Population cycles are fundamentally linked with spatial synchrony, the prevailing paradigm being that populations with cyclic dynamics are easily synchronised. That is, population cycles help give rise to spatial synchrony. Here we demonstrate this process can work in reverse, with synchrony causing population cycles. We show that timescale-specific environmental effects, by synchronising local population dynamics on certain timescales only, cause major population cycles over large areas in white-tailed deer. An important aspect of the new mechanism is specificity of synchronising effects to certain timescales, which causes local dynamics to sum across space to a substantial cycle on those timescales. We also demonstrate, to our knowledge for the first time, that synchrony can be transmitted not only from environmental drivers to populations (deer), but also from there to human systems (deer-vehicle collisions). Because synchrony of drivers may be altered by climate change, changes to population cycles may arise via our mechanism.

1. Surveillance is critical for early detection of emerging and re-emerging infectious diseases. Weighted surveillance leverages heterogeneity in infection risk to increase sampling efficiency. 2. Here, we apply a Bayesian approach to estimate weights for 16 surveillance classes of white-tailed deer in Wisconsin, USA, relative to hunter-harvested yearling males. We used these weights to conduct a surveillance programme for detecting chronic wasting disease (CWD) in white-tailed deer at Shenandoah National Park (SHEN) in Virginia, USA. 3. Generally, for surveillance, risk of infection increased with age and was greater in males. Clinical suspect deer had the highest risk, with weight estimates of 33.33 and 9.09 for community-reported and hunter-reported suspect deer, respectively. Fawns had the lowest risk with an estimated weight of 0.001. 4. We used surveillance weights for Wisconsin deer to determine sampling effort required to detect a CWD-positive case in SHEN if prevalence in yearling males >= 0.025. The sampling required to detect CWD was 37-91 adult deer, depending on the adult male: female ratio in the surveillance stream. We collected rectal biopsies from 49 female and 21 male adult deer, and 10 additional samples from vehicle-killed deer. CWD was not detected and we concluded with 95% probability that prevalence in the reference population (yearling males) was between 0.0% and 3.6%. 5. Synthesis and applications. Our approach allows managers to estimate relative surveillance weights for different host classes and quantify limits of disease detection in real time when only a sample of animals from a population can be tested, resulting in considerable cost savings for agencies performing wildlife disease detection surveillance. Additionally, it provides a rigorous means of estimating prevalence limits when a disease/pathogen is not detected in a sample set. It is therefore applicable to other wildlife, domestic animal and human disease systems, which can be characterized by surveillance classes with heterogeneous probability of infection. This methodology is also extendable to other disciplines such as invasive species, environmental toxicology, and generally, any ecological question seeking to efficiently use scarce financial and human resources to maximize the detection probability of a rare event.

Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations.

The age structure of harvested animals provides the basis for many demographic analyses. Ages of harvested white-tailed deer (Odocoileus virginianus) and other ungulates often are estimated by evaluating replacement and wear patterns of teeth, which is subjective and error-prone. Few previous studies however, examined age-and sex-specific error rates. Counting cementum annuli of incisors is an alternative, more accurate method of estimating age, but factors that influence consistency of cementum annuli counts are poorly known. We estimated age of 1,261 adult (>= 1.5 yr old) white-tailed deer harvested in Wisconsin and Illinois (USA; 2005-2008) using both wear-and-replacement and cementum annuli. We compared cementum annuli with wear-and-replacement estimates to assess misclassification rates by sex and age. Wear-and-replacement for estimating ages of white-tailed deer resulted in substantial misclassification compared with cementum annuli. Age classes of females were consistently underestimated, while those of males were underestimated for younger age classes but overestimated for older age classes. Misclassification resulted in an impression of a younger age-structure than actually was the case. Additionally, we obtained paired age-estimates from cementum annuli for 295 deer. Consistency of paired cementum annuli age-estimates decreased with age, was lower in females than males, and decreased as age estimates became less certain. Our results indicated that errors in the wear-and-replacement techniques are substantial and could impact demographic analyses that use age-structure information. (C) 2014 The Wildlife Society.

