Coastal wetland sea source organic carbon content rapid prediction method based on soil particle size components

Abstract

The invention belongs to the technical field of environmental monitoring, and particularly relates to a prediction method for soil sea source organic carbon. The method comprises the following steps: (1) determining the content of each grade of particle size, the content of organic carbon and total nitrogen and an isotope delta 13C value in a soil sample; (2) calculating the total organic carbon content of the sea source organic carbon according to the ratio of the organic carbon content to the total nitrogen content of the soil sample and the isotope delta 13C value; (3) fitting the particle size content of each level in the soil sample; and (4) performing ridge regression fitting on the particle size data of each level of soil and the sea-source organic carbon content, determining an optimal K value according to a ridge trace map, and constructing a sea-source organic carbon ridge regression prediction model according to the optimal K value, thereby realizing prediction of the sea-source organic carbon content. According to the method, regression analysis is performed on each particle size component of the soil based on the ridge regression model, so that the influence of data colinearity on the model is avoided, and the prediction accuracy and universality are improved; and a large amount of element and isotope determination on the sample is not needed during determination, so that the workload is greatly reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of environmental monitoring, and in particular relates to a method for predicting marine organic carbon in soil. Background Art

[0002] Coastal wetlands are located in the transition zone between land and sea. They are unique areas formed mainly by the impact and accumulation of upstream rivers. They have a high carbon deposition rate and carbon burial capacity, and are an important part of the "blue carbon" ecosystem. The strong carbon sink capacity of coastal wetlands is due to the unique tidal phenomenon. While the tides wash the intertidal zone, they also deposit a large amount of marine organic carbon particles carried in it into the soil. This part of the sediment constitutes an important part of the organic carbon in the soil of coastal wetlands, which is also a key feature that distinguishes it from inland wetlands. At the same time, the particulate organic carbon carried by the upstream rivers gradually settles down in the estuary area as the terrain becomes flat, forming the terrestrial organic carbon part in the soil. In addition, the plant litter grown locally has accumulated over the years to form the plant-derived organic carbon part of the soil in coastal wetlands. Because of the unique hydrological conditions of the intersection of rivers and seas in coastal salt marshes, the composition of organic carbon in the soil is complex and diverse.

[0004] The coastal wetlands are flat and vast. The hydrodynamic intensity gradually decreases when upstream rivers and tides arrive. Under the action of hydrodynamic sorting, marine organic carbon particles of different sizes are deposited in sequence, making the soil particle size distribution show a certain distribution pattern from sea to land. In addition, different particle size components have different adsorption capacities for particulate organic carbon due to different specific surface areas. Fine-grained sediments have a larger specific surface area and a stronger adsorption capacity than coarse-grained sediments. Under the combined action of hydrodynamic sorting and the properties of sediment particle size itself, the marine organic carbon content in the intertidal zone soil of coastal wetlands shows a regular gradient distribution characteristic from sea to land with the sediment particle size.

[0005] It is worth noting that there is a strong correlation between the particle size components of intertidal zone soil in coastal wetlands, which makes the particle size components and marine organic carbon fit by ordinary least squares method, and the independent variables show strong collinearity, resulting in unstable estimation of prediction model coefficients and excessive variance, which affects the generalization ability of the model. The ridge regression model can effectively solve the problem of inaccurate model caused by collinearity between particle size components of intertidal zone soil in coastal wetlands by regularizing the coefficients, which can alleviate the overfitting problem and improve the generalization ability of the model. Therefore, the ridge regression model of particle size components and marine organic carbon in intertidal zone soil in coastal wetlands is constructed to predict marine organic carbon in soil more quickly and accurately.

