Rabies is an acute viral infection that is typically fatal. Most rabies modeling has focused on disease dynamics and control within terrestrial mammals (e.g., raccoons and foxes). As such, rabies in bats has been largely neglected until recently. Because bats have been implicated as natural reservoirs for several emerging zoonotic viruses, including SARS-like corona viruses, henipaviruses, and lyssaviruses, understanding how pathogens are maintained within a population becomes vital. Unfortunately, little is known about maintenance mechanisms for any pathogen in bat populations. We present a mathematical model parameterized with unique data from an extensive study of rabies in a Colorado population of big brown bats (Eptesicus fuscus) to elucidate general maintenance mechanisms. We propose that life history patterns of many species of temperate-zone bats, coupled with sufficiently long incubation periods, allows for rabies virus maintenance. Seasonal variability in bat mortality rates, specifically low mortality during hibernation, allows long-term bat population viability. Within viable bat populations, sufficiently long incubation periods allow enough infected individuals to enter hibernation and survive until the following year, and hence avoid an epizootic fadeout of rabies virus. We hypothesize that the slowing effects of hibernation on metabolic and viral activity maintains infected individuals and their pathogens until susceptibles from the annual birth pulse become infected and continue the cycle. This research provides a context to explore similar host ecology and viral dynamics that may explain seasonal patterns and maintenance of other bat-borne diseases. chiroptera | pathogen persistence | torpor M any aspects of wildlife biology are strongly seasonal, including population dynamics of wildlife diseases (1, 2). Although mechanisms of seasonal variation of human pathogens have been well explored (3), the mechanisms for seasonality of wildlife diseases are not as well understood. Rabies virus dynamics in temperate zone bat populations exhibit a strong seasonal pattern in the number of rabies cases (Fig. 1), unlike mammalian carnivores (4). Previous analyses of bat rabies virus (BRV) using passive surveillance samples have demonstrated a higher prevalence in the spring, but especially during autumn, throughout the United States (5). However, no definitive mechanism for the seasonal pattern of rabies in bats has been described. In addition, how rabies virus is maintained within bat populations remains unclear. Here, we explore factors that drive pathogen maintenance and simultaneously explain the unique seasonal patterns of rabies in bats.Each year, rabies virus infection causes in excess of 55,000 human deaths globally, mostly from dog bites in developing countries (6). Successful vaccination programs of domesticated animals have virtually eliminated dog rabies in North America over the past 50 y, and more recent vaccination strategies for wildlife populations have controlled rabies virus in other carniv...

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size (NÌ‚) and effective sampling area (AÌ‚) are used to calculate density (DÌ‚ = NÌ‚/AÌ‚); and models applicable to sampling regimes using distance‐sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets (n = 11) were developed using nine rodent species from capture–recapture live‐trapping on both trapping grids and trapping webs in four replicate 4.2‐ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates (DÌ‚) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities (D) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web‐based uniform and half‐normal models in program DISTANCE, and the grid‐based models Mb and Mbh in program CAPTURE (with AÌ‚ adjusted by species‐specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web‐based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid‐based DÌ‚ analyses using full ...

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Populations of beaver and willow have not thrived in riparian environments that are heavily browsed by livestock or ungulates, such as elk. The interaction of beaver and elk herbivory may be an important mechanism underlying beaver and willow declines in this competitive environment. We conducted a field experiment that compared the standing crop of willow three years after simulated beaver cutting on paired plants with and without intense elk browsing (ϳ85% utilization rate). Simulated beaver cutting with intense elk browsing produced willow that was small (biomass and diameter) and short, with far fewer, but longer, shoots and a higher percentage of dead biomass. In contrast, simulated beaver cutting without elk browsing produced willow that was large, tall, and leafy, with many more, but shorter, shoots (highly branched) and a lower percentage of dead biomass. Total stem biomass after three years was 10 times greater on unbrowsed plants than on browsed plants. Unbrowsed plants recovered 84% of their pre-cut biomass after only two growing seasons, whereas browsed plants recovered only 6%. Thus, the interaction of beaver cutting and elk browsing strongly suppressed the standing crop of willow. We predict that a lack of willow suitable as winter food for beaver can cause beaver populations to decline, creating a feedback mechanism that reduces beaver and willow populations. Thus, intense herbivory by ungulates or livestock can disrupt beaver-willow mutualisms that naturally occur in less competitive environments.

