As my family and friends will tell you, I am judgmental. When an event happens that could be attributed to mindless error, I am inclined to view it, instead, as deliberate selfishness or irresponsibility. I derive my hypercritical worldview in part from my profession. As a behavioral ecologist, I presume that much of the behavior we see in animals (including humans) has evolved in order to promote their evolutionary fitness. Put another way, I assume that a good deal of animal behavior is selfish — evolved because it allowed the ancestors of living individuals to survive better and leave more offspring than others of their species.

The presumption of selfishness is a helpful touchstone in my field. It provides a starting point when one is interpreting a new and unexpected behavior pattern. For example, if I notice a new soft call emitted by female loons during courtship, I am apt to hypothesize that this call might help mates synchronize their breeding activities so that each will be prepared to do its share of the incubation duties, once eggs are laid. (Such synchronization, which involves rising prolactin levels in the blood, has proved crucial to successful breeding in many species of birds.) So the presumption of selfishness canĀ  be a useful prism through which to understand animal behavior.

A week ago, the folks at REGI learned of an event that pushed even my cynical viewpoint to the limit. Following a report from a lake resident, they found an injured loon on Metonga Lake, which is just south of Crandon, Wisconsin. After Linda and Kevin Grenzer captured the loon (pictured in Linda ‘s photo above) and the REGI team examined and x-rayed it, they learned that it had been shot at close range with a shotgun and had lead shot throughout its body. Despite efforts to save the unfortunate shooting victim, it died in their care. The story might have ended there, except that the loon was banded.

Since Metonga is outside of our study area — some 20 miles east of our southeasternmost lake — we do not know the lake at all. Sleuthing by Linda and me revealed that this oval 2000-acre waterbody supported two breeding pairs in 2018. According to the loon ranger, both pairs hatched chicks this year, although only one of the pairs fledged their two hatchlings. Most important, neither pair contained a banded individual. Thus, the shooting victim was not a member of either resident pair.

Some of the circumstances surrounding the tragic shooting make sense. As many of you know, breeding loon pairs become restless in September and October, often leaving their territorial lakes. Moreover, large, clear lakes like Metonga are favorite spots for wandering adults to visit, as they forage intensively and lay down fat stores to fuel their southward migration. So it is not at all surprising that a breeding adult from a neighboring lake — as we presume the victim was — would be found on Metonga. Finally, virtually all of the loons that we band that show up that far from our study area are females, because females are the more dispersive sex. (On average, females settle 24 miles from their natal lake, while males settle 7 miles from their birthplace.)

The identity of the shooting victim allows us to speculate about its tragic end. When I looked up the band colors and partially-obscured USGS band number that Linda provided, I learned that we had banded this female nine years ago as a chick on Bear Lake in Oneida County. We have not seen her since. The father and mother of this female were among the most approachable loons in the study area. (The male still holds the territory there, as he has since 2001 or earlier.) As Chapman student Mina Ibrahim showed a year ago, tameness (the minimum distance that a resting loon will permit a canoe to approach before diving) is similar between parents and offspring. So it is almost certain that the dead female was a tame individual, like both of her parents.

If our simple inference is correct, then this incident has exposed one hazard of extreme tameness in loons. While the vast majority of humans who approach loons closely are merely curious and would never dream of harming them, an occasional human might do so. It is easy to reconstruct the chain of events that led to the shooting. In the opening week of duck season, a hunter got an easy shot at a duck-like diving bird and took full advantage.

This analysis might well be correct, but it has one hitch. Loons are so well-known across the heart of their breeding range that they can scarcely be confused with ducks. None of the species of ducks that a hunter in northern Wisconsin would be looking to bag is patterned much like a loon. Furthermore, all duck species in the area are far smaller than loons and are prone to fly, not dive, when approached by humans. And since we know that the hunter blasted this loon from very close range, it is even more difficult to believe that the incident arose from a misidentification.

Call me cynical, but I believe that the hunter who killed this loon was not foolhardy, as generous and forgiving people might believe, but rather purposely wicked. Of course, this conclusion further erodes my opinion of other humans. What kind of person deliberately shoots a loon?

