Role of low intensity environmental disturbance in structuring the earliest (Ediacaran) macrobenthic tiered communities

Rangeomorphs were important components of Ediacaran macrobenthic ecosystems, yet their biology and ecology remain poorly constrained. They formed high-density, tiered communities that were subjected to intermittent burial events, the largest of which killed entire communities. Abundant thin event beds in the Ediacaran succession of Charnwood Forest indicate the additional, frequent impact of minor obrution events. The type surface of Charniamasoni is immediately underlain by one such lamina (a tuff) and preserves a distinctly bimodal population. It is dominated by Charnia fronds that are of smaller or comparable length to the holotype (19.4 cm), but also includes notably larger specimens (N45 cm) that would traditionally have been assigned to Charnia grandis. Multiple morphological- and morphometric parameters (length, width, spacing of primary branches) demonstrate that these are indistinguishable from the holotype of C. masoni, affirming the synonymy of the two taxa. Nevertheless, these outsized individuals are distinguished by their proportionally fewer primary branches per unit length. Taphonomic evidence indicates that they were survivors of an incumbent population, the rest of which was culled by a minor ashfall.We suggest that this temporary reduction in competition from neighbours allowed the survivors to grow larger and thereby gain access to a greater proportion of the water column. As the community recovered, their large sizewould have continued to provide themwith an advantage, divorcing them from the density-dependent competition seen in the new understory. The interlude between cohorts implies that newrecruitswere substrate-sensitive, presumably awaiting re-establishment of the biomat. Sub-lethal disturbance events thus played a significant role in structuring Ediacaran communities, and help explain the observed bed-by-bed variability. Taken as a whole, the growth trajectory of C. masoni resembles that of extant organismswith indeterminate growth programmes and no genetically-controlled upper size limit.PRW and CGK were supported by NERC grant NE/I005927/1. We thank our colleagues Mark Dean, Sue Martin, Louise Neep, Scott Renshaw and Paul Shepherd for assistance with moulding and casting; Paul Witney and Simon Harris for photography; and Henry Holbrook for drafting Figs. 1 and 2. We gratefully acknowledge the help in facilitating site access given by Natural England, the Mistaken Point Ecological Reserve (Parks and Natural Areas Division, Government of Newfoundland and Labrador) and landowners in Charnwood Forest. We enjoyed useful discussions with Alex Liu and Helen Boynton, and Mark Woods, Guy Harrington, Lidya Tarhan and two anonymous referees are thanked for their constructive comments on the manuscript.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0031018215001649

Homogenisation and analysis of an expanded long-term monthly rainfall network for the Island of Ireland (1850-2010)

Long-term precipitation series are critical for understanding emerging changes to the hydrological cycle. To this end we construct a homogenised Island of Ireland Precipitation (IIP) network comprising 25 stations and a composite series covering the period 1850-2010, providing the second- longest regional precipitation archive in the British-Irish Isles. We expand the existing catalogue of long-term precipitation records for the island by recovering archived data for an additional eight stations. Following bridging and updating of stations HOMER homogenisation software is used to detect breaks using pairwise and joint detection. Twenty-five breakpoints are detected across 14 stations, and the majority (20) are corroborated by metadata. Assessment of variability and change in homogenised and extended precipitation records reveal positive (winter) and negative (summer) trends. Trends in records covering the typical period of digitisation (1941 onwards) are not always representative of longer records. Furthermore, trends in post-homogenisation series change magnitude and even direction at some stations. While cautionary flags are raised for some series, confidence in the derived network is high given attention paid to metadata, coherence of behaviour across the network and consistency of findings with other long-term climatic series such as England and Wales precipitation. As far as we are aware, this work represents the first application of HOMER to a long- term precipitation network and bodes well for use in other regions. It is expected that the homogenised IIP network will find wider utility in benchmarking and supporting climate services across the Island of Ireland, a sentinel location in the North Atlantic

An evaluation of persistent meteorological drought using a homogeneous Island of Ireland precipitation network

This paper investigates the spatial and temporal properties of persistent meteorological droughts using the homogeneous Island of Ireland Precipitation (IIP) network. Relative to a 1961-1990 baseline period it is shown that the longest observed run of below average precipitation since the 1850s lasted up to 5 years (10 half-year seasons) at sites in southeast and east Ireland, or 3 years across the network as a whole. Dry- and wet-spell length distributions were represented by a first-order Markov model which yields realistic runs of below average rainfall for individual sites and IIP series. This model shows that there is relatively high likelihood (p=0.125) of a 5 year dry-spell at Dublin, and that near unbroken dry runs of 10 years or more are conceivable. We suggest that the IIP network and attendant rainfall deficit modelling provide credible data for stress testing water supply and drought plans under extreme conditions

Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods

Understanding hydrological model predictive capabilities under contrasting climate conditions enables more robust decision making. Using Differential Split Sample Testing (DSST) we analyse the performance of six hydrological models for 37 Irish catchments under climate conditions unlike those used for model training. Additionally, we consider four ensemble averaging techniques when examining inter-period transferability. DSST is conducted using two/three-year non-continuous blocks of (i) the wettest/driest years on record based on precipitation totals, and (ii) years with a more/less pronounced seasonal precipitation regime. Model transferability between contrasting regimes was found to vary depending on the testing scenario, catchment and evaluation criteria considered. As expected, the ensemble average outperformed most individual ensemble members. However, averaging techniques differed considerably in the number of times they surpassed the best individual model-member. Bayesian Model Averaging (BMA) and the Granger-Ramanathan (GRA) method were found to outperform the simple arithmetic mean (SAM) and Akaike Information Criteria Averaging (AICA). Here, GRA performed better than the best individual model in 51% to 86% of cases (according to the Nash-Sutcliffe criterion). When assessing model predictive skill under climate change conditions we recommend (i) setting up DSST to select the best available analogues of expected annual mean and seasonal climate conditions; (ii) applying multiple performance criteria; (iii) testing transferability using a diverse set of catchments and; (iv) using a multi-model ensemble in conjunction with an appropriate averaging technique. Given the computational efficiency and performance of GRA relative to BMA, the former is recommended as the preferred ensemble averaging technique for climate assessment

Reconstruction of Lamb weather type series back to the eighteenth century

The Lamb weather type series is a subjective catalogue of daily atmospheric patterns and flow directions over the British Isles, covering the period 1861–1996. Based on synoptic maps, meteorologists have empirically classified surface pressure patterns over this area, which is a key area for the progression of Atlantic storm tracks towards Europe. We apply this classification to a set of daily pressure series from a few stations from western Europe, in order to reconstruct and to extend this daily weather type series back to 1781. We describe a statistical framework which provides, for each day, the weather types consistent enough with the observed pressure pattern, and their respective probability. Overall, this technique can correctly reconstruct almost 75% of the Lamb daily types, when simplified to the seven main weather types. The weather type series are described and compared to the original series for the winter season only. Since the low frequency variability of synoptic conditions is directly related to the North Atlantic Oscillation (NAO), we derive from the weather type series an NAO index for winter. An interesting feature is a larger multidecadal variability during the nineteenth century than during the twentieth century

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2°C, followed by stabilisation to 4°C

Adaptation responses to climate change differ between global megacities

Urban areas are increasingly at risk from climate change, with negative impacts predicted for human health, the economy and ecosystems1, 2. These risks require responses from cities to improve their resilience. Policymakers need to understand current adaptation spend to plan comprehensively and effectively. Through the measurement of spend in the newly defined ‘adaptation economy’, we analyse current climate change adaptation efforts in ten megacities. In all cases, the adaptation economy remains a small part of the overall economy, representing a maximum of 0.33% of a city’s gross domestic product (here referred to as GDPc). Differences in total spend are significant between cities in developed, emerging and developing countries, ranging from £15 million to £1,600 million. Comparing key subsectors, we demonstrate the differences in adaptation profiles. Developing cities have higher proportional spend on health and agriculture, whereas developed cities have higher spend on energy and water. Spend per capita and percentage of GDPc comparisons more clearly show disparities between cities. Developing country cities spend half the proportion of GDPc and significantly less per capita, suggesting that adaptation spend is driven by wealth rather than the number of vulnerable people. This indicates that current adaptation activities are insufficient in major population centres in developing and emerging economies

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR

Assessing variations of extreme indices inducing weather-hazards on critical infrastructures over Europe?the INTACT framework

Extreme weather events are projected to be more frequent and severe across the globe because of global warming. This poses challenging problems for critical infrastructures, which could be dramatically affected (or disrupted), and may require adaptation plans to the changing climate conditions. The INTACT FP7-European project evaluated the resilience and vulnerability of critical infrastructures to extreme weather events in a climate change scenario. To identify changes in the hazard induced by climate change, appropriate extreme weather indicators (EWIs), as proxies of the main atmospheric features triggering events with high impact on the infrastructures, were defined for a number of case studies and different approaches were analyzed to obtain local climate projections. We considered the influence of weighting and bias correction schemes on the delta approach followed to obtain the resulting projections, considering data from the Euro-CORDEX ensemble of regional future climate scenarios over Europe. The aim is to provide practitioners, decision-makers, and administrators with appropriate methods to obtain actionable and plausible results on local/regional future climate scenarios. Our results show a small sensitivity to the weighting approach and a large sensitivity to bias correcting the future projections.This work has been carried out within the activities of INTACT project, receiving funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° FP7-SEC-2013-1-606799. The information and views set out in this paper are those of the authors and do not necessarily reflect the opinion of the European Union. We acknowledge the World Climate Research Programme's Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5