09/29/2026
Join us tonight for our monthly club meeting! We start at 6:30pm Brass Bear Brewing Uptown, but stop by early to socialize and buy raffle tickets. We have a great raffle today, including a brand new dive computer and light donated by Douglas Klug and a great selection of diving books 🔦📚
ALSO Club Board elections are today! Come to vote or to throw your hat in the ring to help shape the future of the club!
After the elections we’ll have a talk from Dr. Scott Gabara, ecologist at the Channel Islands National Park. Scott will talk about the Channel Islands Kelp Forest Monitoring Program and diving our local National Marine Sanctuary.
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Scott holds a bachelor’s in marine ecology from UC Santa Cruz, a Masters in Marine Science from Moss Landing Marine laboratory through San Jose State, a joint doctorate in ecology with San Diego State University and UC Davis, and has postdoctoral experience working on glacial melt with the University of Alaska Fairbanks based in Juneau, Alaska. He has been leading the Channel Islands National Park kelp forest monitoring program for the past four years. He enjoys underwater photography (check out his photos at scottgabara.weebly.com!) and the ability to share organisms and environments that many folks may not be able to experience and appreciate.
More on the talk: The Kelp Forest Monitoring Program was established by Channel Islands National Park in 1982 to collect baseline information about the kelp forest ecosystem in the Park. Each year the program collects size and abundance data for 70 categories (taxa) of algae, invertebrates, and fish that are indicators of ecosystem health. The current monitoring protocol was adopted in 1997. Scott will explain the back story that motivates the need for baseline ecological data. He will describe the creation of the kelp forest monitoring program, the methods for data collection, and some recent results. By sharing photos, videos, and data from the program, Scott will share the current condition of kelp forests and what we can learn from long term data.