Host-parasite dynamics and strategies for managing infectious diseases of wildlife depend on the functional relationship between disease transmission rates and host density. However, the disease transmission function is rarely known for free-living wildlife, leading to uncertainty regarding the impacts of diseases on host populations and effective control actions. We evaluated the influence of deer density, landscape features, and soil clay content on transmission of chronic wasting disease (CWD) in young (<2-year-old) white-tailed deer (Odocoileus virginianus) in south-central Wisconsin, USA. We evaluated how frequency-dependent, density-dependent, and intermediate transmission models predicted CWD incidence rates in harvested yearling deer. An intermediate transmission model, incorporating both disease prevalence and density of infected deer, performed better than simple density- and frequency-dependent models. Our results indicate a combination of social structure, non-linear relationships between infectious contact and deer density, and distribution of disease among groups are important factors driving CWD infection in young deer. The landscape covariates % deciduous forest cover and forest edge density also were positively associated with infection rates, but soil clay content had no measurable influences on CWD transmission. Lack of strong density-dependent transmission rates indicates that controlling CWD by reducing deer density will be difficult. The consequences of non-linear disease transmission and aggregation of disease on cervid populations deserves further consideration.

Animal movement across the landscape plays a critical role in the ecology of infectious wildlife diseases. Dispersing animals can spread pathogens between infected areas and naïve populations. While tracking free-ranging animals over the geographic scales relevant to landscape-level disease management is challenging, landscape features that influence gene flow among wildlife populations may also influence the contact rates and disease spread between populations. We used spatial diffusion and barriers to white-tailed deer gene flow, identified through landscape genetics, to model the distribution of chronic wasting disease (CWD) in the infected region of southern Wisconsin and northern Illinois, USA. Our generalized linear model showed that risk of CWD infection declined exponentially with distance from current outbreaks, and inclusion of gene flow barriers dramatically improved fit and predictive power of the model. Our results indicate that CWD is spreading across the Midwestern landscape from these two endemic foci, but spread is strongly influenced by highways and rivers that also reduce deer gene flow. We used our model to plot a risk map, providing important information for CWD management by identifying likely routes of disease spread and providing a tool for prioritizing disease monitoring and containment efforts. The current analysis may serve as a framework for modeling future disease risk drawing on genetic information to investigate barriers to spread and extending management and monitoring beyond currently affected regions.

Aerial surveys using direct counts of animals are commonly used to estimate deer abundance. Forward-looking infrared (FUR) technology is increasingly replacing traditional methods such as visual observation from helicopters. Our goals were to compare fixed-wing FUR and visual, helicopter-based counts in terms of relative bias, influence of snow cover and cost. We surveyed five plots: four 41.4 km(2) plots with free-ranging white-tailed deer Odocoileus virginianus populations in Wisconsin and a 5.3 km(2) plot with a white-tailed deer population contained by a high fence in Michigan. We surveyed plots using both fixed-wing FLIR and helicopters, both with snow cover and without snow. None of the methods counted more deer than the other when snow was present. Helicopter counts were lower in the absence of snow, but lack of snow cover did not apparently affect FUR. Group sizes of observed deer were similar regardless of survey method or season. We found that FLIR counts were generally precise (CV = 0.089) when two or three replicate surveys were conducted within a few hours. However, at the plot level, FLIR counts differed greatly between seasons, suggesting that detection rates vary over larger time scales. Fixed-wing FLIR was more costly than visual observers in helicopters and was more restrictive in terms of acceptable survey conditions. Further research is needed to understand what factors influence the detection of deer during FLIR surveys.

ABSTRACT Effective management of wildlife populations often requires motivating hunters to harvest sufficient numbers of animals of prescribed sex and age classes to meet management goals. For cervids, it is convenient to design harvest regulations relative to presence (male) or absence (young and female) of antlers because harvest of females has a larger effect on population growth. We used regression techniques to evaluate effects of 2 supplemental hunting programs based on additional days of hunting opportunity and an additional incentive used to complement additional days on harvest of antlered and antlerless deer in Wisconsin, USA. Earn‐a‐buck regulations, an incentive‐based program that requires hunters to register an antlerless deer before being authorized to harvest an antlered deer, were associated with an average increase of 2.04 deer/km2 in antlerless harvest and a 0.60 deer/km2 decrease in harvest of antlered deer. Providing more opportunity for hunting of antlerless deer in the form of 4‐ and 8‐day supplemental firearm seasons was associated with 1.10 deer/km2 and 1.32 deer/km2 increases, respectively, in antlerless harvest with trivial (0.02 deer/km2 and 0.09 deer/km2) decreases in harvests of antlered deer. Our analysis suggests that extra days of hunting opportunity coupled with the earn‐a‐buck incentive was 56–88% more effective at increasing antlerless harvest relative to additional days of hunting without the incentive. Use of the earn‐a‐buck incentive resulted in decreased harvest of antlered deer and was disliked by many hunters. Quantifying these relationships is important for helping managers predict the costs and benefits of various hunting programs.

