Impact model: Landscape-DNDC

Landscape-DNDC is a modular ecosystem model with special emphasize on representing trace gas fluxes (N2O, CH4, VOC) and nitrate percolation. Ecosystems are represented with different modules, with the forest ecosystems in this database are calculated with the cohort-specific physiologically-based PSIM modul.

local, regional

Information for the model Landscape-DNDC is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Person responsible for model simulations in this simulation round
Rüdiger Grote:, 0000-0001-6893-6890, Karlsruhe Institute of Technology (Germany)
Basic information
Model Version: 1.2
Model Output License: CC0
Reference Paper: Main Reference: Haas E, Klatt S, Fröhlich A, Kraft P, Werner C, Kiese R, Grote R, Breuer L, Butterbach-Bahl K et al. LandscapeDNDC: a process model for simulation of biosphere–atmosphere–hydrosphere exchange processes at site and regional scale. Landscape Ecology,28,615-636,2012
Reference Paper: Other References:
Spatial Aggregation: forest stand
Additional Spatial Aggregation & Resolution Information: The model is run on a plot basis that can have any size. The implicit assumption is that the plot is horizontally homogeneous (e.g. gaps are homogeneously distributed).
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: daily
Temporal Resolution Of Input Data: Land Use/Land Cover: no change
Temporal Resolution Of Input Data: Soil: constant
Additional Temporal Resolution Information: The constant values are referring to water holding capacity, stone fraction, etc. while carbon, nitrogen and water content are dynamically treated and updated in sub-daily resolution.
Input data sets used
Observed Atmospheric Climate Data Sets Used: GSWP3, Historical observed climate data, PGMFD v2.1 (Princeton), WATCH (WFD), WATCH-WFDEI
Emissions Data Sets Used: CO2 concentration
Climate Variables: tasmax, tas, tasmin, rhs, rsds, pr
Additional Input Data Sets: WORLD_atmospheric-ghg-concentration-history NDEPOSITION_EMEP
Was A Spin-Up Performed?: No
Management & Adaptation Measures
Management: Stem reduction implemented as indicated by stand density measurements provided in the scenarios. Biomass was reduced to the same or a smaller proportion than tree number depending on the statistical change in dbh as indicated.
Extreme Events & Disturbances
Key Challenges: Biomass after tree mortality is either removed from the area or put into the litter compartment. However, if trees are dead but still standing (fire, insects), decomposition starts to a different time than death. Similar, trees that are thrown by a storm often don't reach the soil and are also decomposing much slower than otherwise expected.
Key model processes
dynamic vegetation: yes - in terms of dimensional changes and natural mortality of trees. New individuals need to be introduced as a mangement event, there is no natural regeneration.
nitrogen limitation: yes - photosynthesis is reduced if nitrogen supply is not sufficient. Also, respiration increases with tissue nitrogen content and uptake.
CO2 effects: yes - photosynthesis is calculated in dependence on CO2 concentration (Farquhar approach)
light interception: yes - light distribution is calculated in canopy layers according to canopy properties. The model differentiates between direct and diffuse light fractions in each layer.
light utilization: yes - diffuse and direct light is separately used for photosynthesis calculation (Farquhar approach).
phenology: yes - the development of new leaves is driven by growing degree days (cumulative daily temperature above threshold). The demand for other supporting tissues (sapwood, fine roots) is defined due to their relationship to foliage and thus their growth follows that of foliage. Tissue senescence is empirically prescribed.
water stress: yes - photosynthesis is limited by stomatal conductance which in turn is decreased if water supply is not sufficient to fulfill the evaporative demand. In addition, there are some threshold values for foliage and fine root growth. Mortality is not affected by drought.
heat stress: no - (except that evaporative demand increases with temperature and stomata close with increasing vapor pressure deficit)
Evapo-transpiration approach: The model uses a modified Thornthwaite approach that calculates potential evapotranspiration based on temperature. The approach is modified to account for daily demand.
Differences in rooting depth: Potential rooting depth depends on tree height and develops dynamically until soil depth is reached. If mature trees are initialize, roots are generally destributed down to initialized soil depth.
Root distribution over depth: Fine root distribution within the rooting depth is calculated empirically (species-specific).
closed energy balance: no (only latent heat, temperature and radiation input are calculated)
Coupling/feedback between soil moisture and surface temperature: yes - soil temperature is calculated in each soil layer according to the specific soil properties including water content.
latent heat: yes - total evapotranspiration is calculated as the sum of evaporation from interception, ground evaporation, and transpiration.
sensible heat: no
Causes of mortality in vegetation models
Age/Senescence: no
Fire: no
Drought: no
Insects: no
Storm: no
Stochastic random disturbance: yes - a certain amount of mortality is prescribed (or due to radom processes).
Other: Generally, trees die if their ground coverage overlaps more than a defined threshold. Death thus occurs due to competition and mortality increases with growth.
NBP components
Fire: no
Land-use change: no
Harvest: considered as a driving force
Species / Plant Functional Types (PFTs)
List of species / PFTs: piab_picea_abies pisy_pinus_sylvestris pipi_pinus pinaster fasy_fagus_sylvatica
Model output specifications
Output format: species-specific land only
Output per PFT?: output is per unit ground area
Additional Forest Information
Forest sites simulated: bily_kriz peitz soro solling_beech solling_spruce hyytiala lebray collelongo