Hierarchical multi-scale occupancy estimation for monitoring wildlife populations

• Published in: The Journal of wildlife management Vol. 76; no. 1; pp. 154 - 162
• Main Authors: Pavlacky Jr, David C., Blakesley, Jennifer A., WHITE, GARY C., Hanni, David J., Lukacs, Paul M.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01-01-2012; The Wildlife Society; Blackwell Publishing Ltd
• Subjects: Animal populations; Applied ecology; availability probability; availability probability, closure assumption, detection probability, hierarchical model, monitoring, multi‐scale, occupancy estimation, point count, Pollock's robust design, removal design; Birds; Certhia americana; Chondestes grammacus; closure assumption; detection probability; Estimates; Habitat conservation; Habitats; hierarchical model; monitoring; multi-scale; Multiscale modeling; Musical intervals; National forests; occupancy estimation; point count; Pollock's robust design; Population Ecology; removal design; Species; Survey design; Variables; Wildlife conservation; Wildlife habitats; Wildlife management; USA, South Dakota, Black Hills
• ISSN: 0022-541X; 1937-2817
• DOI: 10.1002/jwmg.245

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern.