Abstract: |
The extinction of polar bears by the end of the 21st century has been
predicted and calls have been made to list them as a threatened species under
the U.S. Endangered Species Act. The decision on whether or not to list rests
upon forecasts of what will happen to the bears over the 21st Century.
Scientific research on forecasting, conducted since the 1930s, has led to an
extensive set of principles—evidence-based procedures—that describe which
methods are appropriate under given conditions. The principles of forecasting
have been published and are easily available. We assessed polar bear
population forecasts in light of these scientific principles. Much research
has been published on forecasting polar bear populations. Using an Internet
search, we located roughly 1,000 such papers. None of them made reference to
the scientific literature on forecasting. We examined references in the nine
unpublished government reports that were prepared “…to Support U.S. Fish and
Wildlife Service Polar Bear Listing Decision.” The papers did not include
references to works on scientific forecasting methodology. Of the nine papers
written to support the listing, we judged two to be the most relevant to the
decision: Amstrup, Marcot and Douglas et al. (2007), which we refer to as AMD,
and Hunter et al. (2007), which we refer to as H6 to represent the six
authors. AMD’s forecasts were the product of a complex causal chain. For the
first link in the chain, AMD assumed that General Circulation Models (GCMs)
are valid. However, the GCM models are not valid as a forecasting method and
are not reliable for forecasting at a regional level as being considered by
AMD and H6, thus breaking the chain. Nevertheless, we audited their
conditional forecasts of what would happen to the polar bear population
assuming that the extent of summer sea ice will decrease substantially in the
coming decades. AMD could not be rated against 26 relevant principles because
the paper did not contain enough information. In all, AMD violated 73 of the
90 forecasting principles we were able to rate. They used two un-validated
methods and relied on only one polar bear expert to specify variables,
relationships, and inputs into their models. The expert then adjusted the
models until the outputs conformed to his expectations. In effect, the
forecasts were the opinions of a single expert unaided by forecasting
principles. Based on research to date, approaches based on unaided expert
opinion are inappropriate to forecasting in situations with high complexity
and much uncertainty. Our audit of the second most relevant paper, H6, found
that it was also based on faulty forecasting methodology. For example, it
extrapolated nearly 100 years into the future on the basis of only five years
of data – and data for these years were of doubtful validity. In summary,
experts’ predictions, unaided by evidence-based forecasting procedures, should
play no role in this decision. Without scientific forecasts of a substantial
decline of the polar bear population and of net benefits from feasible
policies arising from listing polar bears, a decision to list polar bears as
threatened or endangered would be irresponsible. |