README ====== metadata info for files related to Shepherd et al, 2023 GCBB paper: Novel miscanthus hybrids - European potential ###### tags: `metadata` `file descriptions` :::info ## Location Code Four calibration sites • TWS – Trawscoed Wales • OLI – Oberer Lindenhof Germany • ZAG – Zagreb Croatia • PAC1 or PAC - Piacenza Italy (lowland site) Extra sites used for verification • PAC2 - Piacenza Italy (upland site) • SCH – Schiphol Netherlands • CHV – Chanteloupe France Optional location PS code denotes that data is plot scale ## Genotype Code The project was larger than the paper, the only genotype codes in the datasets connected with the paper are • GRC3 – Miscanthus sinensis x sinensis (M sin x sin) seeded hybrid • GRC9 – Miscanthus giganteus (M x g) • GRC14 – Miscanthus sacchariflorus x sinensis (M sac x sin) seeded hybrid • GRC15 – Miscanthus sacchariflorus x sinensis (M sac x sin) rhizome hybrid ## Data Files: ## Climate and Soil Moisture Data *file Meteo.csv* • Date (dmy) • Location (code) • Precipitation (mm) • Radiation - Global Radiation (MJ m-2 day-1) • tmax – maximum daily temperature (°C) • tmin – minimum daily temperature (°C) • RH – relative humidity (%) • Wind run (km) • PAW – Calculated plant available water (mm) • SWD – soil water deficit (mm) ## Light Interception data *file LightInterception.csv* • Location (code) • Week (number) • Geno (genotype code) • Light (fraction of light at bottom of canopy: light at top of canopy) • N (no. of replicates for mean) • SE (standard error) ## Standing Crop Biomass data *file StandingCropBiomass.csv* • Date (dmy) • Week (number) • Replicate (number) • Location (code) • Geno (genotype code) • DW_THa (10-stem sample dry weight including leaves if present during season scaled up to tonnes per ha) ## Radiation Use Efficiency calculated *file RUEcalculated.csv* RUE is calculated from plant biomass / ((1 –‘light ratio’) x PAR) Where ‘light ratio’ is the fraction of intercepted light bottom of canopy/top of canopy in file light interception.csv and biomass is from StandingCropBiomass.csv and PAR is photosynthetically active radiation, approx.. 50% of net solar radiation. • Date (dmy) • Location_Geno (location code_genotype code) • RUE (Radiation Use Efficency g biomass MJ-1 PAR) Degreeday~LightInterception file Degreeday~lightinterception.csv Data from logistic fitted light interception (LI) compared to measured LI against degreeday values (i.e. accumulated degrees) . • Date (dmy) • Location (Location code) • Geno (Genotype code) • Ddcum (degreeday accumulation, deg C) • LI measured (light interception, g MJ-1) • SE meas’d (std error of measured LI) • LI logistic fit (light interception, g MJ-1) ## Biomass Via Logistic Model *file BiomassViaLogisticModel.csv* Calculated Biomass determined from light interception (degreeday accumulation~logistic model) x cumulated PAR x RUE. Listed alongside measured biomass. • Date (dmy) • Location-Geno (Location code – Genotype code) • BiomassYield_logisticmodel (t ha-1 y-1) ## Biomass From Meas'd Harvest Yield *file BiomassMeas'dHarvestYield.csv* Measured biomass harvest yield for comparison with 'Biomass Via Logistic Model' data. • Date (dmy) • Location-Geno (Location code – Genotype code) • BiomassYield_meas'd (t ha-1 y-1) ## ValidationData_DifferentSites *file ValidationDataDifferentSites.csv* Calculated biomass yield determined from light interception (degreeday accumulation~logistic model) x cumulated PAR x RUE. Listed alongside measured biomass harvest yield for new validation sites. • Location (code) • Geno (genotype code) • Meas’dHarvest (t ha-1 y-1) • ModelledHarvest (logistic curve) (t ha-1 y-1) ## ValidationData_SameSitesDifferentYears *file ValidationDataSameSitesDifferentYears.csv* Calculated Biomass determined from light interception (degreeday accumulation~logistic model) x cumulated PAR x RUE. Listed alongside measured biomass for the same calibration sites but for 2022 harvest. • Location (code) • Geno (genotype code) • Meas’dHarvest (t ha-1 y-1) • ModelledHarvest (logistic curve) (t ha-1 y-1) • SE meas’d (standard error of replicate mean for measured data) ## Spatial Data Files for Figures 6(a), 6(b), 7, 8 ### in GCBB paper: Shepherd et al. (2022) Novel Miscanthus hybrids - Modelling productivity on marginal land in Europe using dynamics of canopy development determined by light interception ## EUcchpoly.zip ArcGIS polygon shape file containing all European countries ## hildalu.zip HILDA landuse coverage containing classes of landuse • 0 – no data • 111 - Settlement • 222 - Cropland • 333 - Forest • 444 - Grassland • 555 – Other land, mountains, rock, etc. • 666 - Water ## lu_mask Mask of bioenergy crop restriction • 0 – no bioenergy crops due to mountains, forest, national parks, etc. • 1 – bioenergy crop growth allowed ## Sac_ sin_dm Coverage of dry matter biomass harvest yield (t ha-1 y-1) for M sacchariflorus x sinensis (seed propagated hybrid). ## Sac_ sin_sd Coverage of the std deviation of dry matter biomass harvest yield (t ha-1 y-1) for M sacchariflorus x sinensis (seed propagated hybrid). ## Sin_ sin_dm Coverage of dry matter biomass harvest yield (t ha-1 y-1) for M sinensis x sinensis (seed propagated hybrid). ## Sac_gr_ sin Coverage of difference between dry matter biomass harvest yield (t ha-1 y-1) for M sacchariflorus x sinensis and M sinensis x sinensis (both seed propagated hybrids).