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  • ZENODO

  • 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: Barreaux, Antoine; Higginson, Andrew; Bonsall, Michael; English, Sinead;

    Here, we investigate how stochasticity and age-dependence in energy dynamics influence maternal allocation in iteroparous females. We develop a state-dependent model to calculate the optimal maternal allocation strategy with respect to maternal age and energy reserves, focusing on allocation in a single offspring at a time. We introduce stochasticity in energetic costs– in terms of the amount of energy required to forage successfully and individual differences in metabolism – and in feeding success. We systematically assess how allocation is influenced by age-dependence in energetic costs, feeding success, energy intake per successful feeding attempt, and environmentally-driven mortality. First, using stochastic dynamic programming, we calculate the optimal amount of reserves M that mothers allocate to each offspring depending on their own reserves R and age A. The optimal life history strategy is then the set of allocation decisions M(R, A) over the whole lifespan which maximizes the total reproductive success of distant descendants. Second, we simulated the life histories of 1000 mothers following the optimisation strategy and the reserves at the start of adulthood R1, the distribution of which was determined, the distribution of which was determined using an iterative procedure as described . For each individual, we calculated maternal allocation Mt, maternal reserves Rt, and relative allocation Mt⁄Rt at each time period t. The relative allocation helps us to understand how resources are partitioned between mother and offspring. Third, we consider how the optimal strategy varies when there is age-dependence in resource acquisition, energetic costs and survival. Specifically, we include varying scenarios with an age-dependent increase or a decrease with age in energetic costs (c_t), feeding success (q_t), energy intake per successful feeding attempt (y_t), and environmentally-driven extrinsic mortality rate (d_t) (Table 2). We consider the age-dependence of parameters one at a time or in pairs, altering the slope, intercept, or asymptote of the age-dependence (linear or asymptotic function). Our aim is to identify whether the observed reproductive senescence can arise from optimal maternal allocation. As such, we do not impose a decline in selection in later life as all offspring are equally valuable at all ages (for a given maternal allocation), and there are no mutations. For each scenario, we run the backward iteration process with these age-dependent functions, obtain the allocation strategy, and simulate the life history of 1000 individuals based on the novel strategy. We then fit quadratic and linear models to the reproduction of these 1000 individuals using the lme function, nlme package in R. For these models, the response variable is the maternal allocation Mt and explanatory variables are the time period t and t2 (for the quadratic fit only), with individual identity as a random term. We use likelihood ratio tests to compare linear and quadratic models using the anova function (package nlme) with the maximum-likelihood method. If the comparison is significant (p-value <0.05), we considered the quadratic model to have a better fit, otherwise the linear model is considered more parsimonious. We were particularly interested in identifying scenarios where the fit was quadratic with a negative quadratic term. For each scenario, the pseudo R2 conditional value (proportion of variance explained by the fixed and random terms, accounting for individual identity) is calculated to assess the goodness-of-fit of the lme model, on a scale from 0 to 1, using the “r.squared” function, package gabtool. All calculations and coding are done in R. Iteroparous parents face a trade-off between allocating current resources to reproduction versus maximizing survival to produce further offspring. Optimal allocation varies across age, and follows a hump-shaped pattern across diverse taxa, including mammals, birds and invertebrates. This non-linear allocation pattern lacks a general theoretical explanation, potentially because most studies focus on offspring number rather than quality and do not incorporate uncertainty or age-dependence in energy intake or costs. Here, we develop a life history model of maternal allocation in iteroparous animals. We identify the optimal allocation strategy in response to stochasticity when energetic costs, feeding success, energy intake, and environmentally-driven mortality risk are age-dependent. As a case study, we use tsetse, a viviparous insect that produces one offspring per reproductive attempt and relies on an uncertain food supply of vertebrate blood. Diverse scenarios generate a hump-shaped allocation: when energetic costs and energy intake increase with age; and also when energy intake decreases, and energetic costs increase or decrease. Feeding success and mortality risk have little influence on age-dependence in allocation. We conclude that ubiquitous evidence for age-dependence in these influential traits can explain the prevalence of non-linear maternal allocation across diverse taxonomic groups.

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    ZENODO
    Dataset . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2022
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2022
      License: CC 0
      Data sources: Datacite
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    Authors: Shao, Junjiong; Zhou, Xuhui; van Groenigen, Kees; Zhou, Guiyao; +9 Authors

    Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

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    ZENODO
    Dataset . 2023
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2022
      License: CC 0
      Data sources: Datacite
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    Authors: Carla Zarbà; Gaetano Chinnici; Giovanni La Via; Salvatore Bracco; +2 Authors

    In the transition from linear production systems, unsustainable from the point of view of resources, to a model that finds strength in environmental, social and economic sustainability, the circular economy paradigm is the foundation that facilitates the planetary agro-ecological transition. The European Union has taken a number of steps (including the Circular Economy Package of Directives) shaping circularity as a wide-ranging driver measure involving many sectors. The paper intends to provide a regulatory framework on the current general situation regarding circularity in European Union, in order to extrapolate and give evidence to the aspects that intersect the agri-food sector. This is not only because they are poorly addressed in the literature, but also because there is a lack of regulatory instruments on the circular economy specifically addressing this area of interest. For this purpose, the analysis focuses on waste and residue/scrap management issues, recognized by law as by-products and end-of-waste status, as they are covered by circular economy legislation and as they can be applied to the agri-food sector. The latter allow the implementation of circularity strategies in the agri-food sector and, given the numerousness of production chains and the peculiarities of each of them, various regeneration and/or reuse processes of specific resources may be depicted. The intent is to provide useful knowledge on how to implement sustainable waste management, also proposing a concrete case on a by-product of olive oil processing, through which it is possible to highlight how the correct application of regulations favors the adoption of circular economic and management models in the firms involved, as well as informing the relevant economic operators on the possible profiles of legal liability that may arise from insufficient knowledge. Furthermore, this paper delves into the European Green Deal’s Strategy as it enriches the circular economy paradigm with new facets. NextGenerationEU and the National Recovery and Resilience Plan financially support this strategy in the aftermath of the socioeconomic crisis from COVID-19 in the EU Member States. This is in order to achieve the objective of achieving the agro-ecological transition.

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    Sustainability
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    ZENODO
    Article . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Article . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: Leybourne, Daniel J; Preedy, Katharine F; Valentine, Tracy A; Bos, Jorunn I B; +1 Authors

    1. Aphids are abundant in natural and managed vegetation, supporting a diverse community of organisms and causing damage to agricultural crops. Due to a changing climate, periods of drought are anticipated to increase, and the potential consequences of this for aphid-plant interactions are unclear. 2. Using a meta-analysis and synthesis approach, we aimed to advance understanding of how increased drought incidence will affect this ecologically and economically important insect group, and to characterise any potential underlying mechanisms. We used qualitative and quantitative synthesis techniques to determine whether drought stress has a negative, positive, or null effect on aphid fitness and examined these effects in relation to 1) aphid biology, 2) geographical region, 3) host plant biology. 3. Across all studies, aphid fitness is typically reduced under drought. Subgroup analysis detected no difference in relation to aphid biology, geographical region, or the aphid-plant combination, indicating the negative effect of drought on aphids is potentially universal. Furthermore, drought stress had a negative impact on plant vigour and increased plant concentrations of defensive chemicals, suggesting the observed response of aphids is associated with reduced plant vigour and increased chemical defence in drought-stressed plants. 4. We propose a conceptual model to predict drought effects on aphid fitness in relation to plant vigour and defence to stimulate further research. Please check the ReadMe for an explanation of the values included in the dataset. Please note that n/a values are included in the Global_Dataset tab for plant meta-analysis data (_Plant_Vigour, _Plant_Defence, and _Plant_Nutrition), these indicate studies that did not report these parameters. Data was collected and curated using standard systematic literature synthesis approaches. The effect size (Hedges' g) reported in the dataset was calculated from extracted means and standard deviations.

