Distribution Of Total Nitrogen Research Articles

Variations in soil physico-chemical properties, soil stocks, and soil stoichiometry under different soil layers, the major forest region Liupan Mountains of Northwest China.

Liupan Mountains are an important region in China in the context of forest cover and vegetation due to huge afforestation and plantation practices, which brought changes in soil physio-chemical properties, soil stocks, and soil stoichiometries are rarely been understood. The study aims to explore the distribution of soil nutrients at 1-m soil depth in the plantation forest region. The soil samples at five depth increments (0-20, 20-40, 40-60, 60-80, and 80-100 cm) were collected and analyzed for different soil physio-chemical characteristics. The results showed a significant variation in soil bulk density (BD), soil porosity, pH, cation exchange capacity (CEC), and electric conductivity (EC) values. More soil BD (1.41 g cm-3) and pH (6.97) were noticed in the deep soil layer (80-100 cm), while the highest values of porosity (60.6%), EC (0.09 mS cm-1), and CEC (32.9 c mol kg-1) were reflected in the uppermost soil layer (0-20 cm). Similarly, the highest contents of soil organic carbon (SOC), total phosphorus (TP), available phosphorus (AP), total nitrogen (TN), and available potassium (AK) were calculated in the surface soil layer (0-20 cm). With increasing soil depth increment a decreasing trend in the SOC and other nutrient concentration were found, whereas the soil total potassium (TK) produced a negative correlation with soil layer depth. The entire results produced the distribution of SOCs and TNs (stocks) at various soil depths in forestland patterns were 0→20cm > 20→40cm > 40→60cm ≥ 60→80cm ≥ 80→100 cm. Furthermore, the stoichiometric ratios of C, N, and P, the C/P, and N/P ratios showed maximum values (66.49 and 5.46) in 0-20 cm and lowest values (23.78 and 1.91) in 80-100 cm soil layer depth. Though the C/N ratio was statistically similar across the whole soil profile (0-100 cm). These results highlighted that the soil depth increments might largely be attributed to fluctuations in soil physio-chemical properties, soil stocks, and soil stoichiometries. Further study is needed to draw more conclusions on nutrient dynamics, soil stocks, and soil stoichiometry in these forests.

Mapping vertical distribution of SOC and TN in reclaimed mine soils using point and imaging spectroscopy

Soil organic carbon (SOC) and total nitrogen (TN) contents in different soil horizons are essential for vegetation growth and crucial indicators to evaluate soil quality in reclaimed mining areas. Compared with conventional wet chemistry methods, soil spectroscopy, including imaging spectroscopy, can be used as a cost and time-efficient soil analysis technique. However, there is a great challenge in combining laboratory point spectra and laboratory hyperspectral imagery for mapping vertical distribution of SOC and TN (0–100 cm) in reclaimed soils. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The main objective of this study is to provide a generic workflow to efficiently evaluate and map reclaimed mine soils in different horizons using imaging spectroscopy and machine learning approaches. A total of 65 soil samples (0–100 cm) were collected from three reclaimed mining lands and one natural site in northern China. Both point soil spectral information and hyperspectral images (350–2500 nm) were obtained under laboratory condition. In order to enhance the relationship between soil quality indicators and spectral features, the stacked feature selection algorithms and three-bands spectral indices were proposed for further modelling. Three machine learning methods (partial least squares regression; PLSR, random forest; RF, and radial basis function model; RBF) based on the point spectra were applied to calibrate and map continuous vertical distribution of SOC and TN. According to the results, thirty spectral bands were identified as important spectral features for SOC and eighteen bands for TN. With feature spectral bands and optimized three-bands spectral indices, the RF model yielded the best predictions for both SOC (R2 = 0.97, RMSE = 7.5 g kg−1) and TN (R2 = 0.78, RMSE = 0.33 g kg−1). It was concluded that imaging spectroscopy can be used to quantify and map soil quality indicators for better monitoring ecological restoration process in reclaimed soil of mining site.

