Rufopoly is a participatory learning board game enabling players to undertake a journey through a fictitious rural urban fringe called RUFshire, answering questions and making decisions on development challenges and place-making; those answers then inform each player's vision for RUFshire. The encountered questions are determined by the roll of a die and based on primary data collected for a Relu project (2010-2012) about Managing Environmental Change at the Rural Urban Fringe. Rufopoly has been used extensively in early stages of projects and plans such as the pioneering Greater Birmingham and Solihull Local Enterprise Partnership spatial plan and has been used by government, EU project groups, local authorities, business, community groups, universities and schools. It has exposed audiences to issues associated with the delivery and trade-offs associated with planning and environmental issues at the fringe but crucially without the use of complex jargon. We believe that the full potential and impact of Rufopoly has yet to be fully realised. There are several reasons for this: 1. Rufopoly was developed towards the end of our Relu project as an unplanned output for a conference run by Relu in 2011 on 'Who Should run the Countryside?'. Its success prompted its inclusion as an output. 2. There were insufficient funds for it to be successfully tested and integrated with policy and practice communities to maximise its utility as a learning tool as this was never the original intention of the project. 3. It is currently presented as a one size fits all board game of a hypothetical place. More time is needed to explore the potential of Rufopoly to become a generic platform for stakeholders wishing to develop their own versions of the tool to meet their own needs and to fill a widely recognised gap in the effectiveness of participatory tools for improved decsion making. This knowledge exchange project addresses these deficiencies by drawing together the shared knowledge and previous experiences of designers and users of Rufopoly. This informs a series of interactive workshops in Wales, England and Scotland to identify how this kind of game-format can be enhanced into a more effective and multifunctional tool. This will help extend and embed the impact for a range of policy and practice partners in the form of a Rufopoly Resource Kit. By working collaboratively with end users we can identify how Rufopoly can be reconfigured across different user groups and organisations in tune with their agendas and needs. There are four stages to this project: WP1: Review and learn lessons from previous Rufopoly experiences. This involves (1) an assessment of the actual results and findings from past games that were written up and the results analysed. (2) critical assessments of the strengths and weaknesses of Rufopoly from facilitators and core participants. We will draw priamirly from our UK experiences but are also able to secure insights from the international adaptations of Rufopoly from Nebraska (November 2013) and Sweden (2014). WP2: Conduct a series of interactive workshops with different policy and practice audiences. These workshops will be held in England, Scotland and Wales using members of the research team and other participants. The purpose of these workshops is to (1) share results of WP1; (2) assess how the tool could be reconfigured to address the principla needs and challenges facing participants; and (3) prioritise feasible options for a Rufopoly Resource Kit. WP3: Using WP1 and WP2 outcomes, we will design and trial (across our team) the Rufopoly 'Mk2' resource kit and associated materials/guidance. WP4: Launch the Rufopoly Resource Kit and guidance in a live streamed global workshop event. This would; reveal the basic resource kit as co-designed by the team and enable testers of the resource kit to share their experiences maximising knowledge exchange and its range of potential applications.

Birds colliding with wind turbines are seen as one of the key environmental issues associated with wind farms. Before these wind farms are built, we use models to predict how many birds might collide so that we can ensure they are built in places where they do not pose an unacceptable risk to bird populations. However, the data that are used for these models are often very limited, meaning that estimates of the number of collisions likely to occur can be quite imprecise. We have collected high-resolution tracking data from lesser black-backed gulls in the north west of England. These data give detailed information about how birds move around the landscape, including in and around operational offshore wind farms. We will use tracking data to model collision risk within operational wind farms. These data will be used to show the distribution of birds within these wind farms and also to help predict collision risk at individual turbines, which is affected by both the height and speed at which birds fly (data which can be obtained from the tracked birds). This information will allow us to show, for the first time, how the risk of birds colliding with turbines varies across the wind farms. This will enable us to make recommendations about key areas to direct efforts for recording collisions and also where measures to prevent or reduce collisions are likely to be most effective. By recording bird distributions and relating behaviour to environmental conditions, we will be able to start to understand how collision risk varies in relation to changing conditions. This will enable us to use predicted wind conditions to make short-term forecasts about when and where birds are most likely to collide with turbines. This has the potential to help reduce collisions by allowing companies to identify when any individual turbine is likely to pose a high risk to birds, enabling them to better target measures to reduce collisions.

