阅读说明：本技术 一种淡水生态系统健康评价方法 (Fresh water ecosystem health evaluation method ) 是由 籍国东 罗忠新 隋欣 党正柱 于 2021-07-14 设计创作，主要内容包括：本发明提供了一种淡水生态系统健康评价方法。该方法,首先基于高通量测序技术,计算分类单元物种数、Shannon-Wienner多样性指数、污染敏感物种相对丰度、厌氧物种相对丰度和物种网络模块化系数,再通过标准化的参数计算浮游生物完整性指数,并基于计算结果进行评价。该方法首次提出了厌氧物种相对丰度和物种网络模块化系数,并将该两指标与现有代表性指标相结合,以全面反映环境变化对浮游生物物种丰富度、物种多样性、污染敏感性、污染耐受性和水生态功能的影响,提高评价准确性；并且该两指标的提出与结合,还简化了评价流程。因此,本发明的方法,可以快速、准确、灵敏的反映淡水生态系统健康状况,有助于流域管理者实施准确有效的治理措施。(The invention provides a method for evaluating the health of a fresh water ecosystem. The method comprises the steps of firstly calculating the number of classified unit species, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient based on a high-throughput sequencing technology, then calculating the plankton integrity index through standardized parameters, and evaluating based on the calculation result. The method firstly provides the relative abundance of anaerobic species and the modularization coefficient of a species network, and combines the two indexes with the current representative index to comprehensively reflect the influence of environmental change on the species abundance, species diversity, pollution sensitivity, pollution tolerance and water ecological function of plankton, and improve the evaluation accuracy; and the two indexes are provided and combined, so that the evaluation process is simplified. Therefore, the method of the invention can quickly, accurately and sensitively reflect the health condition of the fresh water ecosystem, and is beneficial to a river basin manager to implement accurate and effective treatment measures.)

1. A method for evaluating the health of a fresh water ecosystem is characterized by mainly comprising the following steps:

step 1, aiming at each sampling point in a plurality of sampling points, performing sequencing analysis on DNA of plankton in each sampling point by adopting a high-throughput sequencing analysis method to obtain sequencing data of plankton in a water sample to be evaluated;

step 2, obtaining the number of classification unit objects, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient of each sampling point based on the sequencing data;

step 3, calculating a plankton integrity index based on the classification unit species number, the Shannon-Wienner diversity index, the relative abundance of the pollution sensitive species, the relative abundance of the anaerobic species and the species network modularization coefficient;

and 4, determining the health condition level of the freshwater ecosystem to be evaluated according to the plankton integrity index and the health condition evaluation level of the freshwater ecosystem.

2. The evaluation method according to claim 1, wherein prior to step 1, the evaluation method further comprises:

aiming at each sampling point in a plurality of sampling points, filtering the sample of each sampling point to obtain a sample to be measured, wherein large particle impurities more than 200 mu m are filtered out; wherein the sample is a sample containing plankton cells;

vacuum filtering each sample to be detected by adopting a filter membrane with the aperture of 0.22 mu m, and extracting filter membrane DNA;

and carrying out PCR amplification by taking the DNA as a template to obtain a PCR product for carrying out the sequencing analysis operation.

3. The method according to claim 2, wherein the PCR amplification using the DNA as a template comprises:

performing PCR amplification on the V4 variable region of 18S rDNA by taking the DNA as a template;

the PCR product was detected by 2.0% agarose gel electrophoresis, and the target band was cut and purified, and the resulting PCR product was quantified.

4. The evaluation method according to claim 3, wherein the sequencing analysis of the DNA of plankton in each sample point is: sequencing analysis was performed on the PCR products based on plankton DNA in each sampling point.

5. The evaluation method according to claim 2, wherein after the filtering of the sample at each sampling point to obtain the sample to be tested filtered out of large particle impurities of 200 μm or more, the method further comprises:

measuring the water quality parameter of each sample to be measured; wherein the water quality parameters comprise dissolved oxygen concentration and nutritive salt index; the nutritive salt index includes at least one or more of a total nitrogen index, a total phosphorus index, and a permanganate index.

6. The evaluation method according to any one of claims 1 to 5, wherein the step 2 includes:

obtaining the number of classified unit objects and a Shannon-Wienner diversity index of each sampling point through OTU clustering and diversity analysis based on the sequencing data;

performing correlation analysis on the relative abundance of plankton and water quality parameters based on the sequencing data to obtain the relative abundance of pollution sensitive species and the relative abundance of anaerobic species; wherein the water quality parameters comprise dissolved oxygen concentration and nutritive salt index; the nutritive salt index includes at least one or more of a total nitrogen index, a total phosphorus index, and a permanganate index.

And obtaining species network modularization coefficients of the fresh water ecosystem through molecular ecological network analysis based on the sequencing data.

