Quantifying the errors in animal contacts recorded by proximity loggers

Automated contact detection by means of proximity loggers permits the measurement encounters between individuals (animal-animal contacts) and time spent in a focal resource interest (animal-fixed logger contacts). The ecological inference derived from is intrinsically associated with distance at which occurred. But no currently exist that record this therefore all estimations are error. Here we applied probabilistic approach to model relationship inter-logger distance, quantify error, on free-ranging animals semi-controlled settings. probability recording declined loggers, decline was steeper for weaker radio transmission powers. Even when were adjacent, not guaranteed, irrespective power. Accordingly, precision sensitivity system varied as function power, experimental setting (e.g., depending animal body mass fine-scale movements). By accounting these relationships, able estimate detected occurred certain contacts missed (i.e., false negatives). These calibration exercises have potential improve predictability study enhance applicability key wildlife management issues such disease rates or use landscape features resources.