All Dressed Up and Nowhere to Go

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Spring is on its way. As I twiddled with my phone just now to check conditions in the study area, the temperature was nine degrees warmer in northern Wisconsin than in southern California — the result of an unseasonably warm day in the study area and an unseasonably chilly one here in SoCal. At long last, the ice is melting, and loons will soon be back on their lakes. Meanwhile, as Linda’s photo shows, they gather in droves on open water. Being Linda, she also checked out their bands, yesterday and today, to see how many she could identify. We are all the beneficiaries of her tireless efforts, because her IDs provide a window onto the lives of returning breeders that are, for the moment, baffled in their efforts to reclaim their territories.

Who are these birds, and where are their territories? Are they males or females? Are they, in fact, breeders or young floaters, who lack territories and will spend the year challenging territorial residents for ownership? Are they migrants hundreds of miles from their breeding area or neighbors stopping by until their nearby lake becomes ice-free? We cannot answer all of these questions, but we can answer most of them based on Linda’s meticulous observations.

First of all, the loons in these aggregations are almost all males. Of the 12 birds positively ID’d by Linda, 10 are known males, one is a female, and one is of unknown sex. Linda suspected this herself: she reported numerous territorial yodels, sometimes by multiple males at once, as the birds rafted about in ice-free portions of the lake. Females must be only a few days behind; in fact, as I was writing this, Linda reported seeing a breeding pair near last year’s territory on Nokomis.

Second, loons present on the breeding grounds at the cusp of the seasons are mostly breeders that have come to reoccupy territories, rather than young floaters bent on evicting them. Only one ID’d loon from Linda’s list is a possible floater; all others are known breeders.

Third, loons that aggregate on ice-free water in early spring are a geographical smattering — many from neighboring lakes but a good many from farther north, whose lakes might not be open for a week or more. Linda’s sightings show this clearly, as her list includes breeding males from:

1) the adjacent Nokomis-East Central territory,

2) Indian Lake, which is 6 miles to the NE,

3) Soo Lake, 11 miles to the NE,

4) Silver Lake (Lincoln County), 8 miles S,

5) South Blue Lake, 16 miles to the N,

6) Miller Lake, 18 miles N,

7) Blue Lake-West Territory, 20 miles N,

8) Forest Lake (Vilas County), 40 miles NE,

9) Rock Lake (Vilas County), 50 miles N, and

10) Crab Lake (Vilas County), 50 miles N.

and a lone female from Burrows Lake, 10 miles NW.

What can we learn from these sightings? The preponderance of males confirms that males precede females on migration by at least a few days, and shows that males are the main ones bottlenecking on rivers and open lakes near their ice-locked breeding territories. Returning males push hard to return very close to the date that their lake becomes ice-free; females dawdle by a few days. Why it is so crucial for males to return as close to ice-out as possible is unclear, especially since the paucity of young, non-territorial birds present suggests that breeders are not likely to be challenged for territorial ownership in the first few days after settlement. Perhaps males, because they select the nesting site, return as early as possible to take note of any changes in the lake or shoreline over the winter that might require them to move the nest from the prior year’s site.

We can also discern that these early spring aggregations do not comprise neighbors reacquainting themselves after a winter apart, but individuals from far-flung lakes that do not know each other at all and are likely not to encounter each other again. While we should not be surprised by some tense moments between such unfamiliar individuals — it is, after all, spring and hormone levels are high — we should expect mostly peaceful loafing and feeding. These males simply have nothing to gain from battling unfamiliar loons.

In short, the rafts of loons in Linda’s photo are playing a waiting game. Since territory settlement is a time during which owners must defend their lakes vigorously — even if they do get a brief hiatus after settlement, owing the late return of young challengers — we would expect these males to do next to nothing until their lakes open up. They should feed, rest, and expend as little energy as possible before the onerous task of breeding begins.

 

Lab Results from Jeremy: Females Have Longer Telomeres

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I have always loved working in the field. While others remain indoors, chained to their desks and computers, much of my work requires paddling canoes on beautiful lakes to record behavior of loons. It is a dream job. Recent findings, though, are forcing us back into the laboratory.

