Other language confidence: 0.9644038001719094
The data consists of four vascular plant species lists, one per study site. The site selection is based on the four study areas of the DFG Priority Program 1803 "EarthShape - Earth Surface Shaping by Biota” (www.earthshape.net), namely: arid climate National Park Pan de Azúcar, semi-arid climate Private Reserve Santa Gracia, mediterranean climate National Park La Campana and humid-temperate climate National Park Nahuelbuta in Chile, South America. Each list is a table with (mostly) terrestrial vascular plant species names that have been reported in a variety of sources at the selected sites and the corresponding administrative or biogeographical regions of Chile. The available literature sources varied from specific national park flora lists to Chilean flora books and catalogues and thus, the present lists represent a potential vegetation for the EarthShape study areas. Each table includes the plants’ Latin name, clade taxonomy, the plant growth form as well as the origin. The taxonomy of the vegetation species was updated to the taxonomic information available up to August 2023 from Chilean and South American vascular flora lists.
The netCDF data stored here represent crop production simulations from the LPJmL biosphere model underlying the different steps of the U-turn portrayed in the main paper by Gerten et al. The LPJmL data cover the entire globe with a spatial resolution of 0.5° for the baseline period as well as for different scenarios reflecting the studied ways to restrict crop production through maintaining planetary boundaries on the one hand and the various opportunities to increase food supply within the boundaries on the other hand (see paper, specifically Figs. 1 & 2, Table 2). The stored variable is crop production (fresh matter) multiplied by the fractional coverage of different crop functional types, per 0.5° grid cell. The data are provided in one netCDF file for each scenario. An overview of the scenarios assigned to the folder names is given in the file inventory.The data support the study: Gerten, D., Heck, V., Jägermeyr, J., Bodirsky, B.L., Fetzer, I., Jalava, M., Kummu, M., Lucht, W., Rockström, J., Schaphoff, S., Schellnhuber, H.J.: Feeding ten billion people is possible within four terrestrial planetary boundaries. Nature Sustainability (2020).
The dataset is composed of Hyspex (VNIR/SWIR) hyperspectral imagery acquired during airplane overflights on 01. Oktober, 2015 within the Demmin Research Area. The acquisition conditions were cloud free. The dataset includes two mosaics generated based on 9 HySpex flight lines. The dataset also includes Level 2A EnMAP-like imagery simulated using the end-to-end Simulation tool (EeteS). Additionally a soil database focussed on the soil organic carbon content (SOC) with geographic coordinates, texture and spectral information is included.
The dataset is composed of aisaEagel hyperspectral imagery acquired during airplane overflights on August 27th, 2016 within the Toolik Lake Natural Research Area on the Alaskan North Slope. The dataset includes three flight lines with 130 spectral bands ranging from VIS to NIR (451.7 – 897 nm) wavelength regions. The dataset also includes Level 2A EnMAP-like imagery simulated using the end-to-end Simulation tool (EeteS) with 78 bands from VIS to NIR (423 – 903 mn). The overall goal of the campaign was to acquire imagery over the Toolik Vegetation grid encompassing 94 permanent 1 x 1 m vegetation plots where corresponding, comprehensive multi-seasonal spectral reflectance, photosynthetic pigment, and detailed species composition data exists. The data are highly novel and can be used form vegetation mapping of species composition and activity.
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors.ISIMIP2b is the second simulation round of the second phase of ISIMIP. ISIMIP2b considers impacts on different sectors at the global and regional scales: water, fisheries and marine ecosystems, energy supply and demand, forests, biomes, agriculture, agro-economic modeling, terrestrial biodiversity, permafrost, coastal infrastructure, health and lakes.ISIMIP2b simulations focus on separating the impacts and quantifying the pure climate change effects of historical warming (1861-2005) compared to pre-industrial reference levels (1661-1860); and on quantifying the future (2006-2099) and extended future (2006-2299) impact projections accounting for low (RCP2.6), mid-high (RCP6.0) and high (RCP8.5) greenhouse gas emissions, assuming either constant (year 2005) or dynamic population, land and water use and -management, economic development, bioenergy demand, and other societal factors. The scientific rationale for the scenario design is documented in Frieler et al. (2017).The ISIMIP2b bias-corrected observational climate input data (Lange, 2018; Frieler et al., 2017) consists of an updated version of the observational dataset EWEMBI at daily temporal and 0.5° spatial resolution, which better represents the CMIP5 GCM ensemble in terms of both spatial model resolution and equilibrium climate sensitivity. The bias correction methods (Lange, 2018; Frieler et al., 2017; Lange, 2016) were applied to CMIP5 output of GDFL-ESM2M, HadGEM2-ES, IPSL-CM5A-LP and MIROC5. Access to the input data for the impact models, and further information on bias correction methods, is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/isimip2b-bias-correction).This entry refers to the ISIMIP2b simulation data from eight global vegetation (biomes) models:CARAIBCLM4.5,DLEM,LPJmL,ORCHIDEE,VEGAS,VISIT,LPJ-GUESS----------------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/ (ISIMIP Changelog) and https://www.isimip.org/outputdata/dois-isimip-data-sets/ (ISIMIP DOI publications).----------------------------------------------------------------------------
VERSION HISTORY:- On April 10, 2018 we renamed some simulation files of impact models LPJ-GUESS, ORCHIDEE, JULES-UoE and VISIT, due to the correction of social scenario label “nosoc” for “varsoc”. For impact model VISIT, “nosoc” was relabeled to “pressoc”. These data caveats were documented in the ISIMIP website (ISIMIP2a Biomes: correction of scenario names in file names).- On October 17, 2018, we republished all simulation data for all biomes sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/.For accessing the data set as in the previous version (http://doi.org/10.5880/PIK.2017.002) before October 17, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.deDATA DESCRIPTION:The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to all these data is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).The ISIMIP2a biome outputs are based on simulations from 8 global vegetation (biomes) models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a).
