Studies of infectious disease ecology often rely heavily on knowing when individuals were infected, but estimating this time of infection can be challenging, especially in wildlife. Time of infection can be estimated from various types of data, with antibody level data being one of the most promising sources of information. The use of antibody levels to back-calculate infection time requires the development of a host-pathogen system-specific model of antibody dynamics, and a leading challenge in such quantitative serology approaches is how to model antibody dynamics in the absence of experimental infection data. Here, we present a way to do this in a Bayesian framework that facilitates the incorporation of all available information about potential infection times. We apply the model to estimate infection times of Channel Island foxes infected with Leptospira interrogans, leading to reductions of 51-92% in the window of possible infection times. Using simulated data, we show that the approach works well across a broad range of parameter settings and can lead to major improvements of infection time estimates that depend on system characteristics such as antibody decay rate and variation in peak antibody levels after exposure. The method substantially simplifies the challenge of modeling antibody dynamics in the absence of individuals with known infection times, opens up new opportunities in wildlife disease ecology, and can even be applied to cross-sectional data once the model is trained.
The coastal zone provides foraging opportunities for insular populations of terrestrial mammals, allowing for expanded habitat use, increased dietary breadth, and locally higher population densities. We examined the use of sandy beach resources by the threatened island fox (Urocyon littoralis) on the California Channel Islands using scat analysis, surveys of potential prey, beach habitat attributes, and stable isotope analysis. Consumption of beach invertebrates, primarily intertidal talitrid amphipods (Megalorchestia spp.) by island fox varied with abundance of these prey across sites. Distance-based linear modeling revealed that abundance of giant kelp (Macrocystis pyrifera) wrack, rather than beach physical attributes, explained the largest amount of variation in talitrid amphipod abundance and biomass across beaches. δ13C and δ15N values of fox whisker (vibrissae) segments suggested individualism in diet, with generally low δ13C and δ15N values of some foxes consistent with specializing on primarily terrestrial foods, contrasting with the higher isotope values of other individuals that suggested a sustained use of sandy beach resources, the importance of which varied over time. Abundant allochthonous marine resources on beaches, including inputs of giant kelp, may expand habitat use and diet breadth of the island fox, increasing population resilience during declines in terrestrial resources associated with climate variability and long-term climate change.
The island fox (Urocyon littoralis) is native to 6 of the 8 Channel Islands of California, USA. The species experienced a population decline in the 1990s but recovered after predatory golden eagles (Aquila chrysaetos) were relocated and feral pigs (Sus scrofa), a main food source for the eagles, were removed. As part of an ongoing conservation program, the National Park Service conducts yearly health surveys on foxes residing on Santa Rosa and San Miguel islands. In this study, we document non‐invasive measures of stress and nutritional status from fecal samples collected during surveys from 2009 to 2015. We collected samples defecated in traps overnight or during handling and measured concentrations of glucocorticoid (GC) and triiodothyronine (T3) metabolites using validated assays. We used generalized linear mixed models to assess the relationships between hormones, season, island, age class, sex, body condition, reproductive status, and ectoparasite presence. Overall, males had marginally lower fecal T3 concentrations than females. Concentrations of both hormones positively correlated with body condition. Fecal GC production varied seasonally; concentrations were highest from December to February and declined through the summer and fall. During summer, younger females and those with signs of recent reproduction had higher fecal GC concentrations than older females or those without evidence of reproduction. Fecal T3 concentrations did not vary in relation to season, age, or reproductive status, but on San Miguel Island were positively correlated with ectoparasite presence. There were no other significant differences between islands. Our results provide hormone data for island foxes and demonstrate that production varies in relation to seasonal and biological factors. These reference data will serve as a comparison for future health surveys and allow managers to identify factors associated with increased stress or reduced nutritional state. © 2019 The Wildlife Society.
Background: Despite significant advances in statistical approaches and data collection for analyzing wildlife movements over the last 50 years, there are limited analytical frameworks to be applied when spatial data are collected for purposes other than analyzing movement. Data collected for other purposes (e.g., sporadic captures or survival checks via telemetry) generally have lower temporal frequency or spatial precision than data collected to analyze fine-scale animal movement. The coarseness of the former renders them poorly suited for analysis using existing statistical tools. Methods: We propose a new way of estimating animal movement trajectories by integrating variable quality location data – including frequent but spatially coarse, irregularly-shaped polygon location data arising from VHF telemetry as well as less frequent, more spatially precise location data – using functional data analysis combined with a spatial resampling algorithm. We apply this method to analyze location data from the reintroduced Channel Island fox (Urocyon littoralis) subspecies population on Santa Rosa Island, California, which were collected from 2003-2012 for purposes other than movement analyses but provide an ideal case study to develop and test these novel methods. Results: By combining coarse-grained location knowledge, obtained through field notes and expert interpretation, with more precise location data, we reconstructed individual animal movement trajectories and demonstrated the utility of combining such data. Through the population ensemble of reconstructed trajectories, we learned that captive-born Channel Island foxes exhibited stronger seasonal movements than wild-born foxes, and most long-range movements occurred within the first two years of a fox’s time on the island. Conclusions: This methodology capitalizes on frequently overlooked but valuable spatial data, often found in field notes and expert knowledge, to reconstruct animal movements. Our approach has wide application to systems in which data of variable quality are collected for purposes other than studying movement and could have beneficial applications in species conservation, landscape ecology, disease management, and population monitoring.
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