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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Quemada, M.; Lassaletta, L.; Jensen, L.S.; Godinot, O.; +7 Authors

    peer-reviewed Nitrogen (N) indicators are key for characterizing farm performance, because of the role of N in food production and environmental sustainability. A systematic monitoring of N balance at the farm level could contribute to understanding differences in N management and impacts among farms and among regions. The objective of this study was to increase the understanding of differences in N indicators at the farm level across Europe, and to derive possible target values. Farm-level data were collected through surveys of 1240 farms from Atlantic, Continental and Mediterranean Europe, that were diverse rather tahn country representative. The data were analysed according to a common procedure, using three related indicators: N use efficiency (NUE, farm-gate ratio of N outputs to N inputs), N surplus and N output in agricultural products. Specific target values were derived for farm type (arable, dairy, pig and mixed farms) based on the statistical analysis of the data set. The effect of not accounting for N losses involved in the production of purchased feed and the end use of exported manure (externalisation) on the animal farm indicators was evaluated by recalculating inputs with adjusting factors. The results show a wide variation in NUE and N surplus, mainly related to differences in farming systems and management. Arable farms presented lower mean N input and surplus than livestock farms, and therefore had the highest median NUE. The modest targets (i.e. median of data) for arable farms were NUE 61% and N surplus 68 kg N ha−1, for dairy farms NUE 30% and N surplus 155 kg N ha−1, and for pig farms NUE 40% and N surplus 135 kg N ha−1. Externalisation had a large effect on animal farm indicators. After adjusting for externalisation, the modest target NUE for dairy farms was 19% and for pig farms 23%. Farms outside their agro-environmental optimum could approach their specific targets by increasing or reducing N inputs (intensification or extensification) or adopting additional strategies (sustainable intensification). In conclusion, N indicators were useful to compare farm performance among different farming systems and to define a characteristic operating space for a farm population, but caution should be taken when comparing livestock farms before externalisation adjustment, and consideration should be given to changes in soil N stocks. Farm system-specific targets for N indicators and linkages with the Common Agricultural Policy may create the necessary incentives to optimise NUE and reduce N losses to air and water. Spanish Ministry of Economy and Competitiveness

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    NARCIS; Research@WUR
    Article . 2020
    License: CC BY
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    Research@WUR; Agricultural Systems
    Other literature type . Article . 2020 . Peer-reviewed
    License: CC BY
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    T-Stór
    Article . 2020 . Peer-reviewed
    Data sources: T-Stór
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Richard P. Kipling; C. F. E. Topp; André Bannink; Dave J. Bartley; +20 Authors

    Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. Highlights • Modelling plays a key role in adapting agriculture to climate change. • Modellers' views and literature were analysed to identify adaptation-specific issues. • Novel challenges to modelling climate change adaptation were explored. • Challenges related to Responsibility, Scope, Optimisation, Information, Collaboration. • Adaptation to progressive climate change highlights social impacts of model use. Graphical abstract Image 1

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    Other literature type . Article . 2019
    License: CC BY NC ND
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    Article . 2019
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    Cranfield CERES
    Article . 2019
    License: CC BY NC ND
    Data sources: Cranfield CERES
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    Brage NMBU
    Article . 2019
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    Environmental Modelling & Software
    Article . 2019 . Peer-reviewed
    License: CC BY NC ND
    Data sources: Crossref; NARCIS
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    Article . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      Other literature type . Article . 2019
      License: CC BY NC ND
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      ProdInra
      Article . 2019
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      Cranfield CERES
      Article . 2019
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      Brage NMBU
      Article . 2019
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      Environmental Modelling & Software
      Article . 2019 . Peer-reviewed
      License: CC BY NC ND
      Data sources: Crossref; NARCIS
      UnissResearch
      Article . 2019
      Data sources: UnissResearch
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: van Leeuwen, J.P.; Creamer, Rachel; Cluzeau, Daniel; Debeljak, Marko; +11 Authors

    Soil biodiversity and habitat provisioning is one of the soil functions that agricultural land provides to society. This paper describes assessment of the soil biodiversity function (SB function) as a proof of concept to be used in a decision support tool for agricultural land management. The SB function is defined as ‘the multitude of soil organisms and processes, interacting in an ecosystem, providing society with a rich biodiversity source and contributing to a habitat for aboveground organisms.’ So far, no single measure provides the full overview of the soil biodiversity and how a soil supports a habitat for a biodiverse ecosystem. We have assembled a set of attributes for a proxy-indicator system, based on four ‘integrated attributes’: 1) soil nutrient status, 2) soil biological status, 3) soil structure, and 4) soil hydrological status. These attributes provide information to be used in a model for assessing the capacity of a soil to supply the SB function. A multi-criteria decision model was developed which comprises of 34 attributes providing information to quantify the four integrated attributes and subsequently assess the SB function for grassland and for cropland separately. The model predictions (in terms of low – moderate – high soil biodiversity status) were compared with expert judgements for a collection of 137 grassland soils in the Netherlands and 52 French soils, 29 grasslands and 23 croplands. For both datasets, the results show that the proposed decision model predictions were statistically significantly correlated with the expert judgements. A sensitivity analysis indicated that the soil nutrient status, defined by attributes such as pH and organic carbon content, was the most important integrated attribute in the assessment of the SB function. Further progress in the assessment of the SB function is needed. This can be achieved by better information regarding land use and farm management. In this way we may make a valuable step in our attempts to optimize the multiple soil functions in agricultural landscapes, and hence the multifaceted role of soils to deliver a bundle of ecosystem services for farmers and citizens, and support land management and policy towards a more sustainable society.

