Method for evaluating nitrogen removal capacity of water body based on benthic animal functional traits

Abstract

The application discloses a water body nitrogen biological removal capacity evaluation method based on macrobenthos functional traits, and comprises the following steps: S1, constructing a water body nitrogen biological removal capacity evaluation table based on macrobenthos functional trait evaluation final score; S2, collecting macrobenthos in the water body to be measured, and obtaining the final score of the macrobenthos functional trait evaluation based on the trait grade of the macrobenthos which is strongly related to the water body nitrogen biological removal rate, and then obtaining the corresponding classification based on the water body nitrogen biological removal capacity evaluation table. The application does not need to perform complex tracer adding, real-time water quality monitoring and cumbersome calculation process, only needs to collect and identify the macrobenthos in the stream, obtains the macrobenthos functional trait evaluation result, and then obtains the nitrogen biological absorption rate of the water body to be measured by means of the pre-constructed evaluation table. The application greatly reduces the workload, makes the whole evaluation process more simple and fast, and improves the evaluation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological environment monitoring and evaluation, and particularly relates to a water body nitrogen biological removal capacity evaluation method based on benthic animal functional traits, which aims to use macrobenthos functional traits for related evaluation. BACKGROUND

[0002] Water body nitrogen biological removal capacity is an important part of stream self-purification capacity, and correct evaluation of stream nitrogen biological removal capacity is of great significance to river health assessment and water environment protection. At present, the existing technology mainly uses the field in-situ test method based on the nutrient spiral model to investigate the water body nitrogen biological removal capacity. However, in the implementation process of this method, a large amount of tracers need to be added to exclude the influence of non-biological factors (such as physical convection, dilution, diffusion, etc.) on the biological degradation of nitrogen pollutants; and the method needs to calculate the water body nitrogen biological removal capacity of the stream based on the nutrient spiral model according to the real-time changes of water quality, which makes the test and calculation process more complicated.

[0003] That is, the existing field in-situ test method based on the nutrient spiral model for investigating the water body nitrogen biological removal capacity has at least the following difficulties in the implementation process: 1) the test and calculation process is relatively complicated; 2) it is very susceptible to the interference of non-biological factors in the river; 3) a large amount of tracers need to be used, which makes the investigation cost too high.

[0004] Moreover, the nitrogen biological removal in the water body is mainly completed by microorganisms and algae, so the evaluation method of water body nitrogen biology is mainly dependent on the diversity and richness of microorganisms and algae. However, as primary producers of aquatic ecosystems, microorganisms and algae are easily affected by secondary producers, and non-biological factors (such as physical convection, dilution, diffusion, etc.) in the river also interfere with their effectiveness, resulting in poor correlation between the evaluation parameters of microorganisms and algae and the water body nitrogen biological removal capacity, and thus the evaluation cannot be accurate.

[0005] Therefore, in view of the above problems of the prior art, it is necessary to design a new water body nitrogen biological removal capacity evaluation method, which is more simple, economical and feasible compared with the existing field in-situ test method, and can determine the stream biological removal capacity conveniently and quickly, and reduce the dependence and requirements on test instruments. SUMMARY

[0006] The present application aims to provide a water body nitrogen biological removal capacity evaluation method based on benthic animal functional traits, to solve the problems existing in the prior art and realize convenient, efficient and accurate evaluation of water body nitrogen biological removal capacity.

[0007] To achieve the above object, the technical scheme adopted by the present application is as follows:

[0008] The present application provides a water body nitrogen biological removal capacity evaluation method based on benthic animal functional traits, comprising the following steps:

[0009] S1, constructing a water body nitrogen biological removal capacity evaluation table based on benthic animal functional trait evaluation final score; wherein the water body nitrogen biological removal capacity evaluation table is divided into multiple grades, and the grades are divided based on different ranges of benthic animal functional trait evaluation final score;

[0010] S2, collecting macrobenthos in the water body to be tested, and calculating the benthic animal functional trait evaluation final score of the water body to be tested based on the traits of the benthic animals that are strongly correlated with the water body nitrogen biological removal rate of the indicative water body, and then obtaining the corresponding grade of the water body nitrogen biological removal capacity of the water body to be tested from the pre-constructed water body nitrogen biological removal capacity evaluation table based on the obtained benthic animal functional trait evaluation final score.

[0011] Based on the above disclosed steps, compared with the traditional field in-situ test method based on the nutrient spiral model, the present application does not need to perform complex tracer addition, real-time water quality monitoring and cumbersome calculation process. Only the macrobenthos in the stream is collected and identified according to the steps, the corresponding analysis of the macrobenthos is performed, the benthic animal functional trait evaluation final score based on the trait grade is calculated, and then the corresponding grade of the water body nitrogen biological removal capacity of the water body to be tested is obtained by substituting the obtained benthic animal functional trait evaluation final score into the pre-constructed water body nitrogen biological removal capacity evaluation table. Compared with the prior art, the method of the present application greatly reduces the workload, improves the evaluation efficiency, makes the entire evaluation process more simple and fast, and enhances the feasibility of actual operation.

[0012] The macrobenthos refers to the visible aquatic invertebrates that inhabit the water bottom or attach to the plants or stones in the water, and are often used as underwater sentinels for evaluating water quality changes due to their sensitive response to water quality changes. Although the benthic animals do not directly absorb the nutrients in the river, they feed on the microorganisms and algae in the environment, control the primary producers through the top-down effect, and thus affect the nitrogen biological removal capacity of the stream.

[0013] Due to the above unique position and role of benthic animals in the ecosystem, the functional traits comprehensively reflect the adaptation to the environment and the influence in the ecological chain, and the evaluation system constructed on this basis is less disturbed by the outside world, overcoming the problem that the evaluation method relying on microorganisms and algae is easily disturbed by secondary producers and non-biological factors of the stream. The evaluation result is more stable and reliable, and has stronger relevance with the biological nitrogen removal capacity of the water body, so as to more accurately reflect the actual situation, and provide strong support for river health assessment and water environment protection. That is, the present application discards the conventional method of evaluating the biological nitrogen removal capacity of the water body by microorganisms or algae in the prior art, and adopts the unexpected evaluation of the biological nitrogen removal capacity of the water body by benthic animals, so as to overcome the technical problems existing in the prior art by means of microorganisms or algae for evaluation.

