Understanding landscape patterns in mortality risk is crucial for promoting recovery of threatened and endangered species. Humans affect mortality risk in large carnivores such as wolves (Canis lupus), but spatiotemporally varying density dependence can significantly influence the landscape of survival. This potentially occurs when density varies spatially and risk is unevenly distributed. We quantified spatiotemporal sources of variation in survival rates of gray wolves (C. lupus) during a 21-year period of population recovery in the Upper Peninsula of Michigan, USA. We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, thus exploring a shifting mosaic of survival. Extended CPH models and time-dependent covariates revealed influences of seasonality, density dependence and experience, as well as individual-level factors and landscape predictors of risk. We used results to predict the shifting landscape of risk at the beginning, middle, and end of the wolf recovery time series. Survival rates varied spatially and declined over time. Long-term change was density-dependent, with landscape predictors such as agricultural land cover and edge densities contributing negatively to survival. Survival also varied seasonally and depended on individual experience, sex, and resident versus transient status. The shifting landscape of survival suggested that increasing density contributed to greater potential for human conflict and wolf mortality risk. Long-term spatial variation in key population vital rates is largely unquantified in many threatened, endangered, and recovering species. Variation in risk may indicate potential for source-sink population dynamics, especially where individuals preemptively occupy suitable territories, which forces new individuals into riskier habitat types as density increases. We encourage managers to explore relationships between adult survival and localized changes in population density. Density-dependent risk maps can identify increasing conflict areas or potential habitat sinks which may persist due to high recruitment in adjacent habitats.
Bibliographical noteFunding Information:
Michigan DNR, Grant/Award Number: 751B4300037; Pittman-Robertson, Grant/ Award Number: W-147-R; National Science Foundation, Grant/Award Number: 1545611 and 1556676; the DeVlieg Foundation; Michigan Technological University Ecosystem Science Center
Research was made possible by funding from the Michigan DNR, MTU grant # 751B4300037. The project was supported in part by Federal Aid in the Wildlife Restoration Act under Pittman-Robertson project W-147-R. Additional funding was provided by a National Science Foundation grants to JKB (NSF ID#1545611, NSF ID#1556676), the DeVlieg Foundation and the Ecosystem Science Center (School of Forest Resources and Environmental Science at Michigan Technological University, MI, USA). The Michigan Involvement Committee of Safari Club International provided funding for radiocol-lars and other equipment. We thank Erin Largent, Robert Doepker, Steve Carson, Brian Roell, and Chris Webster for assisting with data needs during analysis. Mike Haen, Brad Johnson, Donald Lonsway, Jeff Lukowski, and Kristie Sitar assisted with capturing and radio-collaring wolves. Pilots Neil Harri, Dean Minett, and Gordon Zuehlke collected collared wolf relocation data. Anna Nisi and Emily Fifelski assisted with data processing. Thanks to John Fieberg, Min Wang, and two anonymous reviewers for providing helpful comments on early versions of the manuscript.
© 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
- Upper Great Lakes wolves
- Upper Peninsula
- landscape of risk
- management of endangered species
- population recovery
- proportional hazards
- spatial modeling
- species recolonization
- survival analysis