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    NARCIS; Research@WUR
    Article . 2019
    License: CC BY
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    Article . 2019
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    Frontiers in Environmental Science
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    DOAJ
    Article . 2019
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    Authors: Taru Sandén; Aneta Trajanov; Aneta Trajanov; Heide Spiegel; +6 Authors

    Agricultural soils provide society with several functions, one of which is primary productivity. This function is defined as the capacity of a soil to supply nutrients and water and to produce plant biomass for human use, providing food, feed, fiber and fuel. Up to about one quarter of all agricultural soils are degraded. This is responsible for an ongoing decrease in biomass productivity. For farmers, the productivity function delivers an economic basis and is a prerequisite for agricultural sustainability. Our study was designed to develop an agricultural primary productivity decision support model. To obtain a highly accurate decision support model that helps farmers and advisors to assess and manage the provision of the primary productivity soil function on their agricultural fields, we addressed the following specific objectives: i) to construct a qualitative decision support model to assess the primary productivity soil function at the agricultural field level; ii) to carry out verification, calibration and sensitivity analysis of this model, and iii) to validate the model based on empirical data. The result is a hierarchical qualitative model comprising of 25 input attributes describing soil properties, environmental conditions, cropping specifications and management practices on each respective field. An extensive dataset from France containing data from 399 sites was used to calibrate and validate the model. The large amount of data enabled data mining to support model calibration. The accuracy of the decision support model prior to calibration supported by data mining was ~ 40%. The data mining approach improved accuracy to 77%. The proposed methodology of combining decision modelling and data mining proved to be an important step forward. This iterative approach yielded an accurate, reliable and useful decision support model for the assessment of the primary productivity soil function at the field level. This can assist farmers and advisors in selecting the most appropriate crop management practices. Embedding this decision support model in a set of complementary models for four adjacent soil functions, as endeavored in the H2020 LANDMARK project, will help take the integrated sustainability of arable cropping systems to a new level.

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    DOAJ-Articles
    Article . 2019
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    Frontiers in Environmental Science
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    Authors: Hiernaux, Pierre; Adamou, Kalilou; Moumouni, Oumarou; Turner, Matthew,; +4 Authors

    International audience; Changing woody plant density across agricultural landscapes of the Sudano-Sahelian region is a debated issue. This paper reports the results of an investigation on the contribution of field hedges to overall woody plant density. Hedges separating individual cropped parcels were studied within village agropastoral territories in the Dantiandou district in western Niger. In 1992, field hedges were mapped over the study area using aerial photography and in 2016, using high resolution Google Earth imagery. In 1992, field hedge length was equal to 1006 km within 435 km 2 of croplands, equivalent to 2.3 km km −2. In 2016, 17.5% of these hedges had disappeared , but 1591 km of new hedges were observed resulting in an increased density of hedges to 5.6 km km −2. In 24 years, hedges had increased at a mean annual rate of 3.7% likely associated with the splitting of crop fields by inheritance. The composition and productivity of hedges were also monitored in 1996, 2010 and 2015. All trees (max-imum height ≥ 4 m), shrubs (< 4 m) and tussock perennial grasses were recorded within twelve field hedge samples of 200 m each. Field measurements were used to estimate basal area, crown area, foliage mass and wood mass of each woody plant within the sampled hedges. No significant trends were found between 1996 and 2015 in woody plant density, basal area, crown cover, wood and foliage masses across all monitored hedges. However, overall means hide a slight decrease in tree contributions, while shrub contributions first increased and then decreased. They also mask contradictory trends among sites most likely related to different rates of shrub coppicing and tree cutting. The woody species composition of the hedges is poor with an increase of Combretum glutinosum to the detriment of Guiera senegalensis over the study period. Multiplying the hedge sample statistics by the changing lengths of field hedges in the study area provides estimates of the contribution of the hedge woody plants to the woody plant population at a landscape scale. Between 1992 and 2016, field hedges contributed to increases of woody plant density by 3.9%, basal areas by 5.4%, crown cover by 2.7%, leading to 6.1% annual increase in foliage mass and 8.8% increase in wood mass.

