A modeling approach to quantify ecological dynamics and functional structures of paleocommunities.

IF 13.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yuangeng Huang, Peter D Roopnarine, Zhong-Qiang Chen
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引用次数: 0

Abstract

Fossils preserve crucial information about the underlying biological and ecological processes of past ecosystems. Models built on paleontological and paleoecological data can help to elucidate the factors influencing ecosystem health, stability, resilience and function, offering a unique perspective on the long-term ecological impacts of the ongoing human-induced biodiversity crisis and ecosystem degradation. Substantial advances have been made in quantifying the ecological dynamics and functional structures of paleocommunities. However, the effective reconstruction of paleo-food webs and the quantitative evaluation of paleocommunity dynamics are still challenging tasks. Here we present a detailed protocol for reconstructing paleo-food webs using fossil data and for modeling the stability and structures of these paleocommunities using the cascading extinction on graphs model. The procedure includes (1) selecting an appropriate geological time range and geographic scope, collecting fossil data and reconstructing paleocommunities; (2) assigning species to guilds on the basis of shared prey-predator relationships and connecting the guilds that interacted trophically; (3) measuring the functional structures and modeling their dynamics using species-level networks and cascading extinction on graphs models; and (4) analyzing the results to understand the community evolution and identify tipping points that predict ecosystem collapse. Organismal expertise is needed in the reconstruction of paleo-food webs. The resulting comparisons of the paleocommunity stability and structure can help calibrate the timing and patterns of ecological changes during critical intervals in Earth history. This Protocol aims to enhance the utilization of ecological modeling in understanding the evolution of ancient ecosystems. The time required for the protocol is community size dependent - for example, ~5 months for communities containing ~1,000 species.

量化古群落生态动态和功能结构的建模方法。
化石保存了过去生态系统中潜在的生物和生态过程的重要信息。基于古生物学和古生态学数据建立的模型有助于阐明影响生态系统健康、稳定性、恢复力和功能的因素,为当前人类引起的生物多样性危机和生态系统退化的长期生态影响提供了独特的视角。在量化古群落生态动态和功能结构方面取得了实质性进展。然而,如何有效地重建古食物网和定量评价古群落动态仍然是一项具有挑战性的任务。本文提出了一种利用化石数据重建古食物网的详细方案,并利用图上级联灭绝模型对这些古群落的稳定性和结构进行了建模。这一过程包括:(1)选择合适的地质时间范围和地理范围,收集化石资料,重建古群落;(2)根据共享的食饵-捕食者关系划分种群,并将有营养相互作用的种群联系起来;(3)利用物种级网络和级联灭绝图模型测量功能结构并建立其动态模型;(4)分析结果,了解群落演化,识别预测生态系统崩溃的临界点。重建古食物网需要有机方面的专业知识。对古群落稳定性和结构的比较可以帮助校准地球历史上关键时期生态变化的时间和模式。本议定书旨在加强利用生态模型来了解古代生态系统的演变。该协议所需的时间取决于群落规模,例如,对于含有~1,000种物种的群落,大约需要5个月。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Protocols
Nature Protocols 生物-生化研究方法
CiteScore
29.10
自引率
0.70%
发文量
128
审稿时长
4 months
期刊介绍: Nature Protocols focuses on publishing protocols used to address significant biological and biomedical science research questions, including methods grounded in physics and chemistry with practical applications to biological problems. The journal caters to a primary audience of research scientists and, as such, exclusively publishes protocols with research applications. Protocols primarily aimed at influencing patient management and treatment decisions are not featured. The specific techniques covered encompass a wide range, including but not limited to: Biochemistry, Cell biology, Cell culture, Chemical modification, Computational biology, Developmental biology, Epigenomics, Genetic analysis, Genetic modification, Genomics, Imaging, Immunology, Isolation, purification, and separation, Lipidomics, Metabolomics, Microbiology, Model organisms, Nanotechnology, Neuroscience, Nucleic-acid-based molecular biology, Pharmacology, Plant biology, Protein analysis, Proteomics, Spectroscopy, Structural biology, Synthetic chemistry, Tissue culture, Toxicology, and Virology.
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