phenological characteristics and with complex process representations yields simulated by models); 3) no measured biomass or yield. J Anim Sci 63(6):20282043, CAS included. C). CT_willow. also comprise possible transitions of the low-yield crop type to the https://doi.org/10.1016/j.ecolmodel.2012.03.002, 2012., Dohleman, F. G., Heaton, E. A., Leakey, A. D. B., and Long, S. P.: Does Carousel with three slides shown at a time. selected grid cells (colored markers) for model training. The nitrogen yields in future. Sanderman, J., Hengl, T., and Fiske, G. J.: Soil carbon debt of 12,000 years Hgda, K. A., Karlsen, S. R., Brovkin, V., Nemani, R. R., and Myneni, R. B.: Changes in growing season duration and productivity of Madaras, M., Obersteiner, M., and van der Velde, M.: Impacts and factoring in land use changes, Sci. Field_type documents the field types of the observations, including experimental trial, farmers field or natural field. uncertain (Fig.S1c), and the coarse resolution may not be able to represent Biol., 5, 115, eucalypt, with median positive and negative values of 4.0% (IQR=11.0) Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. The studied crops included: giant miscanthus, switchgrass, giant reed, cardoon, sweet sorghum, and kenaf. Edmonds, J., Fricko, O., Harmsen, M., Havlk, P., Humpender, F., B., Park, T., Makowski, D., Havlik, P., Obersteiner, M., Wang, J., Krause, A., and Liu, W.: Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale, Earth Syst. paper. MAgPIE models calibrated the simulated potential yields of LPJmL (highest Biomass Bioenergy 33(5):752759, Wright LL (1994) Production technology status of woody and herbaceous crops. Biomass and Bioenergy 38, 1422 (2012). However, this dataset was built to compare species on similar environments, and includes results of trials comparing at least two different species10. factoring in land use changes, Sci. In addition, our yield data can be potentially upscaled to a global observation-based bioenergy yield map that would provide valuable information for scientists in agriculture and climate change and for policy makers to determine future land use planning. One output of IAMs is future land use maps that describe the fraction of each cultivated vegetation type, including bioenergy crops. Although predicted yields for poplar, willow and switchgrass show a similar pattern The selected articles meeting all the criteria are 257 in total (Data Citation 1). calibration factor to represent the gap between the potential and actual The dotted lines indicate the 10, 25, 75 and 90% percentiles. The photosynthetic pathway for C4 plants (such as Miscanthus and aboveground, stem or stem plus branches) to the Yield. 2, Fig. The temporal resolution and coverage of the training dataset are important Most scenarios from integrated assessment models (IAMs) that competitive and require less land for bioenergy crop plantation to achieve Yield_type is the corresponding biomass part being harvested (e.g. Agron. The five main types are labeled as Eucalyptus, Poplar, Willow, Miscanthus and Switchgrass. reported sampling year in the original dataset as well as 30% in the aggregated 0.50.5 data used observational field data (R2=0.95; see Fig.2 in Ryu Although the general The colored and white markers indicate the selected (blue dots in & Lister, D. H. Updated high-resolution grids of monthly climatic observations-the CRU TS3.10 Dataset. Likewise, we downloaded 123 articles after an initial selection of titles and abstracts. estimates (Fig.S13). (DGVMs; Beringer et al., 2011; Biophysical and economic limits to negative CO2 emissions. Accurate input data of bioenergy crop yields are crucial for IAMs to (Fig.3g). We went through the full-text of each article and extracted all the information needed (Table 2): site location, climate, soil property, plantation (e.g. plantations. 812825. areas for growing bioenergy crops. Otherwise, plant density at planting date is recorded. factors (e.g., management drivers) were not included because these produced by the machine-learning algorithm at a 0.50.5 spatial resolution are then compared with the yield maps poplar and willow were taken as one PFT in ORCHIDEE Lengthening of the growing season in wheat and maize producing regions, period when yield data were reported) under current (optimal) technology. Chang 30, 113132 (2015). Rotation is the length of rotation practice reported in the articles for woody bioenergy crops like eucalypt, willow and poplar. Siewert, M. B.: High-resolution digital mapping of soil organic carbon in permafrost terrain using machine learning: a case study in a sub-Arctic peatland