Tree planting has been the most common woodland expansion strategy in the UK for many decades. Despite its many benefits, this approach is increasingly being questioned following overestimates of benefits, poor targeting and challenges in scaling-up tree planting at the level required to meet ambitious woodland expansion targets. Consequently, there is growing interest in incorporating 'natural colonisation' (allowing trees to colonise new areas naturally) into woodland expansion strategies, partly because it is assumed that naturally created woodlands will be more structurally diverse, ecologically complex and resilient than planted sites. Embracing natural colonisation as a complementary approach to tree planting has the potential to radically transform UK treescapes and unlock woodland expansion at scale. Tree planting and natural colonisation may be used in complementary and blended combinations across a landscape, depending on the local conditions and the benefits expected. However, we know very little about the socio-ecological consequences of creating woodlands through approaches incorporating natural colonisation. We also have a poor understanding of land managers' attitudes towards woodland creation approaches other than tree planting, and it is not clear which kinds of land managers do, or would, engage with woodland creation through alternative approaches incorporating natural colonisation, and why. Using an inter-disciplinary approach, we will explore agricultural land managers' attitudes towards woodland creation strategies spanning the planting to natural colonisation continuum. We will also quantify the differing ecological and social consequences of these approaches, and identify factors associated with woodland resilience. Finally, we will integrate socio-ecological evidence to demonstrate how tree planting and natural colonisation can be used in combination to scale-up woodland expansion for a range of objectives on agricultural land. We will focus on broadleaf, and mixed broadleaf and conifer, woodlands created in agricultural landscapes with varying degrees of land-use intensity (from intensive arable lowland to marginal grassland on the upland fringe) and surrounding woodland cover, as these factors are likely to influence stakeholder perceptions and socio-ecological outcomes of woodland creation methods. These landscapes represent a major portion of UK land area with potential for woodland expansion. We will exploit two unique and complementary networks of woodland sites across the UK to create a novel platform from which to assess stakeholders' perceptions and socio-ecological consequences of woodland creation approaches spanning the planting to natural colonisation continuum. These sites provide a rich data resource and access to a diverse range of land-mangers. TreE_PlaNat will provide the evidence base to inform how, where, and for whom different strategies along the 'planting' to 'natural colonisation' continuum can be used to meet Government woodland expansion targets. Stakeholder organisations, including NGOs, statutory agencies and industry, are embedded in this proposal as co-applicants and project partners, demonstrating the co-development of this project and facilitating implementation of our findings.

Targeted management of the UK's fire prone landscapes will be crucial in enabling the country to achieve its commitments both to reach net zero by 2050 and to halt species decline by 2030. Many of our fire prone landscapes represent nationally significant carbon (C) stores. They also provide key habitats for unique species including many on the UK BAP Priority Species listing and are of strategic conservation value. But these typically shrub and grass dominated ecosystems are threatened both by the changing UK wildfire regime and some management tools aimed to mitigate this risk. Critical trade-offs therefore exist between the impact of episodic severe wildfire events and ongoing long term management practises, as well as between the positive and negative impacts of management tools on different prioritised ecosystem services; notably between C storage, habitat management and biodiversity provision. These trade-offs and the associated best management practises will vary between landscapes that have different management history, vegetation composition, legacy soil C stores and natural environmental conditions. Thus selection of the appropriate land management from the diverse toolkit available needs to be very carefully considered; the right tool to address the right priorities at the right location. The evidence base to make this complex choice, however, is currently weak. This undermines the ability of decision makers locally and nationally to assess the consequences of different wildfire management tools. IDEAL UK FIRE will address this urgent need, by determining the environmental costs and benefits of widely applied fuel management tools (burning, cutting, rewetting and managed succession) on habitat quality, biodiversity and the carbon balance in fire prone UK landscapes. We will directly contrast those medium-/long-term responses against the initial impact of the fuel management interventions and potential wildfires of varying severity. Through i) observations and collation of extensive historical monitoring, ii) experimental burns and wider management intervention and iii) the adaptation and application of the JULES land surface model, FlamMap fire analysis system and the Rangeshifter eco-evolutionary modelling platform, the project will: - Quantify carbon consumption and charcoal production across a range of (wild)fire and management intensities in different landscapes and under different land management strategies. - Determine the medium-term trajectories of biodiversity and carbon balance post intervention through a national chronosequence of management tools. - Develop next generation models to simulate the national long-term consequences of land management strategies to the UK ecosystem carbon balance, carbon climate feedbacks, habitat quality and biodiversity. We embed all this knowledge into a newly developed accredited training module for the land management sector. The module supports land managers to understand the consequences of different management tools, supporting them to make informed decisions in their landscapes to best meet both national and local management goals. The training programme will provide a generalisable frame-work to evaluate land management practices and a knowledge platform to inform government policy on the costs and benefits of wildfire management tools.

