Oceanic islands (i.e. islands that have never been connected to a continent) are natural laboratories of evolutionary and biogeographic processes and key to understanding these in continental settings. Seen traditionally as migratory dead ends, it is now thought that these islands may instead represent 'dynamic refugia' and 'migratory stepping stones' for species that are effective dispersers, such as spore-producing plants (mosses, liverworts, hornworts, ferns and lycopods collectively known as cryptogams). Thus, cryptogams are the key terrestrial plants for understanding the biogeography of oceanic islands; they are primary colonists and hence are sentinel organisms for tracking ecological successions and soil development and, unlike many flowering plants, they have almost all arrived naturally by wind-borne propagules rather than as human introductions. The oceanic South Atlantic Islands include Ascension, St. Helena and Tristan da Cunha (all British Overseas Territories) and the Brazilian counterparts, Fernando de Noronha and Trindade. We are putting together a team of UK and Brazilian scientists who already have considerable experience of working on some of these islands to conduct the first comprehensive study of their cryptogamic diversity and biogeography. This work will enable the drawing up of biodiversity action plans, conservation strategies and lead to the recognition of the islands as key locations for monitoring and understanding the effects of climate change. Our research programme will include extensive field work, which coupled with thorough taxonomic analyses, will lead to the first comprehensive assessment of species richness and diversity of both Brazilian and British South Atlantic Oceanic Islands. Major outputs will be authoritative species checklists for the five islands; an illustrated Flora for Fernando de Noronha like those already published for St. Helena and Ascension Island; popular articles to increase public awareness; taxonomic revisions and articles on island biogeography in peer-reviewed journals. These outputs will provide essential baseline data that will: 1) highlight and publicize the importance of the cryptogamic flora to visitors of the islands; 2) allow for better informed and targeted conservation efforts- e.g. Fernando de Noronha is a UNESCO designated World Heritage Site; 3) provide key reference works for long-term monitoring of the effects of climate change and anthropogenic impacts on the biodiversity of the islands ; 4) form the basis for joint research programmes and funding applications by UK and Brazilian partners on island biogeography embracing the origins of the floras, their evolution, endemism and reproductive biology. Embedded in these activities is a major training programme for early career Brazilian scientists and conservation personnel through workshops and fieldwork. This will enable a new generation of Brazilian scientists to carry out independent, state-of-the-art cryptogamic research.

Hundreds of millions of people live close to, and depend upon, the world's large rivers for water, food, transport and the maintenance of a thriving ecosystem. However, these rivers are increasingly vulnerable to the effects of a wide range of natural and human-induced disturbances, including climate change, construction of large dams, river engineering works, deforestation, agricultural intensification, and mining activity. Over the past 20 years, climate change and deforestation have impacted on the hydrology and sediment fluxes within the Amazon River Basin. However, the Amazon has remained one of the few large river systems that has been largely unaffected by dams. This situation is changing rapidly, because widespread hydropower dam construction in Brazil, Bolivia, Peru and Ecuador now threatens the basin, with >300 dams planned or under construction. These dams are expected to trigger severe hydro-physical and ecological disturbances throughout the basin, including massive reductions in sediment and nutrient delivery to the lowland Amazon and its floodplains, substantial degradation of river beds and banks, significant changes in river water levels and flooding, and adverse impacts on river and floodplain ecosystems, on which the human population depends. Recent high profile studies highlight the need for international action to assess and mitigate these impacts, both in the Amazon and elsewhere. However, our capacity to do this is severely restricted by an absence of quantitative models that can predict how environmental disturbances propagate through large rivers and floodplains, over continental distances, and decadal to centennial time periods. Critically, environmental disturbances driven by dams, climate and land cover change promote dynamic river responses (e.g., changes in river width, depth, slope, sediment size, degree of branching and rate of floodplain reworking), which in turn control changes in flood conveyance and downstream sediment delivery. Despite advances in modelling of river dynamics over short distances (<100 km), hydrological models that are applied to continental-scale drainage basins treat rivers and floodplains as static conduits. Consequently, such models are unable to represent or predict the future impacts of environmental change on flooding, sediment fluxes or river and floodplain functioning. This project will deliver a step-change in our ability to model, predict and understand how the world's large rivers are impacted by, and respond to, environmental change. We will achieve this by implementing a research strategy that involves six elements: First, we will develop a new multi-scale numerical modelling approach that enables the effects of river dynamics on environmental disturbance propagation through continental-scale drainage basins to be simulated. Second, we will develop a suite of environmental scenarios representing climate and land cover changes and dam construction throughout the Amazon Basin for the recent past (1985-2015) and future (up to 2200). Third, we will collect new field datasets at sites on the Amazon River that are required to test key components of the model. Fourth, we will work with an international team of project partners to assemble high-resolution field, satellite and model datasets that quantify channel and floodplain processes, and river morphology and dynamics throughout the Amazon Basin. Fifth, we will use these data to carry out rigorous testing of our new model. Sixth, we will apply the model to predict the future evolution of the Amazon River and its tributaries for a wide range of environmental change scenarios, and quantify the controls on hydro-geomorphic disturbance propagation within large drainage basins. We will work with our project partners to disseminate our model code, datasets and project outcomes to non-academic stakeholders, both nationally and internationally.

Threats to the integrity of biodiverse Amazon floodplain habitats from deforestation, dams, and climate change are increasingly severe but to date, Amazon biodiversity scenarios have not considered these critical environments. Building on decades of floodplain-focused research in the Amazon by consortium members, we will improve characterization of Amazonian whitewater floodplain habitats and inundation dynamics, allowing us to 1) scale up existing fish, floodplain forest, and phytoplankton biodiversity datasets, 2) evaluate the potential impacts of regional drivers such as climate, land use change, and dams on floodplain habitats, and 3) engage at local and regional scale a large panel of stakeholders in looking for sustainable strategies for wetlands preservation. The scenarios produced at both scales will be compared in terms of wetlands conservation and biodiversity descriptors including Essential Biodiversity Variables and Sustainable Development Goals indicators. Our study framework focusing on the floodplains of the mainstem Amazon river (Brazil and Colombia) and Juruá river (Brazil) allows comparison between whitewater floodplain sites contrasting greatly in terms of floodplain geomorphology, land use and management history, commercial fishing pressure, and human population density. Innovative aspects of our work include 1) testing a remote-sensing-based approach for mapping phytoplankton biodiversity in floodplain lakes; 2) use of new satellite data to greatly increase the spatiotemporal resolution of floodplain habitat and inundation maps; 3) use of environmental eDNA metabarcoding to examine the distribution and relative abundance of phytoplankton, zooplankton, and fish in floodplain lakes; 4) individual-based modeling of Lévy-flight fish foraging patterns across a network of oxbow lakes; and 5) nested-scale agent-based participatory models to develop scenarios. The proposed work will greatly expand available information for decision-making to support the vast biodiversity and extensive ecosystem services provided by Amazon whitewater floodplains.