Alpine Meadow Degradation Changed Soil Nitrogen Characteristics in the Eastern Qilian Mountains Area, Northwest China

ABSTRACT Nitrogen is the crucially sustainable element for most ecosystem including grassland. Fenced alpine meadow grassland (FG), lightly, moderately and heavily degraded (LD, MD and HD) alpine meadow in spring, summer and winter were studied to clear the effects of alpine meadow degradation on soil total nitrogen (TN), available nitrogen (AN), ammonium nitrogen (NH4 +-N), nitrate nitrogen (NO3 –-N), inorganic nitrogen (IN) content and the ratio of inorganic nitrogen to available nitrogen (IN/AN), and to find practical management strategies on the background of alpine meadow degradation and ecological environment restoration in the Eastern Qilian Mountains area, northwest China. The results showed that soil total nitrogen contents of the alpine meadow types were at a low level, ranged from 1.60 g·kg−1 to 5.15 g·kg−1, but soil available nitrogen contents was at a high level, ranged from 373.2 mg·kg−1 to 650.8 mg·kg−1in the study area. Alpine meadow degradation can seasonally change soil nitrogen status. Degraded alpine meadow had more inorganic nitrogen than fenced meadow in surface soil. Degradation only changed soil NO3 −-N profile distribution in winter and had no significant effect on profile distribution of TN, AN, NH4 +-N and IN. There were significant interactions of alpine meadow types, seasons and soil depth on soil available nitrogen, NH4 +-N, NO3 –-N and inorganic nitrogen content. Although soil available nitrogen increased under degradation, nitrogen input is needed in the restoration of heavily degraded alpine meadow during the summer growing season to improve vegetation coverage because of the low soil inorganic nitrogen and IN/AN ratio in summer growing season in 10–20 cm and 20–30 cm depth.

County-Scale Spatial Distribution of Soil Nutrients and Driving Factors in Semiarid Loess Plateau Farmland, China

Characterized by a topography of thousands of ravines, the Loess Plateau has highly complex spatial variability in terms of soil nutrients. Therefore, it is of considerable importance to study the soil nutrient spatial distribution, driving factors of precise fertilizer management, and the strategic use of soil nutrient resources. In 2017, 242 soil samples were taken from the semiarid Anding district farming region in northern China. The spatial variability and factors influencing soil nutrients were studied using statistical and geostatistical methods. The results showed that the mean soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), available potassium (AK), and pH values were averaged at 12.64 g·kg−1, 0.84 g·kg−1, 23.20 mg·kg−1, 188.87 mg·kg−1, and 8.60, respectively. The nugget-to-sill ratios for the semi-variograms of SOM, TN, AP, and AK varied from 25.84 to 49.93%, while the coefficients of variation varied from 24.53 to 69.44%, revealing that all four indicators exhibited considerable variability, and that the samples’ geographical variability was produced by a combination of random and structural factors. Overall increasing trends were exhibited from the middle to the northeast and southwest in the distributions of SOM, TN, and AP. The spatial distribution of AK displayed the opposite trend, increasing from the southwest to north and southeast. The texture of the tillage layer was the main factor directly affecting SOM, and explained 8% of its variation. The distribution of TN was mainly influenced by the irrigation method and water source type. AP and AK contents differed significantly between the two parent materials, three textures, and three topography types at the level of p < 0.01. In conclusion, the regional soil fertility was poor, spatial heterogeneity was moderate, and influencing factors were complex, highlighting the need to adopt precise fertilization management and adopting land management measures according to the actual influencing factors of each nutrient, thereby contributing to the enhancement of regional fertility.

Simulation on TN and TP Distribution of Sediment in Liaohe Estuary National Wetland Park Using MIKE21-Coupling Model

A hydrodynamic-water quality model was established using MIKE21 to analyze the distribution of total nitrogen (TN) and total phosphorus (TP) in the wetland sediments of Liaohe Estuary National Wetland Park. The purpose of this model is to investigate the spatial and temporal variation patterns in wetland sediments and the distribution of pollutant contents. The research determines the applicability of this model in accurately predicting these patterns. The simulated contour map of the water quality concentration displays significant variation characteristics and reflects the actual concentration of pollutants in the wetland sediment of the Liaohe Estuary, proving the coupled model to be reasonable and accurate. The water quality simulation results indicate that water flowing through the wetland aids in purifying pollutants in the sediment, and the purification effect is more significant during the flood season. The MIKE21 model’s treatment reveals that the content of TN in wetland sediments decreases from southwest to northeast in the surface layer, following the flow direction of surface water. As the depth increases, the content of TN also decreases, with the bottom layer showing a decrease from southwest to northeast. The TP in wetland sediments receives surface water runoff and diffuses from upstream to downstream. The content of TP gradually decreases with increasing depth.