Why must we return to the lab? Most of you know already from recent posts that male loons senesce dramatically in their mid teens and that they also become aggressive at that age. But the fact that males decline, whereas females do not, raises vexing questions about underlying physiological causes of male decline. Does male health hit the skids because of the cumulative impact of blood parasites? Does the greater body size of males make it more difficult for them to maintain good health throughout their lives? Is male decline linked in some fashion to conditions faced during the chick phase? As always happens in science, one finding, even a very clear one, raises a legion of related questions.

Fortunately, we can answer many such questions by taking small blood samples from our loons at the time of capture. Jeremy Spool, a soon-to-be-Ph.D. from University of Wisconsin-Madison, supervised the taking of these samples, which can tell us about hormone levels, parasites, and genetic patterns. Jeremy also completed a preliminary wave of analyses and has made an interesting discovery with regards to telomeres.

First some background. Telomeres are “end caps” on chromosomes — composed of many repeated DNA sequences — that protect chromosomes when they are replicated during cell division. In both humans and loons, the sequence of repeated DNA building blocks (nucleotides) that comprise telomeres is the same: TTAGGG. Telomeres grow shorter with age and with illness in humans and many other animals. Human babies have chromosomes capped with about 2,500 repeats of TTAGGG; older humans have only about 800 such repeats. A number of researchers have found that shortening of telomeres is related to stressful conditions faced by non-human animals. For example, one study reported that cormorants and albatrosses hatched late in the breeding season showed greater shortening of telomeres — possibly indicating more rapid aging — than did individuals born early in the breeding season. A good deal of work remains to be done on telomeres to determine if they can predict patterns of aging and body condition, but there are some promising signs that they can do so.

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Jeremy analyzed telomere length in loon blood samples from 2017 to see if: 1) telomere length was correlated with age, and 2) males and females differed in telomere length. He noted a weak tendency for male telomeres to shorten with age. We will have to add more data to see if the pattern holds up. On the other hand, Jeremy also found that females had telomeres significantly longer than those of males (see figure, above). Since we know that female loons live longer than males and do not experience a sudden decline in condition in their mid teens, this pattern is as we might have predicted.

What does the telomere pattern tell us? While it is vaguely comforting to find a physiological correlate to confirm the difference in aging pattern between male and female loons, telomere shortening is still a mystery in animals generally — and most certainly in loons. We can draw no immediate link between short telomeres and any other aspect of physiology, like parasite load, immunological capacity, or even age. But the male/female difference gives us hope that telomeres might predict body condition, disease resistance, and/or life expectancy, within each sex. If so, then measuring of males’ telomeres might permit us to predict if and when they are near death and should begin behaving aggressively — to allow themselves one last desperate reproductive gasp. Moreover, if young loons, like cormorants, pay a price by losing some of their telomeres from the stress of being hatched late in a breeding season, then differences in hatching date might help us solve the enduring mystery of why some male loons cannot survive past their mid teens, while others thrive well into their 20s.

No Progress on Ice-out, But No Need to Panic

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As many of you know, I am a worry-wart. Normally I get so stressed-out about my kids, my teaching, my research, my health — and many other matters that are going well — that I hardly have time to obsess about loons in the study area. But Linda Grenzer’s bleak photo of conditions on her lake today gave me a jolt. Could the late ice-out that we are facing in 2018 delay the season so much that it damages the breeding prospects of our loon population?

One might think that the later the ice comes off of the lakes, the later the loons nest, and the less time parents have to fatten up their chicks and prepare them for their first southward migration. Thus, a late ice-out might well lead to reduced breeding success for the population. Although there are many “if”s in this string of logic (and a preliminary analysis did not bear out the pattern), I felt concern  gnaw at me.

So I did what scientists often do to stave off despair: I looked at the data. First, I looked to see if loons nest later when the ice goes out later, which almost has to

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be true. It is true, but there is a lot of noise in the data. That is, loons are constrained to nest somewhat later in years when the ice goes out later, but the picture is not simple. The reason for the noise becomes clear when you look at the lag time between when loons settle on their territories and when they hatch their

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young. There is a very strong pattern here. When the ice goes out early (left side of graph), loons dawdle and wait weeks before nesting. But when the ice goes out late, as it will this year, pairs get down to business quickly, nesting within a week or so of territory return. So loon pairs are somehow able to catch up in years of late ice-out so that their breeding schedule does not differ greatly from other years. (Notice also that the orange line in the top graph is flatter than the blue line.)

