The rapid development of the economy has changed the regional landscape pattern. It is a high demand to quantitatively evaluate the impact of landscape pattern changes on the value of ecosystem services for ecological civilization construction and high-quality development. In this study, the research object was taken as the Yangtze River Economic Belt. Fishing net analysis was also made using land use data from eight periods from 1980 to 2020. The linear regression and correlation tests were carried out to clarify the spatiotemporal evolution and linear responses of four landscape pattern indexes and ecosystem service total value. Finally, a nonlinear probability evaluation framework was constructed to quantitatively evaluate the sensitivity of ecosystem service total value to changes in landscape pattern indexes. The results indicated that: 1) cropland, forestland, and grassland were the main types of land use in the study area. The area of cropland and forestland decreased each year, whereas, there was an increase in the area of other types of land use. Rapid economic development and urbanization were the main reasons for the significant increase in the construction land. 2) There was a relatively high index on the multi-year average landscape separation in southern Sichuan Province, eastern Yunnan Province, western Guizhou Province, and Chongqing City, resulting in severe landscape fragmentation, whereas, the distribution of patches was relatively concentrated in eastern Sichuan Province, southern Yunnan Province, western Hubei Province, western Hunan Province, northern Anhui Province, eastern Jiangsu Province, and southern Zhejiang Province. There was a significant increase in the indexes of landscape division and Shannon’s diversity in 43.97% and 64.28% of the study area, indicating the balanced and diversified landscape development. Urbanization was attributed to reducing the ecosystem service total value. 3) The increasing landscape separation index and Shannon’s diversity index were selected to represent the serious landscape fragmentation, leading to a decrease in the ecosystem service total value. It was very necessary to explore the response relationship between different landscape pattern indexes and ecosystem service total value, rather than the simple causal or linear relationship. 4) Four distribution functions were utilized to better fit the landscape pattern index and variations in the ecosystem service total value of each grid. Furthermore, the higher ecosystem service total value was more sensitive to the landscape division index and Shannon’s diversity index, according to the probability evaluation framework. The forestland and grassland were the dominant landscapes that affected the increase in the ecosystem service total value. The probability evaluation framework can be expected to quantitatively describe the nonlinear response relationship between the various ecosystem service total value and landscape pattern index. Landscape optimization should be carried out to promote protection and high-quality development. The finding can provide a solid scientific basis to grasp the variation trends of the landscape pattern and ecosystem services value, particularly for the ecological protection and high-quality warfare in the Yangtze River Economic Belt.

The rapid increase in the intensity of human activities has continuously changed the global underlying surface, resulting in ecological risks to the regional landscape. In this study, an ecological risk system was constructed for the watershed-scale landscape using a variety of landscape pattern indices. The global major basins and sub-basins were taken as the research objects. The land use raster data was collected for 34 consecutive years from 1982 to 2015. The spatiotemporal ecological risk of the global landscape was analyzed at the watershed scale. The various driving factors of landscape ecological risks were then quantified using geo-detectors. At the same time, the spatiotemporal variation was determined for the global net primary productivity (NPP) of vegetation at the watershed scale, in order to reveal the impact of global landscape ecological risks. The results showed that: 1) The range of spatial variation was 0-0.29 for the multi-year average ecological risk of the global landscape at the watershed scale. Specifically, the high-value areas were distributed mainly in the temperate and cold temperate zones, arid climate zone, and polar zone near the Arctic. Meanwhile, 17.44% and 23.45% of the watershed landscape ecological risks showed a significant increase and decrease trend from 1982 to 2015, respectively (P<0.05). 2) There was a large spatial variation in the coefficient of variation of landscape ecological risk in the arid climate, subtropical, and tropical zones. Furthermore, 36.82% watershed of significant change-points were found in the landscape ecological risk from 1988 to 2006. The spatial distribution of the watersheds with the significant changes in the landscape ecological risk was basically consistent with that of watersheds with significant change-points (P<0.05). The global underlying surface changed greatly in the 1990s, indicating the great variation in the landscape ecological risk. 3) There was the greatest impact of precipitation on the landscape ecological risk of major- and sub-watersheds at the multi-year scale. The influencing factors on the landscape ecological risk of watersheds were ranked the descending order of the precipitation, temperature, NDVI, population density, altitude, slope, and gross domestic product. There were also complex interactions among the various influencing factors on the landscape ecological risk. 4) The annual NPP of 52.32% and 12.60% of the watersheds increased and decreased significantly from 1982 to 2015, respectively. The landscape ecological risk was conducive to the NPP in the 9.11% watershed with a significant positive correlation between annual landscape ecological risk and annual NPP (P<0.05). By contrast, the annual landscape ecological risk was significantly negatively correlated with the annual NPP in the 11.43% watershed (P<0.05), where the reduction of landscape ecological risk was conducive to the NPP. The finding can also provide a solid scientific basis for global carbon neutrality and carbon sinks in the terrestrial ecosystems under climate change.