Vertical distribution and pollution assessment of TN, TP, and TOC in the sediment cores of cage farming areas in Dongshan Bay of southeast China

Cage farming is an important means of aquacultural production, while its potential environmental pollution needs to be further investigated. In this study, Dongshan Bay was taken as an example to investigate whether long-term cage farming in a semi-closed bay would cause environmental pollution via vertical distribution assessment. The four sediment cores (YB1, YB2, B1, and B2) were collected from two cage farming areas. Total nitrogen (TN), total organic carbon (TOC), and total phosphorus (TP) were measured. The results showed a negative correlation between TN and TOC and the sediment depth at four sampling sites, and TP was also negatively correlated with the depth at three sites. The average TN (1,405.8, 1,413.8, 1,115.7, and 936.1 mgkg−1) and TP (1,206, 1,141.6, 1,064.6, and 932.8 mgkg−1) values of the four sites were markedly higher than the safety level, with the indexes STN, STP, FF, and ON of the four sites indicating moderate to severe pollution of nitrogen and phosphorus. Particularly, the YB1 and YB2 sites in the area with lower current speed have more severe pollution. The C/N ratio uncovered that the organic matter (OM) might mainly derived from the phytoplankton and nonfibrous plants as a result of excessive fish feed and feces. Collectively, the results indicated that long-term (more than 10 years) cage farming activity in a semi-closed bay such as Dongshan Bay had a negative impact on the environmental quality. Despite limitations in sample size and the absence of stable isotopic analyses, this study enhances our understanding of environmental changes and endogenous pollution risks in shallow marine aquaculture areas. Moreover, it suggests practical approaches such as implementing alternative farming and fallowing periods, should be conducted to mitigate the pollution.

Distribution of Total Nitrogen in Soils of the Tropical Highlands of Cameroon

Distribution of Total Nitrogen in Soils of the Tropical Highlands of Cameroon

Soil Aggregates and Aggregate-Associated Carbon and Nitrogen in Farmland in Relation to Long-Term Fertilization on the Loess Plateau, China

Soil aggregation plays a critical role in the maintenance of soil structure and crop productivity. Fertilization influences soil aggregation, especially by regulating soil organic carbon (SOC) and total nitrogen (TN) contents in aggregate fractions. Here, we conducted a fixed-site field experiment to quantify the effect of five N application rates: 0, 75, 150, 225, and 300 kg·N·ha−1, denoted as N0, N75, N150, N225, and N300, respectively, on soil aggregate stability, aggregate-associated SOC and TN sequestration and crop productivity. Soil aggregates were divided into >0.25 (>5, 5–2, 2–1, 1–0.5, 0.5–0.25) and <0.25 mm through wet and dry sieving methods. The results showed that long-term fertilization increased the proportion of macro-aggregates (>0.25 mm), decreased the proportion of micro-aggregates (<0.25 mm), and improved the aggregates stability. Compared with N0, the proportion of micro-aggregates in N225 was significantly decreased by 66.45% under wet sieving, while the proportion of >5 mm macro-aggregates in N225 was significantly increased by 19.24% under dry sieving (p < 0.05). With the increase in N application rate, the bulk SOC and TN contents first increased and then decreased, and the SOC and TN of N225 were significantly increased by 17.75% and 72.33% compared with N0 (p < 0.05). More specifically, fertilization promoted the distribution and enrichment of SOC and TN in macro-aggregates and reduced the C/N of the micro-aggregates and the contribution of SOC and TN in the micro-aggregates. Compared with N0, the contribution rate of macro-aggregates to SOC and TN of N225 under wet sieving was significantly increased by 84.13 and 17.18%, respectively, while the C/N of micro-aggregates of N225 under wet and dry sieving methods was significantly decreased by 45.95 and 31.74%, respectively (p < 0.05). Moreover, fertilization improved the yield, and N225 significantly increased the total yield by 80.68% compared with N0 (p < 0.05). In conclusion, N225 was the suitable N application for improving soil aggregate stability, carbon and nitrogen sequestration, and crop productivity on the Loess Plateau, China.