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    ZENODO
    Dataset . 2021
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
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    Authors: Smith, Linnea C; Orgiazzi, Alberto; Eisenhauer, Nico; Cesarz, Simone; +10 Authors

    The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types. Location: Europe Time period: 2018 Major taxa studied: Microbial community (fungi and bacteria) We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change. [Methods] Soil samples were collected during the 2018 LUCAS soil sampling campaign. Soil chemical and physical properties were measured at the Joint Research Centre in Ispra, Italy (Orgiazzi et al., 2018). Soil microbial respiration and biomass, as well as water content and water holding capacity, were measured in the Eisenhauer lab of the German Centre for Integrative Biodiversity Research. Fungi/Bacteria was measured by fatty acid analysis by Felipe Bastida at CEBAS CSIC. Climate and geographical data were harvested from various databases, which are listed in Appendix 1 (data sources) of the associated paper. For more details on the soil sampling and physical and chemical properties, see: Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., & Fernández-Ugalde, O. (2018). LUCAS Soil, the largest expandable soil dataset for Europe: a review. European Journal of Soil Science, 69(1), 140-153. https://doi.org/10.1111/ejss.12499 For more details on the measurements of soil microbial respiration and biomass, fatty acids, and water holding capacity, see the supplementary methods of the associated paper (Appendix 2). [Usage Notes] Fatty acid analysis was performed for a subset of 267 samples. Water holding capacity and associated measurements of basal respiration was analyzed in a subset of 100 samples. The samples that were not in these subsets have NA values for the columns associated with these measurements. In order to protect the precise locations of the LUCAS sampling sites, latitude and longitude values could not be given. The approximate location of each sampling site is instead described by the NUTS3 region. If you wish to replicate the structural equation modeling described in the paper, for which latitude is required, please get in touch. A description of each column is available in the associated metadata file. Deutsche Forschungsgemeinschaft, Award: FZT 118-202548816. European Research Council, Award: 694368. European Commission. Directorate-General for the Environment. Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement du Service Public de Wallonie. Eurostat. Peer reviewed

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    ZENODO
    Dataset . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
    License: CC 0
    Data sources: Datacite
    Digital.CSIC
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
    Digital.CSIC
    Dataset . 2021 . Peer-reviewed
    Data sources: Digital.CSIC
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      ZENODO
      Dataset . 2022
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2022
      License: CC 0
      Data sources: Datacite
      Digital.CSIC
      Dataset . 2021
      License: CC 0
      Data sources: Datacite
      Digital.CSIC
      Dataset . 2021 . Peer-reviewed
      Data sources: Digital.CSIC
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    Authors: Warren-Thomas, Eleanor; Nelson, Luke; Juthong, Watinee; Bumrungsri, Sara; +7 Authors

    Monocultural rubber plantations have replaced tropical forest, causing biodiversity loss. While protecting intact or semi-intact biodiverse forest is paramount, improving biodiversity value within the 11.4 million hectares of existing rubber plantations could offer important conservation benefits, if yields are also maintained. Some farmers practice agroforestry with high-yielding clonal rubber varieties to increase and diversify incomes. Here, we ask whether such rubber agroforestry improves biodiversity value or affects rubber yields relative to monoculture. We surveyed birds, fruit-feeding butterflies and reptiles in 25 monocultural and 39 agroforest smallholder rubber plots in Thailand, the world’s biggest rubber producer. Management and vegetation structure data were collected from each plot, and landscape composition around plots was quantified. Rubber yield data were collected for a separate set of 34 monocultural and 47 agroforest rubber plots in the same region. Reported rubber yields did not differ between agroforests and monocultures, meaning adoption of agroforestry in this context should not increase land demand for natural rubber. Butterfly richness was greater in agroforests, where richness increased with greater natural forest extent in the landscape. Bird and reptile richness were similar between agroforests and monocultures, but bird richness increased with the height of herbaceous vegetation inside rubber plots. Species composition of butterflies differed between agroforests and monocultures, and in response to natural forest extent, while bird composition was influenced by herbaceous vegetation height within plots, the density of non-rubber trees within plots (representing agroforestry complexity), and natural forest extent in the landscape. Reptile composition was influenced by canopy cover and open habitat extent in the landscape. Conservation priority and forest-dependent birds were not supported within rubber. Synthesis and applications. Rubber agroforestry using clonal varieties provides modest biodiversity benefits relative to monocultures, without compromising yields. Agroforests may also generate ecosystem service and livelihood benefits. Management of monocultural rubber production to increase inter-row vegetation height and complexity may further benefit biodiversity. However, biodiversity losses from encroachment of rubber onto forests will not be offset by rubber agroforestry or rubber plot management. This evidence is important for developing guidelines around biodiversity-friendly rubber and sustainable supply chains, and for farmers interested in diversifying rubber production. The accompanying ReadMe.txt file explains the contents of each .csv file, including definitions of each column. Sampling protocols are outlined in the paper in Journal of Applied Ecology.

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    ZENODO
    Dataset . 2019
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2019
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2019
      License: CC 0
      Data sources: ZENODO
      DRYAD
      Dataset . 2019
      License: CC 0
      Data sources: Datacite
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    Authors: Wade, Ruth N.; Karley, Alison J.; Johnson, Scott N.; Hartley, Sue E.;

    1. Predicted changes in the frequency and intensity of extreme rainfall events in the UK have the potential to disrupt terrestrial ecosystem function. However, responses of different trophic levels to these changes in rainfall patterns, and the underlying mechanisms, are not well characterised. 2. This study aimed to investigate how changes in both the quantity and frequency of rainfall events will affect the outcome of interactions between plants, insect herbivores (above- and below- ground) and natural enemies. 3. Hordeum vulgare L. plants were grown in controlled conditions and in the field, and subjected to three precipitation scenarios: ambient (based on a local 10 year average rainfall); continuous drought (40% reduction compared to ambient); drought/ deluge (40% reduction compared to ambient at a reduced frequency). The effects of these watering regimes and wireworm (Agriotes species) root herbivory on the performance of the plants, aphid herbivores above-ground (Sitobion avenae, Metapolophium dirhodum and Rhopalosiphum padi), and natural enemies of aphids including ladybirds (Harmonia axyridis) were assessed from measurements of plant growth, insect abundance and mass, and assays of feeding behaviour. 4. Continuous drought decreased plant biomass, whereas reducing the frequency of watering events did not affect plant biomass but did alter plant chemical composition. In controlled conditions, continuous drought ameliorated the negative impact of wireworms on plant biomass. 5. Compared to the ambient treatment, aphid mass was increased by 15% when feeding on plants subjected to drought/ deluge; and ladybirds were 66% heavier when feeding on these aphids but this did not affect ladybird prey choice. In field conditions, wireworms feeding below-ground reduced the number of shoot-feeding aphids under ambient and continuous drought conditions but not under drought/ deluge. 6. Predicted changes in both the frequency and intensity of precipitation events under climate change have the potential to limit plant growth, but reduce wireworm herbivory, while simultaneously promoting above-ground aphid numbers and mass, with these effects transferring to the third trophic level. Understanding the effect of future changes in precipitation on species interactions is critical for determining their potential impact on ecosystem functioning and constructing accurate predictions under global change scenarios. Controlled environment and field experimental dataData file containing all data reported in the paper including plant, soil and insect data from controlled environment and field experiments. First spreadsheet in the data file contains a key to explain all abbreviations used throughout the file.Experimental data.xlsx