[0006] At present, there are some methods for tracing the source of wetland organic carbon. Chinese patent document CN202210193492.5 discloses a method for determining the organic carbon content in marine sediments. The content of organic carbon in the ocean is determined by improving the potassium dichromate oxidation-spectrophotometry method. This method is only applicable to the determination of the organic carbon content in samples from a single marine source, and is not applicable to the tracing of organic carbon from multiple sources in coastal wetlands. Chinese patent document CN202310646963.8 discloses a method for tracing the source of wetland organic carbon in the whole system. This method determines the organic carbon from plants and microorganisms in wetland soil by measuring two biomarkers, normal alkanes and amino sugars in the soil. Chinese patent document CN202010196327.6 discloses a method, device, equipment and system for predicting terrestrial organic carbon content. Based on hydrodynamic conditions and using source distance, a prediction model is constructed for terrestrial marine source rocks in deepwater areas.

[0007] At present, the tracing of soil organic carbon in coastal wetlands mainly focuses on terrestrial, plant and microbial sources of organic carbon. The prediction method for the marine organic carbon content in the intertidal zone is still blank, so there is an urgent need for a method to fill this gap. Summary of the invention

[0008] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a method for predicting marine organic carbon in intertidal soil of coastal wetlands under complex sources, so as to fill the gap in the existing soil organic carbon tracing direction and provide direct guidance for exploring the distribution pattern of soil organic carbon in coastal wetlands.

[0009] To achieve the above object, the technical solution adopted by the present invention is: a method for rapidly predicting the marine organic carbon content in coastal wetlands based on soil particle size components, comprising the following steps: (1) The content of each particle size, organic carbon and total nitrogen content and isotope δ 13 The C value is measured; (2) Based on the ratio of organic carbon to total nitrogen content and isotope δ 13 C value, calculate the proportion and specific content of marine organic carbon in the total organic carbon; (3) Constructing a ridge regression prediction model for marine organic carbon: The soil particle size data measured in the laboratory were used for ridge regression fitting with the marine organic carbon content. The optimal K value was determined based on the ridge trace plot, and regression modeling was performed based on this. The prediction model is as follows: ; in, Expressed as marine organic carbon content , are constants, ; Expressed as the content of each particle size component; (4) Fitting the content of each particle size in the soil sample: ; in, are constants, ; It is expressed as the content of clay components in sediments. Expressed as the content of fine powder components in sediments, Expressed as the content of medium silt components in sediments, It is expressed as the content of coarse silt components in the sediment. Expressed as the content of sand components in sediments; (5) By substituting the fitted data of the content of each particle size in the soil sample into the above-mentioned prediction model, the prediction of the marine organic carbon content in coastal wetlands based on the soil particle size components can be achieved.

[0010] Preferably, in step (1), before determining the content of each particle size in the soil sample, the soil sample is pretreated as follows: H2O2 and hydrochloric acid are added to the air-dried soil sample in sequence to remove soil organic matter and inorganic salts; after the reaction is completed, the sample is repeatedly washed with deionized water for multiple times and allowed to stand; finally, sodium hexametaphosphate solution is added and shaken.

[0011] Preferably, in step (1), before determining the organic carbon and total nitrogen content in the soil sample, the soil sample is pretreated as follows: hydrochloric acid is added to the air-dried soil sample; the sample is then repeatedly washed with deionized water until the supernatant is transparent and close to neutral, and then dried for later use.

[0012] Preferably, in step (2), the MixSIAR package in R language is used to construct a Bayesian three-end member organic carbon mixing model of terrestrial, marine and plant sources, and the model formula is: ; in, and are the measured values ​​of the samples, and are the terrestrial end member values ​​of each indicator, and are the ocean end member values ​​of each indicator, and are the endmember values ​​of each index plant, Respectively, they are the contribution ratios of terrestrial, marine and plant sources in soil organic carbon in the samples.

