Improving dive phase definitions in northern resident killer whales

In contrast with the endangered southern resident killer whales (SRKWs), the northern resident killer whales (NRKWs) have been thriving in their habitats. The main hypotheses proposed to explain the differences in survival of these population are associated with differential reproductive output, body compositions, and feeding rates. Testing some of these hypotheses requires researchers to identify prey captures for these animals. As these events are difficult to directly observe through field operations, researchers equip whales with suction-cup attached biologgers and use kinematic variables during the bottom phase of a dive to predict prey captures. However, universal definitions of the bottom phase have not been established and often appear arbitrarily chosen, leading to potentially over or underestimating foraging events. Using the diving and kinematic data collected from three NRKWs, I show that modifying the bottom phase greatly impacts existing methods used to predict prey capture events. To investigate bottom phase definition variability, I then asked several whale researchers to identify the bottom phase of various dives via an interactive study. Linear mixed-effects model analyses showed that there exists substantial variation in bottom phase definitions across different researchers and across different dive types. I compared several statistical models of the start and end of the bottom phase of a dive, including modifications to existing methods, linear regression models, and functional linear regression models. Compared to the currently used bottom phase definitions, using the model based definitions resulted in significant improvements when predicting prey capture dives. Furthermore, these proposed models offer substantial increases in prediction accuracy of the bottom phase of a dive when comparing these model predictions and the currently used methods to the user-provided bottom phases. Finally, I formulated two methods to determine an adequate sample size for fitting these statistical models. The results of both methods show that an adequate sample size of approximately 50-100 dives can be used to obtain satisfactory model predictions for this data. This work shows that dive phase definitions may impact the results of many existing studies and should be emphasized as an important part of analyzing diving data.Science, Faculty ofStatistics, Department ofGraduat