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    Other literature type . 2019
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    Forest Ecology and Management
    Article . 2019 . Peer-reviewed
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      Other literature type . 2019
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      Forest Ecology and Management
      Article . 2019 . Peer-reviewed
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    Authors: Thomas Gschwantner; Iciar Alberdi; András Balázs; Sébastien Bauwens; +38 Authors

    Abstract Key message Volume predictions of sample trees are basic inputs for essential National Forest Inventory (NFI) estimates. The predicted volumes are rarely comparable among European NFIs because of country-specific dbh-thresholds and differences regarding the inclusion of the tree parts stump, stem top, and branches. Twenty-one European NFIs implemented harmonisation measures to provide consistent stem volume predictions for comparable forest resource estimates. Context The harmonisation of forest information has become increasingly important. International programs and interest groups from the wood industry, energy, and environmental sectors require comparable information. European NFIs as primary source of forest information are well-placed to support policies and decision-making processes with harmonised estimates. Aims The main objectives were to present the implementation of stem volume harmonisation by European NFIs, to obtain comparable growing stocks according to five reference definitions, and to compare the different results. Methods The applied harmonisation approach identifies the deviations between country-level and common reference definitions. The deviations are minimised through country-specific bridging functions. Growing stocks were calculated from the un-harmonised, and harmonised stem volume estimates and comparisons were made. Results The country-level growing stock results differ from the Cost Action E43 reference definition between − 8 and + 32%. Stumps and stem tops together account for 4 to 13% of stem volume, and large branches constitute 3 to 21% of broadleaved growing stock. Up to 6% of stem volume is allocated below the dbh-threshold. Conclusion Comparable volume figures are available for the first time on a large-scale in Europe. The results indicate the importance of harmonisation for international forest statistics. The presented work contributes to the NFI harmonisation process in Europe in several ways regarding comparable NFI reporting and scenario modelling.

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    Annals of Forest Science
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    Authors: Jakob Lavrsen Kure; Jakob Krabben; Simon Vilms Pedersen; Marco Carozzi; +1 Authors

    therefore, abatement technologies have been introduced to mitigate these emissions. The aim of this study was to demonstrate that low-cost measuring techniques are suitable to assess NH3 emissions in smaller plots, appropriate to test different managements. Two experiments were established to quantify NH3 emissions from urea application in a multi-plot design with radii of 5 (R5) and 20 m (R20). Field was bare soil partially surrounded by shelterbelts. Measurement techniques included passive flux samplers (Leuning), and passive concentration samplers (ALPHA) coupled to WindTrax dispersion model. NH3 emission from R5 was consistent with the emission from R20 when the surface-to-atmosphere exchange was not affected by shelterbelts, and wind speed near surface was greater than 1 m s&minus 1 and low emission strength. Cumulative emission over 60 h was 2% of the supplied N from the plots not affected by the shelterbelt, and 1% from the plots affected by shelterbelts, indicating that these structures can significantly reduce NH3 emissions. Ammonia (NH3) emission from agriculture is an environmental threat and a loss of nitrogen for crop production. Mineral fertilizers and manure are significant sources of NH3 1. Both measurement methods gave unreliable NH3 quantification in combination with wind speed lower than 1 m s&minus

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    ProdInra
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    Authors: Albin Lobo; José M. Torres-Ruiz; Régis Burlett; Cédric Lemaire; +8 Authors

    The genus Quercus comprises important species in forestry not only for their productive value but also for their ability to withstand drought. Hence an evaluation of inter- and intraspecific variation in drought tolerance is important for selecting the best adapted species and provenances for future afforestation. However, the presence of long vessels makes it difficult to assess xylem vulnerability to embolism in these species. Thanks to the development of a flow centrifuge equipped with a large rotor, we quantified (i) the between species variability of embolism resistance in four native and two exotic species of oaks in Europe and (ii) the within species variability in Quercus petraea. Embolism resistance varied significantly between species, with the pressure inducing 50% loss of hydraulic conductivity (P-50) ranging between -7.0 and -4.2 MPa. Species native to the Mediterranean region were more resistant than pan-European species. In contrast, intraspecific variability in embolism resistance in Q. petraea was low within provenances and null between provenances. A positive correlation between P-50 and vessel diameter among the six oak species indicates that the more embolism resistant species had narrower xylem vessels and a higher amount of hydraulic bridges between vessels. However, this tradeoff between hydraulic efficiency and safety was not observed between Q. petraea provenances.

