Impact model: GOTILWA+

Sector
Forests
Region
local

GOTILWA+ model - Growth of Trees is Limited by Water, http://www.creaf.uab.cat/gotilwa/, (Gracia et al., 1999; Keenan et al. 2009; Nadal-Sala et al., 2017) - is a process-based forest simulation model. It is focused in forest carbon and water balances in a plot scale. In GOTILWA+ gas exchange processes are calculated at a hourly basis, and they are integrated daily and yearly.

Information for the model GOTILWA+ 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
Daniel Nadal-Sala: daniel.sala@kit.edu, 0000-0002-0935-6201, Karlsruhe Institute of Technology (Germany)
Santiago Sabaté: santi.sabate@ub.edu, 0000-0003-1854-0761, University of Barcelona (Spain)
Additional persons involved: Daniel Nadal-Sala
Output Data
Experiments: I, Ia, II, IIa, IIb, IIc, III, IIIa, IIIb (Hyytiälä, Peitz, Solling beech, Sorø, Le Bray, Collelongo)
Climate Drivers: None
Date: 2018-08-06
Basic information
Model Version: 4.0
Model Output License: CC0
Simulation Round Specific Description: * Data in embargo period, not yet publicly available
Reference Paper: Main Reference: Nadal-Sala D, Keenan T, Sabaté S, Gracia C et al. Forest Eco-Physiological Models: Water Use and Carbon Sequestration. Managing Forest Ecosystems: The Challenge of Climate Change,None,81-102,2017
Reference Paper: Other References:
Resolution
Spatial aggregation: forest stand
Additional spatial aggregation & resolution information: GOTIWA+ simulates 1 ha plots.
Temporal resolution of input data: climate variables: daily
Additional temporal resolution information: Climate variables disaggregated to hourly
Input data
Climate variables: tasmax, tas, tasmin, rlds, rsds, ps, pr
Exceptions to Protocol
Exceptions: yes
Spin-up
Was a spin-up performed?: No
Spin-up design: No spin-up procedure. Initializing runs from the first year with both consistent stand structure and climate data available.
Natural Vegetation
Natural vegetation partition: GOTILWA+ only works with mono-specific stands.
Management & Adaptation Measures
Management: Management procedures as defined in the protocol. In natural runs, a constant regeneration has been considered. This regeneration happens every 10 year of simulation, and equals to the Initial density under managed conditions / rotation length * 10.
Extreme Events & Disturbances
Key challenges: Reproducing individual tree mortality. Reproducing loose of sapwood hydraulic conductivity under stresses. Drought and heath waves affect carbon and water balances.
Model set-up specifications
How did you initialize your model, e.g. using individual tree dbh and height or stand basal area? how do you initialize soil conditions?: GOTILWA+ used representative average individuals per DBH class, each class defined at 5 cm increases. Data from the representative individuals was scaled up to the stand level by using the stand density per DBH class.
How is management implemented? e.g. do you harvest biomass/basal area proportions or by tree numbers or dimensions (target dbh)?: GOTILWA+ has several different options to implement forest management, but in this case the simulations where run by removing a percent of trees, randomly from the different DBH classes, during the management intervention.
When is harvesting simulated by your model (start/middle/end of the year, i.e., before or after the growing season)?: At DOY 365 each year at which a management intervention occurs.
How do you regenerate? do you plant seedlings one year after harvest or several years of gap and then plant larger saplings?: Regenerate appears at the same time than each harvest, with a pre-defined stand density of individuals belonging to 0-5 cm DBH class.
How are the unmanaged simulations designed? is there some kind of regrowth/regeneration or are the existing trees just growing older and older?: The existing trees grow, without further regeneration, if there is no management intervention.
Does your model consider leap-years or a 365 calendar only? or any other calendar?: Only 365 days per year
In hyytiälä and kroof, how did you simulate the "minor tree species"? e.g. in hyytiälä did you simulate only pine trees and removed the spruce trees or did you interpret spruce basal area as being pine basal area?: We interpreted the spruce basal area as pine basal area for the same DBH class. We did not simulate kroof stand.
