A landscape approach to conceptualising the relationship between humans and their environment is now recognised as crucial to understanding the complex dynamics of social-ecological systems under environmental and social change. If we are properly to predict the interactions between environmental change and human well-being in a highly dynamic system, and manage for sustainability, then these feedbacks must be properly understood, particularly if new policy interventions are to be robust to future change. The Ustiurt system provides an unusually good case study for examining these issues. A biodiversity offset scheme is in the pipeline, a prerequisite for which is an understanding of the effects of climate change on landscape dynamics and the population dynamics and movement of the flagship species; the migratory saiga antelope. There has been substantial and quantifiable environmental and social change but the system itself is relatively homogeneous; a rangeland with a single dominant wild ungulate. Projections of future change exist, and there is existing understanding of the saiga's ecology and movement patterns in relation to rangeland dynamics. The overall aim of the research is to contribute to understanding of the role of biodiversity offsetting in landscape management, in a changing world. The objectives are: - To analyse the determinants of rangeland condition over the last 30 years, linked to environmental and social changes in the region. - To use data on individual saiga spatio-temporal movement patterns to examine mechanisms by which climate warming and landscape change could influence saiga movement patterns - To develop spatially explicit models of landscape dynamics and saiga movement patterns. - To use these models to predict the effects of climate change and gas exploration on rangeland condition and saiga distribution and to explore the impacts of potential biodiversity offsets. - To analyse the uncertainties and ecological and economic trade-offs involved in biodiversity offsetting in the region, and provide policy advice to stakeholders based upon these analyses The project addresses the fundamental and globally urgent issue of the inter-relationship between humans, animal populations and their environment at a time of environmental change; and is relevant both to the Climate Systems and Biodiversity themes of NERC, as well as to the LWEC programme. It examines the effects of climate change and human activities on a migratory species, casting light on the drivers of animal movement. It also addresses the issue of biodiversity offsetting, an approach which is gaining popularity without a strong methodological basis. Intellectually, therefore, it stands at the cutting edge of biological and interdisciplinary research. This case study is a particularly stark and interesting example of the interrelationships between environmental change, species conservation and landscape management policy in the past, the near and far future. There is also an unusually high degree of stakeholder involvement from governmental and industry sectors, which will be mediated by the project partner FFI, as the leader of a major project to promote sustainable landscapes in the region. Hence this project will have the potential directly to influence both government policy and CASE partner activities in the region.

We will develop a fully integrated environmental decision support tool for tropical perennial crops and deliver a full technical specification for inclusion into the online, and freely available Cool Farm Tool. The Cool Farm Tool is owned by the Cool Farm Alliance (CFA) who will partner on this project. It is a business-led initiative to assess and improve the sustainability of agriculture-based supply chains. It is funded via a membership model, with membership consisting of over 50 companies including for example major multinationals such as Unilever, PepsiCo, Heineken, Danone, Nestle, Marks and Spencer, and Tesco. Members pay to maintain the tool and deploy at scale in their supply chains but it is a core principle of the Alliance that the tool is and will always be free-to-use for farmers. The CFT itself is a science-based decision support tool designed for use by farmers at farm scale. It has benefitted from significant NERC Discovery and Innovation funding in the past and as a result includes a growing suite of metrics for crop and livestock systems in an expanding set of geographic locations (over 100 countries). Several case studies have shown the impact that has been derived using the tool, for example PepsiCo's "50-in-5" (http://pepsico.co.uk/live/story/celebrating-sustainable-farming) and egg production in North America resulting in a 25% reduction in the carbon footprint from primary production (Vetter et al 2018). Tropical perennial crops are of huge importance to global food supply chains and typically have high dependence on smallholder farmers in DAC countries where decision-support has been hindered less scientific evidence and the focus of researchers in temperate regions. This project build on numerous previous NERC and Wellcome Trust outputs and exploits established successful relationships between the project partners to ensure delivery. We will develop modules based around the existing CFT methods to allow a one-stop shop assessment tool for carbon and water footprinting and biodiversity impacts of farm practice in tropical perennials. Through partnership with the Cool Farm Alliance and the £5.4M Wellcome Trust funded SHEFS project we will ensure delivery of a tool which has practical value to farmers and supply chains. This business-led, science-based, and farmer-focused project will thereby provide robust metrics which will allow farmers to engage and demonstrate their positive actions for sustainability into international supply chains, and the businesses to identify good practices to embed in their sustainable sourcing strategies. The possibility to combine, in a single decision support tool, the multiple impacts of farm practices is attractive for many reasons, not least being that it will reduce the current burden on farmers to conduct multiple assessments of dubious value on multiple impacts for multiple buyers.

