Spatio-Temporal Evolution Characteristics and Driving Factors of Typical Karst Rocky Desertification Area in the Upper Yangtze River
3.1. Characteristics of Spatio-Temporal Distribution of KRD
From Figure 2, it can be observed that from 1990 to 2020, the overall pattern in the study area was dominated by potential rocky desertification and no rocky desertification, with a relatively small proportion of areas where rocky desertification had already occurred (mild, moderate, severe, and extremely severe). Typically, the rocky desertification regions were mainly concentrated in the northern and central parts of Qujing City, with a sporadic distribution in the southeastern part. Specifically, the northern part of Qujing City was characterized by a high degree of rocky desertification, with moderate, severe, and extremely severe rocky desertification concentrated in this area. In contrast, the central and southeastern parts showed a slight degree of rocky desertification, which was mainly manifested as moderate and mild rocky desertification. Overall, the spatial distribution of rocky desertification in Qujing City presented a trend of “light in the south and heavy in the north” pattern.
According to the results of rocky desertification grading from 1990 to 2020 in Qujing, the area of rocky desertification of each grade in 1990, 1995, 2000, 2006, 2011, 2016, and 2020 was counted, and the proportion was calculated (Table 5). From 1990 to 2020, the type of rocky desertification in Qujing City was dominated by potential rocky desertification and no rocky desertification, and the area of rocky desertification (mild, moderate, severe, and extremely severe) was relatively small. The area of rocky desertification decreased by 1728.38 km2, while the area of no rocky desertification increased by 1936.61 km2, accounting for 13.53%. This indicates that the overall condition of rocky desertification in Qujing City showed significant amelioration.
From 1990 to 2020, the rocky desertification changes in each grade were relatively large in the rocky desertification area of Qujing City. In detail, the area of mild rocky desertification was always greater than 19%, and the area of moderate rocky desertification was 4–9%, while the area of severe and extremely severe rocky desertification was always less than 2%, indicating that the rocky desertification in Qujing City was mainly dominated by mild and moderate rocky desertification. From 1990 to 2020, the area of mild rocky desertification decreased continuously and decreased by 1266.07 km2, accounting for 8.85% of the total area. Remarkably, the area of moderate rocky desertification showed a fluctuating downward trend, first decreasing (1990–1995), then increasing (1995–2000), and finally decreasing again (2000–2020). On the contrary, the area of intensely rocky desertification first increased, then decreased, and eventually increased again, reaching a peak in 2000.
Combined with the nine county-level administrative divisions of Qujing City, the change areas of no rocky desertification and rocky desertification during the 31-year period were counted, respectively. From 1990 to 2020, the areas without rocky desertification change were, in descending order, Xuanwei City, Fuyuan County, Luoping County, Shizong County, Qilin District, Huize County, Luliang County, Zhanyi District, and Malong District. Moreover, the areas of rocky desertification that decreased were, in descending order, Xuanwei City, Fuyuan County, Luoping County, Shizong County, Huize County, Qilin District, Zhanyi District, Luliang County, and Malong District. During the 31-year period, Xuanwei City experienced the greatest change in the areas of no rocky desertification and rocky desertification, which were 633.37 km2 and 636.50 km2, respectively, followed by Fuyuan County and Luoping County. On the contrary, Malong District recorded the smallest area of change with 9.09 km2 and 7.80 km2, respectively. This was because the total karst area in Xuanwei City, Fuyuan County, and Luoping County was among the top three in Qujing City, while the total karst area in Malong District was the least. Karst area was the basis for the occurrence and development of rocky desertification, and the rocky desertification area itself had a magnitude gap between administrative regions, which limited the variability of the rocky desertification area in Malong District, indicating that there was no rocky desertification, and therefore, the rocky desertification area had the least variability.
3.2. Analysis of Driving Factors of Rocky Desertification in Qujing City
3.2.1. Influence Analysis
The contribution rate of driving factors to the spatial distribution of rocky desertification was analyzed through differentiation and factor detection (Table 6). Notably, the p value of all driving factors was less than 0.01, indicating that the q value of all driving factors was significantly different. Therefore, the contribution rates of all 11 factors were analyzed. The effects of natural environmental factors on the spatial distribution of rocky desertification in Qujing City were in the following order: FVC (q = 0.41) > slope (q = 0.21) > elevation (q = 0.11) > average annual rainfall (q = 0.07) > soil type (q = 0.05) = soil erosion (q = 0.05). Moreover, the impacts of socio-economic factors on rocky desertification were ranked as follows: land use type (q = 0.26) > land reclamation rate (q = 0.21) > gross domestic product of primary industry (q = 0.06) = population density (q = 0.06) > GDP per kilometer grid (q = 0.01). According to the definition of the q value, among the six natural environmental factors, the FVC and slope were the main driving factors of rocky desertification; among the five socio-economic factors, the land use type and land reclamation rate were the main driving factors.
By comparing the q values of natural environmental factors with socio-economic factors, FVC was identified as the largest natural factor. The average q value of natural factors (0.15) exceeded that of socio-economic factors (0.12). This suggests that natural environmental factors had a greater impact on the occurrence and development of rocky desertification than socio-economic factors in Qujing City.
