Landscape Metrics Explain the Ecological Susceptibility of Terrestrial Ecosystems

Mustafa Nur Istanbuly; Mohammad Kaboli; Sara Ahmadi; Gouhang Tian; Magdalena Michalak; Bahman Jabbarian Amiri

doi:10.3097/LO.2022.1101

Authors

Mustafa Nur Istanbuly University of Tehran, Faculty of Natural Resources, Department of Environmental Science, Karaj, Iran https://orcid.org/0000-0002-9978-855X
Mohammad Kaboli University of Tehran, Faculty of Natural Resources, Department of Environmental Science, Karaj, Iran https://orcid.org/0000-0002-9203-2346
Sara Ahmadi University of Tehran, Faculty of Natural Resources, Department of Environmental Science, Karaj, Iran
Gouhang Tian Henan Agricultural University, College of Landscape Architecture and Art, Henan, China
Magdalena Michalak University of Lodz, Faculty of Economics and Sociology, Department of Regional Economics and the Environment, Lodz, Poland https://orcid.org/0000-0002-5031-9162
Bahman Jabbarian Amiri University of Lodz, Faculty of Economics and Sociology, Department of Regional Economics and the Environment, Lodz, Poland https://orcid.org/0000-0003-1382-786X

DOI:

https://doi.org/10.3097/LO.2022.1101

Keywords:

Susceptibility, Landscape structure, Subjective, Objective, Modeling, Sensitivity, uncertainty

Abstract

This study examines the effects of the change in the shape of landscape patches, known as landscape structure, on ecological susceptibility, which is defined using the object-oriented method. The aim is to determine whether ecological susceptibility is influenced by the shape of the landscape patches in the southern basin of the Caspian Sea. The multivariate linear regression approach is applied to discover the extent to which the mean, median, and weighted average of the landscape structure metrics can explain the total variations of the ecological susceptibility. To determine the optimal models, an intermodel comparison is conducted using the Akaike information criterion. Sensitivity and uncertainty analyses were performed to determine how sensitive ecological susceptibility is to changes in the variables of the models and how they behave under varying conditions. The models (0.64≥r2≥0.27, p ≤ 0.05) indicate that the landscape structure metrics can be applied to predict ecological susceptibility. Examining the mean, median, and weighted average of the landscape metrics in estimating ecological susceptibility also reveals that the models made by the mean and median values have less uncertainty than those developed by the weighted average. The results show that the regularity or irregularity in the shape of the landscape patches and the degree of contiguity of the land use/land cover patches can significantly affect ecological susceptibility. Closed deciduous broad-leaf forest patches, closed mixed forest patches, and open mixed forest patches can be considered crucial land use/land covers to estimate ecological susceptibility.

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