Age and reproductive data obtained from 2,698 bobcats harvested during the 1983-2002 seasons were used to evaluate Wisconsin's bobcat population. Analysis suggested that fall population size has increased during the past 10 years from about 1,500 to about 3,000. Methods Successful hunters and trappers were required to register their bobcat at a DNR station and turn in the carcass at that time. The sex, date of harvest, and county of harvest were recorded for each carcass. A canine tooth was extracted and sent to Matson's Lab, Milltown, MT for processing and aging (determined by counting annuli in the cementum). Ovaries and uteri were removed from all female carcasses. Uteri were examined for the presence/numbers of placental scars and ovaries were examined for corpora lutea. Harvest sex and age structure and age-specific reproductive rates were analyzed for differences between western and eastern halves of the Northern Forest region during 3 time periods (1983-92, 1993-97, and 1998-2002). Bobcat population estimates and trends were determined by incorporating data on harvest size and composition and reproductive rates into Minnesota's Furbearer Population Model. Population trends simulated by the model were compared to data from the Winter Furbearer Track Count survey. Results

Chronic wasting disease (CWD), a prion disease affecting North American cervids, has been discovered in at least 12 states and provinces throughout the continent. Since 2002, a number of states and provinces have initiated surveillance programs to detect CWD in native cervid populations. However, many questions remain about the appropriate methods, geographic scope, and number of samples required for an effective CWD surveillance program. We provide an improved statistical method to calculate the probability of detecting CWD in primary sample units (e.g., county or deer management unit) that also considers deer abundance and the nonrandom distribution of CWD and hunter harvests. We used this method to analyze data from a statewide CWD detection program conducted in Wisconsin during the autumns of 2002 and 2003 to determine the distribution of CWD in white-tailed deer (Odocoileus virginianus). Deer heads were collected at hunter registration stations, and brainstem (obex) and retropharyngeal lymph nodes were removed for disease testing. Our analysis includes samples from >35,000 deer collected outside the known affected area. The probability of detecting chronic wasting disease at a prevalence of 1% varied from 0.89 to ≥0.99 among the 56 primary sample units. Detection probabilities for 1% CWD prevalence were >0.9 in 55 primary sample units, and >0.99 in 10. Detection probabilities will be higher in areas where CWD prevalence exceeds 1%. CWD-positive deer were detected in eight primary sample units surrounding the known affected area during surveillance activities. Our approach provides a novel statistical technique to accommodate nonrandom sampling in wildlife disease surveillance programs.

Emerging infectious diseases threaten wildlife populations and human health. Understanding the spatial distributions of these new diseases is important for disease management and policy makers; however, the data are complicated by heterogeneities across host classes, sampling variance, sampling biases, and the space-time epidemic process. Ignoring these issues can lead to false conclusions or obscure important patterns in the data, such as spatial variation in disease prevalence. Here, we applied hierarchical Bayesian disease mapping methods to account for risk factors and to estimate spatial and temporal patterns of infection by chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus) of Wisconsin, U.S.A. We found significant heterogeneities for infection due to age, sex, and spatial location. Infection probability increased with age for all young deer, increased with age faster for young males, and then declined for some older animals, as expected from disease-associated mortality and age-related changes in infection risk. We found that disease prevalence was clustered in a central location, as expected under a simple spatial epidemic process where disease prevalence should increase with time and expand spatially. However, we could not detect any consistent temporal or spatiotemporal trends in CWD prevalence. Estimates of the temporal trend indicated that prevalence may have decreased or increased with nearly equal posterior probability, and the model without temporal or spatiotemporal effects was nearly equivalent to models with these effects based on deviance information criteria. For maximum interpretability of the role of location as a disease risk factor, we used the technique of direct standardization for prevalence mapping, which we develop and describe. These mapping results allow disease management actions to be employed with reference to the estimated spatial distribution of the disease and to those host classes most at risk. Future wildlife epidemiology studies should employ hierarchical Bayesian methods to smooth estimated quantities across space and time, account for heterogeneities, and then report disease rates based on an appropriate standardization.

