The Application of Novel Research Technologies by the Deep Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND) Consortium

The deep waters of the open ocean represent a major frontier in exploration and scientific understanding. However, modern technological and computational tools are making the deep ocean more accessible than ever before by facilitating increasingly sophisticated studies of deep ocean ecosystems. Here, we describe some of the cutting-edge technologies that have been employed by the Deep Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND; www.deependconsortium.org) Consortium to study the biodiverse fauna and dynamic physical-chemical environment of the offshore Gulf of Mexico (GoM) from 0 to 1,500 m

A Multidisciplinary Approach to Investigate Deep-Pelagic Ecosystem Dynamics in the Gulf of Mexico Following Deepwater Horizon

The pelagic Gulf of Mexico (GoM) is a complex system of dynamic physical oceanography (western boundary current, mesoscale eddies), high biological diversity, and community integration via diel vertical migration and lateral advection. Humans also heavily utilize this system, including its deep-sea components, for resource extraction, shipping, tourism, and other commercial activity. This utilization has had impacts, some with disastrous consequences. The Deepwater Horizon oil spill (DWHOS) occurred at a depth of ∼1500 m (Macondo wellhead), creating a persistent and toxic mixture of hydrocarbons and dispersant in the deep-pelagic (water column below 200 m depth) habitat. In order to assess the impacts of the DWHOS on this habitat, two large-scale research programs, described herein, were designed and executed. These programs, ONSAP and DEEPEND, aimed to quantitatively characterize the oceanic ecosystem of the northern GoM and to establish a time-series with which natural and anthropogenic changes could be detected. The approach was multi-disciplinary in nature and included in situ sampling, acoustic sensing, water column profiling and sampling, satellite remote sensing, AUV sensing, numerical modeling, genetic sequencing, and biogeochemical analyses. The synergy of these methodologies has provided new and unprecedented perspectives of an oceanic ecosystem with respect to composition, connectivity, drivers, and variability

DEEPEND: Characterizing Pelagic Habitats in the Gulf of Mexico Using Model, Empirical, and Remotely-Sensed Data

Pelagic waters of the Gulf of Mexico (GOM) are dominated by mesoscale features such as cyclonic and anticyclonic eddies and the strongly flowing Loop Current. These GOM features may be important drivers of population structure and trophic linkages within the water column. It is important, therefore, to classify water bodies associated with these features to allow quantitative evaluation of community assemblages. We first used an algorithm that integrated sea surface height anomaly and water velocity gradients to classify GOM surface waters between the years 2011-2016, founded on ocean condition data from the 1/25 ° GOM HYbrid Coordinate Ocean Model (HYCOM). The water bodies were segregated into anti-cyclonic, cyclonic, anti-cyclonic boundary, cyclonic boundary, and common water units. Next we compared these classifications to empirically derived ocean conditions as measured by CTD casts within each unit that were collected during the same period on cruises by the Deep Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND) consortium. The classification scheme was further cross-validated by comparing the identified water bodies to the depths of the 20° and 22° isotherms, microbial community assemblages within each unit, and chlorophyll concentrations derived from satellite measurements. We found good agreement of the classification scheme between model (i.e., HYCOM), empirical (i.e., CTD and microbial assemblages), and remotely sensed (i.e., chlorophyll) data. Going forward, the classification scheme will be used to characterize assemblages of pelagic fauna that were collected by DEEPEND cruises in the GOM between 2010-2017

Habitat classification of the Gulf of Mexico (GOM) using the HYbrid Coordinate Ocean Model (HYCOM) and salinity/temperature profiles, cruises DP01-DP04, May 2015 to August 2016

Deep pelagic habitat from the entire Gulf of Mexico (GOM) was classified using the deviation of sea surface height (SSH) from mean SSH for the entire GOM and water temperature at 300 m water depth, founded on ocean condition data from the 1/25° GOM HYbrid Coordinate Ocean Model (HYCOM). Pelagic habitats were segregated into anticyclonic, mixed boundaries, and common water units – all of which likely produce varying levels of forage for deep-sea fauna and may be trophic drivers. Model classifications were compared to classifications based on water column temperature and salinity at depth, as measured by CTD casts during cruises DP01-DP04 in the northern GOM (GRIIDC datasets R4.x257.230:0004, R4.x257.230:0010, R4.x257.230:0011, and R4.x257.230:0012). The classification scheme was further cross-validated by comparing the model classifications to classifications based on microbial communities found within the same water masses. This tool will be used to aid pelagic community analyses of fauna collected by DEEPEND cruises in the GOM spanning 2015-2016

