This dataset contains simulated vegetation and fire variables using the LPJmLv5.6-SPITFIRE and LPJmLv5.6-SPITFIRE-BASE coupled vegetation-fire model. LPJmL is a Dynamic Global Vegetation Model (DGVM), which simulates impacts of climate change and vegetation including carbon, water and energy fluxes on land. SPITFIRE is a process-based fire model that is developed at the Potsdam Institute for Climate Impact Research (PIK) simulating ignitions, fire spread, fuel combustion and plant mortality. BASE is an empirical burned area model, developed at Senckenberg – Leibniz Institution for Biodiversity and Earth System Research (SGN), that is based on remotely sensed information using generalised linear model (GLM) techniques provided by data sources from within the HORIZON2020 project FirEUrisk and elsewhere.
The dataset contains a set of future changes in vegetation and fire variables under future climate and land-use change at the European (ET) scale at 9 km covering 2000-2100 for both couple vegetation-fire models. The models were forced with 5 climate models from the SSP126 and SSP370 climate scenarios (its downscaling to ~9 km grid cell resolution) as well as the land-use projections corresponding to those climate scenarios (provided at ~9 km grid cell resolution). The variables provided in this dataset are at monthly and annual temporal resolution. The simulated changes in fire and vegetation spatio-temporal patterns are the result of changes in climate and land-use and subsequent fire-vegetation feedbacks.
This data has been developed in the course of the HORIZON2020 project FirEUrisk (Deliverable 3.4; Grant Agreement no. 101003890).
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.
In "On the sensitivity of the Devonian climate to continental configuration, vegetation cover, orbital configuration, CO_2 concentration and insolation" we study the sensitivity of the Devonian (419 to 359 million years ago) to several parameters using a coupled climate model. The data presented here is the model output the results of this manuscript are based on. Additionally, the figures of the publication and scripts (Python and Yorick) to analyse the model output and generate the figures are contained. The model output is provided in different netcdf files. The structure of the model output is explained in a readme file. The data is generated using the coupled ocean-atmosphere model CLIMBER3alpha which models climate globally on a 3.75°x3.75° (ocean) and 22.5° (longitude) x 7.5° (latitude) (atmosphere) grid. More information about the model can be found in the manuscript.
The dataset is composed of a) hyperspectral imagery acquired with AISA Eagle and Hawk imaging spectrometer data in the range 400 to 2500 nm on April 2 and August 9, 2011, with a ground sampling distance of 4 m in 12 and 15 flight lines, respectively; b) airborne LiDAR data acquired in single-pulse mode in August 2011 concurrent with hyperspectral data acquisition with an avarage point density of 0.7 hits per meter squared; c) spectral reference measurements acquired with a portable ASD field spectroradiometer around the days of image acquisitions d) fractional cover of green vegetation, dry vegetation, bare soil and rock were visually estimated for 60 (April) and 53 (August) transects of 20-m length. The overall goal of the study was to investigate the potential of hyperspectral and LiDAR data for assessing sediment connectivity at the hillslope to subcatchment scale. For that the fractional cover of green vegetation, dry vegetation, bare soil and rock was derived
by applying a multiple endmember spectral mixture analysis approach to the hyperspectral image data. The LiDAR point clouds were pre-processed to generate a digital elevation map as well as a vegetation height map, both with 4-m spatial resolution.