The accelerated pace of climate-driven shifts is surpassing the temporal scope of conventional field research, potentially leading to a disconnect between ecosystem changes and scientific data collection. Climate change is producing rapid transformations within dynamic marine ecosystems, with a pronounced effect on high trophic-level species such as loggerhead sea turtles (Caretta caretta). We present a new model for data collection using ethnobiological methods, emphasizing how local community members can contribute to expanding scientific knowledge via context-informed observations, to document species occurrences beyond their anticipated habitats during climatic anomalies. In rapidly changing conditions, local expert knowledge can complement conventional scientific methods, providing high-quality data with extensive coverage—especially for elusive species—and yielding insight into potential emerging phenomena that may otherwise go unnoticed. Conventional methods for predicting distribution shifts in rare species are vulnerable to spatial biases, favoring predictions based on the most probable habitats. We present the case study of a live sea turtle sighting by a local expert in Monterey Bay, California, USA, identified post hoc as a loggerhead, to illustrate methods which can be transferred and applied to other rare and highly migratory marine species such as marine mammals, sharks, and seabirds. This emerging framework incorporates diverse knowledge sources and methodologies in monitoring climate-driven ecological shifts, enriching conservation strategies, enhancing our understanding of complex ecosystems, and contributing to robust evidentiary standards for rare species observations.