Guidelines for stakeholder engagement in systematic reviews of environmental management

Abstract: People have a stake in conservation and environmental management both for their own interests and the sake of the environment itself. Environmental decision-making has changed somewhat in recent decades to account for unintentional impacts on human wellbeing. The involvement of stakeholders in environmental projects has been recognised as critical for ensuring their success and equally for the syntheses of evidence of what works, where, and for whom, providing key benefits and challenges. As a result of increased interest in systematic reviews of complex management issues, there is a need for guidance in best practices for stakeholder engagement. Here, we propose a framework for stakeholder engagement in systematic reviews/systematic maps, highlighting recommendations and advice that are critical for effective, efficient and meaningful engagement of stakeholders. The discussion herein aims to provide a toolbox of stakeholder engagement activities, whilst also recommending approaches from stakeholder engagement research that may prove to be particularly useful for systematic reviews and systematic maps

The response of the northern hemisphere storm tracks and jet streams to climate change in the CMIP3, CMIP5, and CMIP6 climate models

The representation of the northern hemisphere (NH) storm tracks and jet streams and their response to climate change has been evaluated in climate model simulations from phases 3, 5 and 6 of the Couple Model Intercomparison Project (CMIP3, CMIP5 and CMIP6, respectively). The spatial patterns of the multi‐model biases in CMIP3, CMIP5, and CMIP6 are similar, however the magnitudes of the biases in the CMIP6 models are substantially lower. For instance, the multi‐model mean RMSE of the North Atlantic storm track for the CMIP6 models (as measured by time‐filtered sea‐level pressure variance) is over 50% smaller than that of the CMIP3 models in both winter and summer, and over 40% smaller for the North Pacific. The magnitude of the jet stream biases are also reduced in CMIP6, but by a lesser extent. Despite this improved representation of the current climate, the spatial patterns of the climate change response of the NH storm tracks and jet streams remain similar in the CMIP3, CMIP5, and CMIP6 models. The SSP2‐4.5 scenario responses in the CMIP6 models are substantially larger than in the RCP4.5 CMIP5 models, which is consistent with the larger climate sensitivities of the CMIP6 models compared to CMIP5

Detection and localization of multiple rate changes in Poisson spike trains

Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. In statistical spike train analysis, stochastic point process models usually assume stationarity, in particular that the underlying spike train shows a constant firing rate (e.g. [1]). However, such models can lead to misinterpretation of the associated tests if the assumption of rate stationarity is not met (e.g. [2]). Therefore, the analysis of nonstationary data requires that rate changes can be located as precisely as possible. However, present statistical methods focus on rejecting the null hypothesis of stationarity without explicitly locating the change point(s) (e.g. [3]). We propose a test for stationarity of a given spike train that can also be used to estimate the change points in the firing rate. Assuming a Poisson process with piecewise constant firing rate, we propose a Step-Filter-Test (SFT) which can work simultaneously in different time scales, accounting for the high variety of firing patterns in experimental spike trains. Formally, we compare the numbers N1=N1(t,h) and N2=N2(t,h) of spikes in the time intervals (t-h,t] and (h,t+h]. By varying t within a fine time lattice and simultaneously varying the interval length h, we obtain a multivariate statistic D(h,t):=(N1-N2)/V(N1+N2), for which we prove asymptotic multivariate normality under homogeneity. From this a practical, graphical device to spot changes of the firing rate is constructed. Our graphical representation of D(h,t) (Figure 1A) visualizes the changes in the firing rate. For the statistical test, a threshold K is chosen such that under homogeneity, |D(h,t)|<K holds for all investigated h and t with probability 0.95. This threshold can indicate potential change points in order to estimate the inhomogeneous rate profile (Figure 1B). The SFT is applied to a sample data set of spontaneous single unit activity recorded from the substantia nigra of anesthetized mice. In this data set, multiple rate changes are identified which agree closely with visual inspection. In contrast to approaches choosing one fixed kernel width [4], our method has advantages in the flexibility of h

The use of cystatin C to inhibit epithelial–mesenchymal transition and morphological transformation stimulated by transforming growth factor-β

