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Environmental factors, including greenhouse gas (GHG) emissions and soil organic carbon (SOC), should be considered when building a sustainable biofuel supply chain. This work developed a three-step optimization approach integrating a geographical information system-based mixed-integer linear programming model to economically optimize the biofuel supply chain on the premise of meeting certain GHG emission criteria. The biomass supply grid cell was considered first, based on a maximum level of GHG emissions, prior to economic optimization. The optimization simultaneously considered dual-feedstock sourcing, selection between distributed and centralized configurations, and the impact of maintaining SOC balance in agricultural soil on biomass availability. The applicability of the modeling approach was demonstrated through a case study that optimized a dual-feedstock renewable jet fuel supply chain via a gasification-Fischer–Tropsch (gasification-FT) conversion pathway in 2050 under three biomass availability scenarios. The case study results show that the differences in procurement costs and GHG emissions between energy crops and agricultural residues have a large impact on the layout of the supply chain. The supply-chain configuration tends to be more centralized with large-scale biorefineries when a supply region has an intensive and centralized distribution of biomass resources. The cost-supply curves demonstrated the technical potential of biofuels that could be obtained at a certain level of cost. Additionally, sensitivity analysis shows that the GHG emission credit from producing extra electricity during the gasification-FT process will be significantly reduced with a rising share of renewable electricity generation in the future.

Partial shading is widely considered to be a limiting factor in the performance of photovoltaic (PV) systems applied in urban environments. Modern system architectures combined with per module deployment of power electronics have been used to improve performance especially at heterogeneous irradiance conditions. In this work another approach is used to combine modern system architecture with alternate module designs. The granularity of cell groups in PV modules is investigated together with the so-called Tessera concept, in which single cells are cut in 16 parts. Typical meteorological year yield calculations show that these alternate module designs in combination with modern system architectures can retrieve up to half the shading losses compared to standard modules and string inverters under identical shading conditions.

For successful conservation of biodiversity, it is vital to know whether protected areas in increasingly fragmented landscapes effectively safeguard species. However, how large habitat fragments must be, and what level of protection is required to sustain species, remains poorly known. We compiled a global dataset on almost 2000 bird species in 741 forest fragments varying in size and protection status, and show that protection is associated with higher bird occurrence, especially for threatened species. Protection becomes increasingly effective with increasing size of forest fragments. For forest fragments >50 ha our results show that strict protection (International Union for Conservation of Nature [IUCN] categories I-IV) is strongly associated with higher bird occurrence, whereas fragments had to be at least 175 ha for moderate protection (IUCN categories V and VI) to have a positive effect. This meta-analysis quantifies the importance of fragment size, protection status, and their interaction for the conservation of bird species communities, and stresses that protection should not be limited to large pristine areas., Frontiers in Ecology and the Environment, 20 (6), ISSN:1540-9295, ISSN:1540-9309

The present study focuses on the Belgian Milk Sheep in Flanders (Belgium) and compares its genetic diversity and relationship with the Flemish Sheep, the Friesian Milk Sheep, the French Lacaune dairy sheep and other Northern European breeds. For this study, 94 Belgian Milk Sheep, 23 Flemish Sheep and 22 Friesian Milk Sheep were genotyped with the OvineSNP50 array. In addition, 29 unregistered animals phenotypically similar to Belgian Milk Sheep were genotyped using the 15K ISGC chip. Both Belgian and Friesian Milk Sheep as well as the East Friesian Sheep were found to be less diverse than the other seven breeds included in this study. Genomic inbreeding coefficients based on runs of homozygosity (ROH) were estimated at 14.5, 12.4 and 10.2% for Belgian Milk Sheep, Flemish Sheep and Friesian Milk Sheep respectively. Out of 29 unregistered Belgian Milk Sheep, 28 mapped in the registered Belgian Milk Sheep population. Ancestry analysis, PCA and FST calculations showed that Belgian Milk Sheep are more related to Friesian Milk Sheep than to Flemish Sheep, which was contrary to the breeders' expectations. Consequently, breeders may prefer to crossbreed Belgian Milk Sheep with Friesian sheep populations (Friesian Milk Sheep or East Friesian Sheep) in order to increase diversity. This research underlines the usefulness of SNP chip genotyping and ROH analyses for monitoring genetic diversity and studying genetic links in small livestock populations, profiting from internationally available genotypes. As assessment of genetic diversity is vital for long-term breed survival, these results will aid flockbooks to preserve genetic diversity. ispartof: ANIMAL GENETICS vol:51 issue:2 pages:258-265 ispartof: location:England status: published

