The study of the spatial distribution of marine species has traditionally relied on single-species distribution models (SDMs), which implicitly assume independence among taxa. However, marine species evolve within structured communities whose dynamics are governed by complex biotic interactions. To account for this complexity, we use joint species distribution models (JSDMs) to model the...
Oyster populations in Chesapeake Bay in the eastern United States have dropped to a few percent of historic levels. Restoration requires building artificial reefs as substrate for oysters to grow on. I will present a metapopulation model for oyster reefs that are coupled by transport of larvae. The model consists of ordinary differential equations for juveniles, adults, dead shell/reef...
This talk focuses on the use of cubical homology and topological persistence as a framework for pattern quantification and image processing. As illustration, we will discuss a study that applies these methods to noisy spatial population data generated by a coupled-patch model to mimic grey scale satellite images of vegetation. Early work shows promise in detecting early warning signals of...
Populations globally are experiencing undue stress due to climate change, habitat destruction and overharvesting. Predicting impending dynamical change or collapse is challenging due to the complex spatiotemporal dynamics natural populations display and the difficulty in obtaining ecological time series. When we explicitly consider a population’s distribution over space, we can quantify...
Explicit consideration of a population's distribution across space introduces added complexity to modeling and data analysis. However, explicit consideration of spatial distribution is important for many ecological processes such as dispersal, invasion, and resilience. Here, we highlight research studying population distributions and patterns with differing techniques to answer a range of...