INTRODUCTION: Transforming growth factor-β (TGF-β) is a potent suppressor of mammary epithelial cell (MEC) proliferation and is thus an inhibitor of mammary tumor formation. Malignant MECs typically evolve resistance to TGF-β-mediated growth arrest, enhancing their proliferation, invasion, and metastasis when stimulated by TGF-β. Recent findings suggest that therapeutics designed to antagonize TGF-β signaling may alleviate breast cancer progression, thereby improving the prognosis and treatment of breast cancer patients. We identified the cysteine protease inhibitor cystatin C (CystC) as a novel TGF-β type II receptor antagonist that inhibits TGF-β binding and signaling in normal and cancer cells. We hypothesized that the oncogenic activities of TGF-β, particularly its stimulation of mammary epithelial–mesenchymal transition (EMT), can be prevented by CystC. METHOD: Retroviral infection was used to constitutively express CystC or a CystC mutant impaired in its ability to inhibit cathepsin protease activity (namely Δ14CystC) in murine NMuMG MECs and in normal rat kidney (NRK) fibroblasts. The effect of recombinant CystC administration or CystC expression on TGF-β stimulation of NMuMG cell EMT in vitro was determined with immunofluorescence to monitor rearrangements of actin cytoskeletal architecture and E-cadherin expression. Soft-agar growth assays were performed to determine the effectiveness of CystC in preventing TGF-β stimulation of morphological transformation and anchorage-independent growth in NRK fibroblasts. Matrigel invasion assays were performed to determine the ability of CystC to inhibit NMuMG and NRK motility stimulated by TGF-β. RESULTS: CystC and Δ14CystC both inhibited NMuMG cell EMT and invasion stimulated by TGF-β by preventing actin cytoskeletal rearrangements and E-cadherin downregulation. Moreover, both CystC molecules completely antagonized TGF-β-mediated morphological transformation and anchorage-independent growth of NRK cells, and inhibited their invasion through synthetic basement membranes. Both CystC and Δ14CystC also inhibited TGF-β signaling in two tumorigenic human breast cancer cell lines. CONCLUSION: Our findings show that TGF-β stimulation of initiating metastatic events, including decreased cell polarization, reduced cell–cell contact, and elevated cell invasion and migration, are prevented by CystC treatment. Our findings also suggest that the future development of CystC or its peptide mimetics hold the potential to improve the therapeutic response of human breast cancers regulated by TGF-β

Tropical cyclone characteristics associated with extreme precipitation in the northern Philippines

The Philippines is exposed to Tropical Cyclones (TCs) throughout the year due to its location in the western North Pacific. While these TCs provide much-needed precipitation for the country’s hydrological cycle, extreme precipitation from TCs may also cause damaging hazards such as floods and landslides. This study examines the relationship between TC extreme precipitation and TC characteristics, including movement speed, intensity, and season, for westward-moving TCs crossing Luzon, northern Philippines. We measure extreme precipitation by the Weighted Precipitation Exceedance (WPE), calculated against a 95th percentile threshold, which considers both the magnitude and spatial extent of TC-related extreme precipitation. WPE has a significant, moderate positive relationship with TC intensity with a non-significant, weak negative relationship with movement speed. When TCs are classified by intensity one day before landfall (or pre-landfall), Typhoons (1-minute maximum sustained wind speed > 64 knots) tend to yield higher WPE than Non-Typhoons ( 11.38 knots). However, the relationship between pre-landfall TC intensity and WPE is more pronounced during June-September while there is no significant difference between the WPE of the Southwest Monsoon (June-September) and Northeast Monsoon (October-December) seasons. These results suggest that it is important to consider the pre-landfall cyclone movement speed, intensity, and season to anticipate extreme precipitation of incoming TCs. A decision table considering these factors is devised to aid in TC extreme precipitation forecasting

High resolution global climate modelling; the UPSCALE project, a large simulation campaign

The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphere only global climate simulations over the period 1985–2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a timeslice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions

Ferromagnetic Semiconductors: Moving Beyond (Ga,Mn)As

The recent development of MBE techniques for growth of III-V ferromagnetic semiconductors has created materials with exceptional promise in spintronics, i.e. electronics that exploit carrier spin polarization. Among the most carefully studied of these materials is (Ga,Mn)As, in which meticulous optimization of growth techniques has led to reproducible materials properties and ferromagnetic transition temperatures well above 150 K. We review progress in the understanding of this particular material and efforts to address ferromagnetic semiconductors as a class. We then discuss proposals for how these materials might find applications in spintronics. Finally, we propose criteria that can be used to judge the potential utility of newly discovered ferromagnetic semiconductors, and we suggest guidelines that may be helpful in shaping the search for the ideal material.Comment: 37 pages, 4 figure

Euro-Atlantic weather regimes in the PRIMAVERA coupled climate simulations: impact of resolution and mean state biases on model performance

Recently, much attention has been devoted to better understand the internal modes of variability of the climate system. This is particularly important in mid-latitude regions like the North-Atlantic, which is characterized by a large natural variability and is intrinsically difficult to predict. A suitable framework for studying the modes of variability of the atmospheric circulation is to look for recurrent patterns, commonly referred to as Weather Regimes. Each regime is characterized by a specific large-scale atmospheric circulation pattern, thus influencing regional weather and extremes over Europe. The focus of the present paper is the study of the Euro-Atlantic wintertime Weather Regimes in the climate models participating to the PRIMAVERA project. We analyse here the set of coupled historical simulations (hist-1950), which have been performed both at standard and increased resolution, following the HighresMIP protocol. The models’ performance in reproducing the observed Weather Regimes is assessed in terms of different metrics, focussing on systematic biases and on the impact of resolution. We also analyse the connection of the Weather Regimes with the Jet Stream latitude and blocking frequency over the North-Atlantic sector. We find that—for most models—the regime patterns are better represented in the higher resolution version, for all regimes but the NAO-. On the other side, no clear impact of resolution is seen on the regime frequency of occurrence and persistence. Also, for most models, the regimes tend to be more tightly clustered in the increased resolution simulations, more closely resembling the observed ones. However, the horizontal resolution is not the only factor determining the model performance, and we find some evidence that biases in the SSTs and mean geopotential field might also play a role