Collaborative Research: Assessing millennial-scale community dynamics using highly-resolved mammal and vegetation food webs

地球上最大动物的灭绝正在从根本上改变其他物种之间的捕食关系（“食物网”），这可能会使它们在未来面临更大的灭绝风险。该项目将检查Rancho La Brea沥青坑的完整化石记录（大型食肉动物到植物），并在12,000年前最后一个冰河时代结束时的重大变化（人类的到来，大型哺乳动物的消失和气候变化）之前建立冰河时代的食物网。了解冰河时期动物和植物之间的关系将有助于生物学家预测哪些物种灭绝的风险最大，并将这些模型预测应用于当今的生物多样性。这个项目也是一个支持科学教育和多样性的绝佳机会，它直接让加州和缅因州的中学生参与到本研究中使用的化石的鉴定中来。项目发现也将在每年吸引35万游客的新拉布雷亚沥青坑博物馆展览中分享。在这个项目中，将对来自多个沥青渗漏的沉积物进行取样，用于美国加利福尼亚州拉布雷亚沥青坑的小动物、昆虫和植物。将对化石进行鉴定，用放射性碳测定年代，然后将其整合到更新世末期大范围环境剧变之前4万年的多营养古食物网中。以前只对上层营养层（特别是食肉动物）进行了详细调查；增加的信息将测试食物网的特性，以预测物种对全球变化的敏感性。这个项目吗?本文采用贝叶斯框架重构生物量流，通过促进多种代理的整合来表征营养相互作用的不确定性，将有助于古和现代食物网研究。

The extinction of Earth's largest animals is radically changing the feeding relationships among other species ("food webs") which may place them at greater risk of extinction in the future. This project will examine Rancho La Brea tar pits for the complete fossil record (large carnivores to plants) and build ice age food webs prior to the major changes at the end of the last ice age 12,000 years ago (human arrival, the loss of large mammals, and climate change). Understanding the relationships among ice age animals and plants will help biologists predict which species were at most risk of extinction and apply these model predictions to present-day biodiversity. This project is also an excellent opportunity to support science education and diversity, by directly involving middle school students in California and Maine in the identification of fossils used in this research. Project findings will also be shared in new La Brea Tar Pits & Museum exhibits, which draw 350,000 visitors each year. For this project, sediments from multiple asphalt seeps will be sampled for the small animals, insects and plants of the La Brea Tar Pits (California, USA). Fossils will be identified, radiocarbon dated, and then integrated into multi-trophic paleo food webs over the 40,000 years before the widespread environmental upheaval at the end of Pleistocene. Previously only the upper trophic levels (particularly carnivores) were investigated in detail; added information will test food web properties for predicting the sensitivity of species to global change. The project?s novel Bayesian framework, employed to reconstruct biomass flow, will be useful to both paleo and modern food web studies by facilitating integration of multiple proxies to characterize uncertainty in trophic interactions.