To decarbonize the European Union, protein consumption must transition to diets low in meat and dairy which will drastically change the material and energy flows in current meat and dairy supply chains. To understand the impacts on current flows, a baseline is required. Although recent studies have improved the scope of reported greenhouse gas (GHG) emissions, no quantitative overview exists including intermediate and final product flows. To address this knowledge gap, we structured the meat and dairy supply chains into a connected set of transformation nodes and distribution nodes. The former are processes transforming inputs into outputs, whereas the latter distribute the outputs to other processes using them as inputs. Currently, livestock play a central role in agriculture and other industries through the consumption of 271 Mt fodder crops, 108 Mt grain, 85 Mt grazed biomass, 49 Mt oil meal, and 16 Mt feed by-products. This feed is transformed into 64 Mt dairy and 35 Mt meat which ensures that the EU28 is a net exporter of meat and dairy while providing 25 Mt of by-products. This production also leads to 435 Mt CO2-eq. with the main contribution from beef cattle (35%), dairy cattle (32%), and swine (20%). Thus, the lower GHG intensities of dairy products compared to meat do not imply a low contribution to the total emissions. By mapping the material, energy, and GHG emission flows, we have created a baseline suitable for identifying potential supply chain changes and their related GHG increase or decrease resulting from the protein transition.

The climate impact of bioenergy is commonly quantified in terms of CO2 equivalents, using a fixed 100‐year global warming potential as an equivalency metric. This method has been criticized for the inability to appropriately address emissions timing and the focus on a single impact metric, which may lead to inaccurate or incomplete quantification of the climate impact of bioenergy production. In this study, we introduce Dynamic Relative Climate Impact (DRCI) curves, a novel approach to visualize and quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category (e.g., emissions, radiative forcing, and temperature change), equivalency metric, and analytical time horizon. The DRCI curves constructed for fourteen bioenergy systems illustrate how value judgments affect the merit order of bioenergy systems, because they alter the importance of one‐time (associated with land use change emissions) versus sustained (associated with carbon debt or foregone sequestration) emission fluxes and short‐ versus long‐lived climate forcers. Best practices for bioenergy production (irrespective of value judgments) include high feedstock yields, high conversion efficiencies, and the application of carbon capture and storage. Furthermore, this study provides examples of production contexts in which the risk of land use change emissions, carbon debt, or foregone sequestration can be mitigated. For example, the risk of indirect land use change emissions can be mitigated by accompanying bioenergy production with increasing agricultural yields. Moreover, production contexts in which the counterfactual scenario yields immediate or additional climate impacts can provide significant climate benefits. This paper is accompanied by an Excel‐based calculation tool to reproduce the calculation steps outlined in this paper and construct DRCI curves for bioenergy systems of choice. EIT Climate-KIC, Grant/Award Number: APSP0002; US Federal Aviation Administration, Office of Environment and Energy, Grant/Award Number: FAA Award Number 13-C-AJFE-MIT

