Abundance estimates for management of endangered false killer whales in the main Hawaiian Islands

• Published in: Endangered Species Research
• Main Authors: Bradford, AL, Baird, RW, Mahaffy, SD, Gorgone, AM, McSweeney, DJ, Cullins, T, Webster, DL, Zerbini, AN
• Format: Article in Journal/Newspaper
• Language: English
• Published: Inter-Research 2018
• Subjects: Zoology; QL1-991; Botany; QK1-989; Killer Whale
• Online Access: https://doi.org/10.3354/esr00903; https://doaj.org/article/0a3f52f58f4f421bb2b28dcb052fd63a

Effectively using the best available data to meet management mandates for endangered populations is a common conservation challenge. False killer whales Pseudorca crassidens occur as 3 distinct populations in Hawaiian waters, including a resident main Hawaiian Islands (MHI) population that is endangered under the US Endangered Species Act. A longitudinal, photo-identification dataset of 171 distinctive individuals and open mark-recapture methods were used to estimate current MHI false killer whale abundance as needed for management of this population. The data are from dedicated and opportunistic surveys conducted from 2000 to 2015 around the MHI and reflect unquantified spatiotemporal biases imposed by necessary sampling constraints. Accounting for temporal variation and especially social group affiliation was important in modeling capture probability. Sensitivity analyses found that the resulting time series of 16 abundance estimates is robust to some forms of sampling variability and bias. However, because the study area was partially sampled each year, the annual abundance estimates apply only to the portion of the population using the sampled area and may underestimate true population abundance. Nonetheless, the resulting estimates and supporting evidence indicate that the MHI false killer whale population is relatively small; for example, only 167 (SE = 23, 95% CI = 128-218) individuals were estimated to have used the sampled area in 2015. Until data are available to estimate or overcome sampling biases, this estimation framework offers a tool for using data that have been regularly collected each year to produce current abundance estimates that are improvements over existing management inputs.