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pyfia.estimation.estimators.growth

Growth estimation for FIA data using GRM methodology. Implements FIA’s Growth-Removal-Mortality methodology for calculating annual tree growth using TREE_GRM_COMPONENT, TREE_GRM_MIDPT, and TREE_GRM_BEGIN tables following EVALIDator approach.

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Functions

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growth

Estimate annual tree growth from FIA data using GRM methodology. Calculates annual growth of tree volume, biomass, or tree count using FIA’s Growth-Removal-Mortality (GRM) tables following EVALIDator methodology. Args:
  • db: Database connection or path to FIA database.
  • grp_by: Column name(s) to group results by.
  • by_species: If True, group results by species code (SPCD).
  • by_size_class: If True, group results by diameter size classes.
  • size_class_type: Type of size class grouping to use (only applies when by_size_class=True):
  • “standard”: FIA numeric ranges (1.0-4.9, 5.0-9.9, etc.)
  • “descriptive”: Text labels (Saplings, Small, Medium, Large)
  • “market”: Timber market categories (Pulpwood, Chip-n-Saw, Sawtimber)
  • land_type: Land type to include in estimation.
  • tree_type: Tree population to include (GRM tables):
  • ‘gs’: growing stock
  • ‘al’ or ‘live’: all live trees at least 1 inch d.b.h., saplings on the microplot included (EVALIDator’s “trees at least 1 inch”)
  • ‘sl’ or ‘sawtimber’: sawtimber-size trees
  • measure: What to measure in the growth estimation.
  • tree_domain: SQL-like filter expression for tree-level filtering, e.g. "SPCD == 131". As in removals() and mortality(), DIA, SPCD and STATUSCD are the GRM midpoint values (TREE_GRM_MIDPT), DIA_BEGIN/DIA_MIDPT/DIA_END are the GRM diameters, and other TREE columns come from the tree’s time-2 record. An expression naming a column that doesn’t exist raises InvalidDomainError.
  • area_domain: SQL-like filter expression for area/condition-level filtering.
  • totals: If True, include population-level total estimates.
  • variance: If True, also return variance columns (*_VARIANCE) alongside the standard errors (*_SE, always returned). Variance = SE squared.
  • most_recent: If True, automatically filter to the most recent evaluation.
Returns:
  • Growth estimates with columns:
  • GROWTH_ACRE: Annual growth per acre
  • GROWTH_TOTAL: Total annual growth (if totals=True)
  • GROWTH_ACRE_SE: Standard error of per-acre estimate
  • GROWTH_TOTAL_SE: Standard error of total estimate (if totals=True)
  • GROWTH_ACRE_VARIANCE, GROWTH_TOTAL_VARIANCE: Variance of the estimates, equal to the matching _SE squared (if variance=True)
  • Additional grouping columns if specified
Examples: Basic volume growth on forestland:
results = growth(db, measure=“volume”, land_type=“forest”) Growth by species (tree count): results = growth(db, by_species=True, measure=“count”)

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Classes

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GrowthEstimator

Growth estimator for FIA data using GRM methodology. Estimates annual tree growth in terms of volume, biomass, or trees per acre using the TREE_GRM_COMPONENT, TREE_GRM_MIDPT, and TREE_GRM_BEGIN tables. Follows EVALIDator methodology with component-based calculations. Methods:

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component_type

Return ‘growth’ as the GRM component type.

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load_data

Load and join tables following EVALIDator SQL join sequence. Growth requires complex join pattern with BEGINEND cross-join. Cannot use the simple GRM loading pattern.

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apply_filters

Apply growth-specific filters. CRITICAL: Include ALL components for BEGINEND cross-join methodology. Do NOT filter by COND_STATUS_CD - GRM columns already handle land basis.

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calculate_values

Calculate growth values using BEGINEND ONEORTWO methodology. Implements EVALIDator’s ONEORTWO logic:
  • ONEORTWO=2: Add ending volumes (positive contribution)
  • ONEORTWO=1: Subtract beginning volumes (negative contribution) Sum across ONEORTWO rows gives NET growth = ending - beginning

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aggregate_results

Aggregate growth with two-stage aggregation. Returns:
  • Bundle containing results, plot_tree_data, and group_cols for explicit variance calculation.

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calculate_variance

Calculate variance for growth estimates using ratio-of-means formula. Implements Bechtold & Patterson (2005) stratified variance calculation. Args:
  • agg_result: Bundle containing results, plot_tree_data, and group_cols from aggregate_results().
Returns:
  • Results with variance columns added.

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format_output

Format growth estimation output.