Marine wild-capture fisheries after nuclear war Kim J. N. Scherrera,1,2, Cheryl S. Harrisonb,c,2, Ryan F. Heneghana, Eric Galbraitha,d, Charles G. Bardeene,f, Joshua Coupeg, Jonas Jägermeyrh,i,j, Nicole S. Lovenduskic,k, August Lunab, Alan Robockg, Jessica Stevensb, Samantha Stevensonl, Owen B. Toonf,j, and Lili Xiag a Institut de Ciència i Tecnologia Ambientals, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain; bSchool of Earth, Environmental and Marine Science, University of Texas Rio Grande Valley, Port Isabel, TX 78578; cInstitute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309; dDepartment of Earth and Planetary Science, McGill University, Montreal, QC H3A 0E8, Canada; eAtmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO 80305; fLaboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO 80303; gDepartment of Environmental Sciences, Rutgers University, New Brunswick, NJ 08901; hGoddard Institute for Space Studies, National Aeronautics and Space Administration, New York, NY 10025; iCenter for Climate Systems Research, Columbia University, New York, NY 10025; jClimate Resilience, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14473 Potsdam, Germany; kDepartment of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO 80309; and lBren School, University of California, Santa Barbara, CA 93117 Edited by Marten Scheffer, Wageningen University and Research Centre, Wageningen, Netherlands, and approved September 16, 2020 (received for review April 29, 2020) Nuclear war, beyond its devastating direct impacts, is expected to Modeling approaches make it possible to evaluate the effects cause global climatic perturbations through injections of soot into of nuclear war of varying magnitudes, with the model simulations the upper atmosphere. Reduced temperature and sunlight could used here (3, 15) agreeing well with earlier simulations in terms drive unprecedented reductions in agricultural production, endan- of climate response (12, 16, 17, 29). Process-based crop modeling gering global food security. However, the effects of nuclear war frameworks have recently made it possible to further investigate on marine wild-capture fisheries, which significantly contribute to potential implications of a nuclear conflict for global food se- the global animal protein and micronutrient supply, remain unex- curity. Jägermeyr et al. (28) found that even a limited regional plored. We simulate the climatic effects of six war scenarios on fish nuclear conflict between India and Pakistan, using less than 1% biomass and catch globally, using a state-of-the-art Earth system of the world’s nuclear weapons (5-Tg soot), is likely to decrease model and global process-based fisheries model. We also simulate global caloric crop production by 11% for 5 y. This decrease how either rapidly increased fish demand (driven by food short- would be four times larger than the highest observed historical ages) or decreased ability to fish (due to infrastructure disrup- anomalies. The high-latitude production shock would propagate tions), would affect global catches, and test the benefits of globally through food trade dependencies. These alarming strong prewar fisheries management. We find a decade-long neg- findings make it important to investigate how other parts of the ative climatic impact that intensifies with soot emissions, with global food production system may be affected by a nuclear war, global biomass and catch falling by up to 18 ± 3% and 29 ± 7% in particular global fisheries, on which many societies depend after a US–Russia war under business-as-usual fishing—similar in (30, 31). magnitude to the end-of-century declines under unmitigated The responses of global marine ecosystems and fisheries to global warming. When war occurs in an overfished state, increas- both volcanic and nuclear-war–driven abrupt climate perturba- ing demand increases short-term (1 to 2 y) catch by at most ∼30% tions are largely unknown. Here, we explore the impacts of followed by precipitous declines of up to ∼70%, thus offsetting only a minor fraction of agricultural losses. However, effective prewar management that rebuilds fish biomass could ensure a Significance short-term catch buffer large enough to replace ∼43 ± 35% of today’s global animal protein production. This buffering function Nuclear conflict poses the chilling prospect of triggering abrupt in the event of a global food emergency adds to the many previ- global cooling, and consequently, severely reduced crop pro- ously known economic and ecological benefits of effective and duction. However, the impacts on marine fisheries are un- precautionary fisheries management. known. If agricultural yields fall on land, could we turn to the sea instead? Here, we show that agricultural losses could not | food from the ocean fisheries management | abrupt climate change | be offset by the world’s fisheries, especially given widespread | nuclear winter global food security overfishing. Cold temperatures and reduced sunlight would decrease the growth of fish biomass, at worst as much as under unmitigated climate change. Although intensified postwar N uclear weapons continue to pose a threat to humanity. Al- though global nuclear weapons stockpiles are lower today than at their peak in 1986, arsenals are growing in India, Paki- fishing could yield a small catch increase, dramatic declines would ensue due to overharvesting. However, effective pre- war fisheries management would create a substantial buffer of stan, and North Korea, adding to those already maintained by fish in the ocean, greatly increasing the oceans’ potential the United States, Russia, China, France, the United Kingdom, contribution during a global food emergency. and Israel (1–4). The United States and Russia are both un- dertaking extensive modernization programs for warheads and Author contributions: K.J.N.S., C.S.H., R.F.H., and E.G. designed research; K.J.N.S., C.S.H., delivery systems (5, 6), and increased tension in South Asia and R.F.H., A.L., and J.S. performed research; K.J.N.S., C.S.H., R.F.H., J.C., A.L., and J.S. analyzed data; and K.J.N.S., C.S.H., R.F.H., E.G., C.G.B., J.C., J.J., N.S.L., A.R., S.S., O.B.T., and L.X. recent failures to renew arms control treaties have intensified wrote the paper. concerns about the prospect of imminent nuclear war (7, 8). The authors declare no competing interest. Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 Beyond the devastating direct impacts, the soot inputs from fires This article is a PNAS Direct Submission. ignited by nuclear air bursts are likely to cause global cooling and This open access article is distributed under Creative Commons Attribution-NonCommercial- reductions in sunlight (9–13), similar to historical volcanic NoDerivatives License 4.0 (CC BY-NC-ND). eruptions (Table 1) (3, 14–23). Nuclear-war–driven climate 1 To whom correspondence may be addressed. Email: kim.jn.scherrer@gmail.com. perturbations are expected to disrupt global primary productiv- 2 K.J.N.S and C.S.H. contributed equally to this work. ity, with a potential threat to human lives through crop failure in This article contains supporting information online at https://www.pnas.org/lookup/suppl/ breadbasket regions and subsequent food shortages worldwide doi:10.1073/pnas.2008256117/-/DCSupplemental. (24–28). First published November 9, 2020. 29748–29758 | PNAS | November 24, 2020 | vol. 117 | no. 47 www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Table 1. Overview of nuclear-war–driven climatic perturbations Soot Δ Radiative forcing, Δ NPP, Anomaly load Warring nations W·m−2 Δ SST, °C % duration, y Description War simulations 5 Tg India and Pakistan −10.9 −0.5 −3 ∼10 Lower-end regional conflict; used in this 100 15-kt weapons study 16 Tg India and Pakistan −31.1 −1.4 −7 ∼10 Intermediate regional conflict; 250 15-kt weapons 27 Tg India and Pakistan −46.9 −2.3 −10 ∼10 Intermediate regional conflict; 250 50-kt weapons 36 Tg India and Pakistan −57.8 −2.9 −12 ∼10 Higher-end regional conflict; 250 100-kt weapons 47 Tg India and Pakistan −68.7 −3.5 −16 ∼10 Upper-limit regional conflict; 500 100-kt weapons 150 Tg Russia and United −115.3 −6.4 −37 ∼10 Nuclear superpower conflict; States ∼4,400 100-kt weapons Previous war 5 Tg India and Pakistan ∼ −10 −0.8 NA ∼10 From ref. 16 simulations 5 Tg India and Pakistan −8.2 to −10 −0.1 NA ∼10 From ref. 17, range depends to −0.6 on war duration 150 Tg Russia and United −84.7 NA NA ∼10 From ref. 18 States Perturbation Other climatic Pinatubo eruption (1991 −6.5 ± 2.7 ∼ −0.1 NA ∼2 Refs. 19–21 perturbations CE) ENVIRONMENTAL Tambora eruption (1815 −17.2 ± 4.9 ∼ −1 NA ∼2 Refs. 19–21 CE) SCIENCES Samalas eruption (1257 −32.8 ± 9.6 ∼ −1 NA ∼2 Refs. 19–21 CE) to −2 RCP 2.6 global warming +2.6 0 to +1 −2 to — Refs. 22 and 23 (2100 CE) +1 RCP 8.5 global warming +8.5 +2 to +4 −11 — Ref. 22 (2100 CE) to −4 SUSTAINABILITY Radiative forcing, sea surface temperature (SST), and oceanic net primary productivity (NPP) anomalies are the maximum annual global means. Anomaly duration is the atmospheric residence time of aerosols. Details for India–Pakistan scenarios are in ref. 3, and for United States–Russia in ref. 15. Previous SCIENCE nuclear war simulations, historical volcanic anomalies, and projected global warming anomalies are given for comparison. NPP has not been reported for previous simulations of nuclear war or volcanic eruptions, indicated by not available (NA). nuclear war scenarios on wild-capture fisheries. Fish and other whether these effects would worsen or