The dataset is composed of Neo HySpex (VNIR & SWIR) and Telops Hyper-Cam (LWIR) hyperspectral imagery acquired during the MOSES GFZ/FUB/UFZ airborne campaign on August 8th, 2020 over the test area Oschersleben covering parts of the Bode catchment in the northern foreland of the Harz Mountain, Central Germany. The study area covers an ecological transect including three TERENO climate stations/flux towers ranging from forest sites (Hohes Holz) to lowland meadows (Grosses Bruch) to intensively used agricultural land (Hordorf). The survey was conducted within the frame of the Helmholtz program MOSES (Modular Observation Solutions for Earth Systems) heatwave event chain, which overall objective is to monitor heat extremes and drought events. In particular, the 2020 MOSES heatwave campaign over the Oschersleben test site aimed at an GFZ/UFZ intercalibration comparison measurements between different hyperspectral instruments flown on same day with different platforms and altitude, and test impact of different workflows on resulting data. This publication contains the GFZ VNIR-SWIR-LWIR hyperspectral dataset. It includes 1) 17 HySpex cloud-free flight lines already mosaicked in orthorectified reflectance, covering the VNIR to SWIR wavelength regions (0.4-2.5 µm) with 408 spectral bands, and 2) a composite of Hyper-Cam 1956 frames processed to surface temperature and spectral emissivity covering the LWIR (7.7 – 11.7 µm) in 125 bands. The dataset also includes Level 2A EnMAP-like reflectance imagery simulated using the end-to-end Simulation tool (EeteS). Associated field data and UFZ hyperspectral data are included in related publications of this campaign.
We provide geochemical background data on the partitioning and cycling of elements between rock, saprolite, soil, plants, and river dissolved and solid loads from at three sites along a global transect of mountain landscapes that differ in erosion rates – an “erodosequence”. These sites are the Swiss Central Alps, a rapidly-eroding post-glacial mountain belt; the Southern Sierra Nevada, USA, eroding at moderate rates; and the slowly-eroding tropical Highlands of Sri Lanka. The backbone of this analysis is an extensive data set of rock, saprolite, soil, water, and plant geochemical data. This set of elemental concentrations is converted into process rates by using regolith production and weathering rates from cosmogenic nuclides, and estimates of biomass growth. Combined, they allow us to derive elemental fluxes through regolith and vegetation. The main findings are: 1) the rates of weathering are set locally in regolith, and not by the rate at which entire landscapes erode; 2) the degree of weathering is mainly controlled by regolith thickness. This results in supply-limited weathering in Sri Lanka where weathering runs to completion, and kinetically-limited weathering in the Alps and Sierra Nevada where soluble primary minerals persist; 3) these weathering characteristics are reflected in the sites’ ecosystem processes, namely in that nutritive elements are intensely recycled in the supply-limited setting, and directly taken up from soil and rock in the kinetically settings; 4) contrary to common paradigms, the weathering rates are not controlled by biomass growth; 5) at all sites we find a deficit in river solute export when compared to solute production in regolith, the extent of which differs between elements but not between erosion rates. Plant uptake followed by litter erosion might explain this deficit for biologically utilized elements of high solubility, and rare, high-discharge flushing events for colloidal-bound elements of low solubility. Our data and the new metrics have begun to serve for calibrating metal isotope systems in the weathering zone, the isotope ratios of which depend on the flux partitioning between the compartments of the Critical Zone. We demonstrate this application in several isotope geochemical companion papers with associated datasets from the same samples. All samples are assigned with International Geo Sample Numbers (IGSN), a globally unique and persistent Identifier for physical samples. The IGSNs are provided in the data tables and link to a comprehensive sample description in the internet.
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to all these data is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).The ISIMIP2a biome outputs are based on simulations from 8 global vegetation (biomes) models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a).
The Arctic Greening Database v0.1 is an open access database created as part of the ETH+ project "Unraveling biogeochemical, microbial and vegetation feedbacks driving soil development and Arctic greening under a warming climate". The database contains data on soil, vegetation, microbial, and environmental properties from 14 active-layer tundra sites sampled in 2022 and 2023 on Svalbard. The spatially-explicit field observations, field and laboratory measurements provides an interdisciplinary collection of data from a remote and data-poor region to study linkages between vegetation, microbiome and pedogenesis in the context of Arctic Greening. The database is structured hierarchically with four connected levels: site, plot, sample, and species. At the site level, aggregated data are provided (e.g. GHG fluxes). This is followed by plot-level data (e.g. plant functional type cover) that connects to sample-level data (soil organic matter content) and species-level data. Tables at the same level are connected via one-to-one relationships, from a broader to finer level one-to-many relationships are in place. Sampling and measurement procedures are described in Section 2 of the database description. The metadata file accompanying a specific .csv file provides further information on data creation, sample processing and units. The current version of the dataset consists of a reduced set of tables that will be updated soon with more curated data from Svalbard and Northern Norway (Finnmark). A more extensive overview of the data will be published as a data paper in the future.
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