Biology subjects

Joseph, M. B.

Publications and source records attributed to Joseph, M. B..

3 recordsLinked to original sources

bioRxiv2018

Untangling the dynamics of persistence and colonization in microbial communities

A central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here we introduce a dynamic statistical model that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data. We separate the fixed pairwise effects of species occurrences on persistence and colonization rates, a potential signal of direct interactions, from latent pairwise correlations in occurrence, a potential signal of shared environmental responses. We apply our modeling approach to a pressing epidemiological question by examining how human papillomavirus (HPV) types coexist. Our results suggest that while HPV types respond similarly to common host traits, direct interactions are sparse and weak, so that HPV type diversity depends largely on shared environmental drivers. Our modeling approach is widely applicable to microbial communities and provides valuable insights that should lead to more directed hypothesis testing and mechanistic modeling.

ecology↗

bioRxiv2018

Understanding and predicting extreme wildfires in the contiguous United States

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30 year wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes.

ecology↗

bioRxiv2018

Disease and climate effects on individuals jointly drive post-reintroduction population dynamics of an endangered amphibian

The emergence of novel pathogens often has dramatic negative effects on previously unexposed host populations. Subsequent disease can drive populations and even species to extinction. After establishment in populations, pathogens can continue to affect host dynamics, influencing the success or failure of species recovery efforts. However, quantifying the effect of pathogens on host populations in the wild is challenging because individual hosts and their pathogens are difficult to observe. Here we use long-term mark-recapture data to describe the dynamics of reintroduced populations of an endangered amphibian (Rana sierrae) and evaluate the success of these recovery efforts in the presence of a recently-emerged pathogen, the amphibian chytrid fungus Batrachochytrium dendrobatidis. We find that high B. dendrobatidis infection intensities are associated with increases in detectability, reductions in survival, and more infected adults. We also find evidence for intensity-dependent survival, with heavily infected individuals suffering higher mortality. These results highlight the need in disease ecology for probabilistic approaches that account for uncertainty in infection intensity using imperfect observational data. Such approaches can advance the understanding of disease impacts on host population dynamics, and in the current study will improve the effectiveness of species conservation actions.

ecology↗