The Nested Plot Field Is Doing More Work Than It Looks
The Plot size choice — Full size or Nested plot — is a small decision with significant consequences for carbon stock calculations. In nested subplot designs, small-diameter stems recorded in the inner subplot must not be included in the analysis layer for the full plot. If that distinction isn't captured at the point of measurement, you end up with two different analysts making two different assumptions during processing, and neither can prove the other is wrong.
Most field apps either force you to create separate databases for full-plot and nested-plot records, or they leave a free-text observations field to carry the distinction informally. Neither solution is queryable. A choice field with exactly two options is. When you export to R or ArcGIS, that column becomes a clean binary variable for filtering — no string parsing, no lookup table, no ambiguity.
Transect and Plot Position as Structural Context
The combination of Management type (CF/NonCF), Transect (T1 through T6), and Plot (P1 through P5) creates a fully structured location key for each tree record without requiring GPS coordinates at the tree level. In community forest carbon studies, coordinates at the transect origin combined with a bearing and plot number are often sufficient — and more important, they're what the study design already specified. The database respects the study geometry rather than imposing a new one.
Five transects with five plots each, in two management types, with both full-size and nested subplots at each position means a single campaign could yield over a hundred plot records, each with multiple tree records. At that volume, the structured choice fields for transect and plot stop being data entry convenience and start being the primary analysis variables. Sorting and aggregating two hundred trees by transect and management type takes seconds. Reconstructing those groupings from handwritten plot labels scanned to PDF takes a day, and it's still not reliable.
What Biomass Estimates Look Like When the Raw DBH Is Preserved
The five sequential DBH fields — DBH through DBH 5 — reflect the reality of sampling irregular trunks where a single diameter measurement would introduce trunk-geometry error into the basal area estimate. For carbon studies, basal area is the gateway to biomass through allometric equations, and those equations are sensitive. A 10% error in DBH compounds through the allometric calculation.
Storing five raw readings lets the analyst apply the averaging method specified in the project protocol, which may differ between the CF and NonCF areas if different standards govern each. It also means the field crew doesn't need to perform arithmetic on the slope — a mistake-prone step when you're on your twelfth tree and the humidity is 90%.
Dead trees in a carbon plot are not null entries. Standing dead wood carries carbon, and the dead versus alive distinction in Tree state is the first split in any IPCC Tier 2 accounting approach. A study that loses the dead stem count because the datasheet had no dedicated state field has a gap in its carbon pools that no amount of retrospective calculation can fill.
The User field embedded in the record is understated. In a multi-person sampling crew, inter-observer variability in DBH measurement is a known issue. Tagging each record to the individual who took the measurement allows bias analysis by enumerator — something most field database designs never even consider collecting.