Are Polar Bear Researchers Blinded by Belief, or Acting Dishonestly?
Suggesting impending climate doom, headlines have been trumpeting polar bears are “barely surviving” and “bears are disappearing” prompted by a press release hyping the paper Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline (hereafter Bromaghin 2014), which based on an ongoing US Geological Survey (USGS) study. Dr. Susan Crockford rightfully criticized the media’s fear mongering and failure to mention increasing bear abundance since 2008 here. She also pointed out that modelers have consistently failed to account for the negative impacts of heavy springtime ice here.
I want to reinforce Crockford’s posts, plus argue the problem is much worse than she suggested. Bromaghin 2014’s purported 25 to 50% population decline is simply not real. The unprecedented decline is a statistical illusion generated by the unrealistic modeling of polar bear survival from 2003 to 2007. The highly unlikely estimates of low survival were made possible only by ignoring the documented effect of cycles of heavy springtime sea ice which forces bears to hunt outside the researchers’ study area. Although several of Bromaghin’s co-authors had previously published about negative impacts of heavy springtime ice, they oddly chose to never incorporate that evidence into the USGS models. The following demonstrates how the statistical illusion of “disappearing polar bears” was generated and I urge you to forward your concerns about USGS fear-mongering via subjective modeling to your congressmen and push them to fully investigate these USGS’ polar bear studies.
Perhaps polar bear researchers are just victims of confirmation bias. Co-authors of Bromaghin 2014 have long tied their authority, fame and fortune to predictions of impending polar bear extinctions due to lost summer sea ice. In a 2008 Dr. Andrew Derocher predicted, “It’s clear from the research that’s been done by myself and colleagues around the world that we’re projecting that, by the middle of this century, two-thirds of the polar bears will be gone from their current populations”. Dr Steve Amstrup, chief scientist for Polar Bear International and the USGS researcher that initiated the Beaufort Sea studies, previously published “Declines in ice habitat were the overriding factors determining all model outcomes. Our modeling suggests that realization of the sea ice future which is currently projected, would mean loss of ≈ 2/3 of the world’s current polar bear population by mid-century.”1 Furthermore the USGS’ political reputation is on the line because their studies led to the listing of polar bears as “threatened” due to decreasing summer ice they attributed to CO2 warming. But why do USGS model estimates differ from Inuit experts and the Nunavut government who have steadfastly claimed it is the time of the most polar bears. And why does the USGS’ models differ from numerous surveys (i.e here and here) that support the Inuit claims?
There are 2 major flaws in USGS models:
1) USGS Polar bear researchers tirelessly point to hypothesized stress due to lost summer sea ice, yet they completely ignore much more critical cycles of heavy springtime ice. As previously documented by Bromaghin’s co-authors, the condition of springtime sea ice determines the abundance and/or accessibility of ringed seal pups. Eighty percent or more of the bears’ annual stored fat is accumulated during the ringed seal pupping season that stretches from late March to the first week of May. At that time female bears emerge from their maternity dens to feast on ringed seal pups, and accordingly USGS mark and recapture studies focus virtually all their efforts during the month of April. Yet not one model has incorporated known changes sea ice during that same period. Is that data purposefully omitted because heavy spring time ice does not support their CO2-driven extinction scenarios?
2) Furthermore heavy springtime ice forces movement outside the study area because it prevents local access to seal pups. Any movement outside the study area prevents subsequent recapture and can erroneously cause models to assume emigrant bears are dead. That false assumption creates lower survival estimates which then dramatically lower population estimates. Misinterpreting a temporary or permanent exodus away from a stressful local environment was the same critical error that led to bogus extinction claims for the Emperor Penguins. Coincidently one modeler, Hal Caswell, created both models falsely suggesting Emperor Penguins and Polar Bears are both on the verge of extinction.
1) Why Spring Ice Conditions Are More Critical than Summer Ice.
South Beaufort Sea bears increase their body weight primarily by binging on ringed seal pups, and the bears’ springtime weight gains are huge. Researchers reported capturing a 17-year-old female, with three cubs-of-the-year, in November 1983 when she weighed just 218 lbs. Her weight would have continued to drop, as it does for all bears, throughout the icy winter. Weights do not increase until seal pups become available in late March and April. But after gorging on seal pups, she was recaptured in July and weighed 903 lbs, a four-fold weight change in just 4 months. 2 (her picture is below). The ability to rapidly gain weight, hyperphagia, evolved as a crucial survival strategy to take advantage of abundant but temporary food sources. Springtime ice conditions govern their access to the fleeting availability of ringed seal pups.
