Integrated Population Modeling of Black Bears in Minnesota: Implications for Monitoring and Management

Fieberg, John; Shertzer, Kyle W.; Conn, Paul B.; Noyce, Karen V.; Garshelis, David L.

doi:10.1371/journal.pone.0012114

Cited by 87 publications

(59 citation statements)

References 29 publications

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“…For example, harvest rates of black bears may vary related to food availability (Fieberg et al 2010). Additionally, changes in harvest methods may affect estimates such as hunter success and effort derived from harvest data.…”

Section: Hunter-harvest Statisticsmentioning

confidence: 99%

The late-denning activities of the American black bear in Utah

Miller¹,

Smith²,

Auger

et al. 2017

Ursus

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EXECUTIVE SUMMARYDuring the early part of the 20 th Century, predators were subjected to high levels of take because of real or perceived threats to human health or safety and conflicts with agriculture/livestock. Many of our native predators have reestablished and are now very common in Oregon. The Oregon Department of Fish and Wildlife (ODFW or department) recognizes the high value of our native wildlife, including predators, and manages for a balance between sustainable populations and acceptable levels of conflicts, which is challenging at times. Public attitude toward black bears (and other wildlife species) has changed during the past several decades, and increasing black bear populations have increased the complexity of certain management issues. State wildlife agencies have been, "…caught in the middle and try to maintain a balance with their management strategies," (Pelton 2000:390) as they shift from goals related to population recovery to goals related to regulation of abundance. The mission of the department is to protect and enhance Oregon's fish and wildlife populations and their habitats for use and enjoyment by present and future generations. This plan is the strategy of the department to meet its mission for management of black bears in Oregon.The 2012 Oregon Black Bear Management Plan updates the 1993-1998 Oregon Black Bear Management Plan. During the planning and revision process, stakeholder groups were invited and provided input for the plan. A public comment period also was utilized during the revision process to inform the public of the intent of the plan, how black bears are managed in Oregon, and for the department to consider public input on bear management.The plan includes information on biology and ecology of bears, with a focus on Oregon; historical and current management approaches; and biological data collection. The plan also establishes a set of four objectives designed to balance ecological, social, and economic considerations for informed decision making when managing populations of black bears. These objectives are not considered mutually exclusive; therefore, some level of trade-off is to be expected under certain situations. As with the previous bear management plans, the department continues to develop efficient and effective bear management strategies to meet objectives within its personnel and fiscal resource limitations.Objective 1 is to maintain healthy and optimum bear populations while providing optimum recreational opportunities, and considering objectives related to other wildlife species and the level of human-bear conflicts. Management of individual species should include considerations related to an ecosystem-based management approach. Management of other wildlife species, such as deer and elk, may affect management of bears, including those related to population abundance. Decisions related to management of harvested species include providing recreational opportunities for hunters. Therefore, objectives should be balanced and trade-offs should be acknowledged. ...

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Section: Hunter-harvest Statisticsmentioning

confidence: 99%

The late-denning activities of the American black bear in Utah

Miller¹,

Smith²,

Auger

et al. 2017

Ursus

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“…Black bears are a major source of mortality of deer neonates through the summer months [42]–[43]. According to the most accurate point estimates, black bear numbers ranged between approximately 15,000 and 26,000 during 1991 to 2008 [44]–[45].…”

Section: Methodsmentioning

confidence: 99%

“…We accounted for the repeated measures design by using a non-parametric bootstrap, re-sampling individuals with replacement. Thus, we treated the observations as though they arose from a two-stage cluster design, with the first stage representing individual animals on the study site (sampled independently) and the second stage representing locations of these animals [44], [56]. This approach has the advantage of simplicity, but more importantly, the regression parameters reflect population-level response patterns that are of primary interest to managers [57].…”

Section: Methodsmentioning

confidence: 99%

A Long-Term Assessment of the Variability in Winter Use of Dense Conifer Cover by Female White-Tailed Deer

