Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models.

Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics. We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth. We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction. Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%. Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.

How sure are you? A web-based application to confront imperfect detection of respiratory pathogens in bighorn sheep.

The relationships between host-pathogen population dynamics in wildlife are poorly understood. An impediment to progress in understanding these relationships is imperfect detection of diagnostic tests used to detect pathogens. If ignored, imperfect detection precludes accurate assessment of pathogen presence and prevalence, foundational parameters for deciphering host-pathogen dynamics and disease etiology. Respiratory disease in bighorn sheep (Ovis canadensis) is a significant impediment to their conservation and restoration, and effective management requires a better understanding of the structure of the pathogen communities. Our primary objective was to develop an easy-to-use and accessible web-based Shiny application that estimates the probability (with associated uncertainty) that a respiratory pathogen is present in a herd and its prevalence given imperfect detection. Our application combines the best-available information on the probabilities of detection for various respiratory pathogen diagnostic protocols with a hierarchical Bayesian model of pathogen prevalence. We demonstrated this application using four examples of diagnostic tests from three herds of bighorn sheep in Montana. For instance, one population with no detections of Mycoplasma ovipneumoniae (PCR assay) still had an 6% probability of the pathogen being present in the herd. Similarly, the apparent prevalence (0.32) of M. ovipneumoniae in another herd was a substantial underestimate of estimated true prevalence (0.46: 95% CI = [0.25, 0.71]). The negative bias of naïve prevalence increased as the probability of detection of testing protocols worsened such that the apparent prevalence of Mannheimia haemolytica (culture assay) in a herd (0.24) was less than one third that of estimated true prevalence (0.78: 95% CI = [0.43, 0.99]). We found a small difference in the estimates of the probability that Mannheimia spp. (culture assay) was present in one herd between the binomial sampling approach (0.24) and the hypergeometric approach (0.22). Ignoring the implications of imperfect detection and sampling variation for assessing pathogen communities in bighorn sheep can result in spurious inference on pathogen presence and prevalence, and potentially poorly informed management decisions. Our Shiny application makes the rigorous assessment of pathogen presence, prevalence and uncertainty straightforward, and we suggest it should be incorporated into a new paradigm of disease monitoring.

An improved understanding of ungulate population dynamics using count data: Insights from western Montana.

Understanding the dynamics of ungulate populations is critical given their ecological and economic importance. In particular, the ability to evaluate the evidence for potential drivers of variation in population trajectories is important for informed management. However, the use of age ratio data (e.g., juveniles:adult females) as an index of variation in population dynamics is hindered by a lack of statistical power and difficult interpretation. Here, we show that the use of a population model based on count, classification and harvest data can dramatically improve the understanding of ungulate population dynamics by: 1) providing estimates of vital rates (e.g., per capita recruitment and population growth) that are easier to interpret and more useful to managers than age ratios and 2) increasing the power to assess potential sources of variation in key vital rates. We used a time series of elk (Cervus canadensis) spring count and classification data (2004 to 2016) and fall harvest data from hunting districts in western Montana to construct a population model to estimate vital rates and assess evidence for an association between a series of environmental covariates and indices of predator abundance on per capita recruitment rates of elk calves. Our results suggest that per capita recruitment rates were negatively associated with cold and wet springs, and severe winters, and positively associated with summer precipitation. In contrast, an analysis of the raw age ratio data failed to detect these relationships. Our approach based on a population model provided estimates of the region-wide mean per capita recruitment rate (mean = 0.25, 90% CI = 0.21, 0.29), temporal variation in hunting-district-specific recruitment rates (minimum = 0.09; 90% CI = [0.07, 0.11], maximum = 0.43; 90% CI = [0.38, 0.48]), and annual population growth rates (minimum = 0.83; 90% CI = [0.78, 0.87], maximum = 1.20; 90% CI = [1.11, 1.29]). We recommend using routinely collected population count and classification data and a population modeling approach rather than interpreting estimated age ratios as a substantial improvement in understanding population dynamics.

Simulation-based validation of spatial capture-recapture models: A case study using mountain lions.

