The migration of birds from temperate and arctic breeding grounds to lower latitudes for the non-breeding season is a major global wildlife event, comprising billions of birds and providing an important component of global ecosystems. Some of these movements are truly amazing - some 12 gram birds fly 3000km non-stop to reach their non-breeding grounds. The majority of inter-continental terrestrial migrations are undertaken by songbirds, which migrate across broad fronts, often stopping to refuel on their journey. Despite intensive study on the breeding grounds, and to a lesser extent the non-breeding grounds and stop-over sites, research to simulate the migratory journeys themselves, or to test theoretic models of migration for such species, is rare. A generic model of migration has never been applied to songbirds undertaking the Europe- trans-Saharan migration; this is a major objective of this proposal. In light of projections of climate and land-use changes on the breeding, non-breeding and stop-over grounds of these species, such models are urgently required. Migrants could be especially vulnerable to climate change given their reliance on the linkage between widely-separated areas, which are potentially undergoing very different changes. The main limitation to developing and testing models of songbird migration has been an inability to monitor individual movements so as to understand their routes and strategies. The recent development of geolocator trackers, which record time and location and can be used on the smaller species that comprise the majority of migrants, has provided data to test migration models for the first time. Here, we will collate tracking, and extensive ringing and observation data for trans-Saharan migrants, to better understand their migratory routes and decisions. Simultaneously, we will develop flight models for individual species, which consider species-specific physiology and form to determine their flight-range potential. We will use the outputs in spatially-explicit dynamic programming (DP) models, and will test their ability to replicate observed patterns of migration. This will build on earlier work modelling optimal migration using very simple systems. We have already developed pilot flight range models that replicate well the timing and routes of migration of tracked individuals of species with near-linear migrations. Building on these data, we will use DP models, with realistic landscape resources/costs, to evaluate optimal migratory routes and refuelling locations given temporally-constrained destination rewards (i.e., likely breeding success). We will consider landscapes with dynamic resource availability, based on factors such as species-specific habitat preferences and likely food availability (based on weather and NDVI), and will include factors such as wind direction, location (relative to time of year) and an individual's energy stores to determine whether they should stay or, if not, where they should move to. We will use these models to explore inter-annual variation in arrival dates at migratory end-points, to aid understanding of what drives phenological changes in migratory species, and to test theories of what determines migratory decisions. Modelling formalises our understanding of migration, making explicit our assumptions and any gaps in available data. Crucially, it can also inform our understanding of the migratory process and how that process will be influenced by future environmental changes. The end product will be a much better understanding of the drivers of the routes and strategies of long-distance migrants, and a modelling framework that can be applied to a wide suite of migratory passerines in different regions, or under scenarios of climate and land-use change, to simulate consequences for migratory journeys.

Considerable effort and money has been devoted to determining the ecological consequences of a wide range of interventions, which has resulted in an extensive literature. However, research shows that practitioners only rarely use this literature when making decisions as to which intervention to implement. Furthermore, many accepted beliefs in conservation practice are actually incorrect. Scientific results are traditionally published in academic journals. However, it is often difficult for practitioners to extract the pertinent information from these. The major problems are that most practitioners do not have access to the Web of Science or equivalent scientific search engines, it is often difficult to target the search for conservation interventions without producing vast numbers of irrelevent titles and many practitioners do not have the training to extract the conservation message from academic papers. Evidence-based medicine has revolutionised medical practice in that the collection, review, and dissemination of the evidence now underpins most medical practice. We suggest that conservation would benefit from a similar revolution and propose that evidence-based conservation should become a standard approach. In this model we envisage practitioners having easy access to summaries of the literature, that they would monitor the effectiveness of some interventions for which the evidence is weak or ambiguous, that there would be reviews and meta analyses where there are numerous studies relating to one issue, and there would be synopses summarising the evidence for the major interventions. This proposal seeks to provide an open access database of the majority of the papers relating to the consequences for birds of conservation interventions. Syntheses of the consequences of a wide range of interventions will be a key output. Full use of the output will also require a change in approaches to conservation. The involvement of all the major organisations involved in bird conservation (BirdLife International - a partnership of over 100 national global bird conservation organisations, British Trust for Ornithology, Joint Nature Conservation Committee, Natural England, Royal Society for the Protection of Birds, Scottish Natural Heritage and World Conservation Monitoring Centre) will both ensure that the project is as required by practitioners but will also ensure that the results will be widely used both in the UK and internationally. Training in the use of evidence-based conservation will be provided through workshops in the UK, Africa and Asia and this work will also be promoted through stands at UK and international meetings. The longer term objective is to change global conservation practice so that the decisions effecting biodiversity are routinely based upon the scientific literature. The expectation is that we can build upon the work and experience of this project to expand it to incorporate all the major aspect of conservation in collaboration with a wide range of other organisation so that the use of evidence in decision making becomes standard practice This proposal would allow us to make a substantial step forward in achieving our objective of reforming global conservation practice.

