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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.

1.Perennial bioenergy systems, such as switchgrass and restored prairies, are alternatives to commonly used annual monocultures such as maize. Perennial systems require lower chemical input, provide greater ecosystem services such as carbon storage, greenhouse gas mitigation, and support greater biodiversity of beneficial insects. However, biomass harvest will be necessary in managing these perennial systems for bioenergy production, and it is unclear how repeated harvesting might affect ecosystem services. 2.In this study, we examined how repeated production-scale harvesting of diverse perennial grasslands influences vegetation structure, natural enemy communities (arthropod predators and parasitoids), and natural biocontrol services in two states (Wisconsin and Michigan, USA) over multiple years. 3.We found that repeated biomass harvest reduced litter biomass and increased bare ground cover. Some natural enemy groups, such as ground-dwelling arthropods, decreased in abundance with harvest whereas others, such as foliar-dwelling arthropods increased in abundance. The disparity in responses is likely due to how different taxonomic groups utilize vegetation and differences in dispersal abilities. 4.At the community level, biomass harvest altered community composition, increased total arthropod abundance, and decreased evenness but did not influence species richness, diversity, or biocontrol services. Harvest effects varied with time, diminishing in strength both within the season (for total abundance and evenness), across seasons (for evenness), or were consistent throughout the duration of the study (for community composition). Greater functional redundancy and compensatory responses of the different taxonomic groups may have buffered against the potentially negative effects of harvest on biocontrol services. 5.Synthesis and applications. Our results show that in the short-term, repeated harvesting of perennial grasslands (when insect activity is low) consistently altered vegetation structure but had mixed effects on natural enemy communities and no discernable effects on biocontrol services. However, the long-term effects of repeated harvesting on vegetation structure, natural enemies, and other arthropod-derived ecosystem services such as pollination and decomposition remain largely unknown. Kim et al. 2017 Harvest effects on natural enemy communities and biocontrolData summary tables and site information used in Kim et al. 2017. Harvesting biofuel grasslands has mixed effects on natural enemy communities and no effects on biocontrol services. Journal of Applied Ecology.Kim et al-Harvest effects on natural enemy communities and biocontrol JAE.xlsx

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

The Marsh Ecology Research Program (MERP) was a long-term interdisciplinary study on the ecology of prairie wetlands. A scientific team from a variety of disciplines (hydrology, plant ecology, invertebrate ecology, vertebrate ecology, nutrient dynamics, marsh management) was assembled to design and oversee a long-term experiment on the effects of water-level manipulation on northern prairie wetlands. Ten years of fieldwork (1980 -1989), combines a routine long-term monitoring program and a series of short-term studies, generated a wealth of new and diverse information on the ecology and function of prairie wetlands (Murkin, Batt, Caldwell, Kadlec and van der Valk, 2000). This data set includes belowground macrophyte production data, collected as part of the vegetation section of MERP. Determination of aquatic macrophyte annual net primary production is vital to the understanding of the dynamics of freshwater marshes. Macrophyte biomass, both live and dead, is a major storage compartment for carbon, nitrogen and phosphorus in a marsh and a major potential energy and nutrient source for the faunal component of the marsh ecosystem. Macrophyte communities are also essential structural components of the habitat of both invertebrates and vertebrates. The major objective of the long-term monitoring of aquatic macrophytes was to determine the impact of the wet-dry cycle on macrophyte above and belowground net annual production. Standard harvest techniques were used because they were the most direct, simple and reliable techniques available for estimating net annual primary production of macrophytes per unit area (van der Valk, 1989). In order to estimate net annual belowground macrophyte production, core samples of the belowground biomass were harvested in the late spring and in the fall. Shoot initiation early in the growing season depletes most of the belowground standing crop, and therefore spring sampling was done quickly (within 2 weeks) to capture this state. Underground biomass then reaches its seasonal maxima in the fall and was captured with the fall sampling. The resulting differences between the fall and spring standing crop biomass provided an estimate of net belowground macrophyte production (van der Valk, 1989). References: Murkin, H.R., B.D.J. Batt, P.J. Caldwell, J.A. Kadlec and A.G. van der Valk. 2000a. Introduction to the Marsh Ecology Research Program. In Prairie Wetland Ecology: The Contribution of the Marsh Ecology Research Program. (Eds) H.R. Murkin, A.G. van der Valk and W.R. Clark. pp. 3-15. Ames: Iowa State University Press. van der Valk, A. 1989. Macrophyte production. In Marsh Ecology Research Program: Long-term Monitoring Procedures Manual. (Eds.) E.J. Murkin and H.R. Murkin, pp. 23-29. Manitoba, Canada: Delta Waterfowl Research Station.

