Method for evaluating transfer from mangrove plant carbon library to sediment carbon library under pollutant stress

Abstract

The invention provides a method for evaluating transfer from a mangrove plant carbon library to a sediment carbon library under pollutant stress. The method comprises the following steps: measuring a mangrove plant delta 13C fraction different value delta and an observed value of a contribution ratio f of organic carbon in an actual sediment from the mangrove plant; establishing a pollution stress response model of delta 13C fractionation; estimating posterior distribution of pollution stress response model parameters based on Bayesian; and calculating the deposit carbon sink rate and carbon sink flux based on the organic carbon source contribution ratio f and the growth model. On the basis that the process of transferring mangrove plant carbon libraries to sediment carbon libraries meets a plant growth model, carbon stable isotope fractionation and Bayesian and parameter inversion methods are adopted, and the differentiation effect of mangrove plant delta 13C fractionation under pollutant stress is analyzed; accurate analysis of the organic carbon source proportion in the mangrove forest sediments and dynamic evaluation of the carbon sink flux of the sediments under the mangrove plant forest are realized, and a scientific basis is provided for protection and management of the mangrove forest carbon sink function.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental ecological protection, in particular to a method for evaluating the transfer of mangrove plant carbon pool to sediment carbon pool under the stress of pollutants. Background Art

[0002] As an important coastal blue carbon ecosystem, mangrove ecosystems play an important role in carbon sequestration. However, under the influence of human activities and global climate change, mangroves are facing increasingly severe pollution stress.

[0003] Currently, stable isotope mixing models have been used to parse the sources of sediment organic carbon. However, these models fail to account for the effects of pollution stress on plant isotope fractionation, leading to biased results in polluted environments. Furthermore, existing carbon sink assessment methods rely primarily on empirical models, satellite remote sensing, and sample plot surveys to assess overall carbon sinks, such as mangrove wetland biomass and sediment total organic carbon. However, they are unable to assess the impact of pollution stress on carbon sink function.

[0004] Therefore, there is an urgent need for a method that can evaluate the transfer of mangrove carbon pools to sediment carbon pools under pollutant stress. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the present invention provides a method for evaluating the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress. The present invention is based on the fact that the transfer process of mangrove plant carbon pool to sediment carbon pool meets the plant growth model, and uses carbon stable isotope fractionation (δ 13 C) analysis method, Bayesian mixed model and parameter inversion method, by analyzing the δ 13 Based on the differentiation effect of C fractionation, a model was constructed to quantitatively analyze the impact of environmental stress factors represented by pollutants on the carbon pool transfer between mangrove plants and understory sediments, and its refined measurement model was used. This achieved accurate analysis of the proportion of organic carbon sources in mangrove sediments and dynamic assessment of the carbon sink flux in mangrove understory sediments, providing a scientific basis for the protection and management of the carbon sink function of mangroves.

[0006] The technical solution of the present invention is: a method for evaluating the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress, comprising the following steps:

[0007] S1) Based on the response relationship between carbon stable isotope fractionation of mangrove plant tissues and pollutant stress, the δ 13 The observed value of C fractionation difference Δ and the contribution ratio f of organic carbon from mangrove plants in actual sediments;

[0008] S2), based on δ 13C fractionation outlier Δ, using the logistic function form to establish δ 13 The pollution stress response model of C fractionation is used to describe the contribution ratio of organic carbon sources f and δ 13 The relationship between C fractionation and heterogeneity Δ;

[0009] S3) Utilization of organic carbon source contribution ratio f and δ 13 C fractionation was performed to determine the Δ difference, and the posterior distribution of the pollution stress response model parameters was estimated based on Bayesian estimation;

[0010] S4) Calculate the sediment carbon sink rate and carbon sink flux based on the organic carbon source contribution ratio f and the Chapman-Richards growth model.

