Classifying Pelagic Habitats in the Gulf of Mexico

I am delighted that our latest paper has been published today in Limnology & Oceanography: Methods, titled "An empirically validated method for characterizing pelagic habitats in the Gulf of Mexico"!

Read-Only Link:

Full Text Link:

About the Paper:

The pelagic (open-ocean) realm is a highly dynamic and fluid environment, which provides by far the largest inhabitable living space on the planet. Despite its great size, we know relatively little about the dynamics and spatial distributions of the organisms that inhabit the pelagic realm, particularly in deep waters. This lack of understanding stems partly from the vast spatial scales involved, but also from the dynamic nature of the environment: compared to seafloor topography for example, the water column is in constant motion, and many important structuring features like mesoscale (10s - 100s of km) eddies and water currents are transient and mobile, with diffuse boundaries. Given the fluid nature of the water column, being able to classify environmental features as relatively discrete entities is therefore a useful starting point to understand what their effects on the fauna might be.

Example sequence showing the Loop Current entering the GoM from the Caribbean and exiting to the Atlantic Ocean. Created by Dr. Matt Johnson using HYCOM model data .

In the Gulf of Mexico (GoM), one of the major oceanographic features is the Loop Current, which enters the GoM from the Caribbean Sea through the Yucatan Channel and exits the GoM into the Atlantic Ocean through the Florida Straits to become the Gulf Stream. Occasionally however, the Loop Current will extend northwards into the GoM and create a (warm-core) Loop-Current Eddy (LCE), with unique water mass characteristics (Fig. 1). The fact that we can identify discrete water mass types in the GoM provides the justification for developing and applying a classification system in this case. LCEs in the GoM are associated with a lower abundance and biomass of pelagic fauna, and may be a means of transporting low-mobility fauna (e.g. plankton and some micronekton) between oceanic basins. A great deal of our recent research with the DEEPEND consortium has been focused on understanding the importance of LCEs in structuring the deep-living pelagic fish assemblage and understanding how they might affect faunal vertical migratory behaviours.

Fig. 1: Collecting water samples and water-column profiles data with a CTD rosette

However, one of the major issues with identifying LCEs and subsequent effects on pelagic organisms is that while in situ water column measurements (such as temperature-depth and temperature-salinity profiles) can readily identify Loop-Current Origin Waters (LCOW), the sampling resolution of the measurements are fine-scale and instantaneous, which makes it difficult to scale up from a particular set of measurements to cover a broader spatial extent, or longer temporal duration. Hydrographic models (such as the HYCOM model) are able to address some aspects of this scaling issue, but to date there have been few attempts to reconcile in situ measurements with a modelling framework and develop them to an ecologically-relevant habitat classification scheme. In our new paper, we attempt to do just that.

By combining in situ empirical physical (TS \ TD profiles) and microbial assemblage data from the GoM water column (10 - 1500 m depth) collected over four research cruises between 2015 - 2017, we were able to identify consistent markers of water mass type corresponding to three potential pelagic "habitats": Gulf Common Water (CW), LCOW, and "MIX" water (which is formed as LCOW mixes in the GoM and degrades to CW; Fig. 2). These were then used to create and validate a classification scheme we could apply to the publicly-available HYCOM model of the GoM, allowing us to predict where LCOW, MIX and CW waters are likely to occur. By using a combination of sea surface height (SSH) and temperature at 300 m depth as our core variables to better allow for vertical transitions between water mass types, we were able to use HYCOM to predict of water mass types within the GoM (Fig. 3). Overall, this model worked well, achieving approximately 80% agreement between the empirical and model datasets, with excellent agreement between LCOW and CW regions. The mismatches between methods almost entirely occurred around MIX waters, as would be expected in transitional regions.

Still, there are still a number of questions left to address in the future, including a better understanding of the effect of LCE age on their characteristics, and identifying markers for other features of interest, such as the Mississippi river plume, cyclonic (cold-core) eddies. Our hope is that this work will provide a useful tool for resource managers and oceanic ecologists working in the GoM, to help identify pelagic "habitat" types across the seascape and better understand their importance to the biota.