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A dataset to explore the influence of functional diversity for long-term forest biomass across six European regions using the model LPJmL-FIT

This dataset contains simulation data using the LPJmL-FIT model (Billing et al., 2019). The purpose of this dataset is to investigate the influence of functional diversity on European forest biomass dynamics under varying climate change scenarios (RCP2.6, RCP4.5, RCP8.5). The LPJmL-FIT ("Lund-Potsdam-Jena managed Land – Flexible Individual Traits") model is a dynamic flexible-trait vegetation model that simulates the establishment, growth, competition, and mortality of individual trees and grasses. Each tree individual is categorized into one of four main plant functional types (PFTs) and assigned a set of functional trait values, including specific leaf area (SLA), leaf longevity (LL), and wood density (WD). The model is driven by daily climate input data, atmospheric CO2 concentration, and soil texture. For this dataset, the model was applied to six different regions across central and eastern Europe, covering a range of environmental gradients. Those sites include: Alpine Mountains, Boreal flatland, Carpathian Mountains, central European flatland, central European low mountain range and eastern European flatland. Each region is represented by a set of 9 grid cells of 0.5° x 0.5° longitude and latitude in size. Four experimental set-ups were investigated, varying in the degree of functional diversity. These set-ups specify characteristics of newly establishing trees, including assignment to PFTs and the range of leaf traits drawn from the full spectrum. This dataset provides detailed model outputs from simulations exploring the effects of different levels of functional diversity on forest adaptation under changing climatic conditions.

Projections of future fire and vegetation variables on European scale

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).

Chemical and isotope data on the deep regolith’s source of mineral nutrients in mountainous temperate forest ecosystems

The data herein were used to trace the source and depth of nutrient uptake in two mountainous temperate forest ecosystems in southern Germany (Conventwald/Black Forest and Mitterfels/Bavarian Forest). Presented are phosphorus (P) concentrations from various P fractions of soil, saprolite, weathered bedrock and unweathered bedrock samples from drilling cores (depth: 20 m, site Conventwald (CON), and 30 m, site Mitterfels (MIT)) obtained by sequential extractions following the Hedley fractionation method. Further, the dataset contains strontium (Sr) and beryllium (Be) isotope data from drilling cores mentioned above. 87Sr/86Sr data are provided for bulk samples of forest floor, soil, saprolite, weathered bedrock, and unweathered bedrock. For soil and saprolite samples, additional Sr isotope ratios of the water-soluble and the exchangeable Sr fractions are provided. 87Sr/86Sr, beryllium concentrations (measured by Quadrupole-ICP-MS) and 10Be(meteoric)/9Be data from living leaves, needles, and stem wood (heartwood and sapwood of Fagus sylvatica and Picea abies) from both study sites are reported. Beryllium concentrations (measured by ICP-OES) and isotope ratios of amorphous oxides sequentially extracted from soil and saprolite at CON and MIT are provided. Soil pH at CON and MIT is also provided. Compiled concentrations of K, Ca, Mg and P and total deposition rates of atmospheric dust deposition are also included in the dataset. The data presented here stem from sampling campaigns and analyses described in Uhlig et al. (2020) to which they are supplementary material to. Samples were mainly processed in the Helmholtz Laboratory for the Geochemistry of the Earth Surface (HELGES), the University of Bonn (P Hedley fractionation) and the University of Cologne - Centre for Accelerator Mass Spectrometry (AMS) (10Be measurements). Tables supplementary to the article, including data quality control, are provided in pdf and xls formats. In addition, data measured in the course of the study are also provided as machine readable ASCII files. All samples are indexed with an International Geo Sample Number (IGSN). Sample metadata can be viewed by adding the IGSN to the “http://igsn.org/” URL (e.g. igsn.org/GFDUH00LT).

Geochemical data on silicon isotope and Ge/Si ratios along a global erodosequence

We provide geochemical data for three sites that define a gradient of 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 central Sri Lanka. Specifically, we provide silicon isotope ratios and germanium/silicon ratios and the major element composition of 1) rock, 2) saprolite, 3) soil, 4) plants, 5) river dissolved loads, 6) the soil and saprolite amorphous silica fraction (accessed with a NaOH leach), and 7) the soil and saprolite clay-size fraction (isolated with a differential settling protocol). These data serve two purposes. First, they allow us to improve understanding of the controls on silicon isotopes and germanium/silicon ratios in the 'Critical Zone'. Specifically, we can quantify the fractionation factors (for silicon isotopes) and the exchange coefficients (for germanium/silicon ratios), for secondary mineral precipitation and for biological uptake. Secondly, we can use mass-balance approaches to quantify the partitioning of silicon - a nutrient, and a major rock-forming element - among secondary minerals, plant material, and solutes. 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.

