A History Rooted in Litigation—The history surrounding two successive efforts by the U.S. Fish & Wildlife Service (USFWS) to remove ESA protections for Greater Yellowstone Ecosystem (GYE) grizzly bears in 2007 and 2017 has had a major configuring effect on research practices and products by the Interagency Grizzly Bear Study Team (IGBST) during the past 20+ years (Section 2).

Scientific Failings of Delisting Rules—Both efforts by the USFWS to remove ESA protections for GYE grizzly were stopped by federal district and appellate court judges who determined that the USFWS misused or selectively misrepresented scientific information in its deliberations. Judges during the first, 2007-2010, round of litigation found that the agency had been negligent in accounting for the effects of whitebark pine (Pinus albicaulis) seed consumption on demography of GYE grizzly bears and had misrepresented the magnitude of whitebark pine mortality during the previous ten years. Judges during the second, 2017-2020, round of litigation similarly found that the USFWS had misrepresented research regarding genetic health of the GYE population and not provided an adequate mechanism for managing grizzly bear mortality (Section 2).

A “Straw Man” Research Agenda—This history of legal losses triggered the deep involvement of USFWS personnel in design and execution of IGBST research, with the explicit goal of rebutting judicial rulings. This politicized research agenda featured a highly rarefied “strawman” contest that focused almost exclusively on a battle between the statistical effects of whitebark pine losses and putatively increased bears densities on demography and behavior of GYE grizzly bears. This constrained and politicized design was flawed from the onset by neglecting numerous additional factors that prospectively affected grizzly bear demography and by relying on dubious or flawed measures of both bear density and whitebark pine abundance (Section 2).

Misrepresented Abundance of Whitebark Pine—IGBST researchers mismeasured or misrepresented the temporal availability of whitebark pine seeds to GYE bears in all their key analyses primarily by conflating abundance of edible seeds, as such, with numbers of live whitebark pine trees during a period of widespread mortality caused by a mountain pine beetle (Dendroctonus ponderosae) outbreak. Mortality of mature trees was offset during the early part of this outbreak by a near doubling of cone production on surviving trees, resulting in essentially no temporal correlation between annual cone crops and numbers of live trees. Because IGBST researchers erroneously relied on the latter as a proxy for the former in most analyses, their representations of pine seed availability had little or no relationship to reality (Sections 3.2).

Mismapped Whitebark Pine—The IGBST also substantially underestimated the spatial extent of cone-producing whitebark pine by relying on a map derived from remote sensing that was contaminated by substantial errors of omission. Most locations where field crews verified that grizzly bears had consumed whitebark pine seeds were located outside the IGBST’s mapped distribution – a level of error that delegitimized statements by IGBST researchers claiming that a substantial portion of GYE bears historically lacked access to mature cone-producing whitebark pine. These substantial errors of omission also called into question the results of IGBST analyses purporting to address the behavioral responses of bears to losses of whitebark pine during and after the mountain pine beetle outbreak (Section 3.3).

Neglect of Manifold Environmental Change—IGBST researchers also routinely failed to account for numerous other factors that likely affected demography of GYE grizzly bears, including increased consumption of army cutworm moths (Euxoa auxilliaris) by grizzly bears in the Absaroka Mountains; functional extirpation of cutthroat trout (Oncorhynchus clarkii) as a bear food in southcentral portions of the ecosystem; declines in numbers of elk (Cervus canadensis) ecosystem wide; declines in numbers of bison (Bison bison) in central portions of Yellowstone National Park; synchronous exponential increases in numbers of bison in northern portions of the park; an epic drought that lasted from 2000 to 2009; and systematic increases in summer temperatures (Sections 3.4-3.5).

Disregard for Changes in Key Natural Foods—A substantial amount of research offers prima facie evidence that all these environmental changes likely affected demography, behavior, and distribution of GYE grizzly bears during 1990-present. Loss of cutthroat trout eliminated an important bear food in one of the most secure portions of the ecosystem. Increased exploitation of army cutworm moths attracted bears to some of the most remote and secure parts of the Absaroka Mountains. Meat from elk and bison was and continues to be one of the most important sources of energy and nutrients for GYE bears, but with regionally varied importance. Drought has continued to have numerous but annually varied ecosystem-wide effects on availability of vegetal foods, including excavated roots and grazed foliage. Importantly, IGBST researchers did not explicitly account for any of these prospectively weighty environmental effects in most of their reported analyses (Sections 3.6-3.8).

Neglected Compensatory Consumption of Meat—There is indisputable evidence that GYE grizzly bears compensated for losses of whitebark pine, cutthroat trout, and native ungulates by not only more heavily consuming army cutworm moths, but also by more intensively exploiting anthropogenic meat – notably livestock on public land grazing allotments and remains of kills made by elk hunters. As with prospective effects attributable to losses of native foods, IGBST researchers failed to account for demographic effects that likely arose from bears exploiting hazardous anthropogenic foods – as well as hazards to cubs arising from exploitation of meat from any source by their mothers (Section 3.9).