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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
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    EASY
    Dataset . 2017
    Data sources: EASY
    DRYAD
    Dataset . 2017
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2018
    License: CC 0
    Data sources: Datacite
    DRYAD
    Dataset . 2017
    License: CC 0
    Data sources: Datacite
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
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      B2FIND
      Dataset . 2017
      Data sources: B2FIND
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      B2FIND
      Dataset . 2017
      Data sources: B2FIND
      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
      EASY
      Dataset . 2017
      Data sources: EASY
      DRYAD
      Dataset . 2017
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2018
      License: CC 0
      Data sources: Datacite
      DRYAD
      Dataset . 2017
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    Authors: Bunyod Holmatov; Arjen Hoekstra; Maarten Krol;

    To reduce greenhouse gas (GHG) emissions, the European Union (EU) has targets for utilizing energy from renewable sources. By 2030, a minimum of 3.5% of energy in the EU���s transport sector should come from renewable biological sources, such as crop residues. This paper analyzed EU���s ���advanced bioethanol��� potential from wheat straw and maize stover and evaluated its environmental (land, water, and carbon) footprint. We differentiated between gross and net bioethanol output, the latter by subtracting the energy inputs in production. Results suggest that the annual amount of the sustainably harvestable wheat straw and maize stover is 81.9 Megatonnes (Mt) at field moisture weight (65.3 Mt as dry weight), yielding 470 PJ as gross (404 PJ as net) advanced bioethanol output. Calculated net advanced bioethanol can replace 2.95% of EU transport sector���s energy consumption. EU���s advanced bioethanol has a land footprint of 0.28 m2 MJ���1 for wheat straw and 0.18 m2 MJ���1 for maize stover. The average water footprint of advanced bioethanol is 173 L MJ���1 for wheat straw and 113 L MJ���1 for maize stover. The average carbon footprint per unit of advanced bioethanol is 19.4 and 19.6 g CO2eq MJ���1 for wheat straw and maize stover, respectively. Using advanced bioethanol can lead to emission savings, but EU���s advanced bioethanol production potential is insufficient to achieve EU���s target of a minimum share of 3.5% of advanced biofuels in the transport sector by 2030, and the associated water and land footprints are not smaller than footprints of conventional bioethanol.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2021
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      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
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    Authors: Robinson, Sinikka; O'Gorman, Eoin; Frey, Beat; Hagner, Marleena; +1 Authors