mitigate the predicted seafood provide almost 20% of the animal protein consumed by losses in agricultural food production. the global human population, out of which wild-caught seafood— Beyond direct climatic perturbations, a nuclear conflict is also the focus of the present study—make up approximately one-half likely to cause socioeconomic perturbations that change global (∼80 to 120 Mt·y−1) (32, 33). Furthermore, wild-caught seafood fishing behavior. Altered climate conditions leading to decreased (herein simply “fish”) is a particularly important source of essential crop production on land (24, 25, 27, 28) could cause a general micronutrients in developing countries, with almost 1 billion people decrease in caloric supply and limit aquaculture and livestock at risk to become micronutrient deficient if global fish catches fall production due to their dependence on feed (39, 40). This would (31). Concerningly, global catches have been stagnant or slightly declining since the 1990s (Fig. 1) (32, 33), and in a majority of the world’s fisheries, biomass is depleted below the level that generates the maximum sustainable yield (BMSY) (34). This indicates that present-day catches exceed the limits of productivity in many re- gions, and effective management measures, which are crucial to remedy this situation (35), have been projected to increase global fish biomass by 200 to 800 Mt (34). A closer investigation into the response and potential of the global fishery under an abrupt global food emergency is therefore warranted. While fishing pressure has a major impact on fish populations Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 and their ability to reproduce, the production of fish biomass Fig. 1. Prewar trajectories of global fisheries. Simulated (A) annual wild fish also depends on environmental characteristics, most importantly catch (megatons wet biomass) and (B) total wild commercially targeted fish net primary production (NPP) and water temperature (36, 37). biomass (gigatons wet biomass) over 1950 to 2019 from the prewar fisheries Since a nuclear war is expected to cause global cooling and de- baseline using the BOATS model with no fisheries regulation. Shaded areas show the SD for the five parameter ensemble runs, and the dotted lines crease oceanic NPP (3, 15, 38), it is likely to have a significant show the ensemble mean. The fishery and ecosystem state in 2019 are used impact on global fish catch. However, it is unknown how these as initial conditions for the nuclear war scenarios. In A, the gray solid line global-scale shifts in NPP and temperature could combine to shows empirical global catches from ref. 33, with uncertainty indicated by affect marine ecosystems and marine food productivity, and the shaded area. Scherrer et al. PNAS | November 24, 2020 | vol. 117 | no. 47 | 29749 likely raise the demand for wild-capture fish as a source of ani- changes are anomalies from the BAU-control scenario, which has mal protein, leading to an increase in price and intensified no war and BAU fishing behavior (Materials and Methods). In the fishing. For example, the Tambora volcanic eruption in 1815 and text, we generally present numbers for the end-member cases of 5- the associated crop failures triggered a hundredfold increase in and 150-Tg soot inputs. the exported catch of marine pelagic fish in the Gulf of Maine (41). On the other hand, substantial damage to fisheries infra- Initial Impacts on Catch and Biomass. Nuclear-war–driven climate structure (e.g., ships, harbors, fuel supply, processing facilities) perturbations (Table 1) generally lead to significant short-term along with supply chain disruptions could lead to reduced fishing losses in global fish catch and biomass in year 2 postwar (Fig. 2 effort, as would unsafe ocean travel due to geopolitical instability and SI Appendix, Fig. S1). Larger soot input exacerbates losses, (42). Although difficult to predict, such socioeconomic changes and the effect is linear with the associated reduction in photo- may greatly influence fisheries outcomes after a nuclear war. synthetically active radiation (PAR) (SI Appendix, Tables S1–S4 This study explores the effects of six nuclear war scenarios and Materials and Methods), which presumably drives the net (Table 1) on the global biomass and catch of fish: five India– reduction in global NPP (SI Appendix, Fig. S6). On average for Pakistan scenarios of increasing intensity with black carbon all socioeconomic fishing responses, catch and biomass decrease (soot) loads of 5 to 47 Tg (details in ref. 3) and one substantially by ∼2% and ∼1%, respectively, for every 1 Tg of soot (∼4% and larger US–Russia war injecting 150 Tg of soot (details in ref. 15). ∼3%, respectively, for every 10% decrease in PAR). All war scenarios are generated by a state-of-the-art Earth sys- Under BAU fishing, global biomass decreases by 1.6% tem model (Community Earth System Model–Whole Atmo- (±0.7%, SD of the five BOATS ensemble runs; Materials and sphere Community Climate Model [CESM-WACCM]; Materials Methods) in the scenario with a 5-Tg soot input, and up to 18 and Methods). Output from CESM-WACCM is used as input to (±3.5)% in the 150-Tg scenario (Fig. 2A and SI Appendix, Fig. the Bioeconomic Marine Trophic Size-Spectrum (BOATS) S1A and Tables S1 and S3). Since this biomass decrease also model, a process-based ocean ecosystem model with dynamic leads to a decrease in the global fishing effort (Eq. 1), catches fall fishing that has been used in a number of future climate appli- more than biomass: by 2.4 (±0.8)% under 5 Tg, and up to 29 cations (23, 43–46). With an unregulated prewar fisheries base- (±7)% in the 150-Tg case (Fig. 2B and SI Appendix, Fig. S1B and line simulation as the starting point (Fig. 1 and Materials and Tables S2 and S4). Methods), we use BOATS to model the impact of nuclear war on If the conflict is followed by intensified fishing due to in- global fisheries. Bracketing a range of possible changes in fishing creased demand (F+, F++; Table 2), catch initially increases at behavior due to the war, we explicitly model five simplistic so- the expense of biomass. Under the 5-Tg soot input, where the cioeconomic responses: business-as-usual (BAU) fishing and a climatic effect is relatively small, F+ and F++ generate catch large or very large increase (F+, F++) or decrease (F−, F−−) in increases of 13% (±17%) and 17% (±14%), respectively, in year fishing intensity (Table 2 and Materials and Methods). We also 2 postwar (Fig. 2B). At the same time, F+ and F++ cause a investigate how strong prewar fisheries management improves 10% (±4%) and 23% (±9%) global biomass decline (Fig. 2A). the ocean’s capacity to alleviate food losses (SI Appendix, Fig. S8 Larger climate perturbations cause more rapid biomass collapse and Materials and Methods). Beyond quantifying the effects of and can preclude a net increase in catch. In the 150-Tg case, nuclear war, these simulations illustrate the potential effects of representing the strongest perturbation, even the greatly inten- large volcanic eruptions or of socioeconomic shocks on global sified fishing effort in F++ fails to compensate for the large marine capture fisheries. negative climate impact, as global catches still fall by 14% (±20%) (Fig. 2B). Results Conversely, decreased fishing intensity due to decreased Below, we present the impacts of both nuclear-war–driven cli- ability to fish (F−; F−−) decreases catch but creates a net in- matic perturbations (soot inputs, Table 1) and socioeconomic crease in biomass despite the climate-driven losses for almost all fishing responses possibly triggered by the global crisis (Table 2). soot inputs (Fig. 2). Under the 5-Tg soot input, F− and F−− For clarity, we hereon define a scenario as a specific combination result in substantial falls in global catch of 23% (±19%) and 52% of soot input and socioeconomic response. First, we present an (±24%), respectively. This increases global biomass by 7% overview of the impacts in year 2 postconflict, pinpointing the (±4%) and 26% (±7%), respectively. Larger soot inputs both initial, transitory effects of altered fishing behavior. We then exacerbate the falls in catch and diminish the biomass recovery describe the longer-term (15-y) fisheries trajectories for all sce- that is enabled by the lowered fishing pressure. Again, the cli- narios, illustrating the duration and rate of recovery. Then, we in- matic effect is linear with PAR (Fig. 2 and SI Appendix, Tables vestigate the spatial patterns of change and link these to national- S1 and S2). level seafood dependence for the 5-Tg case. Finally, we show how strong fisheries regulation increases the potential for higher global Decadal Fishery Response. Longer-term global fisheries trajecto- catches postwar. Unless otherwise stated, presented relative ries under BAU fishing (Fig. 3 A–C) show the general decrease Table 2. Overview of modeled socioeconomic responses Socioeconomic response Code Drivers Implementation Business-as-usual BAU Socioeconomic parameters unaffected by war Unchanged fish price (p) and fishing cost (c) Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 Intensified fishing F+ Crop failure, food system collapse, increased fish demand Twofold increase in p Greatly intensified fishing F++ Severe crop failure, food system collapse, greatly increased Fivefold increase in p demand Decreased fishing ability F− Fuel scarcity, infrastructure destruction, security concerns Twofold increase in c Greatly decreased fishing F−− Severe fuel scarcity, infrastructure destruction, security concerns Fivefold increase in c ability Price and cost changes are implemented instantaneously (step change) in the year of the war. Each socioeconomic response combined with a war-driven climatic perturbation (Table 1) makes up a model scenario. Details are in Socioeconomic Responses. 