Associations of Discrete Call-Type and Behavioral Events of Southern Resident Killer Whales (Orcinus orca) in the Salish Sea Heather Hooper Beam Reach.

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Presentation transcript:

Associations of Discrete Call-Type and Behavioral Events of Southern Resident Killer Whales (Orcinus orca) in the Salish Sea Heather Hooper Beam Reach – Fall beamreach.org/071 Friday Harbor Laboratories – University of Washington Friday Harbor, WA

Behavioral States (as defined by the National Marine Fishery Services)  Traveling  Foraging  Resting  Playing 1. Object play (kelp, floats) 2. Social interactive play (touching, breaching, percussive behaviors) 3. Solitary play  Milling

Behavioral Events  There’s a difference! Breach Tailslap Spyhop Change direction Porpoising Peckslap Rolling Inverted tailslap Inverted surface Lunge Kelping Elfshoe Spyhop & Porpoising

Vocalizations  Clicks  Whistles  Calls Discrete Aberrant Variable While there is no conclusive evidence as to the meaning of specific vocalizations, the social complexity and unity of any one pod or community of killer whales suggests that they must have a communication system that allows them to maintain group cohesion through time and space

Discrete Call Repertoires Discrete calls are most often used during times of group dispersion: 95.2% of all calls during foraging, and 94% of all calls during traveling in the northern residents (Ford 1989). This indicates that discrete calls are used as a way to maintain contact between pod members and/or maintain spatial organization (Ford and Fisher 1983, Ford 1989, Riesch et al. 2006). Ford (1989) proposed that the repertoires of killer whale calls have evolved in order to “increase the reliability and efficiency of intrapod communication.”

Problem Statement  The objective of my study is to identify the vocalizations coming from a specific killer whale and relate that directly to the behavior that particular animal is expressing at the same time. This kind of detailed analysis could be very useful in recognizing the patterns that indicate the function or meaning of discrete calls.  A greater understanding of the communication system of killer whales could give us a better understanding of their customs, health and mental states as individuals or in the whole community. This information would be critical to the protection of the species. Lime Kiln lighthouse

Methods  Southern resident killer whales – J, K, and L pods  observation period spanned from September 6, 2007 to October 20, 2007  study area was the waters surrounding the San Juan Islands, WA, USA.  observational platform was a 42-foot catamaran, the Gato Verde, with a quiet, hybrid, diesel engine

Methods Continued  Hydrophone array  2 solid state recorders  Protractor  Rangefinder  A watch

Call-Type Identification  Calls were identified by visual comparison to Ford’s call catalogue (1987)  Acoustically compared to CallTutor (Val Veirs) Oct 6, 2007 – S42 & S44 calls

Data Collection

Analysis  Calltutor (Val Veirs)  Audacity  Ishmael 1.0 (David Mellenger)  Ford’s Call Catalogue (1987)  Excel (Microsoft) Chi-square test  Null hypothesis = random distribution of discrete calls among all behavioral events

Results  While my original goal was to localize the calls from individual animals, the grouping behavior of the whales observed during my field time and the large amount of error in my measurements made that unfeasible  Localization by Ishmael was able to distinguish calls given by the group of animals where the behavioral events were observed within my acceptable range of error

Results Table 1. The chi-square values for all behavioral events and associated localized calls during the observation period. Significant individual values (>3.841, p=0.05, df=1) are in bold. Total chi-square value=352.2, df=308, p=

Results The chi-square values of behavioral events and associated localized calls occurring greater than ten times during the observation period. Significant individual values (>3.841, critical p=0.05, df=1) are in bold. Total chi-square value=96.2, df=36, p=2.159e-7.

Change Direction  S16 = 27% of calls  Chi-square value =  >>than critical value of S16

Porpoising  S19 ~ S31 when porpoising Calls look alike, short (~0.5s), contour rises up at end 55% of calls S19 Chi-square = S31 Chi-square = 7.236

Peckslaps  Peckslaps – S10, S12, S31 All look and sound very different Compromised 75% of calls S10 Chi-square = S12 Chi-square = S31 Chi-square =

 S31 was absent from breach periods Communication is distinctly different from porpoising and peckslaps Chi-square value =  S37 = breach 2 part call, ~1s, different contour, ending in a steady freq, compromised 15% of calls Chi-square value = Breaches S37

Tailslaps  There were no calls used in the context of tailslaps that were statistically significant This is a statistically random distribution - all individual chi-square values <3.841 critical value

Further Research  Larger sample size  Improve localization techniques  Discrete call variation within each call-type  Underwater behavioral data  Playback studies?

Acknowledgements First of all, I would like to thank Jason Wood my advisor for guiding me through the entire ten weeks. Thank-you to our captain, Mike Kramer for teaching me to sail and guiding us amongst the whales. Shannon Fowler was essential for her guidance and encouragement while aboard the Gato Verde. My peers for their support, advice, humor, and hard work throughout the quarter. There are so many people who helped me in this process, I cannot name them all. To everyone that I came in contact with during this program, your guidance, support and inspiration were invaluable to me. I would also like to thank my parents for their love and support, without which I would never have been able to have gotten this far in my education.