A resource-based approach to modelling the dynamics of interacting populations

The procedure for modelling the growth of single-species populations [Sakanoue, S., 2007. Extended logistic model for growth of single-species populations. Ecol. Model. 205, 159–168] is improved to be applicable to the study of the dynamics of interacting populations. The improved procedure is based on three assumptions: resource availability changes with population size as a variable, resource supply to populations and population demand for resources are defined as functions of resource availability and population size, and the variables of resource availability and population size shift in the supply function attracted to the demand function. These assumptions are organized into three equations. The equations can generate the dynamics models of plant, herbivore, and detritivore populations, and their own resources. The models can be used to describe prey–predator dynamics. They naturally contain nonlinear terms for the predator’s numerical and functional responses. Depending on the terms, the fluctuations in resource availability and population size stabilize. The three equations can also generate the dynamics models of different populations consuming the same resources. The analysis of zero isoclines of the models shows that a superior population can be simply defined as one with a higher intrinsic rate of natural increase, that a stable coexistence may be realized with the intraspecific interference or the interspecific facilitation of superiors, and that the interspecific interference or the intraspecific facilitation of inferiors may make the coexistence unstable and the inferiors winners depending on their initial population size.     

Uncertainty analysis of transient population dynamics

Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat (Oreamnos americanus) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models.     

Spectral analysis unmasks synchronous and compensatory dynamics in plankton communities

Community biomass is often less variable than the biomasses of populations within the community, yet attempts to implicate compensatory dynamics between populations as a cause of this relationship often fail. In part, this may be due to the lack of appropriate metrics for variability, but there is also great potential for large-scale processes such as seasonality or longer-term environmental change to obscure important dynamics at other temporal scales. In this study, we apply a scale-resolving method to long-term plankton data, to identify the specific temporal scales at which community-level variability is influenced by synchrony or compensatory dynamics at the population level. We show that variability at both the population and community level is influenced strongly by a few distinct temporal scales: in phytoplankton, ciliate, rotifer, and crustacean communities, synchronous dynamics are predominant at most temporal scales. However, in phytoplankton and crustacean communities, compensatory dynamics occur at a sub-annual scale (and at the annual scale in crustaceans) leading to substantial reductions in community-level variability. Aggregate measures of population and community variability do not detect compensatory dynamics in these communities; thus, resolving their scale dependence unmasks dynamics that are important for community stability in this system. The methods and results presented herein will ultimately lead to a better understanding of how stability is achieved in communities.     

Temporal Analysis of Genetic Structure to Assess Population Dynamics of Reintroduced Swift Foxes

Reintroductions are increasingly used to reestablish species, but a paucity of long‐term postrelease monitoring has limited understanding of whether and when viable populations subsequently persist. We conducted temporal genetic analyses of reintroduced populations of swift foxes (Vulpes velox) in Canada (Alberta and Saskatchewan) and the United States (Montana). We used samples collected 4 years apart, 17 years from the initiation of the reintroduction, and 3 years after the conclusion of releases. To assess program success, we genotyped 304 hair samples, subsampled from the known range in 2000 and 2001, and 2005 and 2006, at 7 microsatellite loci. We compared diversity, effective population size, and genetic connectivity over time in each population. Diversity remained stable over time and there was evidence of increasing effective population size. We determined population structure in both periods after correcting for differences in sample sizes. The geographic distribution of these populations roughly corresponded with the original release locations, which suggests the release sites had residual effects on the population structure. However, given that both reintroduction sites had similar source populations, habitat fragmentation, due to cropland, may be associated with the population structure we found. Although our results indicate growing, stable populations, future connectivity analyses are warranted to ensure both populations are not subject to negative small‐population effects. Our results demonstrate the importance of multiple sampling years to fully capture population dynamics of reintroduced populations. Análisis Temporal de la Estructura Genética para Evaluar la Dinámica Poblacional de Zorros (Vulpes velox) Reintroducidos     

Spatial variation in population dynamics in a colonial ascidian (Botryllus schlosseri)

