Survival and Recruitment of Gray Wolf Pups Before and after Harvest

Knowledge about recruitment in a population can be critical when making conservation decisions, particularly for harvested species. Harvest can affect population demography in complex ways and this may be particularly true for species whose successful reproduction is linked with complex social dynamics. We used noninvasive genetic sampling and a natural experiment to estimate recruitment in gray wolves (Canis lupus) before and after harvest in the northern Rocky Mountains, Idaho USA (2008-2013). We hypothesized that recruitment would decline after hunting and trapping began and that the decline in recruitment would be attributable to the harvest of pups and not subtler mechanisms associated with group dynamics and reduced reproductive success. We collected fecal samples from wolves in 10 packs for 6 consecutive years, extracted DNA, and genotyped 154 individual pups across 18 microsatellite loci. Population harvest rates averaged 23.8% (SD = 9.2). Our hypothesis that recruitment would decline was supported; survival from 3 – 15 months of age decreased from 0.60 (95% CI: 0.48-0.72) without harvest to 0.38 (95% CI: 0.28-0.48) with harvest and recruitment declined from 3.2 (95% CI: 2.1-4.3) to 1.6 (95% CI: 1.1-2.1) pups per pack after harvest was initiated. We attributed just 18-38% of pup mortality directly to harvest and suggest that there are indirect effects of harvest on recruitment that may be associated with changes in group size and structure. Models that do not include both direct and indirect effects of harvest on recruitment may underestimate the potential impact of harvest on population growth in social species

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Demographic and Component Allee Effects in Southern Lake Superior Gray Wolves.

Recovering populations of carnivores suffering Allee effects risk extinction because positive population growth requires a minimum number of cooperating individuals. Conservationists seldom consider these issues in planning for carnivore recovery because of data limitations, but ignoring Allee effects could lead to overly optimistic predictions for growth and underestimates of extinction risk. We used Bayesian splines to document a demographic Allee effect in the time series of gray wolf (Canis lupus) population counts (1980-2011) in the southern Lake Superior region (SLS, Wisconsin and the upper peninsula of Michigan, USA) in each of four measures of population growth. We estimated that the population crossed the Allee threshold at roughly 20 wolves in four to five packs. Maximum per-capita population growth occurred in the mid-1990s when there were approximately 135 wolves in the SLS population. To infer mechanisms behind the demographic Allee effect, we evaluated a potential component Allee effect using an individual-based spatially explicit model for gray wolves in the SLS region. Our simulations varied the perception neighborhoods for mate-finding and the mean dispersal distances of wolves. Simulation of wolves with long-distance dispersals and reduced perception neighborhoods were most likely to go extinct or experience Allee effects. These phenomena likely restricted population growth in early years of SLS wolf population recovery

Simulations for an individual-based spatially explicit model for southern Lake Superior wolves.

<p>We varied perception neighborhoods where simulated wolves could search for mates 1, 2, 3, 4 and 5 territories away (concentric circles) and the log mean parameter in the lognormal distribution used to calculate individual dispersal distance with average dispersal distances of 25, 50, and 100 kilometers (sectors) on a simulated landscape.</p

Number of repetitions with evidence for Allee effects from simulations of an individual-based spatially explicit model for gray wolves [37] in the southern Lake Superior region.

<p>Number of repetitions with evidence for Allee effects from simulations of an individual-based spatially explicit model for gray wolves [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150535#pone.0150535.ref037" target="_blank">37</a>] in the southern Lake Superior region.</p

Depiction of an individual-based spatially explicit model for growth of the southern Lake Superior wolf population [37].

<p>The hierarchical levels of organization are the individual wolves, grid cells that make up the landscape, territories, and wolf population and the lists (e.g., sex, age, pack status) are the variables that characterize each level.</p

The probability of an Allee effect from simulations of an individual-based spatially explicit model.

<p>Posterior mean and 95% credible intervals of the probability of an Allee effect from simulations varying the perception neighborhood for mate-finding as 1, 2 or >3 territories (terr) away and the mean dispersal distances as low (25 km), average (50 km) and high (100 km) in an individual-based spatially explicit model for gray wolves in the southern Lake Superior region [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150535#pone.0150535.ref037" target="_blank">37</a>].</p

Splines fit to growth versus population size of the southern Lake Superior wolf population in 1980–2011.

<p>Fitted curves with 95% credible intervals from splines fit to the relationship between per capita growth and four measure of population size for gray wolves in the southern Lake Superior wolf (SLS) population (A) and Wisconsin (B), including the number of packs (C) and the proportion of occupied territory in Wisconsin (D).</p