Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem

Show full item record



Alibakhshi , S , Groen , T A , Rautiainen , M & Naimi , B 2017 , ' Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem ' , Remote Sensing , vol. 9 , no. 4 , 352 .

Title: Remotely-Sensed Early Warning Signals of a Critical Transition in a Wetland Ecosystem
Author: Alibakhshi, Sara; Groen, Thomas A.; Rautiainen, Miina; Naimi, Babak
Contributor organization: Faculty of Agriculture and Forestry
University Management
Department of Geosciences and Geography
Date: 2017-04
Language: eng
Number of pages: 19
Belongs to series: Remote Sensing
ISSN: 2072-4292
Abstract: The response of an ecosystem to external drivers may not always be gradual and reversible. Discontinuous and sometimes irreversible changes, called 'regime shifts' or 'Critical transitions', can occur. The likelihood of such shifts is expected to increase for a variety of ecosystems, and it is difficult to predict how close an ecosystem is to a critical transition. Recent modelling studies identified indicators of impending regime shifts that can be used to provide early warning signals of a critical transition. The identification of such transitions crucially depends on the ability to monitor key ecosystem variables, and their success may be limited by lack of appropriate data. Moreover, empirical demonstrations of the actual functioning of these indicators in real-world ecosystems are rare. This paper presents the first study which uses remote sensing data to identify a critical transition in a wetland ecosystem. In this study, we argue that a time series of remote sensing data can help to characterize and determine the timing of a critical transition. This can enhance our abilities to detect and anticipate them. We explored the potentials of remotely sensed vegetation (NDVI), water (MNDWI), and vegetation- water (VWR) indices, obtained from time series of MODIS satellite images to characterize the stability of a wetland ecosystem, Dorge Sangi, near the lake Urmia, Iran, that experienced a regime shift recently. In addition, as a control case, we applied the same methods to another wetland ecosystem in Lake Arpi, Armenia which did not experience a regime shift. We propose a new composite index (MVWR) based on combining vegetation and water indices, which can improve the ability to anticipate a critical transition in a wetland ecosystem. Our results revealed that MVWR in combination with autocorrelation at-lag-1 could successfully provide early warning signals for a critical transition in a wetland ecosystem, and showed a significantly improved performance compared to either vegetation (NDVI) or water (MNDWI) indices alone.
Subject: critical transitions
early warning signals
time series
modified vegetation water index
spectral index
1171 Geosciences
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

Files in this item

Total number of downloads: Loading...

Files Size Format View
remotesensing_09_00352.pdf 10.76Mb PDF View/Open

This item appears in the following Collection(s)

Show full item record