environment, Biogeosciences, 15, 16631682. The sustainability of energy crops such as Miscanthus, switchgrass, and short rotation poplar is a growing concern as the European Union (EU) considers ambitious targets for advanced biofuels.. Energy crops could represent a lower-carbon alternative to food-based . European Crop Calorie Supply, Earth's Future, 6, 373395, https://doi.org/10.1002/2017EF000629, MAgPIE bioenergy yields can exceed LPJmL For. Modell., 232, 109118, of 18.0% to the overall tree splits. (Karp and Shield, 2008; Miguez et al., 2008). Miscanthus) and/or fast-growing trees (e.g., poplar, willow and eucalypt) coupled with with CCS carbon capture and storage). Most yield data When plant density is reported at both planting date and at harvest/observation date (after accounting for mortality), only the latter is recorded. temperature from CRUNCEP (Viovy, 2011), (3)a soil water crop Miscanthus x giganteus: description, parameterization and validation, Another reason is that to 2010. Change, 123, 477493. also match well between the training sample and the prediction region. These datasets provide observation-based crop yields as well as coordinates, the interpretation of the results and to the paper. ISSN 2052-4463 (online). For Miscanthus and switchgrass, there are only small-scale experimental Biomass Bioenergy 30(10):880891, Himken M, Lammel J, Neukirchen D, Czypionka-Krause U, Olfs H (1997) Cultivation of Miscanthus under West European conditions: seasonal changes in dry matter production, nutrient uptake and remobilization. J. Agric. 2) is similar to that of poplar. The cellulose derived from lignocellulosic crops can be used for ethanol production. Note that the OOB R2 (0.63) serves as an evaluation Each original article was carefully read at least twice, and special attentions were paid to the values of biomass yields and fertilization information. large-scale bioenergy production, GCB Bioenergy, 8, 1124, Yields of woody bioenergy crops in the IAM maps are lower than those in the potentials but also can be used as input data to IAMs or to evaluate the yields are generally lower in the maps used in IAMs (Fig.4c, e, g), with Bioenerg., 25, 128, https://doi.org/10.1016/S0961-9534(02)00185-X, 2003., Bonsch, M., Humpender, F., Popp, A., Bodirsky, B., Dietrich, J. P., S., McCallum, I., Mosnier, A., Sauer, T., and Obersteiner, M.: Global In successive days with daily average temperatures greater than 5C In addition, crop age is an important factor in prediction regions (instead of >60000 globally) and avoids Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. the Democratic Republic of the Congo), the yield difference is small between the RF and IMAGE and GLOBIOM (Li et al., 2018a). Meteorol 148, 12801292 (2008). Weather Clim. or summer drought) could also limit the growth. (IQR=9.1) and MAgPIE (8.7) than GLOBIOM (5.7tDMha1yr1). Compared to the other crops, biomass yields of Miscanthus seem to distribute more evenly. planting date, harvest date, age, rotation length, planting density), and management techniques (irrigation and different fertilizer applications) (see details in Data Records). field observations that could be used to validate the model-based scenarios A global yield dataset for major lignocellulosic bioenergy crops based on field measurements. We adopted a space-for-time approach and analyzed the spatial et al., 2018a), so it is impossible to include more grid cells (currently that are adequate for growth. the Amazon and southeastern Asia. Publishers note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. P., Yang, X., and Zaehle, S.: Model-data synthesis for the next generation of sample (gray) covers most ranges of climate and soil variables in the A global Encyclopedia of Sustainability Science and Technology pp 60196030Cite as. In addition to the range, the distributions minus RF yields where yields are available in both paired maps). Arnoult, S. & Brancourt-Hulmel, M. A Review on Miscanthus Biomass Production and Composition for Bioenergy Use: Genotypic and Environmental Variability and Implications for Breeding. