Disentangling influences of driving forces on intra-annual variability in sediment discharge in karst watersheds.

The intra-annual variability in sediment discharge was considerably influenced by the climate variability and vegetation dynamics. Because of the coupled or relationships between climatic and vegetation variables, it is still challenging to decouple the direct and indirect effects of climate variability and vegetation dynamics on hydrological and sediment transport processes. The purpose of this study is to decouple influences of individual driving force on intra-annual distribution of sediment discharge during 2003-2017 using the partial least squares structural equation model (PLS-SEM) method in four typical karst watersheds of Southwest China. The coefficient of variation (Cv), Completely regulation coefficient (Cr), Lorenz asymmetry coefficient and Gini coefficient were used to represent the intra-annual sediment discharge variability. Results showed that the monthly sediment discharge (190 % < Cv < 353 %) exhibited greater variability than its potential affecting factors (18 % < Cv < 101 %). From the PLS-SEM analysis, the water discharge, climate, and vegetation together explain 57 %-75 %, 64 %-79 %, and 53 %-80 % of the total variance in Cv, Cr, and Gini coefficient, respectively. Specifically, water discharge exerts the largest influence on sediment discharge variability (0.65 ≤ direct effect ≤0.97, P < 0.05), while vegetation dynamic mainly indirectly affects sediment discharge variability (-0.88 ≤ indirect effect ≤ -0.01) through influencing water discharge. The climate factors also principally indirectly affect the sediment discharge variability (-0.47 ≤ indirect effect ≤0.19) by affecting water discharge and vegetation. The PLS-SEM can effectively reveal the driving force and influencing mechanism of intra-annual sediment discharge changes, and provide an important reference for regional soil and water resources management in karst watersheds. Future studies can decouple the influences of the extreme climate, unique lithology, discontinuous soil, heterogeneous landscape, and special geomorphology on spatial variability in sediment discharge across different karst watersheds.

Land use change impacts on red slate soil aggregates and associated organic carbon in diverse soil layers in subtropical China.

The conversion of natural forests to other land use types generally has a significant influence on soil aggregation and associated soil organic carbon (SOC) concentration, depending on soil depth. However, the dynamics underlying soil aggregate distribution and aggregate-associated SOC concentration after such conversion remain inadequately understood, especially in the red slate soil region of subtropical China, where the stability of soil aggregates is the primary deterrent to soil erosion. This study investigated the effects of land use changes on soil aggregates and aggregate-associated organic carbon content in diverse soil layers in the aforementioned region. Soil samples were collected from seven typical land use types (natural forest, artificial forest, terraced citrus orchard, downhill citrus orchard, kiwifruit orchard, cornfield, and paddy field). Sampling was conducted at a depth of 0 to 100 cm and at 20 cm increments to determine aggregate distribution and aggregate-associated SOC content. Results showed that land use change and soil depth significantly affected aggregate stability and associated SOC concentration. Upon the conversion of natural forests to orchards and croplands, both macroaggregate (>0.25 mm) and SOC concentrations decreased, thereby weakening soil resistance to erosion caused by flowing water. However, the conversion of natural forests to artificial forests did not decrease aggregate stability or aggregate-associated SOC concentration, suggesting that artificial forests are alternative tree species for soil erosion control, aggregate stability enhancement, and SOC fixation. A general linear model indicated that land use changes accounted for 55 % and 56 % of the total variations in SOC concentration in >5 mm and 2.5 mm aggregates, respectively, implying that such changes more significantly affected large-grain aggregates. This study deepens the understanding of SOC accumulation mechanisms and provides valuable information on improving soil quality and physical structure in the red slate soil region of subtropical China.

Decoupling the influence of vegetation and climate on intra-annual variability in runoff in karst watersheds.

Karst landscapes cover 7-12% of Earth's continental area, and approximately 25% of the world's population partially or completely relies on drinking water from karst aquifers. Water shortages are a challenge worldwide in karst mountainous landscapes. Knowledge of intra-annual variability in runoff and the potential drivers of variability is important for optimizing regional water resources use. The objectives of this study were to investigate temporal variations in the distribution of intra-annual runoff during 2003-2017 in six karst watersheds in southwest China and to identify the key drivers of these variations. The Gini coefficient and Lorentz asymmetry coefficient were used to represent intra-annual variability in runoff. Partial least squares-structural equation modeling (PLS-SEM) was used to decouple the effects of climate variables and vegetation dynamics on the distribution of intra-annual runoff. In all six watersheds, the Gini coefficient ranged from 0.15 to 0.59, with a mean value of greater than 1 for the Lorentz asymmetry coefficient. The heterogeneity of intra-annual runoff distribution showed a decreasing trend from 2003 to 2017. Climate variables and vegetation dynamics strongly influenced intra-annual variability in runoff and accounted for 19-63% and 17-67% of the variation in the Gini coefficient and Lorentz asymmetry coefficient, respectively. Vegetation was negatively correlated with the Gini coefficient, and the direct effect of climate on the Gini coefficient was greater than its indirect effect on the Gini coefficient through vegetation. As compared with traditional multivariate statistical methods, PLS-SEM provides additional valuable information, including information on the direct and indirect impacts of climate and vegetation on the distribution of intra-annual runoff. PLS-SEM is recommended as an effective approach for disentangling the coupled relationships between predictors and hydrological characteristics under different circumstances.

[Ecological Stoichiometry of Carbon, Nitrogen, and Phosphorus in Subtropical Paddy Soils].

This study aims to understand the existence of stable soil organic carbon (C), nitrogen (N), and phosphorus (P) ratios in paddy soil. Based on a field soil survey database, the ecological stoichiometry of the C:N:P ratio of 110 subtropical paddy soil profiles and 587 genetic horizons were analyzed at a regional scale. Relevant analysis and redundancy analysis (RDA) are used to study the relationships between C:N:P ratios and soil-environmental factors (topography, parent materials, soil genetic horizons, soil groups, soil physical, and chemical properties). The results showed that the weighted averages of C:N, C:P, and N:P in paddy soils of subtropical regions were 12.6, 49, and 3.9, respectively, and C:N:P was 38:3.2:1. The C:N of paddy soil did not vary significantly with parent materials, soil groups, or genetic horizons. However, the C:P and N:P variations were significantly different, and the mean values of the two were much lower than global ratios (186 and 13.1) and average levels of C:P and N:P in Chinese soils (136 and 9.3). Although the C:N:P ratio in the paddy soil profile was relatively unstable, the topsoil C:N (14.2) was relatively stable due to the strong interaction between the topsoil and the environment. This reflects the close coupling of C and N in the topsoil of paddy fields under long-term anthrostagnic maturation. However, in the paddy soil profile, C:P and N:P were not stable, and there was no significant correlation between soil organic carbon (SOC) and total P content, total N, or total P content, which suggests that environmental changes may lead to soil C:N:P decoupling. It was found that topography, soil texture, iron oxide, and bulk density are all key soil-environmental factors that regulate the soil profile of rice paddy C:N:P.