[0011] As a preference, in step S1), the mangrove plant δ 13 The expression of C fraction difference value Δ is:

[0012] Δ=δ 13 C p -δ 13 C CK ;(1)

[0013] Where, δ 13 C p represents the carbon stable isotope fractionation of mangrove plants under pollution stress; δ 13 C CK represents the carbon stable isotope fractionation of mangrove plants without pollutant stress;

[0014] The expression of the organic carbon source contribution ratio f is:

[0015] f=(1-e -kt ) m ;(2)

[0016] Where m represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

[0017] Preferably, in step S2), the expression of the pollution stress response model is:

[0018]

[0019] Where, f(Δ) represents the contribution ratio of mangrove plant-derived organic carbon. 13 C is the modified logistic function of the change in fractional outlier Δ; A is the maximum response amplitude; b is the slope parameter; Δ0 is the midpoint of the response; and C0 is the baseline offset.

[0020] Preferably, in step S3), the Bayesian method is implemented using Stan software, and the Hamiltonian Monte Carlo (HMC) algorithm is used to perform posterior sampling by setting the prior distribution and likelihood function of the parameters.

[0021] As a preference, in step S4), the carbon sink rate v of the plant-derived carbon pool transferred to the sediment carbon pool is c for:

[0022]

[0023] Where m represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

[0024] As a preferred method, in step S4), the carbon sink flux φ transferred from mangrove plants to the sediments under the forest p for:

[0025] φ p =C soil ·v c =C soil ·m·k·e -k·t (1-e -k·t ) m-1 ; (5)

[0026] Where C soil It represents the total organic carbon content in the sediments under the mangrove forest.

[0027] As a preferred method, in step S4), the carbon sink flux φ transferred from mangrove plants to understory sediments under environmental pollutant stress is p The impact effect Δ T PS:

[0028] Δ TPS =φ p -φ CK ;(6)

[0029] Where, φ CK It is the transfer flux from the endogenous carbon pool of mangrove plants to the carbon pool in the understory sediments in the absence of pollutant stress.

[0030] The beneficial effects of the present invention are:

[0031] 1. The present invention establishes the δ 13 The quantitative relationship between C fractionation and the proportion of organic carbon sources in understory sediments is used to address the problem of bias in the application of existing stable isotope mixing models in polluted environments.

[0032] 2. This paper integrates the pollution stress response model and the carbon sink dynamic model to achieve a dynamic assessment of the carbon sink flux transferred from mangrove plants to understory sediments under pollution stress;

[0033] 3. The present invention is based on the transfer process of mangrove plant carbon pool to sediment carbon pool to meet the plant growth model, and uses carbon stable isotope fractionation (δ 13 C) analysis method, Bayesian mixed model and parameter inversion method, by analyzing the δ 13 The differentiation effect of C fractionation is used to construct a model that can be used to quantitatively analyze the impact of environmental stress factors represented by pollutants on the carbon pool transfer between mangrove plants and understory sediments, as well as its refined measurement model;

[0034] 4. The present invention achieves accurate analysis of the proportion of organic carbon sources in mangrove sediments and dynamic assessment of the carbon sink flux in sediments under mangrove plants, providing a scientific basis for the protection and management of the carbon sink function of mangroves. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the process of the present invention;

[0036] Figure 2 Schematic diagram of the posterior distribution of parameters of the pollutant stress response model in an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the posterior distribution of the contribution ratio of mangrove plants in an embodiment of the present invention;

[0038] Figure 4 Schematic diagram of model prediction verification in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings:

[0040] Example 1

[0041] like Figure 1 As shown, this embodiment provides a method for evaluating the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress, comprising the following steps:

[0042] S1) Based on the response relationship between carbon stable isotope fractionation of mangrove plant tissues and pollutant stress, the δ 13 The observed value of C fractionation difference Δ and the contribution ratio f of organic carbon from mangrove plants in actual sediments;

[0043] In this embodiment, the mangrove plant δ 13 The expression of C fraction difference value Δ is:

[0044] Δ=δ 13 C p -δ 13 C CK;(1)