Geochemical data on rock weathering along an erodosequence

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.

Global Age Mapping Integration (GAMI)

GAMI is an updated dataset providing global forest age distributions for 2010 and 2020 with 100-meter resolution, improving upon the MPI-BGC forest age product. Utilizing machine learning, specifically XGBoost, the estimates are based on over 40,000 forest inventory plots, biomass/height data, remote sensing, and climate data. The dataset incorporates Landsat-based disturbance history and uses multiple XGBoost models with varied hyperparameters to address aleatoric and epistemic uncertainties. Twenty realizations of biomass data with controlled perturbations simulate natural variability, offering robust statistical measures and confidence intervals. Additionally, GAMI provides age class fraction products at different spatial resolutions for custom analyses. The full description of the data and the updates to version 1.0 (Besnard, 2021, https://doi.org/10.17871/ForestAgeBGI.2021) is provided in the associated data description file.

Geochemical and isotope data on rock weathering, and nutrient balances during fast forest floor turnover in montane, temperate forest ecosystems

The data herein were used to assess the importance of geogenic-derived nutrients on long-term forest ecosystem nutrition in two mountainous temperate forest ecosystems in southern Germany (Conventwald/Black Forest and Mitterfels/Bavarian Forest). Presented are element concentrations of various forest ecosystem compartments along with the soil pH, chemical depletion fractions (CDF), mass transfer coefficients (τ_(X_i)^X), radiogenic Sr isotope ratio (87Sr/86Sr) of soil and saprolite as well as in situ 10Be concentrations of bedload sediment.Element concentrations measured by X-ray fluorescence (XRF) are provided for drilling core samples (depth: 20 m, site Conventwald (CON), and 30 m, site Mitterfels (MIT)) including unweathered parent bedrock (paragneiss) and regolith comprising soil, saprolite and weathered bedrock but also for bedload sediment. Element concentrations were also measured by ICP-OES to determine the element composition of the soil´s and saprolite´s water-soluble, easily exchangeable, carbonate and organic-bound fraction. In addition, ICP-OES derived element concentrations are reported for plant tissues such as needles, leaves, and stem wood comprising heartwood (dead part of wood) and sapwood (living part of wood) of the two tree species European beech (Fagus sylvatica) and Norway spruce (Picea abies).Along with the chemical composition of soil and saprolite calculated weathering indices such as the chemical depletion fraction (CDF) and the mass transfer coefficient (τ_(X_i)^X) are reported for regolith and bedrock. Further, the dataset contains phosphorus (P) concentrations measured by ICP-OES and UV spectrometry from various P fractions obtained by sequential extractions following the Hedley fractionation method. Additionally, the pH of soil and saprolite measured by a pH meter as well as the radiogenic Sr isotope ratio, namely 87Sr/86Sr measured by MC-ICP-MS for bulk bedrock and regolith are reported in the dataset. Finally, to estimate the landscapes lowering rate (total denudation) in situ 10Be concentrations were measured by accelerator mass spectrometry (AMS) on bedload sediment at the outlet of the catchment.The data presented here stem from sampling campaigns described in Uhlig et al. (2019) to which they are supplementary material to. Samples were mainly processed in the Helmholtz Laboratory for the Geochemistry of the Earth Surface (HELGES) and the GFZ section of Inorganic and Isotope Geochemistry (XRF analyses), the University of Bonn (P Hedley fractionation), and the University of Cologne - Centre for Accelerator Mass Spectrometry (AMS) (10Be measurements).This dataset represents the supplementary material to Uhlig et al. (2019). Tables (including data quality control) supplementary to the article are provided in pdf and xls formats. In addition, data measured in the course of the study is given in machine readable ASCII files. All samples are indexed with an International Geo Sample Number (IGSN). Sample metadata can be viewed by adding the IGSN to the “http://igsn.org/” URL (e.g. igsn.org/GFDUH00LT).

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