The CAP Field as the Whole Point
CAP — circunferencia a la altura del pecho — is the single number that anchors every other metric in a forest inventory record. Without it, HT and HC are decorative. Without it, copa measurements float in context-free space. The entire value of this template is built around getting that circumference reading off the tape, entered, and GPS-anchored before you move to the next tree.
Field data collection in tropical forest inventory fails at one predictable point: transcription delay. You take measurements all morning, you record CAP on a tally sheet, you record HT with a hypsometer reading, you sketch crown axes with your eye. Then you get back to camp with twenty trees' worth of data written in a field notebook that got wet at 11 AM when it rained for forty minutes, and you spend the rest of the day trying to remember which reading belonged to which polygon-ID combination.
The Memento structure eliminates the transcription lag entirely. Each tree is a record created at the stem, tagged with the polygon dropdown, assigned an ID in the field, and GPS-stamped immediately. There's no intermediate paper stage. The data is entered once, where the tree is standing.
What Estrato and Fenologia Actually Tell You at Scale
The Estrato field — Brinzal, Latizal, Fustal — tracks the developmental stage of each individual. In a mixed-age natural forest, this stratification is the difference between a regeneration survey and a commercial-volume inventory. Brinzales are seedlings under 1.5m; latizales are young trees past the seedling stage but below commercial-diameter thresholds; fustales are mature stems. Filtering your dataset by Estrato lets you generate recruitment curves by polygon — which is the only way to answer whether the canopy is replacing itself.
Fenologia captures the reproductive state at the moment of observation: Flor, Fruto, Semilla, Vegetativo. In species where seed-set timing matters for collection programs or wildlife habitat assessment, this field converts a routine biometric visit into a phenological monitoring series. Run the same polygon every six weeks and tag the Fenologia state each time. Over a year, you have a phenological calendar for every species in every polygon — without any additional fieldwork.
The Estado_Fitosanitario checkboxes cover Hongos, Necrosis, Herbivoria, Sano, Patogenos Indet, Amarillamiento, Ausencia de hojas, Muerto. "Sano" defaults to true, which is the right default — most trees on any given visit are healthy, and defaulting otherwise would create systematic data entry friction. The pathogen categories are intentionally broad. You're not diagnosing in the field; you're flagging for follow-up assessment and tracking incidence rates by polygon over time.
The Measurement Geometry That Actually Matters
CopaX and CopaY — crown axis measurements in meters — capture canopy closure geometry in a way that basal area alone cannot. A 35cm-CAP fustal with a 4m x 4m copa is occupying a very different light environment than the same stem carrying an 8m x 3m canopy. In plantation monitoring or agroforestry systems where crown overlap drives understory light availability, these two fields combined with GPS coordinates give you enough to reconstruct a canopy cover map without drone overflight.
HC — commercial height — diverges from HT most dramatically in trees with significant crown base height variation, which in the polygons marked "Palmar" indicates a fundamentally different growth form than in the SA-SI series. The gap between HT and HC as a proportion of total height tells you something about form class that volumetric equations need.
The Foto field pins a visual record to every tree-entry combination. At six months, when Estado_Fitosanitario on a tree in R9B shows Necrosis where it previously showed Sano, the photo pair confirms whether the change is real or a calibration artifact between field crews.