Collaborative Research: CMG: Mathematical Modeling and Bayesian Analysis of Paleocommunity Collapse during Mass Extinctions

合作研究：CMG：大规模灭绝期间古群落崩溃的数学建模和贝叶斯分析

• 批准号: 0530825
• 负责人: Peter Roopnarine
• 金额: $ 18.23万
• 依托单位: California Academy of Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0530825&HistoricalAwards=false
• 关键词: Collaborative; Research; CMG; Mathematical; Modeling

The PIs propose to study the role of the shutdown of primary production, during times of mass extinction, in propagating extinction and ecosystem collapse. The disruption of primary production has been suggested as a proximal mechanism of extinction during extreme ecological crises in the Earth's past, perhaps causing avalanches of secondary extinction throughout trophic systems. The complexity of ecological networks presents a distinct challenge to understanding the pathways by which such secondary extinctions are propagated. This project will use a combined approach of numerical simulation and Bayesian statistical modeling to partition extinction due to direct effects on species, versus extinction caused by the loss of trophic resources. Given that food web structure varies with organismal composition through the periods of interest, the PIs will use numerical simulations to evaluate the sensitivity of food webs to perturbations of primary production. They predict that sensitivity will decline during intervals of mass extinction and post-extinction recovery. They will use Bayesian statistical modeling to estimate primary and secondary extinction components using observed extinction data from the fossil record of specific paleobiogeographic communities from the Permian and late Neogene. They will estimate the maximum levels of primary production disruption that could yield observed levels of extinction. They predict such levels to increase dramatically during intervals of mass extinction, if disruption of photosynthesis and secondary extinction were indeed important drivers of ecosystem collapse.

PI建议研究在大规模灭绝期间初级生产的停止在传播灭绝和生态系统崩溃中的作用。初级生产的中断被认为是地球过去极端生态危机期间灭绝的近端机制，可能导致整个营养系统的次级灭绝雪崩。生态网络的复杂性提出了一个独特的挑战，以了解这种次级干扰传播的途径。 该项目将使用数值模拟和贝叶斯统计建模相结合的方法来划分物种直接影响导致的灭绝，以及营养资源损失导致的灭绝。 鉴于食物网结构随生物组成而变化，PI将使用数值模拟来评估食物网对初级生产扰动的敏感性。他们预测，在大规模灭绝和灭绝后恢复期间，敏感性将下降。 他们将使用贝叶斯统计模型来估计主要和次要灭绝成分，使用从二叠纪和晚第三纪特定古生物地理群落的化石记录中观察到的灭绝数据。他们将估计初级生产中断的最大水平，可能导致观察到的灭绝水平。 他们预测，如果光合作用的破坏和二次灭绝确实是生态系统崩溃的重要驱动因素，那么在大规模灭绝期间，这种水平将急剧增加。