What accounts for this pleasing pattern? We can make a pretty good guess based on findings in other migrant birds. Spring migration is an energetically costly process. In an early year, the ice is gone so quickly that loons settle on their lakes as soon as they return from the wintering grounds. In such cases, their fat levels are very low from migration when they first occupy their territories, and it takes a good deal of foraging before they return to good condition. In a late year, loons cannot settle on their territories right away but must wait on nearby rivers that have open water. There, they are able to forage and restore their bodies to good condition. As a result, loons hit their territories in prime body condition and fully recovered from the migratory flight in years of late ice-out. Thus, they can get down to breeding quickly.

Although I was heartened by the data I saw above, I had a look at the numbers that most directly addressed my concern about late ice-out and population breeding success. There is a no statistical tendency for the population to produce more loon chicks in years of early ice-out, despite the many years of data we have to look for such a pattern. Indeed, some of our best years for loon breeding (2013, for example) have occurred when the ice goes out late. So those many of you shivering in northern Wisconsin and other frigid regions can relax about one thing; the loons are no worse off in years when spring comes late than when it arrives early.

Black Flies: Cause for Celebration and Concern

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Ending a short run of bad luck, we just had our paper accepted that describes impacts of black fly infestations on loon nesting behavior. As I have explained in many previous posts, Simulium annulus wreaks havoc with loons’ reproductive efforts. The biological relationship between the fly and the bird is of substantial scientific interest, and we are pleased to have finally brought our low-level data collection on this relationship to fruition.

On the other hand, our celebration of this achievement has been cut short by the cold weather still gripping northern Wisconsin. Why? Because one of our findings was that unseasonably cool springs often bring extended periods of fly abundance. So we face the prospect that the breeding season of 2018 will illustrate the threats to loon breeding we just described so vividly in our article.

There is also reason for hope. As the above figure shows, early ice-outs resulting from warm spring weather ensure that flies will be only a minor nuisance to loons. Late ice-outs pose a problem, but the results vary from a severe rate of nest abandonment (as in 2014, the worst year ever for fly-caused abandonments) to modest impacts. Let’s all hope that 2018 is one of those years when the correlation between cool spring temperatures and severe fly infestations breaks down.

Why Do Some Interns Fake Their Data?

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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.

Better News

It is easy to get into a funk when you are a field biologist. Our livelihood depends upon maintaining momentum. We must keep our work funded, which entails fighting with colleagues in our sub-discipline for the dwindling funds that remain at the National Science Foundation (or some other source). We must attract bright, motivated students willing to work with us and help us push our research forward. And we must publish our work in good journals, or else the entire process grinds to a halt.

Maybe I have grown fragile lately, but my most recent setback with the terminal investment paper was a substantial blow to my momentum. Thus, it was especially sweet to hear last week that a second paper — this one concerning the negative impacts of black flies on loons — was well-received by The Auk: Ornithological Advances and appears close to acceptance there. (I have mentioned certain elements of the black fly story in earlier blogs.)

Sometimes in science, as in life, a fortunate event rescues you from an unrelated unfortunate one — and gives you confidence to forge ahead. Perhaps this bit of luck with the black fly paper can help me shake off some bad news, surge forward towards a new research grant, and move towards a productive new avenue of investigation (ecological traps).

Felled by the “Russian Judge”

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It is a bit unseemly, I suppose, to pile on Russia now. Having been caught meddling with our election and cheating during past Olympics, their reputation could hardly get worse. Yet the metaphor of the Russian judge — meaning a person who brings a strong bias to a process that is supposed to be marked by disinterested fairness and good judgment – is almost irresistible to me at this juncture. Indeed, the metaphor has been throbbing in my brain these past weeks as I have marveled at the scores awarded to figure skaters and Big Air snowboarders.

