• Energy Research

Carbon emissions and their ocean impacts Anthropogenic CO 2 emissions directly affect atmospheric chemistry but also have a strong influence on the oceans. Gattuso et al. review how the physics, chemistry, and ecology of the oceans might be affected based on two CO 2 emission trajectories: one business as usual and one with aggressive reductions. Ocean warming, acidification, sea-level rise, and the expansion of oxygen minimum zones will continue to have distinct impacts on marine communities and ecosystems. The path that humanity takes regarding CO 2 emissions will largely determine the severity of these phenomena. Science , this issue 10.1126/science.aac4722

Carbon emissions and their ocean impacts Anthropogenic CO 2 emissions directly affect atmospheric chemistry but also have a strong influence on the oceans. Gattuso et al. review how the physics, chemistry, and ecology of the oceans might be affected based on two CO 2 emission trajectories: one business as usual and one with aggressive reductions. Ocean warming, acidification, sea-level rise, and the expansion of oxygen minimum zones will continue to have distinct impacts on marine communities and ecosystems. The path that humanity takes regarding CO 2 emissions will largely determine the severity of these phenomena. Science , this issue 10.1126/science.aac4722

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefiting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystemrelevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefiting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystemrelevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

2014 marked the sixth and most widespread mass bleaching event reported in the Northwestern Hawaiian Islands, home to the Papahānaumokuākea Marine National Monument (PMNM), the world's second largest marine reserve. This event was associated with an unusual basin-scale warming in the North Pacific Ocean, with an unprecedented peak intensity of around 20°C-weeks of cumulative heat stress at Lisianksi Island. In situ bleaching surveys and satellite data were used to evaluate the relative importance of potential drivers of bleaching patterns in 2014, assess the subsequent morality and its effects on coral communities and 3D complexity, test for signs of regional acclimation, and investigate long-term change in heat stress in PMNM. Surveys conducted at four island/atoll (French Frigate Shoals, Lisianski Island, Pearl and Hermes Atoll, and Midway Atoll) showed that in 2014, percent bleaching varied considerably between islands/atolls and habitats (back reef/fore reef and depth), and was up to 91% in shallow habitats at Lisianski. The percent bleaching during the 2014 event was best explained by a combination of duration of heat stress measured by Coral Reef Watch's satellite Degree Heating Week, relative community susceptibility (bleaching susceptibility score of each taxon * the taxon's abundance relative to the total number of colonies), depth and region. Mean coral cover at permanent Lisianski monitoring sites decreased by 68% due to severe losses of Montipora dilatata complex, resulting in rapid reductions in habitat complexity. Spatial distribution of the 2014 bleaching was significantly different from the 2002 and 2004 bleaching events likely due to a combination of differences in heat stress and local acclimatization. Historical satellite data demonstrated heat stress in 2014 was unlike any previous event and that the exposure of corals to the bleaching-level heat stress has increased significantly in the northern PMNM since 1982, highlighting the increasing threat of climate change to reefs.