Is the local environment more important than within-host interactions in determining coinfection?

Host populations often vary in the magnitude of coinfection they experience across environmental gradients. Furthermore, coinfection often occurs sequentially, with a second parasite infecting the host after the first has established a primary infection. Because the local environment and interactions between coinfecting parasites can both drive patterns of coinfection, it is important to disentangle the relative contributions of environmental factors and within-host interactions to patterns of coinfection.

A framework for linking competitor ecological differences to coexistence.

Not all ecological differences among competing species affect their ability to locally coexist. Rather, the differences that promote stable coexistence can be those which cause each species to experience stronger intraspecific than interspecific competition. Recent approaches have established how to detect the demographic signature of these competitive effects, but alone they cannot elucidate the ecological differences among species that yield these patterns.

Large-scale probabilistic identification of boreal peatlands using Google Earth Engine, open-access satellite data, and machine learning.

Freely-available satellite data streams and the ability to process these data on cloud-computing platforms such as Google Earth Engine have made frequent, large-scale landcover mapping at high resolution a real possibility. In this paper we apply these technologies, along with machine learning, to the mapping of peatlands-a landcover class that is critical for preserving biodiversity, helping to address climate change impacts, and providing ecosystem services, e.g.

Monitoring butterfly abundance: beyond Pollard walks.

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.

Sociality, density-dependence and microclimates determine the persistence of populations suffering from a novel fungal disease, white-nose syndrome.

Disease has caused striking declines in wildlife and threatens numerous species with extinction. Theory suggests that the ecology and density-dependence of transmission dynamics can determine the probability of disease-caused extinction, but few empirical studies have simultaneously examined multiple factors influencing disease impact. We show, in hibernating bats infected with Geomyces destructans, that impacts of disease on solitary species were lower in smaller populations, whereas in socially gregarious species declines were equally severe in populations spanning four orders of magnitude.