[0045] Where, δ 13 C p represents the carbon stable isotope fractionation of mangrove plants under pollution stress; δ 13 C CK represents the carbon stable isotope fractionation of mangrove plants without pollutant stress;

[0046] The expression of the organic carbon source contribution ratio f is:

[0047] f=(1-e -kt ) m ;(2)

[0048] Where m represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

[0049] S2), based on δ 13 C fractionation outlier Δ, using the logistic function form to establish δ 13 The pollution stress response model of C fractionation is used to describe the contribution ratio of organic carbon sources f and δ 13 The relationship between C fractionation and heterogeneity Δ;

[0050] In this embodiment, the expression of the pollution stress response model is:

[0051]

[0052] Where, f(Δ) represents the contribution ratio of mangrove plant-derived organic carbon. 13 C is the modified logistic function of the change in fractional outlier Δ; A is the maximum response amplitude; b is the slope parameter; Δ0 is the midpoint of the response; and C0 is the baseline offset.

[0053] S3) Utilization of organic carbon source contribution ratio f and δ 13 C fractionation was performed to determine the Δ difference, and the posterior distribution of the pollution stress response model parameters was estimated based on Bayesian estimation;

[0054] In this embodiment, the Bayesian method is implemented using Stan software, and the Hamiltonian Monte Carlo (HMC) algorithm is used to perform posterior sampling by setting the prior distribution and likelihood function of the parameters.

[0055] In this embodiment, the parameters include the maximum response amplitude A, the slope parameter b, the response midpoint Δ0, the baseline offset C0, and the residual standard deviation σ.

[0056] S4) Calculate sediment carbon sink rate, carbon sink flux and impact effects based on the organic carbon source contribution ratio f and the Chapman-Richards growth model;

[0057] The expression of the Chapman-Richards growth model is:

[0058] Y(t)=A ′ ·(1-e -k·t ) m-1

[0059] Where Y(t) represents the growth of the plant at time t; A ′ is the asymptotic maximum value eventually reached by the plant; k is the growth rate constant; m is the shape parameter of plant growth; and t is the actual observation time.

[0060] The carbon sink rate v of the plant carbon pool transferred to the sediment carbon pool c for:

[0061]

[0062] Where m represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

[0063] Carbon sink flux φ transferred from mangrove plants to understory sediments p for:

[0064] φ p =C soil ·v c =C soil ·m·k·e -k·t (1-e -k·t ) m-1 ; (5)

[0065] Where C soil It represents the total organic carbon content in the sediments under the mangrove forest.

[0066] Effects of environmental pollutant stress on the carbon sink flux φ transferred from mangrove plants to understory sediments p The impact effect Δ TPS for:

[0067] Δ TPS =φ p -φ CK ;(6)

[0068] Where, φ CK It is the transfer flux from the endogenous carbon pool of mangrove plants to the carbon pool in the understory sediments in the absence of pollutant stress.

[0069] In this embodiment, when m=1, f=1-e -k·t ; Indicates that the growth rate gradually slows down from the beginning;

[0070] When 0 < m < 1, the growth curve of the growth model shows a rapid initial growth, followed by a relatively fast slowdown, with the overall being relatively smooth and approaching the exponential growth pattern.

[0071] When m > 1, the model curve shows the characteristics of a typical "S-shaped growth curve": slow initial growth; rapid growth in the middle stage with an obvious inflection point; and gradual slowdown and finally tending to a stable asymptotic maximum in the later stage.

[0072] In addition, in this embodiment, by generating a validation data set, the root mean square error (RMSE), coefficient of determination (R 2 ) and mean absolute error (MAE) between the predicted values and the true values of the Chapman-Richards growth model are calculated to evaluate the accuracy and reliability of the model.

