Bill Depth at 26.8mm Is Not a Note — It's a Discriminant Function Variable
The Sex determination script embedded in this template runs a linear discriminant function: 1.245 × bill_depth + 0.202 × bill_length − 24.459. If the result is ≤ 0.311, the bird is logged as Female. Above that threshold, Male. The calculation triggers automatically on entry creation when Sex is set to "Unknown" and both bill measurements are present. This is not a shortcut. It's morphometric sexing — the standard non-invasive method for species where plumage dimorphism is absent or ambiguous, which applies to all three species tracked here: yellow-eyed, little, and Fiordland penguins.
That a field-deployable database is running discriminant function logic at the point of data entry is what separates this tool from a spreadsheet. The measurement goes in, the sex gets resolved, the researcher moves on. No post-season R script, no Excel formula column, no "check this later" note that never gets checked.
The Record Architecture Behind a Single Banded Bird
Each entry in this database is a penguin. Not a sighting — a bird. The Bird ID field uses barcode scanning, typically the PIT tag or transponder ID that uniquely identifies the individual across its entire monitored life. That ID links this record to every nest observation entry logged against it in the companion monitoring database, where adult IDs are stored as relational entries.
The marking event and the resighting event are structurally separated within the same record. Marking captures the initial encounter: DateTime_marking, Location_marking (GPS), Site_marking, Tag type (Allflex 23mm, Trovan 11mm or 8mm, flipper band), the tagger's identity, and the full morphometric suite — weight, bill depth, bill length, flipper length, foot length, head length. Resighting captures every subsequent physical encounter with the same individual, with its own timestamp, location, observer, and full re-measurement capability.
The Mugshot fields — one for marking, one for resighting — store a facial photograph. For penguin researchers, this is not a novelty. Facial pattern recognition is an active method of individual identification for some penguin species, particularly little penguins. Having the mugshot embedded in the same record as the PIT tag reading means that if a transponder fails or migrates subcutaneously, you still have a photographic reference to cross-check against.
Finding a Bird in the Dark, 200 Records Deep
Three months into a field season on a population spread across multiple sites, you get a transponder hit from a reader at a nest box that doesn't match the nest ID logged at marking. Pull the record: the bird was banded as a chick at site C, first resighted as an adult at site A guarding chicks in year two, and is now showing up at site B during moult. The Nest ID fields — both marking and resighting — are linked to the nest library via entries fields, not typed text. So you can filter every bird ever recorded at nest B-07 in under ten seconds, and cross-reference whether this individual's status at the current resighting is "Moulting" or something that warrants closer inspection.
That's the difference between a database and a log. The log tells you what happened today. The database tells you that this specific bird has appeared at three different nest sites across four years, was resighted guarding chicks twice, and the last recorded weight was 2,340g — 410g below its marking weight, which means it's well into moult and the weight drop is expected.