29750 | www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Scherrer et al. soot inputs. At the end of the simulations, global biomass is al- most double and fourfold under F− and F−−, respectively (Fig. 3H and SI Appendix, Fig. S2E), and catches increase by ∼60 and 140% (Fig. 3G and SI Appendix, Fig. S2D). Thus, the total cumulative catches over the 15-y postwar period is almost 30% higher under the 5-Tg and F−− scenario (in contrast to the cumulative 38% decrease under 5 Tg and F++). The greatly decimated effort (Fig. 3I and SI Appendix, Fig. S2F) and higher biomass lead to increased catch efficiency, similar to observations in the North Atlantic after the end of World War II (42), which makes the fisheries more economically efficient. Regional Patterns of Change. While the climatic perturbations decrease the total global fish catch postwar, there is substantial spatial variability, with increasing catch in some regions (Fig. 4). Averaged over the first 5 y postwar under BAU fishing, catch increases patchily in the tropics and subtropics, particularly in the Atlantic Subtropical Gyres under higher soot input scenarios. The largest decreases in catch occur along the equator and midlatitudes. These spatial patterns generally follow spatial changes in NPP following the war predicted by CESM (SI Ap- pendix, Fig. S3), with some influence from changes in water temperature (SI Appendix, Fig. S4). Spatial patterns of catch ENVIRONMENTAL change under increasing or decreasing fishing pressure are sim- Fig. 2. Short-term impacts of nuclear war on global fisheries. Panels show ilar to the patterns under BAU (SI Appendix, Figs. S5 and S6). SCIENCES the average percent difference in (A) biomass and (B) catch between the The spatial patterns translate into differential impacts on the business-as-usual (BAU) control simulation (no war) and different nuclear war simulations (5 to 150 Tg), in year 2 postconflict. Each value is plotted catches of individual fishing nations (Fig. 5, SI Appendix, Table against the war scenario (soot input indicated on upper x axis) and its as- S5, and Materials and Methods). Here, we focus on the 5-Tg BAU sociated percent reduction in global photosynthetically active radiation scenario for comparison with the investigation of crop yields by (PAR). The slope for each marker type shows the impact of the climatic (28). Under this lower-impact scenario, several major fishing perturbation (for a given socioeconomic response F+/−; see Table 1), while nations, such as Russia, Canada, Japan, and the United States, SUSTAINABILITY the vertical spread between marker types shows the effect of the socio- see substantial catch losses in their territorial waters under the economic responses. Statistics for linear regressions are given in SI Appendix, modeled climatic perturbations. Some lower-latitude fishing SCIENCE Tables S1 and S2. nations like Mexico, Peru, Greece, and Somalia experience in- creased catch potential. However, equatorial island nations, who are most dependent on marine food supply, suffer some of the and subsequent recovery in global fish biomass and catch in the largest declines. A comparison with the country-level depen- decade postwar. In the 5-Tg case, global catch decreases by at dence on marine ecosystems for nutrition (47) suggests that most 3.6% (±1.4%), occurring in year 5 postwar (Fig. 3A). In these island states are particularly vulnerable to the predicted contrast, with a 150-Tg soot input, the largest catch decrease is fall in catches (Fig. 5B), among which Indonesia is the most 31% (±9%) in year 3 postwar. Trajectories for the intermediate populous country by far. soot loads consistently lie in between. Eventually, both biomass and catch recover relative to the control climate, with recovery Benefits of Fisheries Regulation. Strong prewar management of taking ∼14 y and somewhat exceeding the BAU-control (Fig. 3 A fisheries greatly increases the capacity of marine fisheries to and B). Due to the climate-driven biomass decline, which ren- mitigate agricultural losses (Fig. 6). If global fisheries are ders fishing less profitable, modeled fishing effort begins to de- strongly regulated to maintain a healthy biomass before the crease immediately after the war and lags harvest and biomass onset of the conflict (SI Appendix, Fig. S8 and Materials and (Fig. 3C and Eq. 1). Methods), the short-term catch increase under intensified fishing Increase in fish demand (F+, F++) in turn increases fishing postwar is greatly enhanced (SI Appendix, Fig. S9). Under a effort. After an initial increase in catch, biomass is depleted, 150-Tg and F+ scenario (Fig. 6), shown here to illustrate the driving a fishery crash in all scenarios that lasts until the end of extent to which intensified fishing could alleviate an extreme the simulation (Fig. 3 D–F and SI Appendix, Fig. S2 A–C). food crisis, global catch increases by 430% (±350%) relative to Catches drop below the BAU control 2 to 3 y postwar, and the unregulated BAU control. This increase is achieved despite stabilize about 45% and 75% lower by the end of the 15-y sim- the substantial climatic impact associated with the 150-Tg soot ulation. For all soot inputs, biomass under F+ decreases, at most input (Fig. 2A). Catch rapidly decreases in the second year but by 50 to 60%, and under F++ by about 84%. This biomass remains somewhat higher than in the unregulated case until depletion means that the largest intensification of fishing (F++) ∼10 y postwar. leads to the lowest total catch when integrated over the whole 15-y postwar period: Under the 5-Tg and F++ scenario, cu- Discussion Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 mulative catch falls by 38%. In summary, nuclear-war–driven climatic perturbations have an If the war induces a substantial decrease in fishing (F−, F−−), overall negative effect on fisheries that increases with soot input, global catches initially decrease and fish biomass rapidly begins despite positive impacts in some subtropical regions. However, to recover (Fig. 3 G–I and SI Appendix, Fig. S2 D–F). The de- socioeconomic responses to the nuclear war could greatly in- cline in catch, down to 49% (±8%) in the F− and 150-Tg sce- fluence the trajectories of global fish catch and biomass. In the nario, is maintained for the first 4 y, but eventually the absence of strong prewar management, if the nuclear war leads recovering fish biomass increases catches long-term. By year 5 to intensified fishing (for example due to terrestrial food short- postwar, catch has begun to exceed the BAU control catch for all ages) a small increase in the global catch is possible for the first Scherrer et al. PNAS | November 24, 2020 | vol. 117 | no. 47 | 29751 Fig. 3. Global fishery developments postwar. Panels show the percent anomaly from the BAU control scenario (dashed line) for all soot inputs (solid lines). Upper row (A–C) shows trajectories of catch, biomass, and fishing effort under BAU fishing, middle row (D–F) shows trajectories under the intensified fishing scenario F+, and lower row (G–I) shows trajectories under the decreased fishing scenarios F−. The shaded areas show SD for the five parameter ensemble runs, while the solid lines are the ensemble mean. The light yellow lines in D–I show the F+ and F− responses in the absence of a climatic perturbation, i.e., the F+ or F− control. few years postwar. This however rapidly depletes the fish stocks unmitigated climate change (RCP 8.5), range from ∼12 to 25%, and is followed by a precipitous decline in catches. Strong fisheries while strong mitigation (RCP 2.6) likely limits the decrease regulation prewar could instead allow catches to become many to <5% (23, 45, 49, 50). In comparison, the 150-Tg case yields times higher than normal in the first year postwar, even despite maximum declines in catch and biomass of 31% and 24%, re- large soot inputs. A decrease in fishing because of damaged in- spectively, under BAU fishing (<4% in the 5-Tg case). Thus, the frastructure would lead to relatively large short-term catch de- negative impacts of unmitigated climate change on fisheries al- creases in a potentially critical time for global food security. most reach those of a large-scale nuclear war between the United States and Russia. However, the abruptness and duration of the Role of NPP, Temperature, Fishing, and Adaptation. The effect of the negative impacts differ greatly, as do the underlying causal nuclear-war–driven climatic perturbations on global fish catch mechanisms. A nuclear conflict generates a net global decrease can largely be explained by the effects of NPP, temperature, and in oceanic NPP (SI Appendix, Fig. S7), likely attributed to a re- fishing pressure. Cooling slows the growth rates of fish, while duction in sunlight reaching the ocean surface (51), in turn lower NPP input decreases the amount of energy available for the leading to a decrease in global catch and biomass. In contrast, ecosystem, causing the postwar decrease in simulated biomass and the reductions under global warming result from a combination catches (43, 48). However, cooling also has a positive impact on the of NPP decreases driven by increased stratification (52), the steady-state fish