Showing papers by "Cooperative Research Centre published in 2016"
TL;DR: Overall, the biggest agricultural producers (China and the United States) could experience the greatest absolute cost from further species invasions, however, developing countries, in particular, Sub-Saharan African countries, appear most vulnerable in relative terms.
Abstract: Invasive species present significant threats to global agriculture, although how the magnitude and distribution of the threats vary between countries and regions remains unclear. Here, we present an analysis of almost 1,300 known invasive insect pests and pathogens, calculating the total potential cost of these species invading each of 124 countries of the world, as well as determining which countries present the greatest threat to the rest of the world given their trading partners and incumbent pool of invasive species. We find that countries vary in terms of potential threat from invasive species and also their role as potential sources, with apparently similar countries sometimes varying markedly depending on specifics of agricultural commodities and trade patterns. Overall, the biggest agricultural producers (China and the United States) could experience the greatest absolute cost from further species invasions. However, developing countries, in particular, Sub-Saharan African countries, appear most vulnerable in relative terms. Furthermore, China and the United States represent the greatest potential sources of invasive species for the rest of the world. The analysis reveals considerable scope for ongoing redistribution of known invasive pests and highlights the need for international cooperation to slow their spread.
519 citations
University of East Anglia1, Bjerknes Centre for Climate Research2, Geophysical Institute, University of Bergen3, University of Paris4, University of Exeter5, Leibniz Institute of Marine Sciences6, Earth System Research Laboratory7, University of Colorado Boulder8, Columbia University9, Cooperative Research Centre10, Hobart Corporation11, Atlantic Oceanographic and Meteorological Laboratory12, University of Miami13, University of Southampton14, Federal University of Pernambuco15, State Oceanic Administration16, University of Gothenburg17, University of Alaska Fairbanks18, Norwegian Polar Institute19, University of Perpignan20, Council of Scientific and Industrial Research21, Commonwealth Scientific and Industrial Research Organisation22, University of Hawaii at Manoa23, Alfred Wegener Institute for Polar and Marine Research24, University of New Hampshire25, Institut de recherche pour le développement26, Plymouth Marine Laboratory27, Oak Ridge National Laboratory28, University of the Aegean29, Max Planck Society30, Japan Agency for Marine-Earth Science and Technology31, United States Geological Survey32, Japan Meteorological Agency33, Leibniz Association34, World Meteorological Organization35, National University of Ireland, Galway36
TL;DR: This ESSD "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection.
Abstract: . The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770 . The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID .
408 citations
University of Arizona1, University of Washington2, University of Dayton3, California Institute of Technology4, Nagoya University5, Scott Polar Research Institute6, ETH Zurich7, Marshall Space Flight Center8, International Centre for Integrated Mountain Development9, NASA Headquarters10, Mountain Institute11, United States Geological Survey12, Tribhuvan University13, University of Victoria14, California State University, Long Beach15, Utrecht University16, Chinese Academy of Sciences17, University of Oslo18, Goddard Space Flight Center19, Nanjing University20, University of Texas at Austin21, Nanjing Normal University22, Texas A&M University23, University of Colorado Boulder24, Kathmandu25, Wadia Institute of Himalayan Geology26, MacDonald, Dettwiler and Associates27, University of California, Santa Barbara28, Hunan University of Science and Technology29, Kansas State University30, Steward Health Care System31, Northwest Normal University32, University of California, Davis33, Cooperative Research Centre34
TL;DR: Satellite imaging isolated hazard potential for earthquake-triggered landslides after the 2015 Gorkha earthquake in Nepal and provided information to relief and recovery officials as emergency operations were occurring, while supported by one of the largest-ever NASA-led campaigns of responsive satellite data acquisitions over a vast disaster zone.
Abstract: The Gorkha earthquake (M 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9,000 and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision makers. We mapped 4,312 co-seismic and post-seismic landslides. We also surveyed 491 glacier lakes for earthquake damage, but found only 9 landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.
338 citations
TL;DR: By ensuring that the specific aim of the intervention, the scale of the desired biophysical effect and an awareness of a range of impacts guide the choice of tree species, location and density of tree placement, street trees can be an important tool for urban planners and designers in developing resilient and resourceful cities in an era of climatic change.