[0013] Compared with the prior art, the present invention has the following beneficial effects: it provides a method for quickly predicting marine organic carbon in coastal wetland soil; the method performs regression analysis on soil particle size components based on a ridge regression model, thereby avoiding the influence of data collinearity on the model and increasing the accuracy and versatility of prediction; the method does not require a large amount of element and isotope determination of samples when determining marine organic carbon in coastal wetland soil, thereby greatly reducing the workload; and it fills the gap in the prediction method of marine organic carbon in coastal wetlands. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is the linear fitting diagram of the transformation between the content of soil clay component, medium silt component, coarse silt component, sand component and fine silt component; Figure 2 This is a correlation diagram between the measured values ​​and predicted values ​​of the ridge regression model of soil marine organic carbon and soil particle size components in an embodiment of the present invention. DETAILED DESCRIPTION

[0015] The present invention is further described below in conjunction with specific embodiments and the accompanying drawings. More details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention is obviously capable of being implemented in a variety of other ways different from the description herein. For those skilled in the art, any substitution, improvement or change made to the embodiments of the present invention is within the protection scope of the present invention, and the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0016] This example demonstrates how to use the method for rapid prediction of marine organic carbon content in coastal wetlands based on soil particle size components of the present invention. Soil sediment samples from the river to the sea in the Yellow River Delta Coastal Wetland Nature Reserve in Dongying City, Shandong Province were collected and brought back to the laboratory for soil particle size composition, soil organic carbon content, soil nitrogen content and isotope δ 13 C was determined by soil C / N ratio and isotope δ 13 The C value is combined with the Bayesian end-member mixture model to analyze and calculate the marine organic carbon content in the soil, and the soil particle size composition is regressed with the marine organic carbon in the soil to achieve a rapid prediction of the marine organic carbon content in coastal wetland soils. The specific plan is as follows:

[0017] (1) Study area: The Yellow River Delta Coastal Wetland Nature Reserve (37°38′N, 119°15′E) is located at the mouth of the Yellow River in Dongying City, Shandong Province. It is a representative estuarine wetland ecosystem in the world. It is a fan-shaped accumulation plain formed by the sedimentation brought by the Yellow River into the Bohai Sea. It is mainly composed of coastal tidal soil and saline soil, with broad and flat tidal flats and tidal channels with dense dendrites. Tidal action is a unique hydrological condition for coastal wetlands. The combined action of the Yellow River runoff and the Bohai Sea water leads to sediment deposition, which makes the Yellow River Delta estuarine system in a dynamic process. The source of organic carbon is no longer a simple mixture of land and sea sources. Its distribution and migration patterns are also complex and diverse.

[0018] (2) Sampling method: The sampling points were selected in the area on the north bank of the Yellow River Delta Nature Reserve that is affected by both the Yellow River and the Bohai Sea. A sampling strip was set up from the Yellow River beach to the coastline. Three 1×1m plots were set up at each sampling point. Each plot was horizontally distributed with an interval of 20m. The latitude and longitude of the sampling point and the dominant vegetation species were recorded. In the plot, soil samples were collected with a soil drill according to the three-point sampling principle and placed in numbered ziplock bags.

[0019] (3) Sample particle size determination pretreatment: Soil samples were naturally air-dried in a cool place, and obvious impurities such as plant tissues and stones were picked out. 10.0 g of air-dried soil samples were weighed and placed in a 50 ml numbered centrifuge tube. 10 mL of 20% H2O2 was added to the centrifuge tube until no bubbles were generated to remove organic matter in the soil sample. Then 10 mL of 10% hydrochloric acid was added to remove residual H2O2 and carbonate in the soil sample. After the reaction, the sample was washed three times with deionized water until the solution was close to or reached neutrality, and then allowed to stand for 12 hours. Finally, 10 mL of 0.05 mol / L sodium hexametaphosphate solution was added and shaken well, and the soil particle size composition was determined.

[0020] (4) Determination and classification of soil particle size composition: After soil sample pretreatment, the Mastersizer 2000 laser particle size analyzer was used for particle size analysis, with a measurement range of 0.01-3500 μm. Each sample was tested three times, and the average value was taken as the result. The soil particle size classification was based on the American soil particle size standard, which divides the soil particle components into clay (0.01-2 μm), fine silt (2-5 μm), medium silt (5-10 μm), coarse silt (10-50 μm), and sand (>50 μm).