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    Article . 2018
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    Europe PubMed Central
    Other literature type . 2018
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    Forest Ecology and Management
    Article . 2018 . Peer-reviewed
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    Authors: Sasha D. Hafner; Andreas Pacholski; Shabtai Bittman; W. Burchill; +23 Authors

    Abstract Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1895 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and “other”) applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to <15%) was carried out using mixed- and fixed-effects models in order to quantify effects of management and environment on ammonia emission, and to highlight challenges for use of the database. Measured emission in this subset ranged from <1% to 130% of applied ammonia after 48 h. Results showed clear, albeit variable, reductions in NH3 emission due to trailing hose, trailing shoe, and open slot injection of slurry compared to broadcast application. There was evidence of positive effects of air temperature and wind speed on NH3 emission, and limited evidence of effects of slurry DM. However, random-effects coefficients for differences among research institutes were among the largest model coefficients, and showed a deviation from the mean response by more than 100% in some cases. The source of these institute differences could not be determined with certainty, but there is some evidence that they are related to differences in soils, or differences in application or measurement methods. The ALFAM2 database should be useful for development and evaluation of both emission factors and emission models, but users need to recognize the limitations caused by confounding variables, imbalance in the dataset, and dependence among observations from the same institute. Variation among measurements and in reported variables highlights the importance of international agreement on how NH3 emission should be measured, along with necessary types of supporting data and standard protocols for their measurement. Both are needed in order to produce more accurate and useful ammonia emission measurements. Expansion of the ALFAM2 database will continue, and readers are invited to contact the corresponding author for information on data submission. The latest version of the database is available at http://www.alfam.dk. Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1895 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and “other”) applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to <15%) was carried out using mixed- and fixed-effects models in order to quantify effects of management and environment on ammonia emission, and to highlight challenges for use of the database. Measured emission in this subset ranged from <1% to 130% of applied ammonia after 48 h. Results showed clear, albeit variable, reductions in NH3 emission due to trailing hose, trailing shoe, and open slot injection of slurry compared to broadcast application. There was evidence of positive effects of air temperature and wind speed on NH3 emission, and limited evidence of effects of slurry DM. However, random-effects coefficients for differences among research institutes were among the largest model coefficients, and showed a deviation from the mean response by more than 100% in some cases. The source of these institute differences could not be determined with certainty, but there is some evidence that they are related to differences in soils, or differences in application or measurement methods. The ALFAM2 database should be useful for development and evaluation of both emission factors and emission models, but users need to recognize the limitations caused by confounding variables, imbalance in the dataset, and dependence among observations from the same institute. Variation among measurements and in reported variables highlights the importance of international agreement on how NH3 emission should be measured, along with necessary types of supporting data and standard protocols for their measurement. Both are needed in order to produce more accurate and useful ammonia emission measurements. Expansion of the ALFAM2 database will continue, and readers are invited to contact the corresponding author for information on data submission. The latest version of the database is available at http://www.alfam.dk.

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    T-Stór
    Article . 2017 . Peer-reviewed
    Data sources: T-Stór
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    Other literature type . Article . 2018
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      T-Stór
      Article . 2017 . Peer-reviewed
      Data sources: T-Stór
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      NARCIS; Research@WUR
      Other literature type . Article . 2018
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Hugh McColl; Fernando Racimo; Lasse Vinner; Fabrice Demeter; +62 Authors

    Ancient migrations in Southeast Asia The past movements and peopling of Southeast Asia have been poorly represented in ancient DNA studies (see the Perspective by Bellwood). Lipson et al. generated sequences from people inhabiting Southeast Asia from about 1700 to 4100 years ago. Screening of more than a hundred individuals from five sites yielded ancient DNA from 18 individuals. Comparisons with present-day populations suggest two waves of mixing between resident populations. The first mix was between local hunter-gatherers and incoming farmers associated with the Neolithic spreading from South China. A second event resulted in an additional pulse of genetic material from China to Southeast Asia associated with a Bronze Age migration. McColl et al. sequenced 26 ancient genomes from Southeast Asia and Japan spanning from the late Neolithic to the Iron Age. They found that present-day populations are the result of mixing among four ancient populations, including multiple waves of genetic material from more northern East Asian populations. Science , this issue p. 92 , p. 88 ; see also p. 31

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    Horizon / Pleins textes
    Other literature type . 2018
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    Apollo
    Other literature type . 2018
    Data sources: Apollo
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    Data sources: UnpayWall
    Apollo
    Article . 2018
    Data sources: Datacite
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    Article . 2018
    https://doi.org/10.7892/boris....
    Other literature type . 2018
    Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Quemada, M.; Lassaletta, L.; Jensen, L.S.; Godinot, O.; +7 Authors

