• Energy Research
• 6. Clean water close
• 2. Zero hunger close
• CN close
• GB close

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

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.

Livestock grazing is among the most intensive land-use activities in grasslands and can affect plant communities directly or indirectly via grazing-induced soil legacies. Under climate change, grasslands are threatened globally by recurrent drought. However, the extent to which drought influences grazing-induced soil legacy effects on plant biomass production and community composition remains largely unexplored. We grew five naturally co-occurring plant species (three dominants and two subordinates) in mixed communities in a glasshouse experiment in live and sterilized soil that had or had not been subjected to 19 years of grazing; these plant communities were then exposed to a subsequent drought. We tested the treatment effects on plant community biomass, proportional aboveground biomass of individual species, arbuscular mycorrhizal (AM) fungal root colonization, and soil nutrient availability. Under drought-free conditions, soils from grazed plots produced significantly higher plant aboveground and total community biomass compared to soils from ungrazed plots. In contrast, plant aboveground and total community biomass were similar between grazed and ungrazed soils under drought conditions. Similarly, soils from grazed plots increased the proportional biomass of dominant species but decreased the proportion of subordinate species; however, the proportional biomass of dominant and subordinate species was similar between grazed and ungrazed soils under drought conditions. Soil NO3--N in grazed soil was significantly higher compared to ungrazed soil. Drought dramatically increased soil NO3--N in sterilized soil and had a more pronounced increase in grazed soil than in ungrazed soil. Arbuscular mycorrhizal fungal root colonization from grazed soil was lower compared to ungrazed soil. Drought significantly increased the soil available phosphorus concentration, as well as plant community AM fungal root colonization. Synthesis. Our study suggests that drought can neutralize positive grazing effects on plant community biomass production via altered plant-soil interactions. Also, we found that drought can alleviate the negative effects of grazing legacies on subordinate species by reducing the competitiveness of dominant species. Our study provides new insights for understanding the underlying mechanisms of grazing effects on grassland productivity under climate change. Please see the README document and the accompanying published article: Duan, DD., Tian, Z., Wu, NN., Feng, XX., Hou, FJ., Nan, ZB., Kardol, P., and Chen, T. 2023. Drought neutralizes positive effects of long-term grazing on grassland productivity through altering plant-soil interactions. Functional Ecology. 

Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants. The updated results are from optimisations runs carried out in response to peer-review comments.

Twenty soil cores were collected from a field site in Lincolnshire in March 2011, three weeks after planting and Nitrogen fertiliser addition. Soil cores of 150-180 millimetre (mm) depth, containing approximately 1.6 kilogram soil (dry weight) were extracted in Polyvinyl chloride (PVC) pipes (height 215 mm depth 102 mm) and stored at 4 degrees centigrade for 30 days. A four-treatment factorial experiment was designed using soils un-amended or amended with biochar and un-wetted or wetted with deionised water (5 replicates per treatment). Soil in all the cores was mixed to 7 centimetre (cm) depth. To half of the cores, biochar (less than 2 mm) was mixed into the soil at a rate of 3 percent soil dry weight (approximately 22 tons per hectare (t ha-1)). After allowing for any potential Carbon dioxide (CO2) flush from newly-mixed soil to equilibrate for seven days, the cores were placed at 16 degrees centigrade in the dark. Un-wetted soil cores were maintained at 23 percent Gravimetric moisture content (GMC), whilst the GMC of 'wetted' soil cores was increased to 28 percent GMC at the time zero (t0) of four wetting events on day 17, 46, 67 and 116. These water addition rates were based on mean and maximum monthly soil GMC measured in the field between 2009-2010. Data from an investigation of the effects of biochar application to soil on greenhouse gas emissions using soil from a bioenergy crop (Miscanthus X. giganteus). Data include physical (bulk density) and chemical analyses of the soil (total carbon (C) and nitrogen (N), extractable ammonium and nitrate), and greenhouse gas (GHG) emissions (carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)) during incubations. Data were collected during two incubation experiments investigating the effects of temperature, soil moisture and soil aeration on biochar induced suppression of GHG emissions. Biochar is a carbon rich substances which is being advocated as a climate mitigation tool to increase carbon sequestration and reduce nitrous oxide emissions.

The dataset comprises of physical and biogeochemical measurements of belowground (root) biomass from across four Scottish saltmarshes. Sites were chosen to represent contrasting habitats types in Scotland, in particular sediment types, vegetation and sea level history. The data provide a quantitative measure of belowground (root) biomass, organic carbon content and belowground (root) carbon. Samples were collected using a wide gauge gouge corer. The samples were processed to determine belowground (root) biomass, the organic carbon was quantified through elemental analysis and these two data sets were combined to calculate the belowground (root) carbon content. The data were collected to help create a detailed picture of saltmarsh carbon storage in surficial soils across Scotland. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1 Soil cores were taken at each sampling location using a wide diameter gouge corer. The location of the sample was recorded using GPS. Prior to analysis the samples were stored at 4 degrees Celsius at the University of St Andrews. Belowground (root) biomass, organic carbon content and belowground (root) carbon data was produced using standard analytical procedures (detailed in the supporting documentation). All laboratory equipment were calibrated in accordance with the laboratory practises at the University of St Andrews. Results were recorded on to lab sheets and transferred into an Excel file. Results were exported as comma separated value (.csv) files for ingestion into the EIDC.