Natural potentials for future cropland expansion The potential for the expansion of cropland is restricted by the availability of land resources and given local natural conditions. As a result, area that is highly suitable for agriculture according to the prevailing local biophysical conditions but is not under cultivation today has a high natural potential for expansion. Policy regulations can further restrict the availability of land for expansion by designating protected areas, although they may be suitable for agriculture. Conversely, by applying e.g. irrigation practices, land can be brought under cultivation, although it may naturally not be suitable. Here, we investigate the potentials for agricultural expansion for near future climate scenario conditions to identify the suitability of non-cropland areas for expansion according to their local natural conditions. We determine the available energy, water and nutrient supply for agricultural suitability from climate, soil and topography data, by using a fuzzy logic approach according to Zabel et al. (2014). It considers the 16 globally most important staple and energy crops. These are: barley, cassava, groundnut, maize, millet, oil palm, potato, rapeseed, rice, rye, sorghum, soy, sugarcane, sunflower, summer wheat, winter wheat. The parameterization of the membership functions that describe each of the crops’ specific natural requirements is taken from Sys et al. (1993). The considered natural conditions are: climate (temperature, precipitation, solar radiation), soil properties (texture, proportion of coarse fragments and gypsum, base saturation, pH content, organic carbon content, salinity, sodicity), and topography (elevation, slope). As a result of the fuzzy logic approach, values in a range between 0 and 1 describe the suitability of a crop for each of the prevailing natural conditions at a certain location. The smallest suitability value over all parameters finally determines the suitability of a crop. The daily climate data is provided by simulation results from the global climate model ECHAM5 (Jungclaus et al. 2006) for near future (2011-2040) SRES A1B climate scenario conditions. Soil data is taken from the Harmonized World Soil Database (HWSD) (FAO et al. 2012), and topography data is applied from the Shuttle Radar Topography Mission (SRTM) (Farr et al. 2007). In order to gather a general crop suitability, which does not refer to one specific crop, the most suitable crop with the highest suitability value is chosen at each pixel. In addition the natural biophysical conditions, we consider today’s irrigated areas according to (Siebert et al. 2013). We assume that irrigated areas globally remain constant until 2040, since adequate data on the development of irrigated areas do not exist, although it is likely that freshwater availability for irrigation could be limited in some regions, while in other regions surplus water supply could be used to expand irrigation practices (Elliott et al. 2014). However, it is difficult to project where irrigation practices will evolve, since it is driven by economic investment costs that are required to establish irrigation infrastructure. In principle, all agriculturally suitable land that is not used as cropland today has the natural potential to be converted into cropland. We assume that only urban and built-up areas are not available for conversion, although more than 80% of global urban areas are agriculturally suitable (Avellan et al. 2012). However, it seems unlikely that urban areas will be cleared at the large scale due to high investment costs, growing cities and growing demand for settlements. Concepts of urban and vertical farming usually are discussed under the aspects of cultivating fresh vegetables and salads for urban population. They are not designed to extensively grow staple crops such as wheat or maize for feeding the world in the near future. Urban farming would require one third of the total global urban area to meet only the global vegetable consumption of urban dwellers (Martellozzo et al. 2015). Thus, urban agriculture cannot substantially contribute to global agricultural production of staple crops. Protected areas or dense forested areas are not excluded from the calculation, in order not to lose any information in the further combination with the biodiversity patterns (see chapter 2.3). We use data on current cropland distribution by Ramankutty et al. (2008) and urban and built-up area according to the ESA-CCI land use/cover dataset (ESA 2014). From this data, we calculate the ‘natural expansion potential index’ (Iexp) that expresses the natural potential for an area to be converted into cropland as follows: Iexp = S * Aav The index is determined by the quality of agricultural suitability (S) (values between 0 and 1) multiplied with the amount of available area (Aav) for conversion (in percentage of pixel area). The available area includes all suitable area that is not cultivated today, and not classified as urban or artificial area. The index ranges between 0 and 100 and indicates where the conditions for cropland expansion are more or less favorable, when taking only natural conditions into account, disregarding socio-economic factors, policies and regulations that drive or inhibit cropland expansion. The index is a helpful indicator for identifying areas where cropland expansion could take place in the near future. Further information Detailled information are available in the following publication: Delzeit, R., F. Zabel, C. Meyer and T. Václavík (2017). Addressing future trade-offs between biodiversity and cropland expansion to improve food security. Regional Environmental Change 17(5): 1429-1441. DOI: 10.1007/s10113-016-0927-1 Contact Please contact: Dr. Florian Zabel, f.zabel@lmu.de, Department für Geographie, LMU München (www.geografie.uni-muenchen.de) This research was carried out within the framework of the GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) Project, which has been supported by the German Ministry of Education and Research (BMBF) program on sustainable land management (grant number: 01LL0901E).

