Joint Spatiotemporal Modeling of Zooplankton and Whale Abundance in a Dynamic Marine Environment

TL;DR

This paper develops a novel joint spatiotemporal modeling framework to simultaneously study the distributions of zooplankton and North Atlantic right whales, incorporating data fusion and complex multi-level structures to improve understanding of their dynamic interactions.

Contribution

It introduces a unique joint species distribution model combining geostatistical and point pattern models with data fusion, tailored for dynamic marine environments.

Findings

Model effectively identifies species distribution patterns.

Joint modeling improves inference over separate models.

Application to real data demonstrates practical utility.

Abstract

North Atlantic right whales are an endangered species; their entire population numbers approximately 372 individuals, and they are subject to major anthropogenic threats. They feed on zooplankton species whose distribution shifts in a dynamic and warming oceanic environment. Because right whales in turn follow their shifting food resource, it is necessary to jointly study the distribution of whales and their prey. The innovative joint species distribution modeling (JSDM) contribution here is different from anything in the large JDSM literature, reflecting the processes and data we have to work with. Specifically, our JSDM supplies a geostatistical model for expected amount of zooplankton collected at a site. We require a point pattern model for the intensity of right whale abundance. The two process models are joined through a latent conditional-marginal specification. Further, each species has two data sources to inform their respective distributions and these sources require novel data fusion. What emerges is a complex multi-level model. Through simulation we demonstrate the ability of our joint specification to identify model unknowns and learn better about the species distributions than modeling them individually. We then apply our modeling to real data from Cape Cod Bay, Massachusetts in the U.S.