The harbour porpoise (Phocoena phocoena) is a small ceteacean species and is common in Dutch coastal waters. The Eastern Scheldt, an estuary in the Dutch province of Zeeland, housed a minimum resident population of about 34 porpoises in 2017. This population is monitored and studied by the Rugvin Foundation. The Rugvin Foundation recently installed ‘Studio Bruinvis’ on one of the quays near Zierikzee. This quay is regularly visited by locals or tourists through bicycle and hiking paths. But more importantly, it is a well-known hotspot for harbour porpoise watching. It is thought that the high number of sightings is linked to prey fish that are attracted by a former and deep underwater ammunition depot located at this hotspot. Studio Bruinvis consists of a mono hydrophone attached to a buoy that is wirelessly linked to a listening post on the quay where visitors can listen live to sounds (clicks) produced by porpoises. The listening post is also equipped with recording equipment. These recordings provide a good opportunity for monitoring porpoise activity around the buoy of Studio Bruinvis. This study aims at gaining more insight on porpoise activity by studying the relation between abiotic factors (i.e. time, water temperature, wind speed, wind direction, tidal state and water height) and porpoise activity.
This knowledge can be used for scientific goals, but also to promote porpoise watching. Nowadays many mobile applications (apps) are available to help people spot and identify wildlife which can help to create awareness. Therefore, a second aim of this study is to develop a mobile predictability application for porpoise watching by studying how to develop such an app. This app can help locals or tourists to achieve a higher chance of spotting harbor porpoises at Studio Bruinvis. To achieve these aims, the following research question had to be answered: “To what extent is harbour porpoise (Phocoena phocoena) click activity influenced by water temperature, water height, tidal water flow, wind direction, wind speed, and time of day around a commonly used hotspot in the Eastern Scheldt and how can this information be integrated in a mobile application to predict harbour porpoise activity?”
To achieve the first set aim, data was collected from August 15th, 2017 until October 5th, 2017. Porpoise activity data was obtained from Studio Bruinvis and consisted of 1248 audio 1-hour-files. Distortion and stratified sampling resulted in a total sample size of 657 audio files. Pamguard was used to detect the number of produced clicks for each audio file. Data for abiotic variables were obtained from Rijkswaterstaat. Binary logistic regression was used to assess the relation between harbour porpoise activity and the independent abiotic factors. For the dependent variable, porpoise activity, a baseline was set to 400 clicks/hour. Samples with values below this baseline, suggest low porpoise activity. Samples with values above the baseline, suggest high porpoise activity, thus a high chance of spotting harbour porpoises at Studio Bruinvis.
The results of this research showed that all variables (i.e. time of day, tide, water temperature, water height, wind speed and wind direction) were found to have a significant effect on porpoise activity. Tide was found to be the most important predictor followed by wind direction, time of day, wind speed, water height and lastly water temperature. Chance of high activity seemed to increase with increased wind speed, increased water temperature and increased water height. Furthermore, outgoing-to-low tide and incoming tides as well as winds from 225ᵒ-270ᵒ (west-south-west direction), and time of day between 8:00-16:00hours showed to best predict porpoise click activity at Studio Bruinvis. The equation generated by the regression model was used as the basis for an app to calculate the likelihood of harbour porpoise activity. The model proved to be able to predict activity levels of ≥400 clicks per hour with around 74% certainty. The model was used to form an equation which was then used for the development of the porpoise prediction app.
In order to develop the porpoise prediction app, a literature review about app development was conducted. With the use of Mockflow and Marvelapps, the Studio Bruinvis app was created. This app consists of several screens with information regarding Studio Bruinvis, harbour porpoises and the Rugvin Foundation. But most importantly, the equation retrieved from the model was used to create a predictive porpoise activity calculator. This calculator informs users whether the likelihood of porpoise activity, and therefore chance to observe porpoises, is high or low.
Despite the outcome of this study, there were some points of discussion. As independent variables in the model, only abiotic factors were used. After a literature study, it was found that these factors are thought to be indirectly related to porpoise activity. The literature study suggests that the used factors can influence prey densities and create foraging opportunities for harbour porpoises, increasing porpoise activity. Due to the short study period and some restrictions that occurred (i.e. distortion), the data did not cover all seasonal conditions. Therefore, the results of this research might not be extrapolated to conditions outside the study period. Furthermore, the chosen baseline of 400 clicks was not validated during this study. Meaning if detected clicks/hour are >400, it is not yet certain if porpoise activity is high at Studio Bruinvis.
The results of this research showed that all variables were found to have a significant effect on porpoise activity. The model proved to be able to predict high porpoise activity (activity levels of ≥400 clicks/h) with around 75% certainty. With this data, the Studio Bruinvis app was created. The results and findings of this study can be seen as a first try in getting a better understanding about factors that influence porpoise activity at Studio Bruinvis and a first step in developing a porpoise activity predictability application.