biomass, by increasing the efficiency with which decrease in the size of phytoplankton (53), and the metabolic energy supplied by NPP can accumulate as biomass in large or- effects of warming on fish physiology (48). ganisms (43, 48). This accumulation is most apparent for the sim- Our results also suggest that the marine fish catch is relatively ulations in an unfished ocean (SI Appendix, Fig. S7), but is less more robust to the effects of a nuclear conflict than land-based pronounced in fished systems, where growth rates limit fish biomass food production. While total global fish catches here decrease by more than NPP. We underline that the representation of ecological ∼4% under the 5-Tg scenario, Jägermeyr et al. (28) found an processes in BOATS greatly simplifies trophic exchanges and does 11% decline in global crop production for 5 y under the same not include fish movement, and that it has a relatively high sensi- soot input. This difference arises because the ocean does not tivity to temperature when compared with other models (23). Still, cool as much as land (cf. figure S6 in ref. 3), and because of the integrated globally, the modeled catch decrease under BAU fishing assumed adaptability of fish, and in turn fisheries, to a cooling Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 is similar to the decrease in global oceanic NPP caused by the environment. In contrast to crops, most fish stocks rapidly move different soot inputs (SI Appendix, Fig. S7B) and is consistent with and migrate in response to climate variations (54). Here, fishing macroecological theory. fleets in turn increase their fishing effort in regions with climate- We note that both the nuclear-war–driven climatic perturba- driven biomass increases, and vice versa, which alleviates global tions and anthropogenic global warming have negative impacts catch losses. This assumption is supported by the global ubiquity on marine fisheries, even though the former causes cooling and of fishing and the fleet’s ability to track seasonal fish movements the latter, warming. Model projections of the long-term (year (55, 56). For agricultural systems, where the war-driven climate 2100) decrease in global fish biomass or catch potential under effects are most severe in regions that produce several major 29752 | www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Scherrer et al. ENVIRONMENTAL SCIENCES SUSTAINABILITY SCIENCE Fig. 4. Spatial distribution of changes in fish catch. Panels show six different soot inputs under BAU fishing, averaged over the first 5 y postwar. A–F show the mean difference in annual fish catch per square meter between the control (0 Tg) and the 5- to 150-Tg soot inputs of the five ensemble runs. In the Lower Right corner, the global catch difference in the 5-y period is indicated (ensemble mean and SD). crops, the limited ability to rapidly adjust production to the valuable to mitigate a global food emergency and allow time for changing climatic conditions (57) exacerbates crop losses. adaptation. We also underline that the direct impacts of cereal production Food System Linkages. Both the drivers of fishing and the im- losses on fish demand are uncertain considering the differences portance of global fish catches are interlinked with the impacts of in nutritional values and total production. The demand for fish nuclear war on other parts of the global food production system. may be more strongly connected to the production of other an- Cereal production is about 25 times larger than fish catches imal protein products (60), in particular aquaculture products, globally (58), with the caloric content per gram of cereals being for which the effects of nuclear war are poorly explored (61). almost six times that of fish (59). This makes offsetting the losses Furthermore, the capacity to adapt conventional agricultural of calories from agriculture very difficult. Still, it is reasonable to production systems (28) and to scale up production of alternative expect that cereal production losses postwar, estimated at 11% foods (fungi, bacteria, etc.) in the event of a crisis (62) could already under the 5-Tg case (28), would impair the production of impact the demand for fish as well as the consequences of falling other animal protein and increase the overall need for other global catches. foods. Here, the increase of global catch under greatly intensi- Contamination of food due to nuclear fallout is a further fied fishing is limited to at most 30% in the 5-Tg case (and less concern for food security. Close to sites of nuclear power plant under larger climate perturbations), ∼30 Mt·y−1 if using the accidents, fish can become highly contaminated by radioactive present-day catch of ∼100 Mt·y−1 as a baseline (32, 33). Such an pollution (63, 64). However, radionuclides are strongly diluted in increase would constitute a significant but small contribution to the ocean given the large volume of water, and the range and global food security. However, strongly regulated global fisheries intensity of contamination of marine systems have been limited Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 could theoretically generate “emergency catches” several hun- in past accidents (64–68). Although it is yet unexplored how the dred percent higher than unregulated fisheries. Since a catch of nuclear war scenarios used here would affect oceanic radionu- ∼100 Mt·y−1 makes up roughly 10% of the total animal protein clide concentrations, seafood appears less likely to be sensitive to supply (32), our results suggest that the 430% (±350%) increase nuclear fallout than terrestrial foods. This suggests that fish in global catches enabled by strong prewar management (Fig. 6) caught outside of the immediate war areas could provide a rel- could offset a loss of ∼43% (±35%) of the present-day annual atively safe food source, which might further increase demand. supply of all other animal protein (cultured fish, meat, dairy, and It is important to underline that the fish biomass in BOATS eggs). Although short-lasting, such a buffer could be extremely represents only the fish and shellfish that have historically been Scherrer et al. PNAS | November 24, 2020 | vol. 117 | no. 47 | 29753 Fig. 5. Country-level fish catch changes under the 5-Tg and BAU fishing scenario. In A, the color of each exclusive economic zone (EEZ) shows the total change in modeled catch (1,000 ton wet biomass·y−1) relative to the BAU control scenario, averaged over the first 5 y postwar. In B, change in EEZ catch vs. national-level dependence on marine ecosystems for nutrition is shown. targeted by fisheries (i.e., those reported in the Sea Around Us of an optimized ensemble of parameterizations that allow us to Database) (33). In the event of global food shortage, it is possible explore a large part of the uncertain parameter space (44, 45), that new marine organisms would become targeted by fisheries, increases the confidence in the model results. expanding the scope for increasing marine catches. The total Still, the extreme rate and magnitude of climatic change biomass of all fish species is highly uncertain (69), meaning that modeled here may have consequences that are not accurately this potential is poorly known, but the biomass of unexploited captured by BOATS. The model implicitly assumes that species mesopelagic fishes is believed to be larger than the total global will quickly migrate and adapt to the changing environmental biomass of currently exploited wild finfish (70). If a global food conditions, and is unable to capture the importance of keystone crisis would induce the rapid development of more effective species, or the seasonal timing of reproduction and feeding in- harvesting technologies for these dispersed fish and other cur- teractions. These factors may severely and perhaps irreversibly rently unexploited species, fisheries could further mitigate ter- affect marine ecosystem productivity under rapid climatic change restrial crop failures, but with potentially large and poorly (75–77). The importance of such unresolved mechanisms is understood consequences for marine ecosystems (71, 72). expected to be larger in ecosystems where the rate of adaptation The conflict-driven changes in the global fish supply would is lower than the rate of climatic change (78)—which is especially likely have highly variable regional impacts, given the importance rapid in this study. For example, nearshore and coral reef sys- of factors like local food production capacity, purchasing power, tems have previously been suggested to be the most sensitive to and trade network functionality (73). We here find that the rapid cooling (75). The maintained biomass growth in BOATS modeled climatic perturbations would cause the largest fall in may therefore be optimistic in such regions, as it disregards the fish catches in developed high-latitude countries, which are also risks for climate-driven nonlinear ecosystem and productivity the hardest hit by crop failures (28), and in developing equatorial shifts due to noninstantaneous adaptation. Nonetheless, the in- island nations, which are highly fish dependent (47). This sug- crease in the productivity of some species and decrease in others gests potential synergistic effects on regional food security, in in the Gulf of Maine after the 1815 Tambora eruption (41), particular if the drop in global food production reduces the which had a greater radiation anomaly than the 5-Tg case willingness or ability to trade. At the same time, regional varia- modeled