Impact model: SALEM

Sector
Forests
Region
regional

Information for the model SALEM 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
Mathieu Fortin: mathieu.fortin.re@gmail.com, French National Institute for Agriculture, Food, and Environment (INRAE) (France)
Thomas Pérot: thomas.perot@inrae.fr, French National Institute for Agriculture, Food, and Environment (INRAE) (France)
Patrick Vallet: patrick.vallet@inrae.fr, 0000-0003-2649-9447, French National Institute for Agriculture, Food, and Environment (INRAE) (France)
Francois de Coligny: francois.decoligny@inrae.fr, French National Institute for Agriculture, Food, and Environment (INRAE) (France)
Basic information
Model Version: 2.0
Model Output License: CC0
Model Homepage: https://zenodo.org/record/5578340
Reference Paper: Main Reference: Aussenac R, Pérot T, Fortin M, de Coligny F, Monnet J, Vallet P et al. The Salem simulator version 2.0: a tool for predicting the productivity of pure and mixed forest stands and simulating management operations. Open Research Europe,1,61,2021
Resolution
Spatial aggregation: forest stand
Temporal resolution of input data: climate variables: annual
Input data
Additional information about input variables: No climatic data is used. Only a synthetic site index based on initial height measurements.
Spin-up
Was a spin-up performed?: No
Natural Vegetation
Natural vegetation dynamics: Forest growth is simulated using empirically calibrated growth equation. Salem is calibrated on French NFI data.
Management & Adaptation Measures
Management: Forest management is based on stand density, and type of thinnings.
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?: Number of stems and Mean quadratic diameter Initial heights were used to calculate a site index
Which data from profound db did you use for initialisation (name of variable, which year)? from stand data or from individual tree data?: Stand data : dbhDQ_cm, density_treeha, age Tree data (for site index only) : dbh1_cm, height1_m
How is management implemented? e.g. do you harvest biomass/basal area proportions or by tree numbers or dimensions (target dbh)?: Harvest is done by reducing stand basal area according to a "kg" index (kg < 1 : from below, kg ~ 1,:from above)
When is harvesting simulated by your model (start/middle/end of the year, i.e., before or after the growing season)?: After the growing season
How do you regenerate? do you plant seedlings one year after harvest or several years of gap and then plant larger saplings?: No regeneration
How are the unmanaged simulations designed? is there some kind of regrowth/regeneration or are the existing trees just growing older and older?: Trees grow older and older, and a mortality process is triggered when density is over a self thinning boundary
How are models implementing the noco2 scenario? please confirm that co2 is follwing the historical trend (based on profund db) until 2000 (for isimipft) or 2005 (for isimip2b) and then fixed at 2000 or 2005 value respectively?: no CO2 input
Does your model consider leap-years or a 365 calendar only? or any other calendar?: Not applicable : simulation step is 1 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?: The two main species are simulated
How did you simulate nitrogen deposition from 2005 onwards in the 2b picontrol run? please confirm you kept them constant at 2005-levels?: NA
What is the soil depth you assumed for each site and how many soil layers (including their depths) do you assume in each site? please upload a list of the soil depth and soil layers your model assumes for each site as an attachment (section 7).: Not applicable. Implicitly included in the site index
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?: no
What is the minimum diameter at which a „tree is considered a tree“? and is there a similar threshold for the minimum harvestable diameter?: Minimum threshold of 7.5 cm No minimum harvestable diameter
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
Please upload a list of your parameters as an attachment (section 7). the list should include species-specific parameters and other parameters not depending on initialization data including the following information: short name, long name, short explanation, unit, value, see here for an example (http://www.pik-potsdam.de/4c/web_4c/theory/parameter_table_0514.pdf): Salem is an empirical model. Parameters are not corresponding to specific processes. All species parameters are given here : https://open-research-europe.ec.europa.eu/articles/1-61
Key model processes
Dynamic vegetation: Empirically calibrated growth model
Nitrogen limitation: no
Co2 effects: no
Light interception: no
Light utilization: no
Phenology: no
Water stress: no
Heat stress: no
Evapo-transpiration approach: no
Differences in rooting depth: no
Root distribution over depth: no
Closed energy balance: no
Coupling/feedback between soil moisture and surface temperature: no
Latent heat: no
Sensible heat: no
Assimilation: no
Respiration: no
Carbon allocation: no
Regeneration/planting: no
Soil water balance: no
Carbon/nitrogen balance: no
Are feedbacks considered that reflect the influence of changing carbon state variables on the other system components and driving data (i.e. growth (leaf area), light, temperature, water availability, nutrient availability)?: no
Causes of mortality in vegetation models
Age/senescence: NA
Fire: NA
Drought: NA
Insects: NA
Storm: If a storm happen, a thinning is triggered depending on the storm severity.
Stochastic random disturbance: NA
Other: Mortality is trigger when the density of the stand reaches a self thinning boundary, calibrated on NFI data.
NBP components
Fire: no
Land-use change: no
Harvest: Harvest from forest management
Other processes: NA
Species / Plant Functional Types (PFTs)
List of species / pfts: [Quercus robur] ([Quro]); [Quercus petraea] ([Qupe]); [Quercus pubescens] ([Qupu]); [Fagus sylvatica] ([Fasy]); [Pinus pinaster] ([Pipi]); [Pinus sylvestris] ([Pisy]); [Pinus nigra subsplaricio] ([Pila]); [Pinus nigra subspnigra] ([Pini]); [Pinus halepensis] ([Piha]); [Abies alba] ([Abal]); [Picea abies] ([Piab]); [Pseudotsuga menziesii] ([Psme]);
Model output specifications
Do you provide the initial state in your simulation outputs (i.e., at year 0; before the simulation starts)?: yes
Output format: output at stand level
When you report a variable as "xxx-total" does it equal the (sum of) "xxx-species" value(s)? or are there confounding factors such as ground/herbaceous vegetation contributing to the "total" in your model?: NA
Did you report any output per dbh-class? if yes, which variables?: no
Additional Forest Information
Forest sites simulated: Collelongo Kroof Solling beech Solling spruce Soro Bili Kriz Hyytiala Le Bray Peitz