Recent interest in the dynamics of marine invertebrate populations has focused largely on taxa with an open population structure. However, in many colonial taxa with limited larval dispersal, settlers may be locally derived. Consequently, dynamics may vary among sites that are separated by relatively short distances. This study explored spatial variation in temporal dynamics of colonial ascidians (Botryllus schlosseri Pallas) inhabiting five sites distributed along a ≈ 17-km temperature and phytoplankton gradient in the Damariscotta River estuary, Maine, USA. Settlement and population densities and sexual reproductive status were assayed throughout the summer seasons of 1996 and 1997. Sexual reproduction and larval settlement commenced earlier in the summer in up-river populations, which subsequently underwent a seasonal population explosion that was much smalier in down-river populations. Two peaks in settlement density up-river (in early July and early September) suggest that colonies there may have completed two sexual generations, in contrast to a single generation at down-river sites. Similar spatial variation is expected among populations of other taxa with limited larval dispersal when they are distributed across environmental gradients. Published online: 18 September 2002     

Confronting two-sex demographic models with data

Most population dynamics models explicitly track the density of a single sex. When the operational sex ratio can vary, two-sex models may be needed to understand and predict population trajectories. Various functions have been proposed to describe the relative contributions of females and males to recruitment, and these functions can differ qualitatively in the patterns that they generate. Which mating function best describes the dynamics of real populations is not known, since alternative two-sex models have not been confronted with experimental data. We conducted the first such comparison, using laboratory populations of the bean beetle Callosobruchus maculatus. Manipulations of the operational sex ratio and total density provided strong support for a demographic model in which the birth rate was proportional to the harmonic mean of female and male densities, and females, males, and their offspring made unique contributions to density dependence. We offer guidelines for transferring this approach to other, less tractable systems in which possibilities for sex ratio manipulations are more limited. We show that informative experimental designs require strong perturbations of the operational sex ratio. The functional form of density dependence (saturating vs. over-compensatory) and the relative contributions of each sex to density dependence can both determine in which direction and at which population densities such perturbations would be most informative. Our experimental results and guidelines for design strategies promote synthesis of two-sex population dynamics theory with empirical data.     

Will Observation Error and Biases Ruin the Use of Simple Extinction Models?

Abstract: Estimating the risk of extinction for populations of endangered species is an important component of conservation biology. These estimates must be made from data that contain both environmental noise in the year-to-year transitions in population size (so-called "process error"), random errors in sampling, and possible biases in sampling ( both forms of observation errors). To determine how much faith to place in estimated extinction rates, it is important to know how sensitive they are to observation error. We used three simple, commonly employed models of population dynamics to generate simulated population time series. We then combined random observation error or systematic biases with those data, fit models to the time series data, and observed how close the extinction dynamics of the fitted models compared with the dynamics of the underlying models. We found that systematic biases in sampling rarely affected estimates of extinction risk. We also found that even moderate levels of random observation error do not significantly affect extinction estimates except over a small range of process errors, corresponding to the region where extinction risk is most uncertain. With more substantial sampling error, estimates of extinction risk degraded rapidly. Field census techniques for a variety of taxa often involve observation errors within ±32% of actual population sizes. For typical time series used in conservation, therefore, we often may not need to be overly concerned about observation errors as an extra source of imperfection in our estimated extinction rates.     

Integral projection models for finite populations in a stochastic environment

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.     

Differences in sensitivity to the fungal pathogen Batrachochytrium dendrobatidis among amphibian populations

Contributing to the worldwide biodiversity crisis are emerging infectious diseases, which can lead to extirpations and extinctions of hosts. For example, the infectious fungal pathogen Batrachochytrium dendrobatidis (Bd) is associated with worldwide amphibian population declines and extinctions. Sensitivity to Bd varies with species, season, and life stage. However, there is little information on whether sensitivity to Bd differs among populations, which is essential for understanding Bd‐infection dynamics and for formulating conservation strategies. We experimentally investigated intraspecific differences in host sensitivity to Bd across 10 populations of wood frogs (Lithobates sylvaticus) raised from eggs to metamorphosis. We exposed the post‐metamorphic wood frogs to Bd and monitored survival for 30 days under controlled laboratory conditions. Populations differed in overall survival and mortality rate. Infection load also differed among populations but was not correlated with population differences in risk of mortality. Such population‐level variation in sensitivity to Bd may result in reservoir populations that may be a source for the transmission of Bd to other sensitive populations or species. Alternatively, remnant populations that are less sensitive to Bd could serve as sources for recolonization after epidemic events.     

