Pathogens can regulate or decimate free-ranging wildlife populations. Wild turkeys (Meleagris gallopavo), which are widespread across the United States, southern Canada, and northern and central Mexico, are a prized upland gamebird that has experienced dramatic population growth and range expansion as the result of reintroduction campaigns. While increased abundance may promote disease transmission, little is known about the effects of pathogen infections on demographic metrics in wild turkeys. Lymphoproliferative disease virus (LPDV) and reticuloendotheliosis virus (REV) are oncogenic retroviruses that infect poultry and wild turkeys and can result in disease and mortality, though most infected individuals appear asymptomatic. We investigated whether retroviral infections influence wild turkey fitness by evaluating effects on female survival and several reproduction metrics. We live-captured 163 female wild turkeys throughout central Maine, USA during three winters, from 2018 to 2020. We collected blood for LPDV and REV molecular diagnostics and attached a GPS or VHF transmitter to monitor survival and nesting. Infection with REV was associated with nearly half the cumulative annual survival probability, while LPDV-infected hens laid an average of 1.4 fewer eggs per clutch. We detected no effects of retroviral infection on nest initiation, nesting propensity, or hatch rate, and coinfection was not associated with any measured demographic metric. These findings demonstrate that retroviral infections can negatively affect survival and clutch size in female wild turkeys even in the absence of overt disease, highlighting the importance of considering pathogen effects when evaluating the population dynamics of free-ranging wildlife.
Species must acclimate, shift their distribution, or adapt in place in response to anthropogenic climate change. Populations at the low-latitude trailing edge of the species distribution typically experience thermal conditions closest to the upper limit of their thermoregulatory capacity. Landscape and functional genomic approaches provide quantitative measures of risk and adaptive capacity which can inform and prioritise conservation actions. Using low-coverage whole genomes from Canada lynx (Lynx canadensis), we characterised population genomic structure and identified putatively adaptive loci using genotype-environment association analyses across the eastern extent of their distribution. We detected genetic breaks across two previously identified biogeographical barriers, the St. Lawrence River and the Strait of Belle Isle, and found relatively high genome-wide diversity in the Maine population at the southern trailing edge. We identified 759 loci from 329 genes as putatively adaptive, many associated with temperature during warm and dry periods, and functionally enriched in photoreception, circadian entrainment, and temperature regulation. We identified 10 putatively adaptive genes linked to epilepsy, presenting candidate genes underlying reports of idiopathic epilepsy in captive populations of closely related lynx species (L. lynx and L. pardinus). Standing variation in putatively adaptive loci was relatively low in Maine, suggesting that currently advantageous alleles may be fixed. Genomic offset showed lynx in Western Newfoundland and the Gaspé Peninsula in Quebec are at the greatest risk of maladaptation under future conditions. Together, these findings highlight the conservation importance of range-edge populations as reservoirs of unique adaptive variation, while also emphasizing their potential vulnerability under continued climate change.
Obtaining accurate information on demographic states, such as the age and sex classes of animals, is an important step for monitoring wildlife populations. Traditionally, demographic data are collected from harvest, aerial surveys and telemetry studies. However, these methods can be expensive, limited to small spatial scales, or biased due to human behavior. Remote cameras have become a mainstay for studying and monitoring wildlife as they are relatively inexpensive, can be deployed over large spatial scales, and effort can be accounted for during surveys. For some species, a variety of demographic information, such as sex and age classes, can be obtained from pictures. Moose Alces alces are a photogenic species found across boreal and semi-boreal forests of the Northern Hemisphere. Previous studies have used demographic data from remote cameras to estimate demographic parameters and population dynamics. A primary assumption is that these age and sex classes are accurately classified. However, numerous factors can influence the ability of observers to identify age and sex classes of moose captured on cameras. We used data from 84 cameras from a 3-year period (2021-2024) in northern Maine, USA, to evaluate how temporal, environmental, site-level, and endogenous factors influence observers' ability to classify age and sex classes of moose. Using Bayesian categorical regression models, we found that temporal variability, position and proximity of moose from cameras, and the behavior of moose influenced our ability to identify age and sex classes. This information can be used to decide which periods to use data for population modeling and how to design studies to reduce the amount of uncertainty associated with different age and sex classes. We anticipate that our approach could also be used for other species whose age and sex classes can be differentiated using remote cameras.
Wood Turtle (Glyptemys insculpta) populations are declining in many portions of the species’ native range due to multiple factors that might influence functional connectivity and population genetic structure. We used 13 microsatellite markers to examine patterns of genetic structure in the Wood Turtle across its native range in Eastern and Midwestern North America. For n = 45 collections with 15 or more individuals (total N = 1,258), multiple clustering approaches revealed two major genetic groups corresponding to the midwestern and eastern collections. Interestingly, a sample from lower Michigan clustered with the Eastern group while a sample from the Upper Peninsula of Michigan clustered with the Midwestern group. Evidence of gene flow between these two major groups arose from the most proximate sites near the edges of each group. These results suggest that Lake Superior and Lake Michigan were historically substantial (but perhaps not complete) barriers to gene flow. Our results suggest that Evolutionarily Significant Unit (ESU) status is warranted for Midwestern and Eastern Wood Turtles in North America. Within the eastern group, we observed a strong pattern of clinal allele frequency variation, with evidence of incipient genetic differentiation between multiple collections from the Potomac and Monongahela Rivers from collections in river basins further to the north. Estimation of full-sibling families indicated a range of distance between close family members of 16.8–301 km, suggesting the possibility of extremely long-distance (though rare) dispersal. Mean expected heterozygosity ranged from 0.553 to 0.722 and allelic richness ranged from 4.1 to 6.8. For a species with such a long generation interval (approximately 40 years (yrs)), isolated populations on the low end of this range of both measures of genetic variation might suffer from negative fitness effects of inbreeding and warrant further monitoring efforts. Our results support the management of this species at, or within, the Hydrologic Unit Code-4 (HUC4) subregion scale.
Reptiles, and turtles in particular, are disproportionately represented in the illegal wildlife trade. Chemical analysis of animal tissues is a powerful tool to combat wildlife laundering, which is the act of disguising animals poached from the wild as legally raised in captivity by means of counterfeit import or export documentation. We used stable isotope ratios and trace element concentrations derived from the claw tips of 449 wood ( Glyptemys insculpta ), spotted ( Clemmys guttata ), and Blanding's turtles ( Emydoidea blandingii ) from the eastern United States to develop a multispecies statistical model for determining the probability that a confiscated turtle was poached from the wild. During model development, our simple model that used 4 stable isotope ratios (δ 13 C, δ 15 N, δ 18 O, δ 2 H) and 4 trace elements (Ti‐47, Fe‐57, Cu‐63, Ba‐137) misclassified only 2 turtles out of 449, yielding a predictive accuracy rate of 99.55%. We further validated the predictive accuracy of our multispecies model by calculating the probability of being wild for 9 eastern box turtles ( Terrapene carolina ) and a replicate sample of 5 wood turtles, all with known classifications of being wild or captive. We now aim to promote our model to aid conservation law enforcement in combating the illegal turtle trade by helping to close the wildlife laundering loophole. We also hope to provide a forensic framework for developing a conservation tool for other taxa of conservation interest.