    peer-reviewed Nitrogen (N) indicators are key for characterizing farm performance, because of the role of N in food production and environmental sustainability. A systematic monitoring of N balance at the farm level could contribute to understanding differences in N management and impacts among farms and among regions. The objective of this study was to increase the understanding of differences in N indicators at the farm level across Europe, and to derive possible target values. Farm-level data were collected through surveys of 1240 farms from Atlantic, Continental and Mediterranean Europe, that were diverse rather tahn country representative. The data were analysed according to a common procedure, using three related indicators: N use efficiency (NUE, farm-gate ratio of N outputs to N inputs), N surplus and N output in agricultural products. Specific target values were derived for farm type (arable, dairy, pig and mixed farms) based on the statistical analysis of the data set. The effect of not accounting for N losses involved in the production of purchased feed and the end use of exported manure (externalisation) on the animal farm indicators was evaluated by recalculating inputs with adjusting factors. The results show a wide variation in NUE and N surplus, mainly related to differences in farming systems and management. Arable farms presented lower mean N input and surplus than livestock farms, and therefore had the highest median NUE. The modest targets (i.e. median of data) for arable farms were NUE 61% and N surplus 68 kg N ha−1, for dairy farms NUE 30% and N surplus 155 kg N ha−1, and for pig farms NUE 40% and N surplus 135 kg N ha−1. Externalisation had a large effect on animal farm indicators. After adjusting for externalisation, the modest target NUE for dairy farms was 19% and for pig farms 23%. Farms outside their agro-environmental optimum could approach their specific targets by increasing or reducing N inputs (intensification or extensification) or adopting additional strategies (sustainable intensification). In conclusion, N indicators were useful to compare farm performance among different farming systems and to define a characteristic operating space for a farm population, but caution should be taken when comparing livestock farms before externalisation adjustment, and consideration should be given to changes in soil N stocks. Farm system-specific targets for N indicators and linkages with the Common Agricultural Policy may create the necessary incentives to optimise NUE and reduce N losses to air and water. Spanish Ministry of Economy and Competitiveness

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    NARCIS; Research@WUR
    Article . 2020
    License: CC BY
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    Research@WUR; Agricultural Systems
    Other literature type . Article . 2020 . Peer-reviewed
    License: CC BY
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    T-Stór
    Article . 2020 . Peer-reviewed
    Data sources: T-Stór
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    Authors: Richard P. Kipling; C. F. E. Topp; André Bannink; Dave J. Bartley; +20 Authors

    Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. Highlights • Modelling plays a key role in adapting agriculture to climate change. • Modellers' views and literature were analysed to identify adaptation-specific issues. • Novel challenges to modelling climate change adaptation were explored. • Challenges related to Responsibility, Scope, Optimisation, Information, Collaboration. • Adaptation to progressive climate change highlights social impacts of model use. Graphical abstract Image 1

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    NARCIS; Research@WUR
    Other literature type . Article . 2019
    License: CC BY NC ND
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    ProdInra
    Article . 2019
    License: CC BY NC ND
    Data sources: ProdInra
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    Cranfield CERES
    Article . 2019
    License: CC BY NC ND
    Data sources: Cranfield CERES
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    Brage NMBU
    Article . 2019
    Data sources: Brage NMBU
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    Environmental Modelling & Software
    Article . 2019 . Peer-reviewed
    License: CC BY NC ND
    Data sources: Crossref; NARCIS
    UnissResearch
    Article . 2019
    Data sources: UnissResearch
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Other literature type . Article . 2019
      License: CC BY NC ND
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      ProdInra
      Article . 2019
      License: CC BY NC ND
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      Cranfield CERES
      Article . 2019
      License: CC BY NC ND
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      Brage NMBU
      Article . 2019
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      Environmental Modelling & Software
      Article . 2019 . Peer-reviewed
      License: CC BY NC ND
      Data sources: Crossref; NARCIS
      UnissResearch
      Article . 2019
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    Authors: van Leeuwen, J.P.; Creamer, Rachel; Cluzeau, Daniel; Debeljak, Marko; +11 Authors

    Soil biodiversity and habitat provisioning is one of the soil functions that agricultural land provides to society. This paper describes assessment of the soil biodiversity function (SB function) as a proof of concept to be used in a decision support tool for agricultural land management. The SB function is defined as ‘the multitude of soil organisms and processes, interacting in an ecosystem, providing society with a rich biodiversity source and contributing to a habitat for aboveground organisms.’ So far, no single measure provides the full overview of the soil biodiversity and how a soil supports a habitat for a biodiverse ecosystem. We have assembled a set of attributes for a proxy-indicator system, based on four ‘integrated attributes’: 1) soil nutrient status, 2) soil biological status, 3) soil structure, and 4) soil hydrological status. These attributes provide information to be used in a model for assessing the capacity of a soil to supply the SB function. A multi-criteria decision model was developed which comprises of 34 attributes providing information to quantify the four integrated attributes and subsequently assess the SB function for grassland and for cropland separately. The model predictions (in terms of low – moderate – high soil biodiversity status) were compared with expert judgements for a collection of 137 grassland soils in the Netherlands and 52 French soils, 29 grasslands and 23 croplands. For both datasets, the results show that the proposed decision model predictions were statistically significantly correlated with the expert judgements. A sensitivity analysis indicated that the soil nutrient status, defined by attributes such as pH and organic carbon content, was the most important integrated attribute in the assessment of the SB function. Further progress in the assessment of the SB function is needed. This can be achieved by better information regarding land use and farm management. In this way we may make a valuable step in our attempts to optimize the multiple soil functions in agricultural landscapes, and hence the multifaceted role of soils to deliver a bundle of ecosystem services for farmers and citizens, and support land management and policy towards a more sustainable society.

