Inferring stochastic group interactions within structured populations via coupled autoregression

The internal behaviour of a population is an important feature to take account of when modelling its dynamics. In line with kin selection theory, many social species tend to cluster into distinct groups in order to enhance their overall population fitness. Temporal interactions between populations are often modelled using classical mathematical models, but these sometimes fail to delve deeper into the, often uncertain, relationships within populations. Here, we introduce a stochastic framework that aims to capture the interactions of animal groups and an auxiliary population over time. We demonstrate the model's capabilities, from a Bayesian perspective, through simulation studies and by fitting it to predator-prey count time series data. We then derive an approximation to the group correlation structure within such a population, while also taking account of the effect of the auxiliary population. We finally discuss how this approximation can lead to ecologically realistic interpretations in a predator-prey context. This approximation also serves as verification to whether the population in question satisfies our various assumptions. Our modelling approach will be useful for empiricists for monitoring groups within a conservation framework and also theoreticians wanting to quantify interactions, to study cooperation and other phenomena within social populations.

Patterns and processes of pathogen exposure in gray wolves across North America

The presence of many pathogens varies in a predictable manner with latitude, with infections decreasing from the equator towards the poles. We investigated the geographic trends of pathogens infecting a widely distributed carnivore: the gray wolf (Canis lupus). Specifically, we investigated which variables best explain and predict geographic trends in seroprevalence across North American wolf populations and the implications of the underlying mechanisms. We compiled a large serological dataset of nearly 2000 wolves from 17 study areas, spanning 80° longitude and 50° latitude. Generalized linear mixed models were constructed to predict the probability of seropositivity of four important pathogens: canine adenovirus, herpesvirus, parvovirus, and distemper virus-and two parasites: Neospora caninum and Toxoplasma gondii. Canine adenovirus and herpesvirus were the most widely distributed pathogens, whereas N. caninum was relatively uncommon. Canine parvovirus and distemper had high annual variation, with western populations experiencing more frequent outbreaks than eastern populations. Seroprevalence of all infections increased as wolves aged, and denser wolf populations had a greater risk of exposure. Probability of exposure was positively correlated with human density, suggesting that dogs and synanthropic animals may be important pathogen reservoirs. Pathogen exposure did not appear to follow a latitudinal gradient, with the exception of N. caninum. Instead, clustered study areas were more similar: wolves from the Great Lakes region had lower odds of exposure to the viruses, but higher odds of exposure to N. caninum and T. gondii; the opposite was true for wolves from the central Rocky Mountains. Overall, mechanistic predictors were more informative of seroprevalence trends than latitude and longitude. Individual host characteristics as well as inherent features of ecosystems determined pathogen exposure risk on a large scale. This work emphasizes the importance of biogeographic wildlife surveillance, and we expound upon avenues of future research of cross-species transmission, spillover, and spatial variation in pathogen infection.

Adaptive monitoring: using citizen scientists to track wolf populations when winter-track counts become unreliable

Abstract ContextIn many countries, annual wolf surveys based on snow-track counts have become unreliable because of inconsistent snow coverage. We considered incidental observations by volunteers throughout the year as an alternative monitoring protocol. AimsWe recruited interested citizens throughout Lithuania, including hunters, foresters and farmers, to estimate wolf distribution, abundance, pack numbers and group size from 2015 to 2018. MethodsObservation-based records of wolves were collected using simple questionnaires that included time, location and method of observation (e.g. track, scat, vocalisation or prey-kill remains). We summarised 979 reports of 1938 observed wolves. Key resultsVolunteer reports suggested an increase in wolf distribution and abundance from 2015 to 2018. The observed number of wolf packs was estimated to be at least 100 by 2018, pack size increased to 3.6, and the share of single wolves decreased from 56% in 2015 to 40% in 2018. ConclusionsWe found that volunteer observations can provide useful information on wolf distribution, pack size and pack numbers. Our results support previous reports of expanding wolf populations in the Baltic region. ImplicationsResults of our citizen-science effort by Nature Research Centre and Lithuanian Hunters and Fishers Association have been accepted by the Ministry of Environment as a complement to other surveys in Lithuania and should aid in developing an informed wolf-management policy.

Ungulate predation and ecological roles of wolves and coyotes in eastern North America

Understanding the ecological roles of species that influence ecosystem processes is a central goal of ecology and conservation biology. Eastern coyotes (Canis latrans) have ascended to the role of apex predator across much of eastern North America since the extirpation of wolves (Canis spp.) and there has been considerable confusion regarding their ability to prey on ungulates and their ecological niche relative to wolves. Eastern wolves (C. lycaon) are thought to have been the historical top predator in eastern deciduous forests and have previously been characterized as deer specialists that are inefficient predators of moose because of their smaller size relative to gray wolves (C. lupus). We investigated intrinsic and extrinsic influences on per capita kill rates of white-tailed deer (Odocoileus virginianus) and moose (Alces alces) during winter by sympatric packs of eastern coyotes, eastern wolves, and admixed canids in Ontario, Canada to clarify the predatory ability and ecological roles of the different canid top predators of eastern North America. Eastern coyote ancestry within packs negatively influenced per capita total ungulate (deer and moose combined) and moose kill rates. Furthermore, canids in packs dominated by eastern coyote ancestry consumed significantly less ungulate biomass and more anthropogenic food than packs dominated by wolf ancestry. Similar to gray wolves in previous studies, eastern wolves preyed on deer where they were available. However, in areas were deer were scarce, eastern wolves killed moose at rates similar to those previously documented for gray wolves at comparable moose densities across North America. Eastern coyotes are effective deer predators, but their dietary flexibility and low kill rates on moose suggest they have not replaced the ecological role of wolves in eastern North America.