Impact model: 3PG

The 3-PG model (Physiological Processes Predicting Growth) was developed by Landsberg and Waring (1997). It was developed to bridge the gap between conventional, mensuration-based growth and yield, and process-based carbon balance models. The output variables it produces are of interest and relevance to forest managers.
3-PG calculates the radiant energy absorbed by forest canopies and converts it into biomass production. The efficiency of radiation conversion is modified by the effects of nutrition, soil drought (thebook_cover model includes continuous calculation of water balance), atmospheric vapour pressure deficits and stand age.

ISIMIP2a

Person responsible for model simulations in this simulation round

Volodymyr Trotsiuk: volodymyr.trotsiuk@wsl.ch, 0000-0002-8363-656X, ETH Zurich (Switzerland)

Additional persons involved: Volodymyr Trotsiuk

Basic information

Model Version: 0.1.1

Model Output License: CC0

Model Homepage: https://github.com/trotsiuk/r3PG

Reference Paper: Main Reference: Landsberg J, Waring R et al. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management,95,209-228,2002

Reference Paper: Other References: Trotsiuk, V., Hartig, F., Forrester, D.I. et al. Review for "r3PG – an R package for simulating forest growth using the 3‐PG process‐based model". Methods Ecol. Evol.,11,1470–1475,2020

Resolution

Spatial aggregation: forest stand

Temporal resolution of input data: climate variables: monthly

Temporal resolution of input data: co2: annual

Temporal resolution of input data: soil: constant

Input data

Observed atmospheric climate data sets used: Historical observed climate data

Socio-economic data sets used: Historical gridded Gross Domestic Product (GDP)

Land use data sets used: Historical, gridded land use (HYDE 3.0)

Other human influences data sets used: Fishing intensity

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

Additional information about input variables: frost days

Spin-up

Was a spin-up performed?: No

Management & Adaptation Measures

Management: Forest management was applied

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?: Tree number and total tree biomass per stands

How is management implemented? e.g. do you harvest biomass/basal area proportions or by tree numbers or dimensions (target dbh)?: Number of trees removed and the type of management (from above, from below, neutral)

When is harvesting simulated by your model (start/middle/end of the year, i.e., before or after the growing season)?: mostly after the growing season

How are the unmanaged simulations designed? is there some kind of regrowth/regeneration or are the existing trees just growing older and older?: no regeneration/regrowth

Does your model consider leap-years or a 365 calendar only? or any other calendar?: no

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).: one soil layer

What is the minimum diameter at which a „tree is considered a tree“? and is there a similar threshold for the minimum harvestable diameter?: 1 cm

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

Key model processes

Dynamic vegetation: yes: Forest dynamics are described by forest growth, regeneration/planting, management.

Nitrogen limitation: no

Co2 effects: yes

Light interception: yes: The total fraction of photosynthetically active radiation absorbed by each cohort is calculated each time based on the Lambert-Beer law.

Phenology: only for deciduous trees using a beginning and end of growing season (Forrester and Tang 2016)

Water stress: yes: After calculating water demand by forest stand and water supply from the soil for each cohort photosynthesis is being reduced if demand is greater than supply. Allocation is also affected.

Evapo-transpiration approach: yes: A single soil layer model with evapo- transpiration determined from Penman-Monteith equation.

Differences in rooting depth: no

Root distribution over depth: no

Closed energy balance: It is not considered.

Coupling/feedback between soil moisture and surface temperature: no

Latent heat: no

Sensible heat: no

Causes of mortality in vegetation models

Age/senescence: yes: Age related stress mortality is calculated.

Other: yes: Self-thinning mortality due to light availability is implemented (stress mortality).

NBP components

Harvest: The model includes harvests, which effect all fluxes.

Other processes: Dead biomass which is not harvested