Analysis of factors controlling soil phosphorus loss with surface runoff in Huihe National Nature Reserve by principal component and path analysis methods

Phosphorus (P) loss with surface runoff accounts for the P input to and acceleration of eutrophication of the freshwater. Many studies have focused on factors affecting P loss with surface runoff from soils, but rarely on the relationship among these factors. In the present study, rainfall simulation on P loss with surface runoff was conducted in Huihe National Nature Reserve, in Hulunbeier grassland, China, and the relationships between P loss with surface runoff, soil properties, and rainfall conditions were examined. Principal component analysis and path analysis were used to analyze the direct and indirect effects on P loss with surface runoff. The results showed that P loss with surface runoff was closely correlated with soil electrical conductivity, soil pH, soil Olsen P, soil total nitrogen (TN), soil total phosphorus (TP), and soil organic carbon (SOC). The main driving factors which influenced P loss with surface runoff were soil TN, soil pH, soil Olsen P, and soil water content. Path analysis and determination coefficient analysis indicated that the standard multiple regression equation for P loss with surface runoff and each main factor was Y = 7.429 - 0.439 soil TN - 6.834 soil pH + 1.721 soil Olsen-P + 0.183 soil water content (r = 0.487, p < 0.01, n = 180). Soil TN, soil pH, soil Olsen P, and soil water content and the interactions between them were the main factors affecting P loss with surface runoff. The effect of physical and chemical properties of undisturbed soils on P loss with surface runoff was discussed, and the soil water content and soil Olsen P were strongly positive influences on the P loss with surface runoff.

Analysis of factors controlling sediment phosphorus flux potential of wetlands in Hulun Buir grassland by principal component and path analysis method

Phosphorus (P) flux potential can predict the trend of phosphorus release from wetland sediments to water and provide scientific parameters for further monitoring and management for phosphorus flux from wetland sediments to overlying water. Many studies have focused on factors affecting sediment P flux potential in sediment-water interface, but rarely on the relationship among these factors. In the present study, experiment on sediment P flux potential in sediment-water interface was conducted in six wetlands in Hulun Buir grassland, China and the relationships among sediment P flux potential in sediment-water interface, sediment physical properties, and sediment chemical characteristics were examined. Principal component analysis and path analysis were used to discuss these data in correlation coefficient, direct, and indirect effects on sediment P flux potential in sediment-water interface. Results indicated that the major factors affecting sediment P flux potential in sediment-water interface were amount of organophosphate-degradation bacterium in sediment, Ca-P content, and total phosphorus concentrations. The factors of direct influence sediment P flux potential were sediment Ca-P content, Olsen-P content, SOC content, and sediment Al-P content. The indirect influence sediment P flux potential in sediment-water interface was sediment Olsen-P content, sediment SOC content, sediment Ca-P content, and sediment Al-P content. And the standard multiple regression describing the relationship between sediment P flux potential in sediment-water interface and its major effect factors was Y = 5.849 - 1.025X ₁ - 1.995X ₂ + 0.188X ₃ - 0.282X ₄ (r = 0.9298, p < 0.01, n = 96), where Y is sediment P flux potential in sediment-water interface, X ₁ is sediment Ca-P content, X ₂ is sediment Olsen-P content, X ₃ is sediment SOC content, and X ₄ is sediment Al-P content. Therefore, future research will focus on these sediment properties to analyze the interrelation among sediment properties factors, main vegetable factors, and environment factors which influence the sediment P flux potential in sediment-water interface.

Prediction of non-muscle invasive bladder cancer outcomes assessed by innovative multimarker prognostic models

Background

We adapted Bayesian statistical learning strategies to the prognosis field to investigate if genome-wide common SNP improve the prediction ability of clinico-pathological prognosticators and applied it to non-muscle invasive bladder cancer (NMIBC) patients.

Methods

Adapted Bayesian sequential threshold models in combination with LASSO were applied to consider the time-to-event and the censoring nature of data. We studied 822 NMIBC patients followed-up >10 years. The study outcomes were time-to-first-recurrence and time-to-progression. The predictive ability of the models including up to 171,304 SNP and/or 6 clinico-pathological prognosticators was evaluated using AUC-ROC and determination coefficient.

Results

Clinico-pathological prognosticators explained a larger proportion of the time-to-first-recurrence (3.1 %) and time-to-progression (5.4 %) phenotypic variances than SNPs (1 and 0.01 %, respectively). Adding SNPs to the clinico-pathological-parameters model slightly improved the prediction of time-to-first-recurrence (up to 4 %). The prediction of time-to-progression using both clinico-pathological prognosticators and SNP did not improve. Heritability (ĥ²) of both outcomes was <1 % in NMIBC.

Conclusions

We adapted a Bayesian statistical learning method to deal with a large number of parameters in prognostic studies. Common SNPs showed a limited role in predicting NMIBC outcomes yielding a very low heritability for both outcomes. We report for the first time a heritability estimate for a disease outcome. Our method can be extended to other disease models.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2361-7) contains supplementary material, which is available to authorized users.