Let me explain. I recently completed a revision of our paper on terminal investment by male loons: the most remarkable finding we have made in 25 years of research. (This is the paper showing that males become highly aggressive and territorial at the same time that their health, survival, and territory defense is declining.) Praised by three reviewers at a prestigious journal, our paper was blocked from acceptance by a fourth reviewer who insisted that we complete a complex statistical analysis to check our results. Review of scientific articles is almost always anonymous, as in this case, so we cannot know the reviewer’s identity or the reason for his/her objection. But my study of his/her statistical point convinced me that it was mistaken. Yet, the editor disregarded my carefully-crafted refutation and chose to support the reviewer. Of course, it is immensely frustrating for an author when an editor sides with a stubborn reviewer. This outcome forced us into a difficult decision: 1) kowtow to the reviewer by reworking our statistical analysis needlessly, which would have entailed a lengthy delay in publication and cost us perhaps $2000 to hire a statistical consultant, or 2) pull the plug on the submission that seemed on the brink of acceptance, pending completion of that difficult statistical revision. I hope I made the right call by withdrawing the paper and sending it to a new journal.

Two factors played a role in my decision to withdraw the paper that, perhaps, should not have. First, I have spent many months polishing this paper and am reaching the end of my rope with it. I am certain that it is sound statistically and likely to be impactful in my field, if I can just navigate the stormy seas of reviewer opinion. Second, I must soon turn my attention to acquiring new research funding and must have this paper in print in order to demonstrate to funding agencies that the past funds they have sent to me have been well spent. Thus, I have chosen to send the paper to a solid – but not highly prestigious – journal in my field, hoping to find a fast track to publication.

I am not the first person to make a decision to publish a great paper in a low-impact journal in order to keep the wheels of research turning. Each paper, in my experience, follows its own journey. A pedestrian paper sometimes catches a wave and ends up in a lofty journal, only to be scoffed at and forgotten in short order. And cool papers sometimes fall into low‑impact journals, are discovered by many scientists, and become classics. Let’s hope the terminal investment paper falls into the latter category.

Small Lakes and Old Females Are More Prone to Nest Abandonment

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I have just completed my paper on black flies. The paper presents evidence that black flies cause nest abandonment, which was lacking in the literature before. The evidence is pretty convincing, I believe. (We shall see what my scientific colleagues think when I submit the work for publication in the next week.)

In the course of looking at black fly impacts on nesting, I stumbled into two  interesting findings. These findings were serendipitous, like much of what scientists report. That is, I was keenly focused on one topic — black flies and nest abandonment — when I made a finding related to another topic — other causes of abandonment. In fact, I analyzed statistically a whole set of factors, some seemingly unrelated to black flies, that might have predicted nest abandonment. Among these were age of the male, age of the female, duration of the pair bond between them, exposure to wind (which might have kept the flies at bay), size of breeding lake, and distance from the nest to the nearest flowing water (from which black flies emerge as adults).

I was excited, but also baffled, to discover two new predictors of nest abandonment. First, pairs on large lakes are less prone to nest abandonment than pairs on small lakes. Second, pairs containing an old female are far more likely to abandon a nest owing to black flies than are pairs containing young females.

Now, I like to think that I know everything about loons. When I am visiting a study lake and someone asks an easy one like, “Do loons mate for life?”, I puff myself up, lower my voice an octave, affect a mild British accent, and pontificate on the serially monogamous breeding system of Gavia immer. But I was wholly wrong-footed by these two new findings. I had been so laser-focused on black flies as the prime movers in nest abandonment that I had included age and lake size in the analysis almost as an afterthought. I had not even considered what it would mean to learn that age and lake size were significant predictors.

The statistical significance of lake size as a predictor of abandonment forced me to confront a complex variable. If numbers of black flies are correlated with nest abandonment (as they are), then it requires no great conceptual leap to infer that black fly harassment is causing loons to abandon their nests. But the fact that lake size predicts abandonment opens up a much broader range of explanations, because lake size is correlated with degree of human recreation, pH, wind exposure, wave action, available food, and numerous other factors. Having picked through the possibilities, an energetic explanation seems most likely to explain the lake size pattern. That is, large lakes provide more food than small lakes, so loon pairs on large lakes should be in better health and condition than those on small lakes. Well-fed, healthy adults with strong immune systems should be better able to cope with the blood loss and exposure to blood-borne pathogens (like Leucocytozoon protozoans, which cause a malaria-like disease in birds) than under-nourished individuals with weaker immune systems.