[0014] In the present application, the water body refers to rivers, streams, ponds, lakes and the like. The macrobenthos refers to the visible aquatic invertebrates living on the water bottom or attached to the water plants or stones.

[0015] Further, the step of constructing the water body nitrogen biological removal capacity evaluation table based on the benthic animal functional trait evaluation final score includes:

[0016] S11, collecting macrobenthos samples at multiple sampling points, and for each sampling point, constructing a macrobenthos quantity matrix based on the species and individuals of the collected macrobenthos;

[0017] S12, constructing a macrobenthos functional trait matrix including multiple benthic animal functional traits according to "Systematic Classification, Biology and Ecology of Freshwater Invertebrates";

[0018] S13, for each sampling point, logarithmically processing the constructed macrobenthos quantity matrix, and multiplying it with the constructed macrobenthos functional trait matrix to obtain a trait level value matrix representing the trait levels in the benthic animal functional traits, wherein the parameter of the jth trait level of the ith benthic animal functional trait is denoted as benthic animal trait level parameter A i j;

[0019] S14, obtaining the water body nitrogen biological removal rate by actual measurement for each sampling point, and screening out strong correlation functional traits and strong correlation trait levels in the benthic animals which are strongly correlated with the water body nitrogen biological removal rate based on the obtained actual measurement water body nitrogen biological removal rate;

[0020] S15, determining the first component value of the strong correlation trait level;

[0021] S16, based on the screened strong correlation trait level, and taking the first component value of the strong correlation trait level as the trait level weight Bi , according to the formula X = ∑A ij ·B i The final score of the benthic animal functional trait evaluation of each sampling point is calculated;

[0022] S17, the statistical distribution of the final score of the benthic animal functional trait evaluation of all sampling points is carried out, the water body nitrogen biological removal capacity is classified based on the quantile interval in which the value of the score is located, to obtain the final water body nitrogen biological removal capacity evaluation table.

[0023] In the present application, by analyzing a variety of rich functional traits, the potential correlation between benthic animals and water body nitrogen biological removal capacity can be further explored in depth and detail, avoiding evaluation deviation caused by incomplete consideration of functional traits, and providing a solid foundation for subsequent accurate calculation of benthic animal functional trait parameters A ij , accurate assessment of the correlation between water body nitrogen biological removal capacity and benthic animal functional traits, greatly improving the scientificity and accuracy of the entire evaluation method, making the evaluation results more persuasive and reliable, and thus better serving the research and protection of stream ecological environment.

[0024] Moreover, in the present application, each step from sample identification to quantitative statistics, data conversion to correspondence analysis ensures the rationality and effectiveness of data processing, so that the finally constructed matrix can accurately reflect the structure and characteristics of the benthic animal community, providing a reliable data basis for subsequent multiplication with the trait matrix to obtain the trait value matrix.

[0025] Further, the step of screening strong correlation functional traits and strong correlation trait grades of benthic animals based on the measured water body nitrogen biological removal rate includes:

[0026] Taking the logarithm of the measured water body nitrogen biological removal rate as the dependent variable, and taking the obtained benthic animal trait grade parameter A ij as the predictor, the significance value of each trait grade is calculated and obtained by pearson correlation analysis;

[0027] Selecting the trait grade with a significance value <0.05, and identifying the corresponding functional trait of the trait grade with a significance value <0.05 as a strong correlation functional trait;

[0028] Taking the logarithm of the measured water body nitrogen biological removal rate as the dependent variable, and taking the obtained benthic animal trait grade parameter A ij as the predictor for regression, and calculating the importance value of each trait grade in the identified strong correlation functional trait by variable projection importance analysis method, screening out the trait grade with an importance value greater than 0.7, and identifying it as a strong correlation trait grade.

[0029] Further, the regression processing is carried out by using the partial least squares regression, and the calculation formula of the importance value is as follows:

[0030]

[0031] wherein VIP represents the importance value; p represents that initially a total of p variables participate in analysis; h represents that finally a total of h times of iterative calculation is carried out; w jk represents the weight adopted by the variable j when mapping at the kth iteration, which reflects the explanation degree of the variable j on the kth mapping result X k ; represents the explanation degree of the kth mapping result X k on Y k .

[0032] In the present application, the importance value (VIP) calculation formula can accurately quantify the importance degree of each trait grade in explaining the water body nitrogen biological removal capacity through complex iterative calculation and weight analysis, and screen out the key trait grade; and the calculation formula of the benthic animal functional trait evaluation final score X is based on the screened strong correlation specific trait grade and its weight, realizes the quantitative evaluation of the water body nitrogen biological removal capacity, and makes the evaluation result have clear numerical basis.

[0033] Further, the calculation formula of the first component value is as follows:

[0034] Bi=Tω1;

[0035] wherein Bi represents the first component value, T is the trait grade numerical matrix, and ω1 is the weight vector obtained after iterative optimization.

[0036] In the calculation process of the partial least squares algorithm, the relationship between the independent variable and the dependent variable is decomposed and reconstructed, the main components are extracted through dimension reduction of data, wherein the first component value (Component1) is an important component score obtained in this process, the value of which reflects the importance degree and direction of the trait grade in explaining the water body nitrogen biological removal capacity, and the positive and negative of which can determine the correlation direction of the trait grade and the water body nitrogen biological removal, the positive value represents the positive correlation, the negative value represents the negative correlation, and the absolute value size embodies the relative importance in the model, and the greater the absolute value, the greater the influence on the water body nitrogen biological removal capacity.

[0037] Moreover, in the present application, the p value of each trait will be calculated. The p value is an important indicator for judging the significance of the trait in the model. If the p value of a trait is less than the set threshold (usually 0.05), it means that the trait has statistical significance in explaining the biological nitrogen removal capacity of the water body, that is, there is a significant linear relationship between the trait and the biological nitrogen removal capacity of the water body.

