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关联相互作用:通过空间和社会相互作用丰富食物网研究。

Connected interactions: enriching food web research by spatial and social interactions.

机构信息

Department of Environmental Science & Policy, University of California , Davis, CA, USA.

Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma , Parma, Italy.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2024 Sep 9;379(1909):20230163. doi: 10.1098/rstb.2023.0163. Epub 2024 Jul 22.

DOI:10.1098/rstb.2023.0163
PMID:39034705
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11293845/
Abstract

This theme issue features 18 papers exploring ecological interactions, encompassing metabolic, social, and spatial connections alongside traditional trophic networks. This integration enriches food web research, offering insights into ecological dynamics. By examining links across organisms, populations, and ecosystems, a hierarchical approach emerges, connecting horizontal effects within organizational levels vertically across biological organization levels. The inclusion of interactions involving humans is a key focus, highlighting the need for their integration into ecology given the complex interactions between human activities and ecological systems in the Anthropocene. The comprehensive exploration in this theme issue sheds light on the interconnectedness of ecological systems and the importance of considering diverse interactions in understanding ecosystem dynamics. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

摘要

本期专题探讨了 18 篇论文,涵盖了代谢、社会和空间联系以及传统营养网络的生态相互作用。这种整合丰富了食物网研究,提供了对生态动态的深入了解。通过研究生物体、种群和生态系统之间的联系,出现了一种层次方法,将组织水平内的水平效应垂直连接到生物组织水平上。人类参与的相互作用是一个关键焦点,鉴于人类活动与人类世生态系统之间的复杂相互作用,突出了将其纳入生态学的必要性。本期专题的全面探讨揭示了生态系统的相互关联性,以及考虑各种相互作用在理解生态系统动态方面的重要性。本文是专题“连接的相互作用:通过空间和社会相互作用丰富食物网研究”的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc36/11293845/d8837c106258/rstb.2023.0163.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc36/11293845/0717ad85b61a/rstb.2023.0163.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc36/11293845/d8837c106258/rstb.2023.0163.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc36/11293845/0717ad85b61a/rstb.2023.0163.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc36/11293845/d8837c106258/rstb.2023.0163.f002.jpg

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本文引用的文献

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3
Neighbourhood benthic configuration reveals hidden co-occurrence social diversity.
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Philos Trans R Soc Lond B Biol Sci. 2024 Sep 9;379(1909):20230174. doi: 10.1098/rstb.2023.0174. Epub 2024 Jul 22.
4
Spatially explicit predictions of food web structure from regional-level data.从区域水平数据预测食物网结构的空间显式模型。
Philos Trans R Soc Lond B Biol Sci. 2024 Sep 9;379(1909):20230166. doi: 10.1098/rstb.2023.0166. Epub 2024 Jul 22.
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Collective intelligence facilitates emergent resource partitioning through frequency-dependent learning.集体智慧通过频率依赖学习促进新兴资源分配。
Philos Trans R Soc Lond B Biol Sci. 2024 Sep 9;379(1909):20230177. doi: 10.1098/rstb.2023.0177. Epub 2024 Jul 22.
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The web of conflict-related interactions in Colombia: exploring causal linkages between ecological and social variables by the qualitative loop analysis.哥伦比亚冲突相关互动网络:通过定性循环分析探索生态和社会变量之间的因果关系。
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