Evaluation of water quality pollution and analysis of vertical distribution characteristics of typical Rivers in the Pearl River Delta, South China

Water quality comprehensive evaluation is an essential technical measure for water environment management and treatment. The previous research methods were often insufficient for studying black-sticking water bodies' formation and transformation mechanisms. In view of this, the single pollution index method and the comprehensive water quality identification index method (Iwq) were used to evaluate the pollution characteristics of rivers; the main pollution factors and sources of the watershed were determined by principal component analysis (PCA), and the vertical stratification characteristics of the water bodies were analyzed. The results showed that the total nitrogen (TN) values of pollutants in typical rivers in the Pearl River Delta were higher than the class V water quality standard, and the ammonia nitrogen (NH3−N) pollution level was the second-highest. TN concentration ranges from 4.27 to 19.83 mg/g, and NH3-N concentration ranges from 2.44 to 15.37 mg/g. In addition, in the monitoring of 15 rivers, 11 of them were the inferior V surface water, including five rivers' comprehensive water quality categories for black-stinking water bodies. This may be related to the process of water self-purification and pollutant transport, and rivers in densely populated areas are often subject to discharge from domestic sewage and industrial sewage. The results of the PCA extracted three principal components (PC), accounting for 88.825% of the total variance, with the first and third PCs controlled by human activities and the second PC influenced by natural sources. There is a more apparent vertical stratification of water bodies here in the typical rivers of the Pearl River Delta, and DO was an important factor affecting the vertical distribution of chemical oxygen demand (COD), NH3-N, TN, total phosphorus (TP), sulfide, Ferrum (Fe), and manganese (Mn). The severe lack of DO in deep water bodies led to elevated levels of NH3-N, Fe, and Mn, and gases such as hydrogen sulfide was released under anaerobic conditions, resulting in eutrophication and black-sticking levels in water bodies.

Mapping Topsoil Total Nitrogen Using Random Forest and Modified Regression Kriging in Agricultural Areas of Central China

Accurate understanding of spatial distribution and variability of soil total nitrogen (TN) is critical for the site-specific nitrogen management. Based on 4337 newly obtained soil observations and 33 covariates, this study applied the random forest (RF) algorithm and modified regression kriging (RF combined with residual kriging: RFK, hereafter) model to spatially predict and map topsoil TN content in agricultural areas of Henan Province, central China. According to the RFK prediction, topsoil TN content ranged from 0.52 to 1.81 g kg-1, and the farmland with the topsoil TN contents of 1.00-1.23 g kg-1 and 0.80-1.23 g kg-1 accounted for 48.2% and 81.2% of the total farmland area, respectively. Spatially, the topsoil TN in the study area was generally higher in the west and lower in the east. By using the Boruta variable selection algorithm, soil organic matter (SOM) and available potassium contents in topsoil, nitrogen deposition, average annual precipitation, livestock discharges, and topsoil pH were identified as the main factors driving the spatial distribution and variation of soil TN in the study area. The RF and RFK models used showed the expected performance and achieved acceptable TN prediction accuracy. In comparison, RFK performed slightly better than the RF model. The R2 and RMSE achieved by the RFK model were improved by 4.5% and 4.5%, respectively, compared with that by the RF model. However, the results suggest that RFK was inferior to the RF model in quantifying prediction uncertainty and thus may have a slight disadvantage in model reliability.

