On behalf of my co-authors, I'm happy to announce that our new paper on joint spatial modeling has just been published. Bokgyeong Kang, Erin M Schliep, Alan E Gelfand, Christopher W Clark, Christine A Hudak, Charles A Mayo, Ryan Schosberg, Tina M Yack, Robert S Schick, Joint spatiotemporal modelling of zooplankton and whale abundance in a dynamic marine environment, Journal of the Royal Statistical Society Series C: Applied Statistics, 2025;, qlaf038, https://doi.org/10.1093/jrsssc/qlaf038 Abstract North Atlantic right whales are an endangered species. Their entire population is estimated to be 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 modelling (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 the 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 linked through a latent conditional-marginal specification. Furthermore, each species has two data sources informing its respective distribution, necessitating a novel data fusion approach. The result is a complex multi-level model. Through simulation, we demonstrate that our joint specification effectively identifies model unknowns and improves the estimation of species distributions compared to modelling them separately. We then apply our model to real data from Cape Cod Bay, Massachusetts, USA. Keywords: data fusion, geostatistical model, hierarchical model, joint species distribution, measurement error, point pattern data Rob Schick, PhD Senior Scientist Southall Environmental Associates, Inc.