Abstract

Abstract Traditional occupancy models that record detection/non‐detection (DND) of a species typically rely on either spatial or temporal survey replication to estimate model parameters. Recording the time until a species is first encountered after starting a survey is often possible with little extra effort and such time‐to‐detection (TTD) surveys may be more efficient than pure DND surveys. Using continuous time data, TTD occupancy models can in theory estimate occupancy and detection parameters using a single TTD survey. However, the robustness and general applicability of TTD models has not been widely addressed and their effectiveness in different study systems remains unknown. We use simulations and bird data of 63 species from a field study in the Karoo region of South Africa to explicitly compare estimates of occupancy, detection and species richness between DND and TTD models under various levels of survey replication and for species with different occupancy and detection characteristics. Simulations revealed that for inconspicuous species single survey TTD models can perform better or equally as well as DND models with a higher number of replicates. This effect was attenuated in widespread species. The benefits of TTD models were more pronounced at low survey replicates and performance of the two methods converged quickly as the number of survey replicates increased. However, results from the field data showed that a single TTD survey was not adequate to reliably estimate occupancy, detection and species richness; especially in rare and inconspicuous species. Increasing the number of TTD surveys to two replicates improved the models substantially. Our results demonstrate that the general utility of TTD surveys depends on the characteristics of the species considered in the study. A single TTD survey may be sufficient in some study designs but is unlikely to be sufficient in most multi‐species field scenarios where communities are made up of species that have a wide range of detection and occupancy probabilities. TTD surveys do provide benefits, however, in that data can be used to construct detection curves which can be used to guide survey effort in the design of future studies.

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