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The data consists of annual measurements of standing aboveground plant biomass, annual aboveground net primary productivity and annual soil respiration between 1998 and 2012. Data were collected from seven European shrublands that were subject to the climate manipulations drought and warming. Sites were located in the United Kingdom (UK), the Netherlands (NL), Denmark ( two sites, DK-B and DK-M), Hungary (HU), Spain (SP) and Italy (IT). All field sites consisted of untreated control plots, plots where the plant canopy air is artificially warmed during night time hours, and plots where rainfall is excluded from the plots at least during the plants growing season. Standing aboveground plant biomass (grams biomass per square metre) was measured in two undisturbed areas within the plots using the pin-point method (UK, DK-M, DK-B), or along a transect (IT, SP, HU, NL). Aboveground net primary productivity was calculated from measurements of standing aboveground plant biomass estimates and litterfall measurements. Soil respiration was measured in pre-installed opaque soil collars bi-weekly, monthly, or in measurement campaigns (SP only). The datasets provided are the basis for the data analysis presented in Reinsch et al. (2017) Shrubland primary production and soil respiration diverge along European climate gradient. Scientific Reports 7:43952 https://doi.org/10.1038/srep43952 Standing biomass was measured using the non-destructive pin-point method to assess aboveground biomass. Measurements were conducted at the state of peak biomass specific for each site. Litterfall was measured annually using litterfall traps. Litter collected in the traps was dried and the weight was measured. Aboveground biomass productivity was estimated as the difference between the measured standing biomass in year x minus the standing biomass measured the previous year. Soil respiration was measured bi-weekly or monthly, or in campaigns (Spain only). It was measured on permanently installed soil collars in treatment plots. The Gaussen Index of Aridity (an index that combines information on rainfall and temperature) was calculated using mean annual precipitation, mean annual temperature. The reduction in precipitation and increase in temperature for each site was used to calculate the Gaussen Index for the climate treatments for each site. Data of standing biomass and soil respiration was provided by the site responsible. Data from all sites were collated into one data file for data analysis. A summary data set was combined with information on the Gaussen Index of Aridity Data were then exported from these Excel spreadsheet to .csv files for ingestion into the EIDC.

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.

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.

Data was either measured in situ in the field (N2O flux, soil moisture, rainfall and air temperature) or samples were taken, processed, and analysed in the laboratory (soil pH, electrical conductivity (EC), ammonium, nitrate, microbial community composition and crop yield). N2O flux data was measured on a mobile gas chromatograph (GC) system and integrated to obtain peak areas on Peak490Win10Canabis programme. The times, peak areas and sample ID were then exported into a .CHR file and imported into Flux.NET.3.3 which calculated N2O flux as an output in Excel which was exported as .csv file for deposit in EIDC. N2O flux was used to calculate cumulative N2O flux using trapezoidal integration in Excel and saved in a separate .csv file for deposit in EIDC. Soil moisture was measured on Accilmas with data stored as a .csv on a DataSnap that was downloaded and sorted by treatment and saved as a .csv file. Rainfall and air temperature were downloaded from the weather station as .csv file. Soil pH and EC were recorded manually into a notebook and input into an Excel spreadsheet and exported as a .csv file. Soil ammonium and nitrate content was measured using the microplate method using a programme called Gen5. Date was exported into an Excel spreadsheet and absorbance units used to calculate ammonium/nitrate content in milligrams per kilogram using a calibration curve from a set of standards in an Excel spreadsheet. This was exported as a .csv file. Crop growth data was recorded in the field in a notebook and input into an Excel spreadsheet and exported as a .csv file. Crop yield was recorded in a notebook and input into an Excel spreadsheet and exported as a .csv file. Microbial community composition was measured using 16S gene sequencing on an Illumina MiSeq. This generated raw sequencing reads which were processed using Python and filtered using QIIME v1.3.1. creating asv.count.table.csv of counts of each Amplicon Sequence Variants (ASVs) per sample and taxa.table.csv of the taxonomic lineage for each ASVs. This dataset contains field data on nitrous oxide (N2O) emissions, microbial community composition, crop yield and growth and soil biochemical properties. The field trial consisted of three different treatments of control, conventional microplastic addition and biodegradable microplastic addition where winter barley was grown. The data presented are from field and laboratory measurements. Data was collected by the data authors. The field trial was carried out from September 2020 to July 2021 at Henfaes Field Centre, UK. Research was funded through NERC Grant NE/V005871/1. Do agricultural microplastics undermine food security and sustainable development in developing countries?