7. The evaluation method according to claim 1, wherein in the step 3, the calculation formula for calculating the plankton integrity index is:

in the formula, P-IBI refers to plankton integrity index, n refers to the total number of sampling points corresponding to the fresh water ecosystem to be evaluated, and S_iNormalized score for the number of taxon objects corresponding to the ith sample point, D_iNormalized score, P, of the Shannon-Wienner diversity index corresponding to the ith sample point_iRelative abundance of contamination sensitive species corresponding to ith sample point, A_iThe relative abundance of anaerobic species corresponding to the ith sampling point is obtained, and N is a species network modularization coefficient;

the normalized score is a numerical value normalized by a ratio method, the range of the normalized score is 0-1, and the score larger than 1 is 1.

8. The method of claim 1 or 7, wherein the relative abundance of the contaminant-sensitive species is: a ratio of the number of sequences of the set of taxa significantly negatively correlated with total phosphorus, total nitrogen, or permanganate index to the sum of the number of sequences of all taxa;

the relative abundance of the anaerobic species refers to: the ratio of the sequence number of the classification unit which is obviously and negatively related to the dissolved oxygen concentration of the water body to the sum of the sequence numbers of all the classification units;

the species network modularization coefficient refers to: calculating a modular value by adopting a Newman method, wherein the numerical value is between 0 and 1;

wherein the significant negative correlation refers to a P value < 0.05.

9. The method of claim 7, wherein the means for calculating the normalized scores of the taxon number of species, the Shannon-wiener diversity index, the relative abundance of the pollution sensitive species, and the relative abundance of the anaerobic species comprises:

setting a reference point and a damaged point, and calculating the standardized score by adopting a ratio method;

for a representative index with a lower value as the disturbance increases, the normalized score is calculated by:

for a representative index with a higher value as the disturbance increases, the normalized score is calculated by the formula:

in the formula, PM_iIs the normalized score, PQ, of the ith sample point_iIs a representative index value, PQ, of the ith sample point₉₅The index is the optimal expected value of a representative index taking the 95% quantile value of the reference point as the ith sampling point, PQ_maxIs the maximum value of the representative index, PQ, at the ith sample point₅The index is the best expected value of the representative index taking the 5% quantile value of the reference point as the ith sampling point.

10. The evaluation method according to claim 1, 7 or 8, wherein the species network modularization coefficients are obtained by constructing a molecular ecological network based on a random matrix theory method and performing ecological network visualization and graphical representation.

Technical Field

The invention relates to the technical field of environmental pollution monitoring and evaluation, and mainly relates to a method for evaluating the health of a fresh water ecosystem.

Background

The fresh water resource comprises water in rivers and lakes, high mountain snow, glaciers, underground water and the like. In recent years, with the rapid development of economic society, people are disturbed excessively and are not protected enough, so that the quality of fresh water in partial areas is deteriorated, hydrological conditions are changed, the habitat is degraded, important or sensitive organisms disappear, and even serious consequences which are difficult to compensate are caused. Therefore, the method develops the health evaluation research of the fresh water ecosystem, establishes effective evaluation indexes and scientific methods, accurately diagnoses the health condition of the fresh water ecosystem, and has great significance for sustainable utilization and management of fresh water resources and promotion of the health development of the fresh water ecosystem.

Biological integrity refers to the ability of a biological community to maintain structural balance and adapt to environmental changes. The biological Integrity Index (IBI) is composed of a plurality of biological condition parameters, and the health of the aquatic ecosystem is obtained by comparing the parameter values with standard values of a reference system. Since Karr established the Fish biological Integrity Index (F-IBI) in 1981 to evaluate river health, many scholars have modified and expanded the Index system, with IBI having been expanded to other aquatic organisms such as large benthic invertebrates, periphytons, algae and microorganisms. At present, IBI is widely applied to health evaluation of aquatic ecosystems such as rivers, lakes, reservoirs, wetlands and the like, and plays an important role in monitoring and managing the environments of water areas such as lakes, estuaries, offshore areas and the like.

However, as the research progresses, the construction method of the biological integrity index becomes more and more rigorous and complicated, and at the present stage, the construction method of the biological integrity index mainly comprises the following steps: 1) determining candidate biological condition parameter indexes in an index library according to population characteristics of a research area; 2) selecting a reference point (undamaged sampling points or damaged minimal sampling points) and an interference point (sampling points which are subjected to various interferences such as point source and non-point source pollution, forest coverage rate reduction, urbanization, dam construction and the like), acquiring parameter index data, and establishing an evaluation index system through analysis of the distribution range, judgment capability (sensitivity analysis) and correlation analysis of the parameter index values; 3) determining each parameter index value and a calculation method of the IBI index, and respectively calculating the IBI index values of the reference point and the interference point; 4) establishing a scoring standard of the biological integrity index; 5) and verifying and revising the IBI through comparison of independent data, and determining the effectiveness of the IBI index method.

However, the above-mentioned existing methods for constructing a biological integrity index have problems of complicated operation, low efficiency, and low accuracy of evaluation in practical practice. Therefore, in order to solve the technical problems in the prior art, a novel and simple method for evaluating the health of a fresh water ecosystem is urgently needed in the technical field.