here (Table 1), lends some credibility to the assumption tions in management effectiveness and the resulting biomass of regional species substitutability in BOATS even under the levels (35) (Uncertainties and Limitations) should also strongly rapid climatic changes that could be caused by a nuclear war. We impact the regional consequences. Overall, further investigation also emphasize that neither BOATS nor CESM resolves the of the interdependencies between fishing, aquaculture (mediated potential impacts of nuclear-war–driven changes in ocean acid- through wild-caught fish being used as feed), and the rest of the ification (as described in ref. 38) on marine organisms. Work is food production system in the event of a global food crisis currently underway to simulate the response of coccolithophores is needed. to acidification in CESM (79); future studies will explore this idea further. Uncertainties and Limitations. This work quantifies the response of An important simplification in the present study is that the global marine ecosystems and fisheries to abrupt, extreme cli- prewar fisheries baseline (Fig. 1) assumes that there is no ef- Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 matic cooling. As a result, the associated uncertainties are bound fective fisheries management. Fishing effort instead evolves as to be large. An advantage of BOATS is that its key ecological predicted in an open access fishery, where effort only decreases processes (growth, metabolism, mortality, and reproduction) are when profit becomes negative (Eq. 1) (80, 81). We use this as- affected in a mechanistic way by changes in temperature and sumption because it better reproduces the development of global NPP (43, 48), increasing the model’s generalizability. The mod- catches (Fig. 1), but note that it leads to a progressive decrease eled fish productivity response to anthropogenic climate change of fish biomass (45, 82) that is pessimistic. Indeed, while there is in BOATS agrees well with fish population-based (rather than evidence of widespread biomass depletion worldwide (34, 83, ecosystem-based) estimates (23, 74). This, together with the use 84), current management methods have curtailed overfishing 29754 | www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Scherrer et al. effort), that a larger war would cause larger increases, and that the prices and costs could eventually return to the prewar level. Further socioeconomic scenario development could explicitly address such counteracting effects and potential responses in the spheres of governance, markets, and fisheries technologies (86). Resilience of Fisheries in the Face of Large-Scale Shocks. The findings presented here are instructive for understanding possible global fisheries responses also under other shocks, both climatic and market-related. Large-scale volcanic eruptions would cause similar climatic perturbations (Table 1) with the associated ef- fects on ecosystems and food production systems, while global fuel crises or food price spikes may also arise due to other factors (87). Volcanic eruptions large enough to have substantial global impacts have a global return period of about 500 to 1,000 y but are unpredictable and have been associated with widespread famine and plagues (29, 88–91). Furthermore, the unfolding COVID-19 pandemic is expected to cause a global food emer- gency (92), which is already having diverse and rapidly evolving impacts on fisheries (93). Beyond crises, fish prices have been rising over the past 20 y (58, 94), and intensified demand, for example mediated by a slowdown of aquaculture growth (32), could induce intensified fishing if unregulated. Most importantly, our results show that poorly managed ENVIRONMENTAL fisheries have a much lower capacity to contribute to global food emergencies than do well-managed fisheries (Fig. 6). For a short SCIENCES pulse in fishing intensity, the magnitude of this emergency catch potential is essentially proportional to the management-induced increase of fish biomass left in the ocean. Thus, management interventions that increase the biomass of fish globally help to buffer against food shocks. This result shows that effective fish- eries management serves not only to achieve sustainability (34, SUSTAINABILITY 50), but also provides a proactive contribution to the resilience of Fig. 6. Contribution of well-regulated fisheries to postwar food security. (A) Catch anomaly (percentage) relative to the BAU control (dashed line), and the global food supply. Beyond showing how global marine SCIENCE (B) the associated anomaly for commercially targeted fish biomass. Both fisheries are impacted by climatic and socioeconomic perturba- panels show trajectories under the 150-Tg and intensified fishing (F+) sce- tions after a nuclear war, our generalizable findings thus also add nario and contrast the impact of strong (green) vs. no (blue) prewar fisheries to the imperative of effective fisheries management (95). regulation. Despite the substantial negative impact of the 150-Tg soot input (Fig. 2A), strong prewar regulations allow a many-fold catch increase im- Materials and Methods mediately after the war by providing a large buffer of fish biomass. To explore the potential impacts of nuclear conflicts on fisheries, we inves- tigate six climatic perturbations of regional and larger-scale nuclear wars (Table 1) (3, 15), an ensemble mean of three control climate runs without soot injection, and five socioeconomic fishing responses (Table 2). The cli- and increased biomass to a significant degree in more than half mate control run is first used to create the prewar fisheries baseline up until of the fisheries where stock assessments are made (which 2019. Using the state of the fishery in 2019 as the initial condition, we model themselves make up 40 to 50% of the total global fish catch) how a nuclear war in the following year (year 1 postconflict), with and (35). Thus, the fisheries in several well-managed regions would without accompanying changes in fishing behavior, impacts global fish respond more like in the simulation with a strongly regulated biomass and catches. global fishery prewar (Fig. 6 and SI Appendix, Fig. S9). Furthermore, we emphasize that the impacts that nuclear Climatic Perturbations after Nuclear War. The climate impacts of nuclear war conflicts themselves might have on the effectiveness of man- are modeled using the CESM, version 1.3, a state-of-the-art coupled climate agement are highly unpredictable, but potentially important. model consisting of atmosphere, ocean, land, and sea ice components. CESM Lack of resources for fisheries regulation, stronger incentives for implements the Parallel Ocean Program physical ocean model (96), here at nominal 1° horizontal resolution and with 60 vertical levels, and the Bio- illegal fishing, and collapse of international management orga- geochemical Elemental Cycling (BEC) ocean ecosystem–biogeochemistry nizations could impair management. On the other hand, war module, which represents the lower trophic levels of the marine ecosystem, fosters increased (parochial) cooperative behavior, which is a key and a dynamic iron cycle (51, 97–101). Similar to other Coupled Model In- element in effective fisheries management (85). This, or strict tercomparison Project (CMIP) class models (102, 103), BEC simulates three war-induced (possibly military) protection of countries’ exclusive phytoplankton functional types: diatoms, small phytoplankton, and diazo- economic zones (EEZs) and their marine food resources could trophs as well as one zooplankton functional type. The productivity (carbon actually improve management effectiveness. fixation) of the three phytoplankton groups are combined to generate NPP Since the realized effect of nuclear war on global fishing be- (104), which is used, along with model-derived sea surface temperature, to Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 havior is highly uncertain, the socioeconomic scenarios were drive the offline fisheries model. The CESM-BEC ecosystem and biogeo- chemistry model is well validated in a variety of scenarios and performs chosen to bracket a large possible range of alternative behaviors. favorably when compared with other CMIP class models (e.g., refs. 101, 105, This approach provides a generalizable understanding of the and 106, and references therein). system’s response to perturbations, but not a prediction of the The climatic response to nuclear war is simulated by injecting black carbon most likely outcome. Consequently, the socioeconomic scenarios (soot) into the atmosphere above the South Asian subcontinent (India and generally have a larger impact on global catches than the climatic Pakistan exchange) (3), or over the United States and Russia (15). Atmo- perturbation (Fig. 2B). We speculate that a war might increase spheric circulation and chemistry is simulated in CESM using the WACCM both fish prices and fishing costs (with opposing effects on fishing (107) with nominal 2° resolution and 66 vertical levels, a model top at ∼145 km, Scherrer et al. PNAS | November 24, 2020 | vol. 117 | no. 47 | 29755 and uses the Rapid Radiative Transfer Model for GCMs (108) for the radiative regulation component described in ref. 46, and assume strong regulation transfer. The Community Aerosol and Radiation Model for Atmospheres (109, effectiveness (S = 10) and regulation toward the local MSY target (EMSY,k). 