    Study site This is a dataset of soil physiochemical properties, bacterial and fungal abundance, and above and belowground plant and invertebrate biomass, sampled at 40 soil plots in the Hengill geothermal valley, Iceland, from 15th to 22nd August 2018. The plots, measuring approximately 1 m2, evenly span a temperature gradient of 10-35°C. The dataset also includes data on the decomposition rate of soil organic matter, which was sampled at 60 plots in the Hengill valley from May to July 2015 (see Robinson et al. 2021 for plot details and sampling regime). Soil properties Soil temperature was measured at 5 cm depth at each plot on 15th, 18th, and 22nd August, and a mean plot temperature calculated. Soil physiochemical properties were analysed from 3 soil cores of 3 cm in diameter, taken from the upper 10 cm soil stratum at each plot; one quarter of each subsample was pooled to obtain an estimate per plot. Aboveground plant matter, excluding roots, were removed from each core. Percentage soil moisture was calculated by measuring the weight of one pooled soil sample before and after drying for 24 h in a 70°C drying oven. Soil pH was obtained from 20 g of the dry soil by adding 100 ml distilled water, shaking for 5 min on 150 rpm, letting the sample stand for 2 h, and measuring soil pH from the water layer using an InoLab pH 720 (WTW) probe. Soil PO4, NH4, and NO3 concentrations were analysed from a second pooled soil; 60 g of fresh soil was extracted in 100 ml distilled water, filtered through a GF/C (1.2μm) glass microfiber filter (Whatman, GE Healthcare Europe GmbH), and analysed using a Lachat QuikChem 8000 analyser (Zallweger Analytics, Inc., Lachat Instruments Division, USA). Total mineral N was calculated as the sum of NH4 and NO3. Soil organic matter content (excluding dry root biomass) was calculated as the weight lost from an oven dried (105°C for 24 hours) soil sample after heating at 550 °C for 5 h. Decomposition rate of soil organic matter was measured using the Cotton-strip Assay method (Tiegs et al. 2013) by placing a 2.5 cm x 8 cm strip of Fredrix-brand unprimed 12-oz. heavyweight cotton fabric (Style #548) 5 cm belowground at 60 plots, concurrently with a Maxim Integrated DS1921G Thermocron iButton temperature logger, on 13th May 2015. The strips were collected on 3rd July, rinsed with stream water to remove residual soil, soaked in 96% ethanol for 30 seconds to kill bacteria and halt decomposition, and dried at 60 °C for 12 h. Using a universal testing machine (Instron 5866 with 500 kN tensile holding clamps), maximum tensile strench of each cotton strip was measured. % tensile loss (proxy for decomposition) was calculated as (C-T) / C x 100, where T is the maximum tensile strength for each strip collected from the field, and C is the mean tensile strength of seven control strips, which had not been placed in the ground. See Robinson et al. 2021 for detailed description of plots sampled in 2015. Microbial abundance Bacterial and fungal abundance was estimated from additional soil cores of 3 cm in diameter taken from the upper 4 cm soil stratum (including the litter layer) at each plot. DNA was extracted using the PowerSoil DNA Isolation Kit (Qiagen, Germany). DNA was quantified using the high-sensitivity Qubit assay (Thermo Fisher Scientific, Switzerland). Relative abundances of bacterial and fungal communities were determined by quantitative PCR (qPCR) on an ABI7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA, USA). PCR amplification of partial bacterial small-subunit ribosomal RNA genes (region V1–V3 of 16S; primers 27F and 512R) and fungal ribosomal internal transcribed spacers (region ITS2; primers IT3 and ITS4) was performed as described previously (Frey et al. 2020, Frey et al. 2021). For qPCR analyses, 2.5 ng DNA in a total volume of 6.6 µL and 8.4 µL GoTaq qPCRMaster Mix (Promega, Switzerland), containing 1.8 mM of each primer and 0.2 mg mL-1 of BSA, were used. The PCR conditions consisted of an initial denaturation at 95 ºC for 10 min, 40 cycles of denaturation at 95 ºC for 40 s, annealing at 58 ºC for 40 s and elongation at 72 ºC for 60 s followed by the final data acquisition step at 80 ºC for 60 s. The specificity of the amplification products was confirmed by melting-curve analysis. Three standard curves per target region (correlations ≥0.997) were obtained using tenfold serial dilutions (10-1 to 10-9 copies) of plasmids generated from cloned targets (Frey et al. 2020). Data were converted to represent the average copy number of targets per μg DNA and per g soil. Vegetation properties Vascular plant biomass was measured from a randomly placed 30 x 30 cm quadrat at each plot. To measure aboveground biomass (AGB) of plants, the aboveground layer of vegetation was cut and removed, dried at 70 °C for 24 h and weighed to obtain biomass per unit area. AGB was estimated as the biomass of graminoids plus forbs; total biomass of mosses was also estimated. Graminoid leaf N concentration was analysed from dried and ground leaf material using a LECO CNS-2000 analyser (LECO Corporation, Saint Joseph, MI, USA). Belowground biomass (BGB) of vascular plants was estimated from a soil core of 3 cm in diameter taken from the 10 cm upper soil stratum (excluding aboveground plant material) at each quadrat. Roots were extracted from the soil cores by rinsing in water using a 250-μm sieve, dried at 70 °C for 24 hours and weighed to obtain biomass per unit area. Root to shoot ratio was calculated as dry weight of BGB per cm2 divided by dry weight of AGB per cm2, and the total vascular plant biomass as the sum of AGB and BGB. Invertebrate community Enchytraied and nematode biomass was estimated from 3 soil cores of 3 cm in diameter taken from the upper 4 cm soil stratum (including litter layer) at each plot. Enchytraieds were extracted using wet funnels (O'Connor 1962) from a pooled sample of one half of each of the three soil cores, counted live, and classified into size classes (length 0-2, 2.1-4, 4.1-6, 6.1-8, 8.1-10, 10.1-12 or >12 mm) and their biomass was calculated according to Abrahamsen (1973). Nematodes were also extracted using wet funnels (Sohlenius 1979) from a pooled sample of a quarter of each of the three soil cores, counted live and preserved in 70% ethanol. Fifty individuals from each sample were identified and classified by trophic group (bacterivore, fungivoe, herbivore, omnivore, predator; Yeates et al. 1993). Soil micro-arthropods were extracted using a modified high-gradient-extractor (MacFayden 1961) from soil cores of 5.4 cm in diameter, taken from the upper 4 cm soil straum (including litter layer) at each plot. Total micro-arthropod biomass was calculated as the sum of all individual species' biomasses, obtained using length-weight regressions (see Robinson et al. 2021), and abundance of individual trophic groups (microbivore/detritivore, herbivore, omnivore, predator) calculated. Epigeal invertebrates were sampled by deploying five pitfall traps in each plot. White plastic cups of 7 cm in diameter and 8.5 cm in depth were filled with 10 ml of ethylene glycol and 30 ml of stream water, and left for 48 h before collection. Samples from the five traps at each plot were combined into a 250-μm sieve and stored in 70% ethanol. Invertebrate activity density (abundance) was estimate as the total number of individuals in the five traps, and total biomass as the sum of all individual species' biomasses. Invertebrates were identified to species level where possible and split into trophic groups, exluding adult Diptera, Hymenoptera, and Lepidoptera. Further details of sampling and collection of epigeal invertebrates are detailed in Robinson et al. (2018). References: Abrahamsen G. (1973) Studies on body-volume, body-surface area, density, and live weight of enchytraeidae (Oligochaeta). Pedobiologia 13: 6–15. Frey B, Carnol M, Dharmarajah A, Brunner I, Schleppi P. (2020) Only minor changes in the soil microbiome of a sub-alpine forest after 20 years of moderately increased nitrogen loads. Frontiers in Forests and Global Change 3: 77. Frey B, Walthert L, Perez-Mon C, Stierli B, Köchli R, Dharmarajah A, Brunner I (2021) Deep soil layers of drough-exposed forests harbor poorly known bacterial and fungal communities. Frontiers in Microbiology 12: 1061. MacFayden A. (1961) Improved funnel-type extractors for soil arthropods. Journal of Animal Ecology 30: 171–184. O’Connor FB. (1962) The extraction of Enchytraeidae from soil. In: P. W. Murphy (Ed.) Progress in soil zoology. Butterworth, London, UK; 279–285. Robinson SI, McLaughlin ÓB, Marteinsdóttir B, O'Gorman EJ. (2018) Soil temperature effects on the structure and diversity of plant and invertebrate communities in a natural warming experiment. Journal of Animal Ecology 87: 634–46. Robinson SI, Mikola J, Ovaskainen O, O’Gorman EJ. (2021) Temperature effects on the temporal dynamics of a subarctic invertebrate community. Journal of Animal Ecology 90: 1217-1227. Sohlenius B. (1979) A carbon budget for nematodes, rotifers and tardigrades in a Swedish coniferous forest soil. Holarctic Ecology 2: 30–40. Tiegs SD, Clapcott JE, Griffiths NA, Boulton AJ. (2013) A standardized cotton-strip assay for measuring organic-matter decomposition in streams. Ecological Indicators 32: 131–139. Yeates GW, Bongers T, De Goede RGM, Freckman DW, Georgieva SS. (1993) Feeding habits in soil nematode families and genera—an outline for soil ecologists. Journal of Nematology 25: 315–331. This is a dataset of soil physiochemical properties, bacterial and fungal abundance, and above and belowground plant and invertebrate biomass, sampled at 40 plots in the Hengill geothermal valley, Iceland, from 15th to 22nd August 2018. The plots span a temperature gradient of 10-35 °C over the sampling period, and this temperature gradient is consistent over time. The dataset also includes data on the decomposition rate of soil organic matter, which was sampled at 60 plots in the Hengill valley from May to July 2015. See README_Robinson_Hengill2018.txt 

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    Authors: Arnald Puy; Bruce Lankford; Jonas Meier; Saskia van der Kooij; +1 Authors

    Abstract An assessment of the human impact on the global water cycle requires estimating the volume of water withdrawn for irrigated agriculture. A key parameter in this calculation is the irrigation efficiency, which corrects for the fraction of water lost between irrigation withdrawals and the crop due to management, distribution or conveyance losses. Here we show that the irrigation efficiency used in global irrigation models is flawed for it overlooks key ambiguities in partial efficiencies, irrigation technologies, the definition of ‘large-scale’ irrigated areas or managerial factors. Once accounted for, these uncertainties can make irrigation withdrawal estimates fluctuate by more than one order of magnitude at the country level. Such variability is larger and leads to more extreme values than that caused by the uncertainties related with climate change. Our results highlight the need to embrace deep uncertainties in irrigation efficiency to prevent the design of shortsighted policies at the river basin-water-agricultural interface.

