Mortality

Growing-stock mortality from the GRM tables — by cause, by disturbance, and with stratified variance.

Mortality queries use the GRM (growth/removal/mortality) tables and a GRM evaluation (EVALID ending in 03). Annual rates come from TREE_GRM_COMPONENT filtered to COMPONENT LIKE 'MORTALITY%', with subplot-type adjustment factors.

Colorado — annual merchantable volume mortality

EVALID: 82003 (Colorado 2020 GRM) · Annual mortality of merchantable bole wood volume of growing-stock trees on forest land · source

View SQL

SELECT
    ps.evalid,
    SUM(
        tgc.SUBP_COMPONENT_GS_FOREST * t.VOLCFNET *
        CASE
            WHEN t.DIA < 5.0 THEN ps.ADJ_FACTOR_MICR
            WHEN t.DIA < COALESCE(CAST(p.MACRO_BREAKPOINT_DIA AS DOUBLE), 9999.0) THEN ps.ADJ_FACTOR_SUBP
            ELSE ps.ADJ_FACTOR_MACR
        END * ps.EXPNS
    ) AS annual_mortality_cuft,
    COUNT(DISTINCT p.CN) AS plot_count
FROM POP_STRATUM ps
JOIN POP_PLOT_STRATUM_ASSGN ppsa ON ppsa.STRATUM_CN = ps.CN
JOIN PLOT p ON ppsa.PLT_CN = p.CN
JOIN COND c ON c.PLT_CN = p.CN
JOIN TREE_GRM_COMPONENT tgc ON tgc.PLT_CN = p.CN
JOIN TREE_GRM_BEGIN t ON t.TRE_CN = tgc.TRE_CN
WHERE
    c.COND_STATUS_CD = 1
    AND tgc.COMPONENT LIKE 'MORTALITY%'
    AND t.VOLCFNET > 0
    AND ps.rscd = 8                -- Colorado
    AND ps.evalid = 82003
GROUP BY ps.evalid;

North Carolina — mortality rate (trees/acre/year)

EVALID: 372303 (North Carolina 2023 GRM) · Average annual mortality rate in trees per acre on forest land · source

Divides expanded annual mortality (trees) by expanded forest area to get a per-acre rate.

View SQL

SELECT
    ps.evalid,
    SUM(
        tgc.SUBP_TPAMORT_UNADJ_AL_FOREST *
        CASE
            WHEN t.DIA < 5.0 THEN ps.ADJ_FACTOR_MICR
            WHEN t.DIA < COALESCE(CAST(p.MACRO_BREAKPOINT_DIA AS DOUBLE), 9999.0) THEN ps.ADJ_FACTOR_SUBP
            ELSE ps.ADJ_FACTOR_MACR
        END * ps.EXPNS
    ) / NULLIF(SUM(
        c.CONDPROP_UNADJ *
        CASE c.PROP_BASIS WHEN 'MACR' THEN ps.ADJ_FACTOR_MACR ELSE ps.ADJ_FACTOR_SUBP END * ps.EXPNS
    ), 0) AS mortality_trees_per_acre_per_year
FROM POP_STRATUM ps
JOIN POP_PLOT_STRATUM_ASSGN ppsa ON ppsa.STRATUM_CN = ps.CN
JOIN PLOT p ON ppsa.PLT_CN = p.CN
JOIN COND c ON c.PLT_CN = p.CN
JOIN TREE_GRM_COMPONENT tgc ON tgc.PLT_CN = p.CN
JOIN TREE_GRM_BEGIN t ON t.TRE_CN = tgc.TRE_CN
WHERE
    c.COND_STATUS_CD = 1
    AND tgc.COMPONENT LIKE 'MORTALITY%'
    AND tgc.SUBP_TPAMORT_UNADJ_AL_FOREST > 0
    AND ps.rscd = 33               -- North Carolina
    AND ps.evalid = 372303
GROUP BY ps.evalid;

Georgia — mortality by cause (132303)

These EVALIDator translations group growing-stock mortality (trees ≥5” DBH on timberland) by cause. They’re long, multi-join queries with full plot-condition grouping for correct expansion — view the authoritative .sql so the statistics stay exact:

By damage agent

Tree-level cause of death (AGENTCD) bucketed into insect / disease / fire / animal / weather / …, by species.

By disturbance type

Condition-level disturbance (DSTRBCD1) — fire, wind, drought, … — by species.

With stratified variance

The full FIA handbook variance estimator — stratified at the estimation-unit level, aggregated to evaluation-group totals with SE (~180 lines).

The Python equivalent is mortality() — pass grp_by="AGENTCD" or "DSTRBCD1". Standard errors (MORT_ACRE_SE, MORT_TOTAL_SE) come back automatically; add variance=True for the matching variance columns.