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    NARCIS; Research@WUR
    Article . 2019
    License: CC BY
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    DOAJ-Articles
    Article . 2019
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    Frontiers in Environmental Science
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    DOAJ
    Article . 2019
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    Authors: Taru Sandén; Aneta Trajanov; Aneta Trajanov; Heide Spiegel; +6 Authors

    Agricultural soils provide society with several functions, one of which is primary productivity. This function is defined as the capacity of a soil to supply nutrients and water and to produce plant biomass for human use, providing food, feed, fiber and fuel. Up to about one quarter of all agricultural soils are degraded. This is responsible for an ongoing decrease in biomass productivity. For farmers, the productivity function delivers an economic basis and is a prerequisite for agricultural sustainability. Our study was designed to develop an agricultural primary productivity decision support model. To obtain a highly accurate decision support model that helps farmers and advisors to assess and manage the provision of the primary productivity soil function on their agricultural fields, we addressed the following specific objectives: i) to construct a qualitative decision support model to assess the primary productivity soil function at the agricultural field level; ii) to carry out verification, calibration and sensitivity analysis of this model, and iii) to validate the model based on empirical data. The result is a hierarchical qualitative model comprising of 25 input attributes describing soil properties, environmental conditions, cropping specifications and management practices on each respective field. An extensive dataset from France containing data from 399 sites was used to calibrate and validate the model. The large amount of data enabled data mining to support model calibration. The accuracy of the decision support model prior to calibration supported by data mining was ~ 40%. The data mining approach improved accuracy to 77%. The proposed methodology of combining decision modelling and data mining proved to be an important step forward. This iterative approach yielded an accurate, reliable and useful decision support model for the assessment of the primary productivity soil function at the field level. This can assist farmers and advisors in selecting the most appropriate crop management practices. Embedding this decision support model in a set of complementary models for four adjacent soil functions, as endeavored in the H2020 LANDMARK project, will help take the integrated sustainability of arable cropping systems to a new level.

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    DOAJ-Articles
    Article . 2019
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    Frontiers in Environmental Science
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    Article . 2019
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    Authors: Hiernaux, Pierre; Adamou, Kalilou; Moumouni, Oumarou; Turner, Matthew,; +4 Authors

    International audience; Changing woody plant density across agricultural landscapes of the Sudano-Sahelian region is a debated issue. This paper reports the results of an investigation on the contribution of field hedges to overall woody plant density. Hedges separating individual cropped parcels were studied within village agropastoral territories in the Dantiandou district in western Niger. In 1992, field hedges were mapped over the study area using aerial photography and in 2016, using high resolution Google Earth imagery. In 1992, field hedge length was equal to 1006 km within 435 km 2 of croplands, equivalent to 2.3 km km −2. In 2016, 17.5% of these hedges had disappeared , but 1591 km of new hedges were observed resulting in an increased density of hedges to 5.6 km km −2. In 24 years, hedges had increased at a mean annual rate of 3.7% likely associated with the splitting of crop fields by inheritance. The composition and productivity of hedges were also monitored in 1996, 2010 and 2015. All trees (max-imum height ≥ 4 m), shrubs (< 4 m) and tussock perennial grasses were recorded within twelve field hedge samples of 200 m each. Field measurements were used to estimate basal area, crown area, foliage mass and wood mass of each woody plant within the sampled hedges. No significant trends were found between 1996 and 2015 in woody plant density, basal area, crown cover, wood and foliage masses across all monitored hedges. However, overall means hide a slight decrease in tree contributions, while shrub contributions first increased and then decreased. They also mask contradictory trends among sites most likely related to different rates of shrub coppicing and tree cutting. The woody species composition of the hedges is poor with an increase of Combretum glutinosum to the detriment of Guiera senegalensis over the study period. Multiplying the hedge sample statistics by the changing lengths of field hedges in the study area provides estimates of the contribution of the hedge woody plants to the woody plant population at a landscape scale. Between 1992 and 2016, field hedges contributed to increases of woody plant density by 3.9%, basal areas by 5.4%, crown cover by 2.7%, leading to 6.1% annual increase in foliage mass and 8.8% increase in wood mass.

