We developed a framework that examines the consequences of temporal changes in temperature and ocean pH on yield and profit of multiple interacting stocks including eastern Bering Sea (EBS) snow, southern Tanner, and red king crab. Our analyses integrated experimental work on the effects of temperature and ocean pH on growth and survival of larval and juvenile crab and monitoring data from surveys, fishery landings, and at-sea observer programs. A post-recruitment model was used to compute the fishing mortality rates at which catch and profit are maximized for each year from 2020 to 2100 given the environmental conditions (ocean pH, bottom temperature and surface temperature) in the year concerned, and the implications of unintended bycatch in directed fisheries. The impacts of future changes in temperature and ocean pH on early life history have effects that differ markedly among stocks, being most pessimistic for Bristol Bay red king crab and most optimistic for EBS snow crab

A stage-structured pre-recruitment model for three species in the Eastern Bering Sea (snow crab, Tanner and red king crab) is parameterized using data from experiments on the effects of ocean pH and temperature on larval and juvenile snow, Tanner and red king crab. The model is then used to project eggs from hatching until they reach the first size-class in the models on which stock assessments are based (post-recruitment model). The pre-recruitment model is projected to 2100 under future projected time-trajectories of ocean pH, surface temperature and bottom temperature for locations chosen to be representative of the three species. The results of the projections are the expected time to achieve the first size-class in the post-recruitment model and the probability of surviving to this size-class, expressed relative to the time and survival probability for a reference period of 2006-2020

This is data from a laboratory experiment in which snow crab juveniles were held at three different pHs (ambient, pH 7.8, and pH 7.5). Growth, survival, and morphology were recorded. The complete methods, which should be read and understood prior to using this data, are under review as: Long, W.C. (In Review). Ocean acidification reduces juvenile snow crab, Chionoecetes opilio, survival but does not affect growth or morphometrics.

This dataset contains model output data that were collected to examine the impact of ocean acidification on fishery yields and profits of red king crab in Bristol Bay. A stage-structured pre-recruit model was developed to capture hypotheses regarding the impact of ocean acidification on the survival of pre-recruit crab. The model was parameterized using life history and survival data for red king crab (Paralithodes camtschaticus) derived from experiments conducted at the National Marine Fisheries Service Kodiak laboratory. A parameterized pre-recruit model was linked to a post-recruit population dynamics model for adult male red king crab in Bristol Bay, Alaska that included commercial fishery harvest. This coupled population dynamics model was integrated with a bioeconomic model of commercial fishing sector profits to forecast how the impacts of ocean acidification on the survival of pre-recruit red king crab will affect yields and profits for the Bristol Bay red king crab fishery fora scenario that includes future ocean pH levels predictions. Expected yields and profits were projected to decline over the next 50-100 years in this scenario given reductions in pre-recruit survival due to decreasing ocean pH levels over time. The target fishing mortality used to provide management advice based on the current harvest policy for Bristol Bay red king crab also declined over time in response to declining survival rates. However, the impacts of ocean acidification due to reduced pre-recruit survival on yield and profits are likely to be limited for the next 10-20 years, and its effects will likely be masked by natural variation in pre-recruit survival. This analysis is an initial step toward a fully integrated under-standing of the impact of ocean acidification on fishery yields and profits, and could be used to focus future research efforts.

This dataset contains the relationship between the effort (fishing days) and yield (in thousand tonnes) and profit (in millions of dollars; real 2019 USD) in 2020 and 2090 in the absence of future time-varying growth. The model used fisheries data collected in the eastern Bering Sea in the years 1975 and 2020. Models are: 0: base model - no environmental impacts; 4: SST impact on growth increment; 5: Nursery ground impact on recruitment; 6: SST impact on growth increment, nursery ground impact on recruitment, and pH impact on survival when there is no past annual variation in growth parameters; 8: SST impact on growth increment, nursery ground impact on recruitment, and pH impact on survival when there is past annual variation in the kappa growth parameter; 9:SST impact on growth increment, nursery ground impact on recruitment, and pH impact on survival when there is past annual variation in the Linf growth parameter. The calculations ignore future variation in recruitment about the stock-recruitment and in the parameters of the growth function.

This data set is the results of a laboratory experiment. Juvenile red king crab and Tanner crab were reared in individual containers for nearly 200 days in flowing control (pH 8.0), pH 7.8, and pH 7.5 seawater at ambient temperatures (range 4.4-11.9 C). Survival, growth, and morphology were measured throughout the experiment. At the end of the experiment, calcium concentration was measured in each crab and the dry mass and condition index of each crab were determined.

In this study, we examined how CO2-driven acidification affected the growth and survival of juvenile golden king crab (Lithodes aequispinus), an important fishery species in Alaska. Juveniles were reared from larvae in surface ambient pH seawater at the Kodiak Laboratory. Newly molted early benthic instar crabs were randomly assigned to one of three pH treatments: (1) surface ambient pH ~ 8.2, (2) likely in situ ambient pH 7.8, and (3) pH 7.5. Thirty crabs were held in individual inserts in each treatment for 127 days and checked daily for molting or death. The complete methods, which should be read and understood prior to using this data, are published as: Long, W. C., Swiney, K. M., & Foy, R. J. (2021). Effects of ocean acidification on young of the year golden king crab (Lithodes aequispinus) survival and growth. Marine Biology, 168(8), 126. https://doi.org/10.1007/s00227-021-03930-y.

Juvenile red and blue king crabs (Paralithodes camtschaticus and P. platypus) were exposed to three pH levels: ambient (pH 8.1), pH 7.8, and pH 7.5 for three weeks. Oxygen consumption and feeding ration were determined immediately after exposure to treatment water and after three weeks exposure. Growth can be calculated from the wet mass observations.

This is data from a laboratory experiment in which red and blue king crab (Paralithodes camtschaticus and P. platypus) juveniles were held at three different pH levels (ambient, pH 7.8, and pH 7.5). Growth, survival, feeding and respiration were recorded. The complete methods, which should be read and understood prior to using this data are published as: Long, W.C., Pruisner, P., Swiney, K.M., and Foy, R. 2019. Effects of ocean acidification on respiration, feeding, and growth of juvenile red and blue king crabs (Paralithodes camtschaticus and P. platypus). ICES J. Mar. Sci. 76(5): 1335-1343. https://doi.org/10.1093/icesjms/fsz090.

Average profit (million $) and average catch (thousand tonnes) [median and 90 % intervals] by harvest strategy and the proportion of years with negative profit. Results are shown for projections based on models 0, 8 and 9. The strategies include the average fishing mortality for 2016–20, and strategies based on constant F and the 40-5 harvest control rule. The target fishing mortality for the latter two strategies are F35%, F35, and FMEY. The calculations account for future variation in recruitment about the stock-recruitment and in the parameters of the growth function.