Disclosure of Invention

In order to solve the technical problems in the prior art, the invention provides a method for evaluating the health of a fresh water ecosystem. The method is mainly a method for evaluating the health of the freshwater ecosystem by taking the plankton integrity index as a judgment index, is simple in sampling method and small in sample demand, and can simply, conveniently and accurately calculate the plankton integrity index under the condition of not needing taxonomy identification experience, so that the aim of improving the accuracy of evaluating the health level of the freshwater ecosystem is fulfilled. The specific contents are as follows:

the invention provides a fresh water ecosystem health evaluation method, which mainly comprises the following steps:

step 1, aiming at each sampling point in a plurality of sampling points, performing sequencing analysis on DNA of plankton in each sampling point by adopting a high-throughput sequencing analysis method to obtain sequencing data of plankton in a water sample to be evaluated;

step 2, obtaining the number of classification unit objects, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient of each sampling point based on the sequencing data;

step 3, calculating a plankton integrity index based on the classification unit species number, the Shannon-Wienner diversity index, the relative abundance of the pollution sensitive species, the relative abundance of the anaerobic species and the species network modularization coefficient;

and 4, determining the health condition level of the freshwater ecosystem to be evaluated according to the plankton integrity index and the health condition evaluation level of the freshwater ecosystem.

Preferably, before step 1, the evaluation method further comprises:

aiming at each sampling point in a plurality of sampling points, filtering the sample of each sampling point to obtain a sample to be measured, wherein large particle impurities more than 200 mu m are filtered out; wherein the sample is a sample containing plankton cells;

vacuum filtering each sample to be detected by adopting a filter membrane with the aperture of 0.22 mu m, and extracting filter membrane DNA;

and carrying out PCR amplification by taking the DNA as a template to obtain a PCR product for carrying out the sequencing analysis operation.

Preferably, the operation of performing PCR amplification using the DNA as a template includes:

performing PCR amplification on the V4 variable region of 18S rDNA by taking the DNA as a template;

the PCR product was detected by 2.0% agarose gel electrophoresis, and the target band was cut and purified, and the resulting PCR product was quantified.

Preferably, the sequencing analysis of the DNA of plankton in each sample point is: sequencing analysis was performed on the PCR products based on plankton DNA in each sampling point.

Preferably, after the filtering is performed on the sample at each sampling point to obtain the sample to be tested, in which large particle impurities above 200 μm are filtered out, the method further includes:

measuring the water quality parameter of each sample to be measured; wherein the water quality parameters comprise dissolved oxygen concentration and nutritive salt index; the nutritive salt index includes at least one or more of a total nitrogen index, a total phosphorus index, and a permanganate index.

Preferably, the step 2 includes:

obtaining the number of classified unit objects and a Shannon-Wienner diversity index of each sampling point through OTU clustering and diversity analysis based on the sequencing data;

performing correlation analysis on the relative abundance of plankton and water quality parameters based on the sequencing data to obtain the relative abundance of pollution sensitive species and the relative abundance of anaerobic species; wherein the water quality parameters comprise dissolved oxygen concentration and nutritive salt index; the nutritive salt index includes at least one or more of a total nitrogen index, a total phosphorus index, and a permanganate index.

And obtaining species network modularization coefficients of the fresh water ecosystem through molecular ecological network analysis based on the sequencing data.

Preferably, in step 3, the calculation formula of the plankton integrity index is:

in the formula, P-IBI refers to plankton integrity index, n refers to the total number of sampling points corresponding to the fresh water ecosystem to be evaluated, and S_iNormalized score for the number of taxon objects corresponding to the ith sample point, D_iNormalized score, P, of the Shannon-Wienner diversity index corresponding to the ith sample point_iRelative abundance of contamination sensitive species corresponding to ith sample point, A_iThe relative abundance of anaerobic species corresponding to the ith sampling point is obtained, and N is a species network modularization coefficient;

the normalized score is a numerical value normalized by a ratio method, the range of the normalized score is 0-1, and the score larger than 1 is 1.

Preferably, the relative abundance of the contamination-sensitive species is: a ratio of the number of sequences of the set of taxa significantly negatively correlated with total phosphorus, total nitrogen, or permanganate index to the sum of the number of sequences of all taxa;

the relative abundance of the anaerobic species refers to: the ratio of the sequence number of the classification unit which is obviously and negatively related to the dissolved oxygen concentration of the water body to the sum of the sequence numbers of all the classification units;

the species network modularization coefficient refers to: calculating a modular value by adopting a Newman method, wherein the numerical value is between 0 and 1;

wherein the significant negative correlation refers to a P value < 0.05.

Preferably, the method for calculating the normalized scores of the taxon number of members, Shannon-Wienner diversity index, relative abundance of pollution sensitive species and relative abundance of anaerobic species specifically comprises the following steps:

setting a reference point and a damaged point, and calculating the standardized score by adopting a ratio method;

for a representative index with a lower value as the disturbance increases, the normalized score is calculated by:

for a representative index with a higher value as the disturbance increases, the normalized score is calculated by the formula:

in the formula, PM_iIs the normalized score, PQ, of the ith sample point_iIs a representative index value, PQ, of the ith sample point₉₅The index is the optimal expected value of a representative index taking the 95% quantile value of the reference point as the ith sampling point, PQ_maxIs the maximum value of the representative index, PQ, at the ith sample point₅The index is the best expected value of the representative index taking the 5% quantile value of the reference point as the ith sampling point.

