气候变化领域集成服务门户(CCPortal): Structure-based identification of sensor species for anticipating critical transitions

CCPortal

DOI	10.1073/pnas.2104732118
	Structure-based identification of sensor species for anticipating critical transitions
	Aparicio A.; Velasco-Hernández J.X.; Moog C.H.; Liu Y.-Y.; Angulo M.T.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:51
英文摘要	Ecological systems can undergo sudden, catastrophic changes known as critical transitions. Anticipating these critical transitions remains challenging in systems with many species because the associated early warning signals can be weakly present or even absent in some species, depending on the system dynamics. Therefore, our limited knowledge of ecological dynamics may suggest that it is hard to identify those species in the system that display early warning signals. Here, we show that, in mutualistic ecological systems, it is possible to identify species that early anticipate critical transitions by knowing only the system structure—that is, the network topology of plant–animal interactions. Specifically, we leverage the mathematical theory of structural observability of dynamical systems to identify a minimum set of “sensor species,” whose measurement guarantees that we can infer changes in the abundance of all other species. Importantly, such a minimum set of sensor species can be identified by using the system structure only. We analyzed the performance of such minimum sets of sensor species for detecting early warnings using a large dataset of empirical plant–pollinator and seed-dispersal networks. We found that species that are more likely to be sensors tend to anticipate earlier critical transitions than other species. Our results underscore how knowing the structure of multispecies systems can improve our ability to anticipate critical transitions. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Critical transitions; Observability; Pollination; Seed dispersal
语种	英语
scopus关键词	biological model; ecosystem; environmental aspects and related phenomena; symbiosis; Ecological and Environmental Phenomena; Ecosystem; Models, Biological; Symbiosis
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/250917
作者单位	Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, 76230, Mexico; Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, United States; Laboratoire des Sciences du Numérique de Nantes, UMR 6004, CNRS, Nantes, 44321, France; Consejo Nacional de Ciencia y Tecnología, Institute of Mathematics, Universidad Nacional Autónoma de México, Juriquilla, 76230, Mexico
推荐引用方式 GB/T 7714	Aparicio A.,Velasco-Hernández J.X.,Moog C.H.,et al. Structure-based identification of sensor species for anticipating critical transitions[J],2021,118(51).
APA	Aparicio A.,Velasco-Hernández J.X.,Moog C.H.,Liu Y.-Y.,&Angulo M.T..(2021).Structure-based identification of sensor species for anticipating critical transitions.Proceedings of the National Academy of Sciences of the United States of America,118(51).
MLA	Aparicio A.,et al."Structure-based identification of sensor species for anticipating critical transitions".Proceedings of the National Academy of Sciences of the United States of America 118.51(2021).