[0038] Further, step S17 comprises:

[0039] Based on the calculated final evaluation score of the benthic animal functional traits of all sampling points, five quantiles are divided as the classification of the biological nitrogen removal capacity of the water body, wherein:

[0040] If the final evaluation score of the benthic animal functional traits is < 25% quantile, it is considered that the biological nitrogen removal rate of the water body is low, corresponding to the water body biological nitrogen removal capacity of grade V;

[0041] If the final evaluation score of the benthic animal functional traits is between 25% and 50% quantile, it is considered that the biological nitrogen removal rate of the water body is low, corresponding to the water body biological nitrogen removal capacity of grade IV;

[0042] If the final evaluation score of the benthic animal functional traits is between 50% and 75% quantile, it is considered that the biological nitrogen removal rate of the water body is general, corresponding to the water body biological nitrogen removal capacity of grade III;

[0043] If the final evaluation score of the benthic animal functional traits is between 75% and 90% quantile, it is considered that the biological nitrogen removal rate of the water body is high, corresponding to the water body biological nitrogen removal capacity of grade II;

[0044] If the final evaluation score of the benthic animal functional traits is > 90% quantile, it is considered that the biological nitrogen removal rate of the water body is high, corresponding to the water body biological nitrogen removal capacity of grade I.

[0045] Further, the plurality of traits includes: maximum size, life cycle, number of reproductive generations, aquatic stage, sexual and asexual reproduction, dispersal mode, resistance form, food type, feeding mode, respiratory site, temperature-adapted microhabitat, movement mode, and relationship with substrate;

[0046] Further, the strongly correlated functional traits are screened and determined as: temperature-adapted microhabitat, movement mode, relationship with substrate, food type, and feeding mode.

[0047] The strongly correlated functional trait grades are screened and determined as: slate / stone / rock / gravel, sand, microphyte, crawling, interstitial (endobenthic), fine sediment / microorganism, biological residue detritus, living microphyte, dead animal, and scraping food type.

[0048] Further, step S2 comprises:

[0049] S21, collecting macrobenthos in the water body to be measured, and constructing a current macrobenthos quantity matrix based on the species and individuals of the collected macrobenthos;

[0050] S22, constructing a macrobenthos functional trait matrix in advance according to Freshwater Invertebrate Systematics, Biology and Ecology, taking logarithmic processing of the current macrobenthos quantity matrix, and multiplying the logarithmic processing result with the pre-constructed macrobenthos functional trait matrix to obtain a current trait grade value matrix representing trait grades of the macrobenthos functional traits, so as to obtain a macrobenthos trait grade parameter A representing a jth trait grade of an ith macrobenthos functional trait in the current trait grade value matrix. ij ;

[0051] S23, calculating a final score of the macrobenthos functional trait evaluation of the current water body to be measured based on the strong correlation trait grades screened in step S14 and taking the corresponding first component value of the strong correlation trait grades determined in step S15 as a trait grade weight B i , and calculating the final score of the macrobenthos functional trait evaluation of the current water body to be measured according to a formula X = ∑A ij ·B i .

[0052] S24, obtaining a corresponding classification of the water body nitrogen biological removal capacity of the current water body to be measured from the water body nitrogen biological removal capacity evaluation table constructed in step S1 based on the final score of the macrobenthos functional trait evaluation of the current water body to be measured.

[0053] Further, the collection of the macrobenthos is based on a Sober net, and after the collection, the macrobenthos is placed into a container containing 95% alcohol for fixation. That is, the Sober net is used to collect the macrobenthos samples in the stream, the material of the Sober net is high-strength corrosion-resistant nylon material, and the mesh size precision is controlled within ±5 μm. In the present application, the Sober net with high-strength corrosion-resistant nylon material has durability and stability in the complex environment of the stream, reduces damage and maintenance cost; the high-precision mesh size control ensures that the collected macrobenthos samples are representative and accurate, improves the sample quality, and provides a reliable data starting point for the entire evaluation method.

[0054] The present application applies the evaluation method to the field of river health assessment and water environment protection, provides an important technical means for ecological research and protection, helps scientific management of water resources and maintenance of river ecological balance, and has important practical significance and social value.

[0055] Compared with the prior art, the present application has the following beneficial effects:

[0056] Compared with the traditional field in-situ test method based on the nutrient spiral model, the present invention does not require complicated tracer addition, real-time water quality monitoring and tedious calculation processes. It only needs to collect and identify large benthic animals in the stream according to the steps, and perform subsequent matrix construction, model calculation and other operations to obtain the evaluation results of the biological nitrogen removal capacity of the water body. This greatly simplifies the evaluation process, reduces the workload, improves the evaluation efficiency, and makes the entire evaluation process simpler and easier. In addition, due to the unique status and role of benthic animals in the ecosystem, their functional traits comprehensively reflect their adaptation to the environment and their influence in the ecological chain. The evaluation system constructed on this basis is less subject to external interference, overcoming the problem that the evaluation that relied on microorganisms and algae in the past was easily interfered with by secondary producers and non-biological factors in the stream. This makes the evaluation results more stable and reliable, more closely related to the actual situation of the biological nitrogen removal capacity of the water body, and can more accurately reflect the ecological function status of the stream.

[0057] The following describes in detail the method and system for evaluating the biological nitrogen removal capacity of benthic animals in water bodies according to the present invention with reference to the embodiments and reference numerals shown in the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The present invention is a flowchart of the steps of the method for evaluating the biological nitrogen removal capacity of water bodies based on the functional traits of benthic animals.

[0059] Figure 2 The present invention provides a flowchart of the steps for constructing an evaluation table for biological nitrogen removal capacity of water bodies based on the final scores of the functional traits evaluation of benthic animals.

[0060] Figure 3 This is a flow chart of the steps for evaluating the biological nitrogen removal capacity of a water body to be tested based on a pre-constructed water body nitrogen removal capacity evaluation table in the present invention. DETAILED DESCRIPTION

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other unless there is a conflict.

