Subsurface temperature estimates from a Regional Ocean Modelling System (ROMS) reanalysis provide accurate coral heat stress indices across the Main Hawaiian Islands.

As ocean temperatures continue to rise, coral bleaching events around the globe are becoming stronger and more frequent. High-resolution temperature data is therefore critical for monitoring reef conditions to identify indicators of heat stress. Satellite and in situ measurements have historically been relied upon to study the thermal tolerances of coral reefs, but these data are quite limited in their spatial and temporal coverage. Ocean circulation models could provide an alternative or complement to these limited data, but a thorough evaluation against in situ measurements has yet to be conducted in any Pacific Islands region. Here we compared subsurface temperature measurements around the nearshore Main Hawaiian Islands (MHI) from 2010 to 2017 with temperature predictions from an operational Regional Ocean Modeling System (ROMS) to evaluate the potential utility of this model as a tool for coral reef management. We found that overall, the ROMS reanalysis presents accurate subsurface temperature predictions across the nearshore MHI region and captures a significant amount of observed temperature variability. The model recreates several temperature metrics used to identify coral heat stress, including predicting the 2014 and 2015 bleaching events around Hawai'i during the summer and fall months of those years. The MHI ROMS simulation proves to be a useful tool for coral reef management in the absence of, or to supplement, subsurface and satellite measurements across Hawai'i and likely for other Pacific Island regions.

The geographic disparity of historical greenhouse emissions and projected climate change.

One challenge in climate change communication is that the causes and impacts of global warming are unrelated at local spatial scales. Using high-resolution datasets of historical anthropogenic greenhouse emissions and an ensemble of 21st century surface temperature projections, we developed a spatially explicit index of local climate disparity. This index identifies positive (low emissions, large temperature shifts) and negative disparity regions (high emissions, small temperature shifts), with global coverage. Across all climate change projections we analyzed, 99% of the earth's surface area has a positive index value. This result underscores that while emissions are geographically concentrated, warming is globally widespread. From our index, the regions of the greatest positive disparity appear concentrated in the polar arctic, Central Asia, and Africa with negative disparity regions in western Europe, Southeast Asia, and eastern North America. Straightforward illustrations of this complex relationship may inform on equity, enhance public understanding, and increase collective global action.

Contrasting patterns in the occurrence and biomass centers of gravity among fish and macroinvertebrates in a continental shelf ecosystem.

The distribution of a group of fish and macroinvertebrates (n = 52) resident in the US Northeast Shelf large marine ecosystem were characterized with species distribution models (SDM), which in turn were used to estimate occurrence and biomass center of gravity (COG). The SDMs were fit using random forest machine learning and were informed with a range of physical and biological variables. The estimated probability of occurrence and biomass from the models provided the weightings to determine depth, distance to the coast, and along-shelf distance COG. The COGs of occupancy and biomass habitat tended to be separated by distances averaging 50 km, which approximates half of the minor axis of the subject ecosystem. During the study period (1978-2018), the biomass COG has tended to shift to further offshore positions whereas occupancy habitat has stayed at a regular spacing from the coastline. Both habitat types have shifted their along-shelf distances, indicating a general movement to higher latitude or to the Northeast for this ecosystem. However, biomass tended to occur at lower latitudes in the spring and higher latitude in the fall in a response to seasonal conditions. Distribution of habitat in relation to depth reveals a divergence in response with occupancy habitat shallowing over time and biomass habitat distributing in progressively deeper water. These results suggest that climate forced change in distribution will differentially affect occurrence and biomass of marine taxa, which will likely affect the organization of ecosystems and the manner in which human populations utilize marine resources.

North Pacific warming shifts the juvenile range of a marine apex predator.

During the 2014-2016 North Pacific marine heatwave, unprecedented sightings of juvenile white sharks (Carcharodon carcharias) emerged in central California. These records contradicted the species established life history, where juveniles remain in warmer waters in the southern California Current. This spatial shift is significant as it creates potential conflicts with commercial fisheries, protected species conservation, and public safety concerns. Here, we integrate community science, photogrammetry, biologging, and mesoscale climate data to describe and explain this phenomenon. We find a dramatic increase in white sharks from 2014 to 2019 in Monterey Bay that was overwhelmingly comprised of juvenile sharks < 2.5 m in total body length. Next, we derived thermal preferences from 22 million tag measurements of 14 juvenile sharks and use this to map the cold limit of their range. Consistent with historical records, the position of this cold edge averaged 34° N from 1982 to 2013 but jumped to 38.5° during the 2014-2016 marine heat wave. In addition to a poleward shift, thermally suitable habitat for juvenile sharks declined 223.2 km2 year-1 from 1982 to 2019 and was lowest in 2015 at the peak of the heatwave. In addition to advancing the adaptive management of this apex marine predator, we discuss this opportunity to engage public on climate change through marine megafauna.

Coastal sharks supply the global shark fin trade.

Progress in global shark conservation has been limited by constraints to understanding the species composition and geographic origins of the shark fin trade. Previous assessments that relied on earlier genetic techniques and official trade records focused on abundant pelagic species traded between Europe and Asia. Here, we combine recent advances in DNA barcoding and species distribution modelling to identify the species and source the geographic origin of fins sold at market. Derived models of species environmental niches indicated that shark fishing effort is concentrated within Exclusive Economic Zones, mostly in coastal Australia, Indonesia, the United States, Brazil, Mexico and Japan. By coupling two distinct tools, barcoding and niche modelling, our results provide new insights for monitoring and enforcement. They suggest stronger local controls of coastal fishing may help regulate the unsustainable global trade in shark fins.

A statistical model for monitoring shell disease in inshore lobster fisheries: A case study in Long Island Sound.

The expansion of shell disease is an emerging threat to the inshore lobster fisheries in the northeastern United States. The development of models to improve the efficiency and precision of existing monitoring programs is advocated as an important step in mitigating its harmful effects. The objective of this study is to construct a statistical model that could enhance the existing monitoring effort through (1) identification of potential disease-associated abiotic and biotic factors, and (2) estimation of spatial variation in disease prevalence in the lobster fishery. A delta-generalized additive modeling (GAM) approach was applied using bottom trawl survey data collected from 2001-2013 in Long Island Sound, a tidal estuary between New York and Connecticut states. Spatial distribution of shell disease prevalence was found to be strongly influenced by the interactive effects of latitude and longitude, possibly indicative of a geographic origin of shell disease. Bottom temperature, bottom salinity, and depth were also important factors affecting the spatial variability in shell disease prevalence. The delta-GAM projected high disease prevalence in non-surveyed locations. Additionally, a potential spatial discrepancy was found between modeled disease hotspots and survey-based gravity centers of disease prevalence. This study provides a modeling framework to enhance research, monitoring and management of emerging and continuing marine disease threats.