Available Projects (Summer 2020)

COVID-19 UPDATE: Most of the projects that are currently on offer within my lab involve analysing data that already exist, meaning that they can be tackled using existing data and remote-working. If you have any questions about the available projects, please feel free to email me at: R.Milligan@nova.edu 

The following projects are currently available in the Seascape Ecology lab, and open to current or new MS Marine Science & MS Marine Biology students at Nova Southeastern University. Data for the following projects are already available, and you will work with Zan Milligan and other lab members to learn the necessary tools and techniques as you go. The list is updated regularly as new opportunities and datasets become available, so check back often if you're interested:


The Deepwater Horizon Oil Spill (DWHOS; April 2010) was a globally unprecedented event, which released an estimated 5 million barrels of crude oil into the deep waters of the Gulf of Mexico from a depth of 1500 m. With extremely limited pre-spill data for the deep-pelagic realm, DWHOS has prompted a decade of extensive research efforts to better understand the dynamic structure, function, and potential vulnerability of the deep-living fauna to disturbance. Nonetheless, we still have many unanswered questions, and there is a need to develop better predictive tools that are applicable to the future management of pelagic ecosystems. Some potential project topics are provided below:

Size structuring of fishes (Population level) 

(Available projects >3 [Taxon-specific])

Understanding how individual body sizes (i.e., lengths and/or weights) within a population vary over time, in relation to depth, or with major environmental variables is an important step in understanding population dynamics within the offshore Gulf of Mexico.


Size spectrum analysis of the fish assemblage (Assemblage level) 

(Available projects >3)

Marine assemblages are often strongly structured by body size, making this a potentially valuable, and simple-to-use indicator of assemblage structure over time, using tools such as size spectrum analysis for example. However, while these tools have been successfully used to examine the effects of coastal fisheries impacts, it is not clear how they may be applied to other impacts and marine systems. Projects on this topic would be required to address questions such as:

  1. What data are needed to accurately determine the size structure of the fish fauna? [Lab work required]

  2. How does the size-structure of the fish assemblage vary over time? With depth? In relation to major environmental features in the Gulf of Mexico?

  3. Do different gear types (i.e., high-speed rope trawl vs. MOCNESS) produce consistent results?

Biomass Patterns (Population / Assemblage Level) 

(Available projects >3 [Taxon-specific])

Much of the analysis conducted to date has focussed on understanding patterns in the abundances of the fish fauna in the offshore Gulf of Mexico. However, biomass data are likely to be more useful in the development of e.g., ecosystem models, and so an understanding of how biomass varies through time, with depth, and in relation to oceanographic features is therefore an important goal. Projects on this topic could be conducted in conjunction with the body-size and/or abundance analyses if appropriate.

Computer-Aided Image Classification of Micronekton 

(Available projects >3 [Taxon-specific])

Through the DEEPEND project, we have amassed the largest collection of deep-living pelagic fishes in the world, but identifying the fauna from this highly speciose region requires extensive taxonomic expertise. In this project, we aim to build a photographic library of specimens, using Prof. Sutton's extensive specimen collection which is housed at Nova Southeastern University. Through this project, we will explore the potential for computer-assisted identification tools to aid in the process specimen identification for future resource management efforts, and to identify the benefits and limitations of such an approach.