How did you simulate nitrogen deposition from 2005 onwards in the 2b picontrol run? please confirm you kept them constant at 2005-levels?: GOTILWA+ does not account for N cycle.
Is there any stochastic element in your model (e.g. in the management or mortality submodel) that will lead to slightly different results if the model is re-run, even though all drivers etc. remain the same?: Not major differences, but the management procedure introduces some randomness in the model outputs.
What is the minimum diameter at which a „tree is considered a tree“? and is there a similar threshold for the minimum harvestable diameter?: From 5 cm DBH
Has your model been "historically calibrated" to any of the sites you simulated? e.g. has the site been used for model testing during model development?: No as far as I know, and especially not the current version of the model
Key model processes
Dynamic vegetation: - See in model setup -
Nitrogen limitation: Nitrogen limitation is not explicitly included in the model description.
Co2 effects: CO2 increase enhances assimilation rate.
Light interception: Two-layers canopy: Light - saturated - leafs, and shadow - unsaturated - leafs.
Light utilization: Photosynthesis
Phenology: Phenology described as temperature limitation upon photosynthesis. Also, temperature control upon burdburst and leaf fall.
Water stress: Stomata control upon photosynthesis related to soil water availability. Also, limitations in photosynthetic parameters depending on the degree of water deficit stress.
Heat stress: Exponential increase of tissue respiration according to increases in temperature. Reduced stomatal conductance under high vapor pressure deficit conditions.
Evapo-transpiration approach: Interception calculated depending on rain intensity and leaf area index. Leaf gas exchange calculated following Leuning (1995)
Differences in rooting depth: Two compartments in the rooting depth: Firstly, fixed proportion between aboveground and belowground biomass. Also, conservative Pipe Model structure among leaf area, sapwood area, and fine roots biomass.
Root distribution over depth: No
Closed energy balance: Leaf energy balance from Gates (1962)
Coupling/feedback between soil moisture and surface temperature: No
Causes of mortality in vegetation models
Age/senescence: No
Fire: No, but fire ocurrence probability, as well as percent of stems dead in case of fire, are calculated+
Drought: Yes
Insects: No
Storm: No
Stochastic random disturbance: No
Other: Hydraulic limitations due to cavitation are accounted in the model. Mortaility in GOTILWA+ model is driven by the balance of available carbohydrates for a given tree.
NBP components
Harvest: Stem wood is removed from the plot. Leafs and branches remain in the plot, and they dynamically are emited as CO2 or integrated into soil organic layers according to climate conditions.
Species / Plant Functional Types (PFTs)
List of species / pfts: Eucalyptus saligna Fraxinus excelsior Fagus sylvatica Pinus sylvestris Pinus halepensis Pinus pinaster Pinus nigra Quercus ilex Quercus pubescens Robinia pseudoacacia
Additional Forest Information
Forest sites simulated: Hyytiala, Peitz, Soro, Le Bray, Solling, Collelongo
Person responsible for model simulations in this simulation round
Daniel Nadal-Sala: daniel.sala@kit.edu, 0000-0002-0935-6201, Karlsruhe Institute of Technology (Germany)
Santiago Sabaté: santi.sabate@ub.edu, 0000-0003-1854-0761, University of Barcelona (Spain)
Additional persons involved: Daniel Nadal-Sala
Output Data
Experiments: historical (Hyytiälä, Peitz, Solling beech, Sorø, Le Bray, Collelongo)
Climate Drivers: None
Date: 2018-07-26
Basic information
Model Version: 4.0
Model Output License: CC0
Reference Paper: Main Reference: Nadal-Sala D, Keenan T, Sabaté S, Gracia C et al. Forest Eco-Physiological Models: Water Use and Carbon Sequestration. Managing Forest Ecosystems: The Challenge of Climate Change,None,81-102,2017
Reference Paper: Other References:
Resolution
Spatial aggregation: forest stand
Horizontal resolution: 1x1 ha
Additional spatial aggregation & resolution information: GOTIWA+ simulates 1 ha plots.