Preferably, the species network modularization coefficient is obtained by constructing a molecular ecological network based on a random matrix theory method and performing ecological network visualization illustration.

The invention provides a method for evaluating the health of a fresh water ecosystem. The evaluation method mainly comprises the following steps: step 1, aiming at each sampling point in a plurality of sampling points, performing sequencing analysis on DNA of plankton in each sampling point by adopting a high-throughput sequencing analysis method to obtain sequencing data of plankton in a water sample to be evaluated; step 2, obtaining the number of classified unit species, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient of each sampling point based on sequencing data; step 3, calculating to obtain a plankton integrity index based on the number of classified unit species, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient; and 4, determining the health condition level of the freshwater ecosystem to be evaluated according to the value of the plankton integrity index and the health condition evaluation level of the freshwater ecosystem. Compared with the prior art, the method for evaluating the health of the fresh water ecosystem, provided by the invention, at least has the following advantages:

1. the evaluation method provided by the application firstly provides the relative abundance of anaerobic species and the species network modularization coefficient, takes the two indexes as the representative indexes for evaluating the integrity of the plankton, combines the representative indexes with the existing representative indexes, makes up the neglect of the water ecological function in the evaluation in the prior art, can comprehensively reflect the influence of environmental changes on the abundance, species diversity, pollution sensitivity, pollution tolerance and water ecological function of the plankton species, and improves the evaluation accuracy.

2. According to the evaluation method, the number of the classified unit species, the Shannon-Wienner diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient are taken as representative indexes of the integrity of the plankton, the index screening process of the integrity index of the plankton is simplified, the health condition of a fresh water ecosystem can be quickly, accurately and sensitively reflected, and a flow domain manager can be facilitated to implement accurate and effective treatment measures.

3. According to the evaluation method, the high-throughput sequencing analysis method is applied to the field of plankton, compared with a microscopic examination method (i.e. a method for analyzing organisms by using a microscope) in the prior art, the problems of high requirements on taxonomic identification experience, low accuracy caused by human errors and system errors, complex operation process, low efficiency and the like in the microscopic examination method can be perfectly solved, and the effects of no need of taxonomic identification experience, high accuracy, simple operation process and high efficiency are achieved.

4. Compared with the conventional screening parameter index method, the evaluation method provided by the invention has the advantage that the correlation obtained by evaluation can reach 0.8 in independent evaluation, so that the evaluation method provided by the invention has higher reliability.

In addition, in the evaluation method provided by the invention, the sampling points are selected based on a large-range water sample for sampling so as to improve the evaluation accuracy; and based on the consideration of water ecological function factors, species network modularization coefficients are introduced to comprehensively reflect the health state of the fresh water ecosystem, and the evaluation accuracy is further improved. Meanwhile, the inventor provides an evaluation index of the relative abundance of anaerobic species in the experimental process so as to accurately reflect the pollution tolerance of plankton, so that a scientific, accurate and artificial-error-free evaluation result can be obtained when the P-IBI value is calculated.

Drawings

FIG. 1 is a flow chart of a method for evaluating health of a fresh water ecosystem according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method for evaluating the health of a fresh water ecosystem according to embodiment 1 of the present invention;

FIG. 3 is a distribution diagram showing the Shannon-Wiener diversity index and the number of taxa in each section calculated in example 1 of the present invention;

FIG. 4 is a graph showing the distribution of the relative abundance of the pollution sensitive species and the relative abundance of the anaerobic species calculated for each section in example 1 of the present invention;

FIG. 5 is a graph showing a plankton correlation network in the yellow river in example 1 of the present invention;

FIG. 6 shows plankton of each cross section calculated in example 1 of the present inventionIntegrity index (P-IBI)_i) A distribution map of;

fig. 7 is a graph showing comparison results of comparison of evaluation results of two different plankton integrity index methods (the evaluation method proposed by the present invention used in example 1, and the evaluation method in the prior art used in example 2) in the midstream of the yellow river in the example of the present invention.

Detailed Description

The following examples are provided to further understand the present invention, not to limit the scope of the present invention, but to provide the best mode, not to limit the content and the protection scope of the present invention, and any product similar or similar to the present invention, which is obtained by combining the present invention with other prior art features, falls within the protection scope of the present invention.

The plankton in the water body is various and large in quantity, plays a vital role in material circulation, energy flow and information transfer of the water body, and the community composition structure and diversity play a vital role in the structure and functional diversity of a water ecological system where the plankton lives. The life cycle of plankton is short, and the plankton reacts sensitively to the change of factors such as physics, chemistry of water, and its structural feature and functional state can reflect the water ecosystem and input the resilience of coerce to the pollution, therefore can be regarded as the "indicator" of water ecosystem quality. Therefore, the embodiment constructs a plankton integrity index system with plankton as a main object for evaluating the aquatic ecological health condition.