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    Environmental Research Letters
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    Environmental Research Letters
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    Wageningen Staff Publications
    Article . 2022
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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: Barreaux, Antoine; Higginson, Andrew; Bonsall, Michael; English, Sinead;

    Here, we investigate how stochasticity and age-dependence in energy dynamics influence maternal allocation in iteroparous females. We develop a state-dependent model to calculate the optimal maternal allocation strategy with respect to maternal age and energy reserves, focusing on allocation in a single offspring at a time. We introduce stochasticity in energetic costs– in terms of the amount of energy required to forage successfully and individual differences in metabolism – and in feeding success. We systematically assess how allocation is influenced by age-dependence in energetic costs, feeding success, energy intake per successful feeding attempt, and environmentally-driven mortality. First, using stochastic dynamic programming, we calculate the optimal amount of reserves M that mothers allocate to each offspring depending on their own reserves R and age A. The optimal life history strategy is then the set of allocation decisions M(R, A) over the whole lifespan which maximizes the total reproductive success of distant descendants. Second, we simulated the life histories of 1000 mothers following the optimisation strategy and the reserves at the start of adulthood R1, the distribution of which was determined, the distribution of which was determined using an iterative procedure as described . For each individual, we calculated maternal allocation Mt, maternal reserves Rt, and relative allocation Mt⁄Rt at each time period t. The relative allocation helps us to understand how resources are partitioned between mother and offspring. Third, we consider how the optimal strategy varies when there is age-dependence in resource acquisition, energetic costs and survival. Specifically, we include varying scenarios with an age-dependent increase or a decrease with age in energetic costs (c_t), feeding success (q_t), energy intake per successful feeding attempt (y_t), and environmentally-driven extrinsic mortality rate (d_t) (Table 2). We consider the age-dependence of parameters one at a time or in pairs, altering the slope, intercept, or asymptote of the age-dependence (linear or asymptotic function). Our aim is to identify whether the observed reproductive senescence can arise from optimal maternal allocation. As such, we do not impose a decline in selection in later life as all offspring are equally valuable at all ages (for a given maternal allocation), and there are no mutations. For each scenario, we run the backward iteration process with these age-dependent functions, obtain the allocation strategy, and simulate the life history of 1000 individuals based on the novel strategy. We then fit quadratic and linear models to the reproduction of these 1000 individuals using the lme function, nlme package in R. For these models, the response variable is the maternal allocation Mt and explanatory variables are the time period t and t2 (for the quadratic fit only), with individual identity as a random term. We use likelihood ratio tests to compare linear and quadratic models using the anova function (package nlme) with the maximum-likelihood method. If the comparison is significant (p-value <0.05), we considered the quadratic model to have a better fit, otherwise the linear model is considered more parsimonious. We were particularly interested in identifying scenarios where the fit was quadratic with a negative quadratic term. For each scenario, the pseudo R2 conditional value (proportion of variance explained by the fixed and random terms, accounting for individual identity) is calculated to assess the goodness-of-fit of the lme model, on a scale from 0 to 1, using the “r.squared” function, package gabtool. All calculations and coding are done in R. Iteroparous parents face a trade-off between allocating current resources to reproduction versus maximizing survival to produce further offspring. Optimal allocation varies across age, and follows a hump-shaped pattern across diverse taxa, including mammals, birds and invertebrates. This non-linear allocation pattern lacks a general theoretical explanation, potentially because most studies focus on offspring number rather than quality and do not incorporate uncertainty or age-dependence in energy intake or costs. Here, we develop a life history model of maternal allocation in iteroparous animals. We identify the optimal allocation strategy in response to stochasticity when energetic costs, feeding success, energy intake, and environmentally-driven mortality risk are age-dependent. As a case study, we use tsetse, a viviparous insect that produces one offspring per reproductive attempt and relies on an uncertain food supply of vertebrate blood. Diverse scenarios generate a hump-shaped allocation: when energetic costs and energy intake increase with age; and also when energy intake decreases, and energetic costs increase or decrease. Feeding success and mortality risk have little influence on age-dependence in allocation. We conclude that ubiquitous evidence for age-dependence in these influential traits can explain the prevalence of non-linear maternal allocation across diverse taxonomic groups.

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    ZENODO
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    DRYAD
    Dataset . 2022
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      ZENODO
      Dataset . 2022
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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: Shao, Junjiong; Zhou, Xuhui; van Groenigen, Kees; Zhou, Guiyao; +9 Authors

    Aim: Climate warming and biodiversity loss both alter plant productivity, yet we lack an understanding of how biodiversity regulates the responses of ecosystems to warming. In this study, we examine how plant diversity regulates the responses of grassland productivity to experimental warming using meta-analytic techniques. Location: Global Major taxa studied: Grassland ecosystems Methods: Our meta-analysis is based on warming responses of 40 different plant communities obtained from 20 independent studies on grasslands across five continents. Results: Our results show that plant diversity and its responses to warming were the most important factors regulating the warming effects on plant productivity, among all the factors considered (plant diversity, climate and experimental settings). Specifically, warming increased plant productivity when plant diversity (indicated by effective number of species) in grasslands was lesser than 10, whereas warming decreased plant productivity when plant diversity was greater than 10. Moreover, the structural equation modelling showed that the magnitude of warming enhanced plant productivity by increasing the performance of dominant plant species in grasslands of diversity lesser than 10. The negative effects of warming on productivity in grasslands with plant diversity greater than 10 were partly explained by diversity-induced decline in plant dominance. Main Conclusions: Our findings suggest that the positive or negative effect of warming on grassland productivity depends on how biodiverse a grassland is. This could mainly owe to differences in how warming may affect plant dominance and subsequent shifts in interspecific interactions in grasslands of different plant diversity levels.

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    ZENODO
    Dataset . 2023
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    Dataset . 2022
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      ZENODO
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    Authors: Carla Zarbà; Gaetano Chinnici; Giovanni La Via; Salvatore Bracco; +2 Authors

    In the transition from linear production systems, unsustainable from the point of view of resources, to a model that finds strength in environmental, social and economic sustainability, the circular economy paradigm is the foundation that facilitates the planetary agro-ecological transition. The European Union has taken a number of steps (including the Circular Economy Package of Directives) shaping circularity as a wide-ranging driver measure involving many sectors. The paper intends to provide a regulatory framework on the current general situation regarding circularity in European Union, in order to extrapolate and give evidence to the aspects that intersect the agri-food sector. This is not only because they are poorly addressed in the literature, but also because there is a lack of regulatory instruments on the circular economy specifically addressing this area of interest. For this purpose, the analysis focuses on waste and residue/scrap management issues, recognized by law as by-products and end-of-waste status, as they are covered by circular economy legislation and as they can be applied to the agri-food sector. The latter allow the implementation of circularity strategies in the agri-food sector and, given the numerousness of production chains and the peculiarities of each of them, various regeneration and/or reuse processes of specific resources may be depicted. The intent is to provide useful knowledge on how to implement sustainable waste management, also proposing a concrete case on a by-product of olive oil processing, through which it is possible to highlight how the correct application of regulations favors the adoption of circular economic and management models in the firms involved, as well as informing the relevant economic operators on the possible profiles of legal liability that may arise from insufficient knowledge. Furthermore, this paper delves into the European Green Deal’s Strategy as it enriches the circular economy paradigm with new facets. NextGenerationEU and the National Recovery and Resilience Plan financially support this strategy in the aftermath of the socioeconomic crisis from COVID-19 in the EU Member States. This is in order to achieve the objective of achieving the agro-ecological transition.