Abstract: Urban tree planting initiatives are being actively promoted as a planning tool to enable urban areas to adapt to and mitigate against climate change, enhance urban sustainability and improve human health and well-being. However, opportunities for creating new areas of green space within cities are often limited and tree planting initiatives may be constrained to kerbside locations. At this scale, the net impact of trees on human health and the local environment is less clear, and generalised approaches for evaluating their impact are not well developed.In this review, we use an urban ecosystems services framework to evaluate the direct, and locally-generated, ecosystems services and disservices provided by street trees. We focus our review on the services of major importance to human health and well-being which include 'climate regulation', 'air quality regulation' and 'aesthetics and cultural services'. These are themes that are commonly used to justify new street tree or street tree retention initiatives. We argue that current scientific understanding of the impact of street trees on human health and the urban environment has been limited by predominantly regional-scale reductionist approaches which consider vegetation generally and/or single out individual services or impacts without considering the wider synergistic impacts of street trees on urban ecosystems. This can lead planners and policymakers towards decision making based on single parameter optimisation strategies which may be problematic when a single intervention offers different outcomes and has multiple effects and potential trade-offs in different places.We suggest that a holistic approach is required to evaluate the services and disservices provided by street trees at different scales. We provide information to guide decision makers and planners in their attempts to evaluate the value of vegetation in their local setting. We show that by ensuring that the specific aim of the intervention, the scale of the desired biophysical effect and an awareness of a range of impacts guide the choice of i) tree species, ii) location and iii) density of tree placement, street trees can be an important tool for urban planners and designers in developing resilient and resourceful cities in an era of climatic change.
334 citations
TL;DR: It is argued that future GS applications will increasingly turn toward abGS, where accuracy is obtained from across-breed reference populations and high-density GS methods that focus on causative genomic regions.
Abstract: • Traditional marker-assisted selection (MAS) did not result in a widespread use of DNA information in animal breeding. The main reason was that the traits of interest in livestock production were much more complex than expected: they were determined by thousands of genes with small effects on phenotype. These effects were usually too small to be statistically significant and so were ignored. • Genomic selection (GS) assumes that all markers might be linked to a gene affecting the trait and concentrates on estimating their effect rather than testing its significance. Three technological breakthroughs resulted in the current wide-spread use of DNA information in animal breeding: the development of the genomic selection technology, the discovery of massive numbers of genetic markers (single nucleotide polymorphisms; SNPs), and high-throughput technology to genotype animals for (hundreds of) thousands of SNPs in a cost-effective manner. • Here we review current methods for GS, including how they deal with practical data, where genotypes are missing on a large scale. The use of whole-genome sequence data is anticipated, and its advantages and disadvantages are depicted. Current and predicted future impacts of GS on dairy and beef cattle, pigs, and poultry breeding are described. Finally, future directions for GS are discussed. • It is anticipated that future GS applications will either be: within breed (wbGS), where accuracy is obtained by maintaining huge withinbreed reference populations; or across breed (abGS) where accuracy is obtained from across-breed reference populations and high-density GS methods that focus on causative genomic regions. We argue that future GS applications will increasingly turn toward abGS.
307 citations
TL;DR: A balanced overview of the advantages and disadvantages of the pyrolysis process of biochar production, end-product quality and the benefits versus drawbacks ofBiochar on soil geochemistry and albedo, microflora and fauna and nutrients.
273 citations
University of Sheffield1, University of California, San Diego2, Université catholique de Louvain3, Australian National University4, National Technological University5, University of Exeter6, Victoria University of Wellington7, University of Bordeaux8, Pierre-and-Marie-Curie University9, University of New South Wales10, Ohio University11, British Antarctic Survey12, Université Paris-Saclay13, Princeton University14, University of California, Los Angeles15, National Center for Atmospheric Research16, University of California, Irvine17, University of Washington18, Ca' Foscari University of Venice19, Cooperative Research Centre20
TL;DR: In this article, the authors analyse recent atmosphere, surface ocean and sea-ice observations in this region and assess their trends in the context of palaeoclimate records and climate model simulations.