The impact of parasite manipulation and predator foraging behavior on predator-prey communities

Parasites are known to directly affect their hosts at both the individual and population level. However, little is known about their more subtle, indirect effects and how these may affect population and community dynamics. In particular, trophically transmitted parasites may manipulate the behavior of intermediate hosts, fundamentally altering the pattern of contact between these individuals and their predators. Here, we develop a suite of population dynamic models to explore the impact of such behavioral modifications on the dynamics and structure of the predator-prey community. We show that, although such manipulations do not directly affect the persistence of the predator and prey populations, they can greatly alter the quantitative dynamics of the community, potentially resulting in high amplitude oscillations in abundance. We show that the precise impact of host manipulation depends greatly on the predator's functional response, which describes the predator's foraging efficiency under changing prey availabilities. Even if the parasite is rarely observed within the prey population, such manipulations extend beyond the direct impact on the intermediate host to affect the foraging success of the predator, with profound implications for the structure and stability of the predator-prey community.     

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.     

Potential effects of environmental contamination on Yuma Myotis demography and population growth.

Unplanned natural and anthropogenic disasters provide unique opportunities for investigating the influence of perturbations on population vital rates and species recovery times. We investigated the potential effects of a major pesticide spill by comparing annual survival rates using mark-recapture techniques on a riparian bat species, Yuma Myotis (Myotis yumanensis). Demography and population dynamics for most bat species remain poorly understood despite advances in mark-recapture estimation and modeling techniques. We compared survival and population growth rates of two roost populations exposed to a large chemical (metam sodium) spill in the upper Sacramento River in Northern California with two roost populations outside the contaminated area from 1992 to 1996. Hypotheses about long-term effects of the spill on female juvenile and adult survival were tested using an information-theoretic approach (AIC). Working hypotheses included effects of age, chemical spill, and time trend on survival. Female adult survival was higher than female juvenile survival across all sites, suggesting stage-specific mortality risks. Model-averaged estimates of female juvenile survival in the contaminated area (0.50-0.74) were lower than in control roosts (0.60-0.78) for each year in the study, suggesting that the spill may have reduced juvenile survival for several years. Female adult survival (0.73-0.89) did not appear to be strongly affected by the spill during the years of the study. There was an increase in survival for both stage-classes across all populations during the study period, which may have been caused by the end of an extended drought in California in the winter of 1993. The spill-affected population was in decline for the first year of the study as indicated by an estimated growth rate (lambda) < 1, but population growth rates increased during the four-year period.     

Reduced effect of Tasmanian devil facial tumor disease at the disease front

Pathogen-driven declines in animal populations are increasingly regarded as a major conservation issue. The Tasmanian devil (Sarcophilus harrisii) is threatened with extinction by devil facial tumor disease, a unique transmissible cancer. The disease is transmitted through direct transfer of tumor cells, which is possible because the genetic diversity of Tasmanian devils is low, particularly in the major histocompatibility complex genes of the immune system. The far northwest of Tasmania now holds the last remaining disease-free wild devil populations. The recent discovery of unique major histocompatibility complex genotypes in the northwestern region of Tasmania has raised the possibility that some animals may be resilient to the disease. We examined the differences in the epidemiology and population effects of devil facial tumor disease at 3 well-studied affected sites in eastern Tasmania and 1 in western Tasmania (West Pencil Pine). In contrast to the 3 eastern sites, there has been no rapid increase in disease prevalence or evidence of population decline at West Pencil Pine. Moreover, this is the only onsite at which the population age structure has remained unaltered 4 years after the first detection of disease. The most plausible explanations for the substantial differences in population effects and epidemiology of the disease between eastern and western sites are geographic differences in genotypes or phenotypes of devils and functional differences between tumor strains in the 2 regions. We suggest that conservation efforts focus on identifying whether either or both these explanations are correct and then, if resistance alleles exist, to attempt to spread the resistant alleles into affected populations. Such assisted selection has rarely been attempted for the management of wildlife diseases, but it may be widely applicable.     