DEEPEND: A Tool for Classification of Mesoscale Watermass Structure for Pelagic Community Analyses

Gulf of Mexico (GOM) pelagic waters are dominated by mesoscale oceanic features such as anti- and cyclonic eddies and the swift Loop Current. These GOM features may structure faunal communities in the deep pelagial and influence trophic linkages from surface waters down. Classifying pelagic habitat structure based on mesoscale watermass features therefore may facilitate quantitative evaluation of pelagic community assemblages. In this study, we developed a tool to classify deep pelagic habitat in the GOM using the deviation of sea surface height (SSH) from mean SSH for the entire GOM and water temperature at 300 m water depth, founded on ocean condition data from the 1/25 ° GOM HYbrid Coordinate Ocean Model (HYCOM) for broad application. Pelagic habitats were segregated into anticyclonic, mixed boundaries, and common water units – all of which likely produce varying levels of forage for deep-sea fauna and may be trophic drivers. Next we contrasted these classifications to classifications based on water column temperature and salinity at depth, as measured by CTD casts during cruises by the Deep Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND) consortium over the years 2015-2016. The classification scheme was further cross-validated by comparing the model classifications to classifications based on microbial communities found within the same water masses. We found high levels of agreement between all three methods. Going forward, this tool will be used to aid pelagic community analyses of fauna collected by DEEPEND cruises in the GOM spanning the years 2010-2017

A Gulf of Mexico Comparative Analysis of Numerical Model Results, Cruise-Based Observations, and Historical Data

The Gulf of Mexico Research Initiative DEEPEND (Deep-Pelagic Nekton Dynamics of the Gulf of Mexico) consortium’s objectives include the characterization of biophysical variability in the water column. Observational and multi-model approaches are used to increase understanding of the dynamics of deeppelagic (0-1500 m) fish assemblages at multiple temporal and spatial scales. The first two DEEPEND cruise campaigns, conducted during the summer of 2015, collected bio-physical data in the Northern Gulf of Mexico. During this time, the Northern Gulf exhibited vigorous mesoscale regimes that were dominated by a large anti-cyclonic eddy intermittently shedding off the loop current; a similar condition that occurred in 2011. A 1/25° horizontal-resolution HYCOM ocean model, running in near real time to support the DEEPEND cruise campaigns, captures these features and illustrates the eddy formation and shedding events that transpired during the summer of 2015. The structure of these eddy regimes is examined at the surface and through the water column using the model results and evaluated against cruise and other observational data from NDBC and NASA

DEEPEND: The Impact of In Situ Data Assimilation in a Numerical Model on the Characterization of the Biophysical Habitat

The Deep-Pelagic Nekton Dynamics of the Gulf of Mexico consortium (DEEPEND) uses observational and multi-model approaches to characterize biophysical variability and investigates the dynamics of deep-pelagic animal assemblages at multiple temporal and spatial scales. Run in near-real time, at 1/25° horizontal-resolution, the HYCOM Gulf of Mexico (HYCOM-GOM) ocean model was used to support the five DEEPEND research cruises (2015-2017) and aid adaptive sampling strategies. Post-cruise, three additional simulations were performed with the HYCOM-GOM configuration to better understand biophysical relationships in the Northeastern Gulf of Mexico. First, a hindcast “nature run” was conducted with no data assimilation. Next two data assimilative runs were completed. One assimilated data from publicly available sources (e.g., the NOAA Global Telecommunication System [GTS]), and the other assimilated in-situ CTD and glider data collected during the cruises. We analyzed the impact of the various assimilated data on the model results and on the characterization of the biophysical habitat and associated environmental drivers

Physical-Bio-Optical Modeling in the Gulf of Mexico: Analysis of Water Mass Relationships to Pelagic Habitat