Abstract: Understanding the causes of recent climatic trends and variability in the high-latitude Southern Hemisphere is hampered by a short instrumental record. Here, we analyse recent atmosphere, surface ocean and sea-ice observations in this region and assess their trends in the context of palaeoclimate records and climate model simulations. Over the 36-year satellite era, significant linear trends in annual mean sea-ice extent, surface temperature and sea-level pressure are superimposed on large interannual to decadal variability. Most observed trends, however, are not unusual when compared with Antarctic palaeoclimate records of the past two centuries. With the exception of the positive trend in the Southern Annular Mode, climate model simulations that include anthropogenic forcing are not compatible with the observed trends. This suggests that natural variability overwhelms the forced response in the observations, but the models may not fully represent this natural variability or may overestimate the magnitude of the forced response.
265 citations
TL;DR: The results suggest that the new BayesRC method was equal to or more powerful than BayesR for detecting candidate causal variants and for genomic prediction of milk traits.
Abstract: Dense SNP genotypes are often combined with complex trait phenotypes to map causal variants, study genetic architecture and provide genomic predictions for individuals with genotypes but no phenotype. A single method of analysis that jointly fits all genotypes in a Bayesian mixture model (BayesR) has been shown to competitively address all 3 purposes simultaneously. However, BayesR and other similar methods ignore prior biological knowledge and assume all genotypes are equally likely to affect the trait. While this assumption is reasonable for SNP array genotypes, it is less sensible if genotypes are whole-genome sequence variants which should include causal variants. We introduce a new method (BayesRC) based on BayesR that incorporates prior biological information in the analysis by defining classes of variants likely to be enriched for causal mutations. The information can be derived from a range of sources, including variant annotation, candidate gene lists and known causal variants. This information is then incorporated objectively in the analysis based on evidence of enrichment in the data. We demonstrate the increased power of BayesRC compared to BayesR using real dairy cattle genotypes with simulated phenotypes. The genotypes were imputed whole-genome sequence variants in coding regions combined with dense SNP markers. BayesRC increased the power to detect causal variants and increased the accuracy of genomic prediction. The relative improvement for genomic prediction was most apparent in validation populations that were not closely related to the reference population. We also applied BayesRC to real milk production phenotypes in dairy cattle using independent biological priors from gene expression analyses. Although current biological knowledge of which genes and variants affect milk production is still very incomplete, our results suggest that the new BayesRC method was equal to or more powerful than BayesR for detecting candidate causal variants and for genomic prediction of milk traits. BayesRC provides a novel and flexible approach to simultaneously improving the accuracy of QTL discovery and genomic prediction by taking advantage of prior biological knowledge. Approaches such as BayesRC will become increasing useful as biological knowledge accumulates regarding functional regions of the genome for a range of traits and species.
260 citations
TL;DR: In this paper, the authors summarize the research to date on observing these trends, identifying their drivers, and assessing the role of anthropogenic climate change in Antarctic sea ice cover, concluding that the expected response is small compared to the very high natural variability of the system.
203 citations
TL;DR: Jennifer L.A. Shaw, Laurence J. Clarke, Scotte D.Wedderburn, Thomas C. Barnes, Laura S. Weyrich, Alan Cooper
199 citations
TL;DR: An overview of existing knowledge on ECs, their fate and transport and a risk-based analysis for ECs management and complementary strategies are presented.
TL;DR: The Australian Natural Disaster Resilience Index (ANDRI) as discussed by the authors takes a top-down approach using indicators derived from secondary data with national coverage and is a hierarchical design based on coping and adaptive capacities representing the potential for disaster resilience.
