Designing occupancy studies: general advice and allocating survey effort
Article first published online: 31 OCT 2005
Journal of Applied Ecology
Volume 42, Issue 6, pages 1105–1114, December 2005
How to Cite
MACKENZIE, D. I. and ROYLE, J. A. (2005), Designing occupancy studies: general advice and allocating survey effort. Journal of Applied Ecology, 42: 1105–1114. doi: 10.1111/j.1365-2664.2005.01098.x
- Issue published online: 23 NOV 2005
- Article first published online: 31 OCT 2005
- Received 26 September 2004; final copy received 24 July 2005 Editor: Phil Stephens
- detection probability;
- habitat modelling;
- occupancy models;
- patch occupancy;
- proportion of area occupied;
- species distribution;
- species occurrence;
- study design
- 1The fraction of sampling units in a landscape where a target species is present (occupancy) is an extensively used concept in ecology. Yet in many applications the species will not always be detected in a sampling unit even when present, resulting in biased estimates of occupancy. Given that sampling units are surveyed repeatedly within a relatively short timeframe, a number of similar methods have now been developed to provide unbiased occupancy estimates. However, practical guidance on the efficient design of occupancy studies has been lacking.
- 2In this paper we comment on a number of general issues related to designing occupancy studies, including the need for clear objectives that are explicitly linked to science or management, selection of sampling units, timing of repeat surveys and allocation of survey effort. Advice on the number of repeat surveys per sampling unit is considered in terms of the variance of the occupancy estimator, for three possible study designs.
- 3We recommend that sampling units should be surveyed a minimum of three times when detection probability is high (> 0·5 survey−1), unless a removal design is used.
- 4We found that an optimal removal design will generally be the most efficient, but we suggest it may be less robust to assumption violations than a standard design.
- 5Our results suggest that for a rare species it is more efficient to survey more sampling units less intensively, while for a common species fewer sampling units should be surveyed more intensively.
- 6Synthesis and applications. Reliable inferences can only result from quality data. To make the best use of logistical resources, study objectives must be clearly defined; sampling units must be selected, and repeated surveys timed appropriately; and a sufficient number of repeated surveys must be conducted. Failure to do so may compromise the integrity of the study. The guidance given here on study design issues is particularly applicable to studies of species occurrence and distribution, habitat selection and modelling, metapopulation studies and monitoring programmes.