The Gulf of Mexico Research Initiative DEEPEND (Deep-Pelagic Nekton Dynamics of the Gulf of Mexico) consortium’s objectives include the characterization of biophysical variability in the water column. Observational and multi-model approaches are used to increase understanding of the dynamics of deep-pelagic (0-1500 m) animal assemblages at multiple temporal and spatial scales. To date, four DEEPEND cruises, conducted during 2015 and 2016, have collected biophysical data in the Northern Gulf of Mexico. A 1/25° horizontal-resolution HYbrid Coordinate Ocean Model (HYCOM), recently coupled to the Carbon Silicate Nitrogen Ecosystem (CoSiNE) model, has been running in near real-time to support the cruise campaigns. The HYCOM-CoSiNE model data are used to study the water column in order to better understand the connections and interactions among biologically active zones, pelagic regimes, hydrodynamics and stratification. The observational data are matched up to model analyses for each cruise track and sampling station to examine the spatio-temporal evolution of biological and physical features, such as chlorophyll maxima, mixed layer depth, the Loop Current and Loop Current eddies, and mesoscale cyclonic (cold core) and anti-cyclonic (warm core) rings. This analysis elucidates a unique platform to better understand the vertical connectivity of pelagic habitat to mesoscale dynamics, physical-biological-optical processes, and water mass characteristics; all chief environmental drivers of habitat preference and behavior. http://www.deependconsortium.org

DEEPEND: Deep-Pelagic Nekton Dynamics of the Gulf of Mexico

The Deepwater Horizon Oil Spill (DWHOS) was primarily a deep-pelagic event. Variable amounts of discharged hydrocarbons reached the ocean surface and/or seafloor, whereas 100% occurred within the water column. Understanding this pelagic habitat is important because about half of all fish species that occur in the Gulf of Mexico (GoM) spend all or part of their lives in the open ocean. Most mesopelagic (200-1000 m depth) species of fishes vertically migrate each night to feed in epipelagic (0-200 m) depths and return to deep water during the day. This behavior affects rapid cycling of natural and anthropogenic material in the water column. Deep-pelagic fishes are prey for gamefishes, seabirds, and marine mammals. Given the steady growth of oil exploration and operations, the likelihood of future spills emphasizes the need to document acute and chronic effects on pelagic fauna. The DEEPEND (Deep-Pelagic Nekton Dynamics) Consortium will conduct a 3-year sampling and analysis program that builds on two intensive NOAA-supported surveys during 2010-11. DEEPEND will focus on short-term and long-term timescales to appraise the dynamic nature of communities using a suite of integrated approaches. These investigations include: 1) a direct assessment of GoM deep-pelagic community structure including the physical and biological drivers of this structure; 2) a time-series analysis/comparison of biophysical data from the years 2010- 2011 and 2015-2017; 3) a time-series examination of differences in genetic diversity among key species; and 4) a biogeochemical analysis of the effect of DWHOS on pelagic biota

Deep-Pelagic Research in the Gulf of Mexico: The DEEPEND Consortium

The Deepwater Horizon oil spill (DWHOS) was unique not only for its volume, but also for its depth of influence (0-1500 m). Variable amounts of hydrocarbons reached the ocean surface and/or seafloor, whereas 100% went through the water column. Understanding this pelagic habitat is important. For example, about half of all fish species that occur in the Gulf of Mexico (GoM) spend all or part of their lives in the open ocean. Many mesopelagic and bathypelagic species migrate vertically each night to feed in the upper water column and return to deep water during the day. This behavior promotes rapid cycling of natural and anthropogenic material in the water column. Deep-pelagic nekton are prey for gamefishes, seabirds, and marine mammals. Given the steady growth of oil exploration and operations, the likelihood of future spills emphasizes the need to document acute and chronic effects on the pelagic fauna. The GoMRI-funded DEEPEND (Deep-Pelagic Nekton Dynamics) consortium was created for that purpose. DEEPEND is in the second of a 3year program that builds on two intensive NOAA-supported surveys during 2010-11. DEEPEND is focussed on timescales from short-term to interannual to appraise the dynamic nature of communities using a suite of integrated approaches. These investigations include: 1) a direct assessment of GoM deep-pelagic community structure including the physical and biological drivers of this structure; 2) a time-series analysis/comparison of biophysical data; 3) a time-series examination of differences in genetic diversity among key species; and 4) a biogeochemical analysis of the effect of DWHOS on pelagic biota. http://www.deependconsortium.or