[0062] The present invention provides a method for evaluating the biological nitrogen removal capacity of water bodies based on the functional traits of benthic animals. Figure 1 As shown, the specific operating steps of the present invention are as follows:

[0063] S1, constructing a water body nitrogen biological removal capacity evaluation table based on the final score of the benthic animal functional trait evaluation; wherein the water body nitrogen biological removal capacity evaluation table is structured as multiple levels, and the levels are divided based on different ranges of the final score of the benthic animal functional trait evaluation;

[0064] S2, collecting macrobenthos in the water body to be tested, and calculating the final score of the benthic animal functional trait evaluation of the water body to be tested based on the trait level of the benthic animal that is strongly related to the water body biological nitrogen removal rate indicating the water body nitrogen biological removal capacity, and then obtaining the corresponding level of the water body nitrogen biological removal capacity in the water body to be tested from the water body nitrogen biological removal capacity evaluation table constructed in advance based on the final score of the benthic animal functional trait evaluation.

[0065] The step of constructing a water body nitrogen biological removal capacity evaluation table based on the final score of the benthic animal functional trait evaluation comprises:

[0066] S11, collecting macrobenthos samples at multiple sampling points, and for each sampling point, constructing a macrobenthos quantity matrix based on the species and individuals of the collected macrobenthos;

[0067] S12, constructing a macrobenthos functional trait matrix comprising multiple benthic animal functional traits according to the Systematic Classification, Biology and Ecology of Freshwater Invertebrates;

[0068] S13, for each sampling point, taking logarithmic processing of the constructed macrobenthos quantity matrix, and multiplying it with the constructed macrobenthos functional trait matrix to obtain a trait level value matrix representing the trait level of the benthic animal functional trait, wherein the parameter of the jth trait level of the ith benthic animal functional trait is denoted as the benthic animal trait level parameter A i j;

[0069] S14, obtaining the water body nitrogen biological removal rate by actual measurement for each sampling point, and screening out the strongly related functional traits and the strongly related trait levels of the benthic animals that are strongly related to the water body nitrogen biological removal rate based on the obtained actual measurement water body nitrogen biological removal rate;

[0070] S15, determining the first component value of the strongly related trait level;

[0071] S16, based on the screened strongly related trait level, and taking the first component value of the strongly related trait level as the trait level weight B i , calculating the final score of the benthic animal functional trait evaluation of each sampling point according to the formula X = ∑A ij ·B i

[0072] ​S17, statistical distribution of the final score of the benthic animal functional traits evaluation of all sampling points, based on the value of the score in the quantile interval, the water body nitrogen biological removal capacity is classified to obtain the final water body nitrogen biological removal capacity evaluation table.

[0073] In step S11, for sample collection, a Sobe net (30*30cm, 250μm, high-strength corrosion-resistant nylon material, mesh size accuracy controlled within ±5μm) is used to collect macrobenthos samples in the stream. In the selected stream area, the Sobe net is placed on the bottom surface, ensuring that the net can cover a certain area and be placed smoothly, and the Sobe net is pressed into the bottom, and the hinge of the Sobe net is slowly closed, so that the macrobenthos enters the net. In the present application, the Sobe net made of high-strength corrosion-resistant nylon material has durability and stability in the complex environment of the stream, reducing damage and maintenance cost; high-precision mesh size control ensures that the collected macrobenthos samples are representative and accurate, improving sample quality and providing reliable data starting point for the entire evaluation method.

[0074] During the collection process, attention should be paid to avoid excessive disturbance to the stream bottom and surrounding environment to ensure that the collected macrobenthos samples are representative. Collect samples at different stream locations and depths to obtain sufficient samples. To demonstrate the feasibility of the present application for evaluating water body nitrogen biological removal capacity using benthic animal functional traits, according to the analysis method described in the present application, 100 macrobenthos samples were collected at 20 sampling points to ensure that the collected samples covered different ecological microenvironments and biological community compositions. After collection, the samples were quickly placed in a container containing an appropriate amount of 95% alcohol for fixation to prevent sample spoilage and biological form change, facilitating subsequent identification and analysis.

[0075] In step S11, after the sample collection step, the steps of benthic animal identification and matrix construction are also included, that is, the macrobenthos quantity matrix is constructed, which specifically includes: first, the collected macrobenthos samples are carefully identified and subdivided to determine the species and quantity of macrobenthos in each sample. Professional classification tools such as "Systematic Classification, Biology and Ecology of Freshwater Invertebrates" and microscope observation can be used to ensure that the identification is as fine as possible. Then, the number of individuals of each benthic animal is counted to construct a macrobenthos quantity matrix. Next, the constructed macrobenthos quantity matrix is converted, usually taking the logarithm of the quantity matrix to meet the mathematical requirements and data distribution characteristics of subsequent analysis.

[0076] In step S12, a macrobenthic functional trait matrix is constructed according to Freshwater Invertebrate Systematics, Biology and Ecology, which specifically includes constructing a macrobenthic functional trait matrix containing 12 functional traits including maximum body size, life cycle, reproductive generation, aquatic stage, sexual and asexual reproduction, dispersal mode, resistance form, food type, feeding mode, respiratory site, temperature-tolerant microhabitat, movement mode, and relationship with substrate.

[0077] In step S13, the constructed macrobenthic quantity matrix is multiplied by the macrobenthic functional trait matrix containing 12 functional traits to obtain a trait rank value matrix T containing 12 functional traits, wherein the parameter of the jth trait rank of the ith macrobenthic functional trait is denoted as A ij This step requires matrix multiplication by computer software to ensure accuracy and efficiency of the calculation process. During the calculation process, the dimensions and element values of the matrix should be carefully checked to avoid calculation errors.

[0078] Next is step S14, which is a step of performing correlation analysis and trait screening based on the measured water body nitrogen biological removal rate. It includes the following steps:

[0079] Step S1401, the water body nitrogen biological removal rate of the sample water body is obtained by actual measurement which indicates the water body nitrogen biological removal capacity (as an example). The water body nitrogen biological removal rate can be obtained by performing an in-situ tracing test in the field, and the implementation process of the in-situ tracing test in the field can be realized by the existing technology, which will not be described here.

[0080] Step S1402, taking the logarithm of the measured water body nitrogen biological removal rate as the dependent variable, and taking the obtained macrobenthic trait rank parameter A ij as the predictor, the significance value (or p value) of each trait rank is calculated and obtained by correlation analysis;

[0081] Step S1403, selecting the trait ranks with a significance value <0.05, and identifying the corresponding traits containing trait ranks with a significance value <0.05 as strong correlation functional traits;

[0082] Step S1404, taking the logarithm of the measured water body nitrogen biological removal rate as the dependent variable, and taking the obtained macrobenthic trait rank parameter A ij as the predictor, and calculating the importance value of each trait rank in the identified strong correlation functional traits by variable projection importance analysis, and screening out the trait ranks with an importance value greater than 0.7, and identifying them as strong correlation trait ranks.