Amount and Vertical Distribution of Soil Organic Carbon and Total Nitrogen in a Dry Tropical Forest Ecosystem, Tanzania

There is a growing interest in understanding soil organic carbon (SOC) and total nitrogen (TN) of various ecosystems worldwide, because they are important indicators of soil quality and soil fertility, especially on the availability of essential nutrients for plant growth; and climate change mitigation. We tested the hypothesis that the amount and vertical distribution of SOC and TN in 0-30cm and 30-100cm depths differ significantly in miombo woodland ecosystems. Soil samples were collected from 15m-radius circular plots (n=33). SOC was determined by Mid-Infrared (MIR) spectroscopy (ICRAF approach) and the Walkley and Black method (NAFORMA approach). The mean amount of SOC and TN at 30-100cm depth were significantly higher (<i>p</i>=0.003 and <i>p</i>=0.0001, respectively) than that within the 0-30cm depth. The amount of SOC at 20-40cm (39tCha^-1) was found to be significantly (<i>p</i>=0.0007) higher than at 0-20cm (32tCha^-1) followed by decreasing pattern to 100cm. On the other hand, TN decreased substantially from 0-20cm to 100cm depth. SOC was significantly (<i>p</i><0.05) and positively correlated with TN. The NAFORMA approach estimated significantly (<I>P</I><<i>0.05</i>) higher SOC than ICRAF approach. Clearing of forests for sesame cultivation invariably resulted in increased nitrogen in the top soil due to addition of ammonium fertilizers, but loss of SOC is due to removal of biomass (including slash burning) and a reduction in the quantity and quality of organic inputs added to the soil. Accurate estimation of SOC at national and regional scales should use the modern methods complimented by the standard methods in different ecosystems.

Maize straw application as an interlayer improves organic carbon and total nitrogen concentrations in the soil profile: A four-year experiment in a saline soil

Soil salinization is a critical environmental issue restricting agricultural production. Deep return of straw to the soil as an interlayer (at 40 cm depth) has been a popular practice to alleviate salt stress. However, the legacy effects of straw added as an interlayer at different rates on soil organic carbon (SOC) and total nitrogen (TN) in saline soils still remain inconclusive. Therefore, a four-year (2015–2018) field experiment was conducted with four levels (i.e., 0, 6, 12 and 18 Mg ha–1) of straw returned as an interlayer. Compared with no straw interlayer (CK), straw addition increased SOC concentration by 14–32 and 11–57% in the 20–40 and 40–60 cm soil layers, respectively. The increases in soil TN concentration (8–22 and 6–34% in the 20–40 and 40–60 cm soil layers, respectively) were lower than that for SOC concentration, which led to increased soil C:N ratio in the 20–60 cm soil depth. Increases in SOC and TN concentrations in the 20–60 cm soil layer with straw addition led to a decrease in stratification ratios (0–20 cm:20–60 cm), which promoted uniform distributions of SOC and TN in the soil profile. Increases in SOC and TN concentrations were associated with soil salinity and moisture regulation and improved sunflower yield. Generally, compared with other treatments, the application of 12 Mg ha–1 straw had higher SOC, TN and C:N ratio, and lower soil stratification ratio in the 2015–2017 period. The results highlighted that legacy effects of straw application as an interlayer were maintained for at least four years, and demonstrated that deep soil straw application had a great potential for improving subsoil fertility in salt-affected soils.

Spatial Distribution and Sources of Organic Matter in the Surface Sediments of Fuxian Lake, SW China

Sedimentary organic matter is an important component of the metabolism of a lake’s ecosystem, and it is generally derived from both the watershed and the primary productivity of a lake. Understanding the sources of organic matter in lakes and lake trophic status is important when evaluating the quality of lake ecosystems. We summarize the spatial distribution of total nitrogen (TN), total organic carbon (TOC), TOC/TN (C/N) molar ratios, and organic carbon isotope (δ13Corg) of the surface sediments of Fuxian Lake, Yunnan–Guizhou Plateau, Southwest China, which is the second deepest freshwater oligotrophic lake in China. The results show that the distributions of TN, TOC, C/N, and δ13Corg of the surface sediments are spatially heterogeneous, which is also the case for the trophic conditions of the lake. Compared with the adjacent eutrophic lakes and typical lakes in other areas with strong human activities, the content of organic matter is at a low level. Meanwhile, the autochthonous organic carbon in the surface sediments was characterized by lower δ13Corg (−25.3~−28.5) and C/N (8.7~12.9), suggesting that the biological carbon pump effect plays a significant part in the stability of carbon sinks by coupling with carbonate weathering. Our results emphasize the importance of the carbon sink of coupled carbonate weathering and aquatic photosynthesis in the evolution of the carbon cycle in lakes. Although modern monitoring shows that Fuxian Lake is an oligotrophic lake, there are potential risks of organic nitrogen pollution with respect to surface sediments, especially in northern and southern shallow-water areas. The organic pollution of lakes can be reduced by controlling the discharge of wastewater and reducing the nutrient loading of agricultural runoff.