What about the higher abandonment rate of pairs that contain an old female? Here again, energetics might be the key. Old females senesce — they experience much lower survival and slightly higher vulnerability to eviction than young females. So it stands to reason that old females are in poorer body condition and are more likely to abandon nests when attacked viciously by black flies. Reproductive decline among old females is widespread in animals, and the tendency of old female loons to abandon nests more readily seems consistent with that pattern.

But what about males? As I have emphasized in recent blog posts, males senesce even more dramatically than females do. How is it possible that old males can continue to incubate eggs when being bitten mercilessly by black flies when old females cannot? Terminal investment appears to be the answer. Terminal investment — efforts to increase breeding output as death approaches — occurs only among male loons, even though both sexes senesce. As the months have passed, we have learned that male loons not only become hyper-aggressive when they reach old age (15 years) in an apparent attempt to hold their territory for another year or two of breeding, they also seem to show a more subtle willingness to try harder to hatch eggs and rear young to fledging. The new finding showing that old males do not abandon nests as readily as old females when beset by black flies is thus part of a growing pattern.

My tentative explanations for the impacts of lake size and sex on nest abandonment are not the end of the story, of course. Rather, they raise more vexing questions. Why on earth would a loon settle to breed on a small lake, when small lakes doom loons to poorer body condition, a higher rate of abandonment, and the likelihood of losing one or both chicks in the event they can hatch the eggs? And even if the higher rate abandonment of nests by old females fits a growing pattern, why do males and females differ so much in their life-history strategy? We do not know….and this is why I love my work!

Proving the Obvious

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A lot of science is scut work. While I do ponder my findings, develop new hypotheses, and publish papers that might (slightly) change the way that others view the natural world, these activities are, in fact, only the most glamorous ones in the scientific profession. I spend far more time worrying that I am mistaken about a result. You see, scientists are nit-pickers who know from personal experience the difficulty of proving something is true. Scientists are skeptical of their own findings as well as those of their colleagues. We are always on the lookout for false assumptions, biased data samples, misleading correlations, and experimental results that are artifacts (false outcomes) of our methods. Thus, we spend a good deal of time poking and prodding our data, turning it this way and that, and making certain it is bullet-proof, before we try to publish or present it to colleagues. Scientists run many tedious and seemingly repetitive statistical tests aimed at testing a single hypothesis and ruling out alternative explanations for patterns we find in our data. If a flaw in our reasoning, an untested assumption, or a problem in experimental design weakens or invalidates our findings, we want to discover it ourselves in the solitude of our office — not have a listener at a talk or a reviewer of a grant proposal do so.

Scientists have a much higher threshold for accepting statements as fact than does the public at large. Indeed, flawed and misleading conclusions — which would bring harsh criticism to a scientist uttering them — are rampant in public discourse. The biased sample problem leads to many misleading conclusions. Following a political debate, TV commentators always tell us who won, based upon a sample of viewers. Unless one is very careful to control the political makeup of an audience, however, the outcome of such a poll is certain to be biased. Naturally, Fox News and CNN have audiences that differ greatly in their political leanings; in addition, people who watch debates on television or in person represent a biased sample of voters, not the population at large. Finally, viewers are more likely to see the candidate they favor as the winner of a debate, so favoritism towards one candidate will make that candidate more likely to be seen as the winner, even if their performance was worse that their opponent’s. That is, if 65% of all voters favor Ms. Sims over Mr. Peach ahead of the debate, and 55% of all voters say afterwards that Ms. Sims won the debate, Mr. Peach almost certainly performed better, because he beat his poll numbers.

I face the biased sample problem constantly in my analysis of loon behavior. For example, we have observed that loons shifting from a first to a second breeding territory tend to move a very short distance, often settling to breed on a new lake right next to their old one. It is tempting to surmise that loons that move between territories cover only a short distance in order to take advantage of their knowledge of the local area and ease their transition to the new breeding space. This sounds plausible but ignores the fact that shifters are not a random cross-section of the population. Instead, these loons are almost all old individuals with low fighting ability that have been evicted from first territories. Moreover, the new territories they shift into are not average breeding territories but new, untested ones with limited nesting habitat that seldom yield offspring. So old, worn out loons do not seem to be carefully choosing to settle in a new breeding space that they know well; rather, they are desperately setting up a new territory near their original one — and in a place that no other loon wishes to use — because it is not worthwhile trying to compete for a proven territory anywhere else.