Compared with the technical problems of the conventional method for determining the index of the biological integrity index by using the morphological identification method (the problems and the defects of the morphological identification method limit the deep understanding of plankton diversity of people, such as the fact that small-quantity, tiny and difficultly-cultured clusters are easily ignored, the operation process is complex, and rich taxonomic identification experience is needed), the embodiment introduces the DNA high-throughput sequencing analysis method into the field of plankton to check higher diversity compared with the morphological method, and greatly improves the precision of plankton detection and classification.

Based on the above content, the embodiment of the invention provides a plankton integrity-based fresh water ecosystem health evaluation method, which is based on a high-throughput sequencing analysis result, omits a complicated process of constructing a plankton integrity index system, can simply, conveniently and accurately calculate the plankton integrity index, and has important significance for developing fresh water ecosystem health evaluation. The embodiment of the invention specifically comprises the following contents:

fig. 1 shows a flow chart of a method for evaluating health of a fresh water ecosystem according to an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides a method for evaluating health of a fresh water ecosystem, including the following steps:

step 1(S1), for each sampling point in the plurality of sampling points, a high-throughput sequencing analysis method is adopted to perform sequencing analysis on the DNA of plankton in each sampling point, and sequencing data of plankton in the water sample to be evaluated is obtained.

During specific implementation, a plurality of sampling sections are set for a fresh water ecosystem to be evaluated, the number of the sampling sections is generally 8, the number of the sampling sections can exceed 8, then each sampling section is determined as a sampling point, sampling of a water sample is carried out, and sequencing analysis is carried out on DNA of plankton in the water sample.

In this embodiment, the sequencing platform used for sequencing analysis may be MiSeq PE300, and paired-end sequencing is used for sequencing. After sequencing is completed, processing the double-end original sequence data obtained by sequencing to obtain sequencing data for calculating the number of the classified unit species, the Shannon-Wienner diversity index, the relative abundance of the pollution sensitive species, the relative abundance of the anaerobic species and the species network modularization coefficient.

In this implementation step, the specific process of the above-mentioned processing may be: sequencing to obtain double-end original sequence data, performing quality control on the double-end original sequence data by using Fastp software, and splicing paired sequences into a sequence by using Flash software according to an overlap relation between PE reads (paired-end reads). The sequence alignment tool Ucluster is called by using Qiame (quantitative instruments into microbial technology) software, and the obtained sequences are merged and OTU clustered according to 97% of sequence similarity. Comparing the OTU representative sequences with template sequences of a Silva database, performing taxonomic annotation on each OTU representative sequence level by adopting an RDP classificator Bayesian algorithm (the classification confidence coefficient is 0.7), and finally obtaining sequencing data for calculating the number of classified unit species, Shannon-Wienner diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient.

And 2(S2), obtaining the classification unit species number, Shannon-Wienner diversity index, pollution sensitive species relative abundance, anaerobic species relative abundance and species network modularization coefficient of each sampling point based on the sequencing data.

In specific implementation, the sequencing data can accurately reflect the species, the number, the quantity and the functions of plankton, so that the species number of classification units, the Shannon-wiener diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient of plankton in each sampling point can be calculated and obtained based on the sequencing data.

In the implementation step, the number of classified unit species, the Shannon-Wienner diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient are selected as plankton integrity representative indexes to reflect the influence of environmental changes on the plankton species abundance, species diversity, pollution sensitivity, pollution tolerance and water ecological function, and in the subsequent steps, the parameters are standardized through a ratio method, the P-IBI value is calculated, and finally the health condition level of the fresh water ecological system is determined according to the P-IBI result.

And 3, calculating a plankton integrity index based on the classification unit species number, the Shannon-Wienner diversity index, the relative abundance of the pollution sensitive species, the relative abundance of the anaerobic species and the species network modularization coefficient (S3).

In specific implementation, the number of classification unit substances, the Shannon-Wienner diversity index, the relative abundance of pollution sensitive species and the relative abundance of anaerobic species can be respectively standardized by a ratio method to obtain corresponding standardized scores. And then, calculating to obtain the plankton integrity index by combining the species network modularization coefficient.

In this implementation step, the formula for calculating the plankton integrity index may be:

in the formula, P-IBI refers to plankton integrity index, n refers to the total number of sampling points corresponding to the fresh water ecosystem to be evaluated, and S_iNormalized score for the number of taxon objects corresponding to the ith sample point, D_iNormalized score, P, of the Shannon-Wienner diversity index corresponding to the ith sample point_iRelative abundance of contamination sensitive species corresponding to ith sample point, A_iThe relative abundance of anaerobic species corresponding to the ith sampling point is obtained, and N is a species network modularization coefficient;

the normalized score is a numerical value normalized by a ratio method, the range of the normalized score is 0-1, and the score larger than 1 is 1.