Prediction of the potentially suitable areas of Leonurus japonicus habitability zones with maxent occurrence points：By sorting out the information of Leonurus japonicus specimens recorded in the Chinese Digital Herbarium (CVH, http://www.cvh.ac.cn/), and combining with the L. japonicus presence points in the Global Biodiversity Information Platform (GBIF, https://www.gbif.org/), the existing distribution positions of L. japonicus were preliminarily obtained, and then the corresponding latitude and longitude coordinates of each distribution point were obtained by Baidu coordinate system. All were used for modeling. environmental variables：Species’ ecoloical niches are affected by climate, topography, biology, and other factors. In consideration of the comprehensiveness and complexity of ecological factors, 34 environmental variables which could reflect species’ ecoloical niches were selected. The list included 19 bioclimatic factors, 14 soil factors and a topographic factor (altitude).The current (1970–2000), 2050s (2041–2060), and 2090s (2081–2100) bioclimatic factor data used in this research were derived from the world climate database Worldclim (http://www.worldclim.Org), and the pixel size of the data was 2.5 arc-minutes (-5 km). The climate data of the 2050s and 2090s were obtained from the Beijing Climate Center-Climate System Model-Medium Resolution (BCC-CSM2-MR), one of the Coupled Model Inter-Comparison Project Phase 6 (CMIP6) datasets, which included three scenarios: sustainable development (SSP126), intermediate development (SSP245) and conventional development (SSP585). SSP scenarios have a high accuracy and separation rate and can integrate local development factors, and so are more convincing than CMIP5 data. The data of soil factors and topographic factors were obtained form the World Soil Database (HWSD) of the FAO (http://www.fao.org/faostat/en/#data), and the provincial national vector map were from China’s Ministry of Natural Resources (http://www.mnr.gov.cn/). The environmental variables is in ASCii format. ASCii can be viewed using standard GIS software such as: environmental variables\\climate\\50126\\bio1.asc Naming convention: Type Variables Description UNITS Bio1 Annual Mean Temperature ℃×10 Bioclimatic Bio2 Mean Diurnal Range ℃×10 Variables Bio3 Isothermality 1 Bio4 Temperature Seasonality 1 Bio5 Max Temperatur ℃×10 Bio6 Min Temperature of Coldest Month ℃×10 Bio7 Temperature Annual Range ℃×10 Bio8 Mean Temperature of Wettest Quarter ℃×10 Bio9 Mean Temperature of Driest Quarter ℃×10 Bio10 Mean Temperature of Warmest Quarter ℃×10 Bio11 Mean Temperature of Coldest Quarter ℃×10 Bio12 Annual Precipitation mm Bio13 Precipitation of Wettest Month mm Bio14 Precipitation of Driest Month mm Bio15 Precipitation Seasonality 1 Bio16 Precipitation of Wettest Quarter mm Bio17 Precipitation of Driest Quarter mm Bio18 Precipitation of Warmest Quarter mm Bio19 Precipitation of Coldest Quarter mm T\_GRAVEL Topsoil Gravel Content %vol. Top Soil Variable T\_SAND Topsoil Sand Fraction % wt. T\_SILT Topsoil Silt Fraction % wt. T\_CLAY Topsoil Clay Fraction % wt. T\_USDA\_TEX\_CLASS Topsoil USDA Texture Classification name T\_REF\_BULK\_DENSITY Topsoil Reference Bulk Density kg/dm3 T\_OC Topsoil Organic Carbon % weight T\_PH\_H2O Topsoil pH (H2O) -log(H+) T\_CEC\_CLAY Topsoil CEC (clay) cmol/kg T\_CEC\_SOIL Topsoil CEC (soil) cmol/kg T\_BS Topsoil Base Saturation % T\_TEB Topsoil TEB cmol/kg T\_ESP Topsoil Sodicity (ESP) % T\_ECE Topsoil Salinity (Elco) dS/m Terrain ELEV Elevation m ENMeval package: To avoid overfitting due to the high complexity of the model constructed with the default parameters, which may cause the predicted distribution of the potential habitat of L. japonicus to deviate too much from the actual situation, this study used the ENMeval package in R 4.3.1, and adjusted the two most important parameters, namely, regularization multiplier (RM) and feature combination (FC), to improve the prediction accuracy of the model. CoordinateCleaner：The R software package ‘CoordinateCleaner’ was used to removing records without coordinate precision and suspected outliers. Based on the ‘subset’ ‘clean\_coordinates’ operation in CoordinateCleaner, we obtained the results of bias corrections on the datasets. SpThin package: Spatial thinning of species occurrence records can help address problems associated with spatial sampling biases. Ideally, thinning removes the fewest records necessary to substantially reduce the effects of sampling bias, while simultaneously retaining the greatest amount of useful information. Spatial thinning can be done manually; however, this is prohibitively time consuming for large datasets. Using a randomization approach, the ‘thin’ function in the spThin R package returns a dataset with the maximum number of records for a given thinning distance, when run for sufficient iterations. geosphere package:The geosphere package in the R environment was used to calculate the centroid range shift distance of L. japonicus under different climate change scenarios. SDMTools：The package in R language was used to calculate the location of centroid in the suitable area of Leonurus japonicus under 6 different economic paths in the current and future periods. VIF package: The usdm package provides a set of functions to support dealing with problematic situations in species distribution modelling (e.g., multicollinearity, positional uncertainty).To detect whether predictor variables are subjected to multicollinearity, you may use vif (variance inflation factor) metric, and some methods implemeted in this package including vifstep or vifcor (a stepwise procedure to identify collinear variables). Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have been reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided the scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of the Maxent model were adjusted by using ENMeva1 package of the R environment, and the optimized Maxent model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the Maxent model has a higher degree of optimization. With the AUC of 0.830 our model showed a good predictive performance The results showed that L. japonicus was widely distributed in the current period. The maximum temperature of the warmest month, the minimum temperature of the coldest month, the precipitation of the wettest month, the precipitation of the driest month and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range-shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126-2090s scenario and the highest under the SSP585-2090s scenario.

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.