ABSTRACT
Marine heatwaves cause widespread environmental, biological, and socio-economic impacts, placing them at the forefront of 21st-century management challenges. However, heatwaves vary in intensity and evolution, and a paucity of information on how this variability impacts marine species limits our ability to proactively manage for these extreme events. Here, we model the effects of four recent heatwaves (2014, 2015, 2019, 2020) in the Northeastern Pacific on the distributions of 14 top predator species of ecological, cultural, and commercial importance. Predicted responses were highly variable across species and heatwaves, ranging from near total loss of habitat to a two-fold increase. Heatwaves rapidly altered political bio-geographies, with up to 10% of predicted habitat across all species shifting jurisdictions during individual heatwaves. The variability in predicted responses across species and heatwaves portends the need for novel management solutions that can rapidly respond to extreme climate events. As proof-of-concept, we developed an operational dynamic ocean management tool that predicts predator distributions and responses to extreme conditions in near real-time.
Subject(s)
Climate , GeographyABSTRACT
The California Current Trophic Database (CCTD) was developed at NOAA Southwest Fisheries Science Center in collaboration with numerous diet data contributors. We compiled the CCTD from twenty-four data sets, representing both systematic collections and directed trophic studies. Diet composition data, including stomach and scat samples, were obtained from 105,694 individual predators among 143 taxa collected throughout the California Current Large Marine Ecosystem (CCLME) from 1967-2019. Predator taxa consist of squids (n = 5), elasmobranchs (n = 13), bony fishes (n = 118), and marine mammals (n = 7). Extensive time series are available for some predators (e.g., California Sea Lion, Pacific Hake, Chinook Salmon). The CCTD represents the largest compilation of raw trophic data within the CCLME, allowing for more refined analyses and modeling studies within this region. Our intention is to further augment and periodically update the dataset as additional historical or contemporary data become available to increase its utility and impact.