[0073] Example 2

[0074] In this embodiment, polystyrene nanoplastics (PS-NP) are used as pollutants and Aegiceras corniculatum is used as the test organism to conduct a stress experiment on pollutant exposure. The exposure concentration gradients are 0 mg / L, 20 mg / L, and 100 mg / L. Samples are collected at different exposure times to detect their carbon stable isotope fractionation values; according to the δ 13 C values of the control group and exposure group samples, the δ 13 C fractionation and differentiation value Δ of mangrove plants under pollutant stress is calculated using formula (1), and the results are shown in Table 1:

[0075] Table 1 δ 13 C values and their differentiation values of Aegiceras corniculatum under PS-NP stress

[0076]

[0077] Determination of δ 13 C of mangrove plant understory sediments and other source samples:

[0078] In a mangrove wetland in southern China, samples of understory sediments of Aegiceras corniculatum and adjacent intertidal flat sediments (control samples) are collected to measure their organic carbon content and δ 13 C values. The results show that the total organic carbon content of the understory sediments of Aegiceras corniculatum is 14.65 g / kg, and its δ 13 C soil value is -27.45‰; the δ 13 C CK value of the intertidal flat is -25.00‰.

[0079] Without considering pollution stress, the contribution ratio f of mangrove plant-derived carbon to sediment organic carbon is 0.363; and using δ 13The pollution stress response model of C fractionation was based on the effect of PS-NP on the δ 13 The C fractionation value is calculated by combining Equation (3) with HMC simulation to establish the organic carbon source contribution ratio f and δ 13 The relationship between the C fractionation difference Δ is used to obtain the key parameter values ​​of formula (3), as shown in Table 2, and the probability density distribution of each parameter is shown in Figure 2 shown.

[0080] Table 2 Posterior distribution of key parameters of pollutant stress response model

[0081] parameter Mean SD HDI_2.5 HDI_97.5 A 0.8806 0.0602 0.7717 0.9957 b 0.0339 0.0261 0.0000 0.0835 <![CDATA[Δ0]]> 0.3236 1.0224 -1.6809 2.2843 <![CDATA[C0]]> 0.0672 0.0187 0.0317 0.1048 σ 0.2571 0.0279 0.2052 0.3115

[0082] Under pollution stress, the posterior distribution of the contribution ratio f (true value) of mangrove plant-derived carbon to sediment organic carbon is:

[0083] According to δ 13 The observed values ​​of C fractionation difference (Δ) and organic carbon source ratio f were calculated using formula (3) combined with HMC simulation. The obtained f values ​​are shown in Table 3. The posterior distribution of mangrove plant contribution ratio f is shown in Figure 3 shown.

[0084] Table 3 Posterior distribution of the contribution ratio f of mangrove plant-derived carbon to sediment organic carbon under pollution stress

[0085]

[0086] The age of the tung tree in this embodiment is 5 years, and the shape parameter m of the tung tree is set to 2.5; in order to examine other current parameters, m = 1, 2, 2.5 are taken respectively, and the carbon sequestration rate, carbon sequestration flux, and impact effect are calculated according to formulas (4), (5), and (6);

[0087] Among them, when Δ=0.605, the calculation results of various parameters are shown in Table 4; the output model parameter estimation results, statistical results of f, carbon sink rate v c The assessment results and carbon sink flux φ p The results are shown in Table 5.

[0088] Table 4 Parameters k and v c The posterior distribution of

[0089] m t <![CDATA[k mean ]]> <![CDATA[k lower ]]> <![CDATA[k upper ]]> <![CDATA[v mean ]]> <![CDATA[v lower ]]> <![CDATA[v upper ]]> 1.0 5 0.1359 0.0953 0.1750 0.0682 0.0617 0.0736 2.0 5 0.2419 0.1916 0.2889 0.1004 0.0935 0.1041 2.5 5 0.2798 0.2273 0.3284 0.1119 0.1050 0.1152

[0090] Among them, k mean 、k lower and k upper are the arithmetic mean of parameter k and the lower and upper limits of the 95% confidence interval (95% CI), respectively; v mean 、v lower and v upper Represents the parameter vc The arithmetic mean and the lower and upper limits of the 95% confidence interval.

