The atmospheric boundary layer (BL) is the layer of the atmosphere near the Earth's surface which is directly influenced by the surface. The BL plays a key role in the atmosphere - controlling the exchange of heat, moisture and other atmospheric constituents (both natural and anthropogenic) between the surface and the free troposphere. The boundary layer is also crucial in the initiation of convection and so impacts on the location and timing of convective rainfall. Turbulence is a key characteristic of the BL but is generally too small scale to be resolved in weather and climate models and so needs to be parametrised. With increased computational resources it is now feasible to run operation weather forecasts at km scales where convection can be resolved explicitly (though not necessarily well resolved). As we move towards sub-km scale the models will also begin to resolve large scale boundary structures. This regime where we partly resolve these key processes is known as the grey zone. Modelling the boundary layer in the grey zone requires re-evaluation and modification of the boundary layer parametrisation schemes and their coupling to convection (parametrised or explicit). This project will firstly evaluate the currently available boundary layer schemes and their coupling to convection in the Met Office Unified Model (MetUM) at different resolutions across the grey zone as well as testing any new developments produced as part of this programme. Secondly it will study the coupling between surface heterogeneity, boundary layer structures and convection to understand the key role of heterogeneity. Previous studies largely focus on homogeneous case studies, despite the fact that most land is actually not flat and covers a variety of land use and surface conditions. Including surface heterogeneity will allow a more thorough evaluation of the current boundary layer schemes as well as providing a physical underpinning for more realistic parametrisations which are aware of the underlying variability in the surface characteristics. The project will make use of the latest field observations from the upcoming Wescon field campaign as well as data from long term observational sites in the UK and US. We will also utilise the latest Meteosat third generation satellite observations to evaluate the model in the tropics. We will combine these observations with idealised large eddy simulations and more realistic simulations with the MetUM to study the behaviour of the boundary layer over the diurnal cycle at homogeneous sites and for heterogeneous regions (e.g. regions with variable surface temperature and moisture, or gentle topography).

Metals are one of the most common pollutants of our soils. However, whether these potential poisons are taken up by an organism and what the subsequent toxic effects are is only known for a small number of species - usually those easily maintained in the laboratory or very common and widespread in the field. The limited scope of our current understanding of metal "accumulation" and the linked "toxicity" in different species makes it difficult for us to predict and monitor the negative effects that metal pollution has on ecosystems - whether directly due to toxicity or as a result of predators eating contaminated prey. We know from past work that even among the limited species tested, metal accumulation and toxicity can vary greatly. Further, we already know some of the main ways that metals can cause toxicity and also some of the systems active in cells by which such effects can be prevented through "detoxification". For metals this process is often associated with changing the form of the metal to an inert inorganic compound, locking it away into intracellular compartments or binding it to different proteins and/or peptides. What we currently do not know, however, is how these mechanisms and systems contrast between species and how this inter-species variations, in turn, lead to differences in the extent of accumulation and linked toxic effect. In this project, we want to develop a "framework" that unifies understanding of how metals are taken up by different soil animals, distributed between tissues, change their chemical associations and cause damage to cells, organs and the organism as a whole, resulting ultimately in toxicity for a species. Our framework is based on developing understanding in three areas. i) Measuring the rates at which a metal enters into, and is distribute, between the tissue of soil animals. We will quantify this by analysing metal levels in major tissues, using radio-labelled compounds to assess uptake and loss and generating tissue maps to determine where and how much metal is accumulating in the body. For larger invertebrates we will dissect the tissue but for the smaller organisms we will use state-of-the-art laser assisted mapping technologies. ii) Assessing the way that metals change their chemical associations on up taken into an organism, either through chemical reactions, compartmentalisation or by binding. We will measure these processes by analysing the chemical form of the metals within different pools in separated tissue samples and by using X-ray methods that determine the co-localisation of metals with other elements and known metal binding molecules. iii) Evaluating the resultant damage to cells and tissues from exposure to the different metal forms. This will be measured by assessing biochemical responses associated with damage and linking these to the pathways that regulate metal accumulation and the chemical form present within the organism. We will determine how the damage caused translates through various levels of biological organisation to result in toxicity at the level of the whole organism. Studying these three aspects for four metals (manganese, lead, copper and cadmium) that have different dominant chemistries and essentialities in eight common and ecologically important soil invertebrate species, will allow us to develop a new model that describes the processes that lead to metal accumulation and toxicity. This approach will greatly improve on the current approaches used in ecosystem focused toxicology, which have so far focused on external metal chemistry in the soil and how this impacts on exposure. Further, developing this organism-focused model, will allow us to extend our studies to other species beyond those studied here to more easily predict how much of a given metal each may accumulate and just what toxic impacts will result. This capacity will significantly advance on the current approaches used in comparative ecotoxicology.