Abstract: Assessment of disaster resilience using an index is often a key element of natural hazard management and planning. Many assessments have been undertaken worldwide. Emerging from these are a set of seven common properties that should be considered in the design of any disaster resilience assessment: assessment purpose, top-down or bottom-up assessment, assessment scale, conceptual framework, structural design, indicator selection, data analysis and index computation and reporting and interpretation. We introduce the design of an Australian Natural Disaster Resilience Index (ANDRI) according to the common properties of resilience assessment. The ANDRI takes a top-down approach using indicators derived from secondary data with national coverage. The ANDRI is a hierarchical design based on coping and adaptive capacities representing the potential for disaster resilience. Coping capacity is the means by which people or organizations use available resources, skills and opportunities to face adverse consequences that could lead to a disaster. Adaptive capacity is the arrangements and processes that enable adjustment through learning, adaptation and transformation. Coping capacity is divided into themes of social character, economic capital, infrastructure and planning, emergency services, community capital and information and engagement. Adaptive capacity is divided into themes of governance, policy and leadership and social and community engagement. Indicators are collected to determine the status of each theme. As assessments of disaster resilience develop worldwide, reporting of their design as standard practice will track knowledge generation in the field and enhance the relationship between applied disaster resilience assessment and foundational principles of disaster resilience.
TL;DR: In this paper, a review of the use of various agricultural waste materials (e.g., sugarcane bagasse, peels of various fruits, wheat straw) as biosorbents for removing arsenic from contaminated water supplies is presented.
Abstract: Arsenic (As) contamination of groundwater reservoirs is a global environmental and health issue given to its toxic and carcinogenic nature. Over 170 million people have been affected by As due to the ingestion of As-contaminated groundwater. Conventional methods such as reverse osmosis, ion exchange, and electrodialysis are commonly used for the remediation of As-contaminated water; however, the high cost and sludge production put limitations on their application to remove As from water. This review critically addresses the use of various agricultural waste materials (e.g., sugarcane bagasse, peels of various fruits, wheat straw) as biosorbents, thereby offering an eco-friendly and low-cost solution for the removal of As from contaminated water supplies. The effect of solution chemistry such as solution pH, cations, anions, organic ligands, and various other factors (e.g., temperature, contact time, sorbent dose) on As biosorption, and safe disposal methods for As-loaded biosorbents to reduce seco...
TL;DR: In this article, a non-contact optical method for strain measurement applying three-dimensional digital image correlation (3D DIC) in uniaxial compression is presented. But this method is limited to the case of sandstone.
Abstract: A non-contact optical method for strain measurement applying three-dimensional digital image correlation (3D DIC) in uniaxial compression is presented. A series of monotonic uniaxial compression tests under quasi-static loading conditions on Hawkesbury sandstone specimens were conducted. A prescribed constant lateral-strain rate to control the applied axial load in a closed-loop system allowed capturing the complete stress–strain behaviour of the rock, i.e. the pre-peak and post-peak stress–strain regimes. 3D DIC uses two digital cameras to acquire images of the undeformed and deformed shape of an object to perform image analysis and provides deformation and motion measurements. Observations showed that 3D DIC provides strains free from bedding error in contrast to strains from LVDT. Erroneous measurements due to the compliance of the compressive machine are also eliminated. Furthermore, by 3D DIC technique relatively large strains developed in the post-peak regime, in particular within localised zones, difficult to capture by bonded strain gauges, can be measured in a straight forward manner. Field of strains and eventual strain localisation in the rock surface were analysed by 3D DIC method, coupled with the respective stress levels in the rock. Field strain development in the rock samples, both in axial and shear strain domains suggested that strain localisation takes place progressively and develops at a lower rate in pre-peak regime. It is accelerated, otherwise, in post-peak regime associated with the increasing rate of strength degradation. The results show that a major failure plane, due to strain localisation, becomes noticeable only long after the peak stress took place. In addition, post-peak stress–strain behaviour was observed to be either in a form of localised strain in a shearing zone or inelastic unloading outside of the shearing zone.
TL;DR: In this paper, the authors present a data set from the International Polar Year project; Marine Mammals Exploring the Oceans Pole to Pole for southern elephant seals, in which a large number of instruments (N = 287) deployed on animals, encompassing a broad circum-Antarctic geographic extent, collected in situ ocean data and at-sea foraging metrics that explicitly link foraging behavior and habitat structure in time and space.