Catastrophic disease events can be devastating for the survival of threatened species, and can reverse years of conservation effort. When populations are already small and vulnerable, due to poaching or habitat loss, disease can be the final straw. Examples of disease as a conservation issue include the Ethiopian wolf, which is susceptible to distemper and rabies from domestic dogs, and rinderpest, which decimated the wild and domestic ungulate populations of Africa in the 19th century. Recently it has been recognised that disease is best understood and tackled in a wider context than just the individual species of host and pathogen; resilient ecosystems are better able to accommodate disease outbreaks, and human-caused environmental change can make species more vulnerable. The saiga antelope is a migratory ungulate which gathers to give birth in large aggregations. It is critically endangered due to a >95% decline in population size over <10 years due to poaching for its horns and meat. However one population (Betpak-dala) has recovered well, to about 250,000 individuals in April 2015. Mass die-offs from disease occur regularly in this species, but the causes and contributing factors have never been properly investigated. In May 2015, 120,000 saigas died within a few days in the Betpak-dala population, about half this population, and >1/3 of the global population. For the first time, a rapid response team was able to attend and collect samples from the affected saigas and their environment. Initial observations suggest that the deaths were a result of a complex interaction between particular environmental conditions (wet weather, lush grass) and the weakness of females which had just given birth, causing pathogens which were present but latent within the saigas to take hold. This is not the whole story, however, which may also include toxins in plants or water, an insect-carried disease, or a directly-transmitted virus. In this project, we will analyse the already-collected samples to diagnose the causes of and contributing factors to this mass die-off. We will run an urgent mission to the field, to collect supplementary information which will help us to home in on the triggers for this disease. We will visit both affected and unaffected areas, to understand what the differences are. We will talk to local herders, and get weather records for the days leading up to the deaths. Next, we will compile everything we know about this outbreak, and about previous outbreaks (recent and historical, in saigas and similar species), to get an overall picture of the pattern of events and environmental conditions which leads to mass saiga deaths. Combining this understanding with projections of future environmental conditions (e.g. climate change) and emerging infectious diseases (e.g. peste des petits ruminants, which is entering Central Asia from Africa), we will explore scenarios of risk from a range of diseases to both saigas and livestock, and how risks could be mitigated (e.g. through vaccination or changes in land use practices). Having assembled this evidence, we will help the Government of Kazakhstan to prepare for future disease outbreaks; we will design surveillance protocols so they can have early warning of potential triggers for mortality, and help them to examine whether, and which, interventions might reduce the risk of outbreaks, or mitigate them. We will run a technical workshop at the upcoming meeting of the UN Convention on Migratory Species' Memorandum of Understanding on saiga conservation, and support signatories (governments and NGOs) to develop and ratify an action plan. This project is a unique chance to investigate a dramatic and complex disease event of huge conservation importance, which will also shed light on the relationship between environmental change and disease. This makes it of wide general interest for ecologists, and an opportunity which it is vital to take while there is still time to act.

Insects are the little things that run the world (E.O. Wilson). With increasing recognition of the importance of insects as the dominant component of almost all ecosystems, there are growing concerns that insect biodiversity has declined globally, with serious consequences for the ecosystem services on which we all depend. Major gaps in knowledge limit progress in understanding the magnitude and direction of change, and hamper the design of solutions. Information about insects trends is highly fragmented, and time-series data is restricted and unrepresentative, both between different groups of insects (e.g. lepidoptera vs beetles vs flies) and between different regions. Critically, we lack primary data from the most biodiverse parts of the world. For example, insects help sustain tropical ecosystems that play a major role in regulating the global climate system and the hydrological cycle that delivers drinking water to millions of people. To date, progress in insect monitoring has been hampered by many technical challenges. Insects are estimated to comprise around 80% of all described species, making it impossible to sample their populations in a consistent way across regions and ecosystems. Automated sensors, deep learning and computer vision offer the best practical and cost-effective solution for more standardised monitoring of insects across the globe. Inter-disciplinary research teams are needed to meet this challenge. Our project is timely to help UK researchers to develop new international partnerships and networks to underpin the development of long-term and sustainable collaborations for this exciting, yet nascent, research field that spans engineering, computing and biology. There is a pressing need for new research networks and partnerships to maximize potential to revolutionise the scope and capacity for insect monitoring worldwide. We will open up this research field through four main activities: (a) interactive, online and face-to-face engagement between academic and practitioner stakeholders, including key policy-makers, via online webinars and at focused knowledge exchange and grant-writing workshops in Canada and Europe; (b) a knowledge exchange mission between the UK and North America, to share practical experience of building and deploying sensors, develop deep learning and computer vision for insects, and to build data analysis pipelines to support research applications; (c) a proof-of-concept field trial spanning the UK, Denmark, The Netherlands, Canada, USA and Panama. Testing automated sensors against traditional approaches in a range of situation; (d) dissemination of shared learning throughout this project and wider initiatives, building a new community of practice with a shared vision for automated insect monitoring technology to meet its worldwide transformational potential. Together, these activities will make a significant contribution to the broader, long-term goal of delivering the urgent need for a practical solution to monitor insects anywhere in the world, to ultimately support a more comprehensive assessment of the patterns and consequences of insect declines, and impact of interventions. By building international partnerships and research networks we will develop sustainable collaborations to address how to quantify the complexities of insect dynamics and trends in response to multiple drivers, and evaluate the ecological and human-linked causes and consequences of the changes. Crucially, this project is a vital stepping-stone to help identify solutions for addressing the global biodiversity crisis as well as research to understand the biological impacts of climate change and to design solutions for sustainable agriculture. Effective insect monitoring underpins the evaluation of future socio-economic, land-use and climate mitigation policies.