110) is coupled with WACCM to simulate the injection, lofting, advection, and EMSY,k is estimated for the long-term monthly mean of the climate control removal of soot aerosols in the troposphere and stratosphere, and their sub- from CESM in each grid cell. This approach results in global catch and bio- sequent impact on climate (111). The India–Pakistan scenarios (5 to 47 Tg; Ta- mass trajectories similar to the unregulated baseline, but with higher catch ble 1) and United States–Russia scenario (150 Tg) build on previous work by and biomass in the last decades thanks to strong management (SI Appendix, Mills et al. and Miller et al. (12, 14) and Robock et al. (29), respectively. Fig. S8). Global Fisheries Model. The BOATS model is used to estimate climatic and Socioeconomic Responses. Due to the large uncertainty of the effects of a socioeconomic impacts on global marine fish biomass and catch through time. nuclear war on global fishing behavior, we here use simple, exploratory We use the model thoroughly described in previous publications (43–45), with socioeconomic responses. We modify two of the key economic model forc- improved accuracy of fish biomass in high-nutrient, low-chlorophyll regions ings, ex-vessel price of fish (p) and cost of fishing effort (c), to induce in- (112) and a newly developed regulation component from (46). BOATS calcu- tensified or decreasing fishing as a response to a nuclear war. Intensified lates fish biomass of three independent fish groups categorized as small, me- fishing is modeled by an instantaneous step increase in p, either a doubling dium, and large fish (defined by maximum sizes of 0.3, 8.5, and 100 kg, (F+) or a factor-of-5 increase (F++) in the year of the war. Decreased fishing is respectively) in noninteracting oceanic grid cells with a 1° horizontal resolution. modeled here by an instantaneous twofold (F−) or fivefold (F−−) step in- Fish in each group grow to their maximum size from a common smallest size crease in c. Finally, as a comparison, we model a BAU scenario where c and p (0.01 kg) along the so-called size spectrum (113), and the resulting biomass remain unchanged throughout the war scenarios. When investigating the depends on the amount of energy available from oceanic NPP, temperature- effect of preemptive management, we use the BAU, F+, and F++ scenarios dependent metabolic growth and mortality rates, the fraction of energy allo- combined with an immediate reduction of the regulation effectiveness to cated to reproduction, and reproductive success (43). Gridded maps of vertically zero (S = 0). Reduced regulation effectiveness is not necessarily the most integrated NPP along with sea surface temperature from CESM are used as likely socioeconomic response (Uncertainties and Limitations), but was ap- input to the model. We underline that BOATS resolves only the subset of plied for consistency with the other postwar scenarios. In all simulations, marine fish biomass that has been targeted by fisheries, for which model es- fishing effort evolves dynamically with a monthly time step, in response to timates can be compared with and constrained by global catch data (33). the changes in p, c, q, and Bk (Eq. 1). In BOATS, fishing effort evolves dynamically in each grid cell and fish size The cost and price increases used here (two and five times) were guided by group, responding to changes in the biomass and the model’s economic the sparse available observations. First, the increases are substantially higher forcings (44, 46). As is common in models simulating fishing activity (114), it than historical variations (56, 94, 115, 118), since there is a large potential for is assumed that profit is a main driver of fishing behavior, but also that extensive socioeconomic changes postwar. In particular, the risk of unprec- fishing behavior can be more or less strongly influenced by regulation edented food shortage even under the 5-Tg emission scenario (28), the relatively high volatility of fuel prices (119), and the hundredfold intensifi- (management). BOATS represents the effort put into fishing each of the cation of fishing recorded in one region after the Tambora eruption (41), three fish size groups (k = 1, 2, 3) as nominal fishing effort, Ek (in watts per warrant an investigation of large variations. Still, intensified fishing requires square meter; reflecting the boat power), which evolves over time as a real fishing capital; boats, gears, and crews. Although the substantial over- function of the average profit, the regulation target for fishing effort, Etarg,k capacity present in many regions today could be mobilized postwar, the (in watts per square meter), and the regulation effectiveness S (dimension- need for capital still constrains fisheries expansion. Therefore, we do not less; S ≥ 0) in a grid cell: investigate higher price increases. dEk revenuek − costk −S = Ke e + Ks (Etarg,k − Ek )(1 − e−S ) Model Runs. Impacts of nuclear conflict and accompanying behavioral dt Ek pqEk Bk − cEk −S changes in the fishery were modeled for a 15-y period postwar using a total of = Ke e + Ks (Etarg,k − Ek )(1 − e−S ), [1] Ek seven soot inputs (including the controls) and five socioeconomic responses. We use the combination of BAU fishing and unchanged climate conditions—the where p is the ex-vessel price of fish (the price at which the catch is sold “BAU control”—for comparison with all other scenarios, generating the percent when it first enters the supply chain; $·grams wet biomass−1), c is the cost per changes given in the results. In addition, we simulate the impact of the unit of fishing effort ($·watts−1·second−1), q is the catchability (meters2·- climate scenarios on fish biomass in an unfished global ocean (see SI Ap- watts−1·second−1), Bk is the fish biomass (grams wet biomass·meter−2), Ke pendix, Impacts of nuclear war on the unfished ocean and Fig. S7), and the (watts2·meter−2·$−1) is the fleet dynamics parameter (which scales the rate of impact of the BAU, F+, and F++ scenarios on a strongly regulated global effort change with respect to profit), and Ks (meters2·second−1) is the reg- fishery (Fig. 6 and SI Appendix, Fig. S9). To estimate the uncertainty in ulation response parameter (which scales the rate of effort change with BOATS model predictions, each of the model runs (including the prewar respect to regulation). The catch is the product qEkBk, where the catchability baselines) was repeated five times using different sets of parameter com- q reflects the effectiveness with which a given unit of fishing effort catches binations derived from the model calibration process (44) (values given in fish, and incorporates both gear technologies, fish finding or aggregating table S1 of ref. 45). The five different parameter sets (the parameter en- technologies, and skill and knowledge of the crew. semble) span a large range of the possible parameter space (SI in ref. 45), As Eq. 1 states, the key factors determining the level of fishing effort in BOATS and results are presented with the ensemble mean and SD. are Bk, p, c, and q (44) and the regulation parameters Etarg,k and S. If S approaches zero (no regulation), the nominal fishing effort will decrease if c increases (in- EEZ Catch Changes and Marine Ecosystem Dependence. The total catch change creasing total cost), and increase if p or Bk increase (increasing revenue), all else is calculated for each EEZ by summing over the area, taking the average of the being equal. In line with the theory of open access fisheries (80, 81), at unregu- ensemble runs and over the first 5 y postwar. We use the country-level nu- lated equilibrium fishing effort stabilizes at a level that generates zero profit. tritional dependence from ref. 47 to indicate vulnerability, or the integrated dependence on marine ecosystems for countries lacking values for nutri- Prewar Fisheries Baseline. We use BOATS with simple historical representa- tional dependence. Dependent territories lacking data in ref. 47 were tions of fish price, fishing cost, and catchability, to create a prewar fisheries assigned the same value as their controlling central state. Disputed areas baseline simulation determining the prewar state of fisheries and ecosystems. and joint regime areas were excluded from the analysis in Fig. 5B. Based on the findings in ref. 45, the prewar fisheries trajectory is hindcasted by forcing the model with constant c (1.8 × 10−4 $ kW−1), constant p (1.1 $ Data Availability. Model output data and code for the fisheries model have kg−1), increasing q (5% y−1), and no regulation (S = 0), with the climate been deposited in Zenodo repositories (http://doi.org/10.5281/zenodo.4110876 Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 control from CESM as input. Although these socioeconomic approximations and http://doi.org/10.5281/zenodo.4117477). are simplistic, they are within the ranges of empirical estimates (82, 115–117), and reproduce the historical evolution of global fisheries, with an increase, plateau, and slight decline of global catches and a continuous ACKNOWLEDGMENTS. This work is funded by the European Research decrease in global fish biomass (Fig. 1). The global distribution of fish bio- Council under the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 682602, with partial support from the mass and fishing effort in model year 2019 are saved to use as initial con- Spanish Ministry of Science, Innovation and Universities, through the ditions for the nuclear war simulations. Acciones de Programacion Conjunta Internacional (PCIN-2017-115), and To investigate the benefits of strong preemptive fisheries management, from the Open Philanthropy Project. We thank two anonymous reviewers we create an alternative prewar simulation. We use the dynamic fisheries for constructive comments that helped improve this manuscript. 