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At the moment, I have turned a critical eye towards black flies and nest abandonment. I have “known” for decades that black flies cause high rates of nest abandonment in certain years, as they did in 2017. But it is one thing to know something is true, and quite another to convince other scientists of what you know. So I have gone back to field records from 1994 to 2017 and tallied occasions when field observers reported severe infestations of black flies on loons or around their nests during the early nesting period. Then I looked at the correlation between reports of severe black flies and rates of nest abandonment across years. The result, as shown in the figure above, is unsurprising. In years when black flies were reported to be abundant, nest abandonments were very common.  (By the way, that data point in the upper right corner is 2014.)

While I was certainly not on pins and needles during this latest analysis of black flies, it is a crucial piece of the puzzle. Lacking any direct data showing that black flies caused loons to abandon nests, my best evidence to support this conclusion was that cool springs lead to a high rate of nest abandonment. The strong correlation pictured above now implies a direct causal connection between flies and abandonments.

I breathed a sigh of relief at this finding. I am not sure how I would have responded if I had found that years of severe black flies were NOT correlated with rates of nest abandonment. Yet I cannot rest. I can imagine a scientific reviewer complaining that the correlation might have resulted from observer bias. For example, once an observer starts to notice that black fly population is high early in the year and possibly related to nest abandonment, he or she might be more likely to report severe black fly infestations on subsequent days. Such behavior by field observers might explain the correlation I found, at least in part.

In short, I am still uneasy about my analysis of black fly impacts on loon nesting. I am looking for additional statistical analyses that could help convince a skeptical audience of the link between flies and abandonments. That is what life is like for a scientist.

 

The Mystery Female and Her Tough Call

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In Linda‘s last round of photos from Bear Lake, you can see the numbers clearly. At the narrow end of the metal band, a fuzzy, curling “6” followed by a clear, swooping “2”. Those two digits — either one of them, actually — identify the Mystery Female of Bear Lake as the chick we banded on July 18, 2005 on North Nokomis Lake. This photo culminates several days during which Linda patiently stalked the female with her camera lens until the bird finally pulled her metal band out of water in an orientation that permitted Linda to photograph the two digits we needed to see from the nine-digit number code.

The story of the Mystery Female concerns more than just solid detective work and crisp photography; it relates to the crucial decisions that a loon must make while attempting to settle on the best possible breeding lake and rear as many offspring as possible. The Mystery Female, Orange over Mint-burgundy — OMb for short — faced such a decision. OMb returned to the study area as a 4-year-old in 2009 and began hunting for a place to breed. She settled on Upper Kaubashine (at the end of the long arrow below) in 2012 and lost clutches of eggs to predators there in both 2012 and 2013. OMb then

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faced a stark choice — remain on a poor territory attempting to breed or abandon Upper K and try to move to a more promising locale.

Shifting from a poor territory to a good one might seem like an easy call to make, but female loons must cope with a shortage of potential mates owing to early senescence and frequent fatal fighting in males. Every year we see many loner females, some of which live on good breeding lakes, waiting for a mate. So it is an open question whether a female should desert a mate and breeding territory — even a poor one — to try and move to a better location. You see, in trying to secure a new territory, a female must temporarily leave her current one, risking its loss to another female on the prowl.

OMb decided to abandon Upper Kaubashine in 2013, establishing herself as the new breeding female on Bear Lake (shorter red arrow), whose female had died. This appeared to be a wise move; Bear had yielded chicks in 9 of the previous 13 seasons, while Upper K had not fledged a chick in 35 years.

Chance plays a big role breeding success of loons, as in all animals. In a curious twist of fortune, Upper Kaubashine stunned lake residents by hatching two chicks from a terribly exposed nest site. Since Bear Lake only produced a single chick this year, OMb’s choice of Bear over Upper K looks like a poor one, as of now. But chick production in these two lakes will probably return to form. If so, and if OMb can hold onto her new territory, her decision to leave a perennial failure for a proven chick-producer will have been a good one.