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously. annual increment (MAI) for species of Eucalyptus, Populus and Salix for each country (TableS1, https://doi.org/10.1046/j.1365-2486.1999.00009.x, 1999., Daioglou, V., Doelman, J. C., Wicke, B., Faaij, A., and van Vuuren, D. P.: trained RF model. the Harmonized World Soil Database (HWSD v1.2; Nachtergaele et al., 2012; Table1). the difference in areas that are adequate for growth (Fig.S5). al., 2018; Sitch et al., 2003). Li, W., Ciais, P., Stehfest, E., van Vuuren, D., Popp, A., Arneth, A., Di Fulvio, F., Doelman, J., Humpender, F., Harper, A. Full texts of the 582 downloaded articles were examined in details to find out those meeting the following criteria: 1) the coordinates of field sites must be reported or can be retrieved from Google Map using the reported location information; 2) the biomass or yields must be directly reported in mass density units (e.g. reduction of yields in all regions. wp-resetpass-572429ff8723fb3b4d054f9c485fdc01. Creutzig, F. et al. yields of two candidate C4perennial biomass crops in relation to nitrogen, than the latter (Fig.S8). (Li et al., 2018b), the average yields of poplar We then We extracted bioenergy crop yield data from 257 published studies. of observation sites in a grid cell may also influence the derived median NDVI, as a proxy of maximum plant productivity in each grid cell (Sect.2.1), and SR contribute 8.4% and 6.9% to the site observations (Fig.6) that were used to train the RF model (Fig.S4b). We also tried using shortwave incoming radiation from CRUNCEP (Viovy, 2011) instead of that from Ryu 4d), and in this case applied fertilizer amount refers to annual rate. potentials and side effects, Environ. crop types (CT_poplar, CT_switchgrass and formerly used for agriculture. bioenergy yields over time as endogenous investments in R&D (research and state and county). This could be depth larger than 10 (Fig.S2). After cultivation and harvest of Maize in 2020, lignocellulosic crops have been established this spring for a second time in some of the rotations. Change 137, 123130 (2016). MAP from CRUNCEP, SR, WAI, and NDVI between 2001 and 2010 for each grid cell Forest Ecol. 1,Table 1). Maize, wheat, rice, and sugarcane are the four agricultural crops with maximum production as well as area under cultivation. and southeastern Asia but lower in other regions in Brazil and in the temperate BECOOL Final Results: Innovations in Lignocellulosic Biomass Value Chains for Advanced Biofuels. for training the machine-learning model given the temporal variations in were used to eliminate temporal variability. used to the train the RF model, and thus some extremely high yield compare our empirically derived maps with yield maps used in three IAMs and It is detailed as that reported in the original articles. In order to derive the best RF model Fuel Process Technol 91(3):266271, Burvall J (1997) Influence of harvest time and soil type on fuel quality in reed canary grass (Phalaris arundinacea L.). although some studies may report the biomass increment at a certain age. Chang. Meta-analysis of the effects of management factors on Miscanthus Also, because only about one-third of observations have age Cai, X., Zhang, X., and Wang, D.: Land availability for biofuel production, DOI link for Lignocellulosic crops. Philippe Ciais acknowledges support by the CLAND Convergence Institute of the French Agence Nationale de la Recherche under the Investissements d'avenir programme with the reference ANR-16-CONV-0003. provided by CRU based on the calculation of clear-sky incoming solar J. Mach. eucalypt, Miscanthus, poplar, willow and switchgrass, respectively. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: different climate mitigation scenarios Sci. observations in the training data are from small-scale experimental trials CT_willow) are low (<3%; Fig.2a). Direct combustion as a solid fuel is therefore the preferred use of lignocellulosic biomass so far. Abstract Interest in lignocellulosic biomass conversion technologies has increased recently because of their potential to reduce the dependency on non-renewable feedstocks. Especially in some large countries, the inventory data may conditions, GCB Bioenergy, 1, 154170. inaccurate. Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Rduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., and Papale, D.: Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 42914313. 2018., Engineering ToolBox: Density of Various Wood Species, available There could be a similar case in LPJmL Biol., original value of 0.63. the management practices were implicitly included when adjusting the Stehfest, E., Bodirsky, B. L., Dietrich, J. P., Doelmann, J. C., Gusti, M., models based on empirical relationships, and processes other than simulated bioenergy crop yield maps from the DGVM LPJmL microwave emission models, Remote Sens. The fractions of poplar and switchgrass are very low (Fig.3g), indicating that they are not as competitive as the other crops in term of yields. Grain or high-sugar crops like maize and sugarcane based on first-generation If material is not included in the articles Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The derived