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2018

21 record(s)
 
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From 1 - 10 / 21
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    The dataset contains individual and georeferenced tree height from a network of 15 common gardens of Pinus nigra Arn. planted between 1968-2009 and located in France, Germany and Spain.

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    Forest-related policies, reporting obligations and decision analyses require relevant, comprehensive and reliable data. To better serve the new information demands, we present an extensive dataset of forest resources in European countries projected until 2040 based on harmonized definitions, assumptions and methodology. The results were mainly computed using the European Forestry Dynamics Model (EFDM). In the computation, each country prepared the input files required by the EFDM or corresponding projection models using their National Forest Inventory (NFI) data and harmonised definitions and standardised workflow. The initial years, areas analysed and technical details of the initial data and formatting the data for the EFDM analyses vary between countries depending on data availability and forestry practices applied. This worksheet presents the projections of the forest growing stock volume, aboveground carbon, and fellings in the area analysed and metadata of the simulations, indicating the parameterisation applied for the EFDM and any possible exceptions to the use of the standard EFDM workflow.

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    The module climate regionalization of the project “Forest productivity, carbon sequestration, climate change” contributes temporal and spatial high-resolution climate data from 1961 - 2100 for 26.450 points of the German National Forest Inventory. For the retrospective computation of the period 1961 - 2013 the historical daily observation data of climate and precipitation stations of the Deutscher Wetterdienst are regionalized with Geographically Weighted Regression. Future climate change scenarios are simulated with the STARS (2011 – 2050) and REMO (2011 – 2100) based on the MPI ESM ECHAM6 RCP scenarios (2.6, 4.5, 8.5). The NFI 2012 environmental data base climate contains timely aggregated climate information (monthly, seasonal, yearly, multiyearly) and provides the climatic input variables for the forest site water budget modelling and for the forest growth modelling.

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    This data set provides valuable environmental information about six experimental triplets of Scots pine and Maritime pine in Spain. An array of 213 physiographic, climatic, stand, understory and edaphic (organic and mineral horizons physicochemical parameters) variables are provided.

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    The dataset contains individual and georeferenced tree height from a network of 9 common gardens of Pinus pinea L. planted between years 1993 and 1997 and located in France and Spain.

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    (i) Key message: The NFIWADS database contains aggregated results for the German National Forest Inventory (NFI) plots based on process-based water balance simulations. More than 150 water budget, soil moisture, and drought stress indicators were derived for mature, closed-canopy beech and spruce stands, and provide a basis for the assessment of forest productivity and risks. (ii) Context: The NFI is an important data source for research on forest growth, tree species distribution and wood supply predictions in Germany. The NFIWADS database extends the environmental vector of explanatory variables by results from water balance simulations. (iii) Aims: The aim of this paper is to share the data for a broad use among forest scientists and to ease data handling by thoroughly describing the methods, background and structure of the data. (iv) Methods: For 24610 NFI plots, two site-specific water balance simulations were carried out, using the process-based hydrological model LWF-BROOK90, respectively for a retrospective period (1961-2013) and for each of three climate change scenarios (2011-2050). The two simulations in each climate representation describe the hydrological conditions of European Beech (Fagus sylvatica, L.) and Norway Spruce (Picea abies [L.], H.Karst) forests. (v) Main features and potential use of database: The daily simulation results were aggregated to monthly and vegetation period representations of water fluxes, soil moisture conditions and drought stress that can be used as explanatory variables for analysing long-term climate-sensitive site-productivity relationships and risk potentials, as well as intra-annual and seasonal variations of forest growth conditions. (vi) Conclusions: The connection of yield data and a broad set of environmental explanatory variables at the NFI opens up new opportunities for forest research at the national scale.

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    We developed a dataset of the potential distribution of seven ecologically and economically important tree species of Europe in terms of their climatic suitability with an ensemble approach while accounting for uncertainty due to model algorithms. The dataset was documented following the ODMAP protocol to ensure reproducibility. Our maps are input data in a decision support tool “SusSelect” which predicts the vulnerability of forest trees in climate change and recommends adapted planting material.

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    This data set provide valuable information about forest ecosystems in Pinus halepensis and Pinus sylvestris plantations in Spain. An array of 74 soil, climatic, physiographic and stand variables from 32 plots in P. halepensis plantations and 77 variables from 35 plots in P. sylvestris plantations are provided.

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    We provided long-term stand and canopy structural data from permanent monitoring plots representative of three most diffuse temperate and Mediterranean forests, under different coppice management regimes. Periodic inventories were performed in the surveyed plots since the 70s. Annual litterfall production and its partitioning (leaf, woody, reproductive parts) and optical canopy measurements using the LAI-2000 Plant Canopy Anayzer were performed every year in these plots since the 90s. These data can be used for evaluating the influence of coppice management in the stand and canopy structure, the parametrization of radiative transfer models that require accurate ground truth data, as well as the calibration of high to medium resolution remotely-sensed data.

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    The dataset contains individual and georeferenced tree height from a network of 14 common gardens of Pinus pinaster Aiton planted between 1966 and 1992 and located in France, Morocco and Spain.