Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6 % of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanket-bog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland, Wales and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre-Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland, and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Southern Ocean isopycnal mixing and ventilation changes driven by winds

Observed and predicted changes in the strength of the westerly winds blowing over the Southern Ocean have motivated a number of studies of the response of the Antarctic Circumpolar Current and Southern Ocean Meridional Overturning Circulation (MOC) to wind perturbations and led to the discovery of the``eddy-compensation" regime, wherein the MOC becomes insensitive to wind changes. In addition to the MOC, tracer transport also depends on mixing processes. Here we show, in a high-resolution process model, that isopycnal mixing by mesoscale eddies is strongly dependent on the wind strength. This dependence can be explained by mixing-length theory and is driven by increases in eddy kinetic energy; the mixing length does not change strongly in our simulation. Simulation of a passive ventilation tracer (analogous to CFCs or anthropogenic CO$_2$) demonstrates that variations in tracer uptake across experiments are dominated by changes in isopycnal mixing, rather than changes in the MOC. We argue that, to properly understand tracer uptake under different wind-forcing scenarios, the sensitivity of isopycnal mixing to winds must be accounted for.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6% of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanketbog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts that large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland,Wales, and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre- Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

abctools: an R package for tuning approximate Bayesian computation analyses

Approximate Bayesian computation (ABC) is a popular family of algorithms which perform approximate parameter inference when numerical evaluation of the likelihood function is not possible but data can be simulated from the model. They return a sample of parameter values which produce simulations close to the observed dataset. A standard approach is to reduce the simulated and observed datasets to vectors of summary statistics and accept when the difference between these is below a specified threshold. ABC can also be adapted to perform model choice. In this article, we present a new software package for R, abctools which provides methods for tuning ABC algorithms. This includes recent dimension reduction algorithms to tune the choice of summary statistics, and coverage methods to tune the choice of threshold. We provide several illustrations of these routines on applications taken from the ABC literature.

MOLES3: implementing an ISO standards driven data catalogue

ISO19156 Observations and Measurements (O&M) provides a standardised framework for organising information about the collection of information about the environment. Here we describe the implementation of a specialisation of O&M for environmental data, the Metadata Objects for Linking Environmental Sciences (MOLES3). MOLES3 provides support for organising information about data, and for user navigation around data holdings. The implementation described here, “CEDA-MOLES”, also supports data management functions for the Centre for Environmental Data Archival, CEDA. The previous iteration of MOLES (MOLES2) saw active use over five years, being replaced by CEDA-MOLES in late 2014. During that period important lessons were learnt both about the information needed, as well as how to design and maintain the necessary information systems. In this paper we review the problems encountered in MOLES2; how and why CEDA-MOLES was developed and engineered; the migration of information holdings from MOLES2 to CEDA-MOLES; and, finally, provide an early assessment of MOLES3 (as implemented in CEDA-MOLES) and its limitations. Key drivers for the MOLES3 development included the necessity for improved data provenance, for further structured information to support ISO19115 discovery metadata export (for EU INSPIRE compliance), and to provide appropriate fixed landing pages for Digital Object Identifiers (DOIs) in the presence of evolving datasets. Key lessons learned included the importance of minimising information structure in free text fields, and the necessity to support as much agility in the information infrastructure as possible without compromising on maintainability both by those using the systems internally and externally (e.g. citing in to the information infrastructure), and those responsible for the systems themselves. The migration itself needed to ensure continuity of service and traceability of archived assets.

Calcium Flux in Neuroblastoma Cells Is a Coupling Mechanism between Non-Genomic and Genomic Modes of Estrogens

Estrogens have been demonstrated to rapidly modulate calcium levels in a variety of cell types. However, the significance of estrogen-mediated calcium flux in neuronal cells is largely unknown. The relative importance of intra- and extracellular sources of calcium in estrogenic effects on neurons is also not well understood. Previously, we have demonstrated that membrane-limited estrogens, such as E-BSA given before an administration of a 2-hour pulse of 17beta-estradiol (E(2)), can potentiate the transcription mediated by E(2) from a consensus estrogen response element (ERE)-driven reporter gene. Inhibitors to signal transduction cascades given along with E-BSA or E(2) demonstrated that calcium flux is important for E-BSA-mediated potentiation of transcription in a transiently transfected neuroblastoma cell line. In this report, we have used inhibitors to different voltage-gated calcium channels (VGCCs) and to intracellular store receptors along with E-BSA in the first pulse or with E(2) in the second pulse to investigate the relative importance of these channels to estrogen-mediated transcription. Neither L- nor P-type VGCCs seem to play a role in estrogen action in these cells; while N-type VGCCs are important in both the non-genomic and genomic modes of estrogen action. Specific inhibitors also showed that the ryanodine receptor and the inositol trisphosphate receptor are important to E-BSA-mediated transcriptional potentiation. This report provides evidence that while intracellular stores of calcium are required to couple non-genomic actions of estrogen initiated at the membrane to transcription in the nucleus, extracellular sources of calcium are also important in both non-genomic and genomic actions of estrogens. Copyright (c) 2005 S. Karger AG, Basel.

Membrane-initiated non-genomic signaling by estrogens in the hypothalamus: cross-talk with glucocorticoids with implications for behavior

The estrogen receptor and glucocorticoid receptor are members of the nuclear receptor superfamily that can signal using both non-genomic and genomic transcriptional modes. Though genomic modes of signaling have been well characterized and several behaviors attributed to this signaling mechanism, the physiological significance of non-genomic modes of signaling has not been well understood. This has partly been due to the controversy regarding the identity of the membrane ER (mER) or membrane GR (mGR) that may mediate rapid, non-genomic signaling and the downstream signaling cascades that may result as a consequence of steroid ligands binding the mER or the mGR. Both estrogens and glucocorticoids exert a number of actions on the hypothalamus, including feedback. This review focuses on the various candidates for the mER or mGR in the hypothalamus and the contribution of non-genomic signaling to classical hypothalamically driven behaviors and changes in neuronal morphology. It also attempts to categorize some of the possible functions of non-genomic signaling at both the cellular level and at the organismal level that are relevant for behavior, including some behaviors that are regulated by both estrogens and glucocorticoids in a potentially synergistic manner. Lastly, it attempts to show that steroid signaling via non-genomic modes may provide the organism with rapid behavioral responses to stimuli.

Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce

Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

Dynamical trust and reputation computation model for B2C E-Commerce

Trust is one of the most important factors that influence the successful application of network service environments, such as e-commerce, wireless sensor networks, and online social networks. Computation models associated with trust and reputation have been paid special attention in both computer societies and service science in recent years. In this paper, a dynamical computation model of reputation for B2C e-commerce is proposed. Firstly, conceptions associated with trust and reputation are introduced, and the mathematical formula of trust for B2C e-commerce is given. Then a dynamical computation model of reputation is further proposed based on the conception of trust and the relationship between trust and reputation. In the proposed model, classical varying processes of reputation of B2C e-commerce are discussed. Furthermore, the iterative trust and reputation computation models are formulated via a set of difference equations based on the closed-loop feedback mechanism. Finally, a group of numerical simulation experiments are performed to illustrate the proposed model of trust and reputation. Experimental results show that the proposed model is effective in simulating the dynamical processes of trust and reputation for B2C e-commerce.