Collaborative Research: Harvesting Long-term Survey Data to Develop Zooplankton Distribution Models for the Antarctic Peninsula

Macrozooplankton are key contributors to marine ecosystem function, and combining empirical sampling and modeling will enable prediction of changing distribution patterns. Challenges in understanding alterations in distributions of these organisms are magnified in the Antarctic Peninsula (AP) ecosystem where ocean warming and sea-ice decline are assumed to drive range shifts in dominant taxa (e.g., krill, pteropods and salps), but functional relationships between zooplankton species distributions and environmental conditions remain uncertain. Therefore, we propose to leverage three decades of zooplankton abundance data and predator (seabird, whale and seal) sighting data from two main longterm survey programs to develop and evaluate predictive Zooplankton Distribution Models (ZDMs) along the AP (at least 60° S to 70° S, ~400,000 km2). To do this, we will adapt a successful machine learning modeling approach from the California Current ecosystem that utilizes bathymetric and oceanographic data to predict zooplankton species distributions. Our main outputs will be 1) a description of species spatiotemporal trends and abundance patterns, 2) a summary of overlap in zooplankton species and predator species distributions, and 3) the creation of a zooplankton mapping tool allowing for public viewing of past and future ZDM predictions.