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.

ISIMIP2a

Person responsible for model simulations in this simulation round

Rüdiger Grote: ruediger.grote@kit.edu, 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: Grote R, Lehmann E, Brümmer C, Brüggemann N, Szarzynski J, Kunstmann H et al. Modelling and observation of biosphere–atmosphere interactions in natural savannah in Burkina Faso, West Africa. Physics and Chemistry of the Earth, Parts A/B/C,34,251-260,2008
Grote R, Korhonen J, Mammarella I et al. Challenges for evaluating process-based models of gas exchange. Forest Systems,20,389,2011
Grote R, Kiese R, Grünwald T, Ourcival J, Granier A et al. Modelling forest carbon balances considering tree mortality and removal. Agricultural and Forest Meteorology,151,179-190,2010
Holst J, Grote R, Offermann C, Ferrio J, Gessler A, Mayer H, Rennenberg H et al. Water fluxes within beech stands in complex terrain. International Journal of Biometeorology,54,23-36,2009
Lindauer M, Schmid H, Grote R, Mauder M, Steinbrecher R, Wolpert B et al. Net ecosystem exchange over a non-cleared wind-throw-disturbed upland spruce forest—Measurements and simulations. Agricultural and Forest Meteorology,197,219-234,2014

Resolution

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

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

Additional input data sets: WORLD_atmospheric-ghg-concentration-history NDEPOSITION_EMEP

Climate variables: tasmax, tas, tasmin, rhs, rsds, pr

Spin-up

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