Spatial capture-recapture (SCR) models have improved the ability to estimate densities of rare and elusive animals. However, SCR models have seldom been validated even as model formulations diversify and expand to incorporate new sampling methods and/or additional sources of information on model parameters. Information on the relationship between encounter probabilities, sources of additional information, and the reliability of density estimates, is rare but crucial to assessing reliability of SCR-based estimates. We used a simulation-based approach that incorporated prior empirical work to assess the accuracy and precision of density estimates from SCR models using spatially unstructured sampling. To assess the consequences of sparse data and potential sources of bias, we simulated data under six scenarios corresponding to three different levels of search effort and two levels of correlation between search effort and animal density. We then estimated density for each scenario using four models that included increasing amounts of information from harvested individuals and telemetry to evaluate the impact of additional sources of information. Model results were sensitive to the quantity of available information: density estimates based on low search effort were biased high and imprecise, whereas estimates based on high search effort were unbiased and precise. A correlation between search effort and animal density resulted in a positive bias in density estimates, though the bias decreased with increasingly informative datasets. Adding information from harvested individuals and telemetered individuals improved density estimates based on low and moderate effort but had negligible impact for datasets resulting from high effort. We demonstrated that density estimates from SCR models using spatially unstructured sampling are reliable when sufficient information is provided. Accurate density estimates can result if empirical-based simulations such as those presented here are used to develop study designs with appropriate amounts of effort and information sources.

Respiratory pathogens and their association with population performance in Montana and Wyoming bighorn sheep populations.

Respiratory disease caused by Mycoplasma ovipneumoniae and Pasteurellaceae poses a formidable challenge for bighorn sheep (Ovis canadensis) conservation. All-age epizootics can cause 10-90% mortality and are typically followed by multiple years of enzootic disease in lambs that hinders post-epizootic recovery of populations. The relative frequencies at which these epizootics are caused by the introduction of novel pathogens or expression of historic pathogens that have become resident in the populations is unknown. Our primary objectives were to determine how commonly the pathogens associated with respiratory disease are hosted by bighorn sheep populations and assess demographic characteristics of populations with respect to the presence of different pathogens. We sampled 22 bighorn sheep populations across Montana and Wyoming, USA for Mycoplasma ovipneumoniae and Pasteurellaceae and used data from management agencies to characterize the disease history and demographics of these populations. We tested for associations between lamb:ewe ratios and the presence of different respiratory pathogen species. All study populations hosted Pasteurellaceae and 17 (77%) hosted Mycoplasma ovipneumoniae. Average lamb:ewe ratios for individual populations where both Mycoplasma ovipneumoniae and Pasteurellaceae were detected ranged from 0.14 to 0.40. However, average lamb:ewe ratios were higher in populations where Mycoplasma ovipneumoniae was not detected (0.37, 95% CI: 0.27-0.51) than in populations where it was detected (0.25, 95% CI: 0.21-0.30). These findings suggest that respiratory pathogens are commonly hosted by bighorn sheep populations and often reduce recruitment rates; however ecological factors may interact with the pathogens to determine population-level effects. Elucidation of such factors could provide insights for management approaches that alleviate the effects of respiratory pathogens in bighorn sheep. Nevertheless, minimizing the introduction of novel pathogens from domestic sheep and goats remains imperative to bighorn sheep conservation.

Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity.

Variation in life-history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among-individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness-related traits among otherwise-identical individuals. An improved understanding of life-history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33-yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among-individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non-breeders. We detected age-related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life-history traits. We found that among-individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life-history theory, is the first to provide a thorough assessment of variation in important vital rates for a long-lived, high-latitude marine mammal while taking full advantage of recent developments in model evaluation.

Assessing respiratory pathogen communities in bighorn sheep populations: Sampling realities, challenges, and improvements.

