A Data Focused Approach: Too Chimplistic?

Schweini grooming Shwali
Schweini grooming Shwali.
By Kaitlin Wellens
September 18, 2015
Discontented grumbles from nearby researchers and field assistants pull my attention away from my target.  As I turn to see the catalyst of this reaction, I rest my eyes on an approaching female chimpanzee, her skeletal figure menacingly framed by winged hair on her shoulders.  Being physically likened to a Disney villain does not do her infanticidal reputation any favors.  This female may represent an extreme case of unanimous dislike, but nonetheless, when I think of any of the chimps I study, a rich history of behaviors, individual traits, and experiences immediately comes to mind.  Despite each day’s work culminating in a set of behavioral codes and subject IDs, it is the anecdotal stories and chimp personalities that dominate our memories and dinner conversations.  Of course, as scientists, objectivity is an important way to keep biases out of our data, so we all strive to separate our opinions from our data collection. And while I value this as a way to conduct sound science, as I wrap up my 8-month field season and prepare to analyze my data, I can’t help but to ask if we lose valuable information by paring these dynamic individuals and their complex histories into data points.  
Controlling for various factors and the rise of interest in personality traits (sometimes termed behavioral syndromes) are important steps in encompassing some of the context in which behaviors occur, but one might argue that they only scratch the surface. An example of this that I have spent a lot of time considering during my field season surrounds one fairly skittish female, Schweini.  Mother of one, Schweini is commonly described by various researchers as one of the more protective mothers.  However, this protective nature is not always easily pulled from the commonly recorded and analyzed maternal behaviors, such as grooming and nursing rates. Rather, it is in rarely recorded instances or the subtleties of her behavior that her protectiveness shows.  For instance, while her son is playing, she often glances in his direction and if things get particularly rowdy, she is known to reach out and grab his leg, pulling him back.  Getting enough data points of this behavior or being able to turn second-long glances into quantifiable data is a challenging task, but it represents an important message: just because our data does not tell us something is there, does not mean it isn’t. 
How could one ever quantify something like the tension in a group you can feel rising before a display or act of aggression occurs? What about the subtle flinches of an individual with a history of being attacked as they walk past others?  Can we quantify something so subjective, and should we? Should we quiet the naturalist in us and allow the data to speak the full story? Or is there a way to have these subtleties inform our more objective science? While we may not currently have clear answers to these questions and others like them, it is nonetheless important to consider what information gets lost amongst our data points, and do our best to work towards telling the complete story.