Temporal resolution of input data: climate variables: daily
Temporal resolution of input data: co2: daily
Temporal resolution of input data: land use/land cover: national inventories—based forests
Temporal resolution of input data: soil: any soil
Additional temporal resolution information: Climate variables disaggregated to hourly
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: Atmospheric CO2 concentration
Climate variables: tasmax, tas, tasmin, rlds, wind, rhs, rsds, ps, pr
Exceptions to Protocol
Exceptions: yes
Spin-up
Was a spin-up performed?: No
Spin-up design: No spin-up procedure. Initializing runs from the first year with both consistent stand structure and climate data available.
Natural Vegetation
Natural vegetation partition: GOTILWA+ only works with mono-specific stands.
Management & Adaptation Measures
Management: Management procedures as defined in the protocol. In natural runs, a constant regeneration has been considered. This regeneration happens every 10 year of simulation, and equals to the Initial density under managed conditions / rotation length * 10.
Extreme Events & Disturbances
Key challenges: Reproducing individual tree mortality. Reproducing loose of sapwood hydraulic conductivity under stresses. Drought and heath waves affect carbon and water balances.
Key model processes
Dynamic vegetation: - See in model setup -
Nitrogen limitation: Nitrogen limitation is not explicitly included in the model description.
Co2 effects: CO2 increase enhances assimilation rate.
Light interception: Two-layers canopy: Light - saturated - leafs, and shadow - unsaturated - leafs.
Light utilization: Photosynthesis following Farquhar and Von Caemmerer (1982)
Phenology: Phenology described as temperature limitation upon photosynthesis. Also, temperature control upon burdburst and leaf fall.
Water stress: Stomata control upon photosynthesis related to soil water availability. Also, limitations in photosynthetic parameters depending on the degree of water deficit stress.
Heat stress: Exponential increase of tissue respiration according to increases in temperature. Reduced stomatal conductance under high vapor pressure deficit conditions.
Evapo-transpiration approach: Interception calculated depending on rain intensity and leaf area index. Leaf gas exchange calculated following Leuning (1995)
Differences in rooting depth: Two compartments in the rooting depth: Firstly, fixed proportion between aboveground and belowground biomass. Also, conservative Pipe Model structure among leaf area, sapwood area, and fine roots biomass.
Root distribution over depth: No
Closed energy balance: Leaf energy balance from Gates (1962)
Coupling/feedback between soil moisture and surface temperature: No
Causes of mortality in vegetation models
Age/senescence: No
Fire: No, but fire ocurrence probability, as well as percent of stems dead in case of fire, are calculated+
Drought: Yes
Insects: No
Storm: No
Stochastic random disturbance: No
Other: Hydraulic limitations due to cavitation are accounted in the model. Mortaility in GOTILWA+ model is driven by the balance of available carbohydrates for a given tree.
NBP components
Harvest: Stem wood is removed from the stand. Leafs and branches remain in the stand, and they dynamically are emited as CO2 or integrated into soil organic layers according to climate conditions.
Species / Plant Functional Types (PFTs)
List of species / pfts: GOTILWA+ works with tree species. Pinus sylvestris Pinus halepensis Pinus pinaster Pinus nigra Quercus ilex Quercus pubescens Fraxinus excelsior Robinia pseudoacacia
Additional Forest Information
Forest sites simulated: Simulations ran in: Hyytiala, Peitz, Soro, Le Bray, Solling, Collelongo
Person responsible for model simulations in this simulation round
Daniel Nadal-Sala: daniel.sala@kit.edu, 0000-0002-0935-6201, Karlsruhe Institute of Technology (Germany)
Santiago Sabaté: santi.sabate@ub.edu, 0000-0003-1854-0761, University of Barcelona (Spain)
Additional persons involved: Dani Nadal—Sala