The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests
暂无分享,去创建一个
Martin Gutsch | Klara Dolos | Hans Pretzsch | Florian Hartig | Hyungjun Kim | Stefan Fleck | Markus Wagner | Giorgio Matteucci | Carlo Trotta | Delphine Picart | Klaus Wiese | Denis Loustau | Flurin Babst | Alicia Palacios-Orueta | Henning Meesenburg | Thomas Rötzer | Kim Pilegaard | Victor Cicuendez | Ivan Mammarella | Hanqin Tian | Timo Vesala | Laura Recuero | Alexander Chikalanov | Jukka Pumpanen | Tanja G. M. Sanders | Justin Sheffield | Annikki Mäkelä | Michael Dietze | Massimo Vieno | Jean-Marc Bonnefond | Joanna A. Horemans | Jan Volkholz | Felicitas Suckow | Ramiro Silveyra Gonzalez | Jörg Steinkamp | Katja Frieler | Andreas Bolte | Friedrich Bohn | Stefan Lange | Andreas Ibrom | Pasi Kolari | Jan Krejza | Lenka Foltýnová | A. Mäkelä | H. Tian | I. Mammarella | T. Vesala | P. Berbigier | A. Ibrom | K. Frieler | M. Büchner | J. Volkholz | S. Fleck | G. Matteucci | J. Sheffield | K. Pilegaard | P. Kolari | F. Hartig | T. Sanders | F. Babst | Alicia Palacios-Orueta | M. Dietze | S. Lafont | Hyungjun Kim | Klara Dološ | J. Bonnefond | A. Bolte | G. Weedon | D. Cameron | D. Loustau | J. Krejza | H. Pretzsch | T. Rötzer | C. Trotta | J. Pumpanen | J. Horemans | P. Lasch-Born | C. Reyer | F. Suckow | M. Wagner | D. Picart | Alessio Collalti | J. Steinkamp | M. Vieno | E. D’Andrea | S. Lange | F. Bohn | Paul Berbigier | Graham P. Weedon | M. Gutsch | Y. Hauf | H. Meesenburg | Sébastien Lafont | Matthias Büchner | Lenka Foltýnová | R. S. Gonzalez | Matthias Noack | Víctor Cicuéndez | L. Recuero | K. Wiese | A. Chikalanov | Iliusi Vega del Valle | S. Martel | Mats Mahnken | Petra Lasch-Born | David Cameron | Christopher P. O. Reyer | Ylva Hauf | Matthias Noack | Alessio Collalti | Ettore D’Andrea | Simon Martel | Mats Mahnken | Klara Dolos | Ylva Hauf | A. Palacios-Orueta | R. S. González
[1] A. Mäkelä,et al. The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests , 2019 .
[2] G. Matteucci,et al. Winter's bite: Beech trees survive complete defoliation due to spring late-frost damage by mobilizing old C reserves. , 2019, The New phytologist.
[3] P. Ciais,et al. The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change , 2019, Ecological applications : a publication of the Ecological Society of America.
[4] Carsten F. Dormann,et al. An R package facilitating sensitivity analysis, calibration and forward simulations with the LPJ-GUESS dynamic vegetation model , 2019, Environ. Model. Softw..
[5] Fleck,et al. The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests. V.0.1.12 , 2019 .
[6] Forrest M. Hoffman,et al. The International Land Model Benchmarking (ILAMB) System: Design, Theory, and Implementation , 2018, Journal of Advances in Modeling Earth Systems.
[7] A. Ibrom,et al. Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate , 2018, Journal of advances in modeling earth systems.
[8] I. Štefančík. Growth characteristics of oak (Quercus petraea [Mattusch.] Liebl.) stand under different thinning regimes. , 2018 .
[9] Michael C Dietze,et al. Prediction in ecology: a first-principles framework. , 2017, Ecological applications : a publication of the Ecological Society of America.
[10] S. Lange. Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset , 2017 .
[11] Philippe Ciais,et al. Photosynthetic productivity and its efficiencies in ISIMIP2a biome models: benchmarking for impact assessment studies , 2017 .
[12] S. Fleck,et al. Impact of stoniness correction of soil hydraulic parameters on water balance simulations of forest plots , 2017 .
[13] Philippe Ciais,et al. Benchmarking carbon fluxes of the ISIMIP2a biome models , 2017 .
[14] Tyler D. Eddy,et al. Assessing the impacts of 1.5 °C global warming - simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b) , 2016 .
[15] The Level II aggregated forest soil condition database links soil physicochemical and hydraulic properties with long-term observations of forest condition in Europe , 2016, Annals of Forest Science.
[16] Stefan Fleck,et al. Long-term changes of ecosystem services at Solling, Germany: Recovery from acidification, but increasing nitrogen saturation? , 2016 .
[17] J. Canadell,et al. Greening of the Earth and its drivers , 2016 .
[18] Sergio Marconi,et al. Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites , 2016 .
