Temporal, Spatial, and Environmental Influences on the Demographics of Grizzly Bears in the Greater Yellowstone Ecosystem

During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded in range. Understanding temporal, environmental, and spatial variables responsible for this change is useful in evaluating what likely influenced grizzly bear demographics in the GYE and where future management efforts might benefit conservation and management. We used recent data from radio-marked bears to estimate reproduction (1983–2002) and survival (1983–2001); these we combined into models to evaluate demographic vigor (lambda [k]). We explored the influence of an array of individual, temporal, and spatial covariates on demographic vigor. We identified an important relationship between k and where a bear resides within the GYE. This potential for a source–sink dynamic in the GYE, coupled with concerns for managing sustainable mortality, reshaped our thinking about how management agencies might approach longterm conservation of the species. Consequently, we assessed the current spatial dynamic of the GYE grizzly bear population. Throughout, we followed the information-theoretic approach. We developed suites of a priori models that included individual, temporal, and spatial covariates that potentially affected reproduction and survival. We selected our best approximating models using Akaike’s information criterion (AIC) adjusted for small sample sizes and overdispersion (AICc or QAICc , respectively). We provide recent estimates for reproductive parameters of grizzly bears based on 108 adult (.3 years old) females observed for 329 bearyears. We documented production of 104 litters with cub counts for 102 litters. Mean age of females producing their first litter was 5.81 years and ranged from 4 to 7 years. Proportion of nulliparous females that produced cubs at age 4–7 years was 9.8, 29.4, 56.4, and 100%, respectively. Mean (6SE) litter size (n1⁄4102) was 2.0 6 0.1. The proportion of litters of 1, 2, and 3 cubs was 0.18, 0.61, and 0.22, respectively. Mean yearling litter size (n 1⁄4 57) was 2.0 6 0.1. The proportion of litters containing 1, 2, 3, and 4 yearlings was 0.26, 0.51, 0.21, and 0.02, respectively. The proportion of radio-marked females accompanied by cubs varied among years from 0.05 to 0.60; the mean was 0.316 6 0.03. Reproductive rate was estimated as 0.318 female cubs/female/year. We evaluated the probability of producing a litter of 0–3 cubs relative to a suite of individual and temporal covariates using multinomial logistic regression. Our best models indicated that reproductive output, measured as cubs per litter, was most strongly influenced by indices of population size and whitebark pine (Pinus albicaulis) cone production. Our data suggest a possible density-dependent response in reproductive output, although perinatal mortality could have accounted for the correlation. We analyzed survival of cubs and yearlings using radiotelemetry of 49 unique female bears observed with 65 litters containing 137 dependent young. We documented 42 deaths: 32 cubs, 5 yearlings, and 5 that could have died as a cub or yearling. Using a nest survival estimator coded in Program MARK, our best model indicated that cub and yearling survival were most affected by residency in the GYE. Survival was highest for cubs and yearlings living outside Yellowstone National Park (YNP) but within the U.S. Fish and Wildlife Service (USFWS) Grizzly Bear Recovery Zone (RZ). Cubs and yearlings living inside YNP had lower survival rates, and those living outside the RZ had the lowest survival rates. Survival rates were negatively related to a population index, suggesting density dependence. Survival improved with higher whitebark pine seed production, greater winter severity, larger litter size, and higher female (mother’s) age. We tested theories of sexually selective infanticide, but results were equivocal. We investigated factors influencing survival of subadult and adult grizzly bears using data from 323 radio-marked bears monitored for 5,989 months. Telemetry records were converted into monthly encounter histories, and survival was estimated using known fate data type in Program 1 E-mail [email protected] Schwartz et al. Demographics of the Yellowstone Grizzly 1 MARK. Bears were grouped into a study sample and conflict (bears specifically trapped because of conflict with humans) sample according to circumstance of capture and monitoring, with data from both contributing to survival estimates. A censored (C) data set included 69 documented mortalities but censored 22 bears with unknown fate. A second, assumed dead (AD), data set considered these 22 bears as mortalities. Most known mortalities (85.5%) were human caused, with 26 and 43 from the study and conflict samples, respectively. Mean annual survival, S _ C F, for study sample female bears using C and AD data sets were S _ C F1⁄40.950 (95%CI1⁄40.898–0.976) and S _ AD F1⁄40.922 (95%CI1⁄40.857–0.995). Process standard deviation (SD) for study sample female bears was estimated at SDC1⁄40.013 and SDAD1⁄40.034. Our best models indicated that study sample bears survived better than conflict sample bears, females survived better than males, survival was lowest during autumn, and survival increased during years with good whitebark pinecone production. Bears with a higher proportion of annual locations outside the RZ exhibited poorer survival than individuals located more frequently inside YNP, the RZ, or both. Indices of winter severity, ungulate biomass, and population size, plus individual covariates, including presence of dependent young, prior conflicts with humans, and age class, were not important predictors of survival in our models. We documented a trend of increased survival through the study that was offset in recent years by lower survival of bears located more frequently outside the RZ. This result suggests that efforts to reduce female mortality initiated in 1983 were successful, and similar measures outside the RZ would improve the prospect for continued growth and expansion of the GYE grizzly bear population. To estimate sustainable mortality of the population, we produced trajectories of the GYE grizzly bear population under a range of survival rates of independent females (.2 years old) using an individual-based, stochastic simulation program and demographic data from radio-marked bears. We incorporated yearly (process) variation in survival rates as estimated from data after removing sampling variation. We summarized trajectories by mean k and by probability of k , 1, both within a 10-year period, and examined sensitivity of results by altering our initial assumptions to reflect uncertainty. Because process variation of female survival was low, k decreased stochastically only slightly from that expected under a completely deterministic model. Uncertainty about mean cub and yearling survival rates was considerable, but because k was relatively insensitive to these parameters, incorporating this uncertainty also lowered resulting trajectories only slightly. Uncertainty about independent female survival had a much larger effect on probability of population decline despite having little effect on expected k. Under our current understanding of the GYE grizzly bear population dynamics, k was independent of male survival rate; variation in male mortality produced only short-term effects on abundance and long-term effects on sex ratio. The appropriate mortality target for independent female bears depends on the risk of a population decline ( i.e., k , 1) that managers and the public are willing to accept. For the chance of a population decline to be 5% under conditions applying during 1983–2002, annual mortality of independent females would have to be 10%. Projections are useful only if viewed over a relatively short time frame because they were based solely on mean 1983–2002 conditions and because small samples make it difficult for managers to know the true mortality rate. To further explore the implications of geographic structure in female survival, we built an array of deterministic models using estimates of reproduction and survival from our best models. We calculated deterministic estimates of k incorporating our residency covariate plus changes in whitebark pinecone production and winter severity. A source–sink dynamic is suggested for the GYE, with k 1 inside YNP and the RZ but k 1 outside the RZ. Such a source–sink dynamic requires new discussions about population management, mortality thresholds, and elimination of anthropogenic foods on the edge of the ecosystem. To enhance future management, we present food and population monitoring guidelines that should be considered in light of our findings. Wildlife Monographs 161: 1–68