Biodiversity on land provides huge benefits to humanity through carbon capture, resilient ecosystems, provision of food, and effects on human health. To manage and conserve our resources we need to understand how biodiversity is changing in response to the environment and human impacts. Moreover, we have implemented global targets to measure and protect nature through recent international agreements. Commonly used methods of reporting (e.g., datasets generated by citizen scientists) have limitations in terms of spatial, temporal and taxonomic resolution. This is problematic given that ecological communities are naturally dynamic systems in which both species and their interactions change, and these kinds of data are necessary to assess nature recovery. Both positive and negative human impacts on nature happen on relatively short timescales, but data are not collected with sufficient regularity for us to understand and manage these rapid changes. Coverage within datasets is biased towards popular animals (e.g., birds), with greater records coverage in densely inhabited areas. I have pioneered an approach that will deliver widespread, rapid understanding of biodiversity and ecological community dynamics on land. My initial work has shown that airborne environmental DNA (eDNA) is shed from animals, plants and fungi into the atmosphere, and that this broadly reflects the composition of the surrounding community. I have recently shown that this material is being continuously collected by an existing globally distributed infrastructure: air quality monitoring networks. These networks are filtering the air at daily or weekly intervals to measure particulates and pollutants but are also inadvertently collecting information on biodiversity. My overall aims are to understand how ecological communities are responding to human impacts globally and deliver technological solutions to the problem of scale in biodiversity monitoring using the air quality networks. I will do this by working with the environmental departments of four countries to analyse the molecular information from their air quality networks over three years. I will explain finescale temporal variation in species richness, turnover, community composition and ecological network "modules" (groups of tightly co-occurring species), and how these change over time according to environmental variation and human impacts. In addition, the recent COVID-19 pandemic offers the opportunity to quantify the effects of reducing human activity on biodiversity dynamics within the framework of a natural longitudinal experiment. While usual biodiversity monitoring was halted during these years, air quality monitoring continued, and these filters have been stored in long-term archives. I will work with an additional five countries (Switzerland and four countries in S America and Asia from the GAPS megacities project) to quantify the impacts of the "Anthropause" on biodiversity dynamics and ecological network properties. I will harness a multidisciplinary approach to further study the nature of airborne environmental DNA itself. Working with atmospheric scientists, I will study the particulate size range of airborne eDNA, in addition to the effects of sampling time and local weather conditions on samples. A combination of field experiments and particulate dispersal modelling will allow me to understand how far eDNA disperses from animal populations. These experiments will be used to inform other work packages in the FLF, but will also be of great interest to end-users implementing the technology. This work will have multiple beneficiaries from many sectors because society increasingly recognises that biodiversity preservation is both a cross-sector responsibility and challenge. I will work with policy stakeholders to explore how these data inform the UK's initiatives to protect and restore nature, monitor invasive species and forecast responses to future environmental changes.

Clouds formed by aircraft (contrails) are the most easily visible human forcing of the climate system. Trapping energy in the Earth system, they contribute more than half of the total climate impact of aviation. This makes reducing contrails an important goal to achieve the UK's climate commitments. Theoretical considerations indicate two pathways for reducing contrails. First, improving engine design to emit fewer particulates may reduce contrail lifetimes and so their climate impact. Second, rerouting aircraft to avoid contrail forming regions. Assessing these pathways requires accurate models of contrail formation, evaluated at the level of an individual aircraft. This evaluation requires observations of contrails across their lifetime, coupled to details of the generating aircraft. Even where they are matched to specific aircraft, existing observations typically view a contrail once, (limiting their use for measuring contrail lifecycles) or cannot provide the detail on the contrail microphysical properties (such as ice crystal number or shape) necessary to assess the efficacy of different pathways to contrail reduction. Improving confidence in our contrail models urgently requires novel observations of contrail properties and lifecycles from individual aircraft. The impact of aircraft on clouds is not limited to contrails forming in clear air. Over half of contrails form embedded in existing clouds and the particulates emitted by aircraft can affect cloud formation several days after they were released. These effects produce a cooling, potentially large enough to offset all other warming effects of aviation, but are not represented in aircraft-level models used for planning contrail avoidance strategies. There are few observational constraints of these effects, targeted observations of the impact of individual aircraft on cloud microphysics are required to assess them and to improve future model simulations. To address these uncertainties and around contrail formation, persistance and climate impact as well as aerosol-cloud interactions, COBALT has three core components: 1. A measurement campaign in the southern UK, combining an array of ground-based cameras with a steerable cloud radar, to make high resolution observations of contrail formation from individual aircraft. Guided by aircraft transponder information, these observations will be focused on contrails and clouds modified by aircraft, characterising contrail formation and perturbed cloud properties within the first few hours of their lifecycle. 2. Counterpart satellite observations, using novel techniques to characterise contrail and cloud development from an hour to several days behind the aircraft. Building on techniques for studying natural cirrus, this will produce a complete characterisation of the contrail lifecycle, along with the first estimate of the aviation aerosol impact on existing cirrus clouds at a global scale. 3. The complete lifecycle characterisation will be combined with flight data from aircraft operators to produce a unique dataset designed specifically for the evaluation of aircraft-level models of contrail formation. An initial focus will be placed on evaluating aircraft-scale models, as these are currently being used to plan aircraft diversions. A comparison of climate model parametrisations of contrail formation will assess the ability of the parametrisations to reproduce the wide-area (>1000km2) contrail observations taken by the camera array. Led by an inter-disciplinary team of scientists and engineers, with partners in key international research centres and industry groups, COBALT will provide the tools necessary to evaluate our current models and ability to avoid contrails, guiding future modelling and operational trials of sustainable fuels and contrail avoidance.

