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

Area of Science:

• Ecosystem services assessment
• Environmental management
• Spatial analysis

Background:

• Accurate parameter assignment is essential for the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model.
• The Habitat Quality module requires precise parameters for effective simulation.
• Existing methods for parameter assignment may lack robustness.

Purpose of the Study:

• To propose a feasible method for assigning key parameters in the InVEST Habitat Quality module.
• To utilize Principal Component Analysis (PCA) and Grey Relational Analysis (GRA) for parameter assignment.
• To validate the proposed method through a case study.

Main Methods:

• Principal Component Analysis (PCA) to determine the weights of threat factors.
• Grey Relational Analysis (GRA) to assess the sensitivity of habitat types to threat factors.
• Case study application in Fuzhou City for habitat quality simulation.

Main Results:

• PCA and GRA provide a feasible approach for InVEST parameter assignment.
• Fuzhou City's habitat quality was generally above fair suitability (approx. 83% fair/good) in 2015 and 2018.
• Higher quality habitats were found in forest, wetland, and grassland ecosystems; lower quality areas were in urban peripheries.
• GDP per capita and population density were identified as key factors influencing habitat quality.

Conclusions:

• The PCA and GRA methods are effective for parameterizing the InVEST Habitat Quality module.
• Regional ecosystem conservation can be supported by this improved parameter assignment method.
• Addressing economic imbalance is vital for mitigating urban environmental pressure and population shifts.