[0083] In the step of correlation calculation in step S1402, the logarithm of the nitrogen biological removal rate of the water body is taken as the dependent variable, and the obtained benthic animal functional trait level parameter A ij is a prediction factor, and the p value of each trait level of the benthic animal is obtained based on pearson correlation analysis calculation. The formula for calculating the correlation coefficient r is:

[0084]

[0085] In the formula, X is the prediction factor Aij; and in the formula, Y is the logarithm of the nitrogen biological removal rate; lxx is the sum of squared deviations from the mean of X, specifically, l YY is the sum of squared deviations from the mean of Y, specifically, the sum of products of deviations from the mean between X and Y

[0086] In the calculation process, the pearson correlation model function in the professional statistical analysis software (such as SPSS, R language, etc.) can be used, the dependent variable and the prediction factor data are input, the model parameters and analysis options are set according to the operation guide of the software, and the p value of each trait level is obtained.

[0087] In the step S1403 of functional trait screening, the trait level with p<0.05 is selected through the result of pearson correlation analysis. That is, if a functional trait contains a trait level with p<0.05, the functional trait is considered to be a strong correlation functional trait, and all trait levels of the functional trait are selected for the next step. According to the calculated p value result, the functional traits meeting the conditions are screened, and the functional trait types having a significant influence on the nitrogen biological removal capacity of the water body are determined. Finally, it is determined that the four types of benthic animal functional traits, i.e., suitable temperature microhabitat, movement mode and relationship with substrate, food type and feeding mode, each contain multiple trait levels.

[0088] It should be particularly pointed out that in different aquatic environments and / or different water sampling points, the strong correlation functional traits and the strong correlation trait levels to be mentioned below determined based on the present application will be different. That is, other strong correlation functional trait combinations other than the aforementioned four strong correlation functional traits of the present application are not necessarily excluded from the protection scope of the present application.

[0089] In order to show the feasibility of using benthic animal functional traits to evaluate the nitrogen biological removal capacity of the water body according to the present application, the number values of the four types of benthic animal functional traits, i.e., suitable temperature microhabitat, movement mode and relationship with substrate, food type and feeding mode, of 20 sampling points are listed in Table 1 according to the analysis method described in the present application.

[0090] Table 1

[0091]

[0092] In the step S1404 of determining the specific trait level of strong correlation, the logarithm of the nitrogen biological removal rate of the water body is taken as the dependent variable, and the obtained benthic animal functional trait level parameter A ij The selected functional index is regressed by using partial least squares regression (PLS), and the VIP value of each functional trait morphology is calculated by using variable projection importance analysis method. The calculation formula of the VIP value is as follows:

[0093]

[0094] where p represents that a total of p variables are initially involved in the analysis; h represents that a total of h iterations are finally performed (a total of h dimensions are obtained); w jk represents the weight (i.e., the coefficient in the covariance matrix) used when the variable j is mapped at the kth iteration (the kth dimension), which reflects the explanatory degree of the variable j on the kth mapping result X k ; represents the explanatory degree of the kth mapping result X k on Y k . The VIP value is equivalent to the R 2 of linear regression, and the greater the VIP value, the stronger the correlation.

[0095] Next, the step S15 of determining the first component value of the specific trait level of strong correlation is performed. In the scheme in the present application, a total of 10 trait levels with VIP>0.7 are screened out, and the value of the first component (Component 1) is determined. The component refers to a potential variable (which can be understood as a score) extracted from the original data. The first component is the first component extracted when the partial least squares method is performed, which can capture most of the information in the data and can explain a significant part of the variation in the original data, so as to well explain the main trend in the data. In the calculation process, the statistical software is used for calculation and analysis in strict accordance with the formula and analysis method, so as to ensure that the accurate VIP value and the first component value are obtained.

[0096] Specifically, the calculation formula of the value Bi (i.e., the first component value) of the first component is as follows:

[0097] Bi=Tω1

[0098] where T is the benthic animal functional trait value matrix, and ω1 is the weight vector obtained after iteration optimization.

[0099] The 10 trait levels screened out and the value Bi of the first component are shown in Table 2 below

[0100] Table 2

[0101]

[0102] Next, the step of calculating the final score of the benthic animal functional trait evaluation of the sampling points is performed, specifically: after the final screening of 10 trait levels, the value of the corresponding first component is taken as the weight B i , and the final score X of the benthic animal functional trait evaluation is calculated according to the formula X = ∑A ij ·B i , wherein A ij is an element in the benthic animal functional trait value matrix T, representing the parameter of the jth trait level of the ith benthic animal functional trait; and B i is the trait level weight.

[0103] In step S17, according to the calculated final score X of the benthic animal functional trait evaluation, five quantiles are divided into five stream nitrogen biological removal capacity levels. If X < 25% quantile, it is considered that the nitrogen biological removal rate is low, corresponding to the Vth nitrogen biological removal capacity; if X belongs to 25%-50% quantile, it is considered that the nitrogen biological removal rate is relatively low, corresponding to the IVth nitrogen biological removal capacity; if X belongs to 50%-75% quantile, it is considered that the nitrogen biological removal rate is general, corresponding to the IIIth nitrogen biological removal capacity; if X belongs to 75%-90% quantile, it is considered that the nitrogen biological removal rate is relatively high, corresponding to the IIth nitrogen biological removal capacity; and if X > 90% quantile, it is considered that the nitrogen biological removal rate is high, corresponding to the Ith nitrogen biological removal capacity.

[0104] According to the following Table 3, the water body nitrogen biological removal capacity rating can be determined, so as to realize the level evaluation of the water body nitrogen biological removal capacity, and provide a scientific basis for river health assessment and water environment protection. In the whole process, the calculation results of each step need to be recorded and verified to ensure the reliability of the data and the accuracy of the conclusion.