Let me apologize right now for the negative tone of many recent blog posts. I hope my recent negativity does not obscure what has always been a stimulating, productive and (I hope) useful field research project. We have discovered a trove of exciting, odd, and often unexpected behavioral patterns in a species whose breeding system was thought to be monotonously monogamous. We have also described important ecological patterns — such as natal site imprinting and ecological traps — which might help us conserve loons. Along the way, I have met and worked with scores of wonderful people, including over 70 field interns. Most of these folks used the experience of loon research to help mold their career plans, aiming eventually for grad school in wildlife or ecology, or for jobs in conservation at the local, state, or federal level. Every year I get a charge out of meeting a new crop of young people eager to contribute to the project, learn field techniques and lay the groundwork for their careers.

However, not all interns work out. This past field season was my most difficult ever. In 2017 I failed to motivate one of my field assistants to complete data collection at all of her assigned lakes each day, and her complaints and poor performance hurt team morale. But last year was doubly trying, because a second field assistant falsified her data. In truth, this was the third instance of falsification that I had observed during the study.

One can dismiss data falsification by one or two field workers as flukes. When we found that Laura was not going to some of the lakes on her circuit in 1996 and was faking her arrival and departure times at some others, we were horrified. Having never encountered this problem before, though, we eventually decided that something was wrong with Laura for her to have betrayed our trust. Margaret, my head field assistant that year, announced, “I always thought she was a spoiled brat”, and I quickly agreed. When Frank, another team leader, caught Chelsea faking her data in 2005, I allowed myself to reach a similar conclusion. The problem was Chelsea, not us. I assured Frank that I would be more careful in screening potential field assistants in the future.

The third instance of faking data, which occurred last year, forced me to confront an unpleasant possibility: something about the way we select student assistants or go about data collection makes our project prone to data falsification. One aspect of this problem is obvious. While we are able to cover more ground and collect more data per observer than most other studies by having each observer work independently, solitary data collection opens the door to cheating. A single weak person in a weak moment who decides to fake data has no check on their behavior, whereas neither of two observers working in a pair would likely risk discovery by proposing data falsification to their teammate. And solitary work is hard — day after day of rising at 4am, facing all sorts of diverse weather conditions (especially strong wind), and maintaining the focus to collect data of high quality.

Fortunately, the design of our data collection also makes it easy to detect falsification. You see, we systematically rotate observer visits to lakes to limit the impact of observer bias. Observer bias — the innocent and natural tendency of each individual observer to detect and record certain events in their environment and not others — occurs in all observational studies. We limit such bias by making sure that all observers visit all study lakes and that no two consecutive visits to a given lake are by the same observer. This protocol gives us a means to detect faking of data, because any occasion when one visitor’s observations at a lake fail to match those of the previous visitor — like one observer reporting a failed nest and a different observer a week later reporting chicks — is immediately flagged for further scrutiny. Rotation of lake visits should also discourage cheating, because field assistants know that the lakes that they are assigned to visit on a certain day will be visited by a teammate in a week’s time. In effect, we are all constantly checking on each other’s observations. We are like a community of paranoiacs!

Our unintentional safeguard against data falsification is lucky, but it only makes the repeated occurrence of cheating more puzzling. Our field assistants are young people, eager to gain experience and to show their field skills to scientists who might write them strong reference letters. Their application to work with me must include names of three references and considerable information about their academic background and training. Why would such people risk fallout from a severe violation of academic integrity by falsifying data? We can fully never solve this puzzle, I suppose. Needless to say, exit interviews with data cheats are not feasible. In the three instances of falsification: 1) Laura simply denied faking data, despite having been caught red-handed doing so, 2) Chelsea admitted falsifying data and commented, “I cannot believe that I took that chance”, and 3) our faker from last year also admitted her wrongdoing, but insisted that she faked data only on the single occasion when she was caught.

A few bad apples will not ruin the study. We are built to detect such misbehavior, which allows us to toss out anything suspect and preserve the integrity of the data. But it seems worthwhile reflecting on how things have turned sour for a few field assistants so that we can prevent it down the road. I plan to work to prevent cheating by two means. First and foremost — and after consulting with a sociologist and a past field intern about an earlier draft of this blog — I will work harder in the future to give interns a stake in the work. That is, I will try harder to inform them of the scientific questions we are asking and give them the opportunity to ask questions themselves about loon behavior and ecology on side projects, like the one done by Gabby a few years ago. Second, I think it is important to talk about data falsification explicitly and let folks know: 1) that this is very harmful to the project and 2) that they are welcome to take an extra day off here and there, if they feel themselves getting tired of the daily grind of rising early, paddling many miles a day, and typing their data into the computer.

I am a long way from fully understanding why some students falsify data. I probably never will. Perhaps a few adjustments can reduce the frequency of this problem and help keep me focused on all of the positives that have come from our work.