Abstract: In the Southern Ocean, wide-ranging predators offer the opportunity to quantify how animals respond to differences in the environment because their behavior and population trends are an integrated signal of prevailing conditions within multiple marine habitats. Southern elephant seals in particular, can provide useful insights due to their circumpolar distribution, their long and distant migrations and their performance of extended bouts of deep diving. Furthermore, across their range, elephant seal populations have very different population trends. In this study, we present a data set from the International Polar Year project; Marine Mammals Exploring the Oceans Pole to Pole for southern elephant seals, in which a large number of instruments (N = 287) deployed on animals, encompassing a broad circum-Antarctic geographic extent, collected in situ ocean data and at-sea foraging metrics that explicitly link foraging behavior and habitat structure in time and space. Broadly speaking, the seals foraged in two habitats, the relatively shallow waters of the Antarctic continental shelf and the Kerguelen Plateau and deep open water regions. Animals of both sexes were more likely to exhibit area-restricted search (ARS) behavior rather than transit in shelf habitats. While Antarctic shelf waters can be regarded as prime habitat for both sexes, female seals tend to move northwards with the advance of sea ice in the late autumn or early winter. The water masses used by the seals also influenced their behavioral mode, with female ARS behavior being most likely in modified Circumpolar Deepwater or northerly Modified Shelf Water, both of which tend to be associated with the outer reaches of the Antarctic Continental Shelf. The combined effects of (1) the differing habitat quality, (2) differing responses to encroaching ice as the winter progresses among colonies, (3) differing distances between breeding and haul-out sites and high quality habitats, and (4) differing long-term regional trends in sea ice extent can explain the differing population trends observed among elephant seal colonies.
TL;DR: A model to estimate target DNA concentration and dispersion at survey sites and to estimate the sensitivity of an eDNA survey method is presented and it is shown how these data can be used to compare sampling schemes that differ in the number of field samples collected per site and number of PCR replicates per sample to achieve ≥95% sensitivity at a given targetDNA concentration.
Abstract: Imperfect sensitivity, or imperfect detection, is a feature of all survey methods that needs to be accounted for when interpreting survey results. Detection of environmental DNA (eDNA) is increasingly being used to infer species distributions, yet the sensitivity of the technique has not been fully evaluated. Sensitivity, or the probability of detecting target DNA given it is present at a site, will depend on both the survey method and the concentration and dispersion of target DNA molecules at a site. We present a model to estimate target DNA concentration and dispersion at survey sites and to estimate the sensitivity of an eDNA survey method. We fitted this model to data from a species-specific eDNA survey for Oriental weatherloach, Misgurnus anguillicaudatus, at three sites sampled in both autumn and spring. The concentration of target DNA molecules was similar at all three sites in autumn but much higher at two sites in spring. Our analysis showed the survey method had ≥95% sensitivity at sites where target DNA concentrations were ≥11 molecules per litre. We show how these data can be used to compare sampling schemes that differ in the number of field samples collected per site and number of PCR replicates per sample to achieve ≥95% sensitivity at a given target DNA concentration. These models allow researchers to quantify the sensitivity of eDNA survey methods to optimize the probability of detecting target species, and to compare DNA concentrations spatially and temporarily.
TL;DR: This review has critically evaluated the technological profile of existing in-situ remediation approaches for priority and emerging pollutants, recent innovative technologies for on-site pollutant remediation, and current challenges as well as future prospects for developing innovative approaches to enhance the efficacy of remediation at contaminated sites.
Abstract: Though several in-situ treatment methods exist to remediate polluted sites, selecting an appropriate site-specific remediation technology is challenging and is critical for successful clean up of polluted sites. Hence, a comprehensive overview of all the available remediation technologies to date is necessary to choose the right technology for an anticipated pollutant. This review has critically evaluated the (i) technological profile of existing in-situ remediation approaches for priority and emerging pollutants, (ii) recent innovative technologies for on-site pollutant remediation, and (iii) current challenges as well as future prospects for developing innovative approaches to enhance the efficacy of remediation at contaminated sites.
TL;DR: The level of contamination and health risk assessment for arsenic (As) and other elements in drinking water, vegetables and other food components in two blocks (Mohiuddinagar and Mohanpur) from the Samastipur district, Bihar, India is investigated.
