Predictions of future climate, essential for safeguarding society and ecosystems, are underpinned by numerical models of the Earth system. These models are routinely tested against, and in many cases tuned towards, observations of the modern Earth system. However, the model predictions of the climate of the end of this century lie largely outside of this evaluation period, due to the projected future CO2 forcing being significantly greater than that seen in the observational record. Indeed, recent work reconstructing past CO2 has shown that the closest analogues to the 22nd century, in terms of CO2 concentration, are tens of millions of years ago, in 'Deep-Time'. The Palaeoclimate Modelling Intercomparison Project (PMIP) provides a framework (but no funding!) by which the palaeoclimate modelling community assesses state-of-the-art climate models relative to past climate data. Traditionally, PMIP has focussed on the relatively recent mid-Holocene (6,000 years ago) and Last Glacial Maximum (21,000 years ago), but these time periods have even lower CO2 than modern (~280 and ~180 ppmv respectively, c.f. ~400 ppmv for the modern). Recently, PMIP has expanded into other time periods, most notably the mid-Pliocene (3 million years ago), but even then, CO2 was most likely less than modern values (~380 ppmv). The modelling community would clearly benefit from an intercomparison of 'Deep-Time' climates, when CO2 levels were close to those predicted for the end of this century. We will organise and provide funding for 2 workshops, with the aim of producing papers describing the experimental design and outputs from a new climate Model Intercomparison Project - "DeepMIP", focussing on past climates in which atmospheric CO2 concentrations were similar to those projected for the end of this century. The papers will evaluate the models relative to past geological data, and aim to understand the reasons for the model-model differences and model-data (dis)agreements, providing information of relevance to the IPCC. A previous NERC grant, NE/K014757/1, is currently aiming to assess climate sensitivity (the response of surface air temperature to a doubling of atmospheric CO2), through geological time. That project is focussing on many time periods, but with only one model. This IOF will complement that project, and bring added-value, by focussing on one particular time period, but with many models. As such we will address the crucial issue of model-dependence.

Human activity has led to an increase in pCO2 and methane levels from pre-industrial times to today. While the former increase is primarily due to fossil fuel burning, the increase in methane concentrations is more complex, reflecting not only direct human activity but also feedback mechanisms in the climate system related to temperature and hydrology-induced changes in methane emissions. To unravel these complex relationships, scientists are increasingly interrogating ancient climate systems. Similarly, one of the major challenges in palaeoclimate research is understanding the role of methane biogeochemistry in governing the climate of ice-free, high-pCO2 greenhouse worlds, such as during the early Paleogene (around 50Ma). The lack of proxies for methane concentrations is problematic, as methane emissions from wetlands are governed by precipitation and temperature, such that they could act as important positive or negative feedbacks on climate. In fact, the only estimates for past methane levels (pCH4) arise from our climate-biogeochemistry simulations wherein GCMs have driven the Sheffield dynamic vegetation model, from which methane fluxes have been derived. These suggest that Paleogene pCH4 could have been almost 6x modern pre-industrial levels, and such values would have had a radiative forcing effect nearly equivalent to a doubling of pCO2, an impact that could have been particularly dramatic during time intervals when CO2 levels were already much higher than today's. Thus, an improved understanding of Paleogene pCH4 is crucial to understanding both how biogeochemical processes operate on a warmer Earth and understanding the climate of this important interval in Earth history. We propose to improve, expand and interrogate those model results using improved soil biogeochemistry algorithms, conducting model sensitivity experiments and comparing our results to proxy records for methane cycling in ancient wetlands. The former will provide a better, process-orientated understanding of biogenic trace gas emissions, particularly the emissions of CH4, NOx and N2O. The sensitivity experiments will focus on varying pCO2 levels and manipulation of atmospheric parameters that dictate cloud formation; together, these experiments will constrain the uncertainty in our trace greenhouse gas estimates. To qualitatively test these models, we will quantify lipid biomarkers and determine their carbon isotopic compositions to estimate the size of past methanogenic and methanotrophic populations, and compare them to modern mires and Holocene peat. The final component of our project will be the determination of how these elevated methane (and other trace gas) concentrations served as a positive feedback on global warming. In combination our work will test the hypothesis that elevated pCO2, continental temperatures and precipitation during the Eocene greenhouse caused increased wetland GHG emissions and atmospheric concentrations with a significant feedback on climate, missing from most modelling studies to date. This work is crucial to our understanding of greenhouse climates but such an integrated approach is not being conducted anywhere else in the world; here, it is being led by international experts in organic geochemistry, climate, vegetation and atmospheric modelling, and palaeobotany and coal petrology. It will represent a major step forward in our understanding of ancient biogeochemical cycles as well as their potential response to future global warming.