[0105] Table 3

[0106]

[0107] In order to show the feasibility of the benthic animal functional trait evaluation of the water body nitrogen biological removal capacity proposed in the present application, according to the analysis method described in the content of the application, the final score X of the benthic animal functional trait evaluation, the nitrogen biological removal capacity evaluation level and the actual of the 20 sampling points are listed in the following Table 4.

[0108] In this example, the final score X of the benthic animal functional trait evaluation of the point 25, the point 26, the point 23, the point 6 and the point 24 is less than 0.1927, and it is considered that the nitrogen biological removal rate of these points is low, corresponding to the nitrogen biological removal ability of level V; the final score X of the benthic animal functional trait evaluation of the point 13, the point 11, the point 8, the point 12, the point 9, the point 7 belongs to the range of 0.1927-0.2070, and it is considered that the nitrogen biological removal rate of these points is relatively low, corresponding to the nitrogen biological removal ability of level IV; the final score X of the benthic animal functional trait evaluation of the point 17, the point 16, the point 15 and the point 2 belongs to the range of 0.2070-0.2357, and it is considered that the nitrogen biological removal rate of these points is general, corresponding to the nitrogen biological removal ability of level III; the final score X of the benthic animal functional trait evaluation of the point 21, the point 1 and the point 8 belongs to the range of 0.2357-0.2492, and it is considered that the nitrogen biological removal rate of these points is relatively high, corresponding to the nitrogen biological removal ability of level II; the final score X of the benthic animal functional trait evaluation of the point 20 and the point 19 is greater than 0.2492, and it is considered that the nitrogen biological removal rate of these points is high, corresponding to the nitrogen biological removal ability of level I;

[0109] Table 4 below shows that the actual nitrogen biological removal rate of most sampling points In the range of the corresponding level of the predicted nitrogen biological removal rate , it is shown that the prediction effect of the present application is good.

[0110] Table 4

[0111]

[0112] After the foregoing evaluation table is constructed, when the water body nitrogen biological removal capacity of the water body to be measured needs to be evaluated, only the benthic animals in the water body to be measured need to be collected, and then the final score of the benthic animal functional trait evaluation of the water body to be measured is calculated and obtained, and the final score is substituted into the evaluation table, and the nitrogen biological removal capacity classification can be obtained correspondingly, so as to realize the evaluation of the water body nitrogen biological removal capacity of the water body to be measured.

[0113] Specifically, in the evaluation step of the water body to be measured in step S2, it includes: S21, collecting the macrobenthos in the water body to be measured, and constructing a current macrobenthos quantity matrix based on the species and individuals of the collected macrobenthos;

[0114] S22, according to the Freshwater Invertebrate System Classification, Biology and Ecology, a matrix of functional traits of macrobenthos is constructed in advance. The current macrobenthos quantity matrix is logarithmically processed, and is multiplied by the matrix of macrobenthos functional traits constructed in advance, to obtain a current trait level value matrix representing the trait levels of the macrobenthos functional traits, so as to obtain a macrobenthos trait level parameter A representing the jth trait level of the i th macrobenthos functional trait in the current trait level value matrix ij ;

[0115] S23, based on the strong correlation trait levels screened in step S14, and taking the corresponding first component value of the strong correlation trait level determined in step S15 as a trait level weight B i , the final score of the macrobenthos functional trait evaluation of the current water body is calculated according to the formula X = ∑A ij ·B i ;

[0116] S24, based on the final score of the macrobenthos functional trait evaluation of the current water body obtained, the corresponding classification of the water body nitrogen biological removal capacity of the current water body is obtained from the water body nitrogen biological removal capacity evaluation table constructed in step S1.

[0117] Based on the above disclosed steps, compared with the conventional field in-situ test method based on the nutrient spiral model, the present application does not need to perform complex tracer addition, real-time water quality monitoring and cumbersome calculation process. Only macrobenthos in the stream is collected and identified according to the steps, the macrobenthos is subjected to correspondence analysis and calculation, the final score of the macrobenthos functional trait evaluation based on the functional traits is obtained, and then the final score is compared with the evaluation table constructed in advance, so that the evaluation result of the water body nitrogen biological capacity of the water body to be tested is obtained. Compared with the prior art, the method of the present application greatly reduces the workload, improves the evaluation efficiency, makes the whole evaluation process more simple and fast, and enhances the feasibility of actual operation.

[0118] Moreover, due to the unique position and role of macrobenthos in the ecosystem, the functional traits of macrobenthos comprehensively reflect the adaptation to the environment and the influence in the ecological chain, and the evaluation system constructed based thereon is less disturbed by the outside world, overcoming the problem that the evaluation method relying on microorganisms and algae is easily disturbed by secondary producers and non-biological factors in the stream. The evaluation result is more stable and reliable, and has stronger relevance with the water body nitrogen biological removal capacity, so that the actual situation can be more accurately reflected, providing strong support for river health assessment and water environment protection. That is, the present application discards the conventional method of evaluating the water body nitrogen biological removal capacity by microorganisms or algae in the prior art, and adopts the macrobenthos to evaluate the water body nitrogen biological removal capacity, so as to overcome the technical problems existing in the prior art of evaluating by means of microorganisms or algae.

[0119] In the present application, by analyzing a variety of functional traits, the potential correlation between benthic animals and the nitrogen biological removal capacity of the water body can be further explored in depth and detail, evaluation bias caused by incomplete consideration of functional traits can be avoided, and the subsequent accurate calculation of the benthic animal functional trait parameter A ij , accurate assessment of the correlation between the nitrogen biological removal capacity of the water body and the functional traits of benthic animals provides a solid foundation, greatly improves the scientificity and accuracy of the entire evaluation method, and makes the evaluation results more persuasive and reliable, thereby better serving the research and protection of the ecological environment of the stream.

[0120] Moreover, in the present application, each step from sample identification to quantitative statistics, data conversion and correspondence analysis ensures the rationality and effectiveness of data processing, so that the finally constructed matrix can accurately reflect the structure and characteristics of the benthic animal community, and provide a reliable data basis for subsequent multiplication with the trait matrix to obtain the trait value matrix.

