In a nuclear war, volcanic eruption, asteroid or comet impact that causes an abrupt sunlight reduction scenario (ASRS), agricultural yields would plummet. Global society is currently unprepared for such an event, implying an urgent need for evaluation and prioritization of solutions. We show effective deployment of resilient food solutions appears sufficient to fulfill global energy and macronutrient food requirements, potentially saving billions from famine. A Monte Carlo analysis of resilient food outcomes, using a linear optimization model, shows a 95% probability of global food availability between 2,100 and 3,500 Kcals per capita per day in a nuclear winter scenario involving 150 Tg of soot in the stratosphere. Our analysis indicates nutritionally sufficient diets from resilient foods would be widely affordable, costing US$1.73 daily, though subsidization could be needed across Southern Asia and Sub-Saharan Africa. Post-disaster conflict or insufficient international cooperation could increase costs and reduce output, hampering effective resilient food deployment.

Extreme solar storms, high-altitude electromagnetic pulses, and coordinated cyber attacks could disrupt regional/global electricity. Since electricity basically drives industry, industrial civilization could collapse without it. This could cause anthropological civilization (cities) to collapse, from which humanity might not recover, having long-term consequences. Previous work analyzed technical solutions to save nearly everyone despite industrial loss globally, including transition to animals powering farming and transportation. The present work estimates cost-effectiveness for the long-term future with a Monte Carlo (probabilistic) model. Model 1, partly based on a poll of Effective Altruism conference participants, finds a confidence that industrial loss preparation is more cost-effective than artificial general intelligence safety of ~ 88% and ~ 99+% for the 30 millionth dollar spent on industrial loss interventions and the margin now, respectively. Model 2 populated by one of the authors produces ~ 50% and ~ 99% confidence, respectively. These confidences are likely to be reduced by model and theory uncertainty, but the conclusion of industrial loss interventions being more cost-effective was robust to changing the most important 4–7 variables simultaneously to their pessimistic ends. Both cause areas save expected lives cheaply in the present generation and funding to preparation for industrial loss is particularly urgent.

No abstract

In the event of an abrupt sunlight reduction scenario, there is a time window that occurs between when food stores would likely run out for many countries (~6 months or less) and ~1 year when resilient foods are scaled up. A promising temporary resilient food is leaf protein concentrate (LPC). Although it is possible to extract LPC from tree biomass (e.g., leaves and needles), neither the yields nor the toxicity of the protein concentrates for humans from the most common tree species has been widely investigated. To help fill this knowledge gap, this study uses high-resolution mass spectrometry and an open-source toolchain for non-targeted screening of toxins on five common North American coniferous species: Western Cedar, Douglas Fir, Ponderosa Pine, Western Hemlock, and Lodgepole Pine. The yields for LPC extraction from the conifers ranged from 1% to 7.5%. The toxicity screenings confirm that these trees may contain toxins that can be consumed in small amounts, and additional studies including measuring the quantity of each toxin are needed. The results indicate that LPC is a promising candidate to be used as resilient food, but future work is needed before LPCs from conifers can be used as a wide-scale human food.

Global agricultural catastrophes, which include nuclear winter and abrupt climate change, could have long-term consequences on humanity such as the collapse and nonrecovery of civilization. Using Monte Carlo (probabilistic) models, we analyze the long-term cost-effectiveness of resilient foods (alternative foods) - roughly those independent of sunlight such as mushrooms. One version of the model populated partly by a survey of global catastrophic risk researchers finds the confidence that resilient foods is more cost effective than artificial general intelligence safety is ~86% and ~99% for the 100 millionth dollar spent on resilient foods at the margin now, respectively. Another version of the model based on one of the authors produced ~95% and ~99% confidence, respectively. Considering uncertainty represented within our models, our result is robust: reverting the conclusion required simultaneously changing the 3-5 most important parameters to the pessimistic ends. However, as predicting the long-run trajectory of human civilization is extremely difficult, and model and theory uncertainties are very large, this significantly reduces our overall confidence. Because the agricultural catastrophes could happen immediately and because existing expertise relevant to resilient foods could be co-opted by charitable giving, it is likely optimal to spend most of the money for resilient foods in the next few years. Both cause areas generally save expected current lives inexpensively and should attract greater investment.

The digital transformation of societies has been a core concern for the information systems (IS) research community since its emergence. While most of this work has had a positive outlook, recently a stronger focus on the unintended consequences and dark side of digitalization has come to the fore. This paper contributes to this emerging stream of research by zooming in on a heretofore unrecognized question with potentially catastrophic consequences: What happens to our increasingly digitalized societies when a pro-longed blackout causes a large fraction of digital systems and services to stop working for an extended period of time? To answer this motivating question, we conducted two system dynamics-based simulation experiments to tease out how different degrees of digitalization in a society would affect the resilience of the food system in the face of two different, extreme but plausible prolonged blackout scenarios. We find that a high degree of digitalization has a strong significant negative impact on food system resilience in the investigated scenarios. In the discussion of our findings, we conceptualize “the risk of digital fragility” as the underlying driver of the observed results. Moving forward, we suggest seven mitigation strategies for the risk of digital fragility as fruitful avenues for future research.

African countries have been severely affected by food insecurity such that 54% of the population (73 million people) are acutely food insecure, in crisis or worse. Recent work has found technical potential for feeding humanity during global catastrophes using leaves as stop-gap alternative foods. To determine the potential for adopting agricultural residue (especially crop leaves) as food in food-insecure areas, this study provides a new methodology to quantify the calories available from agricultural residue as alternative foods at the community scale. A case study is performed on thirteen communities in Nigeria to compare national level values to those available in rural communities. Two residue utilization cases were considered, including a pessimistic and an optimistic case for human-edible calories gained. Here, we show that between 3.0 and 13.8 million Gcal are available in Nigeria per year from harvesting agricultural residue as alternative food. This is enough to feed between 3.9 and 18.1 million people per year, covering from 10 to 48% of Nigeria’s current estimated total food deficit.

In the event of an abrupt sunlight reduction scenario there is a time window that occurs between when food stores would likely run out for many countries (~6 months or less) and ~1 year when resilient foods are scaled up. A promising temporary resilient food is leaf protein concentrate (LPC). Although it is possible to extract LPC from tree biomass (e.g. leaves and needles), neither the yields nor the toxicity of the protein concentrates for humans from the most common tree species has been widely investigated. To help fill this knowledge gap, this study uses high-resolution mass spectrometry and an open source toolchain for non-targeted screening of toxins on five common North American coniferous species: Western Cedar, Douglas Fir, Ponderosa Pine, Western Hemlock, and Lodgepole Pine. The yields for LPC extraction from the conifers ranged from 1% to 7.5%. The toxicity screenings confirm that these trees may contain toxins that can be consumed in small amounts and additional studies including measuring the quantity of each toxin are needed. The results indicate that LPC is a promising candidate to be used as resilient food, but future work is needed before LPCs from conifers can be used as a wide-scale human food.