Spatial and Temporal Changes of Habitat Quality and Its Influential Factors in China Based on the InVEST Model

Abstract

The loss of biodiversity is one of the three global crises today. How to reduce habitat destruction and overexploitation to protect biodiversity is an urgent issue to be addressed. This study aims to explore the influential factors and driving mechanisms of habitat quality to find ways to reduce the interference of human activities on habitat quality. This paper evaluates the habitat quality in 30 provinces of China from 2010 to 2020 using the InVEST model and studies its geospatial differences by spatial auto-correlation. Then it investigates the influencing factors and driving mechanisms based on Geodetector and proposes strategies to improve habitat quality for different regions. The study shows that first, habitat quality is not distributed homogeneously in Chinese provinces, and habitat quality varies widely among different regions in the structure. Second, factors have different influences on habitat quality, which can be grouped into “key factors” and “auxiliary factors”. Its driving forces vary greatly over time, with per capita water resources, nighttime light index, area of afforested land, forest area, and destructed forest area as key factors in both 2010 and 2020. Third, the factor pairs are all bifactor or non-linear enhanced, showing that two factors have a stronger combined effect on habitat quality than a single factor. In particular, factors such as per capita water resources and area of afforested land in very strong interactions with others. Fourth, corresponding strategies are proposed for different regions in China to improve habitat quality according to the analysis of the spatial inequality of habitat quality and its driving mechanism, providing a reference for relevant regions abroad.

The Change in Habitat Quality for the Yunnan Snub-Nosed Monkey from 1975 to 2022

“…Habitat rarity score (the relative commonness of the habitat state compared to a baseline state of the same location) is also calculated using the InVEST model. The resulting habitat quality score (sometimes simply referred to as habitat quality) and habitat rarity score (sometimes simply referred to as habitat rarity) can be used together to reflect biodiversity within the analyzed area [ 9 , 29 , 30 , 31 , 43 ].…”

“…The habitat quality module of the InVEST model is effective at quantifying a habitat’s quality by evaluating habitat quality indicators [ 11 , 28 ]. These indicators include land cover types, threat factors, and the rate of decrease in the threat factor impact as the distance from the threat factor increases [ 11 , 28 , 29 ]. The InVEST model has more flexibility, higher reliability, easier access to data, and more easily visualized results when compared with other models [ 9 , 29 , 30 , 31 ].…”

“…These indicators include land cover types, threat factors, and the rate of decrease in the threat factor impact as the distance from the threat factor increases [ 11 , 28 , 29 ]. The InVEST model has more flexibility, higher reliability, easier access to data, and more easily visualized results when compared with other models [ 9 , 29 , 30 , 31 ]. The InVEST model has been used in habitat quality studies to address a wide range of questions with particular focus on species conservation (e.g., shorebirds in the Yellow River Delta [ 32 ], the Dantoo crane in the wetlands of Yancheng, Jiangsu [ 33 ], and grassland depression birds in North America [ 34 ]).…”

Assessing Spatiotemporal Dynamics of Habitat Quality under Urbanization Stress in Guangdong Province: An inVEST-MGWR Analytical Approach

“…These detrimental changes have compromised vital ecosystem services, threatening sustainable development of human societies. Consequently, scientific assessment and continuous monitoring of habitat quality changes are vitally important for the effective conservation and restoration of ecosystems [6,7].…”

Temporal and spatial change of habitat quality and its driving forces: The case of Tacheng region, China

“…Land use change is one of the most important factors directly affecting the habitat quality index. In general, forest land and grassland have excellent habitat quality with a variety of species, numerous plant communities, and the capacity to be self-sustaining and adaptable to disturbances (Chen et al, 2023). Arable land typically has a monoculture with high vegetation cover, with moderate habitat quality.…”