[0121] In addition, in the calculation process of the partial least squares algorithm, the relationship between the independent variable and the dependent variable is decomposed and reconstructed, and the main components are extracted by dimensionality reduction of the data, wherein the first component is an important component score obtained in this process, and its value reflects the importance and direction of the trait grade in explaining the nitrogen biological removal capacity of the water body, and the positive and negative of the trait grade and the nitrogen biological removal of the water body can be determined by the positive and negative of the trait grade and the nitrogen biological removal of the water body, the positive value represents positive correlation, and the negative value represents negative correlation, and the absolute value size reflects the relative importance in the model, and the greater the absolute value, the greater the influence on the nitrogen biological removal capacity of the water body.

[0122] At the same time, the present application can comprehensively and comprehensively reflect the characteristics of benthic animals in the stream ecological system and the correlation with the environment by covering 12 kinds of functional traits, and can provide rich information for accurately evaluating the influence of benthic animals on the nitrogen biological removal capacity of the water body, greatly improving the accuracy and reliability of the evaluation, and avoiding one-sidedness of the evaluation.

[0123] Moreover, in the present application, the regression algorithm will screen the functional traits included in the model, and it will introduce or remove variables one by one to find the optimal model fitting effect. In this process, Pearson correlation analysis is carried out to calculate the significance value (p value) of each trait level. The p value is an important indicator for judging the significance of the trait level in the model. If the p value of a trait level is less than the set threshold (usually 0.05), it means that the trait level has statistical significance in explaining the nitrogen biological removal capacity of the water body, that is, there is a significant linear relationship between the trait level and the nitrogen biological removal capacity of the water body. That is, by setting the p value threshold to 0.05, by selecting the trait level with a p value less than 0.05, those trait levels that have little or no significant impact on the dependent variable (nitrogen biological removal capacity of the water body) can be effectively excluded, which helps to simplify the model structure and avoid the model becoming complex and difficult to explain due to the inclusion of too many irrelevant or secondary variables. The simplified model requires less time and resources in the calculation and analysis process, improving the efficiency of the study; at the same time, reducing the number of variables also helps to reduce the probability of multiple correlation problems, further improving the stability and accuracy of the model, making the evaluation of the nitrogen biological removal capacity of the water body more efficient and accurate.

[0124] In the present application, the important value (VIP) calculation formula can accurately quantify the importance of each trait level in explaining the nitrogen biological removal capacity of the water body through complex iterative calculation and weight analysis, and select the key trait level; and the calculation formula of the final score X of the benthic animal functional trait evaluation is based on the selected important trait level and its weight, which realizes the quantitative evaluation of the nitrogen biological removal capacity of the water body, and makes the evaluation result have clear numerical basis.

[0125] Moreover, in the present application, the pre-set VIP value is 0.07, which can prevent the model from being too complex while ensuring that the model has certain explanatory power. If the VIP value is set too low, too many variables may be introduced, leading to overfitting of the model, which may perform well on training data but have poor generalization ability on new data; while setting too high may miss some important but relatively weakly influenced variables. That is, the setting of the VIP value of 0.07 finds a balance point to some extent, so that the model can accurately capture the main influencing factors, and will not become difficult to explain and apply due to too many variables, which helps to improve the stability and reliability of the model, and provides strong support for accurate evaluation of the nitrogen biological removal capacity of the water body.

[0126] The present application establishes a link between the functional traits of benthic animals and the nitrogen biological removal capacity of water bodies, providing a new method and perspective for studying the biological driving mechanism of nitrogen cycling in stream ecosystems. Compared to previous methods that focused more on the impact of physical and chemical factors on nitrogen removal, this method highlights the importance of biological factors, particularly benthic animals, and helps to more comprehensively and deeply understand the material circulation process and ecological function of stream ecosystems, revealing the role and contribution of different benthic animal functional traits in nitrogen biological removal, providing specific cases and data support for ecologists to further study the relationship between biodiversity and ecosystem function, and enriching the theoretical system of ecosystem ecology.

[0127] Moreover, from sample collection to final capacity determination, each step is closely connected, establishing a complete and logically coherent evaluation system for the nitrogen biological removal capacity of water bodies, breaking away from the dependence on complex experimental conditions and easily disturbed biological indicators of traditional methods, providing a new scientific approach for evaluating the nitrogen biological removal capacity of water bodies, and improving the systematicness and accuracy of the evaluation.

[0128] The advantages of the method provided in the present application are summarized as follows:

[0129] 1) Directly determine the nitrogen biological removal capacity of streams through benthic animals, convenient and fast; 2) The requirement for instruments is not high, with good practicality and generalizability; 3) Because the consumables only need field sampling container bottles and alcohol, and the hardware only needs a Sobe net and a stereomicroscope, the cost is low; 4) Compared to using microbial indicators to determine the nitrogen removal capacity of streams, it is more economical; 5) Most importantly, compared to traditional methods using field in-situ experiments, this method is simpler, more economical and more feasible.

[0130] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the purpose and scope of the present application, and all should be included in the scope of the claims of the present application.

