Early warning signals have limited applicability to empirical lake data
Abstract Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear w...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-43744-8 |
| _version_ | 1797414748367618048 |
|---|---|
| author | Duncan A. O’Brien Smita Deb Gideon Gal Stephen J. Thackeray Partha S. Dutta Shin-ichiro S. Matsuzaki Linda May Christopher F. Clements |
| author_facet | Duncan A. O’Brien Smita Deb Gideon Gal Stephen J. Thackeray Partha S. Dutta Shin-ichiro S. Matsuzaki Linda May Christopher F. Clements |
| author_sort | Duncan A. O’Brien |
| collection | DOAJ |
| description | Abstract Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory. |
| first_indexed | 2024-03-09T05:38:02Z |
| format | Article |
| id | doaj.art-c4f1a0b8be364081a5bd2776b4c39db5 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-09T05:38:02Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-c4f1a0b8be364081a5bd2776b4c39db52023-12-03T12:27:41ZengNature PortfolioNature Communications2041-17232023-12-0114111410.1038/s41467-023-43744-8Early warning signals have limited applicability to empirical lake dataDuncan A. O’Brien0Smita Deb1Gideon Gal2Stephen J. Thackeray3Partha S. Dutta4Shin-ichiro S. Matsuzaki5Linda May6Christopher F. Clements7School of Biological Sciences, University of BristolDepartment of Mathematics, Indian Institute of Technology RoparKinneret Limnological Laboratory, Israel Oceanographic & Limnological ResearchLake Ecosystems Group, UK Centre for Ecology & HydrologyDepartment of Mathematics, Indian Institute of Technology RoparBiodiversity Division, National Institute for Environmental StudiesUK Centre for Ecology & Hydrology, Bush Estate, PenicuikSchool of Biological Sciences, University of BristolAbstract Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.https://doi.org/10.1038/s41467-023-43744-8 |
| spellingShingle | Duncan A. O’Brien Smita Deb Gideon Gal Stephen J. Thackeray Partha S. Dutta Shin-ichiro S. Matsuzaki Linda May Christopher F. Clements Early warning signals have limited applicability to empirical lake data Nature Communications |
| title | Early warning signals have limited applicability to empirical lake data |
| title_full | Early warning signals have limited applicability to empirical lake data |
| title_fullStr | Early warning signals have limited applicability to empirical lake data |
| title_full_unstemmed | Early warning signals have limited applicability to empirical lake data |
| title_short | Early warning signals have limited applicability to empirical lake data |
| title_sort | early warning signals have limited applicability to empirical lake data |
| url | https://doi.org/10.1038/s41467-023-43744-8 |
| work_keys_str_mv | AT duncanaobrien earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT smitadeb earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT gideongal earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT stephenjthackeray earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT parthasdutta earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT shinichirosmatsuzaki earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT lindamay earlywarningsignalshavelimitedapplicabilitytoempiricallakedata AT christopherfclements earlywarningsignalshavelimitedapplicabilitytoempiricallakedata |