Parameter assignment for InVEST habitat quality module based on principal component analysis and grey coefficient analysis

Shiyun Wang; Xiaonan Liang; Jiaoyue Wang; Shiyun Wang; Xiaonan Liang; Jiaoyue Wang

doi:10.3934/mbe.2022649

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 12: 13928-13948. doi: 10.3934/mbe.2022649

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Research article

Parameter assignment for InVEST habitat quality module based on principal component analysis and grey coefficient analysis

1.
Department of Science, Shenyang Aerospace University, Shenyang 110136, China
2.
Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
3.
Key Laboratory of Pollution Ecology and Environmental Engineering, Chinese Academy of Sciences, Shenyang 110016, China
4.
Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang 110016, China

Received: 08 July 2022 Revised: 29 August 2022 Accepted: 08 September 2022 Published: 21 September 2022

The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model is a concise approach to evaluate the status of habitat quality for supporting ecosystem management and decision making. Assigning parameters accurately in the InVEST model is the premise for effectively simulating habitat quality. The purpose of this study is to propose an available method for assigning the important parameters in the Habitat Quality module of InVEST. Herein, the methods of principal component analysis (PCA) and grey relational analysis (GRA) were utilized to assign the weights of threat factors and the sensitivity of each habitat type to each threat factor, respectively. Through a case study of the habitat quality of Fuzhou City, we find that using PCA and GRA methods to assign parameters is feasible. Generally, the habitat quality of Fuzhou City in 2015 and 2018 was above the fair suitable level, and the proportion of fair suitable and good suitable habitats was about 83%. The areas with higher habitat quality were mainly concentrated in forest, wetland and grassland ecosystems. The spots with lower habitat quality were scattered all over the main urban areas of districts and counties, and their periphery. GDP per capita and population density were the main factors that affect the habitat quality of Fuzhou City. Narrowing the economic imbalance gap is an important way to reduce population shift and relieve the pressure of the urban environment in economically developed areas. This study is expected to provide an effective method for assigning parameters in the InVEST Habitat Quality Module and support regional ecosystem conservation.
- habitat quality,
- principal component analysis,
- grey coefficient analysis,
- InVEST model,
- driving factors
Citation: Shiyun Wang, Xiaonan Liang, Jiaoyue Wang. Parameter assignment for InVEST habitat quality module based on principal component analysis and grey coefficient analysis[J]. Mathematical Biosciences and Engineering, 2022, 19(12): 13928-13948. doi: 10.3934/mbe.2022649

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Abstract

The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model is a concise approach to evaluate the status of habitat quality for supporting ecosystem management and decision making. Assigning parameters accurately in the InVEST model is the premise for effectively simulating habitat quality. The purpose of this study is to propose an available method for assigning the important parameters in the Habitat Quality module of InVEST. Herein, the methods of principal component analysis (PCA) and grey relational analysis (GRA) were utilized to assign the weights of threat factors and the sensitivity of each habitat type to each threat factor, respectively. Through a case study of the habitat quality of Fuzhou City, we find that using PCA and GRA methods to assign parameters is feasible. Generally, the habitat quality of Fuzhou City in 2015 and 2018 was above the fair suitable level, and the proportion of fair suitable and good suitable habitats was about 83%. The areas with higher habitat quality were mainly concentrated in forest, wetland and grassland ecosystems. The spots with lower habitat quality were scattered all over the main urban areas of districts and counties, and their periphery. GDP per capita and population density were the main factors that affect the habitat quality of Fuzhou City. Narrowing the economic imbalance gap is an important way to reduce population shift and relieve the pressure of the urban environment in economically developed areas. This study is expected to provide an effective method for assigning parameters in the InVEST Habitat Quality Module and support regional ecosystem conservation.

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