## 2 Study Area and Data Sources
### Methods
#### 2.3.1 The HQ Assessment Based on the InVEST Model  
The InVEST model assumes that biodiversity is proportional to HQ and evaluates the capacity and potential of ecosystems to support species survival, reproduction, and activity by calculating HQ [31; 32]. HQ is directly related to habitat suitability provided by LUC types [33], evaluating both the intensity of external threats and ecosystem sensitivity. The calculation formula is as follows:  
\[Q_{xj}=H_{xj}\cdot\left[1-\left(\frac{D_{xj}^{2}}{D_{xj}^{2}+k^{2}}\right)\right] \tag{1}\]  
where \(Q_{xj}\) is the HQ of grid \(x\) in LUC-type \(j\). Its value is between 0 and 1, and the higher the value, the better the HQ. \(D_{xj}\) is the habitat degradation degree of grid \(x\) in LUC-type \(j\), ranging from 0 to 1. \(H_{xj}\) is the habitat suitability of \(x\) in LUC-type \(j\), in which the suitability of the non-habitat LUC type is 0 and the suitability of the optimal habitat category is 1. \(k\) is the half-saturation constant.  
In general, the suitability of natural landscapes is relatively high, while man-made landscapes are largely unsuitable [10]. Therefore, this study divided the habitat types into  
Figure 2: The framework of this study.  
six categories based on the features of the study region and previous research [34; 35; 36]. WL and WTL were considered to be the LUC types with the highest habitat suitability for species, and their suitability values were set as 1 (Table 1).  
\[D_{xj}=\sum_{r=1}^{r}\sum_{y=1}^{y}\left(\begin{array}{c}w_{r}\\ \sum\limits_{n=1}^{n}w_{r}\end{array}\right)\cdot r_{y}\cdot i_{rxy}\cdot\beta _{x}\cdot S_{jr} \tag{2}\]  
where \(i_{rxy}\) is the impact of threat factor \(r\) in grid \(y\) on grid \(x;w_{r}\) is the weight of different threat factors; \(r_{y}\) indicates the intensity of the threat factor; and \(S_{jr}\) is the sensitivity of different habitats to different threat factors.  
In a general sense, natural landscapes exhibit the highest sensitivity to threat factors, followed by semi-artificial landscapes and artificial landscapes, which are relatively less sensitive to threat factors with a certain degree of resistance to interference [37]. The sensitivity value spans from 0 to 1, where a score of 1 signifies the utmost sensitivity, while a score of 0 denotes no sensitivity. In addition, the higher the degree of human use of land species, the more serious the threat is to the habitat. CL is a notable expression of the alteration in the human natural environment, portraying the threat posed by human pressure to the natural ecosystem. As a semi-natural and semi-artificial environment, AL poses a certain degree of threat to the natural ecosystem [38]. Transport networks have cumulative and irreversible impacts on ecosystem services and biodiversity, and their construction leads to habitat fragmentation, thus becoming a serious threat [39]. Therefore, this study took CL, AL, and transportation land as threat factors. This study determined the sensitivity assignment of different habitat types (Table 1), the weight of threat factors, and the maximum impact distance of threat sources (Table 2) concerning the literature review and InVEST model manual and the specific conditions of the study area [40; 41; 42].