Holocene expansion of the Caledonian pinewoods: spatial and temporal patterns at regional and landscape scales

Background To facilitate climatic change adaptation, landscape and conservation managers require understanding of spatio-temporal patterns of expansion of potential dominant species. Studying past expansions of canopy-dominant trees can contribute such understanding. Aims Test hypotheses about expansions of dominants using as a model the mid-Holocene expansion of forests dominated by Pinus sylvestris in the Scottish Highlands. Methods Pollen analysis and radiocarbon dating of Holocene sediments of a larger basin and several small hollows were performed in three landscapes along a north–south transect. A larger basin records expansion timing at landscape scale, whilst small hollows evidence within-landscape spatio-temporal patterns. Results Vegetation existing prior to the expansion of pinewoods influenced landscape-scale spatio-temporal expansion patterns of P. sylvestris. Open vegetation generally was invaded earlier and/or to a greater extent; invasion was often later, or did not occur, where woodland with a substantial temperate broadleaved tree and shrub component (e.g. Corylus avellana, Quercus spp.) was present. Most small hollows, not just those where pinewoods became locally established, recorded vegetation change during the expansion. Some present landscape-scale forest composition patterns were established at that time. Conclusions Studying past expansions of dominants provides evidence relevant to planning conservation and landscape management to facilitate ecological adaptation as species adjust their distributions and abundances in response to climatic change

Predicting future European breeding distributions of British seabird species under climate change and unlimited/no dispersal scenarios

Understanding which traits make species vulnerable to climatic change and predicting future distributions permits conservation efforts to be focused on the most vulnerable species and the most appropriate sites. Here, we combine climate envelope models with predicted bioclimatic data from two emission scenarios leading up to 2100, to predict European breeding distributions of 23 seabird species that currently breed in the British Isles. Assuming unlimited dispersal, some species would be “winners” (increase the size of their range), but over 65% would lose range, some by up to 80%. These “losers” have a high vulnerability to low prey availability, and a northerly distribution meaning they would lack space to move into. Under the worst-case scenario of no dispersal, species are predicted to lose between 25% and 100% of their range, so dispersal ability is a key constraint on future range sizes. More globally, the results indicate, based on foraging ecology, which seabird species are likely to be most affected by climatic change. Neither of the emissions scenarios used in this study is extreme, yet they generate very different predictions for some species, illustrating that even small decreases in emissions could yield large benefits for conservation

On Bayesian Modelling of the Uncertainties in Palaeoclimate Reconstruction

We outline a model and algorithm to perform inference on the palaeoclimate and palaeoclimate volatility from pollen proxy data. We use a novel multivariate non-linear non-Gaussian state space model consisting of an observation equation linking climate to proxy data and an evolution equation driving climate change over time. The link from climate to proxy data is defined by a pre-calibrated forward model, as developed in Salter-Townshend and Haslett (2012) and Sweeney (2012). Climatic change is represented by a temporally-uncertain Normal-Inverse Gaussian Levy process, being able to capture large jumps in multivariate climate whilst remaining temporally consistent. The pre-calibrated nature of the forward model allows us to cut feedback between the observation and evolution equations and thus integrate out the state variable entirely whilst making minimal simplifying assumptions. A key part of this approach is the creation of mixtures of marginal data posteriors representing the information obtained about climate from each individual time point. Our approach allows for an extremely efficient MCMC algorithm, which we demonstrate with a pollen core from Sluggan Bog, County Antrim, Northern Ireland.Comment: 25 pages, 7 figure

Submesoscale dispersion in the vicinity of the Deepwater Horizon spill

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 meters to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. \textcolor{black} {Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200m$-$50km scales and clearly indicate that dispersion at the submesoscales is \textit{local}, driven predominantly by energetic submesoscale fluctuations.} The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.Comment: 9 pages, 6 figure

EpiCollect: Linking Smartphones to Web Applications for Epidemiology, Ecology and Community Data Collection

Epidemiologists and ecologists often collect data in the field and, on returning to their laboratory, enter their data into a database for further analysis. The recent introduction of mobile phones that utilise the open source Android operating system, and which include (among other features) both GPS and Google Maps, provide new opportunities for developing mobile phone applications, which in conjunction with web applications, allow two-way communication between field workers and their project databases.Here we describe a generic framework, consisting of mobile phone software, EpiCollect, and a web application located within www.spatialepidemiology.net. Data collected by multiple field workers can be submitted by phone, together with GPS data, to a common web database and can be displayed and analysed, along with previously collected data, using Google Maps (or Google Earth). Similarly, data from the web database can be requested and displayed on the mobile phone, again using Google Maps. Data filtering options allow the display of data submitted by the individual field workers or, for example, those data within certain values of a measured variable or a time period.Data collection frameworks utilising mobile phones with data submission to and from central databases are widely applicable and can give a field worker similar display and analysis tools on their mobile phone that they would have if viewing the data in their laboratory via the web. We demonstrate their utility for epidemiological data collection and display, and briefly discuss their application in ecological and community data collection. Furthermore, such frameworks offer great potential for recruiting 'citizen scientists' to contribute data easily to central databases through their mobile phone