[19] V. Banos,et al. La démarche prospective au service d’un développement forestier intégré. Une étude de cas sur le massif des Landes de Gascogne , 2016 .
[20] Hans Pretzsch,et al. Representation of species mixing in forest growth models. A review and perspective , 2015 .
[21] Ensemble simulations for the RCP8.5-Scenario , 2015 .
[22] C. Reyer. Forest Productivity Under Environmental Change—a Review of Stand-Scale Modeling Studies , 2015, Current Forestry Reports.
[23] Ranga B. Myneni,et al. Recent trends and drivers of regional sources and sinks of carbon dioxide , 2015 .
[24] Steven W. Running,et al. User's Guide Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm , 2015 .
[25] Ensemble simulations for the RCP 8 . 5-Scenario , 2015 .
[26] Sylvain Delzon,et al. Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? , 2014, Journal of environmental management.
[27] G. Balsamo,et al. The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA‐Interim reanalysis data , 2014 .
[28] Mixed Norway spruce (Picea abies [L.] Karst) and European beech (Fagus sylvatica [L.]) stands under drought: from reaction pattern to mechanism , 2014, Trees.
[29] E. Nikinmaa,et al. Above-ground woody carbon sequestration measured from tree rings is coherent with net ecosystem productivity at five eddy-covariance sites. , 2014, The New phytologist.
[30] W. Post,et al. The North American Carbon Program Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design , 2013 .
[31] F. Piontek,et al. The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework , 2013, Proceedings of the National Academy of Sciences.
[32] H. Pretzsch,et al. Modelling the impact of climate change on the productivity and water-use efficiency of a central European beech forest , 2013 .
[33] K. Larsen,et al. Synthesis on the carbon budget and cycling in a Danish, temperate deciduous forest , 2013 .
[34] Rob Kooper,et al. On improving the communication between models and data. , 2013, Plant, cell & environment.
[35] Béatrice Josse,et al. Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes , 2013 .
[36] F. Piontek,et al. A trend-preserving bias correction – the ISI-MIP approach , 2013 .
[37] Arain,et al. Use of change-point detection for friction–velocity threshold evaluation in eddy-covariance studies , 2013 .
[38] S. Dondeyne,et al. World Reference Base for Soil Resources , 2013 .
[39] P. S. Duncker,et al. Classification of forest management approaches: a new conceptual framework and its applicability to European forestry , 2012 .
[40] Markus Reichstein,et al. On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning , 2012 .
[41] S. Higgins,et al. Connecting dynamic vegetation models to data – an inverse perspective , 2012 .
[42] Susan L. Ustin,et al. Derivation of phenological metrics by function fitting to time-series of Spectral Shape Indexes AS1 and AS2: Mapping cotton phenological stages using MODIS time series , 2012 .
[43] Marc Simard,et al. A comprehensive benchmarking system for evaluating global vegetation models , 2012 .
[44] M. Gauß,et al. The EMEP MSC-W chemical transport model -- technical description , 2012 .
[45] J. Lamarque,et al. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): overview and description of models, simulations and climate diagnostics , 2012 .
[46] Steven F Railsback,et al. Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.
[47] Rainer Matyseek. Growth and defence in plants : resource allocation at multiple scales , 2012 .
[48] Rainer Matyssek,et al. Growth and Defence in Plants , 2012, Ecological Studies.
[49] C. Reyer,et al. Management of mixed oak-pine forests under climate scenario uncertainty. , 2011 .
[50] Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany. , 2011, Environmental pollution.
[51] W. J. Shuttleworth,et al. Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century , 2011 .
[52] K. Calvin,et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 , 2011 .
[53] Niels Otto Jensen,et al. Increasing net CO2 uptake by a Danish beech forest during the period from 1996 to 2009 , 2011 .
[54] G. Nabuurs,et al. Statistical mapping of tree species over Europe , 2011, European Journal of Forest Research.
[55] Bruce E. Wilson,et al. A SOAP Web Service for accessing MODIS land product subsets , 2011, Earth Sci. Informatics.
[56] H. Hasenauer,et al. Assessing the impacts of climate change and nitrogen deposition on Norway spruce (Picea abies L. Karst) growth in Austria with BIOME-BGC. , 2011, Tree physiology.
[57] Thomas Rötzer,et al. Models for supporting forest management in a changing environment , 2011 .
[58] B. Michalzik,et al. The importance of canopy-derived dissolved and particulate organic matter (DOM and POM) — comparing throughfall solution from broadleaved and coniferous forests , 2010, Annals of Forest Science.
[59] J. Yeluripati,et al. Predicting changes in soil organic carbon in mediterranean and alpine forests during the Kyoto Protocol commitment periods using the CENTURY model , 2010 .
[60] A. Arneth,et al. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation , 2010 .
[61] P. Hari,et al. Water balance of a boreal Scots pine forest , 2010 .
[62] Erkki Lähde,et al. Silvicultural alternatives in an uneven-sized forest dominated by Picea abies , 2010, Journal of Forest Research.