Although the largest earthquakes (e.g., 2004 Sumatra) occur where tectonic plates collide, large earthquakes (Mag. 7-8+) also occur on strike-slip faults where plates are moving horizontally past each other. Strike-slip faults such as the San Andreas or the North Anatolian Fault (Turkey) occur in highly populated areas where earthquakes can have devastating human consequences. Although faults are seismic monitored, our knowledge of why earthquakes occur remains poor. This is because we have no samples of rocks that ruptured during a modern earthquake because failure typically occurs deep in the crust (>5-10 km). Nor do we have in situ measurements of the thermal and fluids conditions that determine how materials respond to the relative motion of the plates. Ancient fault rocks do occur but these rocks are commonly altered and have unknown tectonic context. The Alpine Fault is major strike-slip fault, that runs along the western range front of the Southern Alps, New Zealand. The fault is the boundary between the Australian and Pacific plates with the Australian crust moving to the northeast at ~27 mm/year. Because plate motions are not parallel to the Alpine Fault, collision is occurring at an oblique angle. This has resulted in the recent (~5 million years) rapid (>6-8 mm/yr) uplift of the Pacific plate over the Australian plate forming the >3000 m-high Southern Alps. Rocks, that until a few million years ago where more than 25 km deep in the crust, now crop out at the surface along the fault. Importantly, rocks that as recently as a few 10s of thousands of years ago, were fracturing and deforming within the Alpine Fault zone itself, now occur at the surface. This well known tectonic geometry and one-sided uplift along a major strike-slip fault is unique, and provides an excellent natural laboratory to understand earthquake processes. It is surprising that there have been no large earthquakes on the Alpine Fault in European times. However, paleo-seismic evidence indicates a major earthquake in ~1717, and that large earthquakes occurr every 200-400 years. These quakes were very large with up to 8 m horizontal movement in each event. The Alpine Fault is late in its seismic cycle and overdue for a large, devastating earthquake. This has lead an international group of scientists to propose drilling a series of shallow and deep (~4 km) bore holes into the Alpine Fault Zone to sample the fault rocks in situ, and to install instruments (seismicity, strain, temperature, fluid pressure) to monitor a major fault during the final build up to a large earthquake. Data from the Alpine fault can be used to understand other fault zones. Before we can decide where to drill a deep hole, we need to know how hot it is at the target depth. Our proposed work will make estimates of the temperature of rocks at depth by investigating geothermal warm springs (up to 60 deg C) that occur along the Alpine Fault. These warm springs occur because rapid uplift has brought deep hot rocks near to the surface. Geologists commonly use fluids from geysers or seafloor black-smoker vents, as windows into conditions deep within the crust. The chemistry of fluids and gases emitted can tell us where the fluids come from and how they have reacted. Unfortunately, there is very little known about the Alpine Fault geothermal systems because many of the springs are in very remote locations, and the scientists didn't have access to modern techniques. From investigating fluid-rock exchange in other hydrothermal environments, we have developed new methods to understand reactions between fluids and minerals. We will match warm spring fluids to minerals that formed within the Alpine Fault zone, during different stages of the uplift of these rocks to the surface. When matches can be made, we will be know that the reactions and conditions producing modern fluids must be occurring within the Alpine Fault today.