Neglected Hazards of Consuming Anthropogenic Meat—The consequences of losing native foods located in secure environments and related compensatory increases in exploitation of anthropogenic meat were manifest in a quadrupling of known or likely grizzly bear mortalities. This sharp increase in bear deaths closely followed terminal losses of whitebark pine trees to a mountain pine beetles outbreak and was typified by a near doubling of the proportion of deaths caused by conflicts with elk hunters or retaliations for depredation on livestock. Mortalities simultaneously doubled as a fraction of total estimated population size, suggesting a commensurate increase in grizzly bear mortality rates. Even more consequential, the fraction of female versus male bears killed because of depredation conflicts also more than doubled (Sections 3.10-3.12).

Obfuscating Artifacts of Changing Methods—At the same time that these dramatic environmental changes and related effects on diets, behavior, and demography of grizzly bears were unfolding, methods for estimating size and trend of the GYE bear population remained in flux and beset by bias. Presumed instantaneous increases in population size amounting to sometimes 100s of bears were largely and at times even entirely an artifact of changing methods (Section 4.1).

Biased Methods for Estimating Population Size & Trend—Even with presumed improvements in models, the metric that drove most methods and results during 2007-2023 remained counts of unduplicated females with cubs-of-the-year (COY). These counts and derivative estimates of population size and trend could be explained almost entirely by increasing efforts on the part of researchers to detect unduplicated females with COY during aerial surveys, as well as by increases in sightability of bears arising from dietary shifts that led bears to more heavily exploit non-forest habitats – notably increased consumption of meat from ungulates and cutworm moths on alpine aggregation sites (Section 4.2).

Risky Management of Mortality—Prima facie problems with estimating population size and trend in the GYE continue to be aggravated by methods used to derive a proxy estimate of annual mortality that GYE managers rely on for annual deliberations. This proxy measure is little more than the ratio of estimated total dead and live bears (numerator and denominator, respectively) estimated for the GYE each year. Even though managers and researchers both assume that this proxy accurately represents true mortality rates there, is fact, no known relationship between the two. Even more problematic, the proxy measure of annual mortality rates used for management purposes is reckoned against benchmarks that were derived from simulation models employing estimates of mortality rates based on known fates of radio-marked bears – again with no well-established or otherwise known relationship between the proxy measure and a fundamentally different set of methods and data (Section 4.3).

Biased Estimates of Bear Mortality—Problems arising from the absence of any direct or verifiable relationship between methods used to calculate proxies for real-time management of bear mortality and methods used by researchers to estimate population mortality benchmarks have been aggravated by employment of biased methods for field estimates of total annual mortality. These methods developed by the IGBST for estimating numbers of unreported and undetected in addition to known and probably probable deaths almost certainly underestimate the true numbers dying (Section 4.4).

Implausible Estimates of Death Rates—Other evidence suggests that death rates calculated by managers from field data and by the IGBST from radio-marked bears have been increasingly underestimated over time. Field rates have been biased low simply because total numbers of bears dying during a given year have been increasingly underestimated. Other evidence calls into question estimates of mortality rates calculated by the IGBST from radio-marked bears, including a doubling in numbers of bears known to die relative to total estimated population size (a proxy for mortality rate), synchronous with dietary shifts arising from losses of whitebark pine seeds. The annual churn in numbers of bears captured and subsequently monitored similarly nearly doubled during this same period, suggesting that captured bears were increasingly dying at a rate faster than they could be captured (Section 4.5).

Doubtful Estimates of Population Growth Rate—The IGBST used a trend metric that was biased by search effort and bear sightabilities (i.e., unduplicated females with COY) together with implausibly low estimates of bear death rates to derive estimates of population size and trajectory for GYE grizzly bears. The resulting dubious estimates were likely inflated, with this bias compounded by failure of IGBST researchers to account for reduced reproductive output of older female bears (i.e., senescence). This concatenation of problems calls into question all estimates of population size and trend produced by the IGBST during the past 20 years (Section 4.6).

A Dubious Measure of Bear Density—Returning to the contest between effects of conspecific density and whitebark pine losses on GYE grizzly bears, it turns out that the metric used by the IGBST for spatial and temporal representations of bears densities was likely biased by increasing efforts to capture and radio-track bears, which further called into question analyses compromised by mismeasurements of whitebark pine seed availability and inattention to other environmental effects. When adjusted for an expanding distribution, population-averaged bear densities did not appreciably change during 1990-2022 and were in fact lowest at a time that conflicted with when the IGBST claimed densities were highest (Section 4.7).