Uncertainties and recommendations

An assessment of the impacts of changes in climate and UV-B radiation on Arctic terrestrial ecosystems, made within the Arctic Climate Impacts Assessment (ACIA), highlighted the profound implications of projected warming in particular for future ecosystem services, biodiversity and feedbacks to climate. However, although our current understanding of ecological processes and changes driven by climate and UV-B is strong in some geographical areas and in some disciplines, it is weak in others. Even though recently the strength of our predictions has increased dramatically with increased research effort in the Arctic and the introduction of new technologies, our current understanding is still constrained by various uncertainties. The assessment is based on a range of approaches that each have uncertainties, and on data sets that are often far from complete. Uncertainties arise from methodologies and conceptual frameworks, from unpredictable surprises, from lack of validation of models, and from the use of particular scenarios, rather than predictions, of future greenhouse gas emissions and climates. Recommendations to reduce the uncertainties are wide-ranging and relate to all disciplines within the assessment. However, a repeated theme is the critical importance of achieving an adequate spatial and long-term coverage of experiments, observations and monitoring of environmental changes and their impacts throughout the sparsely populated and remote region that is the Arctic

Effects of changes in climate on landscape and regional processes, and feedbacks to the climate system

Biological and physical processes in the Arctic system operate at various temporal and spatial scales to impact large-scale feedbacks and interactions with the earth system. There are four main potential feedback mechanisms between the impacts of climate change on the Arctic and the global climate system: albedo, greenhouse gas emissions or uptake by ecosystems, greenhouse gas emissions from methane hydrates, and increased freshwater fluxes that could affect the thermohaline circulation. All these feedbacks are controlled to some extent by changes in ecosystem distribution and character and particularly by large-scale movement of vegetation zones. Indications from a few, full annual measurements of CO2 fluxes are that currently the source areas exceed sink areas in geographical distribution. The little available information on CH4 sources indicates that emissions at the landscape level are of great importance for the total greenhouse balance of the circumpolar North. Energy and water balances of Arctic landscapes are also important feedback mechanisms in a changing climate. Increasing density and spatial expansion of vegetation will cause a lowering of the albedo and more energy to be absorbed on the ground. This effect is likely to exceed the negative feedback of increased C sequestration in greater primary productivity resulting from the displacements of areas of polar desert by tundra, and areas of tundra by forest. The degradation of permafrost has complex consequences for trace gas dynamics. In areas of discontinuous permafrost, warming, will lead to a complete loss of the permafrost. Depending on local hydrological conditions this may in turn lead to a wetting or drying of the environment with subsequent implications for greenhouse gas fluxes. Overall, the complex interactions between processes contributing to feedbacks, variability over time and space in these processes, and insufficient data have generated considerable uncertainties in estimating the net effects of climate change on terrestrial feedbacks to the climate system. This uncertainty applies to magnitude, and even direction of some of the feedbacks

Global biome patterns of the Middle and Late Pleistocene

Our primary aim was to assess the hypothesis that distinctive features of the patterns of vegetation change during successive Quaternary glacial–interglacial cycles reflect climatic differences arising from forcing differences. We addressed this hypothesis using 207 half-degree resolution global biome pattern simulations, for time slices between 800 and 2 ka, made using the LPJ-GUESS dynamic global vegetation model. Simulations were driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 206 palaeoclimate experiments; four additional simulations were driven using projected future CO2 concentrations. Climate experiments were run using HadCM3. Using a rule-based approach, above-ground biomass and leaf area index of LPJ-GUESS plant functional types were used to infer each grid cell's biome. The hypothesis is supported by the palaeobiome simulations. To enable comparisons with the climatic forcing, multivariate analyses were performed of global vegetation pattern dissimilarities between simulations. Results showed generally similar responses to glacial–interglacial climatic variations during each cycle, although no two interglacials or glacials had identical biome patterns. Atmospheric CO2 concentration was the strongest driver of the dissimilarity patterns. Dissimilarities relative to the time slice with the lowest atmospheric CO2 concentration show the log-linear relationship to atmospheric CO2 concentration expected of an index of ecocarbon sensitivity. For each simulation, extent and total above-ground biomass of each biome were calculated globally and for three longitudinal segments corresponding to the major continental regions. Mean and minimum past extents of forest biomes, notably Temperate Summergreen Forest, in the three major continental regions strongly parallel relative tree diversities, hence supporting the hypothesis that past biome extents played an important role in determining present diversity. Albeit that they reflect the climatic consequences only of the faster Earth system components, simulated potential future biome patterns are unlike any during the past 800 ky, and likely will continue to change markedly for millennia if projected CO2 concentrations are realised

Deletion of DXZ4 on the human inactive X chromosome alters higher-order genome architecture

During interphase, the inactive X chromosome (Xi) is largely transcriptionally silent and adopts an unusual 3D configuration known as the "Barr body." Despite the importance of X chromosome inactivation, little is known about this 3D conformation. We recently showed that in humans the Xi chromosome exhibits three structural features, two of which are not shared by other chromosomes. First, like the chromosomes of many species, Xi forms compartments. Second, Xi is partitioned into two huge intervals, called "superdomains," such that pairs of loci in the same superdomain tend to colocalize. The boundary between the superdomains lies near DXZ4, a macrosatellite repeat whose Xi allele extensively binds the protein CCCTC-binding factor. Third, Xi exhibits extremely large loops, up to 77 megabases long, called "superloops." DXZ4 lies at the anchor of several superloops. Here, we combine 3D mapping, microscopy, and genome editing to study the structure of Xi, focusing on the role of DXZ4 We show that superloops and superdomains are conserved across eutherian mammals. By analyzing ligation events involving three or more loci, we demonstrate that DXZ4 and other superloop anchors tend to colocate simultaneously. Finally, we show that deleting DXZ4 on Xi leads to the disappearance of superdomains and superloops, changes in compartmentalization patterns, and changes in the distribution of chromatin marks. Thus, DXZ4 is essential for proper Xi packaging.National Human Genome Research Institute (U.S.) (Grant HG003067