[0091] Table 5 Calculation results of carbon sink rate and carbon sink flux

[0092]

[0093] The results showed that when Tung blossom plants were subjected to PS-NP stress, their carbon stable isotope fractionation value changed to 0.605‰, and their carbon flux transferred to the sediment carbon pool decreased by 0.0029 g / kg / a.

[0094] The embodiment verifies the performance indicators (RMSE, R 2 , MAE) and verification graphs, such as Figure 4 As shown, the accuracy and reliability of the model were evaluated. In the embodiment, the R 2 Reaching above 0.98 indicates that the model has high prediction accuracy; RMSE < 0.01 indicates high prediction accuracy, and MAE < 0.01 indicates a small average prediction error.

[0095] The above embodiments and descriptions are only for explaining the principles and best embodiments of the present invention. Without departing from the spirit and scope of the present invention, the present invention may be subject to various changes and improvements, which shall fall within the scope of the invention to be protected.

Claims

1. A method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress, characterized in that: The steps include: S1) Based on the response relationship between carbon stable isotope fractionation of mangrove plant tissues and pollutant stress, the δ 13 The observed value of C fractionation difference Δ and the contribution ratio f of organic carbon from mangrove plants in actual sediments; S2), based on δ 13 C fractionation outlier Δ, using the logistic function form to establish δ 13 The pollution stress response model of C fractionation is used to describe the contribution ratio of organic carbon sources f and δ 13 The relationship between C fractionation and heterogeneity Δ; S3) Utilization of organic carbon source contribution ratio f and δ 13 C fractionation was performed to determine the Δ difference, and the posterior distribution of the pollution stress response model parameters was estimated based on Bayesian estimation; S4) Calculate the sediment carbon sink rate, carbon sink flux, and the impact of carbon sink flux based on the organic carbon source contribution ratio f and the Chapman-Richards growth model.

2. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 1, characterized in that: In step S1), the mangrove plant δ 13 The expression of C fraction difference value Δ is: D=d 13 C p -d 13 C CK (1) Where, δ 13 C p represents the carbon stable isotope fractionation of mangrove plants under pollution stress; δ 13 C CK Represents the carbon stable isotope fractionation of mangrove plants without pollutant stress.

3. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 1, characterized in that: In step S1), the expression of the organic carbon source contribution ratio f is: F=(1-E -kt ) m ; (2) Where M represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

4. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 1, characterized in that: In step S2), the expression of the pollution stress response model is: Where, f(Δ) represents the contribution ratio of mangrove plant-derived organic carbon. 13 C is the modified logistic function of the change in fractional outlier Δ; A is the maximum response amplitude; b is the slope parameter; Δ0 is the midpoint of the response; and C0 is the baseline offset.

5. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 1, characterized in that: In step S3), the Bayesian method is implemented using Stan software, and the Hamiltonian Monte Carlo (HMC) algorithm is used to perform posterior sampling by setting the prior distribution and likelihood function of the parameters.

6. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 1, characterized in that: In step S4), the carbon sink rate v of the plant carbon pool transferred to the sediment carbon pool is c for: Where m represents the shape parameter of plant growth; k represents the growth rate constant; and t represents the actual observation time.

7. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 6, characterized in that: In step S4), the carbon sink flux φ transferred from mangrove plants to the sediments under the forest p for: φ p =C soil ·v c =C soil ·m·k·e -k·t (1-e -k·t ) m-1 (5) Where C soil It represents the total organic carbon content in the sediments under the mangrove forest.

8. The method for assessing the transfer of mangrove plant carbon pool to sediment carbon pool under pollutant stress according to claim 7, characterized in that: In step S4), the carbon sink flux φ transferred from mangrove plants to understory sediments due to environmental pollutant stress is p The impact effect Δ T PS: D TPS =φ p -f CK (6) Where, φ CK It is the transfer flux from the endogenous carbon pool of mangrove plants to the carbon pool in the understory sediments in the absence of pollutant stress.

Images