29756 | www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Scherrer et al. 1. A. Robock, O. B. Toon, Self-assured destruction: The climate impacts of nuclear war. 38. N. S. Lovenduski et al., The potential impact of nuclear conflict on ocean acidifica- Bull. At. Sci. 68, 66–74 (2012). tion. Geophys. Res. Lett. 47, e2019GL086246 (2020). 2. O. B. Toon, A. Robock, M. Mills, L. Xia, Asia treads the nuclear path, unaware that 39. A. Mottet et al., Livestock: On our plates or eating at our table? A new analysis of self-assured destruction would result from nuclear war. J. Asian Stud. 76, 437–456 the feed/food debate. Glob. Food Secur. 14, 1–8 (2017). (2017). 40. SAPEA, “Food from the oceans—how can more food and biomass be obtained from 3. O. B. Toon et al, Rapidly expanding nuclear arsenals in Pakistan and India portend the oceans in a way that does not deprive future generations of their benefits?” regional and global catastrophe. Sci. Adv. 5, eaay5478 (2019). (Evidence Review Report No. 1, SAPEA, Berlin, 2017). 4. H. M. Kristensen, “Global nuclear arsenals, 1990–2018” in Nuclear Safeguards, Se- 41. K. E. Alexander et al., Tambora and the mackerel year: Phenology and fisheries curity, and Nonproliferation, J. E. Doyle, Ed. (Butterworth-Heinemann, ed. 2, 2019), during an extreme climate event. Sci. Adv. 3, e1601635 (2017). chap. 1, pp. 3–35. 42. D. Beare, F. Hölker, G. H. Engelhard, E. McKenzie, D. G. Reid, An unintended ex- 5. BBC News, Russia deploys Avangard hypersonic missile system. BBC News (27 De- periment in fisheries science: A marine area protected by war results in Mexican cember 2019). https://www.bbc.com/news/world-europe-50927648. Accessed 27 June waves in fish numbers-at-age. Naturwissenschaften 97, 797–808 (2010). 2020. 43. D. A. Carozza, D. Bianchi, E. D. Galbraith, The ecological module of BOATS-1.0: A 6. SIPRI, SIPRI Yearbook 2020 (SIPRI, 2020). https://www.sipri.org/sites/default/files/ bioenergetically constrained model of marine upper trophic levels suitable for 2020-06/yb20_summary_en_v2.pdf. Accessed 27 June 2020. studies of fisheries and ocean biogeochemistry. Geosci. Model Dev. 9, 1545–1565 7. J. Mecklin, Why nuclear weapons should be a major focus of the 2020 campaign. (2016). Bull. At. Sci. 76, 1–2 (2020). 44. D. A. Carozza, D. Bianchi, E. D. Galbraith, Formulation, general features and global 8. P. Pulla, India-Pakistan nuclear escalation: Where could it lead? Nature 573, 16–17 calibration of a bioenergetically-constrained fishery model. PLoS One 12, e0169763 (2019). (2017). 9. P. J. Crutzen, J. W. Birks, The atmosphere after a nuclear war: Twilight at noon. 45. E. D. Galbraith, D. A. Carozza, D. Bianchi, A coupled human–Earth model perspective Ambio 11, 114–125 (1982). on long-term trends in the global marine fishery. Nat. Commun. 8, 14884 (2017). 10. R. P. Turco, O. B. Toon, T. P. Ackerman, J. B. Pollack, C. Sagan, Nuclear winter: Global 46. K. Scherrer, E. Galbraith, Regulation strength and technology creep play key roles in consequences of multiple nuclear explosions. Science 222, 1283–1292 (1983). global long-term projections of wild-capture fisheries. ICES J. Mar. Sci., 2020, fsaa109 11. O. B. Toon et al., Atmospheric effects and societal consequences of regional scale (2020). nuclear conflicts and acts of individual nuclear terrorism. Atmos. Chem. Phys. 7, 47. E. R. Selig et al., Mapping global human dependence on marine ecosystems. Conserv. 1973–2002 (2007). Lett. 12, e12617 (2018). 12. M. J. Mills, O. B. Toon, R. P. Turco, D. E. Kinnison, R. R. Garcia, Massive global ozone 48. D. A. Carozza, D. Bianchi, E. D. Galbraith, Metabolic impacts of climate change on loss predicted following regional nuclear conflict. Proc. Natl. Acad. Sci. U.S.A. 105, marine ecosystems: Implications for fish communities and fisheries. Glob. Ecol. Bio- 5307–5312 (2008). geogr. 28, 158–169 (2019). 13. P. Yu et al., Black carbon lofts wildfire smoke high into the stratosphere to form a 49. W. W. L. Cheung, G. Reygondeau, T. L. Frölicher, Large benefits to marine fisheries of ENVIRONMENTAL persistent plume. Science 365, 587–590 (2019). meeting the 1.5°C global warming target. Science 354, 1591–1594 (2016). 14. G. H. Miller et al., Abrupt onset of the Little Ice Age triggered by volcanism and 50. S. D. Gaines et al., Improved fisheries management could offset many negative ef- sustained by sea-ice/ocean feedbacks. Geophys. Res. Lett. 39, L02708 (2012). fects of climate change. Sci. Adv. 4, eaao1378 (2018). SCIENCES 15. J. Coupe, C. G. Bardeen, A. Robock, O. B. Toon, Nuclear winter responses to nuclear 51. J. K. Moore, S. C. Doney, K. Lindsay, Upper ocean ecosystem dynamics and iron cy- war between the United States and Russia in the Whole Atmosphere Community cling in a global three-dimensional model. Global Biogeochem. Cycles 18, GB4028 Climate Model Version 4 and the Goddard Institute for Space Studies ModelE. (2004). J. Geophys. Res. - Atmospheres 124, 8522–8543 (2019). 52. L. Kwiatkowski, O. Aumont, L. Bopp, Consistent trophic amplification of marine 16. M. J. Mills, O. B. Toon, J. Lee‐Taylor, A. Robock, Multidecadal global cooling and biomass declines under climate change. Glob. Change Biol. 25, 218–229 (2019). unprecedented ozone loss following a regional nuclear conflict. Earth’s Future 2, 53. J. P. Dunne, R. A. Armstrong, A. Gnanadesikan, J. L. Sarmiento, Empirical and 161–176 (2014). mechanistic models for the particle export ratio. Global Biogeochem. Cycles 19, SUSTAINABILITY 17. F. S. R. Pausata, L. Chafik, R. Caballero, D. S. Battisti, Impacts of high-latitude volcanic GB4026 (2005). eruptions on ENSO and AMOC. Proc. Natl. Acad. Sci. U.S.A. 112, 13784–13788 (2015). 54. P. Lehodey et al., Climate variability, fish, and fisheries. J. Clim. 19, 5009–5030 (2006). 18. A. Robock et al., Climatic consequences of regional nuclear conflicts. Atmos. Chem. 55. J. Guiet, E. Galbraith, D. Kroodsma, B. Worm, Seasonal variability in global industrial SCIENCE Phys. 7, 2003–2012 (2007). fishing effort. PLoS One 14, e0216819 (2019). 19. M. Sigl et al., Timing and climate forcing of volcanic eruptions for the past 56. D. A. Kroodsma et al., Tracking the global footprint of fisheries. Science 359, 2,500 years. Nature 523, 543–549 (2015). 904–908 (2018). 20. M. O. Chikamoto et al., Intensification of tropical Pacific biological productivity due 57. E. E. Butler, N. D. Mueller, P. Huybers, Peculiarly pleasant weather for US maize. Proc. to volcanic eruptions. Geophys. Res. Lett. 43, 1184–1192 (2016). Natl. Acad. Sci. U.S.A. 115, 11935–11940 (2018). 21. Y. A. Eddebbar et al., El Niño–like physical and biogeochemical ocean response to 58. FAO, Food Outlook: Biannual Report on Global Food Markets (FAO, Rome, 2018). tropical eruptions. J. Clim. 32, 2627–2649 (2019). 59. FAO, Food Balance Sheets—A Handbook (FAO, Rome, 2001). 22. IPCC, “Technical summary” in IPCC Special Report on the Ocean and Cryosphere in a 60. J. S. Brashares et al., Bushmeat hunting, wildlife declines, and fish supply in West Changing Climate, H.-O. Pörtner et al., Ed. (IPCC, 2019), pp. 39–69. Africa. Science 306, 1180–1183 (2004). 23. H. K. Lotze et al., Global ensemble projections reveal trophic amplification of ocean 61. W. P. Cropper Jr, M. A. Harwell, “Chapter 5. Food availability after a nuclear war” biomass declines with climate change. Proc. Natl. Acad. Sci. U.S.A. 116, 12907–12912 in The Environmental Consequences of Nuclear War (SCOPE 28), , M. A. Harwell, (2019). T. C. Hutchinson, Eds. (Ecological, Agricultural, and Human Effects, 1985), vol. 2, 24. P. R. Ehrlich et al., Long-term biological consequences of nuclear war. Science 222, pp. 359–426. 1293–1300 (1983). 62. D. C. Denkenberger, J. M. Pearce, Feeding everyone: Solving the food crisis in event 25. M. Özdoğan, A. Robock, C. J. Kucharik, Impacts of a nuclear war in South Asia on of global catastrophes that kill crops or obscure the sun. Futures 72, 57–68 (2015). soybean and maize production in the Midwest United States. Clim. Change 116, 63. I. Kryshev, Radioactive contamination of aquatic ecosystems following the Cher- 373–387 (2013). nobyl accident. J. Environ. Radioact. 27, 207–219 (1995). 26. L. Xia, A. Robock, Impacts of a nuclear war in South Asia on rice production in 64. K. Buesseler et al., Fukushima daiichi-derived radionuclides in the ocean: Transport, Mainland China. Clim. Change 116, 357–372 (2013). fate, and impacts. Annu. Rev. Mar. Sci. 9, 173–203 (2017). 27. L. Xia, A. Robock, M. Mills, A. Stenke, I. Helfand, Decadal reduction of Chinese ag- 65. H. D. Grover, M. A. Harwell, Biological effects of nuclear war II: Impact on the bio- riculture after a regional nuclear war. Earths Futur. 3, 37–48 (2015). sphere. Bioscience 35, 576–583 (1985). 28. J. Jägermeyr et al., A regional nuclear conflict would compromise global food se- 66. WHO, Nuclear accidents and radioactive contamination of foods (WHO, 2011). curity. Proc. Natl. Acad. Sci. U.S.A. 117, 7071–7081 (2020). https://www.who.int/publications/m/item/nuclear-accidents-and-radioactive-contamination- 29. A. Robock, L. Oman, G. L. Stenchikov, Nuclear winter revisited with a modern climate of-foods. Accessed 21 October 2020. model and current nuclear arsenals: Still catastrophic consequences. J. Geophys. 67. H. D. Livingston, P. P. Povinec, Anthropogenic marine radioactivity. Ocean Coast. Res. - Atmos. 112, D13107 (2007). Manage. 43, 689–712 (2000). 