Organic Fertilizer Application Effects on Soil Agglomeration Stability and Organic Carbon and Total Nitrogen Distribution: A Meta-Analysis

The application of organic fertilizers is a standard measure of circular agriculture, which can purify the environment, ensure food safety and strengthen the sustainable use of soil. The purpose of this study was to evaluate the effects of organic fertilizers on the stability of soil aggregates and soil fertility using a meta-analysis. A total of 169 case-controlled studies from 45 papers were included through screening, and Wordy sentences 169 soil data from the organic fertilizer group and 169 soil data from the control group (CK) were collected. The stability of meta-analysis results after combining effect sizes was assessed by sensitivity analysis, and the publication bias was evaluated by funnel plot. Meta-analysis results showed that the application of organic fertilizer significantly affected the mean weight diameter (MWD) (P&lt;0.05), increased the organic carbon (SOC) content of the soil (P&lt;0.05) .and significantly increased the total nitrogen (STN) content of the earth (P&lt;0.05). Funnel plot analysis showed that there was only a small amount of publication bias in the study .and sensitivity research showed that the analysis was stable and reliable. In conclusion, the application of organic fertilizer can significantly affect the stability of soil aggregates and has a potentially positive effect on improving soil fertility. This meta-analysis provides a scientific basis for the rational utilization of organic fertilizers and soil structure optimization in China.

Effect of different planting pattern arrangements on soil organic matter and soil nitrogen content under a maize/soybean strip relay intercropping system.

Assessing the spatial distribution of organic matter and total nitrogen in soil is essential for management and optimum utilization of fertilizers. Therefore, the present field experiment was conducted to evaluate the impact of different planting pattern arrangements on the spatial distribution of soil total nitrogen and organic matter content under a maize/soybean strip relay intercropping system. The planting was arranged in a manner such that soil sampling could be done from continuous maize/soybean relay strip intercropping (MS1), maize/soybean relay strip intercropping in rotation (MS2), traditional maize/soybean intercropping (MS3), sole maize (M), sole soybean (S), and fallow land (FL) from 2018 to 2020. The results showed significant variations for soil organic matter and total nitrogen content under different planting pattern arrangements of maize and soybean in the strip relay intercropping system. Across all systems, the highest soil organic matter (29.19 g/kg) and total nitrogen (10.19 g/kg) were recorded in MS2. In contrast, the lowest soil organic matter (1.69 g/kg) and total nitrogen (0.64 g/kg) were observed in FL. Soil organic matter and total nitrogen in MS2 increased by 186.45% and 164.06%, respectively, when compared with FL. Soil organic matter and total nitrogen in MS2 increased by 186.45% and 164.06%, respectively, when compared with FL. Furthermore, under MS2, the spatial distribution of soil organic matter was higher in both maize and soybean crop rows as compared with other cropping patterns, whereas the soil total nitrogen was higher under soybean rows as compared with maize in all other treatment. However, correlation analysis of the treatments showed variations in organic matter content. It can be concluded that different planting patterns can have varying effects on soil organic matter and total nitrogen distribution under the strip relay intercropping system. Moreover, it is recommended from this study that MS2 is a better planting pattern for the strip relay intercropping system, which can increase the spatial distribution of soil organic matter and total nitrogen, thereby improving soil fertility, C:N ratio, and crop production. This study will serve as a foundation towards the scientific usage of chemical fertilizers in agricultural sector.