Respiratory disease has been a persistent problem for the recovery of bighorn sheep (Ovis canadensis), but has uncertain etiology. The disease has been attributed to several bacterial pathogens including Mycoplasma ovipneumoniae and Pasteurellaceae pathogens belonging to the Mannheimia, Bibersteinia, and Pasteurella genera. We estimated detection probability for these pathogens using protocols with diagnostic tests offered by a fee-for-service laboratory and not offered by a fee-for-service laboratory. We conducted 2861 diagnostic tests on swab samples collected from 476 bighorn sheep captured across Montana and Wyoming to gain inferences regarding detection probability, pathogen prevalence, and the power of different sampling methodologies to detect pathogens in bighorn sheep populations. Estimated detection probability using fee-for-service protocols was less than 0.50 for all Pasteurellaceae and 0.73 for Mycoplasma ovipneumoniae. Non-fee-for-service Pasteurellaceae protocols had higher detection probabilities, but no single protocol increased detection probability of all Pasteurellaceae pathogens to greater than 0.50. At least one protocol resulted in an estimated detection probability of 0.80 for each pathogen except Mannheimia haemolytica, for which the highest detection probability was 0.45. In general, the power to detect Pasteurellaceae pathogens at low prevalence in populations was low unless many animals were sampled or replicate samples were collected per animal. Imperfect detection also resulted in low precision when estimating prevalence for any pathogen. Low and variable detection probabilities for respiratory pathogens using live-sampling protocols may lead to inaccurate conclusions regarding pathogen community dynamics and causes of bighorn sheep respiratory disease epizootics. We recommend that agencies collect multiples samples per animal for Pasteurellaceae detection, and one sample for Mycoplasma ovipneumoniae detection from at least 30 individuals to reliably detect both Pasteurellaceae and Mycoplasma ovipneumoniae at the population-level. Availability of PCR diagnostic tests to wildlife management agencies would improve the ability to reliably detect Pasteurellaceae in bighorn sheep populations.

Birth dates vary with fixed and dynamic maternal features, offspring sex, and extreme climatic events in a high-latitude marine mammal.

Reproductive synchrony tends to be widespread in diverse species of plants and animals, especially at higher latitudes. However, for long-lived mammals, birth dates for different individuals can vary by weeks within a population. A mother's birth timing can reveal useful information about her reproductive abilities and have important implications for the characteristics and survival of her offspring. Despite this, our current knowledge of factors associated with variation in birth dates is modest. We used long-term data for known-age Weddell seals in Antarctica and a Bayesian hierarchical modeling approach to study how birth dates varied with fixed and temporally varying features of mothers, whether sex allocation varied with birth timing, and annual variation in birth dates. Based on birth dates for 4465 pups born to 1117 mothers aged 4-31, we found that diverse features of mothers were associated with variation in birth dates. Maternal identity was the most important among these. Unlike most studies, which have reported that birth dates occur earlier as mothers age, we found that birth dates progressively occurred earlier in the year in the early part of a mother's reproductive life, reached a minimum at age 16, and then occurred later at later ages. Birth dates were positively related to a mother's age at primiparity and recent reproductive effort. The earliest birth dates were for pups born to prime-age mothers who did not reproduce in the previous year but began reproduction early in life, suggesting that females in the best condition gave birth earlier than others. If so, our finding that male pups tended to be born earlier than females provides support for the Trivers-Willard sex-allocation model. Average birth dates were quite consistent across years, except for 2 years that had notable delays and occurred during the period when massive icebergs were present and disrupted the ecosystem.

Tight coupling of primary production and marine mammal reproduction in the Southern Ocean.

Polynyas are areas of open water surrounded by sea ice and are important sources of primary production in high-latitude marine ecosystems. The magnitude of annual primary production in polynyas is controlled by the amount of exposure to solar radiation and sensitivity to changes in sea-ice extent. The degree of coupling between primary production and production by upper trophic-level consumers in these environments is not well understood, which prevents reliable predictions about population trajectories for species at higher trophic levels under potential future climate scenarios. In this study, we find a strong, positive relationship between annual primary production in an Antarctic polynya and pup production by ice-dependent Weddell seals. The timing of the relationship suggests reproductive effort increases to take advantage of high primary production occurring in the months after the birth pulse. Though the proximate causal mechanism is unknown, our results indicate tight coupling between organisms at disparate trophic levels on a short timescale, deepen our understanding of marine ecosystem processes, and raise interesting questions about why such coupling exists and what implications it has for understanding high-latitude ecosystems.