> ## Documentation Index
> Fetch the complete documentation index at: https://pyfia.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 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

<Info>**EVALID:** 82003 (Colorado 2020 GRM) · Annual mortality of merchantable bole wood volume of growing-stock trees on forest land · [source](https://github.com/mihiarc/pyfia/blob/main/reference/queries/mortality/colorado_mortality_merchantable_volume.sql)</Info>

<Accordion title="View SQL">
  ```sql theme={null}
  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;
  ```
</Accordion>

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

<Info>**EVALID:** 372303 (North Carolina 2023 GRM) · Average annual mortality rate in trees per acre on forest land · [source](https://github.com/mihiarc/pyfia/blob/main/reference/queries/mortality/north_carolina_mortality_trees_per_acre.sql)</Info>

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

<Accordion title="View SQL">
  ```sql theme={null}
  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;
  ```
</Accordion>

## 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:

<CardGroup cols={2}>
  <Card title="By damage agent" icon="bug" href="https://github.com/mihiarc/pyfia/blob/main/reference/queries/mortality/georgia_growing_stock_mortality_by_agent.sql">
    Tree-level cause of death (`AGENTCD`) bucketed into insect / disease / fire / animal / weather / …, by species.
  </Card>

  <Card title="By disturbance type" icon="cloud-bolt" href="https://github.com/mihiarc/pyfia/blob/main/reference/queries/mortality/georgia_growing_stock_mortality_by_disturbance.sql">
    Condition-level disturbance (`DSTRBCD1`) — fire, wind, drought, … — by species.
  </Card>

  <Card title="With stratified variance" icon="square-root-variable" href="https://github.com/mihiarc/pyfia/blob/main/reference/queries/mortality/mortality_with_variance.sql">
    The full FIA handbook variance estimator — stratified at the estimation-unit level, aggregated to evaluation-group totals with SE (\~180 lines).
  </Card>
</CardGroup>

<Tip>The Python equivalent is [`mortality()`](/api/pyfia-estimation-estimators-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.</Tip>