In 2001, Bromaghin 2014 co-author Stirling described the negative impacts of heavy rafted springtime ice. “In the eastern Beaufort Sea, in years during and following heavy ice conditions in spring, we found a marked reduction in production of ringed seal pups and consequently in the natality of polar bears.” Stirling noted it took about 3 years for both seal and bear populations to rebound. Stirling also reported the South Beaufort Sea undergoes ~10-year cycles of such heavy ice, and those stressful cycle had been observed in the 70s, 80s and 90s. 5 The most recent cycle of heavy ice is well documented and occurred precisely when bears increasingly exited the study area from 2003 to 2007.
In 2008, Bromaghin 2014 co-authors Stirling, Richardson, Thiemann, and Derocher published Unusual Predation Attempts of Polar Bears on Ringed Seals in the Southern Beaufort Sea: Possible Significance of Changing Spring Ice Conditions. 10 Those researchers had observed that “unusually rough and rafted sea ice extended for several tens of kilometers offshore in the southeastern Beaufort Sea from about Atkinson Point to the Alaska border during the seals’ breeding season from 2003 through 2006”, precisely when their models calculated low survival and a rapid decline in the polar bear population.
Those researchers reported “heavy ice reduces the availability of low consolidated ridges and refrozen leads with accompanying snowdrifts typically used by ringed seals for birth and haul-out lairs.” And they observed, “Hunting success of polar bears (Ursus maritimus) seeking seals was low despite extensive searching for prey. It is unknown whether seals were less abundant in comparison to other years or less accessible because they maintained breathing holes below rafted ice rather than snowdrifts, or whether some other factor was involved.“ (Forcing bears to claw through rafted ice gives the seals ample time to escape.) Polar bears never defend territories. Instead polar bears are highly mobile. Dependent upon seal pups for most of their annual energy supply, a supply that varies annually, bears simply migrate to regions with greater seal abundance.
After giving birth and completing their annual molt by late June, most ringed seals migrate out to sea to fatten and are no longer available to the bears. After late June the amount of sea ice is no longer important habitat for ringed seals. So any correlations with summer sea ice extent from August to November have a relatively insignificant impact on survival. In fact, more open water benefits seals. In a previous essay, Why Less Summer Ice Increases Polar Bear Populations, I explained why ringed seals avoid thick multi-year ice, and why more open water later in the season benefits the whole food web. Bromaghin 2014’s co-author Stirling previously co-authored a paper reporting ringed seals must feed intensively in the open waters of summer in order to store the fat needed to survive the winter, and that seals suffer when sea ice is slow to break up. 4 He pointed out that in 1992 when breakup of sea ice was delayed by 25 days, the body condition of all ringed seals declined resulting in declining body condition of bears. To supplement their diet, bears will feed on a wide array of alternative items from whale carcasses, walruses to geese eggs. Despite the 2nd lowest extent of Arctic summer ice in 2007, researchers on Wrangel Island reported fatter bears than they had previously documented.6 All the evidence suggests summer ice is far less critical than the condition of springtime ice. So is the erroneous focus on summer ice conditions merely driven by researchers predictions that rising CO2 will cause widespread polar bear extinctions in 30 years?
2) Movement Lowers Survival Estimates which Lowers Population Estimates
Bromaghin 2014 authors acknowledged that the observed movement could bias model results, but simply dismissed the observed transiency of wandering bears writing, “The analyses of movement data suggested that Markovian dependency in the probability of being available for capture between consecutive years remains a potential source of bias. However, we view these results with some caution because of the small sample sizes and prior evidence that bears prefer ice in waters over the narrow continental shelf. Further, there is no reason to suspect behavior leading to non-random movement during the spring capture season changed during the investigation.” But their dismissal is nothing less than dishonest. Bromaghin 2014 authors had indeed observed that heavy springtime ice resulted in reduced hunting success and reduced body condition and would force bears to hunt elsewhere.
Bromaghin 2014 authors were denying their own evidence. A subset of bears had been radio-collared in order to track their movements. Between 2001-2003 when their study area experienced normal springtime ice conditions, researchers estimated high survival probability and high abundance, and only 24% of the radio-collared females had wandered outside their study area making them unavailable for recapture. In contrast during the years of heavy springtime ice between 2004 and 2006 researchers estimated unprecedented low survival, low abundance and observed an increased number of collared females outside the study area doubling to 47% in 2005 and 36% in 2006. 7,9 Yet Bromaghin 2014 argue “there is no reason to suspect behavior leading to non-random movement during the spring capture season changed during the investigation.”