It should be noted that, because the calculation methods may be various, in this embodiment, the calculation formula for calculating the plankton integrity index is not limited and listed one by one, that is, the calculation formula for calculating the plankton integrity index may be other, and it should be understood that the technical idea of the calculation formula for calculating the plankton integrity index in this embodiment step is essentially: and selecting the number of classified unit species, Shannon-Wienner diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species and species network modularization coefficient as plankton integrity representative indexes to calculate the plankton integrity index so as to completely and comprehensively reflect the influence of environmental change on the plankton species abundance, species diversity, pollution sensitivity, pollution tolerance and aquatic ecological function.

And 4, determining the health condition level of the freshwater ecosystem to be evaluated according to the plankton integrity index and the health condition evaluation level of the freshwater ecosystem by referring to the plankton integrity index.

In this implementation step, the evaluation level of the health condition of the fresh water ecosystem may be set according to an actual situation, and is not limited in this implementation step.

In specific implementation, the setting of the evaluation level of the health condition of the fresh water ecosystem in the implementation step may be: establishing a health evaluation standard according to the P-IBI value, and dividing the health of the fresh water ecosystem into 5 grades, wherein the 5 grades are 0.8-1 (healthy), 0.6-0.8 (sub-healthy), 0.4-0.6 (general), 0.2-0.4 (poor) and 0-0.2 (poor) in sequence.

In this embodiment, in order to improve accurate sequencing analysis of plankton DNA, preferably, before step 1, the evaluation method further includes the following steps:

aiming at each sampling point in the plurality of sampling points, filtering a sample corresponding to each sampling point to obtain a sample to be detected, wherein large particle impurities more than 200 micrometers are filtered out; wherein the sample is a sample containing plankton cells;

vacuum filtering each sample to be detected by adopting a filter membrane with the aperture of 0.22 mu m, and extracting the DNA of the filter membrane;

and carrying out PCR amplification by taking the extracted DNA as a template to obtain a PCR product for sequencing analysis operation.

In this embodiment, preferably, the operation of performing PCR amplification using the extracted DNA as a template may specifically include:

performing PCR amplification on the V4 variable region of 18S rDNA by taking the extracted DNA as a template;

the PCR product was detected by 2.0% agarose gel electrophoresis, and the target band was cut and purified, and the resulting PCR product was quantified. Based on this, preferably, the DNA of plankton in each sampling point is sequenced and analyzed as: sequencing analysis was performed on the PCR products obtained based on the DNA of plankton in each sample point.

In this embodiment, in order to accurately obtain the relative abundance of the pollution-sensitive species and the relative abundance of the anaerobic species, preferably, after filtering the sample at each sampling point to obtain the sample to be tested, in which large particle impurities above 200 μm are filtered, the evaluation method further includes:

measuring the water quality parameter of each sample to be measured; wherein the water quality parameter comprises one or more of a dissolved oxygen concentration, a total nitrogen index, a total phosphorus index, and a permanganate index.

When the water quality parameters are measured, the field parameters such as dissolved oxygen, temperature, pH and the like are measured on the sampling field, 500mL of water sample is collected and stored at low temperature and is brought back to a laboratory, and the total nitrogen index, the total phosphorus index and the potassium permanganate index are measured within 48 hours.

In this embodiment, the method for calculating the taxon number, Shannon-wiener diversity index, relative abundance of pollution sensitive species, relative abundance of anaerobic species, and species network modularization coefficient of each sampling point may preferably be as follows:

based on sequencing data, obtaining the number of classified unit objects and the Shannon-Wienner diversity index of each sampling point through OTU clustering and diversity analysis;

performing correlation analysis on the relative abundance of planktons and water quality parameters based on sequencing data to obtain the relative abundance of pollution sensitive species and the relative abundance of anaerobic species; wherein the water quality parameter comprises one or more of a dissolved oxygen concentration, a total nitrogen index, a total phosphorus index, and a permanganate index.

And obtaining species network modularization coefficients of the fresh water ecosystem through molecular ecological network analysis based on sequencing data.

In this embodiment, the relative abundance of the contamination-sensitive species is preferably: the ratio of the number of sequences of the set of taxa negatively correlated with total phosphorus, total nitrogen or permanganate index to the sum of the number of sequences of all taxa. The relative abundance of anaerobic species refers to: the ratio of the sequence number of the classification unit which is negatively related to the dissolved oxygen concentration of the water body to the sum of the sequence numbers of all the classification units.

Relative abundance of contamination sensitive species-sequence number/total sequence number of set of taxa negatively correlated with total phosphorus, total nitrogen or permanganate index x 100%;

relative abundance of anaerobic species is sequence number/total sequence number of the classification unit negatively correlated to the concentration of dissolved oxygen in water body x 100%.

It should be noted that the above negative correlation, when implemented, may be a significant negative correlation, so as to simplify the calculation process and ensure the accuracy of the obtained value of the representative index.

In the embodiment, the species network modularization coefficient is a modularization value obtained by calculating by adopting a Newman method, and the numerical value is between 0 and 1 and is used for reflecting the functionality of a species community.