We analyze past and anticipated future trends in crop yields, per capita consumption, and population to estimate agricultural land requirements globally by 2050 and 2100. Assuming “business as usual,” higher-income countries are expected to show little or no net growth in cropland by the end of the century, even in the face of moderate climate change. In contrast, in lower-income countries, we project that land requirements will grow dramatically, and climate change will likely double this expansion. Although economic growth is often considered to work in opposition to conservation, accelerating economic development in lower-income countries, which would help alleviate poverty and increase standards of living, would also greatly reduce potential cropland expansion in lower-income countries, even with climate change, owing to slower population growth and improved crop yields that more than offset increased per capita consumption. Combining economic development in low-income countries with reduced consumption in high-income countries could dramatically shrink global cropland requirements by the year 2100 even with moderate climate change. Such a remarkable reduction in cropland area would have enormous benefits for both biodiversity and global climate change.  All of the data files are analyzed using R.

The yield gap for maize across the Ethiopia has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management. The yield gap of a crop grown in a certain location and cropping system is defined as the difference between the yield and biomass under optimum management and the average yield achieved by farmers. Yield under optimum management is labeled as potential yield (Yp) under irrigated conditions or water-limited potential yield (Yw) under rain-fed conditions.Yp is location specific because of the climate, and not dependent on soil properties assuming that the required water and nutrients are non-limiting and can be added through management. Thus, in areas without major soil constraints, Yp is the most relevant benchmark for irrigated systems. Whereas, for rain-fed crops, Yw, equivalent to water-limited potential yield, is the most relevant benchmark. Both Yp and Yw are calculated for optimum planting dates, planting density and region-specific crop variety which is critical in determining the feasible growth duration, particularly in tropical climatic conditions where two or even three crops are produced each year on the same field. Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Yield gaps, thus considering the spatial variation in environment and the production system. This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={c2bbd5ed-fd4c-4a3f-b0b1-113a5d4f3ddf}. The yield gaps plotted in the map were calculated as the average values of 7 years (the year 2004 -2010). The unit is Megagram per hectare (Mg ha-1) which is equivalent to tons ha-1. The climate data at the national scale was made available from the National Aeronautics and Space Administration (NASA), Goddard Institute of Space Studies(https://data.giss.nasa.gov/impacts/agmipcf/agmerra/), AgMERRA.The dataset is stored at 0.25°×0.25° horizontal resolution (~25km). Soil parameter values were extracted from the soil property maps of Africa at 1 km x 1 km resolution (http://www.isric.org/data/soil-property-maps-africa-1-km). Maize yields (Mg ha-1) and fertilizer application (Nitrogen and Phosphorus) rates over seven years (2004 - 2010) at administrative zone level have been collected from the Central Statistical Agency, Ethiopia.

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.