Project highlights

  • Join an international, interdisciplinary team of scientists to develop predictive models of marine biodiversity; 
  • Train for highly transferable skills including data science, quantitative modelling and programming;  
  • Conduct impactful research that will contribute to policy making. 


The marine biota provides an important component of our food systems, yet our knowledge of how many species being harvested for human use is rather limited, especially among marine invertebrates. For example, marine bivalves, including the widely beloved scallops, oysters, and cockles, are exploited by humans for food across the world, while also being important players in ecosystems. However, a critical first step towards understanding the diversity, traits and geographic distribution of exploited bivalve species was only initiated recently, in our newly published study (2023 Nature Communications). We compiled the first global list of bivalve species reported as having been used by humans and integrated the data with a global bivalve database of species traits, fossil occurrences and geographic distributions, setting the foundation for a predictive framework forward for effective conservation and resource management.  

In this project, we will employ quantitative techniques to answer three research questions:  

  1. Good genes or good locations? Exploited bivalves are found to be of large sizes and living in shallower waters, suggesting inheritability of the potential for exploitation. Meanwhile, the proportion of bivalve species being exploited varies dramatically across the world, suggesting biogeographic and/or social-economic influence. A comparative analysis, synthesizing phylogenetic and geographic factors, including biological traits, environmental conditions and anthropogenic pressures, will illuminate the underlying drivers of exploitation variation.  
  2. Who have we missed? Using results for Q1, we will build predictive models, using a variety of techniques for cross-validations, to identify exploitable species for conservation and management that were not on the initial list. Some of these species were missing due to the lack of accessible documentation and others represent unrecognized food sources, especially if they are abundant and widespread to ensure sustainability and require low harvesting effort.   
  3. Where will they be by 2050? Fossil evidence shows that the geographic distributions of marine bivalves were extremely dynamic in response to climate changes. We will model how exploited species are likely to shift their distributions relative to the human populations that rely on them, which are critical for sustainable harvesting and conservation.  

A photo of diverse harvested bivalve species from the Smithsonian museum and a global map of the proportion of exploited species in marine bivalves.


University of Birmingham


  • Organisms and Ecosystems


Project investigator

Shan Huang (University of Birmingham, [email protected])


Professor Fabian Spill (University of Birmingham, [email protected])

Dr. Katie Collins (Natural History Museum, [email protected])

Dr. Stewart Edie (Smithsonian Institute, [email protected])

How to apply


This project will take advantage of cutting-edge techniques in data science. All bivalve data are integrated in a relational database and actively curated by the larger collaborative team. As an important component of the research training, you will contribute to continuously updating the database, especially the geographic occurrence and exploitation data using the literature. All other data are available in public databases or through the collaboration network of the supervisory team.  

To answer the research questions, you will synthesize the data using a variety of statistical and mathematical models. You will compare potential factors of exploitation (Q1) using Bayesian multi-level regressions and machine learning, which also provide a multi-perspective framework for identifying missing species (Q2). Future distributions of exploited species (Q3) will be inferred using up-to-date species distribution models (SDM), based on environmental conditions of current distributions, fossil occurrences and widely acceptable future climate scenarios.   

Training and skills

Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.  

You will gain a variety of experience and trainings in biodiversity research and data science. Working closely with a multi-disciplinary supervisory team, you will develop various skills highly transferable across academia and industry, including database development, data query, statistical modelling and spatial analyses using the widely-used R programme. Trainings also include scientific writing and presenting at conferences. You will have opportunities for research visits to two of the world’s largest natural history museums and interact with a larger, international collaborative team (e.g. Prof. David Jablonski at University of Chicago and Prof. Kaustuv Roy at University of California San Diego).  

Partners and collaboration

Both contacts at the partner institutes will contribute to overall project development and will host research visits during the project. In addition, Dr. Collins (NHM) will supervise updating the list of exploited bivalve species, arrange access to the NHM library resources (for compiling data from the literature) and provide guidance on taxonomic revision. Dr. Edie will contribute to training in database management and advise on analytical strategies. The larger collaboration team includes researchers from University of Chicago, University of California San Diego and University of California Santa Barbara.   

Further details

Further details on how to contact the supervisor for this project and how to apply for this project can be found here: 

For any enquiries related to this project please contact Dr. Shan Huang ([email protected]). More about Shan’s research can be found at her university staff webpage:

To apply to this project: 

  • You must include a CENTA studentship application form, downloadable from: CENTA Studentship Application Form 2024. 
  • You must include a CV with the names of at least two referees (preferably three) who can comment on your academic abilities. 
  • Please submit your application and complete the host institution application process via:   Please select the PhD Geography and Environmental Science (CENTA) 2024/25 Apply Now button. The CENTA application form 2024 and CV can be uploaded to the Application Information section of the online form.  Please quote CENTA 2024-B22  when completing the application form. 

Applications must be submitted by 23:59 GMT on Wednesday 10th January 2024. 

Possible timeline

Year 1

Initial CENTA and project-related training, learning about the bivalve database and comparing various factors in relation to bivalve exploitation (Q1). 

Year 2

Writing manuscript 1, developing predictive models for identifying missing species from the list of exploited bivalves (Q2) and writing manuscript 2. 

Year 3

Inferring future distribution of exploited bivalves (Q3) and writing manuscript 3 and the PhD thesis. 

Data update and revision will be a continuous effort throughout the project, but individual publications can be produced based on the most up-to-date versions of the dataset at the time.  

Further reading

Edie, S. M., Huang, S., Collins, K. S., Roy, K. and Jablonski, D. (2018) ‘Loss of biodiversity dimensions through shifting climates and ancient mass extinctions’, Integr. Comp. Biol., 58, pp. 1179–1190. 

Huang, S., Edie, S.M., Collins, K.S., Crouch, N.M.A., Roy, K., and Jablonski, D. (2023) ‘Diversity, distribution and intrinsic extinction vulnerability of exploited marine bivalves’, Nature Communications.  

Gephart, J.A., Henriksson, P.J.G., and Parker, R.W.R. et al. (2021) ‘Environmental performance of blue foods’, Nature, 597, pp. 360–365.