CPUE were profound, especially when horizontal SST gradients were located within the Rossby radius of internal deformation. The results suggest that the optical characteristics of the water (transparency and chlorophyll concentration) play a greater role in influencing the distribution and relative apparent abundance of tunas than previously thought.Synoptic scale SST data derived from NOAA-series satellites were essential for monitoring the location and orientation of the Chespeake Bay plume frontal zone in relation to observed changes in the fishery. The utility of the Coastal Zone Color Scanner (CZCS) on the NIMBUS satellite could not be extensively evaluated in this research due to problems of obtaining usable data for the Virginia coastal waters for the 1979 and 1980 fishing seasons

Predicting the occurrence of Atlantic bluefin tuna (\u3ci\u3eThunnus thynnus\u3c/i\u3e) larvae in the northern Gulf of Mexico: building a classification model from archival data

Although bluefin tuna are found throughout the Atlantic Ocean, spawning in the western Atlantic has been recorded predominantly in the Gulf of Mexico (GOM) in spring. Larval bluefin tuna abundances from the northern GOM are formulated into an index used to tune the adult stock assessment, and the variability of this index is currently high. This study investigated whether some of the variability in larval bluefin tuna abundances was related to environmental conditions, by defining associations between larval bluefin tuna catch locations, and a suite of environmental variables. We hypothesized that certain habitat types, as defined by environmental variables, would be more likely to contain bluefin tuna larvae. Favorable habitat for bluefin tuna larvae was defined using a classification tree approach. Habitat within the Loop Current was generally less favorable, as were warmcore rings, and cooler waters on the continental shelf. The location and size of favorable habitat was highly variable among years, which was reflected in the locations of larval bluefin tuna catches. The model successfully placed bluefin tuna larvae in favorable habitat with nearly 90% accuracy, but many negative stations were also located within theoretically favorable habitat. The probability of collecting larval bluefin tuna in favorable habitat was nearly twice the probability of collecting bluefin tuna larvae across all habitats (35.5 versus 21.0%). This model is a useful addition to knowledge of larval bluefin tuna distributions; however, the incorporation of variables describing finer-scale features, such as thermal fronts, may significantly improve the model’s predictive power

Satellite Remote Sensing of Surface Oceanic Fronts in Coastal Waters off West–Central Florida

Two algorithms designed to detect deepwater oceanic features and arbitrary edge profiles were tuned to automatically delineate fronts in coastal waters off west–central Florida using satellite-derived sea surface temperature (SST), chlorophyll-a concentration (Chl), normalized water-leaving radiance (nLw), and fluorescence line height (FLH) images during select periods in the spring and fall of 2004 and 2005. The dates correspond to recreational king mackerel, Scomberomorus cavalla, tournaments. A histogram-based algorithm was useful to detect coastal surface SST, nLw, and FLH fronts, specifically. A gradient-based algorithm, with a smaller kernel box of 3 × 3 pixels, best identified nearshore ( \u3c 10 m depth) features in Chl images at the mouth of Tampa Bay, but was less effective for fronts farther offshore where gradients were weaker. Local winds and tide levels estimated from a coastal observing buoy, and bathymetric gradients were examined to help understand the factors that influenced front formation and stability. Periods of strong and variable winds led to front movement of up to 10 km per day or dissipation within 2–3 days in over 80% of the fronts detected in SST, Chl, nLw, and FLH imagery. Short episodes of less variable wind velocities typically led to more stable and stationary fronts, within 3–5 km, for up to four days. The occurrence of fronts closely associated with the coastal bathymetry, namely at the 20 m and 30 m isobaths, was significantly higher in the fall SST imagery and in the spring Chl imagery. Fall SST fronts related to bathymetric gradients likely resulted from progressive cooling of the water with depth. Stronger Chl and nLw443 gradients at the mouths of estuaries in the fall compared to the spring were attributed to increased precipitation and periods of stronger winds or tides. The FLH imagery was most useful in delineating coastal algal blooms. The automatic front detection techniques applied here can be an important tool for resource managers to track coastal oceanographic features daily, over synoptic spatial scales

Comparison between environmental characteristics of larval bluefin tuna Thunnus thynnus habitat in the Gulf of Mexico and western Mediterranean Sea

Despite being well adapted for feeding in cold water on their North Atlantic feeding grounds, Atlantic bluefin tuna undertake long migrations to reach warm, low productivity spawn - ing grounds in the Gulf of Mexico and Mediterranean Sea. Environmental conditions within spawning areas have been presumed to benefit larval survival, through appropriate feeding conditions, and enhanced larval retention and growth rates. However, field collections and studies to explore the potential mechanisms are rare. In this study, a comparison of the environmental characteristics of both spawning sites was completed using standardized environmental data and modeling methods. Predictive models of larval occurrence were constructed using historical larval collections, and environmental variables from both in situ and remotely sensed sources. Results showed that larvae on both spawning grounds were most likely to be found in warm (23 to 28°C), low chlorophyll areas with moderate current velocities and favorable regional retention conditions. In the Gulf of Mexico, larvae were located in offshore waters outside of the Loop Current and warm eddies, while in the western Mediterranean, larval occurrences were associated with the confluence of inflowing Atlantic waters and saltier resident surface waters. Although our results suggested common themes within preferred spawning grounds on both sides of the Atlantic Ocean, the ecological processes governing larval survival and eventual recruitment are yet to be fully understood.Keywords: Bluefin tuna, Spawning, Mediterranean Sea, Gulf of Mexic

Comparison between environmental characteristics of larval bluefin tuna Thunnus thynnus habitat in the Gulf of Mexico and western Mediterranean Sea

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