Traditional chemical risk assessment relies on undertaking laboratory ecotoxicity studies, but can only assume what the population or ecosystem functioning consequences might be. We aim to move beyond these current limitations by interrogating wildlife population data (terrestrial, freshwater and marine) in the context of chemical exposure in a way that will progress the field. Our high-level aim is to identify which populations and environments are doing well under the current chemical regime and which are not. This will allow the UK to focus its research where the greatest wildlife declines are occurring and bring clarity to the issue of chemical risk in the environment that continues to cause great uncertainty. Only a few studies have exploited Britain's long-term wildlife population data with regards to the influence of chemical exposure. Chemical exposures we will examine will include pesticides in the terrestrial and freshwater environments, the chemical mixture in sewage effluent, metals and persistent organic pollutants. We will be looking at macroinvertebrates and fishes in our rivers, invertebrates and sparrowhawks on land and cetaceans (dolphins and killer whales) off our coasts. These environments and species represent current concerns across the natural environment for both diffuse and point source pollution. We will focus on species and taxa that are either core providers of ES or represent aspects of native biodiversity identified by the public as important to societal wellbeing. There are many stressors and compensating factors other than chemicals that can influence wildlife populations. We will incorporate such factors into our analyses to assess their role and significance and thus also address the research question: How important are chemical stressors in relation to other pressures in the environment? By comparing long-term and spatially explicit trends in natural populations, with the response predicted by classical ecotoxicity as reported in the literature, we will evaluate whether such tests are indicative of impacts in the wild. This is essential to assess to what extent traditional risk assessments, typical of those used in the Water Framework and similar Directives, are predictive of outcomes for wildlife populations in terrestrial, freshwater or marine environments.

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.

The wind energy sector is an industry of strategic national importance, which can help secure our energy supplies, reduce our emissions and dependence on imported fossil fuels, and protect our environment. It is an industry on which our clean energy future rests. Despite the positive benefits of wind farms however, there is concern and uncertainty over the possible negative effects wind turbines may have on the environment, particularly on birds. For example, uncertainty remains over collision mortality i.e. the number of birds killed directly through collision with wind turbines. These uncertainties are far from trivial for the industry and have real consequences, potentially delaying wind farm projects and inhibiting the ability of the UK to meet its binding 2020 targets. Three projects in Round 2 of wind farm developments in the UK were delayed by over three years due in part to uncertainties over the assessment of impacts. Therefore better quantification of the uncertainty and variability associated with the estimation of impacts is required. During Environmental Impact Assessments of wind farm developments, bird collision mortality is estimated using a mathematical model which describes the interaction of a bird with a wind turbine and predicts the risks of bird collisions with turbines. There are a limited number of collision risk models in use, not only in the UK but globally. However, it is recognised by many, including industry, statutory nature conservation agencies and academics that there is much room for improvement of these models. For example, collision risk models are deterministic and rarely include variation in the input parameters such as bird density, or bird biometrics which are inherently variable, but instead use average values. Additionally, any uncertainty in these values is not expressed. Adopting a single best value for parameters may reduce complexity and increase the accessibility of results for decision-makers however it can be misleading because it ignores the range of consequences that are plausible. This project aims to i) review current models that are used to predict bird collision mortality caused by wind farm developments, ii) determine statistical methods suited to address any shortcomings of current models and then, using this information, iii) develop an updated model which incorporates variability and uncertainty. Reviewing current models and highlighting their strengths and weaknesses, as well as reviewing methods to incorporate variability and uncertainty will aid the development of a product, a collision risk model, which is fit for purpose. Development of the understanding of uncertainty in the outputs of collision risk models will be a key part of this project, and will be of direct benefit to industry, government advisors and regulators in the assessment and licensing processes for wind farm projects. The involvement of these parties will be vital in steering this project because any revision of a collision risk model has to function to better inform planning decisions for wind farm developments. To ensure that all relevant parties are involved, contribute and ultimately buy-in to the development of a new, updated model, there will be a workshop to discuss issues surrounding current practices to which developers, licensing authorities, statutory nature conservation bodies, academics and others will be invited. Also, to ensure the outputs of this project have impact and are used by the industry, the model and any documents produced will be made freely available and accessible through a dedicated webpage. Wind energy has an important role in meeting energy targets, so there is a clear need to ensure that decisions made through the planning processes use the best available information, data and models. Improved understanding of the risks of collision to birds - a key effect considered in ornithological impact assessments of wind farms - is thus vital.