Naïve Conceptions of Carrying Capacity & Density Dependence—Mismeasurement of key environmental and demographic variables by the IGBST were compounded by the invocation of simplistic and misleading conceptions of carrying capacity and density-dependent effects. IGSBT researchers assumed a static capacity of the environment to support bears, comparable to a sardine can, and effects of bears on each other comparable to those of randomly moving ping-pong balls, with all effects equal. But carrying capacity self-evidently fluctuates annually and over time. The spatial organization of bears is also dynamic, as evident in changing diets and habitat selection. Different diets entail different hazards, especially from encounters of subordinate bears with adult males, sufficient to explain all changes in survival of cub and yearling bears independent of any variation in bear densities. When these behavioral changes are considered in concert with changing habitats and foods, the static reckonings of carrying capacity and “density-dependent effects” by the IGBST are basically meaningless (Sections 4.7-4.8).

Disregard for Long-Term Population Viability—The IGBST and USFWS basically ignored the best available science regarding requisites of long-term population viability, defensible time frames for judging risk, and relationships between genetically effective and total population size, resulting in unsubstantiated claims that a census population of 500 grizzly bears would ensure long-term genetic health. The current scientific consensus as well as plausible models of long-term population viability suggest that populations of grizzly bears should number 3,000-4,000 animals to ensure genetic health and adaptive evolutionary potential over periods of 40 bear generations – roughly 400 years (Section 5.1).

Implausible Estimates of Genetically Effective Population Size (Ne)—The IGBST produced estimates of Ne (numbers of bears making genetic contributions to subsequent generations) that were an implausibly high fraction of estimated total numbers of bears – in the range of 40-60% – as well as inconsistent with direct approximations from demographic data. Moreover, trends in the ratio of effective to census population size increased substantially over time. These problematic patterns call into question estimates of Ne made by the IGBST, especially given the highly complex and contingent nature of models used to estimate this elusive quantity (Section 5.2).

Overlooked Logistics of Trucking Bears—The USFWS, IGBST, and state wildlife management agencies are making plans to translocate 2-4 bears per decade from the Northern Continental Divide (NCDE) to Greater Yellowstone populations to alleviate concerns about long-term genetic health. These plans are unrealistic and otherwise dubious for several reasons including evidence suggesting that 10-20 successfully translocated bears may be needed each decade (i.e., bear generation) to mitigate loss of alleles and genetic heterozygosity, and that this number may increase to 75-150 if rates of successful breeding by transplanted bears are comparable to observations from other ecosystems (i.e., 13%). Nor do these plans consider the possibility of outbreeding depression resulting from the loss of locally adaptive genes with the long-distance transport of bears from dissimilar environments of the NCDE (Section 5.3).

Poorly Framed Models & Hypotheses—The multiple failings of IGBST research described in Sections 3-5 of this report evince an approach to science that neglects numerous consequential environmental drivers of grizzly bear behavior and demography, selectively attends to a handful of factors chosen largely for political reasons, mismeasures or misrepresents the few factors that are attended to, and deploys methods that produce dubious results at odds with straight-forward evidence. In more arcane terms, these failings are manifest in under-specified hypotheses and models and prejudiced interpretations of research results constructed with the apparent a priori intent of dismissing effects attributable to environmental change while ascribing all demographic changes to effects of conspecific densities (Section 6.1).

Social, Psychological, and Institutional Distortions—The politicized history spawned by failed attempts to remove ESA protections predictably interacted with social-psychological dynamics to amplify corruptive effects on scientific practices of IGBST researchers. Key elements of these dynamics included in-group loyalties, financial dependencies, and perverse institutional incentives created by the USFWS, state wildlife management agencies, and the U.S. Geological Survey (USGS) – parent organization of the IGBST (Section 6.2).

Corruptive Financial and Political Influences—Research agendas of IGBST scientists were fundamentally shaped by personal and monetary influences exerted by the USFWS and exacerbated by financial dependencies created by a parent agency operating under a business model of research production. IGBST researchers existed, moreover, in a politically over-heated authoritative environment dominated by regional elected officials and appointed agency leaders who used a biased selection of unreliable information to promote removal of ESA protections for GYE grizzly bears (Section 6.2).

Perpetuation of a Data Monopoly—The production of reliable science requires transparency and opportunities for multiple independent researchers to test and potentially replicate research results. This especially holds true for topics that spawn controversy, as does grizzly bear management. There is only one GYE grizzly bear population as well as a single data set collected at public expense by government employees. Under such circumstances, there is no justification for IGBST researchers aggressively perpetuating a data monopoly, as they have done for the past 30+ years. This monopoly has debarred any opportunity for correctives offered by ideals of scientific practice and ample scope to produce the flawed science described in this report (Section 6.3)

Invocation of Fallible Peer Review—Finally, IGSBT researchers claim to correct all the problematic practices and products described here through the presumed cleansing process of peer review. The IGBST and USFWS have routinely justified this presumption with inflated claims for the efficacies of peer review, and with disregard for evidence showing that peer review is fallible and no substitute for corrections arising from the often-contentious dialectic of multiple independent scientists investigating topics of shared interest in an open arena (Section 6.4).