The oldest, thickest sea ice in the 'last ice area' of the Arctic - a region thought to be most resilient to climate warming - unexpectedly broke up twice in the past year. Our current theories assume that the end-of-summer ice-covered area will steadily retreat into the Central Arctic Basin as global warming accelerates over coming decades. However, the dynamic break-up events witnessed in 2018 challenge this prevailing view. Here we hypothesise that a weaker, increasingly mobile Central Arctic ice pack is now susceptible to dynamic episodes of fragmentation which can precondition the ice for rapid summer melt. This mechanism of dynamic seasonal preconditioning is unaccounted for in global climate models, so our best current projections are overlooking the possibility for rapid disintegration of the Arctic's last ice area. Our team has demonstrated that seasonal preconditioning is already responsible for the neighbouring Beaufort Sea becoming ice-free twice in the past five years. Even ten years ago this region contained thick perennial sea ice, mirroring the Central Arctic Ocean, but it has now transitioned to a marginal Arctic sea. Could the processes responsible for the decline of the Beaufort Sea ice pack start to manifest themselves in the Central Arctic? Currently, a shortfall in satellite observations of the Arctic pack ice in summer prevents us from testing our hypothesis. We desperately require pan-Arctic observations of ice melting rates, but so far satellite observations of sea ice thickness are only available during winter months. Our project will therefore deliver the first measurements of Arctic sea ice thickness during summer months, from twin satellites: ESA's Cryosat-2 & NASA's ICESat-2. We have designed a new classification algorithm for separating ice and ocean radar altimeter echoes, regardless of surface melting state, providing the breakthrough required to fill the existing summer observation 'gap'. Exploiting the recent launch of multiple SAR missions for polar reconnaissance, our project will integrate information on ice-pack ablation, motion and deformation to generate a unique year-round sea ice volume budget in the High Arctic. This record will inform high-resolution ice dynamics simulations, performed with a suite of state-of-the-art sea ice models from stand alone (CICE), ocean-sea ice (NEMO/CICE), to fully coupled regional high resolution (RASM), and global coarser resolution (HadGEM) models, all now equipped with the anisotropic (EAP) sea ice rheology developed by our team. Using the regional and stand-alone models we will analyse the role of mechanics in this keystone region north of Greenland to scrutinise the coupling and preconditioning of winter breakup events - such as those witnessed in 2018 - to summer melting rates. Using the coupled models, we will quantify the likelihood of the Arctic's last ice area breaking up much sooner than expected due to oceanic and atmospheric feedbacks and how this will affect the flushing of ice and freshwater into the North Atlantic.

