Benjamin T. Maletzke | Search USGS

USGS2025

Forecasting dynamics of a recolonizing wolf population under different management strategies

Species recovery can be influenced by a wide variety of factors, such that predicting the spatiotemporal dynamics of recovering species can be exceedingly difficult. These predictions, however, are valuable for decision makers tasked with managing species and determining their legal status. We applied a spatially explicit projection model to estimate population growth and viability of gray wolves ( Canis lupus ) from 2021 to 2070 in the state of Washington, USA, where wolves have been naturally recolonizing since the establishment of the first resident pack in 2008. Using this model, we predicted the effects of 12 scenarios relating to management actions (e.g., lethal removals by the state agency, translocation, recreational harvest) and system uncertainties (e.g., immigration from out of state, disease) on the probability of meeting Washington's wolf recovery goals, the probability of extinction, and other metrics related to population status. Population recovery was defined under Washington's Wolf Conservation and Management Plan as four breeding pairs in each of three recovery regions and three additional breeding pairs anywhere in the state. The baseline and two translocation scenarios indicated a high (> 90%) probability of wolf recovery in Washington by 2070, but scenarios related to harvest mortality (removal of 5% of the population every 6 months), increased lethal removals (removal of 8.53% of the population across the state each year), and cessation of immigration from out of state resulted in probabilities of < 0.20 (0.01, 0.04, and 0.17, respectively) of meeting recovery goals by 2070. Only two scenarios of 12 (increased harvest and lethal removals scenarios) resulted in a geometric mean of population growth ≤ 1, indicating long-term population stability or growth for most scenarios. Our results suggest that wolves will continue to recolonize Washington and that recovery goals are likely to be met so long as harvest and lethal removals are not at unsustainable levels and adjacent populations support immigration into Washington.

Washington↗

USGS2016

A long-term evaluation of biopsy darts and DNA to estimate cougar density

Accurately estimating cougar ( Puma concolor ) density is usually based on long-term research consisting of intensive capture and Global Positioning System collaring efforts and may cost hundreds of thousands of dollars annually. Because wildlife agency budgets rarely accommodate this approach, most infer cougar density from published literature, rely on short-term studies, or use hunter harvest data as a surrogate in their jurisdictions; all of which may limit accuracy and increase risk of management actions. In an effort to develop a more cost-effective long-term strategy, we evaluated a research approach using citizen scientists with trained hounds to tree cougars and collect tissue samples with biopsy darts. We then used the DNA to individually identify cougars and employed spatially explicit capture–recapture models to estimate cougar densities. Overall, 240 tissue samples were collected in northeastern Washington, USA, producing 166 genotypes (including recaptures and excluding dependent kittens) of 133 different cougars (8-25/yr) from 2003 to 2011. Mark–recapture analyses revealed a mean density of 2.2 cougars/100 km 2 (95% CI=1.1-4.3) and stable to decreasing population trends (β=-0.048, 95% CI=-0.106–0.011) over the 9 years of study, with an average annual harvest rate of 14% (range=7-21%). The average annual cost per year for field sampling and genotyping was US$11,265 ($422.24/sample or $610.73/successfully genotyped sample). Our results demonstrated that long-term biopsy sampling using citizen scientists can increase capture success and provide reliable cougar-density information at a reasonable cost.

Washington↗