GROWTH SIMULATOR

A timber plantation growth simulator, with stands and management policies options.

Based on . By: Alejandro Miranda, Blas Mola and Víctor Hinojosa

1. For 34 types of eucalyptus and pinus plantations in the central-south of Chile, a statistical study fitted the following power law (tabla.csv):

$$ biomass(t) = \alpha \cdot t^\beta + \gamma $$

1. To extrapolate to earlier years; due to the formula yielding negative values (for a few types of pinus). A linear adjustment was made:

$$ \text{biomass}(t) = \begin{cases} \left(\alpha \cdot \text{stableyear}^\beta + \gamma \right) \cdot \frac{t}{\text{stableyear}} & \text{if } t < \text{stableyear} \\ \alpha \cdot t^\beta + \gamma & \text{if } t >= \text{stableyear} \end{cases} $$

Stable year is the year when the formula begins to yield stable results (it depends on the type of pinus).

1. A template for generating a timber plantation and different management policies was made (config.toml)

   horizonte = 10 # number of years to generate
   rodales = 36 # number of stands to generate, choosing one model at random
   
   [random]
   # random number generator seed: omit or comment for different results each run
   seed = 5
   # `low` (inclusive) to `high` (exclusive)
   # n, n+1 for getting a single value: n
   # see np.random.randint
   edades = [1, 18] # min, max age of generated stands
   has = [5, 15] #  min, max hectares of generated stands
   
   # ranges: start, stop, step
   # n, n+1 for getting a single value range: [n]
   # see np.arange
   [eucalyptus]
   cosechas = [10, 20, 3] # for each Eucalyptus stand, generate different biomass histories harvesting in the year 10, 13, 16 and 19 (4 histories) 
   
   [pino]
   raleos = [6, 11, 2] # thinning policies in the years 6, 8, 10.
   cosechas = [18, 29, 3] # harvesting policies in the years 18, 21, 24, ... (every 3 years)
   # all feasible histories combining thinning and harvesting policies will be generated
   min_ral = 6 #lower bound to tree thinning actions

2. For a real instance, the numbers of stands and its characteristics can be passed instead of generated at random. For this a .csv or .shp file is used, the data must include the following fields:

• fid: Stand or feature ID of the polygon in the .csv or .shp file
• mid: Unique identifier for the model to which the stand belongs, must match the id field in tabla.csv
• age: Age of the stand
• hectare (ha): Area in hectares

See auxiliary.py for GIS extraction or creation of this attributes table bosque_data.csv using the methods get_data and create_bosque.

quick start

0. Clone, download or just get simulator.py, tabla.csv and config.toml
1. Have numpy installed (and toml if python version < 3.11)
2. Console run: python simulator.py to generate at random or python simulator.py -f bosque_data.csv to use a real instance
3. Scripting/Interactive use:

   import simulator
   rodales = simulator.main(['-s']) # rodales is a list of dictionaries each representing a stand with its biomass history, harvesting and thinning policies

4. Done! The output is a list of several csv files: biomass.csv, events.csv, vendible.csv, codigo_kitral.csv & bosque.csv

more info

1. python simulator.py --help
2. See example folder
3. Read __doc__s
4. Read config.toml
5. Read Methodoly section of

models plots

example of new formula of biomass in model whith id 30