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    Sustainability
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    ZENODO
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    Authors: Leybourne, Daniel J; Preedy, Katharine F; Valentine, Tracy A; Bos, Jorunn I B; +1 Authors

    1. Aphids are abundant in natural and managed vegetation, supporting a diverse community of organisms and causing damage to agricultural crops. Due to a changing climate, periods of drought are anticipated to increase, and the potential consequences of this for aphid-plant interactions are unclear. 2. Using a meta-analysis and synthesis approach, we aimed to advance understanding of how increased drought incidence will affect this ecologically and economically important insect group, and to characterise any potential underlying mechanisms. We used qualitative and quantitative synthesis techniques to determine whether drought stress has a negative, positive, or null effect on aphid fitness and examined these effects in relation to 1) aphid biology, 2) geographical region, 3) host plant biology. 3. Across all studies, aphid fitness is typically reduced under drought. Subgroup analysis detected no difference in relation to aphid biology, geographical region, or the aphid-plant combination, indicating the negative effect of drought on aphids is potentially universal. Furthermore, drought stress had a negative impact on plant vigour and increased plant concentrations of defensive chemicals, suggesting the observed response of aphids is associated with reduced plant vigour and increased chemical defence in drought-stressed plants. 4. We propose a conceptual model to predict drought effects on aphid fitness in relation to plant vigour and defence to stimulate further research. Please check the ReadMe for an explanation of the values included in the dataset. Please note that n/a values are included in the Global_Dataset tab for plant meta-analysis data (_Plant_Vigour, _Plant_Defence, and _Plant_Nutrition), these indicate studies that did not report these parameters. Data was collected and curated using standard systematic literature synthesis approaches. The effect size (Hedges' g) reported in the dataset was calculated from extracted means and standard deviations.

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    ZENODO
    Dataset . 2021
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    DRYAD
    Dataset . 2021
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    Data sources: Datacite
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      ZENODO
      Dataset . 2021
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      Dataset . 2021
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    Authors: Smith, Linnea C; Orgiazzi, Alberto; Eisenhauer, Nico; Cesarz, Simone; +10 Authors

    The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types. Location: Europe Time period: 2018 Major taxa studied: Microbial community (fungi and bacteria) We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change. [Methods] Soil samples were collected during the 2018 LUCAS soil sampling campaign. Soil chemical and physical properties were measured at the Joint Research Centre in Ispra, Italy (Orgiazzi et al., 2018). Soil microbial respiration and biomass, as well as water content and water holding capacity, were measured in the Eisenhauer lab of the German Centre for Integrative Biodiversity Research. Fungi/Bacteria was measured by fatty acid analysis by Felipe Bastida at CEBAS CSIC. Climate and geographical data were harvested from various databases, which are listed in Appendix 1 (data sources) of the associated paper. For more details on the soil sampling and physical and chemical properties, see: Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., & Fernández-Ugalde, O. (2018). LUCAS Soil, the largest expandable soil dataset for Europe: a review. European Journal of Soil Science, 69(1), 140-153. https://doi.org/10.1111/ejss.12499 For more details on the measurements of soil microbial respiration and biomass, fatty acids, and water holding capacity, see the supplementary methods of the associated paper (Appendix 2). [Usage Notes] Fatty acid analysis was performed for a subset of 267 samples. Water holding capacity and associated measurements of basal respiration was analyzed in a subset of 100 samples. The samples that were not in these subsets have NA values for the columns associated with these measurements. In order to protect the precise locations of the LUCAS sampling sites, latitude and longitude values could not be given. The approximate location of each sampling site is instead described by the NUTS3 region. If you wish to replicate the structural equation modeling described in the paper, for which latitude is required, please get in touch. A description of each column is available in the associated metadata file. Deutsche Forschungsgemeinschaft, Award: FZT 118-202548816. European Research Council, Award: 694368. European Commission. Directorate-General for the Environment. Direction Générale Opérationnelle Agriculture, Ressources Naturelles et Environnement du Service Public de Wallonie. Eurostat. Peer reviewed

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    ZENODO
    Dataset . 2022
    License: CC 0
    Data sources: ZENODO
    DRYAD
    Dataset . 2022
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    Data sources: Datacite
    Digital.CSIC
    Dataset . 2021
    License: CC 0
    Data sources: Datacite
    Digital.CSIC
    Dataset . 2021 . Peer-reviewed
    Data sources: Digital.CSIC
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      ZENODO
      Dataset . 2022
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      Dataset . 2022
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      Dataset . 2021
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      Dataset . 2021 . Peer-reviewed
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    Authors: Warren-Thomas, Eleanor; Nelson, Luke; Juthong, Watinee; Bumrungsri, Sara; +7 Authors

    Monocultural rubber plantations have replaced tropical forest, causing biodiversity loss. While protecting intact or semi-intact biodiverse forest is paramount, improving biodiversity value within the 11.4 million hectares of existing rubber plantations could offer important conservation benefits, if yields are also maintained. Some farmers practice agroforestry with high-yielding clonal rubber varieties to increase and diversify incomes. Here, we ask whether such rubber agroforestry improves biodiversity value or affects rubber yields relative to monoculture. We surveyed birds, fruit-feeding butterflies and reptiles in 25 monocultural and 39 agroforest smallholder rubber plots in Thailand, the world’s biggest rubber producer. Management and vegetation structure data were collected from each plot, and landscape composition around plots was quantified. Rubber yield data were collected for a separate set of 34 monocultural and 47 agroforest rubber plots in the same region. Reported rubber yields did not differ between agroforests and monocultures, meaning adoption of agroforestry in this context should not increase land demand for natural rubber. Butterfly richness was greater in agroforests, where richness increased with greater natural forest extent in the landscape. Bird and reptile richness were similar between agroforests and monocultures, but bird richness increased with the height of herbaceous vegetation inside rubber plots. Species composition of butterflies differed between agroforests and monocultures, and in response to natural forest extent, while bird composition was influenced by herbaceous vegetation height within plots, the density of non-rubber trees within plots (representing agroforestry complexity), and natural forest extent in the landscape. Reptile composition was influenced by canopy cover and open habitat extent in the landscape. Conservation priority and forest-dependent birds were not supported within rubber. Synthesis and applications. Rubber agroforestry using clonal varieties provides modest biodiversity benefits relative to monocultures, without compromising yields. Agroforests may also generate ecosystem service and livelihood benefits. Management of monocultural rubber production to increase inter-row vegetation height and complexity may further benefit biodiversity. However, biodiversity losses from encroachment of rubber onto forests will not be offset by rubber agroforestry or rubber plot management. This evidence is important for developing guidelines around biodiversity-friendly rubber and sustainable supply chains, and for farmers interested in diversifying rubber production. The accompanying ReadMe.txt file explains the contents of each .csv file, including definitions of each column. Sampling protocols are outlined in the paper in Journal of Applied Ecology.