Remote Sensing Retrieval of Total Nitrogen in the Pearl River Delta Based on Landsat8

The Pearl River Delta in South China is subject to severe eutrophication, which is significantly exacerbated by the total nitrogen (TN). Remote sensing technology with large-scale synchronous observations in the Pearl River Delta can effectively monitor organic pollution. Statistical methods based on remote sensing images have been widely used in water quality parameter retrieval for inland rivers, reservoirs, and lakes, but have seldom been applied in the Pearl River Delta. TN is also a non-optically active substance, so it is difficult to retrieve TN through analysis methods. This study retrieves the concentration of total nitrogen (TN) based on Landsat8 images of the Pearl River Delta using a statistical method. The stepwise regression function is built by analyzing the TN concentration and the single-band, two-band, and three-band spectral information groups measured by an ASD FieldSpec3 spectrometer. The retrieval results show that the proposed method performs well with a small mean absolute error (MAE) (0.36 mg/L for TN) and high agreement (R2 = 0.61 for TN) between the in situ data and the retrieval concentration. The results demonstrate that the concentration of TN in the east of the Pearl River Delta was higher than in the west. Dachan Bay and Shenzhen Bay had the highest TN concentrations, which were around 3.02 mg/L and 3.67 mg/L. The 750–850 nm band could be an important reference for further exploring the spectral characteristics and retrieval of TN. The retrieval method in this study is easy to implement and convenient for local TN distribution capture, which can provide a timely reference for daily water quality supervision and management in the Pearl River Delta.

Satellite and Machine Learning Monitoring of Optically Inactive Water Quality Variability in a Tropical River

Large-scale monitoring of water quality parameters (WQPs) is one of the most critical issues for protecting and managing water resources. However, monitoring optically inactive WQPs, such as total nitrogen (TN), ammoniacal nitrogen (AN), and total phosphorus (TP) in inland waters, is still challenging. This study constructed retrieval models to explore the spatiotemporal evolution of TN, AN, and TP by Landsat 8 images, water quality sampling, and five machine learning algorithms (support vector regression, SVR; random forest regression, RFR; artificial neural networks, ANN; regression tree, RT; and gradient boosting machine, GBM) in the Nandu River downstream (NRD), a tropical river in China. The results indicated that these models can effectively monitor TN, AN, and TP concentrations at in situ sites. In particular, TN by RFR as well as AN and TP by ANN had better accuracy, in which the R2 value ranged between 0.44 and 0.67, and the RMSE was 0.03–0.33 mg/L in the testing dataset. The spatial distribution of TN, AN, and TP was seasonal in NRD from 2013–2022. TN and AN should be paid more attention to in normal wet seasons of urban and agricultural zones, respectively. TP, however, should be focus on in the normal season of agricultural zones. Temporally, AN decreased significantly in the normal and wet seasons while the others showed little change. These results could provide a large-scale spatial overview of the water quality, find the sensitive areas and periods of water pollution, and assist in identifying and controlling the non-point source pollution in the NRD. This study demonstrated that multispectral remote sensing and machine learning algorithms have great potential for monitoring optically inactive WQPs in tropical large-scale inland rivers.

Spatial Prediction of Total Nitrogen in Soil Surface Layer Based on Machine Learning

In order to satisfy the basic requirements of sustainable agricultural development, it is important to understand the spatial distribution characteristics of soil total nitrogen (TN) content to better guide accurate fertilization to increase grain yield. To this end, this paper constructs three inversion models of partial least squares regression (PLSR), back propagation neural network (BPNN) and support vector machines (SVM) with remote sensing data to predict the TN content in Datong County, Xining City, Qinghai Province, China. The results showed that the average TN content was 1.864 g/kg, and the coefficient of variation (CV) was 30.596%. The prediction accuracy of the SVM model (R2 = 0.676, RMSE = 0.296) among the three inversion models was higher than that of the BPNN model (R2 = 0.560, RMSE = 0.305) and the PLSR model (R2 = 0.374, RMSE = 0.334). The model with the highest accuracy predicted the spatial distribution of TN, and TN content showed a spatial distribution trend which was high in the northwest and low in the southeast, and gradually decreased from north to south. This study provides reference basis and support for soil fertility evaluations and sustainable agricultural development.

