Macroalgae exhibit diverse responses to human disturbances on coral reefs.

Scientists and managers rely on indicator taxa such as coral and macroalgal cover to evaluate the effects of human disturbance on coral reefs, often assuming a universally positive relationship between local human disturbance and macroalgae. Despite evidence that macroalgae respond to local stressors in diverse ways, there have been few efforts to evaluate relationships between specific macroalgae taxa and local human-driven disturbance. Using genus-level monitoring data from 1205 sites in the Indian and Pacific Oceans, we assess whether macroalgae percent cover correlates with local human disturbance while accounting for factors that could obscure or confound relationships. Assessing macroalgae at genus level revealed that no genera were positively correlated with all human disturbance metrics. Instead, we found relationships between the division or genera of algae and specific human disturbances that were not detectable when pooling taxa into a single functional category, which is common to many analyses. The convention to use percent cover of macroalgae as an indication of local human disturbance therefore likely obscures signatures of local anthropogenic threats to reefs. Our limited understanding of relationships between human disturbance, macroalgae taxa, and their responses to human disturbances impedes the ability to diagnose and respond appropriately to these threats.

Collapse and recovery of seafood wholesale prices in time of COVID-19.

The COVID-19 pandemic has spread around the world, disrupting economies, societies and daily life. Early research anticipated significant negative impacts for the globalized seafood supply network. Here, we explore the impact of the COVID-19 pandemic on wholesale prices from five major seafood markets around the world. An anomalies analysis was used to establish a 5-year baseline price for each commodity. Daily price data from 2020 were compared to the baseline to identify collapses (>1.96 SE from baseline) and analyse collapse characteristics (timing, duration and magnitude). Non-uniform price collapses were observed across, and within, the markets analysed. Toyosu (Tokyo) Market experienced price collapses to 51% of commodities, Rungis (Paris) 36%, Mercamadrid (Madrid) 19%, Mercado La Nueva Viga (Mexico City) 35% and the Portland Fish Exchange (Portland, Maine) 32%. Collapse magnitude varied from 11% to 79% of the 5-year average price. Average collapse duration ranged from 13 to 24 weeks with some commodities (4%-22%) remaining collapsed at the end of 2020. For markets where volume data were available, collapses were also noted (59% of commodities in Toyosu, 10% in Mercamadrid and 19% in Portland Fish Exchange); in these cases, the volume collapse was more severe than the related price collapse. To better detect, anticipate and respond to future shocks, we recommend that relevant government agencies conduct comprehensive economic reviews of the COVID-19 pandemic throughout the seafood supply chain, including the outcomes of emergency measures, short- and long-term implications of market volatility and identify areas of supply and labour vulnerabilities.

Cloudiness reduces the bleaching response of coral reefs exposed to heat stress.

Climate change and warming ocean temperatures are a threat to coral reef ecosystems. Since the 1980s, there has been an increase in mass coral bleaching and associated coral mortality due to more frequent and severe thermal stress. Although most research has focused on the role of temperature, coral bleaching is a product of the interacting effects of temperature and other environmental variables such as solar radiation. High light exacerbates the effects of thermal stress on corals, whereas reductions in light can reduce sensitivity to thermal stress. Here, we use an updated global dataset of coral bleaching observations (n = 35,769) from 1985 to 2017 and satellite-derived datasets of SST and clouds to examine for the first time at a global scale the influence of cloudiness on the likelihood of bleaching from thermal stress. We find that among coral reefs exposed to severe bleaching-level heat stress (Degree Heating Weeks >8°Cˑweek), bleaching severity is inversely correlated with the interaction of heat stress and cloud fraction anomalies (p < 0.05), such that higher cloudiness implies reduced bleaching response. A Random Forest model analysis employing different set of environmental variables shows that a model employing Degree Heating Weeks and the 30-day cloud fraction anomaly most accurately predicts bleaching severity (Accuracy = 0.834; Cohen's Kappa = 0.769). Based on these results and global warm-season cloudiness patterns, we develop a 'cloudy refugia' index which identifies the central equatorial Pacific and French Polynesia as regions where cloudiness is most likely to protect corals from bleaching. Our findings suggest that incorporating cloudiness into prediction models can help delineate bleaching responses and identify reefs which may be more resilient to climate change.

Enabling conditions for an equitable and sustainable blue economy.

The future of the global ocean economy is currently envisioned as advancing towards a 'blue economy'-socially equitable, environmentally sustainable and economically viable ocean industries1,2. However, tensions exist within sustainable development approaches, arising from differing perspectives framed around natural capital or social equity. Here we show that there are stark differences in outlook on the capacity for establishing a blue economy, and on its potential outcomes, when social conditions and governance capacity-not just resource availability-are considered, and we highlight limits to establishing multiple overlapping industries. This is reflected by an analysis using a fuzzy logic model to integrate indicators from multiple disciplines and to evaluate their current capacity to contribute to establishing equitable, sustainable and viable ocean sectors consistent with a blue economy approach. We find that the key differences in the capacity of regions to achieve a blue economy are not due to available natural resources, but include factors such as national stability, corruption and infrastructure, which can be improved through targeted investments and cross-scale cooperation. Knowledge gaps can be addressed by integrating historical natural and social science information on the drivers and outcomes of resource use and management, thus identifying equitable pathways to establishing or transforming ocean sectors1,3,4. Our results suggest that policymakers must engage researchers and stakeholders to promote evidence-based, collaborative planning that ensures that sectors are chosen carefully, that local benefits are prioritized, and that the blue economy delivers on its social, environmental and economic goals.