pyfvs-fia 0.2.2

Python implementation of the Forest Vegetation Simulator - Part of the FIA Python Ecosystem

Forest growth modeling in Python

Part of the FIAtools Python Ecosystem
pyFIA · gridFIA · pyFVS · askFIA

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A Python implementation of the Forest Vegetation Simulator (FVS) Southern variant. Simulate growth and yield for loblolly, shortleaf, longleaf, and slash pine from age 0 to 50 years.

Supported Species

Code	Species	Scientific Name
LP	Loblolly Pine	Pinus taeda
SP	Shortleaf Pine	Pinus echinata
LL	Longleaf Pine	Pinus palustris
SA	Slash Pine	Pinus elliottii

Quick Start

pip install pyfvs

from pyfvs import Stand

# Initialize a planted stand
stand = Stand.initialize_planted(
    species="LP",
    trees_per_acre=500,
    site_index=70
)

# Simulate 50 years of growth
stand.grow(years=50)

# Get results
metrics = stand.get_metrics()
print(f"Final volume: {metrics['volume']:.0f} ft³/acre")

Growth Models

pyFVS implements individual tree growth models from FVS documentation:

Height-Diameter (Curtis-Arney)

height = 4.5 + p2 × exp(-p3 × DBH^p4)

Large Tree Diameter Growth

ln(DDS) = β₁ + β₂×ln(DBH) + β₃×DBH² + β₄×ln(CR) + β₅×RH + β₆×SI + ...

Small Tree Height Growth (Chapman-Richards)

height = c1 × SI^c2 × (1 - exp(c3 × age))^(c4 × SI^c5)

Architecture

Tree Initial State
       │
       ▼
   DBH >= 3.0? ──No──► Small Tree Model
       │                    │
      Yes                   ▼
       │            Height Growth
       ▼                    │
  Large Tree Model          ▼
       │            Height-Diameter
       ▼                    │
  Predict ln(DDS)           ▼
       │              Update DBH
       ▼                    │
  Calculate DBH Growth      │
       │                    │
       └────────┬───────────┘
                ▼
        Update Crown Ratio
                │
                ▼
        Crown Competition
                │
                ▼
        Updated Tree State

Configuration

Species parameters are stored in YAML configuration files:

# cfg/species/lp_loblolly_pine.yaml
species_code: "LP"
common_name: "Loblolly Pine"
height_diameter:
  p2: 243.860648
  p3: 4.28460566
  p4: -0.47130185
bark_ratio:
  b1: -0.48140
  b2: 0.91413

Output

pyFVS generates yield tables with standard forest metrics:

Age	TPA	QMD	Height	BA	Volume
0	500	0.5	1.0	0.7	0
10	485	4.2	28.5	47.2	892
20	420	7.8	52.1	139.8	3,241
30	310	10.4	68.3	182.5	5,128
...	...	...	...	...	...

Integration with pyFIA

from pyfia import FIA
from pyfvs import Stand

# Get current stand conditions from FIA
with FIA("database.duckdb") as db:
    db.clip_by_state(37)
    stand_data = db.get_stand_summary(plot_id="123")

# Initialize pyFVS with FIA data
stand = Stand.from_fia_data(stand_data)
stand.grow(years=30)

The FIAtools Ecosystem

pyFVS is part of the FIAtools Python ecosystem - a unified suite of open-source tools for forest inventory analysis:

Tool	Purpose	Key Features
pyFIA	Survey & plot data	DuckDB backend, 10-100x faster than EVALIDator
gridFIA	Spatial raster analysis	327 species at 30m resolution, Zarr storage
pyFVS	Growth simulation	Chapman-Richards curves, yield projections
askFIA	AI interface	Natural language queries for forest data

Explore the full ecosystem at fiatools.org

References

• FVS Southern Variant Documentation
• Bechtold & Patterson (2005) "The Enhanced Forest Inventory and Analysis Program"

Citation

@software{pyfvs2025,
  title = {pyFVS: Python Implementation of the Forest Vegetation Simulator},
  author = {Mihiar, Christopher},
  year = {2025},
  url = {https://fiatools.org}
}

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fiatools.org · Python Ecosystem for Forest Inventory Analysis
_{Built by Chris Mihiar · USDA Forest Service Southern Research Station}