Future redistribution of fishery resources suggests biological and economic trade-offs according to the severity of the emission scenario.

Climate change is anticipated to have long-term and pervasive effects on marine ecosystems, with cascading consequences to many ocean-reliant sectors. For the marine fisheries sector, these impacts can be further influenced by future socio-economic and political factors. This raises the need for robust projections to capture the range of potential biological and economic risks and opportunities posed by climate change to marine fisheries. Here, we project future changes in the abundance of eight commercially important fish and crab species in the eastern Bering Sea and Chukchi Sea under different CMIP6 Shared Socioeconomic Pathways (SSPs) leading to contrasting future (2021-2100) scenarios of warming, sea ice concentration, and net primary production. Our results revealed contrasting patterns of abundance and distribution changes across species, time periods and climate scenarios, highlighting potential winners and losers under future climate change. In particular, the least changes in future species abundance and distribution were observed under SSP126. However, under the extreme scenario (SSP585), projected Pacific cod and snow crab abundances increased and decreased, respectively, with concurrent zonal and meridional future shifts in their centers of gravity. Importantly, projected changes in species abundance suggest that fishing at the same distance from the current major port in the Bering Sea (i.e., Dutch Harbor) could yield declining catches for highly valuable fisheries (e.g., Pacific cod and snow crab) under SSP585. This is driven by strong decreases in future catches of highly valuable species despite minimal declines in maximum catch potential, which are dominated by less valuable taxa. Hence, our findings show that projected changes in abundance and shifting distributions could have important biological and economic impacts on the productivity of commercial and subsistence fisheries in the eastern Bering and Chukchi seas, with potential implications for the effective management of transboundary resources.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.