Article
Version 1
Preserved in Portico This version is not peer-reviewed
Can Land Use Land Cover Change Explain the Reduced Resilience in Forests?
Version 1
: Received: 12 October 2023 / Approved: 13 October 2023 / Online: 16 October 2023 (08:47:29 CEST)
Version 2 : Received: 21 December 2023 / Approved: 25 December 2023 / Online: 26 December 2023 (08:50:59 CET)
Version 2 : Received: 21 December 2023 / Approved: 25 December 2023 / Online: 26 December 2023 (08:50:59 CET)
A peer-reviewed article of this Preprint also exists.
Alibakhshi, S., Espinosa-Leal, L., & Azadi, H. (2023). Can Land Use Land Cover Change Explain the Reduced Resilience in Forests?. Alibakhshi, S., Espinosa-Leal, L., & Azadi, H. (2023). Can Land Use Land Cover Change Explain the Reduced Resilience in Forests?.
Abstract
Detecting abrupt transitions in ecosystems, known as regime shifts, holds immense implications for conservation and management endeavors. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within Mangrove Forest ecosystems. Employing a fusion of remote sensing analysis, time series analysis, and the critical slowing down theory, Mangrove Forests' state change was explored across two distinct study sites. One site has been adversely affected by disturbances stemming from land use and land cover changes, while the other serves as an unaffected reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite, quantifying three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). Furthermore, temporal alterations in land-use and land cover are scrutinized using Landsat data from 1996, 2002, 2008, and 2014. To identify early warning signals of critical transitions, indicators such as autocorrelation, skewness, and standard deviation are applied. The results show the robust capabilities of remote sensing in generating early warning signals of critical transition in Mangrove Forests. NDVI outperformed MVWR and MNDWI as ecosystem state indicators. This study not only highlights the potential of remote in identifying the approaching regime shifts in Mangrove Forest ecosystems but also adds knowledge on ecosystem dynamics. This is the first report of the successful application of remote sensing in generating early warning signals for imminent critical transitions within Mangrove forests in the Middle East.
Keywords
land-use and land cover-change; monitoring ecosystem dynamics; remote sensing; Mangrove forests
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