Global-scale sustainability transformations are urgently required to address catastrophic climate change and biodiversity loss. In practice, however, the conservation, restoration and management actions to combat these crises will be applied at local scales: to individual forests, fields, lakes, and grasslands. Practitioners, policymakers and ecologists have long-recognised the futility of silver bullet, 'one-size-fits-all' strategies, and the importance of targeting and tailoring actions to specific or individual contexts, and developing action plans for specific species, or individual sites. For example, the UK government's ambitious tree planting initiatives emphasise the importance of 'the right tree in the right place' to achieving Net Zero, because the wrong trees planted in the wrong place may fail to establish, or worse still, lead to net carbon emissions that persist for decades. However, despite the need for context-specific information for individual sites, ecology has traditionally focused on average effects, rather than individual effects, undermining the ultimate goal of applied ecology: the application of ecological science to the real-world. To do science that can truly inform on-the-ground policies, ecology can capitalise on methods developed by the rapidly advancing field of 'precision medicine', which similarly rests on the premise that the effect of a given drug or treatment may be different for each individual patient, necessitating personalised healthcare plans. The application of precision medicine methodologies, which require 'big data', is now possible due to the increasing availability of vast quantities of ecological data from multiple sources, including remote sensors, citizen scientists and environmental monitoring networks. In this exploratory project, we will adapt the use of precision medicine approaches to applied ecological problems and develop novel approaches that help guide the next generation of applied ecologists into the big-data era. We will develop frameworks and tools for sampling and modelling big data in a way that yields accurate and practicable knowledge that can inform on-the-ground actions. This project will achieve this using a 'virtual ecology' approach using an existing computer model - 'iLand' - that simulates real, forested landscapes in Europe, the U.S.A and Japan. First, we will use iLand to virtually implement forest restoration actions to individual forests across these landscapes. The forests in these landscapes will then be subjected to virtual sampling, thus mimicking the collection of data by ecologists, citizen scientists and remote sensing technologies. For example, we will mimic surveyors that measure forest biodiversity as part of a national environmental monitoring campaigns. We will then apply different modelling methods to analyse the virtually sampled data, including methods developed in the field of precision medicine as well as methods that are commonly used in ecology. By comparing the results of these analyses against the 'true' simulated data, we will be able to evaluate how different sampling and modelling decisions influence the accuracy of our results. Specifically, we will assess the accuracy of predictions individual forest responses to restoration actions across a range of environmental conditions (i.e., elevation, climate, soil types). We will use this understanding to develop guidelines for designing future environmental monitoring surveys, and modelling of big data, that maximises the accuracy of these predictions. By shifting applied ecology's focus away from average effects, towards actionable, individual-level effects, our guidelines will enable policymakers to target and prioritise restoration actions to areas where desired effects are greatest, thus maximising efficacy of limited resources for addressing climate change and biodiversity loss.