Background The ‘placebo effect’ and ‘nocebo effect’ are phenomena whereby beneficial (placebo) or adverse (nocebo) effects result from the expectation that an inert substance will relieve or cause a particular symptom. These terms are often inappropriately applied to effects experienced on drug therapy. Quantifying the magnitude of placebo and nocebo effects in clinical trials is problematic because it requires a ‘no treatment’ arm. To overcome the difficulties associated with measuring the nocebo effect, and the fact that its definition refers to inert compounds, rather than drugs, we introduce the concept of ‘drucebo’ (a combination of DRUg and plaCEBO or noCEBO) to relate to beneficial or adverse effects of a drug, which result from expectation and are not pharmacologically caused by the drug. As an initial application of the concept, we have estimated the contribution of the drucebo effect to statin discontinuation and statin‐induced muscle symptoms by performing a systematic review of randomized controlled trial of statin therapy. Methods This preferred reporting items for systematic reviews and meta‐analysis‐compliant systematic review was prospectively registered in PROSPERO (CRD42017082700). We searched PubMed and Cochrane Central from inception until 3 January 2018 using a search strategy designed to detect studies including the concepts (Statins AND Placebo AND muscle pain). We included studies that allowed us to quantify the drucebo effect for adverse muscle symptoms of statins by (i) comparing reported rates of muscle symptoms in blinded and unblinded phases of randomized controlled trials and (ii) comparing rates of muscle symptoms at baseline and during blinded therapy in trials that included patients with objectively confirmed statin intolerance at baseline. Extraction was performed by two researchers with disagreements settled by a third reviewer. Results Five studies allowed the estimation of the drucebo effect. All trials demonstrated an excess of side effects under open‐label conditions. The contribution of the drucebo effect to statin‐associated muscle pain ranged between 38% and 78%. The heterogeneity of study methods, outcomes, and reporting did not allow for quantitative synthesis (meta‐analysis) of the results. Conclusions The drucebo effect may be useful in evaluating the safety and efficacy of medicines. Diagnosis of the drucebo effect in patients presenting with statin intolerance will allow restoration of life‐prolonging lipid‐lowering therapy. Our study was limited by heterogeneity of included studies and lack of access to individual patient data. Further studies are necessary to better understand risk factors for and clinical management of the drucebo effect.

The export of wood pellets from the southeastern United States (USA) has grown significantly in recent years, following rising demand from Europe. Increased wood pellet demand could lead to spatially variable changes in timberland management and area in the USA. This study presents an assessment of the impacts of increasing wood pellet demand (an additional 11.6 Mt by 2030) on land-use dynamics, taking into account developments in other wood product markets as well as expected changes in other land uses. An economic model for the forest sector of the southeastern USA (SRTS) was linked to a land-use change model (PLUC) to identify potential locations of land-use change following scenarios of demand for pellets and other wood products. Projections show that in the absence of additional demand for wood pellets, natural timberland area is projected to decline by 450-15 000 km(2) by 2030, mainly through urbanization and pine plantation establishment. Under the high wood pellet demand scenario, more (2000-7500 km(2)) natural timberland area is retained and more (8000-20 000 km(2)) pine plantation is established. Shifts from natural timberland to pine plantation occur predominantly in the Atlantic coastal region. Future work will assess the impact of projected transitions in natural timberland and pine plantations on biodiversity and carbon storage. This modeling framework can be applied for multiple scenarios and land-use projections to identify locations of timberland area changes for the whole southeastern USA, thereby informing the debate about potential impacts of wood pellet demand on land-use dynamics and environmental services. (c) 2017 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

The widespread production of cash crops can result in the decline of forests, peatlands, rice fields and local community land. Such unwanted land-use and land-cover (LULC) change can lead to decreased carbon stocks, diminished biodiversity, displaced communities and reduced local food production. In this study, we analysed to what extent four main commodities, namely, palm oil, pulpwood, rice and rubber, can be produced in North and East Kalimantan in Indonesia without such unwanted LULC change. We investigated the technical potential of four measures to mitigate unwanted LULC change between 2008 and 2020 under low, medium and high scenarios, referring to the intensities of the mitigation measures compared with those implemented in 2008. These measures are related to land sparing through (i) the improvements of yields, (ii) chain efficiencies, (iii) chain integration and (iv) the steering of any expansion of these commodities to suitable and available underutilised (potentially degraded) lands. Our analyses resulted in a land-sparing potential of 0.4–1.2 Mha (i.e. 24–62% of the total land demand of the commodities) between 2008 and 2020, depending on the land-use projection of the four commodities and the scenario for implementing the mitigation measures. Additional expansion on underutilised land is the most important mitigation measure (45–62% of the total potential), followed by yield improvements as the second most important mitigation measure (32–46% of the total potential). Our study shows that reconciling the production of palm oil, pulpwood, rice and rubber with the maintenance of existing agricultural lands, forests and peatlands is technically possible only (i) under a scenario of limited agricultural expansion, (ii) if responsible land zoning is applied and enforced and (iii) if the yields and chain efficiencies are strongly improved.

