My co-authors and I are pleased to share our latest publication from our use of gliders to explore whale habitat: _Remote sensing and mapping habitat features pertinent to fin whale life histories in coastal and offshore waters of Vancouver Island, British Columbia_ Journal of Experimental Marine Biology and Ecology 537, 151511 Abstract: Current knowledge of the population size and movement of fin whales in the northeast Pacific is lacking, but is critical in implementing effective management actions. Here we used ocean gliders to survey the deep-coastal and offshore waters of Vancouver Island to add to what is known about fin whale habitat use in the Canadian Pacific. Passive acoustic recordings were made continuously, from which fin whale vocalizations were used as a proxy to presence. Oceanographic and preyscape variables were also taken to better delineate habitat units in horizontal and vertical space. Comparisons were made between on-shelf and shelf-break zones, and measures taken in- and out-side submarine canyons. Temporal comparisons between winter and spring were also possible. An on-shelf and shelf-break divide was seen, with cooler, fresher waters present closer to the coast for both deployments. The spring deployment showed fin whale acoustic presence focused around topographical features, including the shelf-break and canyons. The most prevalent cue was their 40-Hz call, which suggests foraging. Echosounder readings suggested denser aggregations of larger bodied zooplankton prey were present at canyon heads and along the shelf break. During the winter, calls in the acoustic record were more numerous than in the spring, and dominated by the 20-Hz call. A proportion of the recordings also showed 'song' patterning, which suggests breeding activity. Interpolated surfaces were used to examine the spatiotemporal relationships between the high-resolution habitat point data and presence of far-propagating fin whale calls. The predicted use of habitat by fin whales, as represented by their calls, was examined through Random Forest machine learning models using oceanographic and preyscape measures as input variables from these interpolations. Distance from the shelf break and preyscape variables were determined important in predicting whale habitat use in the spring, with model accuracy exceeding 80%. Call presence showed a much weaker relationship to environmental var-iables for the winter recordings with reduced accuracy of model predictions (13%). An understanding of habitat selection by fin whales may also aid in determining the importance of habitat units and areas that may critical to life history functions. The paper is free to read/download from JEMBE online at https://authors.elsevier.com/a/1cThA51aUfmHA [1] until March 16, 2021 Please feel free to contact me if you have questions, or for a PDF after that time Best, Rianna Burnham, PhD Links: ------ [1] https://authors.elsevier.com/a/1cThA51aUfmHA