Soil and water loss has been one of the most serious hazards to the basin ecology in recent years. An accurate sediment transport model can greatly contribute to the control of soil and water loss in the basin. This study aims to explore the variation trend of sediment transport by Mann-Kendall. The runoff and sediment transport data was also collected from the 19 hydrological stations in the Loess Plateau. Annual sediment transport model was then established to take the runoff erosion power as the core factor in Pearson correlation analysis. Random forest variables were selected to evaluate the influence of factors (such as annual runoff erosion power, check-dam index, check-dam relative index, normalized difference vegetation index (NDVI) and impervious land area) on the annual sediment transport of the basin. The parameters were also determined in the annual sediment transport model by nonlinear least square method. The accuracy of the model was compared with different factor combinations. The annual sediment transport model was proposed with the strong applicability for the Loess Plateau. The attribution analysis was finally carried out on annual sediment transport. The results showed as follows: 1) It was reasonable to choose the runoff erosion power as the core factor in the annual sediment transport model. But there was a significant negative correlation between the area of watershed and the accuracy of the single factor annual sediment transport model with only annual runoff erosion power that built by the power function. The correlation coefficient was -0.505 (P<0.05). The accuracy of the single factor model decreased with the increase of the watershed area. As such, the applicability of the model was poor in watersheds larger than 7 000 km². 2) The best performance was achieved in the multi-factor annual sediment transport model with the combination of annual runoff erosion power, check-dam index and impervious area factors. The average NSE and RMSE values of the model were 0.84 and 0.21 10⁸t at the calibration rate, 0.79 and 0.27 10⁸t at the verification period. Compared with the single-factor annual sediment transport model that only considering the annual runoff erosion power, the mean NSE value increased by 339.39%, whereas, the mean RMSE value decreased by 81.88% during the verification period. The mean NSE value increased by 7.69%, while the mean RMSE value decreased by 38.64%, compared with the annual sediment transport model considering erosion power, the relative index of check-dam and NDVI combination. 3) The influencing factors on the annual sediment transport were as follows: annual runoff erosion power, impervious area and check-dam index. Their average contribution rates to the annual sediment transport were 79.52%, -38.89%, and 15.97%, respectively. The runoff of most watersheds decreased, where the inter-annual distribution of runoff tended to be uniform, which was greatly reduced the probability of large flow concentrated sediment transport. The simulation and prediction of sediment transport can provide the theoretical support for the prevention and control of soil and water loss in the ecological management of the Loess Plateau.

Mountain watersheds, as the critical regional water sources, are highly sensitive to climate change. It is a high demand to investigate the hydrological variations in mountain watersheds for the protection of regional ecological environments and sustainable water resources. This study aims to explore the spatiotemporal variation in the potential evapotranspiration and attribution analysis of typical watershed runoff in the Qinling Mountain Areas. Six typical watersheds were selected as the research objects. Meteorological data was daily collected from 79 meteorological stations from 1965 to 2019. Annual runoff data was from the hydrological control stations in the watersheds, together with the annual sunspot numbers, atmospheric circulation indices, and the Nino3.4 index, such as the Penman-Monteith equation. The modified Mann-Kendall trend test was employed to analyze the spatiotemporal variations in the potential evapotranspiration (PET) across the study area using cross-wavelet transforms and the time-varying Budyko framework. PET sensitivity was assessed on various climatic factors to explore the potential drivers of PET changes. Finally, the contributions of PET were quantified for the runoff variations across different periods. The results indicated: 1) There were some significant differences in spatial distribution and trends in the multi-year average PET and climate factors from 1965 to 2019. Multi-year average PET and sunlight hours (SH) exhibited a spatial pattern of higher in the northeast and lower in the southwest. While the maximum and minimum relative humidity (RHmax and RHmin) showed the opposite trends. Additionally, the temperature generally increased on an annual scale, while the SH and wind speed (WS) decreased across a broad area. The average annual WS of all vegetation types was below 1.8 m/s. The significant reduction in the annual WS was concentrated mainly in the vegetation types, such as the broad-leaved forest, cultivated vegetation, shrub, coniferous forest, and grass (P<0.05). It was also found that the differential modes were used to accurately simulate the annual variation of PET in the Qinling Mountain Area on an annual scale, with the coefficient of certainty R² (0.96) between the calculated and the actual value. 2) The annual PET and climatic factors exhibited different patterns of change across various vegetation types. Specifically, there was a significant decrease in the SH in the broadleaf forests and cultivated vegetation areas, with the spatially uneven distribution of relative humidity change trends (P<0.05). The sensitivity of annual PET to annual SH showed an overall pattern of low in the north and high in the east and west in spatial distribution, with a value range of -0.04~0.04. However, there was no spatial distribution pattern in the sensitivity of PET to RHmax. The highest sensitivity of annual PET to multiple climatic factors was found in the grassland vegetation. There was a great variation in the duration and scope of the influence of topographical factors, solar activity, and atmospheric circulation on the annual PET. The PET showed a highly significant decreasing trend with the increasing elevation and slope (P<0.001). Among them, 98.73% of meteorological stations shared a negative correlation between annual PET and the Arctic Oscillation index (AO index), and 20.25% shared a significant negative correlation (P<0.05). 3) Furthermore, the three northern foothill watersheds showed a decreasing trend in the annual runoff depth among the six typical watersheds. While two of the three southern foothill watersheds exhibited an increasing trend. There was a generally relatively small impact of PET on the runoff variation in the different typical watersheds and sliding window periods. The variation in the vegetation was the primary driving factor on the watershed runoff. The sustainable utilization of water resources in the mountain watersheds can greatly contribute to ecological protection and high-quality development in the Yellow River and Yangtze River Basins. Continuous monitoring and adaptive management were also highlighted in response to the future climates. The multiple types of data and reliable hydrological analysis were integrated to fully understand the complex interactions between climatic factors and hydrological processes in mountainous regions.