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Research in the Seascape Ecology lab focusses on

  1. Identifying spatial and temporal distribution patterns of mobile deep-sea animals and their underlying drivers;

  2. Understanding how the migration and dispersal of deep-sea animals creates connections between ecosystems;

  3. Understanding how deep-sea ecosystems are impacted by anthropogenic activities, and how we might be able to predict and manage the effects of future change.

To achieve these goals, we make use of world-class datasets and cutting-edge data analysis and statistical tools. 

Spatial Distributions of Deep-Sea Fishes

Much of our current research focuses on understanding the drivers that influence spatial distributions of deep-sea fishes over time, in relation to distinct habitat features in the water column or at the seafloor (e.g. cold-water corals, abyssal hills, mesoscale eddies). Using the Gulf of Mexico as a case study, we are currently working to determine the relative importance of environmental conditions, life-history traits, and dispersal (by ocean currents or active movement) in structuring the assemblages and populations of deep-living fishes in the oceanic Gulf of Mexico. By better understanding the distributions, behaviour, and natural variability of these assemblages, we hope to develop tools that will enable us to predict the impacts of future human or natural impacts and the spatiotemporal scales at which they are most relevant within the pelagic realm. 

Human Impacts in the Deep Sea

The vast size and highly dynamic nature of the deep oceans make them difficult to study, and yet the resources they hold are being increasingly targeted as human activities move progressively away from coastal and shelf ecosystems. Understanding the risks associated with such activities, creating predictive tools and identifying indicators of change are therefore important for the sustainable management of our oceans. Following the Deepwater Horizon oil spill in 2010, we are working with Tracey Sutton and the DEEPEND consortium to develop methods with which we can readily identify biologically-relevant pelagic habitats, and detect evidence of faunal change. Through this work, we aim to develop tools that will be of use to both researchers and resource managers in predicting faunal responses in the offshore Gulf of Mexico, and other pelagic systems.

Distributions of fishes around an abssal hill
Classifying water masses in the Gulf of Mexic

Temporal Variability in Deep-Sea Demersal Fishes

Through the Deep-ocean Environmental Long-Term Observatory System (DELOS) project, we are studying temporal changes in the abundances of deep-sea fishes on the continental slope off Angola, West Africa. Working on long-term photographic data collected from an active oil field at a depth of 1500 m since 2009, we are working to understand how seasonal patterns in abundance might be linked to overlying sea surface productivity within the region, and to understand the drivers that might cause such recurrent behaviours within the assemblage. 


Mobile organisms can create important connections between ecosystems. In pelagic ecosystems, many deep-living organisms conduct diel vertical migrations between the deep depths their inhabit during the day and the surface waters where they feed, and thus are likely to play important roles in carbon sequestration from the atmosphere. Across the deep-sea floor, long-lived, high trophic level fishes accumulate energy from prey or widely-dispersed carrion falls, and redistribute it over space and time. Similarly, the open and deep oceans are increasingly recognised as important habitats and feeding grounds for numerous commercially-important and charismatic marine species. Understanding how different types of animal movements connect distant ecosystems and influence their functioning across varying spatial and temporal scales is an important ecological question that we are working to answer.

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DEEPEND - Deep Pelagic Nekton Dynamics of the Gulf of Mexico
Deep-ocean Environmental Long-term Observatory System

Collaborations & Current Projects

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