Rethinking “absence” in biodiversity data collection and modeling

What this was about

Rob Stevenson presented the outcome of a working group (with Abby Benson, Ruben Perez, Deborah Arlt, Yiming and Wesley Hochachka) on confusing 'absence' terminology. He argued presence and absence are asymmetric (presence is a fact, absence a question) and absence is only meaningful against an expectation frame such as a Humboldt Extension survey target. Surveying methodology and analysis texts, the group found the museum (presence-only) and biological survey (repeated, effort-based) communities use different data and models, with detectability as the unifying concept. The main outcome was the TDWG Executive's approval in May of changing Darwin Core occurrenceStatus values from present/absent to detected/not detected.

Why it matters. The occurrenceStatus vocabulary change affects how every data manager records and interprets non-detections, and clarifies terminology for distribution modelling.

In the room

• Many overlapping absence terms exist in the literature (confirmed absence, zero count, pseudo-absence, etc.).
• Presence and absence are asymmetric: presence is a fact, absence is a question.
• Absence is meaningful only against a model of what should have been present; survey targets in the Humboldt Extension provide that frame.
• Survey methodology books rarely define absence terms in data-sharing terms; Hill et al.'s handbook was most useful.
• Museum data (presence-only, Bioclim/GARP/MaxEnt niche models) and survey data (repeated surveys, occupancy and hierarchical models) come from different communities.
• Detectability, from mark-recapture, distance sampling and occupancy models, is the key clarifying concept.
• Darwin Core occurrenceStatus changed from present/absent to detected/not detected.

Notable moments