[63] Üllar Rannik,et al. Relative Humidity Effect on the High-Frequency Attenuation of Water Vapor Flux Measured by a Closed-Path Eddy Covariance System , 2009 .
[64] R. Brumme,et al. Functioning and management of European beech ecosystems , 2009 .
[65] G. Gravenhorst,et al. Climatic Condition at Three Beech Forest Sites in Central Germany , 2009 .
[66] Eero Nikinmaa,et al. Long-term measurements of the carbon balance of a boreal Scots pine dominated forest ecosystem , 2009 .
[67] P. Khanna,et al. Changes in C and N Contents of Soils Under Beech Forests over a Period of 35 Years , 2009 .
[68] S. Ustin,et al. Development of angle indexes for soil moisture estimation, dry matter detection and land-cover discrimination , 2007 .
[69] Manfred J. Lexer,et al. Multiple-use forest management in consideration of climate change and the interests of stakeholder groups , 2007, European Journal of Forest Research.
[70] T. Vesala,et al. Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation , 2006 .
[71] E. Wood,et al. Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling , 2006 .
[72] S. Hein,et al. Effect of species composition, stand density and site index on the basal area increment of oak trees (Quercus sp.) in mixed stands with beech (Fagus sylvatica L.) in northern France , 2006 .
[73] J. Schütz. Modelling the demographic sustainability of pure beech plenter forests in Eastern Germany , 2006 .
[74] Pierre Friedlingstein,et al. Comparing and evaluating process‐based ecosystem model predictions of carbon and water fluxes in major European forest biomes , 2005, Global change biology.
[75] T. Vesala,et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm , 2005 .
[76] Timo Pukkala,et al. Optimising the management of Pinus sylvestris L. stand under risk of fire in Catalonia (north-east of Spain) , 2005 .
[77] Philippe Ciais,et al. Modeling climate change effects on the potential production of French plains forests at the sub-regional level. , 2005, Tree physiology.
[78] Tiina Markkanen,et al. Effect of thinning on surface fluxes in a boreal forest , 2005 .
[79] M. Lindner,et al. Model-based analysis of management alternatives at stand and regional level in Brandenburg (Germany) , 2005 .
[80] Susan L. Ustin,et al. Assessment of NDVI and NDWI spectral indices using MODIS time series analysis and development of a new spectral index based on MODIS shortwave infrared bands , 2005 .
[81] P. Hari,et al. Estimation of forest–atmosphere CO2 exchange by eddy covariance and profile techniques , 2004 .
[82] E. Feoli,et al. Syntaxonomical analysis of beech woods in the Apennines (Italy) using the program package IAHOPA , 2004, Vegetatio.
[83] D. Loustau,et al. Variability of stem and branch maintenance respiration in a Pinus pinaster tree. , 2003, Tree physiology.
[84] Per Ambus,et al. Field measurements of atmosphere-biosphere interactions in a Danish beech forest , 2003 .
[85] P. Berbigier,et al. CO2 and water vapour fluxes for 2 years above Euroflux forest site , 2001 .
[86] F. Woodward,et al. Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models , 2001 .
[87] M. Hanewinkel,et al. Modelling the conversion from even-aged to uneven-aged stands of Norway spruce (Picea abies L. Karst.) with a distance-dependent growth simulator , 2000 .
[88] H. J. Schellnhuber,et al. ‘Earth system’ analysis and the second Copernican revolution , 1999, Nature.
[89] R. Pape. Influence of Thinning and Tree Diameter Class on the Development of Basic Density and Annual Ring Width in Picea abies , 1999 .
[90] A. Bondeau,et al. Comparing global models of terrestrial net primary productivity (NPP): overview and key results , 1999 .
[91] H. Pretzsch,et al. Die Fichten-Buchen-Mischbestände des Sonderforschungsbereiches „Wachstum oder Parasitenabwehr?“ im Kranzberger Forst , 1998, Forstwissenschaftliches Centralblatt vereinigt mit Tharandter forstliches Jahrbuch.
[92] D. Loustau,et al. Variability of the photosynthetic characteristics of mature needles within the crown of a 25-year-old Pinus pinaster. , 1998, Tree physiology.
[93] A. Cescatti,et al. Silvicultural alternatives, competition regime and sensitivity to climate in a European beech forest , 1998 .
[94] T. Pukkala,et al. A spatial yield model for optimizing the thinning regime of mixed stands of Pinus sylvestris and Picea abies , 1998 .
[95] M. Sykes,et al. A comparison of forest gap models: Model structure and behaviour , 1996 .
[96] G. Kerr. The effect of heavy or ‘free growth’ thinning on oak (Quercus petraea and Q. robur) , 1996 .
[97] Aaldrik Tiktak,et al. Review of sixteen forest-soil-atmosphere models , 1995 .
[98] H. Sterba. Estimating Potential Density from Thinning Experiments and Inventory Data , 1987 .
[99] Stephen Nortcliff,et al. Soil properties , 1980, Nature.
[100] J. Monteith. SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .