Effects of land use types on soil erodibility in a small karst watershed in western Hubei

Background

Soil erosion is a severe problem in the karst watershed, and analysis of soil erosion at the watershed scale is urgently needed.

Methods

This study tried to estimate the soil erodibility factor (K-factor) using the Erosion Productivity Impact Calculator (EPIC) nomograph and evaluate the spatial distribution of the predicted K-factor in a karst watershed. Soil properties and K-factors of five land use types (NF: natural mixed forest, CF: cypress forest, EF: economic forest, ST: stone dike terrace, VF: vegetable land) in the Xialaoxi small watershed were compared and key factors affecting erodibility were analyzed.

Results

Results showed that (1) The erodibility K-factor was unevenly distributed within different site types and strongly influenced by anthropogenic activities. The soil K-factors of sample sites subjected to frequent human disturbance (ST, VF) were high, ranging from 0.0480-0.0520 t hm² h/(MJ mm hm²), while the soil K-factors of natural site types (NF, CF, and EF) were low, ranging from 0.0436-0.0448 t hm² h/(MJ mm hm²). (2) The soil texture in the Xialaoxi watershed was mostly loamy, and that of the agricultural areas frequently disturbed by agricultural practices (ST, VF) was silty loam. (3) Soil carbon fractions were affected by land use types. Soil organic carbon storage of NF and CF had strong spatial heterogeneity. The soil organic carbon (SOC) and labile organic carbon (LOC) of the two were significantly higher than those of the disturbed EF and cultivated land soil. (4) There was a synergistic effect between the soil properties and the K-factor. K was significantly negatively related to sand fractions (2-0.05 mm) and non-capillary porosity, while positively related to silt content (0.05-0.002 mm). Overall, changes in bulk density (BD), total porosity (TP), non-capillary porosity (NCP), texture, and organic matter content caused by natural restoration or anthropogenic disturbance were the main reasons for soil erodibility. Natural care (sealing) and construction of stone dike planting practices were effective ways to reduce soil erosion in small karst watershed areas of western Hubei.

Digital mapping of soil erodibility factor in northwestern Iran using machine learning models

Understanding the spatial distribution of soil erodibility factor (K-factor) at the district scale is essential for managing water erosion risk. In this research, we performed to predict the low and high classes of K-factor in the northwest of Iran. Based on this, soil sampling was performed at 64 points using the grid sampling method with 1 km spacing. To calculate the K-factor, the distribution of particle size and organic carbon (OC) were determined. In addition, 21 terrain attributes were calculated by Digital Elevation Model (DEM) to add value to the soil data. Then, K-factor was modeled using Random Forest (RF) and Artificial Neural Network (ANN) models. In the next step, a non-linear Multiple Logistic Regression (NMLR) was used to obtain low and high classes of K-factor. The results showed that the performance of RF is superior to ANN with a high coefficient of determination [R² = 0.85] and good accuracy [RMSE = 0.003 (Mg ha h/ha MJ mm)]. Therefore, the RF was employed for predicting the K-factor spatial distribution. Finally, using the NMLR model, the study area was divided into low and high classes of K-factor with good correlation [R² Cox and Snell = 0.78, R² Nagelkerke = 0.65]. The areas of these two classes were 60.4% for low class and 39.6% for the high class of K-factor. Based on these results, it was concluded that the resultant map of low and high classes of K-factor could be used by farmers and managers for managing soil water erosion risks in the study area.

CT pulmonary angiography in pregnancy: Specific conversion factors to estimate effective radiation dose from dose length product: A retrospective cross-sectional study across a multi-hospital integrated healthcare network

PURPOSE

Effective dose describes radiation-related cancer risk from CT scans and is estimated using a readily available conversion factor (k-factor), which varies by body part and study type. To purpose of this study is to determine the specific k-factor for CTPA in pregnant patients and its predictive factors.

METHODS

This retrospective cross-sectional study evaluates CTPA in pregnancy across a multihospital integrated healthcare network from January 2012 to April 2017. Patient and CTPA-related data were obtained from the electronic health record and a radiation dose index monitoring system. Each patient's effective dose was determined by patient-specific Monte-Carlo simulation with Cristy phantoms and divided by patient dose-length-product to determine the k-factor. K-factor for pregnant patients was compared to the k-factor for adults of standard physique with a one-sample t-test. Bivariate and multivariable analyses were performed for patient and CT predictors of k-factor.