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    ZENODO
    Dataset . 2019
    License: CC 0
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    DRYAD
    Dataset . 2019
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      Dataset . 2019
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      Dataset . 2019
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    Authors: Wade, Ruth N.; Karley, Alison J.; Johnson, Scott N.; Hartley, Sue E.;

    1. Predicted changes in the frequency and intensity of extreme rainfall events in the UK have the potential to disrupt terrestrial ecosystem function. However, responses of different trophic levels to these changes in rainfall patterns, and the underlying mechanisms, are not well characterised. 2. This study aimed to investigate how changes in both the quantity and frequency of rainfall events will affect the outcome of interactions between plants, insect herbivores (above- and below- ground) and natural enemies. 3. Hordeum vulgare L. plants were grown in controlled conditions and in the field, and subjected to three precipitation scenarios: ambient (based on a local 10 year average rainfall); continuous drought (40% reduction compared to ambient); drought/ deluge (40% reduction compared to ambient at a reduced frequency). The effects of these watering regimes and wireworm (Agriotes species) root herbivory on the performance of the plants, aphid herbivores above-ground (Sitobion avenae, Metapolophium dirhodum and Rhopalosiphum padi), and natural enemies of aphids including ladybirds (Harmonia axyridis) were assessed from measurements of plant growth, insect abundance and mass, and assays of feeding behaviour. 4. Continuous drought decreased plant biomass, whereas reducing the frequency of watering events did not affect plant biomass but did alter plant chemical composition. In controlled conditions, continuous drought ameliorated the negative impact of wireworms on plant biomass. 5. Compared to the ambient treatment, aphid mass was increased by 15% when feeding on plants subjected to drought/ deluge; and ladybirds were 66% heavier when feeding on these aphids but this did not affect ladybird prey choice. In field conditions, wireworms feeding below-ground reduced the number of shoot-feeding aphids under ambient and continuous drought conditions but not under drought/ deluge. 6. Predicted changes in both the frequency and intensity of precipitation events under climate change have the potential to limit plant growth, but reduce wireworm herbivory, while simultaneously promoting above-ground aphid numbers and mass, with these effects transferring to the third trophic level. Understanding the effect of future changes in precipitation on species interactions is critical for determining their potential impact on ecosystem functioning and constructing accurate predictions under global change scenarios. Controlled environment and field experimental dataData file containing all data reported in the paper including plant, soil and insect data from controlled environment and field experiments. First spreadsheet in the data file contains a key to explain all abbreviations used throughout the file.Experimental data.xlsx

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    ZENODO
    Dataset . 2018
    License: CC 0
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
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    B2FIND
    Dataset . 2017
    Data sources: B2FIND
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      Dataset . 2017
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    Authors: Bunyod Holmatov; Arjen Hoekstra; Maarten Krol;

    To reduce greenhouse gas (GHG) emissions, the European Union (EU) has targets for utilizing energy from renewable sources. By 2030, a minimum of 3.5% of energy in the EU���s transport sector should come from renewable biological sources, such as crop residues. This paper analyzed EU���s ���advanced bioethanol��� potential from wheat straw and maize stover and evaluated its environmental (land, water, and carbon) footprint. We differentiated between gross and net bioethanol output, the latter by subtracting the energy inputs in production. Results suggest that the annual amount of the sustainably harvestable wheat straw and maize stover is 81.9 Megatonnes (Mt) at field moisture weight (65.3 Mt as dry weight), yielding 470 PJ as gross (404 PJ as net) advanced bioethanol output. Calculated net advanced bioethanol can replace 2.95% of EU transport sector���s energy consumption. EU���s advanced bioethanol has a land footprint of 0.28 m2 MJ���1 for wheat straw and 0.18 m2 MJ���1 for maize stover. The average water footprint of advanced bioethanol is 173 L MJ���1 for wheat straw and 113 L MJ���1 for maize stover. The average carbon footprint per unit of advanced bioethanol is 19.4 and 19.6 g CO2eq MJ���1 for wheat straw and maize stover, respectively. Using advanced bioethanol can lead to emission savings, but EU���s advanced bioethanol production potential is insufficient to achieve EU���s target of a minimum share of 3.5% of advanced biofuels in the transport sector by 2030, and the associated water and land footprints are not smaller than footprints of conventional bioethanol.

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    ZENODO
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      ZENODO
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    Authors: Robinson, Sinikka; O'Gorman, Eoin; Frey, Beat; Hagner, Marleena; +1 Authors