On current trajectories, the concentration of atmospheric carbon dioxide (CO2) will exceed 550 ppm by the middle of this century. Such high carbon dioxide concentrations last occurred over 25 million years ago during the "greenhouse" climates of the early Cenozoic. In particular, the early Eocene epoch (~55 to 48 million years ago) was characterized by the warmest climates of the past 65 million years, with no ice sheets on Antarctica, polar regions ~20-40 degrees C warmer and sea levels ~50 to 70m higher than present. These warm Eocene climates can be simulated using the same climate models that are used to predict future climate change, such as those used in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (2013-14). In this report, climate model simulations of the Eocene were compared against temperature estimates from the geological record to test the accuracy of modelled warming in Polar regions at greatly increased CO2. PI Dunkley Jones was responsible for collating the Eocene temperature estimates used and figured in the IPCC AR5 report. This work is now being substantially improved ahead of the next IPCC report within a collaborative international project to run IPCC-class climate models with a consistent set of boundary conditions and Eocene geographies, as part of the "Deep-time Model-data Intercomparison Project" (DeepMIP). Significant improvements in the accuracy of the critical geological data used to test these models - Eocene surface temperatures and atmospheric CO2 concentrations - are, however, more difficult to establish. Current moderately reliable estimates of ocean surface temperatures for the early Eocene are limited to only seven locations globally, and, at high latitudes, can diverge by up to 20 degrees C depending on the proxy method used. Current estimates of early Eocene CO2 concentrations are even more uncertain, ranging from ~300 ppm to in excess of 2000 ppm. There is only one sound early Eocene data point based on the CO2 proxy methods highlighted by the IPCC as having particular promise - those based on foraminiferal boron isotopes and alkenone carbon isotope compositions. Here we aim to make a step-change improvement in these "proxy" estimates by taking advantage of two new opportunities. The first, is the serendipitous discovery of a remarkable suite of very well preserved, unaltered marine microfossils, made of calcium carbonate, alongside similarly well-preserved organic molecular biomarkers produced by Eocene marine algae and bacteria. The chemistry of this fossil material is the basis for proxy temperature and/or atmospheric CO2 estimation. The quality of this material is so high that we propose to generate ~170 alkenone-based CO2 estimates for the early Eocene, where previously there were none, and 15 boron-isotope based estimates to test the single data point currently available. The rare co-occurrence of these substrates and their abundance also provides the opportunity to use multiple independent methods to estimate both ocean temperatures (4 methods) and atmospheric CO2 (2 methods) on the same sample set, and so directly compare estimates from different methodologies at the same time and place. The second key opportunity is a new collaboration between the PI Dunkley Jones and astrophysicists with advanced expertise in data analysis, statistical modelling and signal processing. With the generation of the largest ever dataset of proxy-to-proxy comparisons from any Greenhouse climate, this new collaboration will maximise our ability to draw robust conclusions about systematic errors within any given proxy method. This is vital for the reconstruction of warm climate states where there are persistent discrepancies between temperature reconstructions based on different proxy methods. Here, we will be able to directly compare methods from the same samples and with uniformly excellent preservation.

The aim of the MARIS project is to provide a new framework for the sustainable management of risks of biological invasion. Biological invasions and their effects on ecosystem biodiversity and functioning are one of the main causes of global change. The management of invasive species depends on both the knowledge of the ecological characteristics of the target species and of the sociological contexts that control its installation, persistence, the perception and potential spread through dispersal. The MARIS project will use Ulex europaeus (L.), a ‘world invasive species’ outside its native European range, as model species. We will study it in a wide range of ecological and social conditions both in native (French Brittany and Landes of Gascogne) and invaded areas (French Reunion Island, New Zealand and the Spanish Canary Islands). The ecological part of the project will focus on three specific stagers for the control of the population dynamics: recruitment, persistence and dispersal. The climate and soil conditions which favour successful recruitment of seedlings and persistence (seed bank and resprouting) of the species will be assessed in meta-analysis, experiments (using phytotron and common garden) and field surveys. This part of the project will also address the dispersal distance enabled by different vectors (vehicles, sheep and water). The sociological part will focus on analyses of human perceptions and uses of Ulex europaeus. A mechanistic species distribution model will be coupled with existing models to simulate population dynamics at the stand scale to account for local processes at regional scale. To achieve the right balance, the uncertainty of model outputs and the complexity of the local scale model will be weighed against the gain in accuracy provided by the final hybrid model. Field surveys and experimental results as well as information collected on social uses and perception of the species will be included in the model. The global risk analysis framework will be used to combine all the results of the project. Results of the ecological experiments and of the field studies and expert knowledge will be used to define biological thresholds. Sociological field surveys will make it possible to account for the perceptions of the different actors (managers, users) in creating scales for the assessment of risk as well as for drawing up risk management plans. Economic data on the cost of the Ulex europaeus eradication programme in the literature will be used to propose a pragmatic sustainable management to control its expansion.