In this embodiment, preferably, the sum of the numbers of taxa, Shannon-wiener diversity index, the relative abundance of pollution sensitive species and the relative abundance of anaerobic species are all representative indexes of plankton integrity, and the method for calculating the normalized score of the representative indexes specifically includes the following steps:

setting a reference point and a damaged point, and calculating a standardized score by adopting a ratio method;

for a representative index that has a lower value as the disturbance increases, the normalized score is calculated by:

for a representative index with a higher value as the disturbance increases, the normalized score is calculated by:

in the formula, PM_iIs the normalized score, PQ, of the ith sample point_iIs a representative index value, PQ, of the ith sample point₉₅The index is the optimal expected value of a representative index taking the 95% quantile value of the reference point as the ith sampling point, PQ_maxIs the maximum value of the representative index, PQ, at the ith sample point₅The index is the best expected value of the representative index taking the 5% quantile value of the reference point as the ith sampling point.

The reference points are used to determine the reference state of the body of water, and refer to specific locations that are not damaged or are minimally damaged and are representative of the biological integrity of the body of water or adjacent bodies of water. The determination of the reference point mainly comprises the following four methods, namely, historical data estimation; surveying and sampling reference points; model prediction; and fourthly, expert consultation. The following two principles should be followed in the selection of the reference point:

(ii) with minimal human interference:

the reference point is selected from the places which are not interfered by human activities, but the reference point which is really not interfered in a specific water body is difficult to find. In practice, therefore, the location with the least human interference is often selected as the reference point.

② representative:

the selected reference point must be representative of the optimal conditions of the water body investigation region. On the basis of water habitat survey and evaluation, a reference point is selected according to the minimum interference and the representative principle. However, some water bodies are greatly interfered by human beings, and the ecological environment is greatly different from the 'natural' state, so that no proper reference point can be selected, and an ecological model or expert consultation method can be adopted at this time.

In this embodiment, preferably, the species network modularization coefficient is obtained by constructing a molecular ecological network based on a random matrix theory method and performing ecological network visualization illustration.

The method for evaluating the health of the fresh water ecosystem, provided by the embodiment of the invention, has the advantages of simple sampling method, less sample demand, no need of taxonomy identification experience, and capability of simply, conveniently and accurately calculating the plankton integrity index, thereby evaluating the health level of the fresh water ecosystem.

The method for evaluating the health of the fresh water ecosystem, provided by the embodiment of the invention, comprises the steps of firstly calculating the number of classified unit species, Shannon-Wienner diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient based on a high-throughput sequencing technology, then calculating the plankton integrity index through standardized parameters, and evaluating based on the calculation result. The method firstly provides the relative abundance of anaerobic species and the modularization coefficient of a species network, and combines the two indexes with the current representative index to comprehensively reflect the influence of environmental change on the abundance, species diversity, pollution sensitivity, pollution tolerance and water ecological function of plankton species and improve the evaluation accuracy. Moreover, the two indexes are provided and combined, so that the evaluation method provided by the embodiment of the invention is simple to operate and high in accuracy, not only is the artificial error caused by microscopic examination of plankton avoided, but also the index screening process of plankton integrity indexes is simplified, the health condition of a fresh water ecosystem can be reflected quickly, accurately and sensitively, and the method is beneficial to a territorial manager to implement accurate and effective treatment measures.

In order to make the person skilled in the art better understand the present invention, the method for evaluating the health of the fresh water ecosystem provided by the present invention is illustrated by the following specific examples. It is noted that other advantages and effects of the present invention will be readily apparent to those skilled in the art from the disclosure herein. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.

Example 1 (please refer to fig. 2 for the implementation flow of this embodiment):

1) sample collection and pretreatment

Laying 26 sections in the midstream river reach of the yellow river, measuring on-site parameters such as DO (dissolved oxygen), T (temperature), pH and the like of each on-site section, collecting 500mL of surface water sample, storing at low temperature, bringing the surface water sample back to a laboratory, and measuring water quality parameters such as total nitrogen, total phosphorus, potassium permanganate index and the like within 48 hours. 1.0L of surface layer water sample (about 0.5m below the water surface) containing plankton cells is collected for each section, and is pre-filtered by a stainless steel sieve with the aperture of 200 mu m, and large particle impurities with the aperture of more than 200 mu m are filtered out.

Vacuum filtering 1.0L of pretreated water sample with 0.22 μm filter membrane, storing the filter membrane at low temperature, and performing DNA extraction, PCR amplification and high-throughput sequencing analysis on the filter membrane according to the DNA extraction kit instruction. Wherein, the DNA extraction Kit adopts an MP Soil DNA rapid extraction Kit (FastDNA Spin Kit for Soil), and the DNA extraction of the sample is carried out according to the instruction. Selecting a design primer (TAReuk 454F: CCAGCASC-YGCGGTAATTCC, TAReukR: ACTTTCGTTCTTGA TYRA) of the V4 region of the 18S rDNA gene for PCR amplification, detecting a PCR amplification product by adopting a 2% agarose gel electrophoresis method, detecting a target band in the PCR amplification product of all samples, detecting no band in blank control, namely successfully amplifying the 18S rDNA of each water body sample, and recovering the PCR product.

