Abstract
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.
Highlights
Accurate estimates of key vital rates are crucial for promoting restoration and recovery of threatened and endangered species, especially where humans contribute to changes in population demographics
Humans affect mortality risk in large carnivores such as wolves (Canis lupus), but spatiotemporally varying density dependence can significantly influence the landscape of survival
We focused on mapping risk across time using Cox Proportional Hazards (CPH) models with time-dependent covariates, exploring a shifting mosaic of survival
Summary
Accurate estimates of key vital rates are crucial for promoting restoration and recovery of threatened and endangered species, especially where humans contribute to changes in population demographics. Hypothesized influences included individual-level factors (age, sex, body condition at capture, capture type, vaccination status, and pack membership status) and continuous spatial covariates (distance from pack territory, landscape characteristics, spatiotemporally varying density, and movement information). Testing for such effects contributes to (1) evaluation of the factors that increase mortality risk, (2) understanding of how management may influence the population, and (3) knowledge about habitat fitness and potential sink habitats used by wolves. Applicable habitat modeling tools that can be extended to any population that is tracked across time
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