TL;DR: In this article, the authors investigated multiple stressors on a subantarctic diatom and found that temperature and iron enrichment enhanced growth and helped to overcome nutrient depletion, while considering individual and interactive effects.
Abstract: Investigation of multiple stressors on a subantarctic diatom reveals the importance of considering individual and interactive effects. Experiments show that temperature and iron enrichment enhance growth and help overcome nutrient depletion.
01 Nov 2016
TL;DR: The assembly of an updated quasi‐global dataset of higher‐frequency sea level information obtained from tide gauges operated by many agencies around the world, containing longer and more geographically representative sea level records is described.
Abstract: This paper describes the assembly of an updated quasi-global dataset of higher-frequency sea level information obtained from tide gauges operated by many agencies around the world. We believe that the construction of such a dataset is fundamental to scientific research in sea level variability and also to practical aspects of coastal engineering. A first version of the dataset was used in approximately a dozen published studies, and this second version is about twice the size, containing longer and more geographically representative sea level records. The dataset has acquired a digital object identifier and may be obtained from several sources. The paper mentions some of the merits of and deficiencies with the present version and takes a forward look at how the dataset may be updated in the future.
TL;DR: University students experience a range of unique psychosocial stressors that increase their risk of major depression and GAD, in addition to sociodemographic risk factors.
Abstract: Few studies have examined modifiable psychosocial risk factors for mental disorders among university students, and of these, none have employed measures that correspond to clinical diagnostic criteria. The aim of this study was to examine psychosocial and demographic risk factors for major depression and generalised anxiety disorder (GAD) in a sample of Australian university students. An anonymous web-based survey was distributed to undergraduate and postgraduate students at a mid-sized Australian university. A range of psychosocial and demographic risk factors were measured, and logistic regression models were used to examine significant predictors of major depression and GAD. A total of 611 students completed the survey. The prevalence of major depression and GAD in the sample was 7.9 and 17.5 %, respectively. In terms of demographic factors, the risk of depression was higher for students in their first year of undergraduate study, and the risk of GAD was higher for female students, those who moved to attend university, and students experiencing financial stress. In terms of psychosocial factors, students with experience of body image issues and lack of confidence were at significantly greater risk of major depression, and feeling too much pressure to succeed, lack of confidence, and difficulty coping with study was significantly associated with risk of GAD. University students experience a range of unique psychosocial stressors that increase their risk of major depression and GAD, in addition to sociodemographic risk factors. It is important to examine psychosocial factors, as these are potentially modifiable and could be the focus of university-specific mental health interventions.
TL;DR: Genomic best linear unbiased prediction was used to calculate GEBV for heat tolerance for milk, fat, and protein yield and some slight improvement in the accuracy of prediction was achieved when cows were included in the reference population for Holsteins.
TL;DR: Change in ocean heat flux is a plausible physical mechanism to explain past and projected changes in this sector of the East Antarctic Ice Sheet and its contribution to sea level.
Abstract: Mass loss from the West Antarctic ice shelves and glaciers has been linked to basal melt by ocean heat flux. The Totten Ice Shelf in East Antarctica, which buttresses a marine-based ice sheet with a volume equivalent to at least 3.5 m of global sea-level rise, also experiences rapid basal melt, but the role of ocean forcing was not known because of a lack of observations near the ice shelf. Observations from the Totten calving front confirm that (0.22 ± 0.07) × 106 m3 s−1 of warm water enters the cavity through a newly discovered deep channel. The ocean heat transport into the cavity is sufficient to support the large basal melt rates inferred from glaciological observations. Change in ocean heat flux is a plausible physical mechanism to explain past and projected changes in this sector of the East Antarctic Ice Sheet and its contribution to sea level.
TL;DR: This work advocates the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution, and illustrates how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits.
Abstract: Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.
TL;DR: In this article, a review brings together basic concepts of soil acidification and recent developments on the implications of liming in relation to C and N transformations and cycling, particularly GHG emissions from soils.