30. E. H. Allison et al., Vulnerability of national economies to the impacts of climate 68. E. Ilus, The Chernobyl accident and the Baltic Sea. Boreal Environ. Res. 12, 1–10 change on fisheries. Fish Fish. 10, 173–196 (2009). (2007). 31. C. D. Golden et al., Nutrition: Fall in fish catch threatens human health. Nature 534, 69. S. Jennings, K. Collingridge, Predicting consumer biomass, size-structure, production, 317–320 (2016). catch potential, responses to fishing and associated uncertainties in the world’s 32. FAO, The State of World Fisheries and Aquaculture: Meeting the Sustainable De- marine ecosystems. PLoS One 10, e0133794 (2015). velopment Goals (FAO, Rome, 2018). 70. Y. M. Bar-On, R. Phillips, R. Milo, The biomass distribution on Earth. Proc. Natl. Acad. Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 33. D. Pauly, D. Zeller, Catch reconstructions reveal that global marine fisheries catches Sci. U.S.A. 115, 6506–6511 (2018). are higher than reported and declining. Nat. Commun. 7, 10244 (2016). 71. M. A. St. John et al., A dark hole in our understanding of marine ecosystems and 34. C. Costello et al., Global fishery prospects under contrasting management regimes. their services: Perspectives from the mesopelagic community. Front. Mar. Sci. 3, 31 Proc. Natl. Acad. Sci. U.S.A. 113, 5125–5129 (2016). (2016). 35. R. Hilborn et al., Effective fisheries management instrumental in improving fish stock 72. A. Martin et al., The oceans’ twilight zone must be studied now, before it is too late. status. Proc. Natl. Acad. Sci. U.S.A. 117, 2218–2224 (2020). Nature 580, 26–28 (2020). 36. E. Chassot et al., Global marine primary production constrains fisheries catches. Ecol. 73. United Nations, The Global Social Crisis: Report on the World Social Situation 2011 Lett. 13, 495–505 (2010). (United Nations, New York, 2011). 37. K. D. Friedland et al., Pathways between primary production and fisheries yields of 74. C. M. Free et al., Impacts of historical warming on marine fisheries production. Sci- large marine ecosystems. PLoS One 7, e28945 (2012). ence 363, 979–983 (2019). Scherrer et al. PNAS | November 24, 2020 | vol. 117 | no. 47 | 29757 75. M. A. Harwell, T. C. Hutchinson, W. P. Cropper Jr, C. C. Harwell, “Vulnerability of 99. M. C. Long, K. Lindsay, S. Peacock, J. K. Moore, S. C. Doney, Twentieth-century ecological systems to climatic effects of nuclear war” in The Environmental Conse- oceanic carbon uptake and storage in CESM1(BGC). J. Clim. 26, 6775–6800 (2013). quences of Nuclear War (SCOPE 28), Volume II, Ecological, Agricultural and Human 100. K. Lindsay et al., Preindustrial-control and twentieth-century carbon cycle experi- Effects, M. A. Harwell, T. C. Hutchinson, Eds. (Wiley, 1985), chap. 2, pp. 359–426. ments with the Earth System Model CESM1(BGC). J. Clim. 27, 8981–9005 (2014). 76. A. E. Cahill et al., How does climate change cause extinction? Proc. Biol. Sci. 280, 101. C. S. Harrison, M. C. Long, N. S. Lovenduski, J. K. Moore, Mesoscale effects on carbon 20121890 (2013). export: A global perspective. Global Biogeochem. Cycles 32, 680–703 (2018). 77. M. L. Pinsky, R. L. Selden, Z. J. Kitchel, Climate-driven shifts in marine species ranges: 102. C. Laufkötter et al., Drivers and uncertainties of future global marine primary pro- Scaling from organisms to communities. Annu. Rev. Mar. Sci. 12, 153–179 (2020). duction in marine ecosystem models. Biogeosciences 12, 6955–6984 (2015). 78. F. Baltar et al., Towards integrating evolution, metabolism, and climate change 103. C. Laufkötter et al., Projected decreases in future marine export production: The role studies of marine ecosystems. Trends Ecol. Evol. 34, 1022–1033 (2019). of the carbon flux through the upper ocean ecosystem. Biogeosciences 13, 79. K. M. Krumhardt et al., Coccolithophore growth and calcification in an acidified 4023–4047 (2016). ocean: Insights from community Earth system model simulations. J. Adv. Model. 104. K. M. Krumhardt, N. S. Lovenduski, M. C. Long, K. Lindsay, Avoidable impacts of Earth Syst. 11, 1418–1437 (2019). ocean warming on marine primary production: Insights from the CESM ensembles. 80. H. S. Gordon, The economic theory of a common-property resource: The fishery. Global Biogeochem. Cycles 31, 114–133 (2017). J. Polit. Econ. 62, 124–142 (1954). 105. A. Tagliabue et al., How well do global ocean biogeochemistry models simulate 81. G. Hardin, The tragedy of the commons. The population problem has no technical dissolved iron distributions? Global Biogeochem. Cycles 30, 149–174 (2016). solution; it requires a fundamental extension in morality. Science 162, 1243–1248 106. T. Rohr, C. Harrison, M. C. Long, P. Gaube, S. C. Doney, Eddy-modified iron, light, and (1968). phytoplankton cell division rates in the simulated Southern Ocean. Global Bio- 82. D. Squires, N. Vestergaard, Technical change in fisheries. Mar. Policy 42, 286–292 geochem. Cycles 34, e2019GB006380 (2020). (2013). 107. D. R. Marsh et al., Climate change from 1850 to 2005 simulated in CESM1(WACCM). 83. C. Costello et al., Status and solutions for the world’s unassessed fisheries. Science J. Clim. 26, 7372–7391 (2013). 338, 517–520 (2012). 108. M. J. Iacono et al., Radiative forcing by long-lived greenhouse gases: Calculations 84. M. L. D. Palomares et al., Fishery biomass trends of exploited fish populations in with the AER radiative transfer models. J. Geophys. Res. - Atmos. 113, D13103 (2008). marine ecoregions, climatic zones and ocean basins. Estuar. Coast. Shelf Sci. 243, 109. O. B. Toon, R. P. Turco, D. Westphal, R. Malone, M. Liu, A multidimensional model 106896 (2020). for aerosols: Description of computational analogs. J. Atmos. Sci. 45, 2123–2144 85. M. Bauer et al., Can war foster cooperation? J. Econ. Perspect. 30, 249–274 (2016). (1988). 86. A. Merrie, P. Keys, M. Metian, H. Österblom, Radical ocean futures-scenario devel- 110. C. G. Bardeen, O. B. Toon, E. J. Jensen, D. R. Marsh, V. L. Harvey, Numerical simu- opment using science fiction prototyping. Futures 95, 22–32 (2018). lations of the three-dimensional distribution of meteoric dust in the mesosphere 87. S. Baum, D. C. Denkenberger, J. M. Pearce, A. Robock, R. Winkler, Resilience to and upper stratosphere. J. Geophys. Res. - Atmos. 113, D17202 (2008). Global Food Supply Catastrophes (Social Science Research Network, 2015). 111. C. G. Bardeen, R. R. Garcia, O. B. Toon, A. J. Conley, On transient climate change at 88. R. B. Stothers, Mystery cloud of AD 536. Nature 307, 344–345 (1984). the Cretaceous-Paleogene boundary due to atmospheric soot injections. Proc. Natl. 89. R. B. Stothers, Volcanic dry fogs, climate cooling, and plague pandemics in Europe and the Middle East. Clim. Change 42, 713–723 (1999). Acad. Sci. U.S.A. 114, E7415–E7424 (2017). 90. C. Newhall, S. Self, A. Robock, Anticipating future volcanic explosivity index (VEI) 7 112. E. D. Galbraith, P. Le Mézo, G. Solanes Hernandez, D. Bianchi, D. Kroodsma, Growth eruptions and their chilling impacts. Geosphere 14, 572–603 (2018). limitation of marine fish by low iron availability in the open ocean. Front. Mar. Sci. 6, 91. P. Papale, Global time-size distribution of volcanic eruptions on Earth. Sci. Rep. 8, 509 (2019). 6838 (2018). 113. K. H. Andersen, N. S. Jacobsen, K. D. Farnsworth, The theoretical foundations for size 92. United Nations, Policy brief: The impact of COVID-19 on food security and nutrition spectrum models of fish communities. Can. J. Fish. Aquat. Sci. 73, 575–588 (2015). (2020). https://unsdg.un.org/resources/policy-brief-impact-covid-19-food-security- 114. I. E. van Putten et al., Theories and behavioural drivers underlying fleet dynamics and-nutrition. Accessed 21 October 2020. models. Fish Fish. 13, 216–235 (2012). 93. FAO, “Q&A: COVID-19 pandemic—impact on fisheries and aquaculture” (Food and 115. U. R. Sumaila, A. D. Marsden, R. Watson, D. Pauly, A global ex-vessel fish price da- Agriculture Organization of the United Nations, 2020). www.fao.org/2019-ncov/q- tabase: Construction and applications. J Bioecon 9, 39–51 (2007). and-a/impact-on-fisheries-and-aquaculture/en/. Accessed 21 October 2020. 116. O. R. Eigaard, P. Marchal, H. Gislason, A. D. Rijnsdorp, Technological development 94. S. Tveterås et al., Fish is food—the FAO’s fish price index. PLoS One 7, e36731 (2012). and fisheries management. Rev. Fish. Sci. Aquacult. 22, 156–174 (2014). 95. B. Worm et al., Rebuilding global fisheries. Science 325, 578–585 (2009). 117. M. Palomares, D. Pauly, On the creeping increase of vessels’ fishing power. Ecol. Soc. 96. G. Danabasoglu et al., The CCSM4 ocean component. J. Clim. 25, 1361–1389 (2011). 24, 31 (2019). 97. J. K. Moore, K. Lindsay, S. C. Doney, M. C. Long, K. Misumi, Marine ecosystem dy- 118. V. W. Y. Lam, U. R. Sumaila, A. Dyck, D. Pauly, R. Watson, Construction and first namics and biogeochemical cycling in the community Earth system model [CESM1(BGC)]: applications of a global cost of fishing database. ICES J. Mar. Sci. 68, 1996–2004 Comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 scenarios. (2011). J. Clim. 26, 9291–9312 (2013). 119. BP, BP statistical review of world energy (BP, 2019). https://www.bp.com/content/ 98. J. K. Moore et al., Sustained climate warming drives declining marine biological dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/ productivity. Science 359, 1139–1143 (2018). bp-stats-review-2019-full-report.pdf. Accessed 21 October 2020. Downloaded at Universitat Autonoma de Barcelona (UAB) on April 14, 2021 29758 | www.pnas.org/cgi/doi/10.1073/pnas.2008256117 Scherrer et al.