Investigation of Factors Affecting Biodiversity in Arid Ecosystems Using the InVEST Model and Structural Equation Modeling (Case Study: Jiroft County)

Khosravi Mashizi, Azam; Sharafatmandrad, Mohsen

doi:10.22034/jdmal.2026.2071597.1511

Investigation of Factors Affecting Biodiversity in Arid Ecosystems Using the InVEST Model and Structural Equation Modeling (Case Study: Jiroft County)

Document Type : Original Article

Authors

Azam Khosravi Mashizi

Mohsen Sharafatmandrad

Associate Professor, Department of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran.

10.22034/jdmal.2026.2071597.1511

Abstract

In recent decades, the decline in biodiversity has become a global crisis. This study aims to examine biodiversity and identify the key factors influencing it. Since the InVEST habitat quality model was used to investigate biodiversity in Jiroft County. Threats were weighted with the AHP model, determining their maximum impact along gradients, and the habitat quality model was used to evaluate biodiversity. The maximum spatial influence of each threat was determined along its respective gradient and integrated into the habitat quality model. In addition, vegetation characteristics, including canopy cover, Simpson's diversity index, and Margalef's richness index, were measured across different vegetation types. The AHP results indicated that livestock grazing and agricultural land use were the two most significant threats to biodiversity in the semi-arid ecosystems of the region. Habitat quality values derived from the InVEST model ranged from 0.03 to 0.69, revealing a highly heterogeneous spatial pattern of biodiversity across the landscape. Among the vegetation types, the Astragalus gossypinus–Artemisia aucheri community exhibited the highest habitat quality index (0.58 ± 0.16), indicating greater biodiversity conservation potential. Structural Equation Modeling (SEM) demonstrated that precipitation had the strongest direct positive effect on biodiversity (p < 0.001), followed by vegetation canopy cover (p < 0.01), species diversity (p < 0.01), and elevation (p < 0.01). Furthermore, areas located at higher elevations exhibited higher habitat quality and greater capacity to support biodiversity, whereas lowland areas characterized by intensive human activities showed substantially lower habitat quality. These findings confirm the effectiveness of the InVEST Habitat Quality model for quantifying and mapping biodiversity in the dry ecosystems of Iran. Moreover, integrating the InVEST model with SEM provides a robust framework for identifying the key ecological drivers of biodiversity and offers valuable scientific support for regional conservation planning, habitat restoration, and sustainable ecosystem management in semi-arid landscapes.

Keywords

Habitat quality

Simpson index

Analytic Hierarchy Process

Species diversity

Subjects