Dynamic evolution and scenario simulation of habitat quality under the impact of land-use change in the Huaihe River Economic Belt, China

Abstract

Habitat quality is an important indicator for evaluating the biodiversity provided by ecosystem. Estimating and scenario-simulating the dynamic evolution and future development trends of habitat quality under the influence of land-use change is significant in regional biodiversity conservation, formulating land-use planning, and maintaining the ecological environmental sustainability. In this article, we included the Huaihe River Economic Belt as the area of study because of its vital location in China and applied the CA–Markov and InVEST models to analyze the spatio-temporal evolution of habitat quality and to simulate the future development trends of habitat quality under three different land-use scenarios: fast urban growth scenario, farmland conservation-oriented scenario, and ecological conservation-oriented scenario. The results showed that the land-use change in the Huaihe River Economic Belt was mostly represented by the continuous increase of the built-up area, whereas other land types all declined in area from 1995 to 2015. The land-use changes under these three abovementioned alternative future scenarios with different development orientations were considerably different. The built-up area has been shown to expand rapidly to occupy other land types on a large scale under the fast urban growth scenario. Urban land increased slightly and a large area of rural residential land would be converted into farmland under the farmland conservation-oriented scenario. The built-up area and farmland might decrease while woodland, grassland and water would increase in extent of areas under the ecological conservation-oriented scenario. Habitat quality has been shown to be generally poor, continuing to decline from 1995 to 2015, while its spatial distribution was higher in the southwest and northeast areas and lower in the central regions. The future habitat quality would display a downward trend under the fast urban growth and farmland conservation-oriented scenarios with a further deterioration of the ecological environment, while the ecological conservation-oriented scenario predicted the converse trend that the ecological environment would be improved productively. This study may be useful for understanding the impact of land-use dynamics on biodiversity. The research results can provide a scientific basis for the decision-makers to formulate biodiversity conservation and land management policies.

InVEST model analysis of the impacts of land use change on landscape pattern and habitat quality in the Xiaolangdi Reservoir area of the Yellow River basin, China

“…Therefore, this study selected farmland, bare land, urban land, rural residential areas, paved and unpaved roads, and other construction land as threat factors for the ecological environment of the Reservoir area. The distances and weights of threat factors, the habitat suitability of different land use types, and the sensitivity of threat factors were assigned values (Tables S3 and S4) following the InVEST model's user manual (Sharp et al, 2018) in combination with previous studies of the Loess Plateau region and similar environments (Bai et al, 2019; Bao et al, 2015; Mengist et al, 2021; Sun et al, 2019; Tang et al, 2021; Terrado et al, 2016).…”

“…The influence of pressure factors related to human production and life on habitats is mainly manifested in the habitat suitability of different land use types in the model (Bai et al, 2019) S3 and S4) following the InVEST model's user manual (Sharp et al, 2018) in combination with previous studies of the Loess Plateau region and similar environments (Bai et al, 2019;Bao et al, 2015;Mengist et al, 2021;Sun et al, 2019;Tang et al, 2021;Terrado et al, 2016). of the entire study area.…”

Linking Ecosystem Service and MSPA to Construct Landscape Ecological Network of the Huaiyang Section of the Grand Canal

“…We selected the habitat quality index to comprehensively evaluate biodiversity conservation service. The habitat quality index is calculated by the Habitat Quality module of the InVEST model, whereby the value of the index ranges between 0 and 1; the greater the index, the higher the habitat quality and the greater the biodiversity [72,73]. The equation is as follows:…”

“…The data required to run the InVEST habitat quality module include land-use cover maps, threat factors layers, the impact distance of threat factors, the sensitivity of habitats to threat factors, and the distance between habitats and threat factors sources. Referring to the relevant literature [72][73][74][75][76], and combining the knowledge of experts, we selected paddy field, dry land, urban land, rural residential land, and industrial and traffic land as the threat factors, assigning the maximum stress distance and weight of each threat factor, and assigning the sensitivity of various habitat types to the threat factors (Tables 2 and 3).…”

Impacto Futuro Del Cambio De Cobertura Y Uso De La Tierra en Comunidades Indígenas Yagua De La Amazonía Peruana

“…Una forma de cuantificar y representar el impacto sobre los ecosistemas con enfoque espacial con base al uso de la tierra y a la influencia de las amenazas a los hábitats, es a través del índice de calidad del hábitat (Aneseyee et al, 2020); el cual tiende a disminuir por efectos del aumento de la presión del uso de la tierra sobre los hábitats cercanos (Sharp et al, 2018). Así mismo, uno de los modelos más utilizados para determinar la calidad del hábitat es InVEST (Zhang et al, 2020;Tang et al, 2021), que permite obtener la extensión relativa y el grado de impacto en el tiempo de los tipos de hábitats en un territorio determinado (Sharp et al, 2018).…”