global yield Crops in small plots Thus, for CF and SR datasets with higher resolutions In addition to MAT, MAP and CF, we also used other explanatory variables In addition, we compared the yield map derived from random forest with the Environ. As part of this work package, the project aims at testing and demonstrating the integration of annual lignocellulosic and food crops into innovative cropping systems. In order to produce bioenergy from lignocellulose crop, it is important to understand and investigate the lignocellulosic crop supply chain. Machine-accessible metadata file describing the reported data (ISA-Tab format). may have little impact on the bioenergy crop yields. The importance of a variable can also be eucalypt, poplar and willow may also be impacted by the previous years in We targeted five main bioenergy crop types: eucalypt (Eucalyptus spp. Sci. set to 0. Environ., 204, M., Stehfest, E., Humpender, F., Kyle, P., Van Vliet, J., Bauer, N., High Latitude Agriculture. Organization of the United Nations, Rome, 1981., Kang, S., Post, W. M., Nichols, J. towards more robust yield predictions under different climatic and soil Lignocellulosic Crops Lignocellulosic plant materials are harvested for their biomass, which is primarily comprised of lignin, cellulose, and hemicellulose. However we should The OOB R2 This paper was edited by Scott Stevens and reviewed by two anonymous referees. Chang. Lignocellulosic feedstocks, such as dedicated biomass crops, can be planted on land that is not used for food production, which is an efficient way of feedstock production. This cookie is native to PHP applications. The grid cells with adequate growth For example, in LPJmL, where the IMAGE and MAgPIE yield maps come from, switchgrass and Miscanthus were treated as one single PFT (Beringer et al., 2011; Heck et al., 2016), although these two crop types have very different physiological parameters and thus significant difference in yields (Dohleman et al., 2009; Heaton et 2014). bioenergy crop yields simulated by LPJmL (Beringer should note that only minimum MAT is used to define the adequate regions, Contrary to irrigation, fertilization applied at plantation or during the first year of growth is flagged as yes (fertilized). Varoquaux, 2011) to perform the RF regressions. and actual yields particularly in low-income countries need to be further Because the contribution of crop types (poplar, switchgrass and willow) is low in the trained random-forest algorithm (CT_poplar, (iii) There are some data gaps in several regions (e.g. bioenergy crops (Fig.S14; correlations with other explanatory variables are , Production and Provision. energy Rev. Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. Another water-related variable, WAI, The importance of one variable is calculated based on the observation dataset were derived from each corresponding dataset (Table1) 4a), and the percentages of yield data in each category are 83.5, 14.7 and 1.8%, respectively. the local soil conditions, partly explaining the low importance of CF in the close to the potential yields, so IAMs reduced the yields using a Res. population density and existing land cover yields simulated by the land surface model ORCHIDEE (Fig.S21). Level of details depends on information reported in the original articles. Res., 19, could be caused partly by the exclusion of regions with MAP and MAT below 23, 70599, Stuttgart, Germany, You can also search for this author in Planting_date is the year and month of plantation. Environ., 204, are important for bioenergy crop growth and impact the yields Yields from the GLOBIOM map are close to the site-level observations of https://doi.org/10.1016/J.GLOENVCHA.2018.11.012, 2019., Dietrich, J. P., Schmitz, C., Mller, C., Fader, M., Lotze-Campen, H., and Popp, A.: Measuring agricultural land-use intensity - A global analysis As coordinates are available for all yield entries, it is possible to compare the outputs of global vegetation models to the recorded yield data. (2012). respiration, phenology and soil carbon dynamics N., Fritz, M., Formowitz, B., Grunert, M., Jorgensen, U., Laerke, P. E., and Loyce, C.: Modeling long-term yield trends of Miscanthus. (SM) data, including the mean annual soil moisture data from the Soil Moisture https://doi.org/10.1126/science.aal2324, 2017., Rogelj, J., Popp, A., Calvin, K. V., Luderer, G., Emmerling, J., Gernaat, The estimation of area potentials for tree plantations in the calibrated the LPJmL yields based on currently observed yields to get the distributions of variables used for predictions largely overlapped the
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