Knowledge of factors influencing animal distribution and abundance is essential in many areas of ecological research, management, and policy‐making. Because common methods for modeling and estimating abundance (e.g., capture‐recapture, distance sampling) are sometimes not practical for large areas or elusive species, indices are sometimes used as surrogate measures of abundance. We present an extension of the Royle and Nichols (2003) generalization of the MacKenzie et al. (2002) site‐occupancy model that incorporates length of the sampling interval into the model for detection probability. As a result, we obtain a modeling framework that shows how useful information can be extracted from a class of index methods we call indirect detection indices (IDIs). Examples of IDIs include scent station, tracking tube, snow track, tracking plate, and hair snare surveys. Our model is maximum likelihood, and it can be used to estimate site occupancy and model factors influencing patterns of occupancy and abundance in space. Under certain circumstances, it can also be used to estimate abundance. We evaluated model properties using Monte Carlo simulations and illustrate the method with tracking tube and scent station data. We believe this model will be a useful tool for determining factors that influence animal distribution and abundance.

Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs.

Ecologists have long hypothesized that fragmentation of tropical landscapes reduces avian nest success. However, this hypothesis has not been rigorously assessed because of the difficulty of finding large numbers of well-hidden nests in tropical forests. Here we report that in the East Usambara Mountains in Tanzania, which are part of the Eastern Arc Mountains, a global biodiversity hotspot, that daily nest survival rate and nest success for seven of eight common understory bird species that we examined over a single breeding season were significantly lower in fragmented than in continuous forest, with the odds of nest failure for these seven species ranging from 1.9 to 196.8 times higher in fragmented than continuous forest. Cup-shaped nests were particularly vulnerable in fragments. We then examined over six breeding seasons and 14 study sites in a multivariable survival analysis the influence of landscape structure and nest location on daily nest survival for 13 common species representing 1,272 nests and four nest types (plate, cup, dome, and pouch). Across species and nest types, area, distance of nest to edge, and nest height had a dominant influence on daily nest survival, with area being positively related to nest survival and distance of nest to edge and nest height being both positively and negatively associated with daily nest survival. Our results indicate that multiple environmental factors contribute to reduce nest survival within a tropical understory bird community in a fragmented landscape and that maintaining large continuous forest is important for enhancing nest survival for Afrotropical understory birds.avian conservation | demography | nest predators R educed nest survivorship, due to elevated rates of nest predation, has long been hypothesized as an important contributory factor to population declines and local extinctions of birds in fragmented tropical landscapes (1, 2). Habitat fragmentation results in a reduction in area, an increase in remnant isolation, the creation of edge, and an alteration in the habitat structure of the remnants, all of which may contribute either directly or indirectly to changes in avian nest survival (3-6). Given that nearly two thirds of all bird species are endemic to the tropics (7,8) and that moist tropical forests are being lost worldwide at a rate of 0.52% annually (9), understanding the impact of habitat fragmentation on the demography of tropical birds is clearly important for avian conservation.However, because of the difficulty of finding large numbers of well-hidden nests in tropical forests (10, 11), rigorously assessing the impact of habitat fragmentation on avian nest survivorship has been challenging. Previous studies comparing avian nest survivorship between fragmented and intact forest in the tropics have either used artificial nests and eggs (12, 13), which unfortunately often poorly mimic the fate of real nests and eggs (14-16); or if real nests have been found, have lumped species together in the analysis because of small sample sizes (17),...

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