Using functional indicators to detect state changes in terrestrial ecosystems

Zhongmin Hu; Vasilis Dakos; Max Rietkerk

doi:10.1016/j.tree.2022.07.011

Using functional indicators to detect state changes in terrestrial ecosystems

Zhongmin Hu
, Vasilis Dakos
, Max Rietkerk

Hainan University
Institut des Sciences de l'Evolution de Montpellier (ISEM)

Research output: Contribution to journal › Review article › peer-review

Abstract

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

Original language	English
Pages (from-to)	1036-1045
Number of pages	10
Journal	Trends in ecology & evolution
Volume	37
Issue number	12
Early online date	Aug 2022
DOIs	https://doi.org/10.1016/j.tree.2022.07.011
Publication status	Published - Dec 2022

Bibliographical note

Funding Information:
This research was jointly supported by the National Natural Science Foundation of China (grant no. 31922053 ), National Key R&D Program of China (grant no. 2017YFA0604801 ), Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2019QZKK0405 ), Key R&D Program of Hainan (grant no. ZDYF2022SHFZ042 ), and the start-up fund of Hainan University [no. KYQD(ZR)21096 ]. The authors appreciate Dr Andrea Stephens and three anonymous reviewers for their constructive comments on earlier versions of this manuscript.

Publisher Copyright:
© 2022 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

ecosystem functions
ecosystem model
ecosystem state change
global change
tipping point

Access to Document

10.1016/j.tree.2022.07.011

PIIS0169534722001756Final published version, 1.54 MBLicence: Taverne

Cite this

@article{0903723559e04f0f88514e384dc8f141,

title = "Using functional indicators to detect state changes in terrestrial ecosystems",

abstract = "Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.",

keywords = "ecosystem functions, ecosystem model, ecosystem state change, global change, tipping point",

author = "Zhongmin Hu and Vasilis Dakos and Max Rietkerk",

note = "Funding Information: This research was jointly supported by the National Natural Science Foundation of China (grant no. 31922053 ), National Key R\&D Program of China (grant no. 2017YFA0604801 ), Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2019QZKK0405 ), Key R\&D Program of Hainan (grant no. ZDYF2022SHFZ042 ), and the start-up fund of Hainan University [no. KYQD(ZR)21096 ]. The authors appreciate Dr Andrea Stephens and three anonymous reviewers for their constructive comments on earlier versions of this manuscript. Publisher Copyright: {\textcopyright} 2022 Elsevier Ltd",

year = "2022",

month = dec,

doi = "10.1016/j.tree.2022.07.011",

language = "English",

volume = "37",

pages = "1036--1045",

journal = "Trends in ecology \& evolution",

issn = "0169-5347",

publisher = "Elsevier Ltd",

number = "12",

}

TY - JOUR

T1 - Using functional indicators to detect state changes in terrestrial ecosystems

AU - Hu, Zhongmin

AU - Dakos, Vasilis

AU - Rietkerk, Max

N1 - Funding Information: This research was jointly supported by the National Natural Science Foundation of China (grant no. 31922053 ), National Key R&D Program of China (grant no. 2017YFA0604801 ), Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2019QZKK0405 ), Key R&D Program of Hainan (grant no. ZDYF2022SHFZ042 ), and the start-up fund of Hainan University [no. KYQD(ZR)21096 ]. The authors appreciate Dr Andrea Stephens and three anonymous reviewers for their constructive comments on earlier versions of this manuscript. Publisher Copyright: © 2022 Elsevier Ltd

PY - 2022/12

Y1 - 2022/12

N2 - Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

AB - Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

KW - ecosystem functions

KW - ecosystem model

KW - ecosystem state change

KW - global change

KW - tipping point

UR - https://www.scopus.com/pages/publications/85136244592

U2 - 10.1016/j.tree.2022.07.011

DO - 10.1016/j.tree.2022.07.011

M3 - Review article

C2 - 36008160

SN - 0169-5347

VL - 37

SP - 1036

EP - 1045

JO - Trends in ecology & evolution

JF - Trends in ecology & evolution

IS - 12

ER -

Using functional indicators to detect state changes in terrestrial ecosystems

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this