The Buxton Climate Change Impacts study was established in 1992 on a steep daleside of calcareous grassland outside Buxton, Derbyshire, UK. In five replicate blocks of 3 x 3 m plots, the vegetation has been subjected to climate treatments of winter heating (3C above ambient, Nov-April), summer drought (no rain, July-Aug), summer augmented rainfaill (20% above the long-term average, June-Sept), and two interaction treatments (heating-drought, heating-watered) in addition to replicated controls. The grassland is maintained in a short turf to simulate sheep and cattle grazing each autumn (Oct). In addition to annual point quadrat touches conducted at the whole-plot (9 m2) scale, permanent microsite quadrats were established within each plot in 2008 at the 100 cm2 scale. Species cover and environmental parameters have been monitored in microsites annually (2009-2011 controls only). This data package contains microsite soil depth and pH data; another package contains species cover data.

This dataset contains measures of fitness traits from Eschscholzia californica progeny which were experimentally supplemented with selfed or outcrossed pollen to determine the effects of self-fertilisation on a plant which has a low propensity to self. A glasshouse experiment was conducted using 40 plants. On each plant two flowers were emasculated and the first supplemented with outcrossed pollen and the second with self-pollen. From each supplemented plant, a seed was sowed from the outcrossed fruit and from the selfed fruit. The following fitness traits were recorded; the germination rate, the duration from germination to reproductive maturity (time of first flower), together with the height (cm) and biomass (number of flowers and buds) at reproductive maturity. The dataset was part of a larger experiment looking at the effect of floral resources on the pollination services to isolated plants. We performed a glasshouse experiment using 40 artificially crossed plants. On each plant, we emasculated two flowers and supplemented the first with outcrossed pollen and the second with self-pollen. This involved methodically wiping two dehiscing anthers from a donor plant or the focal plant onto the receptive stigma with dissecting tweezers, before covering it in fine muslin. From each supplemented plant, we sowed a seed from the outcrossed fruit and from the selfed fruit (given that selfed fruits predominantly only produced one seed) into 1L pots. These were then stored under glasshouse conditions before the fitness traits were measured.

This dataset includes the results summary from a lab-scale bioreactor experiment as discussed in the research paper with the same name, published at Processes MDPI (De Groof, V.; Coma, M.; Arnot, T.C.; Leak, D.J.; Lanham, A.B. Adjusting Organic Load as a Strategy to Direct Single-Stage Food Waste Fermentation from Anaerobic Digestion to Chain Elongation. Processes 2020, 8, 1487.). The study comprised two operational phases of duplicate reactors fed with food waste, each set to target a different product. The data comprises a summary on feedstock composition, microbial community analysis and operational conditions and product outcome per operational phase. The archaeal and bacterial community data includes the final sequences of the operational taxonomic units found and their relative abundance in each sample as determined by 16s rRNA amplicon sequencing. The raw data files have been submitted in the specialized EMBL-EBI database and are available under the accession number PRJEB39281. This dataset was prepared and processed in Microsoft Excel from raw analytical data. The bioinformatic processing prior to the microbial community summary in the spreadsheet was done as outlined in the publication, and results were processed via the DNASense data analysis app (applies Rstudio IDE v.3.5.1 with the ampvis v.2.5.8. package). This version includes rarefaction curves and values of alpha-diversity, richness and evenness per sample in the OTU_table tab. Analytical

Supplementary material for the publication " Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G. Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions.

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.

The Characterisation of Feedstocks project provides an understanding of UK produced 2nd generation energy biomass properties, how these vary and what causes this variability. In this project, several types of UK-grown biomass, produced under varying conditions, were sampled. The biomass sampled included Miscanthus, Short Rotation Forestry (SRF) and Short Rotation Coppice (SRC) Willow. The samples were tested to an agreed schedule in an accredited laboratory. The results were analysed against the planting, growing, harvesting and storage conditions (i.e.The provenance) to understand what impacts different production and storage methods have on the biomass properties.The main outcome of this project is a better understanding of the key characteristics of UK biomass feedstocks (focusing on second generation) relevant in downstream energy conversion applications, and howthese characteristics vary by provenance. This Excel Workbook presents the data arising from all experiments carried out under the Characterisation of Feedstocks Project.The data set includes:The sites sampled, the conditions at the time of sampling, provenance data, soil laboratory results and biomass laboratory results.The feedstock studies carried out to yield these data are shown in the “Workbook Details” sheet – this sheet also briefly describes the quality assurance process for the data. As a result of the breadth and depth of data provided in these tables, the ETI anticipates that these data will be useful to a range users includingAcademics whose research focuses on bioenergy crop production or use of bioenergy crops in pre-treatment or conversion technologies;Modellers seeking biomass physical property dataBioenergy project developers seeking to understand their design envelopes;Existing commercial biomass users seeking to understand process performance;Biomass buyers assessing risks and defining fuel specifications.