RESULTS

A total of 534 patients were included. The mean k-factor for all patients was 0.0249 (mSv·mGy^-1·cm^-1), 78% greater than k-factor of 0.014 (p < 0.001) suggested for the general adult population. Multivariable analysis demonstrated lower k-factors with increasing pitch (p = 0.0002), patient size (p < 0.001), and scan length (p < 0.0001). The 120 kVp (p < 0.001) and 140 kVp (p = 0.0028) analyses showed a larger k-factor than 80 and 100 kVp studies combined.

CONCLUSIONS

Specific k-factor for CTPA in pregnant patients is greater than the previously used generic chest CT k-factor and should be used to estimate the effective dose for CTPA exams in pregnancy.

Structure of the Mini-K-J and Its Utility for Measuring Fast Life History Traits in Japanese Undergraduate Students

Life history theory is useful for taking an evolutionary approach to individual differences. An individual's life history strategy (LHS), based on life history theory, can be measured using the Arizona Life History Battery or a part of it-the Mini-K-as the K-factor. In this study, I examined two research questions regarding the Japanese version of the Mini-K (i.e., Mini-K-J). First, I assessed the construct validity and invariance between sexes of the Mini-K-J because there existed issues with the factor structure of the original Mini-K. These issues were addressed in the original Mini-K, but not in the Japanese version. In particular, I examined whether the instrument consists of a single higher order factor (K-factor) and whether sex invariance exists in the factor structure, following Richardson et al. Second, I assessed criterion validity of the Mini-K-J. In particular, I examined whether the Mini-K-J could capture fast LHS traits in Japanese undergraduates because the Mini-K-J has been validated only using slow LHS traits. The results showed that (1) the Mini-K-J generated a single higher order factor (i.e., K-factor) and five first-order factors, (2) there existed sex invariance of the factor structure, and (3) the higher order K-factor mean might have a different meaning between sexes. These results predominately support Richardson et al. Further, the higher order K-factor of the Mini-K-J could capture fast LHS personality traits. These results suggest that the Mini-K-J would be useful for future studies related to LHS.

From Environment to Mating Competition and Super-K in a Predominantly Urban Sample of Young Adults

Recent research suggests human life history strategy (LHS) may be subsumed by multiple dimensions, including mating competition and Super-K, rather than one. In this study, we test whether a two-dimensional structure best fit data from a predominantly urban sample of young adults ages 18-24. We also test whether latent life history dimensions are associated with environmental harshness and unpredictability as predicted by life history theory. Results provide evidence that a two-dimensional model best fit the data. Furthermore, a moderate inverse residual correlation between mating competition and Super-K was found, consistent with a life history trade-off. Our findings suggest that parental socioeconomic status may enhance investment in mating competition, that harshness might persist into young adulthood as an important correlate of LHS, and that unpredictability may not have significant effects in young adulthood. These findings further support the contention that human LHS is multidimensional and environmental effects on LHS are more complex than previously suggested. The model presented provides a parsimonious explanation of an array of human behaviors and traits and can be used to inform public health initiatives, particularly with respect to the potential impact of environmental interventions.

Repetitive transcranial magnetic stimulation over left angular gyrus modulates the predictability gain in degraded speech comprehension

Increased neural activity in left angular gyrus (AG) accompanies successful comprehension of acoustically degraded but highly predictable sentences, as previous functional imaging studies have shown. However, it remains unclear whether the left AG is causally relevant for the comprehension of degraded speech. Here, we applied transient virtual lesions to either the left AG or superior parietal lobe (SPL, as a control area) with repetitive transcranial magnetic stimulation (rTMS) while healthy volunteers listened to and repeated sentences with high- versus low-predictable endings and different noise vocoding levels. We expected that rTMS of AG should selectively modulate the predictability gain (i.e., the comprehension benefit from sentences with high-predictable endings) at a medium degradation level. We found that rTMS of AG indeed reduced the predictability gain at a medium degradation level of 4-band noise vocoding (relative to control rTMS of SPL). In contrast, the behavioral perturbation induced by rTMS changed with increased signal quality. Hence, at 8-band noise vocoding, rTMS over AG versus SPL decreased the number of correctly repeated keywords for sentences with low-predictable endings. Together, these results show that the degree of the rTMS interference depended jointly on signal quality and predictability. Our results provide the first causal evidence that the left AG is a critical node for facilitating speech comprehension in challenging listening conditions.

Soil erodibility in Europe: a high-resolution dataset based on LUCAS

The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032 thahha(-1)MJ(-1)mm(-1) with a standard deviation of 0.009 thahha(-1)MJ(-1)mm(-1). The yielded soil erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where highest percentages of surface stone cover were observed.