EPSRC : Connor Lenihan : EP/R513064/1 The goal of this project is to combine the respective strengths two novel, complementary approaches to solving the Quantum Many Body Problem, the name given to the problem of the equations of quantum mechanics becoming impossible to solve by conventional methods due to very large numbers of particles being involved, such as in materials. To deal with this, an abstract mathematical formalism was developed, which requires advanced numerical algorithms, implementation and large-scale calculations on a computer. We will attempt to bring together the key advantages of two pf the most promising algorithms, the well- established Diagrammatic Monte Carlo method, and the more recently discovered Algorithmic Matsubara Integration (AMI). The new technique produced will allow physicists to reliably describe and control the most challenging, and most important, phenomena of strong electron correlations in a class of problems previously out of reach for any state of the art method.

The project aims are to synthesise and characterise materials suitable for the adsorption and separation of toxic gases, such as NOx and SOx, with the opportunity to also investigate catalysts for CO2 separation. The opportunity to develop and examine novel and existing materials for applications in the adsorption and separation of toxic gases is of great importance. Reducing emissions from freight exhaust, oil refineries, and other gas evolving industries is of great importance to the health of the planet and its inhabitants. This is one of the biggest topics of discussion in the twentieth century and something that needs to be addressed immediately and on a global scale. A variety of analytical techniques will be used to thoroughly characterise materials and analyse the effectiveness of the materials for the applications being investigated. Extensive knowledge would be gained surrounding the materials and their applications, and a variety of other techniques will create more data to analyse.

NERC : Zoe Melvin : NE/L002604/1 Global wildlife is increasingly subject to human-induced disturbance, such as habitat loss and land-use changes. Some species are able to cope with these changes while others are not, leading to species declines and extinctions. One of the most important ways that animals cope with human disturbance is by using flexible coping strategies in new situations created by disturbance. Social grouping is one strategy that animals adapt according to the situation that they are in. The goal for any animal is to maximise the amount of food you eat while reducing your risk of death so that you can pass on your genes to the next generation. Group-living animals can reduce their risk of death by sharing the time spent looking for danger, but they also need to share food with other group members. Being flexible in the size of your group would allow you to maximise the benefits and minimise the costs of group-living given your situation. For example, animals could group together in areas with many predators to allow them to eat while sharing the time spent looking for danger and split apart in areas of low risk to reduce competition for food with other group members. Similarly, animals could group together more at times of the day or the year when their chances of encountering a predator is higher. As more and more habitat is lost or degraded, animals are forced to feed in areas that present a higher risk of encountering human predators, such a farmland. Being able to group together flexibly in risky habitats and split up in low-risk habitats may allow species to cope better with human induced-change. In this project, we aim to investigate the effect that grouping together has on where and when animals choose to feed. I will address this question using 18 female elk in one herd in Manitoba that lives in a mostly agricultural landscape. These elk wear Global Positioning System (GPS) collars that have been collecting data on their locations at regular intervals for two years. I will use a combination of tests to investigate what is driving elk to choose certain habitats and whether the distance between each animal and its closest neighbour changes in more in risky areas (i.e. agricultural land) and more risky times of day (i.e. hunting season and daytime when humans are more active). This research will give us a better understanding of how animals cope with habitat disturbance and the potential for social grouping to be used as a coping strategy. Elk populations in Manitoba are generally in decline which could have negative impacts on livelihoods of people that depend on the hunting industry. The information gained in this study will help local stakeholders to make decisions about land-use changes and hunting quotas in their area to promote the sustainable population growth of elk and support local livelihoods.

NERC : Jessie Foest : NE/S00713X/1 Northern high-latitude ecosystems are warming faster than any other ecosystem on Earth. Such warming strongly affects the vegetation in previously temperature-limited systems such as the sub-arctic tundra. Treelines, the ecotones between forests and the tree-less tundra, are expected to respond by shifting northwards. However, a meta-analysis on treeline advances found that only half of the examined treelines had advanced since 1900. Why warming is associated with treeline advances in some but not other populations remains unresolved. It is crucial to understand how treeline ecosystems will respond to climate change. Firstly, the soils in tree-less tundra regions store a third of the Earth's soil carbon. When trees encroach on these areas, they change soil conditions (e.g. drying, aerating soils) and facilitate further vegetation shifts. This may release the stored carbon from the soil. Additionally, climate feedback loops may arise because of changes in the system's albedo, where an increase in tree cover may drive further warming. Tree reproduction may help explain why treelines show lagged responses to warming. A recent global synthesis of reproductive behaviour across 13 sub-arctic treeline ecotones reported that low numbers of viable seeds were produced in these populations. In plants, the early life stages that occur after seeds fall to the forest floor (i.e. germination and seedling establishment) are characterised by high mortality rates. Low levels of seed production may thus result in complete failure of seedling recruitment. Consequently, some populations might be unable to advance poleward with climate warming. However, we have a poor understanding of how seed production and seed viability vary in sub-arctic forests. In this project we will investigate how climate controls seed production and viability in black spruce (Picea mariana), the dominant treeline-forming species in the north-west sub-arctic. Moreover, the proposed research will be used to establish a longer-term experiment to test our hypothesis that the capacity for black spruce treeline advance is determined by their ability to produce sufficient viable seeds. Snapshot data collected by the hosting group and their network between 2006-2011 revealed that the amount of spring-time growing degree days (days with daily mean temperatures >5 degree C), higher levels of summer precipitation and higher conspecific densities of trees increase seed production in a variety of treeline-forming species. Consecutive years with more growing degree days and low precipitation levels, variables linked to moisture stress, were associated with low seed production. Seed viability was affected by climatic conditions during flowering, as well as by stand and seed characteristics. Continuing and expanding data collection in these quickly changing ecosystems will help determine if the drivers of seed production are changing. Such an evolving understanding is required to accurately model and predict future seed availability in forest tundra systems.

NERC : Beth Evans : NE/L123456/1 Agricultural expansion in northern boreal regions presents an opportunity to generate food security and self-sufficiency in the face of climate change. However, little is known about how conversion of boreal forest to agriculture affects soil invertebrate communities, despite their essential role in sustaining crop productivity among many other soil functions essential to human well-being. This project will assess how soil invertebrate communities and the biological quality of soil on farmland change due to conversion and how long the soil has been cultivated since. Soil biological quality, measured using the QBS-ar index, is a good indicator not only of soil biodiversity, but the capacity of soils to maintain soil functioning for delivery of goods and services. In addition to generating an original data set for use by the wider scientific community, we will produce a range of technical and plain-language resources to (i) facilitate widespread monitoring of soil biological quality and (ii) inform agricultural policy and land management decision-making tools to develop sustainable agricultural landscapes in Canada's northern boreal regions.