Project 2: Global storm risk to coastal cities under climate change
Dr Yu Mo, Prof Jim Hall, Oxford University Centre for the Environment
OVERVIEW: Tropical cyclones, also known as hurricanes, typhoons, or windstorms, cause large losses to coastal cities every year. The storm losses, unfortunately, are expected to further increase as the globally average storm intensity increases in a warmer climate. In addition, the storm risk to coastal cities is highly uncertain owing to the ever-increasing coastal development. The objectives of this project are to (1) assess storm damage using satellite-based Earth observations to better evaluate storm risk, and (2) introduce the student to quantitative skills in physical geography and geospatial data analysis. During the project, the student will, built on existing codes, acquire and process night-time light data (i.e., VIIRS and DMSP) to assess economic loss of storm events over the past few decades; and collect and verify reported social-economic data to validate the satellite measurements.
Potential areas of interest include Small Island Developing States (SIDS) in the Indian Ocean and the Pacific. The data analysis will be performed with the Google Earth Engine, a cutting-edge cloud-based platform for planetary-scale geospatial data storage.
TIMELINE: The project is divided into three stages: (1) week 1-2, background reading for storm damage assessment and learning example codes; (2) week 3-4, collect and validate new data datasets; and (3) week 5-6, data analysis and report generation.
STUDENT’S INITIATIVE: The student will work with the supervisor to choose the study’s region of interest and the satellite datasets to be studied. The student will also be free to choose the format of the final report. For example, it can be a report focus on a statistical analysis of the data or a novel form of data visualization. The student will also be encouraged to submit the report to a conference and to be a co-author of a peer-review journal article.
A willingness and aptitude to learn tools and computer codes for analysis of big datasets.
Project 4: Assessing the dynamics of seal-fishery interactions in the UK
Dr Katrina David, Department of Biology (Zoology)
As apex predators, marine mammals play important regulatory roles in marine systems. Following protective legislation in the 20th century, many marine species’ populations have recovered from human exploitation. Increases in these populations has increased the spatial overlap of foraging and global-fisheries areas—leading to negative economic outcomes for fisheries and conflict with these animals. This is the case in the UK, where grey seal populations have increased under protective legislation and now negatively impact UK fisheries. With 33% of fish stocks overfished, and fish consumption growing by 1.5% per year, conflict between marine mammals and fisheries is likely to increase. This research is motivated by the need to identify the economic impact of grey seals on UK fisheries, and how this impact is affected by fishery and seal population characteristics. Global reports of fisheries losses incurred by seal depredation remain anecdotal, with no understanding of the economic impacts of these losses or their drivers. Without this information, policy organisations like DEFRA are unable to understand whether compensation or other seal-mitigation responses are required to support fisheries. This project will develop a mechanistic understanding of the extent and drivers of seal impacts on fisheries, which could include fishery characteristics (gear, target species) and seal population characteristics (location, population size or trend). The project will also initialise a long-term structured population dataset for grey seals in UK waters—for which important data regarding rates of growth, survival and reproduction are missing. This is an exciting and timely research area because unravelling the workings of this social-ecological system will help achieve better conservation outcomes while improving people’s income and living conditions.
Project 6: Synthesis and public database of multiple-stressor interactions in freshwater ecosystems
Dr. James Orr and Dr. Michelle Jackson, Department of Biology (Zoology)
Freshwater ecosystems are central to our existence but they are being crippled by a huge diversity of anthropogenic stressors. The devastating ecological impacts of pesticides like Roundup, harmful algal blooms caused by excess nutrients, invasive species like the Zebra mussel, and heat waves associated with climate change all regularly make headline news. Freshwater ecologists have invested a huge amount of effort towards understanding the mechanisms of these stressors individually. Unfortunately, in a multiple-stressor world, knowing the individual effects of each stressor isn’t sufficient for accurate prediction of their combined impacts. This is because stressors that co-occur in time and space can interact with each other in complex ways. For instance, many invasive species become far more harmful to native species under warmer climates. Chemical reactions between multiple pesticides can create lethal cocktails that aren’t predicted by traditional risk assessments. There is even evidence that many pollutants can become attached to microplastics, making their combination more toxic than just the sum of their individual effects alone. A major challenge for freshwater ecologists and conservation biologists is to understand the mechanism underpinning all of these stressor interactions so that accurate predictions can be made about their combined effects.
We recently searched the literature using a novel machine learning tool to find freshwater multiple-stressor experiments. Based on previous traditional literature reviews, we expected to find about 200 relevant publications. Remarkably, we’ve found over 3000! This unexpected and exciting result has presented us with a novel challenge: we currently don’t have the time to screen and collect data from all these papers by ourselves. For accuracy and efficiency, the full text screening, which requires constant dialogue and cross-validation, must be performed by a small group of researchers who can dedicate their time to the project. We are therefore looking for a research assistant to help us screen and collect data from these publications for six to eight weeks during the summer of 2022. The research assistant will also get the opportunity to collaborate with us on an exciting freshwater multiple-stressor experiment being conducted this summer at the University of Oxford’s field station in Wytham. There is also potential to learn about the exciting tools, like flow imaging microscopy, that we use in the laboratory to understand how ecological communities are being impacted by multiple stressors. Finally, towards the end of the placement, the research assistant will collaborate with us on the development of a web-based interactive public database of multiple stressors in freshwaters based on our screening work.