Claims

1. A method for evaluating the biological nitrogen removal capacity of water bodies based on the functional traits of benthic animals, characterized in that: The following steps are involved: S1, constructing an evaluation table for biological nitrogen removal capacity of water bodies based on the final scores of the functional traits evaluation of benthic animals; wherein the evaluation table for biological nitrogen removal capacity of water bodies is constructed into multiple levels, and the levels are divided based on different ranges of the final scores of the functional traits evaluation of benthic animals; S2, collecting macrobenthos from the water body to be tested, and calculating a final score of the benthic functional trait evaluation of the water body to be tested based on the trait grade of the benthic animals that is strongly correlated with the biological nitrogen removal rate of the water body that indicates the biological nitrogen removal capacity of the water body, and then deriving a corresponding grade of the biological nitrogen removal capacity of the water body to be tested from a pre-constructed evaluation table for biological nitrogen removal capacity of the water body based on the obtained final score of the functional trait evaluation of the benthic animals; The steps of constructing a water body nitrogen biological removal capacity evaluation table based on the final score of the benthic animal functional trait evaluation include: S11, collecting macrobenthic animal samples at multiple sampling points, and for each sampling point, constructing a macrobenthic animal quantity matrix based on the species and individuals of the collected macrobenthic animals; S12, constructing a macrobenthic functional trait matrix including multiple benthic functional traits; S13, for each sampling point, the constructed macrobenthos number matrix is ​​logarithmized and multiplied by the constructed macrobenthos functional trait matrix to obtain a trait grade value matrix representing the trait grade of the macrobenthos functional traits, where the parameter of the j-th trait grade of the i-th macrobenthos functional trait is recorded as the macrobenthos trait grade parameter A ij ; S14, measuring each sampling point to obtain a biological nitrogen removal rate of water bodies, and screening out strongly correlated traits and strongly correlated trait levels in benthic animals that are strongly correlated with the biological nitrogen removal rate of water bodies based on the obtained measured biological nitrogen removal rates of water bodies; S15, calculating and determining the first component value of the strongly correlated trait level based on the obtained measured biological nitrogen removal rate of the water body in combination with the partial least squares method; S16, based on the screened strong correlation trait level, the first component value corresponding to the strong correlation trait level is used as the trait level weight , according to the formula Calculate the final score of benthic functional trait evaluation at each sampling point; S17, statistically distribute the final scores of the functional traits evaluation of benthic animals at all sampling points, and grade the biological nitrogen removal capacity of water bodies based on the quantile interval of the score values ​​to obtain a final evaluation table of the biological nitrogen removal capacity of water bodies.

2. The method according to claim 1, characterized in that The step of screening out the strongly correlated functional traits and strongly correlated trait levels in benthic animals that are strongly correlated with the biological nitrogen removal rate of water bodies based on the obtained measured biological nitrogen removal rate of water bodies comprises: The logarithm of the measured biological nitrogen removal rate in water was used as the dependent variable to obtain the benthic animal trait grade parameter A. ij As the predictor, the significance value of each trait level was calculated and obtained through correlation analysis; The trait levels with significance values ​​less than 0.05 were selected, and the corresponding functional traits containing the trait levels with significance values ​​less than 0.05 were identified as strongly correlated functional traits; The logarithm of the measured biological nitrogen removal rate in water was used as the dependent variable to obtain the benthic animal trait grade parameter A. ij Regression was performed for the predictive factors, and the variable projection importance analysis method was used to calculate the importance value of each trait level in the identified strongly correlated functional traits. Trait levels with importance values ​​greater than 0.7 were screened out and identified as strongly correlated trait levels.

3. The method according to claim 2, characterized in that The step S17 includes: Based on the final evaluation scores of benthic functional traits of all sampling points, five quantiles were divided as the classification of the biological nitrogen removal capacity of water bodies, where: If the final evaluation score of the benthic functional traits is less than the 25th percentile, the biological nitrogen removal rate of the water body is considered to be low, corresponding to the biological nitrogen removal capacity of the water body at level V; If the final evaluation score of the benthic functional traits falls between the 25% and 50% quantiles, it is considered that the biological nitrogen removal rate of the water body is low, corresponding to the IV level of biological nitrogen removal capacity of the water body; If the final evaluation score of the benthic functional traits falls between the 50% and 75% percentiles, the biological nitrogen removal rate of the water body is considered average, corresponding to the biological nitrogen removal capacity of the water body at level III; If the final evaluation score of the benthic functional traits falls between the 75% and 90% percentiles, it is considered that the biological nitrogen removal rate of the water body is high, corresponding to the II level of biological nitrogen removal capacity of the water body; If the final evaluation score of the functional traits of benthic animals is >90% quantile, it is considered that the biological nitrogen removal rate of the water body is high, corresponding to Level I biological nitrogen removal capacity of the water body.

4. The method according to claim 3, characterized in that Partial least squares regression is used for regression processing, and the calculation formula of the important value is: ； Where: VIP stands for important value; p means that there are p variables involved in the analysis initially; h means that h iterations are performed in the end; w jk Indicates the weight used when variable j is mapped at the kth iteration, reflecting the effect of variable j on the kth mapping result X k the degree of explanation; Indicates the kth mapping result X k Y k degree of explanation.

5. The method according to claim 4, characterized in that The calculation formula for the first component value is: ； Where Bi represents the first component value, T is the trait grade numerical matrix, is the weight vector obtained after iterative optimization.

6. The method according to claim 5, characterized in that The multiple functional traits include: maximum body size, life cycle, reproductive generations, aquatic stage, sexual and asexual reproduction, dispersal mode, resistance morphology, food type, feeding mode, respiratory site, suitable temperature microhabitat, movement mode and relationship with the substrate.

7. The method according to claim 6, characterized in that The strongly correlated functional traits were screened and determined to be: thermophilic microhabitat, movement pattern and relationship with substrate, food type, and feeding pattern; The strongly correlated trait levels were screened and determined to be: slate / stone / stone / gravel, sand, micro-plants, crawling, interstitial benthic, fine sediment / microorganisms, biological debris, living micro-plants, dead animals, and scraping types.

8. The method according to any one of claims 1 to 7, characterized in that The step S2 comprises: S21, collecting macrobenthic animals in the water body to be tested, and constructing a current macrobenthic animal population matrix based on the species and individuals of the collected macrobenthic animals; S22, logarithm processing is performed on the current macrobenthos number matrix, and it is multiplied by the pre-constructed macrobenthos functional trait matrix to obtain the current trait grade value matrix representing the trait grade in the macrobenthos functional trait, thereby obtaining the macrobenthos trait grade parameter A representing the jth trait grade of the i-th macrobenthos functional trait in the current trait grade value matrix. ij ; S23, based on the strongly correlated trait levels screened out in step S14, and using the corresponding first component values ​​of the strongly correlated trait levels determined in step S15 as trait level weights , according to the formula Calculate the final score of the functional traits evaluation of the benthic animals in the current water body to be tested; S24, based on the final score of the functional traits evaluation of the benthic animals in the current water body to be tested, the corresponding grade of the biological nitrogen removal capacity of the water body to be tested is obtained from the evaluation table of biological nitrogen removal capacity of water body constructed in step S1.

9. The method according to claim 8, characterized in that The collection of benthic animals was based on the Sober net. After the collection was completed, the benthic animals were placed in a container filled with 95% alcohol for fixation.

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