[0021] (5) Organic carbon (SOC), total nitrogen (TN) and isotope δ 13C value determination soil sample pretreatment: weigh 5g of air-dried soil sample and place it in a 25ml numbered centrifuge tube, then add 1mol L-1 hydrochloric acid in batches several times until no bubbles emerge to remove inorganic carbon in the soil sample. Then place the centrifuge tube in a 2000r min-1 centrifuge for five minutes, then pour out the supernatant and add distilled water to wash the residual hydrochloric acid, repeat the above steps until the supernatant in the centrifuge tube is transparent and close to neutral. Finally, dry the acidified sample in an oven at 65℃ to constant weight.

[0022] (6) Determination of organic carbon (SOC) content and C / N: Acidification combustion method was used to weigh about 10 mg of soil sample into a tin boat and then sent to an elemental analyzer (B104Elementar Unicube). The organic matter containing C and N elements in the sample was burned under high temperature and high purity oxygen conditions, and then reduced to a stable mixed gas containing CO2 and N2 by a reduction tube. After being captured and separated by an adsorption column, the soil organic carbon (SOC) and total nitrogen (TN) content in the sample can be calculated based on the original weight of the sample, and then the C / N ratio of the sample can be calculated. The calculation formula is as follows: .

[0023] (7) Isotope δ 13 C value determination: Using stable isotope combustion mass spectrometry, about 40 mg of soil sample was weighed and placed in a tin bucket, then folded into round balls and sent to a stable isotope mass spectrometer (253Plus, Thermo Fisher Scientific). The pretreatment of this indicator is the same as the determination method of SOC and TN content, and is connected to an element analyzer (B104Elementar Unicube). The sample was burned by the element analyzer, and the elements were separated and sent to the mass spectrometer for analysis. The signal intensity of the target element was obtained by comparison with the reference gas. Repeated testing of the sample showed δ 13 The analytical accuracy of Corg is higher than 0.05‰, and the calculation formula is as follows: .

[0024] (8) Calculation of marine organic carbon content: The Bayesian mixed model (MixSIAR) was used to calculate the marine organic carbon content. The model used the MixSIAR package in the R language to combine prior knowledge and observed data, using the C / N value and isotope δ 13 C value, and finally calculate the contribution ratio of organic carbon from different sources to the total organic carbon in the soil. The model is based on the following formula: ; in, and are the measured values ​​of the samples, and are the terrestrial end member values ​​of each indicator, and are the ocean end member values ​​of each indicator, and are the endmember values ​​of each index plant, Respectively, they are the contribution ratios of terrestrial, marine and plant sources in soil organic carbon in the samples.

[0025] Refer to the three end members of terrestrial, marine and plant sources Values ​​and isotopes The contribution ratio and specific content of marine organic carbon in the soil of each sample point were calculated.

[0026] (9) The soil particle size data at all levels and the marine organic carbon content were subjected to ridge regression fitting. The optimal K value was determined based on the ridge trace plot, and regression modeling was performed based on this. The prediction model is as follows: ; in, Expressed as marine organic carbon content, It is expressed as the content of clay components (< 2 μm) in the sediment. It is expressed as the content of fine powder components (2~5μm) in the sediment. It is expressed as the content of medium-sized silt particles (5-10 μm) in the sediment. It is expressed as the content of coarse powder components (10~50μm) in the sediment. Expressed as the content of sand components (> 50 μm) in sediments, Expressed as the content of each particle size component, , are constants ( ).

[0027] In this embodiment, the ridge regression prediction model based on marine organic carbon and soil particle size components in coastal wetland soil is: .

[0028] (10) According to the principle of hydrodynamic sorting, as the hydrodynamic intensity changes, there are regular changes in the content of particle size components of each level. Specifically, when the seawater washes the mudflat, the flow rate slows down, the hydrodynamic intensity of the tide gradually weakens, and the marine coarse sediment particles attached to the seawater settle before the fine sediment particles, causing the proportion of fine particle sediments in the soil to increase in the total particle sediments, which constitutes the mutual conversion between the content of particle size components of different levels. The particle size component model is as follows: ; in, are constants, .