BACKGROUND: Several pre-clinical studies have identified the anti-proliferative effects of 25-hydroxyvitamin D (25(OH) D; vitamin D). Ultraviolet radiation (UVR) is essential for vitamin D synthesis yet increases the risk of melanoma. Observational studies on the association of vitamin D levels with melanoma risk have reported inconclusive results, and are difficult to interpret due to the potential confounding from the dual role of UVR. OBJECTIVES: Our objective was to determine whether there is a causal association between genetically predicted 25(OH) D concentrations and melanoma using a Mendelian randomization (MR) approach. METHODS: We performed MR using summary data from a large genome-wide association study (GWAS) meta-analysis of melanoma risk, consisting of 12,874 cases and 23,203 controls. Five SNPs that are associated with 25(OH) D concentration rs12785878, rs10741657, rs2282679, rs6013897 and rs116970203 were selected as instrumental variables (IVs). Inverse variance weighted method was used to access the evidence for causality. MR results from the melanoma meta-analysis were combined with results from an MR study based on a melanoma risk GWAS using UK Biobank data. RESULTS: A 20 nmol/L decrease in 25(OH) D was not associated with melanoma risk (OR = 1.06, 95% CI = 0.94 - 1.19). Results from the UK Biobank were concordant with this, with meta-analysis of our and UK Biobank derived MR causal estimates showing no association (OR = 1.02, 95% CI = 0.92 - 1.13 for a 20nmol/L decrease). CONCLUSIONS: Our study results suggest that the genetically vitamin D levels may not be causally associated with the risk of melanoma. This article is protected by copyright. All rights reserved.

Subgroup by treatment interaction assessments are routinely performed when analysing clinical trials and are particularly important for phase 3 trials where the results may affect regulatory labelling. Interpretation of such interactions is particularly difficult, as on one hand the subgroup finding can be due to chance, but equally such analyses are known to have a low chance of detecting differential treatment effects across subgroup levels, so may overlook important differences in therapeutic efficacy. EMA have therefore issued draft guidance on the use of subgroup analyses in this setting. Although this guidance provided clear proposals on the importance of pre‐specification of likely subgroup effects and how to use this when interpreting trial results, it is less clear which analysis methods would be reasonable, and how to interpret apparent subgroup effects in terms of whether further evaluation or action is necessary.\ud \ud A PSI/EFSPI Working Group has therefore been investigating a focused set of analysis approaches to assess treatment effect heterogeneity across subgroups in confirmatory clinical trials that take account of the number of subgroups explored and also investigating the ability of each method to detect such subgroup heterogeneity. This evaluation has shown that the plotting of standardised effects, bias‐adjusted bootstrapping method and SIDES method all perform more favourably than traditional approaches such as investigating all subgroup‐by‐treatment interactions individually or applying a global test of interaction. Therefore, these approaches should be considered to aid interpretation and provide context for observed results from subgroup analyses conducted for phase 3 clinical trials.