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    Other literature type . 2019
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    Forest Ecology and Management
    Article . 2019 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
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      Horizon / Pleins textes
      Other literature type . 2019
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Forest Ecology and Management
      Article . 2019 . Peer-reviewed
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    Authors: Thomas Gschwantner; Iciar Alberdi; András Balázs; Sébastien Bauwens; +38 Authors

    Abstract Key message Volume predictions of sample trees are basic inputs for essential National Forest Inventory (NFI) estimates. The predicted volumes are rarely comparable among European NFIs because of country-specific dbh-thresholds and differences regarding the inclusion of the tree parts stump, stem top, and branches. Twenty-one European NFIs implemented harmonisation measures to provide consistent stem volume predictions for comparable forest resource estimates. Context The harmonisation of forest information has become increasingly important. International programs and interest groups from the wood industry, energy, and environmental sectors require comparable information. European NFIs as primary source of forest information are well-placed to support policies and decision-making processes with harmonised estimates. Aims The main objectives were to present the implementation of stem volume harmonisation by European NFIs, to obtain comparable growing stocks according to five reference definitions, and to compare the different results. Methods The applied harmonisation approach identifies the deviations between country-level and common reference definitions. The deviations are minimised through country-specific bridging functions. Growing stocks were calculated from the un-harmonised, and harmonised stem volume estimates and comparisons were made. Results The country-level growing stock results differ from the Cost Action E43 reference definition between − 8 and + 32%. Stumps and stem tops together account for 4 to 13% of stem volume, and large branches constitute 3 to 21% of broadleaved growing stock. Up to 6% of stem volume is allocated below the dbh-threshold. Conclusion Comparable volume figures are available for the first time on a large-scale in Europe. The results indicate the importance of harmonisation for international forest statistics. The presented work contributes to the NFI harmonisation process in Europe in several ways regarding comparable NFI reporting and scenario modelling.

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    Annals of Forest Science
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    Authors: Jakob Lavrsen Kure; Jakob Krabben; Simon Vilms Pedersen; Marco Carozzi; +1 Authors

    therefore, abatement technologies have been introduced to mitigate these emissions. The aim of this study was to demonstrate that low-cost measuring techniques are suitable to assess NH3 emissions in smaller plots, appropriate to test different managements. Two experiments were established to quantify NH3 emissions from urea application in a multi-plot design with radii of 5 (R5) and 20 m (R20). Field was bare soil partially surrounded by shelterbelts. Measurement techniques included passive flux samplers (Leuning), and passive concentration samplers (ALPHA) coupled to WindTrax dispersion model. NH3 emission from R5 was consistent with the emission from R20 when the surface-to-atmosphere exchange was not affected by shelterbelts, and wind speed near surface was greater than 1 m s&minus 1 and low emission strength. Cumulative emission over 60 h was 2% of the supplied N from the plots not affected by the shelterbelt, and 1% from the plots affected by shelterbelts, indicating that these structures can significantly reduce NH3 emissions. Ammonia (NH3) emission from agriculture is an environmental threat and a loss of nitrogen for crop production. Mineral fertilizers and manure are significant sources of NH3 1. Both measurement methods gave unreliable NH3 quantification in combination with wind speed lower than 1 m s&minus

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    ProdInra
    Article . 2018
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    Agronomy
    Article . 2018
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    Article . 2018
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      ProdInra
      Article . 2018
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      Agronomy
      Article . 2018
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    Authors: Albin Lobo; José M. Torres-Ruiz; Régis Burlett; Cédric Lemaire; +8 Authors

    The genus Quercus comprises important species in forestry not only for their productive value but also for their ability to withstand drought. Hence an evaluation of inter- and intraspecific variation in drought tolerance is important for selecting the best adapted species and provenances for future afforestation. However, the presence of long vessels makes it difficult to assess xylem vulnerability to embolism in these species. Thanks to the development of a flow centrifuge equipped with a large rotor, we quantified (i) the between species variability of embolism resistance in four native and two exotic species of oaks in Europe and (ii) the within species variability in Quercus petraea. Embolism resistance varied significantly between species, with the pressure inducing 50% loss of hydraulic conductivity (P-50) ranging between -7.0 and -4.2 MPa. Species native to the Mediterranean region were more resistant than pan-European species. In contrast, intraspecific variability in embolism resistance in Q. petraea was low within provenances and null between provenances. A positive correlation between P-50 and vessel diameter among the six oak species indicates that the more embolism resistant species had narrower xylem vessels and a higher amount of hydraulic bridges between vessels. However, this tradeoff between hydraulic efficiency and safety was not observed between Q. petraea provenances.

