Adrian P. Wydeven | USGS Science

USGS2016

Gray wolf exposure to emerging vector-borne diseases in Wisconsin with comparison to domestic dogs and humans

World-wide concern over emerging vector-borne diseases has increased in recent years for both animal and human health. In the United Sates, concern about vector-borne diseases in canines has focused on Lyme disease, anaplasmosis, ehrlichiosis, and heartworm which infect domestic and wild canids. Of these diseases, Lyme and anaplasmosis are also frequently diagnosed in humans. Gray wolves ( Canis lupus ) recolonized Wisconsin in the 1970s, and we evaluated their temporal and geographic patterns of exposure to these four vector-borne diseases in Wisconsin as the population expanded between 1985 and 2011. A high proportion of the Wisconsin wolves were exposed to the agents that cause Lyme (65.6%) and anaplasma (47.7%), and a smaller proportion to ehrlichiosis (5.7%) and infected with heartworm (9.2%). Wolf exposure to tick borne diseases was consistently higher in older animals. Wolf exposure was markedly higher than domestic dog ( Canis familiaris ) exposure for all 4 disease agents during 2001–2013. We found a cluster of wolf exposure to Borrelia burgdorferi in northwestern Wisconsin, which overlaps human and domestic dog clusters for the same pathogen. In addition, wolf exposure to Lyme disease in Wisconsin has increased, corresponding with the increasing human incidence of Lyme disease in a similar time period. Despite generally high prevalence of exposure none of these diseases appear to have slowed the growth of the Wisconsin wolf population.

PLoS ONE↗

USGS2015

Mortality patterns and detection bias from carcass data: An example from wolf recovery in Wisconsin

We developed models and provide computer code to make carcass recovery data more useful to wildlife managers. With these tools, wildlife managers can understand the spatial, temporal (e.g., across time periods, seasons), and demographic patterns in mortality causes from carcass recovery datasets. From datasets of radio-collared and non-collared carcasses, managers can calculate the detection bias by mortality cause in a non-collared carcass dataset compared to a collared carcass dataset. As a first step, we provide a standard procedure to assign mortality causes to carcasses. We provide an example of these methods for radio-collared wolves ( n  = 208) and non-collared wolves ( n  = 668) found dead in Wisconsin (1979–2012). We analyzed differences in mortality cause relative to season, age and sex classes, wolf harvest zones, and recovery phase (1979–1995: initial recovery, 1996–2002: early growth, 2003–2012: late growth). Seasonally, illegal kills and natural deaths were proportionally higher in winter (Oct–Mar) than summer (Apr–Sep) for collared wolves, whereas vehicle strikes and legal kills were higher in summer than winter. Spatially, more illegally killed collared wolves occurred in eastern wolf harvest zones where wolves reestablished more slowly and in the central forest region where optimal habitat is isolated by agriculture. Natural mortalities of collared wolves (e.g., disease, intraspecific strife, or starvation) were highest in western wolf harvest zones where wolves established earlier and existed at higher densities. Calculating detection bias in the non-collared dataset revealed that more than half of the non-collared carcasses on the landscape are not found. The lowest detection probabilities for non-collared carcasses (0.113–0.176) occurred in winter for natural, illegal, and unknown mortality causes.

Wisconsin↗