A previous study by Amstrup had mapped the range over which radio-collared bears travelled each year. From his 3 examples illustrated below it is clear that polar bears are not always found in the same place each year. Furthermore in accordance with the changing availability of seal pups due to cycles of heavy springtime ice, he reported polar bears exhibited their lowest fidelity to any given area during the spring pupping season. Finally Amstrup’s map shows bears naturally wander outside the boundaries of the study areas searching for food. Because researchers restricted their search efforts to the east of Barrow Alaska, bears moving in and out of the Chukchi sea area have a far less recapture probabilities. Likewise bears that wander between Alaska and Canada will have different recapture probabilities because different amounts of effort were expended in each country.
Due to movement of bears in and out of the Chukchi Sea region, Amstrup had determined those movements heavily biased previous survival and abundance estimates. 8, 12 Bromaghin 2014 also report that the Chukchi Sea region is more productive than the Beaufort Sea. So it is highly likely that bears migrate between the Beaufort Sea study area and the Chukchi Sea in response to varying periods of localized heavy springtime ice and seal pup availability. So why does Bromaghin 2014 dismiss observed movement bias by arguing “there is no reason to suspect behavior leading to non-random movement during the spring capture season changed during the investigation” and contrary to their own evidence suggest bears would remain in the more productive Chukchi Sea region.
In 2001 Amstrup had previously estimated survival rates of South Beaufort bears as 96.2% and natural survival rates were 99.6% and a population could be more than 2500 bears in 1998. 3 Amstrup reported “polar bears compensate for a low reproductive rate with the potential for long life” (i.e high survival). Because movements of bears into and out of his study area had greatly biased his results he warned, “models that predict rapid increases or decreases in population size would not mirror reality.” Curiouser and curiouser he no longer heeds his own advice. Amstrup and his colleagues suddenly embraced the unprecedented low survival rates of 77%, and a rapid 25 to 50% decline in the population between 2004 and 2008 as seen in their graph of estimated abundance.
In order for their model to generate that unprecedented low survival rate of 77%, (despite no observed change in the trend of body condition for 95% of Beaufort Sea bears) 11 modelers had to dismiss the observed movements outside their study area. Once Bromaghin’s authors had dismissed the significance of springtime movement, their models would interpret a lack of recaptures as an indicator of dead bears which then produced the illusion of a rapidly declining polar bear population.
Below is a table illustrating the simplified effects of historical survival estimates on abundance calculations (assuming no additions from new births and immigration). The numbers listed in the gray columns on the left are the USGS study’s actual number of bears captured annually, and the number of that total capture that were previously marked bears. As the study progressed and newly captured bears are marked, the pool of marked bears increases. If the study area was a closed system, we would expect each year’s total number of captures to consist of an increasingly higher percentage of marked bears once the pool of marked bears was large enough. But each year the number of previously marked bears made up only ~50% of the total captures, suggesting a larger population was more likely than what was currently estimated, and that the length of this study was not yet long enough.
In the simplest models, abundance is determined by dividing the total number of bears captured each year by the percentage of captured marked bears from the pool of previously marked bears. (Read How science Counts Bears for a further discussion of mark and recapture studies) However the size of the pool of marked bears depends upon the bears’ survival probability. To illustrate, for each year I generated 3 different pools according to different historical survival estimates. The resulting change in abundance calculated from those 3 different survival probabilities are highlighted in yellow.
If researchers assumed 100% survival, which is close to Amstrup’s 99.6% in his original study, (but with no additions from birth or immigration) then Bromaghin’s data would estimate a 2010 growing population of 2,255 bears. An estimate that is remarkably similar to Amstrup’s 1998 estimate of ~2500 bears.
If the researchers assumed Amstrup’s 96% survival, a lower survival estimate due to the impact of hunting, then the 2010 abundance would be calculated at 1865 bears. Again remarkably close to Amstrup’s suggested abundance of 1800 for a hunted population.
In the 2006 USGS analyses, 7 the authors interpreted fewer recaptures as an averaged lower survival rate of 92%. A 92% survival rate would produce a stable 2010 population estimate of 1664 bears, which is also 70% higher than Bromaghin’s results.
The only way to generate a tragically declining bear population was to employ much lower survival estimates. And as evidenced by their graph below, that is just what they did for the period of heavy springtime ice with low seal availability and much greater movement out of the study area. When the springtime ice returned to normal so did the bears, and their estimated survival rates likewise returned to the expected high ~95%. The huge error bars in Bromaghin’s survival probabilities (see graph below) during those heavy ice years, illustrates the great uncertainty regards the actual fate of marked bears that were never recaptured.
So we must question why these polar bear researchers ignored their co-author’s earlier warning, “models that predict rapid increases or decreases in population size would not mirror reality.”
Were polar bear researchers blinded by climate change beliefs, or acting dishonestly?
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