Environmental change is happening on a global scale. Freshwater ecosystems represent some of the most endangered habitats in the world, with declines in diversity (83% in the period 1970-2014) far exceeding that of terrestrial counterparts. One of the primary causes of reduced riverine ecosystem health is a loss of habitat associated with excessive fine sediment deposition (typically referred to as particles <2mm). Fine sediment is a natural part of river systems, however alterations to land use (e.g. intensive farming) and channelization / impoundment (via dams and reservoirs) have altered the quantity of fine sediment such that inputs now far exceed historic levels. Additionally, increasing hydrological extremes associated with climatic change, such as intense rainfall events, are likely to further increase the delivery of fine sediment to river channels. Fine sediment deposition alters and degrades instream habitats making rivers unsuitable for flora and fauna to live in. Such changes lead to reductions in the biodiversity of riverine ecosystems and affects all components of the food web from fish and insects through to algae. Understanding the ecological implications of fine sediment is therefore imperative to be able to manage our rivers so that they can support and sustain healthy ecosystem functioning and support anthropogenic activities (e.g., fisheries, recreational activities). This is however challenging because a number of environmental factors control the consequences of fine sediment for flora and fauna. The proposed Fellowship aims to understand and quantify which environmental factors (e.g. land use, size of fine sediment and of the gravels within the river, time of year) influence the severity of fine sediment deposition for river communities. Specific objectives are to (i) quantify the trends between fine sediment loading and ecological responses in the UK and internationally; (ii) determine if there is a threshold of fine sediment loading before ecological degradation occurs and how this varies within individual rivers, (iii) develop understanding of how environmental controls (e.g. grain size, hydrological exchange) structure the effects of fine sediment and; (iv) outline a future research agenda to tackle the management of fine sediment in rivers. In achieving these objectives, my Fellowship will provide a framework to determine when and which river types (e.g. highland or lowland, geology) are most at threat from fine sediment pressures internationally. The Fellowship will focus on macroinvertebrates (river invertebrates such as snails, insects and crustaceans) as a target organisms being abundant, diverse and occurring across the globe. The Fellowship represents a novel and exciting research programme with international reach and applicability that combines global datasets with multi-country field and artificial stream channel experiments (alpine and lowland) and laboratory experiments over different spatial scales to develop and validate theories spanning different environmental settings. The fellowship will lead to an exciting step-change in our understanding and will address unique fundamental research questions whilst working synergistically with UK statutory regulatory agencies and end-users such as the Environment Agency of England, Natural Resources Wales and Scottish Environmental Protection Agency. The research generated will have important ramifications for how stakeholders allocate resources to monitor and manage UK riverine ecosystems and will enable more efficient and targeted conservation and restoration plans.

Until recently, awareness of the importance of winter carbon dioxide emissions from arctic soils was highly limited, resulting from incorrect assumptions that emissions from frozen soils beneath snow were insignificant compared to other sources. Consequently, carbon dioxide emissions during arctic winter months are frequently omitted from global carbon cycling budgets and our capacity to measure atmosphere-snow-soil processes controlling carbon dioxide emission and simulate them in climate models are under-developed. This limits our ability to make future climate projections, especially in arctic tundra and forested regions, which characterise about 27% of the Earth's land surface and are warming more than twice as fast as the global average since the late twentieth century. Carbon dioxide, a gas which causes the Earth's atmosphere to trap heat causing the planet to warm, is emitted by microbes decomposing organic material in soil. Decomposition can occur when the soil is frozen, but rates of carbon dioxide emission decrease as soil temperatures decrease, down to -20 degrees Celsius when carbon dioxide emissions become negligible. Winter snow cover has an important impact on arctic soil temperatures, acting like a duvet covering a bed. A thick duvet with lots of air trapped between the feathers provides insulation. Air trapped between the snow crystals within a snowpack acts in a similar manner, limiting the loss of heat from soils warmed in the summer to the cold atmosphere during long arctic winters. As the ground is often snow covered for at least half of the year in Arctic regions, it is vital that we understand processes that control the impact of snow cover on soil temperatures and carbon dioxide emissions, and accurately represent these processes in climate models. Here we ask, how sensitive are measured carbon dioxide concentrations within arctic snowpacks to the variability of snowpack physical properties (e.g. size of the snow crystals)? Can more realistic simulations of snowpack density and thermal conductivity in climate models reduce the underprediction in carbon dioxide emissions from arctic snowpacks? And, how may future changes in winter soil temperatures and snow cover affect future carbon dioxide emissions? In order to answer these questions, we will create a new field measurement database of arctic meteorology, soil and snow properties, and carbon dioxide concentrations. We will use this database to develop more realistic representations of processes controlling winter carbon dioxide emissions in climate models, which will lead to confident model projections of future winter carbon dioxide emissions from the wider Arctic region. By combining field and laboratory measurements with climate modelling, this partnership between Canadian, Finnish and UK scientists will increase our predictive understanding of Arctic environmental change resulting from, and contributing to, our warming planet.