Summer REPs

This year, NERC has allocated the DTP in Environmental Research funding for eight Summer REPs. These are mini projects of 6 - 10 weeks that are undertaken in departments within a research group and with supervision of a senior academic.

Summer Research Experience Placements are a great way for undergraduate students to get paid research experience during the summer holidays. You can apply for a Summer REP if you are currently an undergraduate undertaking your first degree and won't have completed prior to the date of the Summer REP.  You also need to be eligible to be funded by NERC (UK resident, or pre-settled/settled status).

Summer REPs are increasingly being aimed at helping socio-economic and under-represented ethnicity students to get valuable research experience, particularly those who need to work during the holidays.  Students will be paid a living wage in line with the table below.  They also give students from other areas the added opportunity to become familiar with an Oxford department and to network with staff and students. 

This year, for the first time, we are excited to announce that we are able to offer free accommodation for the duration of the Summer REPs for students coming from outside Oxford, in addition to the salary.  We will be basing salary on the UKRI stated wage band for 23+ which is £10.18 per hour (plus free accommodation), irrespective of age.  We assume a working week of 37 hours.

If you wish to apply for a project, you should first make contact with the supervisor to discuss the project and then go to the online application form.  Deadline to apply has been extended to 14th May 2023.

We are still gathering projects from our supervisors, but these are the projects that have so far been submitted. 

Department of Archaeology

Reconstructing the sustainability of past farming practices in western Germany

Amy Styring – amy.styring@arch.ox.ac.uk

The stable carbon and nitrogen isotope values of plants reflect the soil and environmental conditions in which they are growing. They can therefore act as a ‘time capsule’ of past agricultural practices, providing indicators of manuring and watering intensity that can help to understand how sustainable food production was in prehistory. This project will determine the stable carbon and nitrogen isotope values of cereal grains preserved on archaeological sites in western Germany to explore how the intensity of farming practices (i.e., manuring inputs) changed through time, from the Neolithic to Roman period (5500 BC – 400 AD). This will provide the comparative framework to understand how farming practice in this region compared to elsewhere in Europe and to the subsequent Medieval period (500 – 1200 AD).

Identifying volcanic ash in North Atlantic marine records to help reconstruct explosive eruption histories of the Azores and the Canary Islands

Victoria Smith victoria.smith@arch.ox.ac.uk, Danielle McLean and Emma Horn,Tephrochronology Research Group

The explosive volcanic histories of volcanic islands in the Atlantic (Azores and the Canary Islands) are poorly constrained as on land deposits are often eroded or buried by deposits of subsequent activity. These detailed histories are crucial to understanding frequency and magnitude of past eruptions, which is essential to understanding the hazard posed by volcanoes which in turn can be used to mitigate risk. A way at getting detailed histories of volcanic islands is by identifying visible and cryptically preserved ash layers in marine cores. This project will focus on marine cores off the coast of NW Africa with the aim of constraining the explosive eruption history of the Azores and the Canary Islands. The successful applicants will be trained in the laboratory on the procedure to locate volcanic ash layers, and will use an electron microprobe to chemically characterise the layers so they can be assigned to source.

Department of Biology

Division of Labour 

supervised by Stuart West stuart.west@biology.ox.ac.uk

Division of labour is when cooperating individuals specialise to carry out specific tasks and it is a unifying feature across all levels of biology, from groups of cells to complex animal societies. How can we explain variation across species, in both whether there is division of labour, and the form that it takes. Why does division of labour emerge in some species, but not others? This project will examine the ecology and life history of insects, to test the role that different factors have played in the evolution of reproductive division of labour (eusociality). The project will collect data from the literature on key explanatory variables, to test their possible role in the evolution of division of labour, with a comparative (across species) approach

Quantifying and predicting community resilience

 Supervised by Rob Salguero-Gomez - rob.salguero@biology.ox.ac.uk

Resilience is a key property of natural ecosystems. Indeed, their ability to respond to disturbances by opposing change via their resistance, or quickly recovering from them is a key characteristic of healthy, biodiverse ecological systems. Yet, the quantification and prediction of resilience in natural systems remains elusive because ecological systems are typically very complex. The NERC REP student will join a team leading mathematical and experimental developments in the field of ecological resilience to investigate the key characteristics of species that result in higher community-level resilience. The student will be exposed to a wealth of research approaches (including fieldwork in Wytham Woods, drone piloting, orthomosaic image analysis, and R programming) to gain key insights into what makes communities resilient. At Wytham Woods, the student will partake in DRAGNet (Disturbance and Resource Acquisition in Grasslands Network), a global network of plant community ecologists evaluating the effects of mechanical and chemical disturbances on endemic grassland communities. Specifically, the experiments that the student will be able to participate in exert the local plant communities to simulated cattle stepping and fertilization, with the ultimate goal of understanding what mechanisms allow the local communities to go back to equilibrium after such intense disturbances.