3.2.2. Risk Analysis
Risk zone detection was used to recombine the attribute values of the internal division of a single factor and analyze the effect of the combination on the spatial distribution of rocky desertification. According to the factor detection, the main driving factors of rocky desertification in Qujing City were the FVC, land use type, slope, and land reclamation rate. Therefore, the risk zone detection was analyzed for the above-four main driving factors.
According to Table 7, the higher the value of FVC combination, the lower the impact on rocky desertification, i.e., rocky desertification is less likely to occur in areas with a high FVC (>0.7). Consequently, the combination of a low FVC (
As shown in Table 8, except for the combination area with slopes of 25°–35°, 15°–25° and 8°–15°, other slope ranges had a significant impact on rocky desertification. This is because human activities are more frequent and intensive in low-slope areas (0–5°, 5°–8°), while rocky desertification is more likely to occur in high-slope areas (35°–80°) where the natural ecological environment is poor.
Based on Table 9, it is clear that except forest land and other land uses, other land use types have a significant impact on rocky desertification. This may be due to the fact that the forest land types (including forest land, shrubland, and sparse forest land) and other land types (including marshland and bare land) significantly increased the uncertainty of the occurrence and development of rocky desertification. As a result, special attention should be paid to the formulation of ecological restoration policies according to local conditions in future work on rocky desertification prevention and control, and no generalizations should be made.
The land reclamation rate in this study was calculated as the proportion of cultivated land area per square kilometer. Hence, a land reclamation rate of 0 means that a square kilometer of land is not cropland and may therefore be forest or another type of land. When the land use type is forest land, it can be categorized into forest land, shrubland, or sparse forest land depending on the density of the canopy. Notably, the occurrence probability of rocky desertification is different for each forest land type. Moreover, the possibility of rocky desertification is also varied within the context of other land use types. As a result, the uncertainty of rocky desertification increases considerably when the area of cultivated land per square kilometer is too small, and the results show that there is no significant difference between the land reclamation rate of 0 and the combination of 0–10% (Table 10). Conversely, a high rate of land reclamation indicates good soil conditions and is largely free of rocky desertification. Therefore, there was little difference between the combinations having high rates of land reclamation, as shown in Table 10.
3.2.3. Difference Analysis
Ecological detection was employed to compare whether there is a significant difference between the combination of two factors on rocky desertification. Table 11 shows that the combination of the main driving factors of rocky desertification exhibits significant differences on the spatial distribution of rocky desertification, indicating that the interaction between the main driving factors has a great impact on the occurrence and development of rocky desertification. Nevertheless, the effects of the five factors, including the annual average rainfall, soil type, soil erosion, population density, and gross domestic product of primary industry, on rocky desertification did not differ significantly between any two of the factors, and therefore, the combination of these factors was not further analyzed for their interactions.
3.2.4. Interaction Analysis
In reality, the occurrence and development of rocky desertification is the result of the interaction of multiple factors. Hence, the interaction between different environmental factors was studied and the specific type of interaction between two factors was assessed based on the interaction detection of the geo-detector. In comparing the q-value of two factors with the q-value under the interaction, the latter has a larger q-value, indicating that the interaction of the two factors enhances the explanatory power of rocky desertification, otherwise the explanatory power under the interaction is weakened.
According to Table 12, the interactive driving factors with high explanatory power on the spatial distribution of rocky desertification in Qujing City are FVC ∩ slope (q = 0.79) and slope ∩ land use type (q = 0.56). Among the natural environmental factors, FVC ∩ slope (q = 0.79) and FVC ∩ average annual rainfall (q = 0.45) showed greater explanatory power for rocky desertification in the interaction of the two factors. While among the socio-economic factors, land use type ∩ gross value of primary industry production (q = 0.33) and land use type ∩ land reclamation rate (q = 0.32) exhibited greater explanatory power. Moreover, in the interaction between natural factors and social factors, slope ∩ land use type (q = 0.56) and FVC ∩ land reclamation rate (q = 0.49) possessed greater explanatory power. Consequently, the interaction between natural factors (vegetation cover ∩ slope) was greater than the interaction between social and natural factors (slope ∩ land use type), and is even greater than the interaction between social factors (land use type ∩ GDP of the primary industry). This also indicates that the explanatory power of natural environmental factors in the spatial distribution of rocky desertification in Qujing City is more significant.
The q values for the interactions of FVC ∩ slope, land use type ∩ primary industry product, and slope ∩ land use type were all greater than the sum of the q values of the respective two factors, indicating that the relationship between each two factors was nonlinearly enhanced. In addition, the q values for the interactions of FVC ∩ average annual rainfall, land use type ∩ land reclamation rate, and FVC ∩ land reclamation rate were all larger than that of any one factor, indicating that there was a two-factor enhancement relationship between each of the two factors. Although the q values of the interaction of each environmental factor were different, they were all greater than that of a single factor, and the interaction between the factors acted as facilitators.