Emerging wildlife diseases pose a significant threat to natural and human systems. Because of real or perceived risks of delayed actions, disease management strategies such as culling are often implemented before thorough scientific knowledge of disease dynamics is available. Adaptive management is a valuable approach in addressing the uncertainty and complexity associated with wildlife disease problems and can be facilitated by using a formal model.We developed a multi-state computer simulation model using age, sex, infection-stage, and seasonality as a tool for scientific learning and managing chronic wasting disease (CWD) in white-tailed deer Odocoileus virginianus. Our matrix model used disease transmission parameters based on data collected through disease management activities. We used this model to evaluate management issues on density- (DD) and frequency-dependent (FD) transmission, time since disease introduction, and deer culling on the demographics, epizootiology, and management of CWD.Both DD and FD models fit the Wisconsin data for a harvested white-tailed deer population, but FD was slightly better. Time since disease introduction was estimated as 36 (95% CI, 24-50) and 188 (41->200) years for DD and FD transmission, respectively. Deer harvest using intermediate to high non-selective rates can be used to reduce uncertainty between DD and FD transmission and improve our prediction of long-term epidemic patterns and host population impacts. A higher harvest rate allows earlier detection of these differences, but substantially reduces deer abundance.Results showed that CWD has spread slowly within Wisconsin deer populations, and therefore, epidemics and disease management are expected to last for decades. Non-hunted deer populations can develop and sustain a high level of infection, generating a substantial risk of disease spread. In contrast, CWD prevalence remains lower in hunted deer populations, but at a higher prevalence the disease competes with recreational hunting to reduce deer abundance.Synthesis and applications. Uncertainty about density- or frequency-dependent transmission hinders predictions about the long-term impacts of chronic wasting disease on cervid populations and the development of appropriate management strategies. An adaptive management strategy using computer modelling coupled with experimental management and monitoring can be used to test model predictions, identify the likely mode of disease transmission, and evaluate the risks of alternative management responses.

Published reports of peak breeding and parturition dates for White-tailed Deer (Odocoileus virginianus) indicate that deer in northern regions typically breed during November and give birth during late May and early June. However, we report a late born White-tailed Deer fawn killed by a vehicle between 12-13 March 2007 in south central Wisconsin. Morphology measurements and body weight indicated the individual was 63-76 days old, was born between 26 December 2006 and 8 January 2007, and was conceived between 14-27 June 2006. To our knowledge, this observation represents the latest documented breeding activity in northern deer populations.

Chronic wasting disease (CWD) is a fatal, emerging disease of cervids associated with transmissible protease-resistant prion proteins. The potential for CWD to cause dramatic declines in deer and elk populations and perceived human health risks associated with consuming CWD-contaminated venison have led wildlife agencies to embark on extensive CWD control programs, typically involving culling to reduce deer populations. We characterized the spatial distribution of CWD in white-tailed deer (Odocoileus virginianus) in Wisconsin to facilitate CWD management. We found that CWD prevalence declined with distance from a central location, was locally correlated at a scale of 3.6 km, and was correlated with deer habitat abundance. The latter result is consistent with patterns expected for a positive relationship between density and prevalence of CWD. We recommend management activities focused on culling in geographic areas with high prevalence to have the greatest probability of removing infected individuals. Further research is needed to elucidate the factors involved in CWD spread and infection rates, especially the role of density-dependent transmission.

Chronic wasting disease (CWD) was discovered in free-ranging white-tailed deer (Odocoileus virginianus) in south-central Wisconsin in 2002. The current control method for CWD in the state is the harvest of deer from affected areas to reduce population density and lower CWD transmission. We used spatial regression methods to identify factors associated with deer harvest across south-central Wisconsin. Harvest of deer by hunters was positively related to deer density (slope=0.003, 95% CI=0.0001-0.006), the number of landowners that requested harvest permits (slope =0.071, 95% CI=0.037-0.105), and proximity to the area of highest CWD infection (slope =-0.041, 95% CI=-0.056-0.027). Concomitantly, harvest was not impacted in areas where landowners signed a petition protesting intensive deer reduction (slope = -0.00006, 95% CI=-0.0005-0.0003). Our results suggest that the success of programs designed to reduce deer populations for disease control or to reduce overabundance in Wisconsin are dependent on landowner and hunter participation. We recommend that programs or actions implemented to eradicate or mitigate the spread of CWD should monitor and assess deer population reduction and evaluate factors affecting program success to improve methods to meet management goals.