By-products of agricultural and forestry processes, known as residues, may act as a primary source of renewable energy. Studies assessing the availability of this resource so far offer few insights on the drivers and constraints of the available potential, the associated costs and how the availability may vary across scenarios. This study projects long-term global supply curves of the available potential by using consistent scenarios of agriculture and forestry production, livestock production and fuel use from a spatially explicit integrated assessment model. Particular attention is paid to the drivers and constraints. In the projections residue production is related to agricultural and forestry production and intensification, and the limiting effect of ecological and alternative uses of residues are accounted for. Depending on the scenario, theoretical potential is projected to increase from approximately 120 EJ/yr today to 140-170 EJ/yr by 2100, coming mostly from agricultural production. In order to maintain ecological functions approximately 40% is required to remain in the field, and a further 20-30% is diverted towards alternative uses. Of the remaining potential (approximately 50 EJ/yr in 2100), more than 90%, is available at less than 10$2005/GJ. Crop yield improvements increase residue productivity, albeit at a lower rate. The consequent decrease in agricultural land results in a lower requirement of residues for erosion control. The theoretical potential is most sensitive to baseline projections of agriculture and forestry demand; however this does not necessarily affect the available potential which is relatively constant across scenarios. The most important limiting factors are the alternative uses. Asia and North America account for two thirds of the available potential due to the production of crops with high residue yields and socioeconomic conditions which limit alternative uses.

It is commonly recognized that large uncertainties exist in modelled biofuel-induced indirect land-use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land-use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic - land-use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land-use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell-based (5 × 5 km2) probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land-use change, such as greenhouse gas emissions.

Melanoma is the deadliest form of skin cancer, mainly affecting populations of European ancestry. Some observational studies suggest that particular diets reduce melanoma risk, putatively through an increase in polyunsaturated fatty acid (PUFA) consumption. However, interpretation of these observational findings is difficult due to residual confounding or reverse causality. To date, a randomized controlled trial has not been carried out to examine the relationship between PUFAs and melanoma. Hence, we performed a Mendelian randomisation (MR) study to evaluate the link between PUFAs and melanoma. To perform MR, we used summary results from the largest risk genome‐wide association study (GWAS) meta‐analysis of melanoma, consisting of 12,874 cases and 23,203 controls. As instrumental variables we selected SNPs associated with PUFA levels from a GWAS meta‐analysis of PUFA levels, from the CHARGE consortium. We used the inverse variance weighted method to estimate a causal odds ratio. To aid interpretation, we established a benchmark “large” predicted change in PUFAs in which, for example, an increase in docosahexaenoic acid (DPA) of 0.17 units (equal to 1 standard deviation) moves a person from the 17th percentile to the median. Raising PUFA levels by a large amount (increasing DPA by 0.17 units) only negligibly changed melanoma risk: odds ratio [OR] = 1.03 (95% confidence interval [CI] = 0.96–1.10). Other PUFAs yielded similar results as DPA. Our MR analysis suggests that the effect of PUFA levels on melanoma risk is either zero or very small.

The use of biomass as feedstock for energy is often associated with increased claims on land, competition with food production and impacts on other ecosystem services. Studies on sustainability aspects of bioenergy production often indicate biodiversity as a key concern. This article presents a first comprehensive review of published impacts of bioenergy crop production on biodiversity, evaluates the drivers and pressures of biodiversity change and summarizes current trends and impacts. The review provides insight into the types of biodiversity indicators applied under a range of conditions and the mitigating measures proposed to minimize negative impacts or realize biodiversity benefits. The 53 selected publications give diverse results that are explained by the various spatial scales, production systems and regions, time horizons, methodologies and biodiversity indicators used. Reported impacts depend on initial land use and are mostly negative, especially in tropical regions. The impacts of second generation bioenergy crops tend to be less negative than first generation ones, and are in some cases positive (at the field level), in particular in temperate regions. Land-use change appears as the key driver of biodiversity change, whereas the associated habitat loss, alterations in species richness and abundance are the main impacts addressed. Such changes are often paired with the (initiation of a) process of biological homogenization. The article confirms that concerns about the expansion of bioenergy crop production not only relate to the direct effects on biodiversity by replacing natural vegetation, but increasingly to indirect effects as well. These effects have, however, shown to be difficult to quantify. At the same time, the land sparing vs. land sharing debate receives growing attention, whereas little evidence exists in bioenergy literature on the impacts of large-scale application of these strategies on (agro)biodiversity. Following the findings of the review, the article finally provides recommendations for future research.