Habitat complexity modifies post-settlement mortality and recruitment dynamics of a marine fish

For species that have an open population structure, local population size may be strongly influenced by a combination of propagule supply and post-settlement survival. While it is widely recognized that supply of larvae (or recruits) is variable and that variable recruitment may affect the relative contribution of pre- and post-settlement factors, less effort has been made to quantify how variation in the strength of post-settlement mortality (particularly density-dependent mortality) will affect the importance of processes that determine population size. In this study, I examined the effects of habitat complexity on mortality of blue rockfish (Sebastes mystinus) within nearshore reefs off central California. I first tested whether variation in habitat complexity (measured as three-dimensional complexity of rocky substrate) affected the magnitude of both density-independent and density-dependent mortality. I then used limitation analysis to quantify how variation in habitat complexity alters the relative influence of recruitment, density-independent mortality, and density-dependent mortality in determining local population size. Increased habitat complexity was associated with a reduction in both density-independent and density-dependent mortality. At low levels of habitat complexity, limitation analysis revealed that mortality was strong and recruitment had relatively little influence on population size. However, as habitat complexity increased, recruitment became more important. At the highest levels of habitat complexity, limitation by recruitment was substantial, although density-dependent mortality was ultimately the largest constraint on population size. In high-complexity habitats, population dynamics may strongly reflect variation in recruitment even though fluctuations may be dampened by density-dependent mortality. By affecting both density-independent and density-dependent mortality, variation in habitat complexity may result in qualitative changes in the dynamics of populations. These findings suggest that the relative importance of pre- vs. post-settlement factors may be determined by quantifiable habitat features, rather than ambient recruitment level alone. Because the magnitude of recruitment fluctuations can affect species coexistence and the persistence of populations, habitat-driven changes in population dynamics may have important consequences for both community structure and population viability.     

Bayesian Methods in Conservation Biology

Abstract: Bayesian statistical inference provides an alternate way to analyze data that is likely to be more appropriate to conservation biology problems than traditional statistical methods. I contrast Bayesian techniques with traditional hypothesis-testing techniques using examples applicable to conservation. I use a trend analysis of two hypothetical populations to illustrate how easy it is to understand Bayesian results, which are given in terms of probability. Bayesian trend analysis indicated that the two populations had very different chances of declining at biologically important rates. For example, the probability that the first population was declining faster than 5% per year was 0.00, compared to a probability of 0.86 for the second population. The Bayesian results appropriately identified which population was of greater conservation concern. The Bayesian results contrast with those obtained with traditional hypothesis testing. Hypothesis testing indicated that the first population, which the Bayesian analysis indicated had no chance of declining at > 5% per year, was declining significantly because it was declining at a slow rate and the abundance estimates were precise. Despite the high probability that the second population was experiencing a serious decline, hypothesis testing failed to reject the null hypothesis of no decline because the abundance estimates were imprecise. Finally, I extended the trend analysis to illustrate Bayesian decision theory, which allows for choice between more than two decisions and allows explicit specification of the consequences of various errors. The Bayesian results again differed from the traditional results: the decision analysis led to the conclusion that the first population was declining slowly and the second population was declining rapidly.     

