Assessment of Occurrence of Indo-Pacific Bottlenose Dolphins (Tursiops aduncus) in Response to Pile Driving Noise in the Fremantle Inner Harbour (Western Australia)

The research investigated the use of land-based cameras versus field personnel for marine mammal detection. The study demonstrated that the use of cameras was cost-effective for dolphin monitoring. Secondly, the research investigated associations of bottlenose dolphin (Tursiops aduncus) occurrence in the Fremantle Inner Harbour with noise from vibratory and/or impact pile driving. The number of dolphins detected was significantly reduced by the presence of pile driving, regardless if it was vibratory or impact pile driving

An Assessment of the Effectiveness of High Definition Cameras as Remote Monitoring Tools for Dolphin Ecology Studies.

Research involving marine mammals often requires costly field programs. This paper assessed whether the benefits of using cameras outweighs the implications of having personnel performing marine mammal detection in the field. The efficacy of video and still cameras to detect Indo-Pacific bottlenose dolphins (Tursiops aduncus) in the Fremantle Harbour (Western Australia) was evaluated, with consideration on how environmental conditions affect detectability. The cameras were set on a tower in the Fremantle Port channel and videos were perused at 1.75 times the normal speed. Images from the cameras were used to estimate position of dolphins at the water’s surface. Dolphin detections ranged from 5.6 m to 463.3 m for the video camera, and from 10.8 m to 347.8 m for the still camera. Detection range showed to be satisfactory when compared to distances at which dolphins would be detected by field observers. The relative effect of environmental conditions on detectability was considered by fitting a Generalised Estimation Equations (GEEs) model with Beaufort, level of glare and their interactions as predictors and a temporal auto-correlation structure. The best fit model indicated level of glare had an effect, with more intense periods of glare corresponding to lower occurrences of observed dolphins. However this effect was not large (-0.264) and the parameter estimate was associated with a large standard error (0.113).The limited field of view was the main restraint in that cameras can be only applied to detections of animals observed rather than counts of individuals. However, the use of cameras was effective for long term monitoring of occurrence of dolphins, outweighing the costs and reducing the health and safety risks to field personal. This study showed that cameras could be effectively implemented onshore for research such as studying changes in habitat use in response to development and construction activities

Equipment.

<p>Camera box mounted at the top of the camera tower (A); camera tower lowered for equipmemt servicing (B); camera box showing central window of the video camera and left window used for the still camera (the right window was for an additional camera not used in this study) (C).</p

Dolphin detection range versus bearing.

<p>Number of dolphin group detections as a function of bearing and range from the cameras (bearing to the group is based on the position of the first detected dolphin surfacing within the group).</p

Location of the study site within the Fremantle Inner Harbour, Western Australia.

<p>The circle indicates the study area and the white box indicates the place where cameras were located. Source: ESRI ArcGlobe 10.0.</p

Field of view.

<p>The area covered by the still (grey and white) and video (white) cameras and the location of the camera tower (black triangle), and dolphin (black cross).</p

Generalised Estimating Equations model to identify significant predictive variables in detecting transit events.

<p>Significance code: 0.01 = ‘*’.</p><p>Generalised Estimating Equations model to identify significant predictive variables in detecting transit events.</p

Effort for each environmental variable.

<p>Effort (hours) of data collected under each environmental variable (Beaufort Scale, Light Level, Percentage of Droplet Coverage, Haze Level, Rain Presence, Cloud Cover and Glare).</p

Position of first detected dolphin within a group in the Fremantle Inner Harbour as a function of range and bearing using both cameras.

<p>White dots correspond to plots obtained from the still camera and red dots correspond to plots obtained from the video camera.</p

An example image taken with the still camera.

<p>Ranges and bearings from the camera (top); zoomed in image to show target (below).</p