Humans have modified over 75% of the global land area, leading to huge, negative impacts on biodiversity. A major consequence is that once large natural habitats have become fragmented into small islands of habitat within a sea of human-modified land such as farms and cities. Most species depend on dispersal (the movement of individuals from where they are born to a different location) to maintain healthy populations across landscapes. When their habitat becomes fragmented into small, isolated patches, species are often unable to disperse effectively between the remnant patches and this frequently results in population declines, loss of genetic diversity and local extinctions of species. Understanding how best to manage landscapes that are fragmented is a key challenge. One of the most promising responses to fragmentation is to conserve or restore wildlife corridors, i.e. swaths of natural habitat between otherwise isolated habitat patches to facilitate dispersal, gene flow, and population rescue. Indeed, corridor creation is at the core of national (e.g. England's 25 Year Environment Plan) and international (e.g. the UN's Connectivity Conservation Project) environmental policies. Many conservation and environment agencies (e.g., Natural England, the USA's 22 Landscape Conservation Cooperatives) are designing - and public and private conservation investors are implementing - wildlife corridors. Huge sums of money in direct expenses and foregone development opportunities are being invested in corridors. However, we lack an understanding of if such corridors work. Most of what is known about corridor efficacy comes from experiments on model systems that do not resemble real-world wildlife corridors. New studies are needed to address the crucial questions: do corridors counter real-world fragmentation; and what corridor characteristics constrain effectiveness? To address these questions, we need to do fundamental research into the ecology of species' dispersal over large-scales and within complex, human-modified landscapes. Existing experiments on corridors study the effects of corridors less than 0.5km long and less than 0.4km wide, much smaller than corridors in the real world. Our objective in this project is assess corridor effectiveness in a number of human-modified landscapes. We will address major knowledge gaps about the characteristics of effective corridors by studying 4-6 focal species in each of 20 landscapes in Europe and the Americas. Each of these 20 landscapes contains three types of habitat configurations: isolated habitat patches, pairs of patches connected by a corridor, and a large intact natural area. The landscapes are ideal because they vary in corridor widths (0.2-3km) and lengths (1-25km), which resembles the large scales at which habitat fragmentation and corridors are design in reality. Using genetic methods to assess how a variety of mammal species move in these different habitat configurations, we will identify whether mammals are able to use corridors at these large scales and which corridor characteristics (e.g. length, width) most strongly influence success. We will assess where and how unsuccessful corridors fail. We will also use novel analysis of species characteristics, such as body size, dispersal ability, brain size and reproductive rate, to identify which types of species are most likely to benefit from corridors and determine whether different types of species might require different types of corridors. Finally, we will use our new data in ecological models to test a range of methods for planning wildlife corridors, which will make the project useful to conservation managers globally. Our project will deliver vital new information on how to make wildlife corridors successful for a large variety of species, will bring new understanding into species dispersal over very large scales, and will provide new methods for determining where to best invest resources for conservation.

Long Term Large Scale - Freshwater Ecosystems (LTLS-FE): Rivers in the United Kingdom have in the past and the present been subjected to a range of pressures due to the release of chemicals and by-products, such as domestic wastewater, acid rain, the application of nutrients and pesticides to soils, and the use of domestic products such as medicines. While some of these pressures (e.g. acid rain, wastewater discharges) appear to have eased over recent decades, others (e.g. pesticides, nutrients) remain and may be increasing. In addition to these pressures, climate change is also expected to impact on the quality of UK rivers, for example by leading to changes in anthropogenic chemical use, by changing the amount of water in rivers and thus how much water is available to dilute chemicals, by making storms and floods more or less frequent, and by changing the volume of chemicals washed into rivers from the land. Climate change could also influence freshwater biodiversity, for example by increasing the exposure of organisms to pulses of toxic chemicals during storms or by increasing the likelihood that UK rivers are invaded by alien species which outcompete native species. The quality and health of UK rivers are of great interest to many groups - the general public who rely on waters for recreation such as swimming and angling, to the regulators who are tasked with improving and then maintaining water quality, and to water companies who partly rely on rivers for drinking water supplies. It is therefore important that we try to understand as well as possible how water quality and health might be affected by future changes in the way society uses chemicals and water, and how these might be further affected by climate change. This is a complex problem, because the factors that drive river quality are many and they will vary over time and from place to place. This project will tackle the problem by developing a model that will use these drivers to predict how chemical inputs, river quality and river health will change in the context of different 'pathways', or scenarios of change in society and climate. By doing this, we will provide a range of 'projections' of future river quality and health. These projections will help scientists and policymakers to understand the main factors controlling river quality and health. This will help them to develop solutions to manage and ameliorate possible changes in the factors that influence river quality and health, with the goal of maintaining and improving the state of UK rivers in a changing world. As well as our projections of possible futures for UK river quality and health, we will make the data and model code available to all at the end of the project. This will provide other researchers with possibilities such as changing the mathematics of the model, adding new chemicals as they emerge, or applying the model to other countries and parts of the world.