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    Oskar Bordeaux
    Article . 2018
    Data sources: Oskar Bordeaux
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    Europe PubMed Central
    Other literature type . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Forest Ecology and Management
    Article . 2018 . Peer-reviewed
    License: Elsevier TDM
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      Oskar Bordeaux
      Article . 2018
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      Europe PubMed Central
      Other literature type . 2018
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      Forest Ecology and Management
      Article . 2018 . Peer-reviewed
      License: Elsevier TDM
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    Authors: Sasha D. Hafner; Andreas Pacholski; Shabtai Bittman; W. Burchill; +23 Authors

    Abstract Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1895 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and “other”) applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to <15%) was carried out using mixed- and fixed-effects models in order to quantify effects of management and environment on ammonia emission, and to highlight challenges for use of the database. Measured emission in this subset ranged from <1% to 130% of applied ammonia after 48 h. Results showed clear, albeit variable, reductions in NH3 emission due to trailing hose, trailing shoe, and open slot injection of slurry compared to broadcast application. There was evidence of positive effects of air temperature and wind speed on NH3 emission, and limited evidence of effects of slurry DM. However, random-effects coefficients for differences among research institutes were among the largest model coefficients, and showed a deviation from the mean response by more than 100% in some cases. The source of these institute differences could not be determined with certainty, but there is some evidence that they are related to differences in soils, or differences in application or measurement methods. The ALFAM2 database should be useful for development and evaluation of both emission factors and emission models, but users need to recognize the limitations caused by confounding variables, imbalance in the dataset, and dependence among observations from the same institute. Variation among measurements and in reported variables highlights the importance of international agreement on how NH3 emission should be measured, along with necessary types of supporting data and standard protocols for their measurement. Both are needed in order to produce more accurate and useful ammonia emission measurements. Expansion of the ALFAM2 database will continue, and readers are invited to contact the corresponding author for information on data submission. The latest version of the database is available at http://www.alfam.dk. Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1895 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and “other”) applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to <15%) was carried out using mixed- and fixed-effects models in order to quantify effects of management and environment on ammonia emission, and to highlight challenges for use of the database. Measured emission in this subset ranged from <1% to 130% of applied ammonia after 48 h. Results showed clear, albeit variable, reductions in NH3 emission due to trailing hose, trailing shoe, and open slot injection of slurry compared to broadcast application. There was evidence of positive effects of air temperature and wind speed on NH3 emission, and limited evidence of effects of slurry DM. However, random-effects coefficients for differences among research institutes were among the largest model coefficients, and showed a deviation from the mean response by more than 100% in some cases. The source of these institute differences could not be determined with certainty, but there is some evidence that they are related to differences in soils, or differences in application or measurement methods. The ALFAM2 database should be useful for development and evaluation of both emission factors and emission models, but users need to recognize the limitations caused by confounding variables, imbalance in the dataset, and dependence among observations from the same institute. Variation among measurements and in reported variables highlights the importance of international agreement on how NH3 emission should be measured, along with necessary types of supporting data and standard protocols for their measurement. Both are needed in order to produce more accurate and useful ammonia emission measurements. Expansion of the ALFAM2 database will continue, and readers are invited to contact the corresponding author for information on data submission. The latest version of the database is available at http://www.alfam.dk.

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    T-Stór
    Article . 2017 . Peer-reviewed
    Data sources: T-Stór
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    NARCIS; Research@WUR
    Other literature type . Article . 2018
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      T-Stór
      Article . 2017 . Peer-reviewed
      Data sources: T-Stór
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      NARCIS; Research@WUR
      Other literature type . Article . 2018
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    Authors: Hugh McColl; Fernando Racimo; Lasse Vinner; Fabrice Demeter; +62 Authors

    Ancient migrations in Southeast Asia The past movements and peopling of Southeast Asia have been poorly represented in ancient DNA studies (see the Perspective by Bellwood). Lipson et al. generated sequences from people inhabiting Southeast Asia from about 1700 to 4100 years ago. Screening of more than a hundred individuals from five sites yielded ancient DNA from 18 individuals. Comparisons with present-day populations suggest two waves of mixing between resident populations. The first mix was between local hunter-gatherers and incoming farmers associated with the Neolithic spreading from South China. A second event resulted in an additional pulse of genetic material from China to Southeast Asia associated with a Bronze Age migration. McColl et al. sequenced 26 ancient genomes from Southeast Asia and Japan spanning from the late Neolithic to the Iron Age. They found that present-day populations are the result of mixing among four ancient populations, including multiple waves of genetic material from more northern East Asian populations. Science , this issue p. 92 , p. 88 ; see also p. 31

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    Horizon / Pleins textes
    Other literature type . 2018
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    Apollo
    Other literature type . 2018
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    Science
    Article
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    Apollo
    Article . 2018
    Data sources: Datacite
    Science
    Article . 2018
    https://doi.org/10.7892/boris....
    Other literature type . 2018
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