Effective surface albedo due to snow cover of the surrounding area

Albedo inversion techniques are investigated in this work. Several methods are applied to spectral irradiance data from a measurement campaign held in the German Alps during the spring of 1999. One first method is based on the comparison of measurements of absolute levels of UV irradiance with model calculations. The second method takes advantage of changes in the spectral slope of spectral UV irradiance, which is a function of the surface albedo. In the third method, the surrounding area is partitioned into snow-covered and snow-free regions, and the effective albedo estimated by applying a higher or lower reflectivity to each facet before integrating over the surroundings. We present sensitivity analysis, the differences and the correlations between the various methods as well as the results for the different locations

Enriching the Shared Socioeconomic Pathways to co-create consistent multi-sector scenarios for the UK

As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale

Enriching the shared socioeconomic pathways to co-create consistent multi-sector scenarios for the UK

As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale

Can we model cultural ecosystem services, and are we measuring the right things?

Abstract: Cultural ecosystem services (CES), a key aspect of nature's contributions to people, remain a challenge to incorporate into decision making. One contributing factor is the difficulty of defining and describing these, due partly to: ongoing poor understanding of what drives people to interact with nature, a lack of appropriate data to quantify these interactions, and basic difficulties in measuring and modelling the complex array of social, psychological and behavioural attributes which help explain people's actions. In this study we present a framework which develops the concepts of cultural capital, social capital and human capital as specific forms of human‐centred capital, in the context of their contribution to understanding CES. Each form of capital encompasses separate attributes of beneficiaries. Testing the framework with data from a separate trans‐disciplinary study illustrated that the framework was readily applicable to specific situations. A measure of cultural capital, EcoCentrism, explained more variation than a suite of seven demographic variables. Applying the framework also showed that despite using a wide range of explanatory variables, a large proportion of observed variation remained unaccounted for. This suggests that more work is needed to understand and to develop metrics which can measure additional factors which underlie peoples’ motivations to engage with nature. The framework is applicable to other types of ecosystem service, and may also be useful for exploring relational values. A free Plain Language Summary can be found within the Supporting Information of this article

Effects of Natura 2000 on nontarget bird and butterfly species based on citizen science data

ABSTRACT The European Union's Natura 2000 (N2000), is one of the largest international networks of protected areas. One of its aims is to secure the status of a pre-determined set of (targeted) bird and butterfly species. However, also non-target species may benefit from N2000. We evaluated how the terrestrial component of this network relates to the abundance of non-targeted, more common bird and butterfly species using data from long-term volunteer-based monitoring programs in 9,602 sites for birds and 2,001 sites for butterflies. In almost half of the 155 bird species assessed, and particularly among woodland specialists, abundance increased with the proportion of N2000 sites in the landscape. The corresponding positive relationship was found for 27 of the 104 butterfly species, although most of these species were generalists. These positive relationships disappeared for most of the species when land-cover covariates were taken into account, hinting that land-cover is a primary factor defining the positive effects of the N2000 network. The increase in abundance with N2000 was correlated with the specialization index for bird species, but not for butterfly species. Although the N2000 network supports higher abundance of a large spectrum of species, the low number of specialist butterfly species showing a positive association stresses the need to implement management plan improving the quality of habitats of N2000 areas potentially harboring openland butterfly specialists. For a better understanding of the processes involved, we advocate for a standardized collection of data on N2000 sites. Article impact statement: Across Europe the abundance of a majority of nontarget birds and a quarter of nontarget butterflies increased with Natura 2000 coverage. This article is protected by copyright. All rights reservedpeerReviewe

Binding to SMN2 pre-mRNA-protein complex elicits specificity for small molecule splicing modifiers

Small molecule splicing modifiers have been previously described that target the general splicing machinery and thus have low specificity for individual genes. Several potent molecules correcting the splicing deficit of the SMN2 (survival of motor neuron 2) gene have been identified and these molecules are moving towards a potential therapy for spinal muscular atrophy (SMA). Here by using a combination of RNA splicing, transcription, and protein chemistry techniques, we show that these molecules directly bind to two distinct sites of the SMN2 pre-mRNA, thereby stabilizing a yet unidentified ribonucleoprotein (RNP) complex that is critical to the specificity of these small molecules for SMN2 over other genes. In addition to the therapeutic potential of these molecules for treatment of SMA, our work has wide-ranging implications in understanding how small molecules can interact with specific quaternary RNA structures

Efficient occupancy model-fitting for extensive citizen-science data

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen scientists