Three White-tailed Deer shot within 5 km during the 2001 hunting season in Wisconsin tested positive for chronic wasting disease, a prion disease of cervids. Subsequent sampling within 18 km showed a 3% prevalence (n=476). This discovery represents an important range extension for chronic wasting disease into the eastern United States.

The 2008 Beaver Helicopter Survey produced population estimates of approximately 27,800 and 17,500 beavers in Management Zones A and B, respectively. Estimates of the beaver population in the northern third of Wisconsin decreased 35% between 2005 and 2008 and more than 50% since 1995. Background In 1989 the Wisconsin State Legislature provided funds for the WDNR to determine the feasibility of significantly reducing beaver numbers in problem areas. A portion of that money was used to develop a census method for evaluating the effectiveness of various beaver control efforts. Initial development and testing during 1990-92 resulted in a helicopter survey capable of estimating regional beaver populations within +20% (Kohn and Ashbrenner 1994). This survey was repeated in 1995, 1998, 2001, 2005, and 2008. Methods Active beaver colonies within 42 randomly selected blocks in Beaver Management Zone A and 43 blocks in Zone B were counted from a Schweizer 333 (Fig. 1). The blocks ranged in size from 3.3 to 8.5 mi2, and averaged 5.5 mi2. The size and shape of each block was dependent upon locations of suitable boundaries (usually roads) which could be easily identified from the air. The total area surveyed was 228.7 mi2 in Beaver Management Zone A and 238.6 mi2 in Zone B. Two observers plus the pilot were used to identify active colonies. Active colonies were identified by the presence of fresh feed piles, cuttings, and/or evidence that the lodge had been recently maintained. Each block was completely surveyed even though large portions of some blocks did not contain beaver habitat. The estimated number of active colonies within each block was calculated by dividing the number observed by an observation rate of 0.81 (Payne 1981, Kohn and Ashbrenner 1994). Numbers of colonies within each Beaver Management Zone were then estimated by dividing the estimated number of colonies per mi2 in the survey blocks into the gross area of the Zone. A mean colony size of 5.5 beaver per colony (Peterson 1979, Kohn and Ashbrenner 1994) was then used to estimate the beaver population within each Zone. Results The 2008 Beaver Helicopter Survey was conducted during October 31-November 5. The survey required 67 hours of flight time, and the total aircraft cost (flight time, per diem for pilot and crew member, fuel truck, and hangar rental) was $45,400.

Harvest size and sex and age structure data are combined in population models to estimate the size of the fisher population in the northern third of Wisconsin. Recent differences in model simulated trends and winter track count trends suggest fisher populations may have been overestimated. Adjustments were made to starting population size in models for Fisher Management Zones A, B, and D. Adjusted models produce an estimate of approximately 11,500 fishers in fall 2009 in the northern 1/3 of the state. A harvest of 2,200 fishers was recommended for the 2009 season. Methods Trappers in all zones were required to register their fishers at a DNR station. In 2008, trappers in zones E and F were required to surrender the carcass of animals they caught. Date of harvest and harvest zone (Fig. 1) were recorded for each carcass. A section of the lower jaw including the canine and fourth premolar was extracted from each carcass. These samples were sent to Matson's Laboratory, Milltown, MT for processing and aging by counting annuli in the cementum of the fourth premolar. The sex of each fisher carcass was determined by examining reproductive organs. Ovaries were removed from all female carcasses and stored in 10% formalin until they were firm enough to hand section. The sections were then examined for corpora lutea to estimate number of young. Fisher population estimates and trends were determined using Minnesota's Fisher Population Model and data obtained from harvest registration, carcass collections, and the Winter Furbearer Track Counts. Kohn et al. (1993) described procedures and interpretations in detail for data collected during 1985-92. The Fisher Population Model was refined in 1995-96. Major changes included adjustments to illegal harvest estimates during earlier seasons with low harvests, and direct use of track frequencies observed in Winter Furbearer Track Counts as an independent estimate of population trends. The model was then modified for application in each Fisher Management Zone in 1997. Starting population size in the model was adjusted in zones A and C in 2003 and in zone C in 2008 to improve the correlation between model simulated population trends and trends in winter track counts. Because of continued differences between model simulated population trends and winter track count trends additional reductions were made to the starting population size in models for zones A, B, and D in 2009. Results