Effects of vegetation and terrain changes on spatial heterogeneity of soil C-N-P in the coastal zone protected forests at northern China.

Soil organic carbon (SOC), total nitrogen (TN) and total phosphorus (TP) are important indicators reflecting soil quality, and they can be used to effectively evaluate the effect of soil remediation. Many studies have evaluated the content of SOC, TN and TP in different ecosystems. However, after constructing protected forests for ecological restoration in the ecologically fragile coastal zone, the spatial distribution and influencing mechanism of SOC, TN and TP content is still uncertain. In this study, the spatial heterogeneity and influencing factors of SOC, TN and TP in surface (0-20cm) soil were analyzed by traditional analysis and geostatistics. A total of 39 soil samples were collected under the coastal zone protected forest types including Quercus acutissima Carruth (QAC), Pinus thunbergii Parl (PTP), mixed PTP and QAC (QP) and Castanea mollissima BL (CMB) in the coastal zone protected forests in northern China. The results show that SOC, TN and TP content were defined as moderate variation, and they also show significant changes under different protected forest types (P<0.05). The semivariance results indicate that SOC, TN and TP all exhibited strong spatial dependence class, with Range of 224m, 229m and 282m respectively, which were more than the sampling scale of 200m. The spatial prediction results showed that SOC, TN and TP content all appear in large areas of extremely low value in CMB, and its cross validation results showed that using vegetation and terrain factors as covariates in the spatial prediction of SOC, TN and TP can improve the prediction accuracy. The results of correlation analysis showed that the influencing factor for SOC and TN, and TP were NDVI and topographical changes, respectively. In general, vegetation and terrain factors as auxiliary factors can improved the accuracy of soil C-N-P spatial distribution prediction after afforestation in coastal zone.

Impact of deforestation and temporal land-use change on soil organic carbon storage, quality, and lability.

Soil organic carbon (SOC) plays a key role in regulating soil quality functions and ecosystem services. The objective of our study was to evaluate the impact of deforestation and subsequent land-use change on the SOC and total nitrogen (TN) concentration, quality, and lability under otherwise similar soil and environmental conditions. Geo-referenced composite soils (0 to 30 cm depth at 7.5 cm interval) sampled from agriculture, bioenergy plantations (Miscanthus x giganteus), Conservation Reserve Program (CRP), and wetland were analyzed for SOC, TN, active C (AC), humic- and fulvic acid (HA and FA), non-humic C (NH), E4: E6 ratio, humification indices (HI, HR, and DH), and carbon and nitrogen management indices (CPI, NPI, and CMI), compared to soils under protected forest as a control. Results showed that the CRP had the highest depth distribution and profile-wise stocks of SOC, TN, AC, and FA with respect to the lowest in agriculture upon conversion of forest. Moreover, the SOC and TN contents were significantly stratified in the CRP when compared to agriculture. While agriculture had the wider HA: FA ratios with highest HI and HR but lowest DH values, the CRP, in contrast, had the narrow HA: FA ratios with lowest HI but highest DH values, when compared to the forest. Spectral analyses have shown lower E4: E6 ratios under the forest when compared to both agriculture and the CRP; however, the later had significantly higher E4: E6 ratios than that of agriculture. The CPI, as measures of SOC accumulation or depletion, significantly decreased by 16% under agriculture but increased by 12% under the CRP. While the CMI, as measures of SOC accumulation or depletion and lability, with higher values under the CRP suggested a proportionally more labile SOC accumulation, in contrast, the smaller values under agriculture indicated a greater depletion of labile SOC over time. Moreover, the CRP may have favored a more labile SOC accumulation with higher proportions of aliphatic C compounds, whereas agriculture may have a SOC with high proportions of non-labile aromatic C compounds. Principal components analysis clearly separated and/or discriminated the land-use impacts on soil carbon pools and TN. Likewise, redundancy analysis of the relationship between measured soil parameters and land-use validated that the TOC, TN, FA, humin, and CPI were significantly impacted due to synergism among soil properties as positively influenced by the CRP upon conversion of agriculture.