    Study site This is a dataset of soil physiochemical properties, bacterial and fungal abundance, and above and belowground plant and invertebrate biomass, sampled at 40 soil plots in the Hengill geothermal valley, Iceland, from 15th to 22nd August 2018. The plots, measuring approximately 1 m2, evenly span a temperature gradient of 10-35°C. The dataset also includes data on the decomposition rate of soil organic matter, which was sampled at 60 plots in the Hengill valley from May to July 2015 (see Robinson et al. 2021 for plot details and sampling regime). Soil properties Soil temperature was measured at 5 cm depth at each plot on 15th, 18th, and 22nd August, and a mean plot temperature calculated. Soil physiochemical properties were analysed from 3 soil cores of 3 cm in diameter, taken from the upper 10 cm soil stratum at each plot; one quarter of each subsample was pooled to obtain an estimate per plot. Aboveground plant matter, excluding roots, were removed from each core. Percentage soil moisture was calculated by measuring the weight of one pooled soil sample before and after drying for 24 h in a 70°C drying oven. Soil pH was obtained from 20 g of the dry soil by adding 100 ml distilled water, shaking for 5 min on 150 rpm, letting the sample stand for 2 h, and measuring soil pH from the water layer using an InoLab pH 720 (WTW) probe. Soil PO4, NH4, and NO3 concentrations were analysed from a second pooled soil; 60 g of fresh soil was extracted in 100 ml distilled water, filtered through a GF/C (1.2μm) glass microfiber filter (Whatman, GE Healthcare Europe GmbH), and analysed using a Lachat QuikChem 8000 analyser (Zallweger Analytics, Inc., Lachat Instruments Division, USA). Total mineral N was calculated as the sum of NH4 and NO3. Soil organic matter content (excluding dry root biomass) was calculated as the weight lost from an oven dried (105°C for 24 hours) soil sample after heating at 550 °C for 5 h. Decomposition rate of soil organic matter was measured using the Cotton-strip Assay method (Tiegs et al. 2013) by placing a 2.5 cm x 8 cm strip of Fredrix-brand unprimed 12-oz. heavyweight cotton fabric (Style #548) 5 cm belowground at 60 plots, concurrently with a Maxim Integrated DS1921G Thermocron iButton temperature logger, on 13th May 2015. The strips were collected on 3rd July, rinsed with stream water to remove residual soil, soaked in 96% ethanol for 30 seconds to kill bacteria and halt decomposition, and dried at 60 °C for 12 h. Using a universal testing machine (Instron 5866 with 500 kN tensile holding clamps), maximum tensile strench of each cotton strip was measured. % tensile loss (proxy for decomposition) was calculated as (C-T) / C x 100, where T is the maximum tensile strength for each strip collected from the field, and C is the mean tensile strength of seven control strips, which had not been placed in the ground. See Robinson et al. 2021 for detailed description of plots sampled in 2015. Microbial abundance Bacterial and fungal abundance was estimated from additional soil cores of 3 cm in diameter taken from the upper 4 cm soil stratum (including the litter layer) at each plot. DNA was extracted using the PowerSoil DNA Isolation Kit (Qiagen, Germany). DNA was quantified using the high-sensitivity Qubit assay (Thermo Fisher Scientific, Switzerland). Relative abundances of bacterial and fungal communities were determined by quantitative PCR (qPCR) on an ABI7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA, USA). PCR amplification of partial bacterial small-subunit ribosomal RNA genes (region V1–V3 of 16S; primers 27F and 512R) and fungal ribosomal internal transcribed spacers (region ITS2; primers IT3 and ITS4) was performed as described previously (Frey et al. 2020, Frey et al. 2021). For qPCR analyses, 2.5 ng DNA in a total volume of 6.6 µL and 8.4 µL GoTaq qPCRMaster Mix (Promega, Switzerland), containing 1.8 mM of each primer and 0.2 mg mL-1 of BSA, were used. The PCR conditions consisted of an initial denaturation at 95 ºC for 10 min, 40 cycles of denaturation at 95 ºC for 40 s, annealing at 58 ºC for 40 s and elongation at 72 ºC for 60 s followed by the final data acquisition step at 80 ºC for 60 s. The specificity of the amplification products was confirmed by melting-curve analysis. Three standard curves per target region (correlations ≥0.997) were obtained using tenfold serial dilutions (10-1 to 10-9 copies) of plasmids generated from cloned targets (Frey et al. 2020). Data were converted to represent the average copy number of targets per μg DNA and per g soil. Vegetation properties Vascular plant biomass was measured from a randomly placed 30 x 30 cm quadrat at each plot. To measure aboveground biomass (AGB) of plants, the aboveground layer of vegetation was cut and removed, dried at 70 °C for 24 h and weighed to obtain biomass per unit area. AGB was estimated as the biomass of graminoids plus forbs; total biomass of mosses was also estimated. Graminoid leaf N concentration was analysed from dried and ground leaf material using a LECO CNS-2000 analyser (LECO Corporation, Saint Joseph, MI, USA). Belowground biomass (BGB) of vascular plants was estimated from a soil core of 3 cm in diameter taken from the 10 cm upper soil stratum (excluding aboveground plant material) at each quadrat. Roots were extracted from the soil cores by rinsing in water using a 250-μm sieve, dried at 70 °C for 24 hours and weighed to obtain biomass per unit area. Root to shoot ratio was calculated as dry weight of BGB per cm2 divided by dry weight of AGB per cm2, and the total vascular plant biomass as the sum of AGB and BGB. Invertebrate community Enchytraied and nematode biomass was estimated from 3 soil cores of 3 cm in diameter taken from the upper 4 cm soil stratum (including litter layer) at each plot. Enchytraieds were extracted using wet funnels (O'Connor 1962) from a pooled sample of one half of each of the three soil cores, counted live, and classified into size classes (length 0-2, 2.1-4, 4.1-6, 6.1-8, 8.1-10, 10.1-12 or >12 mm) and their biomass was calculated according to Abrahamsen (1973). Nematodes were also extracted using wet funnels (Sohlenius 1979) from a pooled sample of a quarter of each of the three soil cores, counted live and preserved in 70% ethanol. Fifty individuals from each sample were identified and classified by trophic group (bacterivore, fungivoe, herbivore, omnivore, predator; Yeates et al. 1993). Soil micro-arthropods were extracted using a modified high-gradient-extractor (MacFayden 1961) from soil cores of 5.4 cm in diameter, taken from the upper 4 cm soil straum (including litter layer) at each plot. Total micro-arthropod biomass was calculated as the sum of all individual species' biomasses, obtained using length-weight regressions (see Robinson et al. 2021), and abundance of individual trophic groups (microbivore/detritivore, herbivore, omnivore, predator) calculated. Epigeal invertebrates were sampled by deploying five pitfall traps in each plot. White plastic cups of 7 cm in diameter and 8.5 cm in depth were filled with 10 ml of ethylene glycol and 30 ml of stream water, and left for 48 h before collection. Samples from the five traps at each plot were combined into a 250-μm sieve and stored in 70% ethanol. Invertebrate activity density (abundance) was estimate as the total number of individuals in the five traps, and total biomass as the sum of all individual species' biomasses. Invertebrates were identified to species level where possible and split into trophic groups, exluding adult Diptera, Hymenoptera, and Lepidoptera. Further details of sampling and collection of epigeal invertebrates are detailed in Robinson et al. (2018). References: Abrahamsen G. (1973) Studies on body-volume, body-surface area, density, and live weight of enchytraeidae (Oligochaeta). Pedobiologia 13: 6–15. Frey B, Carnol M, Dharmarajah A, Brunner I, Schleppi P. (2020) Only minor changes in the soil microbiome of a sub-alpine forest after 20 years of moderately increased nitrogen loads. Frontiers in Forests and Global Change 3: 77. Frey B, Walthert L, Perez-Mon C, Stierli B, Köchli R, Dharmarajah A, Brunner I (2021) Deep soil layers of drough-exposed forests harbor poorly known bacterial and fungal communities. Frontiers in Microbiology 12: 1061. MacFayden A. (1961) Improved funnel-type extractors for soil arthropods. Journal of Animal Ecology 30: 171–184. O’Connor FB. (1962) The extraction of Enchytraeidae from soil. In: P. W. Murphy (Ed.) Progress in soil zoology. Butterworth, London, UK; 279–285. Robinson SI, McLaughlin ÓB, Marteinsdóttir B, O'Gorman EJ. (2018) Soil temperature effects on the structure and diversity of plant and invertebrate communities in a natural warming experiment. Journal of Animal Ecology 87: 634–46. Robinson SI, Mikola J, Ovaskainen O, O’Gorman EJ. (2021) Temperature effects on the temporal dynamics of a subarctic invertebrate community. Journal of Animal Ecology 90: 1217-1227. Sohlenius B. (1979) A carbon budget for nematodes, rotifers and tardigrades in a Swedish coniferous forest soil. Holarctic Ecology 2: 30–40. Tiegs SD, Clapcott JE, Griffiths NA, Boulton AJ. (2013) A standardized cotton-strip assay for measuring organic-matter decomposition in streams. Ecological Indicators 32: 131–139. Yeates GW, Bongers T, De Goede RGM, Freckman DW, Georgieva SS. (1993) Feeding habits in soil nematode families and genera—an outline for soil ecologists. Journal of Nematology 25: 315–331. This is a dataset of soil physiochemical properties, bacterial and fungal abundance, and above and belowground plant and invertebrate biomass, sampled at 40 plots in the Hengill geothermal valley, Iceland, from 15th to 22nd August 2018. The plots span a temperature gradient of 10-35 °C over the sampling period, and this temperature gradient is consistent over time. The dataset also includes data on the decomposition rate of soil organic matter, which was sampled at 60 plots in the Hengill valley from May to July 2015. See README_Robinson_Hengill2018.txt 

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    Authors: Arnald Puy; Bruce Lankford; Jonas Meier; Saskia van der Kooij; +1 Authors

    Abstract An assessment of the human impact on the global water cycle requires estimating the volume of water withdrawn for irrigated agriculture. A key parameter in this calculation is the irrigation efficiency, which corrects for the fraction of water lost between irrigation withdrawals and the crop due to management, distribution or conveyance losses. Here we show that the irrigation efficiency used in global irrigation models is flawed for it overlooks key ambiguities in partial efficiencies, irrigation technologies, the definition of ‘large-scale’ irrigated areas or managerial factors. Once accounted for, these uncertainties can make irrigation withdrawal estimates fluctuate by more than one order of magnitude at the country level. Such variability is larger and leads to more extreme values than that caused by the uncertainties related with climate change. Our results highlight the need to embrace deep uncertainties in irrigation efficiency to prevent the design of shortsighted policies at the river basin-water-agricultural interface.

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    Environmental Research Letters
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    Wageningen Staff Publications
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