Article
Version 2
Preserved in Portico This version is not peer-reviewed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
Generating early warning signals of reduced resilience in ecosystems is crucial for conservation and management endeavors. However, the practical implications of such early warning signal systems are still limited by the lack of data and uncertainties associated with predicting complex systems such as ecosystems. This research aims to investigate the feasibility of developing an early warning system capable of identifying an upcoming critical transition within mangrove forest ecosystems. Using time series analysis of remote sensing images, the resilience of mangrove forests was explored across two distinct study sites. One site (Qeshm Island) has been adversely affected by land-use and land-cover changes, while the other (Gabrik) serves as a reference ecosystem. The study uses data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite to quantify three remotely sensed indices: the Normalized Difference Vegetation Index (NDVI), the Modified Normalized Difference Water Index (MNDWI), and the Modified Vegetation Water Ratio (MVWR). In addition, Landsat data has been used to explore temporal alterations in land-use and land cover. To identify early warning signals, indicators such as autocorrelation (acf(1)), standard deviation (SD), and skewness (SK) are applied. The findings indicate a signal of reduced resilience by a significant increase in NDVI statistical metrics (acf(1): 0.50, SD: 0.9). Although MNDWI showed significant early warning signals in Qeshm Island (acf(1); 0.86, SD: 0.90), it provided a false alarm in the reference study site. MVWR failed to generate early warning signals of reduced resilience (acf(1); -0.100, SD: -0.07, SK: -0.21). Land-use land-cover change may explain reduced resilience in the forests. This study not only emphasizes the potential of remote sensing in monitoring the state of mangrove forests but also contributes to advancing our understanding of ecosystem dynamics. The findings of this study can be integrated with ecosystem management tools to enhance the effectiveness of conservation efforts aimed at safeguarding mangroves. This is the first report of the successful application of remote sensing in generating early warning signals of reduced resilience 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.
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Commenter: Sara Alibakhshi
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