Estimation of bowhead whale (Balaena mysticetus) population density using spatially explicit capture-recapture (SECR) methods.

Mary Woodcock Kroble
Friday 10 November 2017
Date: 18 June 2018
Time: 2:00 pm - 3:00 pm

Speaker: Gisela Cheoo (University of Lisbon)


Management and conservation of wildlife populations is a major concern. Population density is a key ecological variable when making adequate decisions about them. A variety of methods can be used for estimating density. Capture-recapture/mark-recapture (CR/MR) methods are a popular alternative, but ignoring the spatial component of captures has historically led to problems with resulting inferences on abundance. Spatially explicit capture-recapture (SECR) methods use the spatial information to solve two key problems of classical CR/MR: defining a precise study area where captures occur over and reducing unmodeled heterogeneity in capture probabilities.

Arrays of Directional Autonomous Seafloor Acoustic Recorders (DASARs) recorded bowhead whales’ calls through their migration corridor near the north Alaska coast. The available passive acoustic dataset was collected over 5 sites (with 3-11 sensors per site) and 8 years (2007-2014) via manual and automated analyses. In the former, trained staff classified the whale calls manually by listening to recordings and examining spectrograms, whereas in the latter these multi-year data sets were processed by a multi-stage detection, classification and localization algorithm.

Manual data presents some pitfalls including false positives (in particular “singletons”, i.e., calls detected exclusively in one sensor) and non-independence among sensors (caused by human intervention) for density estimation. Automated data doesn’t suffer the non-independence issue but the false positive rate is approximately 6 times higher. Considering only automated data, we will discuss the contribution of singletons in the likelihood functions to estimate abundance, using the methods developed by Conn et al. (2011) (truncation of singletons and dealing with false positives via mixture models) as a starting point.  This dataset is also amenable to an extended SECR analysis, where bearing and received level information are also used, and this is possible future work.


Conn, P. B., Gorgone, A. M., Jugovich, A. R., Byrd, B. L., & Hansen, L. J. (2011). Accounting for transients when estimating abundance of bottlenose dolphins in Choctawhatchee Bay, Florida. The Journal of Wildlife Management, 75(3), 569-579.