[0029] In this embodiment, based on the hydrodynamic sorting conditions, after fitting the actual data, it was found that the contents of soil clay, medium silt, coarse silt and sand were significantly correlated with the content of fine silt, such as Figure 1 As shown, in order to simplify the problem, the soil particle size components at all levels are converted into fine powder components, and the formula is solved as follows: .

[0030] (11) After the soil particle size components at all levels and the fine silt component are converted, they are brought into the marine organic carbon and soil particle size ridge regression model to solve the problem, and the prediction of marine organic carbon in the intertidal zone of coastal wetlands based on soil particle size components can be achieved: .

[0031] In this embodiment, the correlation diagram of the measured value and the predicted value of the ridge regression model of soil marine organic carbon and soil particle size components shows a significant correlation between the two (p < 0.001). Figure 2 shown.

[0032] From the above description, it can be seen that the embodiment of the present invention uses a large amount of field measured data and, based on the ridge regression model, finds the parameters of the correlation between the marine organic carbon in coastal wetland soil and the soil particle size components at all levels, thereby reducing the deviation between the model coefficients and the actual values ​​of different soil particle size components due to data collinearity, and can achieve rapid and accurate prediction of the marine organic carbon content in the intertidal zone soil of coastal wetlands, greatly reducing the workload of indicator measurement.

Claims

1. A rapid prediction method for marine organic carbon content in coastal wetlands based on soil particle size components, characterized in that: The steps include: (1) The content of each particle size, organic carbon and total nitrogen content and isotope δ 13 The C value is measured; (2) Based on the ratio of organic carbon to total nitrogen content and isotope δ 13 C value, calculate the proportion and specific content of marine organic carbon in the total organic carbon; (3) Constructing a ridge regression prediction model for marine organic carbon: The soil particle size data measured in the laboratory were used for ridge regression fitting with the marine organic carbon content. The optimal K value was determined based on the ridge trace plot, and regression modeling was performed based on this. The prediction model is as follows: ； in, Expressed as marine organic carbon content , are constants, ; Expressed as the content of each particle size component; (4) Fitting the content of each particle size in the soil sample: ； in, are constants, ; It is expressed as the content of clay components in sediments. Expressed as the content of fine powder components in sediments, Expressed as the content of medium silt components in sediments, It is expressed as the content of coarse silt components in the sediment. Expressed as the content of sand components in sediments; (5) By substituting the fitted data of the content of each particle size in the soil sample into the above-mentioned prediction model, the prediction of the marine organic carbon content in coastal wetlands based on the soil particle size components can be achieved.

2. The method for rapid prediction of marine organic carbon content in coastal wetlands based on soil particle size components according to claim 1, characterized in that: In the step (1), before determining the content of each particle size in the soil sample, the soil sample is pretreated as follows: H2O2 and hydrochloric acid are added to the air-dried soil sample in sequence to remove soil organic matter and inorganic salts; after the reaction is completed, the sample is repeatedly washed with deionized water for multiple times and allowed to stand; finally, sodium hexametaphosphate solution is added and shaken.

3. The method for rapid prediction of marine organic carbon content in coastal wetlands based on soil particle size components according to claim 1, characterized in that: In the step (1), before determining the organic carbon and total nitrogen content in the soil sample, the soil sample is pretreated as follows: hydrochloric acid is added to the air-dried soil sample; the sample is then repeatedly washed with deionized water until the supernatant is transparent and close to neutral, and then dried for later use.

4. The method for rapid prediction of marine organic carbon content in coastal wetlands based on soil particle size components according to claim 1, characterized in that: In the step (2), the MixSIAR package in the R language is used to construct a Bayesian three-end member organic carbon mixing model of terrestrial, marine and plant sources, and the model is used to calculate the proportion of marine organic carbon in the total organic carbon. The model formula is: ； in, and are the measured values ​​of the samples, and The terrestrial end-member values ​​of each indicator are respectively: and are the ocean end member values ​​of each indicator, and are the endmember values ​​of each index plant, Respectively, they are the contribution ratios of terrestrial, marine and plant sources in soil organic carbon in the samples.

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