In recent years, three major innovations have occurred in ecology. (1) The emergence of new statistical methods for analysing community data; (2) the rapid detection of species and whole communities from environmental DNA (eDNA) and bulk-sample DNA; and (3) the wide availability of remotely sensed environmental covariates. The efficiency gains are such that hundreds or even thousands of species can now be detected and, to an extent, quantified in hundreds or even thousands of samples. Collectively, these three innovations have the potential to relieve the problems of data limitation and analysis that environmental management has been struggling with, opening the way to near-real-time tracking of state and change in biodiversity and its functions and services over whole landscapes. The aim of our project is to develop an integrated statistical framework for DNA-based surveys of biodiversity. The framework will allow the estimation of community compositions and the identification of the landscape characteristics that drive them. We will develop a Bayesian hierarchical model accounting for the probabilistic nature of DNA-based data due to observation error and taxonomic uncertainty and for model uncertainty due to the unknown strength and direction of landscape effects on the system. We will build sophisticated and efficient algorithms within a Bayesian framework for identifying the important landscape covariates that predict community structure and provide guidelines on optimal allocation of resources in DNA-based surveys for achieving the required power to infer species distributions and to link them to landscape covariates. The huge potential contribution of DNA-based data to landscape decision-making is demonstrated by how Natural England, Local Planning Authorities, and the NatureSpace Partnership use eDNA to create a biodiversity-offset market ('District Licensing') for the protected Great Crested Newt (GCN). Water samples from 500 ponds across the South Midlands (spanning ~3320 sq km) were tested for GCN and used to create a distribution map, which was then zoned into four 'impact risk' levels. Builders pay a known, sliding-scale fee, and a portion of the fee is used to build and manage new habitat. District Licensing is only feasible with eDNA's greater efficiency. GCN District Licensing expands to at least 16 LPAs in 2020, aiming to go nationwide, which would make it the largest biodiversity-focused, land-use decision scheme in the UK, if not the world. The natural-and highly desirable-extension to the GCN scheme would be to map 'all biodiversity' and to make land-use decisions (e.g. impact risk maps, offset markets, habitat creation) on this broader basis. In fact, samples originally collected for GCN can be repurposed for this larger goal by using 'metabarcoding,' meaning that the eDNA is PCR-amplified for a larger range of taxa. Given the District-Licensing expansion plans, pond eDNA metabarcoding alone could provide an efficient way to map biodiversity across much of the UK. This is far from the only such programme. Ecologists in industry and academia around the world are plunging ahead with large-scale DNA-sampling campaigns, and there is, as yet, no comprehensive set of statistical methods for modelling the individual steps of the new observation processes, quantifying the resulting uncertainty, and assessing how it affects decision-making at the landscape level. Our proposed modelling framework will provide such tools by explicitly capturing measurement bias within biodiversity models as a set of observation processes, and not merely as error. Improving sampling designs and workflows as a result of our proposed models will profoundly increase the efficiency and credibility of inference and therefore reduce the risk of biodiversity loss during the political process of allocating land to different uses.