“The ocean is in constant flux,” says Santora. “The real new management challenge in this century is developing the new toolset to deal with increased climate variability, these increased predator populations, and their interactions with highly capitalized fisheries.”
In October 2019, the federal government proposed designating over 175,000 square nautical miles in the Pacific Ocean as critical humpback whale habitat. This proposal, which would require that the fishing and shipping industries mitigate their impact on whales in the area, aligns with the International Union for Conservation of Nature’s goal to protect 30 percent of the world’s oceans with marine protected areas, or MPAs, by 2030.
But MPAs have static geographic bounds. How can we protect habitats that shift with rising temperatures? How can we see changes coming, and plan conservation around them?
“That’s the million-dollar question,” says Forney. As a marine ecologist, she knows that the ocean is a dynamic place, full of moving parts. Krill, anchovies, and other forage fish move with upwelling zones, changing temperatures, and current patterns. Whales, turtles, tuna, and other pelagic species follow. A dynamic ocean, Forney says, requires dynamic management.
To put it simply, animals move. Somehow, the boundaries that protect them should move with them.
A 2015 paper in BioScience defines dynamic ocean management as “management that uses near real-time data to guide the spatial distribution of commercial activities.” Larry Crowder, a biologist at Stanford’s Hopkins Marine Station in Monterey and an author of that paper, describes it this way: Ocean models can serve like weather forecasts, telling us where species will likely migrate, and allowing us to plan our human activities accordingly.
“Pelagic organisms are highly mobile. They use whole oceans. They feed on oceanographic features that are dynamic,” says Crowder. “All the more reason to take a more dynamic approach. ” Or, to put it simply, animals move. Somehow, the boundaries that protect them should move with them.
IN 1999, CALIFORNIA LAWMAKERS passed the Marine Life Protection Act, establishing a network of MPAs extending the length of the state’s 840-mile coastline. This network would protect identified ocean features, including “rocky reefs, intertidal zones, sandy or soft ocean bottoms, underwater pinnacles, sea mounts, kelp forests, submarine canyons, and seagrass beds.” Today, over 100 MPAs offer varying levels of protection to 852 square miles of state waters. Crowder calls it “one of the most complete and thorough systems of protected areas along any coastline anywhere in the world.”
Though it largely leaves out migratory animals, the Marine Life Protection Act does consider “marine breeding and spawning grounds” as well as “current patterns” and “upwelling zones,” oceanographic features that change with the climate. But how well are these dynamic systems understood, and how could boundaries on a map contain these ever-moving parts?
These were the questions that filled the labs at Scripps Institution of Oceanography, at the University of California, San Diego, in the late 1990s. “We didn’t have all the answers, but we were trying to point to questions that should be asked,” says Forney, who was a PhD student at the historic, sun-soaked La Jolla campus, where esteemed scientists like Paul Dayton were trying to promote the value of biodiversity even in so-called “unprotected” parts of the ocean. “The escalating loss of marine life is bad enough as an ecological problem. But it constitutes an economic crisis as well,” Dayton co-wrote in 1999. Marine refuges were good. Learning how to fish, transport goods, and support ocean-based economies with fewer impacts on biodiversity would be even better.
In 2000, Forney co-published a paper with Dayton and a fellow doctoral student named David Hyrenbach that many would later consider the flagship paper on the idea of mobile MPAs. While Forney focused on marine mammals, Hyrenbach, currently a professor of oceanography at Hawai’i Pacific University, brought an expertise on seabirds — animals that truly know no human-set boundaries. Arctic terns, for instance, have the longest migration of any other animal on Earth, traveling from pole to pole, roundtrip, each year. Black-footed albatrosses fly from the Hawaiian Islands to forage across the North Pacific. Their migration is dictated by the shifting North Pacific Transition Zone, an oceanic front that serves as a buffet line for pelagic species.
Hyrenbach, Forney, and Dayton’s paper outlined the truth of pelagic species: Their habitats are “neither fixed nor predictable,” and protecting them “will require dynamic MPAs” that move with oceanographic conditions. These mobile MPAs would be especially important in areas that attract economically significant fisheries. In the North Pacific, for instance, albatrosses and turtles are often killed by longlines targeting albacore tuna. Eliminating the fishery wouldn’t be economically feasible, even if it were the best thing for wildlife. Somehow, the authors suggested, dynamic MPAs would have to predict the unpredictable.
“[The paper] was ahead of its time,” says Forney. “We didn’t have the tools or technology, or the ecological understanding of some species, to make it happen.” She knew that mobile MPAs would require extensive wildlife surveys, sophisticated models, the computer capacity to put it all together, and the communicative channels to inform shipping regulators and fisheries managers. These existed only in part in 2000.
THE MOBILE MPA CONCEPT didn’t have to travel far in Forney’s network to be realized. Alistair Hobday — a former Stanford water-polo player — is credited by his colleagues with developing the first mobile MPA off the coast of New South Wales in his native Australia to save critically endangered southern bluefin tuna from longline bycatch.
Hobday, who was Forney’s classmate at Scripps, studies bluefin tuna for the Commonwealth Scientific and Industrial Research Organisation, Australia’s federal science agency. At eight feet long, these fish are big enough to outfit with fist-sized electronic tags. Hobday was able to see where tuna spent every day of their lives, from breeding areas in the Indian Ocean to their migration through the Great Australian Bight and the Tasman Sea.
In 1997, NASA began compiling information on chlorophyll and sea temperature through a satellite sensor called SeaWiFS, short for Sea-Viewing Wide Field-of-View Sensor. Hobday calls this dataset and others like it “breakthroughs” for ocean conservation. Starting then, oceanographers could look at shifting ecosystems on real-time, color-coded maps. Hobday matched these models with his tracking data like “a jigsaw puzzle” to see how tuna move with these shifts. “We had the ocean models for that region, a big enough fish, and data on that fish — all the pieces to make it work,” he says. In 2003, Hobday started sending twice-monthly coordinates to the fisheries managers, who set up regulatory no-fishing zones accordingly.
Other examples soon followed. In 2006, NOAA released the first version of TurtleWatch, a constantly updated map showing the thermal habitat of loggerhead turtles north of Hawai’i. This map was then sent to fisheries managers as a voluntary tool to avoid bycatch in the longline swordfish fishery. In 2015, scientists expanded the tool to include leatherback turtles. Another NOAA project called WhaleWatch uses historic tracking data for endangered blue whales to prevent ship strikes near the Port of Los Angeles and San Francisco Bay. In Delaware Bay, the Atlantic Sturgeon Risk Model matches historic telemetry data with conditions models to make three-day forecasts on the location of the endangered anadromous giants. And last year, Crowder began installing satellite tags on blue marlin and sailfish off the coast of Costa Rica to kickstart a project called DynaMar, which would help fishers prevent reaching bycatch quotas and prematurely shutting down their fisheries.