## 4 Discussions
### Evaluation on Research Method Selection and Application  
Land use serves as a significant indicator of the interaction between human activities and ecosystems [104], with extensive cropland areas serving as a stark testament to human influence. The transfer matrix of land use reveals the trends and principles of land use changes by examining the exchanges among various land use categories at different time points. The land use dynamic index is a comprehensive metric that encapsulates the direction, pace, and intensity of land use changes, offering superior practicality and advantages [70]. These two methods have been widely utilized in land use studies within PAs. [PERSON] [71] and [PERSON] [21] employed the land use dynamic index to monitor and evaluate the spatiotemporal changes of wetlands, revealing a lack of effectiveness in wetland conservation, a finding that contrasts with our results. Using a transition matrix from a different land use classification system, which subdivides forests into three categories, [PERSON] observed increases in forest cover of 5% and 3% inside and outside PAs, respectively [105]. In contrast to previous research [73; 105; 106], we utilized the aforementioned two methods to conduct a comprehensive and accurate analysis of land use variation. In our study, forests both inside and outside the MdfNNR exhibited a decreasing trend. However, the declining trend inside the reserve was less pronounced than outside, which, to some extent, underscores the effectiveness of conservation efforts. We used the Globeland30 data, which has emerged as a widely accepted resource for analyzing land use patterns [8; 67], to investigate land use changes. In contrast, the previous research [61] conducted relied on the China Multi-temporal Land Use Remote Sensing Monitoring Dataset of the Resource and Environmental Science and Data Center, whereas other scholars opted for Landsat and Sentinel images for land use classification [107; 108]. Though each of these data sources have their unique advantages, they vary in their estimations of the extent of different land use types, primarily due to differences in data quality and classification methods. Our investigation indicates that the degree of land use changes in ZINNR was minimal between 2000 and 2010, with more noticeable variations emerging between 2010 and 2020. This sudden shift between these two periods differs from the findings of previous research [61; 107; 108]. This discrepancy is primarily due to inconsistencies in small-scale land use classification across different datasets. Therefore, we propose that future research should more effectively consider the scale and location of the study area when selecting data sources. This approach will enable a more accurate analysis of land use patterns. In contrast to previous studies, the landscape index chosen for this research is distinguished by its comprehensive scope and systematic approach. Earlier studies, such as Mu [21], evaluated the conservation effectiveness of wetland conservation areas based solely on landscape fragmentation, whereas Lu [38] relied exclusively on the Landscape Development Intensity Index for their assessments. In this study, we utilized ten landscape indexes spanning five different aspects, including patch characteristics, patch shape, landscape characteristics, landscape shape, and landscape diversity. This approach allowed us to create a comprehensive quantitative characterization of spatial and shape characteristics across patches and landscapes. This methodology enabled us to accurately analyze the landscape patterns of PAs within a scientific and comprehensive framework. Moreover, we also adopted a visual analysis of landscape indexes, which offers superior analytical efficiency compared to previous studies [109; 110; 111; 112], benefiting both researchers and readers. We deviated from the traditional moving window method [76; 113] and instead embraced a combination of grid analysis and Kriging interpolation to provide accurate landscape boundary analyses.