Transient population dynamics in periodic matrix models: methodology and effects of cyclic permutations

Many biological populations are subject to periodically changing environments such as years with or without fire, or rotation of crop types. The dynamics and management options for such populations are frequently investigated using periodic matrix models. However the analysis is usually limited to long-term results (asymptotic population growth rate and its sensitivity to perturbations of vital rates). In non-periodic matrix models it has been shown that long-term results may be misleading as populations are rarely in their stable structure. We therefore develop methods to analyze transient dynamics of periodic matrix models. In particular, we show how to calculate the effects of perturbations on population size within and at the end of environmental cycles. Using a model of a weed population subject to a crop rotation, we show that different cyclic permutations produce different patterns of sensitivity of population size and different population sizes. By examining how the starting environment interacts with the initial conditions, we explain how different patterns arise. Such understanding is critical to developing effective management and monitoring strategies for populations subject to periodically recurring environments.     

A multispecies test of source–sink indicators to prioritize habitat for declining populations

For species at risk of decline or extinction in source–sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site‐ or habitat‐specific demographic conditions, movement abilities, and behaviors. We calculated source–sink metrics over a range of periods of data collection and prioritized consistently high‐output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source–sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data‐rich source–sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short‐term regional persistence. Because source–sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas     

Demography of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii)

Every species occupies a limited geographic area, but how spatiotemporal environmental variation affects individual and population fitness to create range limits is not well understood. Because range boundaries arise where, on average, populations are more likely to go extinct than to persist, range limits are an inherently population-level problem for which a demographic framework is useful. In this study, I compare demographic parameters and population dynamics between central and marginal populations of monkeyflowers, Mimulus cardinalis and M. lewisii, along an elevation gradient spanning both species' ranges. Central and marginal populations of both species differed in survival and fecundity. For M. lewisii, these components of fitness were higher in central than in marginal populations, but for M. cardinalis the converse was true. To assess spatiotemporal variation in population dynamics, I used transition matrix models to estimate asymptotic population growth rates (lambda) and found that population growth rates of M. lewisii were highest at the range center and reduced at the range margin. Population growth rates of M. cardinalis were highest at the range margin and greatly reduced at the range center. Life table response analysis decomposed spatiotemporal variation in lambda into contributions from each transition between life stages, finding that transitions from large nonreproductive and reproductive plants to the seed class and stasis in the reproductive class made the largest contributions to spatial differences in lambda. These transitions had only low to moderate sensitivities, indicating that differences in projected population growth rates resulted mainly from observed differences in transition matrix parameters and their underlying vital rates.     

Emerging prion disease drives host selection in a wildlife population

Infectious diseases are increasingly recognized as an important force driving population dynamics, conservation biology, and natural selection in wildlife populations. Infectious agents have been implicated in the decline of small or endangered populations and may act to constrain population size, distribution, growth rates, or migration patterns. Further, diseases may provide selective pressures that shape the genetic diversity of populations or species. Thus, understanding disease dynamics and selective pressures from pathogens is crucial to understanding population processes, managing wildlife diseases, and conserving biological diversity. There is ample evidence that variation in the prion protein gene (PRNP) impacts host susceptibility to prion diseases. Still, little is known about how genetic differences might influence natural selection within wildlife populations. Here we link genetic variation with differential susceptibility of white-tailed deer to chronic wasting disease (CWD), with implications for fitness and disease-driven genetic selection. We developed a single nucleotide polymorphism (SNP) assay to efficiently genotype deer at the locus of interest (in the 96th codon of the PRNP gene). Then, using a Bayesian modeling approach, we found that the more susceptible genotype had over four times greater risk of CWD infection; and, once infected, deer with the resistant genotype survived 49% longer (8.25 more months). We used these epidemiological parameters in a multi-stage population matrix model to evaluate relative fitness based on genotype-specific population growth rates. The differences in disease infection and mortality rates allowed genetically resistant deer to achieve higher population growth and obtain a long-term fitness advantage, which translated into a selection coefficient of over 1% favoring the CWD-resistant genotype. This selective pressure suggests that the resistant allele could become dominant in the population within an evolutionarily short time frame. Our work provides a rare example of a quantifiable disease-driven selection process in a wildlife population, demonstrating the potential for infectious diseases to alter host populations. This will have direct bearing on the epidemiology, dynamics, and future trends in CWD transmission and spread. Understanding genotype-specific epidemiology will improve predictive models and inform management strategies for CWD-affected cervid populations.