Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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LPJmL4 model output for the publications in GMD: LPJmL4 - a dynamic global vegetation model with managed land: Part I – Model description and Part II – Model evaluation
Schaphoff, Sibyll ; Bloh, Werner von; Rammig, Anja ; Thonicke, Kirsten ; Biemans, H. ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Knauer, Jürgen ; Langerwisch, Fanny ; Lucht, Wolfgang ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina - \ 2018
soil carbon - vegetation carbon - global carbon balance - permafrost distribution - discharge - fractional burned area - crop yields - global dynamic vegetation model - vegetation dynamics
LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. The LPJmL4 model combines plant physiological relations, generalized empirically established functions and plant trait parameters. The model incorporates dynamic land use at the global scale and is also able to simulate the production of woody and herbaceous short-rotation bio-energy plantations. Grid cells may contain one or several types of natural or agricultural vegetation. A comprehensive description of the model is given by Schaphoff et al. (2017a, http://doi.org/10.5194/gmd-2017-145). The data presented here represent some standard LPJmL4 model results for the land surface described in Schaphoff et al. (2017a,). Additionally, these results are evaluated in the companion paper of Schaphoff et al. (2017b, http://doi.org/10.5194/gmd-2017-146). The data collection includes some key output variables made with different model setups described by Schaphoff et al. (2017b). The data cover the entire globe with a spatial resolution of 0.5° and temporal coverage from 1901-2011 on an annual basis for soil, vegetation, aboveground and litter carbon as well as for vegetation distribution, crop yields, sowing dates, maximum thawing depth, and fire carbon emissions. Vegetation distribution is given for each plant functional type (PFT), crop yields, and sowing dates are given for each crop functional type (CFT), respectively. Monthly data are provided for the carbon fluxes (net primary production, gross primary production, soil respiration) and the water fluxes (transpiration, evaporation, interception, runoff, and discharge) and for absorbed photosynthetically active radiation (FAPAR) and albedo.
LPJmL4 Model Code
Schaphoff, Sibyll ; Bloh, Werner von; Thonicke, Kirsten ; Biemans, H. ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina ; Stehfest, Elke ; Waal, Liesbeth de; Heyder, Ursula ; Gumpenberger, Marlies ; Beringer, Tim - \ 2018
Potsdam Institute for Climate Impact Research (PIK)
soil carbon - vegetation carbon - global carbon balance - permafrost distribution - discharge - fractional burned area - crop yields - global dynamic vegetation model - vegetation dynamics
LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. The LPJmL4 model combines plant physiological relations, generalized empirically established functions and plant trait parameters. The model incorporates dynamic land use at the global scale and is also able to simulate the production of woody and herbaceous short-rotation bio-energy plantations. Grid cells may contain one or several types of natural or agricultural vegetation.
LPJmL4 - A dynamic global vegetation model with managed land - Part 1 : Model description
Schaphoff, Sibyll ; Bloh, Werner von; Rammig, Anja ; Thonicke, Kirsten ; Biemans, Hester ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Knauer, Jürgen ; Langerwisch, Fanny ; Lucht, Wolfgang ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina - \ 2018
Geoscientific Model Development 11 (2018)4. - ISSN 1991-959X - p. 1343 - 1375.
This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.
Pan-arctic climate and land cover trends derived from multi-variate and multi-scale analyses (1981-2012)
Urban, M. ; Forkel, M. ; Eberle, J. ; Huttich, C. ; Schmullius, C. ; Herold, M. - \ 2014
Remote Sensing 6 (2014)3. - ISSN 2072-4292 - p. 2296 - 2316.
snow water equivalent - space-time climate - photosynthetic trends - surface temperature - northern siberia - shrub expansion - radiometer data - orbital drift - vegetation - tundra
Arctic ecosystems have been afflicted by vast changes in recent decades. Changes in temperature, as well as precipitation, are having an impact on snow cover, vegetation productivity and coverage, vegetation seasonality, surface albedo, and permafrost dynamics. The coupled climate-vegetation change in the arctic is thought to be a positive feedback in the Earth system, which can potentially further accelerate global warming. This study focuses on the co-occurrence of temperature, precipitation, snow cover, and vegetation greenness trends between 1981 and 2012 in the pan-arctic region based on coarse resolution climate and remote sensing data, as well as ground stations. Precipitation significantly increased during summer and fall. Temperature had the strongest increase during the winter months (twice than during the summer months). The snow water equivalent had the highest trends during the transition seasons of the year. Vegetation greenness trends are characterized by a constant increase during the vegetation-growing period. High spatial resolution remote sensing data were utilized to map structural vegetation changes between 1973 and 2012 for a selected test region in Northern Siberia. An intensification of woody vegetation cover at the taiga-tundra transition area was found. The observed co-occurrence of climatic and ecosystem changes is an example of the multi-scale feedbacks in the arctic ecosystems.
Trend change detection in NDVI time series: Effects of inter-annual variability and methodology
Forkel, M. ; Carvalhais, N. ; Verbesselt, J. ; Mahecha, M.D. ; Neigh, C. ; Reichstein, M. - \ 2013
Remote Sensing 5 (2013)5. - ISSN 2072-4292 - p. 2113 - 2144.
spectral vegetation indexes - satellite data - north-america - boreal forest - el-nino - alaska - modis - climate - disturbance - accuracy
Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite datase
Identification of land surface temperature and albedo trends in AVHRR Pathfinder data from 1982 to 2005 for northern Siberia
Urban, M. ; Forkel, M. ; Schmullius, C. ; Hese, S. ; Hüttich, C. ; Herold, M. - \ 2013
International Journal of Remote Sensing 34 (2013)12. - ISSN 0143-1161 - p. 4491 - 4507.
recent climate-change - shrub expansion - orbital drift - vegetation - dynamics - impacts - growth - tundra
The arctic regions are highly vulnerable to climate change. Climate models predict an increase in global mean temperatures for the upcoming century. The arctic environment is subject to significant changes of the land surface. Especially the changes of vegetation pattern and the phenological cycle in the taiga–tundra transition area are of high importance in climate change research. This study focuses on time series and trend analysis of land surface temperature, albedo, snow water equivalent, and normalized difference vegetation index information in the time period of 1982–2005 for northern Siberia. The findings show strong dependencies between these parameters and their inter-annual dynamics, which indicate changes in vegetation growing period. We found a strong negative correlation between land surface temperature and albedo conditions for the beginning (60–90%) of the growing season for selected hot spot trend regions in northern Siberia
Hot spots, hot moments and time-span of changes in drivers and their responses on carbon cycling in Europe
Tomelleri, E. ; Forkel, M. ; Fuchs, R. ; Jung, M. ; Mahecha, M.D. ; Reichstein, M. ; Weber, U. - \ 2012
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