Abstract: Soil acidification can be accelerated by intensive farming or prevented by sustainable management practices. Soil acidification in a managed agricultural production system is caused by the transformation of carbon (C), nitrogen (N), and sulfur (S), which releases protons (H+) to soil solution. Soil acidification decreases soil pH, causing adverse effects on plants and soil microorganisms. Acidification, coupled with aluminum, manganese, and iron toxicities, and phosphorus, calcium, magnesium, and potassium deficiencies, can lead to low soil fertility. Soil acidity influences soil C and N cycles by controlling activities of microorganisms involved in the transformations of these two elements. Traditionally, lime materials are added to neutralize acidic soils and to overcome the problems associated with soil acidification, but they also influence C and N cycles, thereby affecting greenhouse gas (GHG) flux in soils. For example, liming has been shown to decrease nitrification-induced nitrous oxide (N2O) emission from many agricultural lands. However, there are concerns that liming increases the availability of soil nitrate ( N O 3 − ), which is a substrate for N2O emission through denitrification. The dissolution of liming materials can act as either a net source or sink for carbon dioxide (CO2). Lime-derived CO2 reacts with microbial respiration-derived carbonic acid in soils to yield carbonate material, serving as a sink of CO2 in soil. In calcareous soils with high pH, agricultural lime (CaCO3) serves as a net sink for CO2 whereas in acid soils it serves as a net source of CO2. In acid soils, increased availability of aluminum (Al3+) ions inhibits activity of methane (CH4) oxidizers. Adding lime to soils has shown to increase CH4 oxidation and reduce GHG emission. The present review brings together basic concepts of soil acidification and recent developments on the implications of liming in relation to C and N transformations and cycling, particularly GHG emissions from soils. Given the major influence of lime addition on soil microorganisms relating to C and N cycles, future research should focus on the role of liming on soil microbial communities to provide insight into combined mitigation of N2O, CO2, and CH4 gases from agricultural soils.
University of Western Macedonia1, University of the West2, University of Paris-Est3, Delft University of Technology4, University of Milan5, Netherlands Organisation for Applied Scientific Research6, Cooperative Research Centre7, Eötvös Loránd University8, National Institute for Health and Welfare9, University of Porto10
TL;DR: Analysis of detailed parameters revealed that “noise inside the buildings” was highly associated with occupants’ overall comfort, and “Layout of the offices’ was the next parameterhighly associated with overall comfort.
Abstract: Indoor environmental conditions (thermal, noise, light, and indoor air quality) may affect workers’ comfort, and consequently their health and well-being, as well as their productivity. This study aimed to assess the relations between perceived indoor environment and occupants’ comfort, and to examine the modifying effects of both personal and building characteristics. Within the framework of the European project OFFICAIR, a questionnaire survey was administered to 7441 workers in 167 “modern” office buildings in eight European countries (Finland, France, Greece, Hungary, Italy, The Netherlands, Portugal, and Spain). Occupants assessed indoor environmental quality (IEQ) using both crude IEQ items (satisfaction with thermal comfort, noise, light, and indoor air quality), and detailed items related to indoor environmental parameters (e.g., too hot/cold temperature, humid/dry air, noise inside/outside, natural/artificial light, odor) of their office environment. Ordinal logistic regression analyses were performed to assess the relations between perceived IEQ and occupants’ comfort. The highest association with occupants’ overall comfort was found for “noise”, followed by “air quality”, “light” and “thermal” satisfaction. Analysis of detailed parameters revealed that “noise inside the buildings” was highly associated with occupants’ overall comfort. “Layout of the offices” was the next parameter highly associated with overall comfort. The relations between IEQ and comfort differed by personal characteristics (gender, age, and the Effort Reward Imbalance index), and building characteristics (office type and building’s location). Workplace design should take into account both occupant and the building characteristics in order to provide healthier and more comfortable conditions to their occupants.
TL;DR: This review is an exploration of the ex-situ technologies for cleaning-up the contaminated soil, groundwater and air emissions, highlighting their principles, advantages, deficiencies and the knowledge gaps.
Abstract: Pollution and the global health impacts from toxic environmental pollutants are presently of great concern. At present, more than 100 million people are at risk from exposure to a plethora of toxic organic and inorganic pollutants. This review is an exploration of the ex-situ technologies for cleaning-up the contaminated soil, groundwater and air emissions, highlighting their principles, advantages, deficiencies and the knowledge gaps. Challenges and strategies for removing different types of contaminants, mainly heavy metals and priority organic pollutants, are also described.
TL;DR: New observations from CTD-instrumented elephant seals in 2011–2013 are shown that provide the first complete assessment of dense shelf water formation in Prydz Bay, highlighting the susceptibility of Antarctic bottom water to increased freshwater input from the enhanced melting of ice shelves, and ultimately the potential collapse of AntarcticBottom water formationIn a warming climate.
Abstract: A fourth production region for the globally important Antarctic bottom water has been attributed to dense shelf water formation in the Cape Darnley Polynya, adjoining Prydz Bay in East Antarctica. Here we show new observations from CTD-instrumented elephant seals in 2011–2013 that provide the first complete assessment of dense shelf water formation in Prydz Bay. After a complex evolution involving opposing contributions from three polynyas (positive) and two ice shelves (negative), dense shelf water (salinity 34.65–34.7) is exported through Prydz Channel. This provides a distinct, relatively fresh contribution to Cape Darnley bottom water. Elsewhere, dense water formation is hindered by the freshwater input from the Amery and West Ice Shelves into the Prydz Bay Gyre. This study highlights the susceptibility of Antarctic bottom water to increased freshwater input from the enhanced melting of ice shelves, and ultimately the potential collapse of Antarctic bottom water formation in a warming climate.
Potsdam Institute for Climate Impact Research1, University of Bristol2, University of Grenoble3, Centre national de la recherche scientifique4, Cooperative Research Centre5, Australian Antarctic Division6, ETH Zurich7, British Antarctic Survey8, Alfred Wegener Institute for Polar and Marine Research9, Courant Institute of Mathematical Sciences10, New York University Abu Dhabi11, Lawrence Berkeley National Laboratory12, Met Office13, Université libre de Bruxelles14, California Institute of Technology15
TL;DR: The Marine Ice Sheet Ocean Model Intercomparison Project (MISOMIP) as mentioned in this paper is a community effort aimed at designing and coordinating a series of model intercomparisons projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS).
Abstract: . Coupled ice sheet–ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of marine ice sheets and tidewater glaciers, from process studies to future projections of ice mass loss and sea level rise. The Marine Ice Sheet–Ocean Model Intercomparison Project (MISOMIP) is a community effort aimed at designing and coordinating a series of model intercomparison projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). Here we describe computational experiments constituting three interrelated MIPs for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities. These consist of ice sheet experiments under the Marine Ice Sheet MIP third phase (MISMIP+), ocean experiments under the Ice Shelf-Ocean MIP second phase (ISOMIP+) and coupled ice sheet–ocean experiments under the MISOMIP first phase (MISOMIP1). All three MIPs use a shared domain with idealized bedrock topography and forcing, allowing the coupled simulations (MISOMIP1) to be compared directly to the individual component simulations (MISMIP+ and ISOMIP+). The experiments, which have qualitative similarities to Pine Island Glacier Ice Shelf and the adjacent region of the Amundsen Sea, are designed to explore the effects of changes in ocean conditions, specifically the temperature at depth, on basal melting and ice dynamics. In future work, differences between model results will form the basis for the evaluation of the participating models.
TL;DR: This review provides an in-depth consideration of the production, characterization and agricultural use of different biochars and its characteristics vary with production conditions and the feedstock used.
Abstract: In recent years biochar has been demonstrated to be a useful amendment to sequester carbon and reduce greenhouse gas emission from the soil to the atmosphere. Hence it can help to mitigate global environment change. Some studies have shown that biochar addition to agricultural soils increases crop production. The mechanisms involved are: increased soil aeration and water-holding capacity, enhanced microbial activity and plant nutrient status in soil, and alteration of some important soil chemical properties. This review provides an in-depth consideration of the production, characterization and agricultural use of different biochars. Biochar is a complex organic material and its characteristics vary with production conditions and the feedstock used. The agronomic benefits of biochar solely depend upon the use of particular types of biochar with proper field application rate under appropriate soil types and conditions. © 2016 Society of Chemical Industry.