This dataset includes data on the chemical, physical and biological traits of weed seeds of 11 arable weed species in relation to the persistence of these seeds in the soil seedbank within a common-garden burial study. We performed a common garden weed seed burial study at the University of Illinois Crop Sciences Research and Education Center in Savoy, IL (40.048757 N, -88.237206 E), from October 2007 through October 2012. The experiment was arranged in a split-plot design with four replications of the sub-plot variable species nested within main plot variable burial duration (1 to 5 years). Eleven annual weed species were included, spanning a broad range of seed sizes, dormancy types and seedbank persistence: Abutilon theophrasti Medik (velvetleaf), Ambrosia trifida L. (giant ragweed), Amaranthus tuberculatus [Moq]. Sauer (common waterhemp), Bassia scoparia [L.] A. J. Scott (kochia), Chenopodium album L. (common lambsquarters), Ipomoea hederacea Jacq. (ivyleaf morningglory), Panicum miliaceum L. (wild proso millet), Polygonum pensylvanicum L. (Pennsylvania smartweed), Setaria faberi Herrm. (giant foxtail), Setaria pumila [Poir] Roem. (yellow foxtail) and Thlaspi arvense L. (field pennycress). Weed seeds were collected in 2007 from the experimental site and adjoining fields by gently shaking mature inflorescences over a bucket and bulking seeds from multiple plants to form a composite sample for each species. Light seed were removed by processing with a seed cleaner, after which seeds were stored in air tight containers at 4C until burial. Immediately prior to burial, seed viability was assayed with tetrazolium. Burial units consisted of 100 seeds of a given species placed in the bottom of a 2.5 cm deep square tray, 10 cm on a side, made of 0.5 mm stainless steel wire mesh. Tray bottoms were permeable to water, but prevented seeds from escaping. Trays were filled 2 cm deep with soil from a nearby grass sward that had not been cropped for over 30 years, to avoid contamination with weed seeds (verified by elutriating samples of this soil). Within each experimental unit, we excavated a 2 cm deep rectangle 30 cm wide by 40 cm long, and placed trays for each of the 11 species side by side into this depression so that their soil surface was flush with the surrounding soil, leaving a 0.5 cm wire mesh lip exposed in each tray. Each experimental unit was covered by wire mesh with 1 cm square openings to permit access to invertebrate granivores. The study plot was fenced to exclude large vertebrates. Seedling emergence was recorded weekly from March through October every year. Seed trays for a given burial duration treatment were removed in October of the assigned year and seeds recovered via elutriation (Wiles et al. 1996). Recovered seeds were incubated under oscillating temperature conditions (15 C/dark for 10 hr, 25 C/light for 14 hr) for 2 weeks and germination recorded. Ungerminated seeds assessed as viable through tetrazolium testing were considered dormant. SEED TRAITS We measured chemical and physical seed traits on freshly collected seeds following the methods outlined in Tiansawat et al. (2014), using multiple measures of each trait class to provide functional redundancy and allow them to be treated as latent or manifest variables during multivariate analyses. For the chemical defense trait class we measured ortho-dihydroxyphenol (o-DHP) concentration, abundance and diversity of phenolic compounds quantified with high performance liquid chromatography, impact of seed homogenate on brine shrimp survival, and seed removal by invertebrate granivores. Physical traits measured included seed coat thickness, seed mass, and seed coat rupture force. Pairwise interspecific phylogenetic distances were quantified using the phydist subroutine of Phylocom 4.2 (www.phylodiversity.net). Also included is a list of references from the associated literature review.

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--based on the Excel data files--some of which were described in the reports. The scripts depend on the 'score_site' package, and the score site package depends on a number of standard Python libraries (see the score_site install instructions).

This data provides the underlying project-level analysis and data sources complied in response to the DOE request to determine the amount of geothermal capacity that could be available to meet the President's request to double renewable energy capacity by 2020. The enclosed data contains compiled data on individual project names and locations (by geothermal area and region), ownership, estimated nameplate capacity, and project status, and also contains inferred data on the barriers and viability of the project to meet a 2020 development timeline. The analysis of this data is discussed in the attached NREL report.