2013

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BackgoundLong-term studies allow capture of a wide breadth of environmental variability and a broader context within which to maximize our understanding of relationships to specific aspects of wildlife behavior. The goal of our study was to improve our understanding of the biological value of dense conifer cover to deer on winter range relative to snow depth and ambient temperature.Methodology/Principal FindingsWe examined variation among deer in their use of dense conifer cover during a 12-year study period as potentially influenced by winter severity and cover availability. Female deer were fitted with a mixture of very high frequency (VHF, n = 267) and Global Positioning System (GPS, n = 24) collars for monitoring use of specific cover types at the population and individual levels, respectively. We developed habitat composites for four study sites. We fit multinomial response models to VHF (daytime) data to describe population-level use patterns as a function of snow depth, ambient temperature, and cover availability. To develop alternative hypotheses regarding expected spatio-temporal patterns in the use of dense conifer cover, we considered two sets of competing sub-hypotheses. The first set addressed whether or not dense conifer cover was limiting on the four study sites. The second set considered four alternative sub-hypotheses regarding the potential influence of snow depth and ambient temperature on space use patterns. Deer use of dense conifer cover increased the most with increasing snow depth and most abruptly on the two sites where it was most available, suggestive of an energy conservation strategy. Deer use of dense cover decreased the most with decreasing temperatures on the sites where it was most available. At all four sites deer made greater daytime use (55 to >80% probability of use) of open vegetation types at the lowest daily minimum temperatures indicating the importance of thermal benefits afforded from increased exposure to solar radiation. Date-time plots of GPS data (24 hr) allowed us to explore individual diurnal and seasonal patterns of habitat use relative to changes in snow depth. There was significant among-animal variability in their propensity to be found in three density classes of conifer cover and other open types, but little difference between diurnal and nocturnal patterns of habitat use.Conclusions/SignificanceConsistent with our findings reported elsewhere that snow depth has a greater impact on deer survival than ambient temperature, herein our population-level results highlight the importance of dense conifer cover as snow shelter rather than thermal cover. Collectively, our findings suggest that maximizing availability of dense conifer cover in an energetically beneficial arrangement with quality feeding sites should be a prominent component of habitat management for deer.

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“…The AD model builder (Fournier ) has been used to fit many previous statistical population models (Broms et al , Fieberg et al ), but R, which has become widely used for statistical analysis, also has the capabilities to fit these models (Berg et al ). We found the maximum likelihood of the joint likelihoods using the nlminb function in the statistical software R (R Core Team ) and confidence intervals of the estimates using the profile likelihood method (Venzon and Moolgavkar ).…”

Section: Methodsmentioning

confidence: 99%

Evaluation of ptarmigan management with a population reconstruction model

2018

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The rock ptarmigan (Lagopus muta) is a popular game bird in Iceland, but the population has endured a long‐term decline. A hunting ban was enforced in 2003, but 2 years later hunting was allowed again with added restrictions. The aim of this study was to investigate the effects of a change in hunting regulations on the ptarmigan population in northeast Iceland, 1998–2013, using a population reconstruction model and to estimate the abundance of juveniles and adults, natural survival, and harvest mortality. The estimated abundance at the beginning of the hunting season ranged from 42,000 (95% CI = 36,000–49,000) birds in 2002 to 158,000 (95% CI = 105,000–250,000) in 1998. The natural survival of adult rock ptarmigan was density dependent and ranged from 36% to 65% (95% CI = 30–75%). Survival for juveniles was constant and was estimated to be 19% (95% CI = 18–20%). We included a change point in the model to account for a change in the harvest mortality that could have occurred with the changes in the hunting regulations. The results indicated that the change in hunting regulations did reduce ptarmigan harvest mortality and changed the harvest strategies of hunters. Inclusion of a change point in models is useful for managers to test if a change in regulations had an effect on the target population. © 2018 The Wildlife Society.

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Integrated Population Modeling of Black Bears in Minnesota: Implications for Monitoring and Management

Cited by 87 publications

References 29 publications

The late-denning activities of the American black bear in Utah

The late-denning activities of the American black bear in Utah

A Long-Term Assessment of the Variability in Winter Use of Dense Conifer Cover by Female White-Tailed Deer

Evaluation of ptarmigan management with a population reconstruction model

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