This project was an extension of a study conducted by Tonachella et al. (2012, p. 297-309) and the Pacific Whale Foundation (PWF), which summarized the long-term humpback whale sightings data. In an effort to elaborate upon the understanding of humpback whale density and distribution, I analyzed the ‘Great Whale Count’ data using ArcGIS 10.4. The Great Whale Count involves citizen science to engage members of the public and promote environmental stewardship, while contributing toward longitudinal humpback whale sighting data in Maui. Five survey sites (Ho’okipa, S-Turns, Lahaina Shores, Pali Lookout, and Pu’u Olai) were analyzed to evaluate whether humpback whales exhibit a concentrated, or habitat specific, distribution along the Maui coastline. Data were organized by single year (2002-2016) and five-year intervals (2002-2006, 2007-2011, and 2012-2016), and point density, hotspot, and high/low clustering tools were used in ArcGIS. To standardize the results from ArcGIS, an ANOVA test was performed based on the mean number of humpback whales per survey site, followed by a time series trend analysis. Based on the point density values, hot and cold spot locations, high/low clustering p-values and critical z-scores, humpback whales were most commonly observed in Pu’u Olai. For the ANOVA and time series trend analysis, based on a p-value of 1.61E-08 for each year and a p-value of 0.0064 for each five-year interval, there was a significant difference in humpback whale distribution among sites, with the highest frequency of sightings recorded at Pu’u Olai. Overall, identifying habitat use and distribution of humpback whales, while a complex and arduous task, can help better predict frequency and occurrence, which will contribute to improved management.
Berg, Rheanne, "Investigating humpback whale (Megaptera novaeangliae) distribution and density in the Maui County Waters using ArcGIS" (2016). Internship Reports (Restricted). 10.
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