Population ecology and the management of whale watching operations on a data‐deficient dolphin population

Abstract

Abstract Whale watching is a popular commercial activity, producing socio‐ecological benefits but also potential long‐term effects on the targeted cetacean population. This industry is currently developing in data‐deficient contexts in a largely unregulated fashion. Management schemes should adopt precaution and be informed by the relevant literature, but would be more effective if the assessment of the target population vulnerability, biological impacts, and management implications was drawn from site‐specific data. This paper focuses on a reef‐associated, data‐deficient population of spinner dolphins in the Egyptian Red Sea. In Satayah Reef, new information on population size and dynamic parameters were documented using visual observation and photo‐identification‐based capture–recapture methods (Cormack–Jolly–Seber time‐since‐marking model). Dolphins occurred on 98% of the survey days. Average school size was 66 individuals (±42.1 SE), with most groups including calves. The population was equally divided into recurrent and transient individuals. An “emigration + mortality” model best described residence at the site. Five recurrent males (5% of the Satayah population) provided connectivity between this and the geographically close population of Samadai Reef. Average annual survival probability was 0.83 (±0.06 SE) in the year following first capture and 0.99 (±0.06 SE) for recurrent individuals. Mean yearly population sizes ranged 143–207 individuals. The study had the power to detect a 30% decline in the population, but not the rate of change in abundance estimated from the data (r = 0.018 ± 0.04), which would have required a 3‐ to 5‐times longer study. Synthesis and application: These findings advance the assessment of the Satayah population's intrinsic vulnerability and have three major management applications: (a) the delineation of management units; (b) the identification of key indicators for future impact monitoring and assessment; and (c) realistic estimates of the statistical power for trend detection. Based on our results, we recommend supporting future research, devising site‐specific time–area closure plans, and integrating them in a regional scheme. Approaches employed in this case study can inform the management of whale watching industries targeting other data‐deficient populations.

Keywords

• CJS models
• inequality model
• lagged identification rate
• Red Sea
• spinner dolphin
• tourism management