Resilience of food web modules to changing climate environments

Supervised by Mike Bonsall – michael.bonsall@biology.ox.ac.uk

The world is warming at an unprecedented rate. The recent IPCC report highlighted that climate change is rapid, widespread and intensifying. Over the next 20 years average global temperatures are expected to increase by a further 1.5°C. But climate change is not just about increasing temperatures, it is also about increasing variability in climatic factors and how ecosystem respond to these different aspects of environmental change. In this REP, the student will develop mathematical models of ecological food web modules (2 and/or 3 species interactions) to investigate the resilience of different modules to climate change. Deterministic and stochastic models of competitive, mutualistic and parasitic food web interactions will be developed and analysed using metrics to assess the likelihood of tipping points, changes in dynamics and resilience in these ecological systems.

Large African predator population assessments

Supervised by Dr Andrew Loveridge andrew.loveridge@biology.ox.ac.uk & Dr Lara Sousa  lara.sousa@biology.ox.ac.uk

The Trans-Kalahari Predator Programme (TKPP, https://www.wildcru.org/research/tkpp/) is a research and conservation project based in the Wildlife Conservation Research Unit (Department of Biology). TKPP has undertaken over 35 biodiversity surveys using camera traps across protected area sites in both Botswana and Zimbabwe. This has generated a dataset of ~ 2.5 million images of African species. With a focus on spotted hyaena (Crocuta crocuta) and other large predators, the successful Summer Research Experience Placements will work with the project scientists to collate and identify spotted hyenas individuals, for a number of survey datasets, which will involve learning methods and techniques for individual identification of animals (using AI/machine learning interfaces) and the application of analytical tools for estimating species occurrence, with opportunities for co-authorship on publications generated from these analyses if appropriate.

Pre-requisites. Interest in African ecology and biodiversity conservation. Familiarity with (or willingness to learn) R and GIS. Use of suitable laptop and access to an internet connection.

Capacity to take on 1-2  students for this work

Department of Earth Sciences

Mapping the global distribution of marine zooplankton with machine learning

Supervisors: Prof. Samar Khatiwala samar.khatiwala@earth.ox.ac.uk, Prof. Heather Bouman heather.bouman@earth.ox.ac.uk and Dr. Anna Rufas Blanco
Duration: 8 weeks

Marine zooplankton are key drivers of the transfer of carbon from the surface to the deep ocean, where carbon stays sequestered for centuries. Zooplankton feed on organic matter and, in their life cycle, they generate faecal pellets and moribund carcasses that sink to the deep ocean,transporting a large amount of organic carbon. Despite the critical role of zooplankton in the global carbon cycle, our understanding of the distribution of zooplankton biomass in the water column is hindered by both lack of sampling and a simplistic representation of zooplankton feeding dynamics in the ocean biogeochemical models embedded within the Earth System Models used to project future climate change. This represents a major obstacle in our understanding of the role of zooplankton as a facilitator of the transfer of carbon to the deep ocean and reliably predicting changes in the marine carbon sink. This project is aimed at developing and analyzing a global zooplankton biomass data product from extant data sets and using machine learning to map the sparse observations on a global scale. This work will help make significant progress in our understanding of zooplankton dynamics and improve global ocean biogeochemical models.

Impact of Southern Ocean polynyas on the ocean circulation and biogeochemistry

Supervisor: Prof. Samar Khatiwala

Duration: 8 weeks

Polynyas are giant 'holes' in the seasonal sea ice covering the Southern Ocean and Arctic. Seemingly appearing randomly and 'out of nowhere', they can have an enormous impact on air-sea fluxes of heat and climatically-important gases such as CO2 and oxygen. These in turn can affect deep and bottom water formation as well as the marine carbon cycle. This project will analyze the spatiotemporal distribution of polynyas in IPCC CMIP6 climate model simulations and compare them with satellite data. Polynyas will be automatically identified in fields of sea ice fraction by using image processing methods such as the flood-fill algorithm. Machine learning approaches, in particular random forest, will then be applied to better understand the physical controls (atmospheric and oceanic) on the frequency and spatial location of polynyas. Time permitting, the work will involve performing simulations with a global ocean biogeochemical model to quantitatively assess the impact of polynyas on the marine carbon cycle.

Interpreting seismic signals from the Brunt Ice Shelf

Mike Kendall mike.kendall@earth.ox.ac.uk and Tom Hudson – Earth Sciences

Subject area: geophysics and seismology

The Brunt Ice Shelf floats on the Weddell Sea and is one of many Antarctic ice shelves under threat from warming global temperatures. In 2012, cracks in the Brunt started to expand, eventually leading to large slabs of ice detaching from the shelf. In 2023 the ice shelf released an iceberg roughly the size of the greater London area. The British Antarctic Survey operates the Halley Research Station on the Brunt Ice Shelf. In the austral summer of 2022/23, geophysicists at the Halley base deployed a small array of seismometers near one of the propagating cracks. These seismometers have recorded a wide of seismic signals, the source of which is not always clear. This internship will explore the nature of these enigmatic signals and what insights they provide into ice crevassing. As this will be a computer based project, suitable interns will have good numerical and computational skills and an interest in seismology. 

Deciphering seismic tremor

Jess Hawthorne jessica.hawthorne@earth.ox.ac.uk 

Some seismic signals are simple.  They represent the ground shaking created by a single burst of seismic energy---a single earthquake, perhaps.  However, other seismic signals are more complex.  They are created by a complex suite of bursts: by a dense cluster of earthquakes or by a more continuous source like moving water, wind, or magma.  In this project, which would suit a student with or without geology or geophysics experience, you will help develop new tools to decipher these complex seismic signals, known as seismic tremor.  You will use template-based and neural network approaches to identify individual bursts of energy in synthetic and observed tremor, likely focusing on tectonic tremor in Alaska or Costa Rica, where tremor is created by millions of tiny earthquakes.  Your work will help us identify these earthquakes and understand why they are tiny.

School of Geography and the Environment

Stress-testing England’s Biodiversity Net Gain policy

Rich Grenyer (richard.grenyer@ouce.ox.af.uk) and Nat Duffus (natalie.duffus@biology.ox.ac.uk)

Biodiversity Net Gain (BNG) is a new, mandatory requirement for housing and industrial building developments in England. It requires that they demonstrate a 10% increase in biodiversity when finished, calculated using the Biodiversity Metric - a way of trading off different habitat types and conditions against each other. However, there is little evidence to support the Biodiversity Metric as a measure for real world biodiversity. Without evidence that metric calculations translate into actual biodiversity gains, how can we know what BNG will really achieve? This Summer REP project will involve the collection of invertebrate and floristic biodiversity measures to test for correlation against the score assigned by the Biodiversity Metric. The placement will be primarily in the field, on various farms in Oxfordshire, working on data collection, habitat mapping with GIS, habitat assessments (using UKHAB), and applying the Biodiversity Metric, with training provided for all these skills. There will also be a desk-based component, presenting an opportunity for the student to analyse the floral data collected against the metric scores, and learn more about the wider policy context of the work and how to write scientific papers with the possibility of coauthorship.

Previous experience identifying common British plants and/or invertebrates  desirable but not essential. Full training can be given, as with all lab, field or analytical techniques.

Quantify global storm risk to coastal cities under climate change with satellite-based nighttime night observations

Jim Hall (jim.hall@eci.ox.ac.uk) and Yu Mo  (yu.mo@ouce.ox.ac.uk)

OVERVIEW: Tropical cyclones, also known as hurricanes, typhoons, or windstorms, cause large losses to coastal cities every year. The storm losses 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 ever-increasing coastal development. The objectives of this project are to (1) develop matrices to assess storm risk and city resilience 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.   

Pre-requisites - Interest or experience in physical geography

Department of Physics (Atmospheric, Oceanic & Planetary)

Modelling the ocean drivers of ice-sheet melting in Greenland fjords

Lead supervisor: Andrew Wells (andrew.wells@physics.ox.ac.uk, Dept of Physics), co-supervisor Helen Johnson (Dept of Earth Sciences) 

The response of the Greenland ice sheet to changing ocean conditions is a key uncertainty in future projections of sea level rise. The Greenland ice sheet discharges into the ocean through many long and narrow fjords, which mediate the exchange of heat and freshwater between the ocean and ice sheet edge. Such fjords are challenging to resolve in global Earth System models, which has motivated the development of a box-model parameterisation of fjord circulation for coupled ocean and ice sheet models. 

Recent work has shown that the evolving ocean stratification in fjords has a key impact on ice-sheet frontal melting and the depth at which meltwater discharges into the wider ocean. However, the impact on future ice sheet retreat is unknown. This project will investigate the importance of fjord dynamics for the coupling between ocean and ice sheet across a range of case studies, using a box-model parameterisation of fjord circulation in conjunction with a flow-line model of outlet glacier dynamics. The project will be computational in nature, so past programming experience is an advantage. The project will suit students interested in applying mathematical and computational modelling skills to tackle a problem at the interface of physical oceanography, glaciology, and numerical Earth-system modelling. 

Satellite Measurements of Atmospheric Composition

Supervisor: Dr Anu Dudhia anu.dudhia@physics.ox.ac.uk 

The IASI instruments on the MetOp satellites routinely measure the infrared spectrum emitted upwards from the Earth. From these spectra we can occasionally identify anomalous signatures associated with large concentrations of various gases emitted in pollution events. The project is to study these in more detail.

Project Outcomes

A brief report summarising the occurrences of large concentrations of a chosen molecule, with some background on the processes that might explain these events.

Entry requirements: Reasonable computing skills, python preferred.