Emerging resilience metrics in an intensely managed ecological system

Simple item page
dc.contributor.authorToumasis, Nikolaos
dc.contributor.authorSimms, Daniel
dc.contributor.authorRust, Will
dc.contributor.authorHarris, Jim A.
dc.contributor.authorWhite, John R.
dc.contributor.authorZawadzka, Joanna
dc.contributor.authorCorstanje, Ron
dc.date.accessioned2024-03-13T14:54:24Z
dc.date.available2024-03-13T14:54:24Z
dc.date.issued2024-01-05
dc.description.abstractThere is growing interest in understanding resilience of ecosystems because of the potential of abrupt and possibly irreversible shifts between alternative ecosystem states. Tipping points are observed in systems with strong positive feedback, providing early warning signals of potential instability. These points can be detected through metrics like critical slowing down (CSD), such as increased recovery time, variance, and autocorrelation. These indicators have been tested in laboratory experiments and field settings, ignoring trait changes. Here we present a long-term temporal analysis of several large, intensely monitored constructed wetlands, the Everglades Stormwater Treatment Areas (STAs), in which sudden changes in plant community composition have been observed. Using wavelet analysis, significant increases and decreases of variance properties (long-term flow data, water quality and nutrient TP loads) across these systems can indicate when and which STAs are less resilient to perturbations. In this study, continuous wavelet transform (CWT) was used to determine the periodicity of any cyclical activity in the data and to determine changes in autocorrelation and variance as measures of CSD. The change detection methods were used to find significant changes in variations and correlations across the time series. By employing these techniques, we were able to spot substantial shifts in model-observed wavelet correlation and model residual wavelet variance and thereby identify where these systems exhibit CSD. Although our analysis is limited to historical data, the proposed approach has practical value in that it identifies STAs that may be vulnerable to perturbation. The study also presents one of the few studies in which CSD is observed in practice rather than modelled in theory.en_UK
dc.description.sponsorshipNational Environment Research Council (Restoring Resilient Ecosystems) NE/V006444/1en_UK
dc.identifier.citationToumasis N, Simms D, Rust W, et al., (2024) Emerging resilience metrics in an intensely managed ecological system. Ecological Engineering, Volume 200, March 2024, Article number 107151en_UK
dc.identifier.eissn1872-6992
dc.identifier.issn0925-8574
dc.identifier.urihttps://doi.org/10.1016/j.ecoleng.2023.107151
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20978
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectWavelet analysisen_UK
dc.subjectContinuous wavelet transformen_UK
dc.subjectStormwater Treatment Areaen_UK
dc.subjectTotal phosphorusen_UK
dc.subjectInflowen_UK
dc.subjectOutflowen_UK
dc.subjectSoluble reactive phosphorusen_UK
dc.subjectAutocorrelationen_UK
dc.subjectResilienceen_UK
dc.titleEmerging resilience metrics in an intensely managed ecological systemen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2023-11-14

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Emerging_resilience_metrics-2024.pdf
Size:
8.93 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SWEE)