Passive acoustic monitoring on activity patterns of Indo-Pacific humpback dolphins (Sousa chinensis) in an estuary
Date Issued
2016
Date
2016
Author(s)
Lee, Chia-Yun
Abstract
Odontocetes use echolocation clicks to navigate and forage. Primarily active in estuarine and shallow coastal waters of less than 20 m, Indo-Pacific humpback dolphins (Sousa chinensis) rely on echolocation for investigating their environment and for feeding purposes. It has also been shown that the spatial distribution of some humpback dolphin populations varies between dry and wet seasons. During the dry season, they prefer the inner estuary, whereas during the wet season and after heavy rainfall, they move into the outer estuary. Following previous research, this study used passive acoustic monitoring (PAM) to investigate the occurrence and behaviors of humpback dolphins in response to different quantities of river runoff during the dry and wet seasons. The monitoring area was divided into four sections based on their distance to the estuary. To detect the echolocation clicks of the cetaceans, three acoustic data loggers were deployed in the Xin Huwei River estuary, Yunlin County, Taiwan, from July 2009 to November 2015. This thesis presents the results of two separate studies. In the first study, I monitored and calculated the occurrence rate of humpback dolphins with different levels of runoff to generate predictive models using the Julian day and runoff index. In the second study, I compared the acoustic-behavioral changes of humpback dolphins in dry and wet seasons with various levels of runoff. The first study adopted the resampling approach and spline function was used to build predictive models of humpback dolphin occurrence and response to runoff. The dolphin-detecting rate showed distinct patterns between the inner and outer estuary. During the dry season (from December to April), the echolocation clicks of humpback dolphins were mostly detected in the inner estuary, whereas clicks peaked in the outer estuary during the wet season (from April to September). The dolphin detecting rate was shown to positively correlate with the lower levels of runoff but negatively correlate with the higher levels of runoff (>5mm). While the explanatory power of the rainfall model was lower for the outer estuary, the big data set obtained through PAM can be used to effectively predict the occurrence pattern of humpback dolphins by building a value model. The resultant predictive model offers the first reliable tool for predicting the occurring pattern of humpback dolphins based on acoustic data. In the second study, I analyzed the composition of humpback dolphin echolocation clicks and their detecting angles and ranges at different levels of runoff. The results showed that the short-range sonar (having been associated in previous studies with feeding and foraging behaviors) occurred primarily at lower levels of runoff in the inner estuary. By contrast, the long-range sonar occurred mainly at higher levels of runoff. Moreover, humpback dolphins exhibited more complex movements and relatively wider ranges at lower levels of runoff but showed no significant changes in movement type and range with increasing levels of runoff in the outer estuary. The variation in acoustic behaviors and spatial distribution indicates that the activities and behavioral patterns of humpback dolphins in the estuarine habitat are probably driven by river runoff which could impact prey abundance.
Subjects
Sousa chinensis
passive acoustic monitoring
echolocation clicks
predictive modeling
spatiotemporal variation
acoustic behavior
habitat utilization
Type
thesis
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