McLaughlin Chloee M, Shi Yuning, Viswanathan Vishnu, Sawers Ruairidh, Kemanian Armen R, Lasky Jesse R
Intercollege Graduate Degree Program in Plant Biology, Pennsylvania State University, University Park, PA 16802.
Department of Biology, Pennsylvania State University, University Park, PA 16802.
bioRxiv. 2025 Feb 20:2024.05.18.594591. doi: 10.1101/2024.05.18.594591.
Aerosol-producing global catastrophes such as nuclear war, super-volcano eruption, or asteroid strike, although rare, pose a serious threat to human survival. Light-absorbing aerosols would sharply reduce temperature and solar radiation reaching the earth's surface, decreasing crop productivity including for locally adapted traditional crop varieties, i.e. landraces. Here, we test post-catastrophic climate impacts on barley, maize, rice, and sorghum, four crops with extensive landrace cultivation, under a range of nuclear war scenarios that differ in the amount of black carbon aerosol (soot) injected into the climate model. We used a crop growth model to estimate gradients of environmental stressors that drive local adaptation. We then fit genotype environment associations using high density genomic markers with gradient forest offset (GF offset) methods and predicted maladaptation through time. As a validation, we found that our GF models successfully predicted local adaptation of maize landraces in multiple common gardens across Mexico. We found strong concordance between GF offset and disruptions in climate, and landraces of all tested crop species were predicted to be the most maladapted across space and time where soot-induced climate change was the greatest. We further used our GF models to identify landrace varieties best matched to specific post-catastrophic conditions, indicating potential substitutions for agricultural resilience. We found the best landrace genotype was often far away or in another nation, though countries with more climatic diversity had better within-country substitutions. Our results highlight that a soot-producing catastrophe would result in the global maladaptation of landraces and suggest that current landrace adaptive diversity is insufficient for agricultural resilience in the case of the soot scenarios with the greatest change to climate.
诸如核战争、超级火山爆发或小行星撞击等产生气溶胶的全球性灾难，尽管罕见，但对人类生存构成严重威胁。吸光气溶胶会大幅降低到达地球表面的温度和太阳辐射，降低包括当地适应性传统作物品种（即地方品种）在内的作物生产力。在此，我们在一系列核战争情景下，测试了灾难性气候对大麦、玉米、水稻和高粱这四种广泛种植地方品种的作物的影响，这些情景在注入气候模型的黑碳气溶胶（烟尘）量上有所不同。我们使用作物生长模型来估计驱动当地适应性的环境压力梯度。然后，我们使用高密度基因组标记和梯度森林偏移（GF偏移）方法拟合基因型与环境的关联，并预测随时间的适应不良情况。作为验证，我们发现我们的GF模型成功预测了墨西哥多个共同园圃中玉米地方品种的当地适应性。我们发现GF偏移与气候干扰之间存在很强的一致性，并且预计所有测试作物物种的地方品种在烟尘引起气候变化最大的时空范围内适应不良最为严重。我们进一步使用我们的GF模型来确定最适合特定灾难性后条件的地方品种，这表明了农业恢复力的潜在替代品种。我们发现最佳的地方品种基因型往往距离很远或在另一个国家，不过气候多样性更高的国家在国内有更好的替代品种。我们的结果突出表明，产生烟尘的灾难将导致地方品种在全球范围内适应不良，并表明在对气候影响最大的烟尘情景下，当前地方品种的适应性多样性不足以实现农业恢复力。