And (3) purifying the PCR amplification product, sending the PCR amplification product to Shanghai Meiji bio-corporation for sequencing (Illumina Miseq platform) to obtain sequencing original data (uploaded to NCBI database), firstly performing quality control on the original data by using Fastp software, filtering bases with tail quality value of less than 20 of reads (wherein the reads represent sequences), setting a window of 50bp, cutting back-end bases from the window if the average quality value in the window is less than 20, and filtering the reads with quality value of less than 50 bp. According to the overlap relation between PE reads (paired-end reads), paired reads are spliced into a sequence by using Flash software. And distinguishing samples according to the barcode and the primer sequences at the head end and the tail end of the splicing sequence to obtain an effective sequence, correcting the sequence direction, and performing quality control filtration on data. And calling a sequence comparison tool UCLUST by using Qiame software, merging the obtained sequences according to 97% of sequence similarity, and carrying out OTU clustering to obtain the OTU grouping condition. Comparing the OTU representative sequences with template sequences of a Silva 128 database, performing taxonomic annotation on each OTU representative sequence by adopting an RDP classifier Bayesian algorithm (the classification confidence coefficient is 0.7), and counting the community composition of each sample at each taxonomic level respectively.

The midstream river reach of the yellow river is a stable river channel which is evolved for a long time, and the function of an ecological system is complete. The water pollution index is special, COD_Mn、DO、pH、NH₃both-N and TP are I, II types of water on the earth surface basically, TN index is poor V type of water basically, and the using water quality index has no distinction degree. The Shannon-Wienner diversity index interval of plankton in midstream of the yellow river is kept between 3 and 4, and the diversity index interval does not have discrimination. The OTU index (namely the abundance of plankton species) of plankton is selected as an evaluation index of a reference point and a damaged point in comprehensive consideration, the points with the OTU total number being more than 90% quantile are reference points, and other sampling points are interference points greatly influenced by human beings. Wherein, the points less than 10% quantile are highly interfered sites, and the points between 10% quantile and 90% quantile are moderately interfered sites.

The number of taxon objects is the number of clustered OTUs. The number of the classification unit species of each section in this embodiment is shown in fig. 1.

The Shannon-Wiener diversity index equation is as follows:

in the formula, pi represents the proportion of individuals belonging to the ith species in the sample, for example, the total number of individuals in the sample is N, and the number of individuals of the ith species is N_iThen p is_i＝n_i/N。

Based on the above formula, the Shannon-Wiener diversity index of each section is shown in fig. 3.

The relative abundance ratio range of 100 genera in front of each sampling section is 96.6-99.7%, and the community characteristics of the plankton in the yellow river can be basically reflected. And (4) counting the ratio of the sequence number of the classification unit set with each section significantly and negatively correlated with ammonia nitrogen, total phosphorus, total nitrogen or permanganate index to the sum of the sequence numbers of all classification units, namely the relative abundance of the pollution sensitive species. And (4) counting the ratio of the sequence number of each section and the classification unit which is obviously and negatively related to the dissolved oxygen concentration of the water body to the sum of the sequence numbers of all the classification units, namely the anaerobic relative abundance.

The relative abundance of the contamination sensitive species and the anaerobic species for each section were calculated as shown in fig. 4.

Based on the 18S rDNA high-throughput sequencing result, the OTU with the sequence not being 0 in at least 50% of the sampling points is reserved, a species matrix table is obtained after the OTU is leveled by the minimum sequence number, and the OTU is processed on an http:// ieg4.rccc. ou. edu/website to obtain a node and edge attribute file. And (3) performing visualization of an ecological network by using Gephi software (specifically shown in FIG. 5). The modularity factor of the species network in the dominant microbial community related network in the yellow river is 0.535.

Here, it should be noted that, with reference to fig. 5, the essence of the species network modularization coefficient is to perform a species network module function analysis, specifically: it is generally accepted that microorganisms belonging to the same module are often involved in performing the same function. The proportions of module 1, module 2 and module 3 in fig. 5 are 22.22%, 19.81% and 21.74%, respectively, which indicates that more than 50% of plankton in the water ecosystem are concentrated to complete 3 community functions.

And quantitatively evaluating the health condition of the aquatic ecosystem of the midstream river reach of the yellow river by calculating P-IBI values of different sections of the midstream of the yellow river.

Substituting the obtained normalized score of the classification unit species number of each section, Shannon-wiener diversity index, pollution sensitive species relative abundance, anaerobic species relative abundance and species network modularization coefficient into the following formula to calculate the plankton integrity index (P-IBI) of each section_i)：

Wherein n is the total number of sampling points 26 corresponding to the fresh water ecosystem to be evaluated.

Calculating to obtain plankton integrity index (P-IBI) of each cross section of midstream of yellow river_i) As shown in fig. 6.

As can be seen from FIG. 6, the difference of health level is obvious in each section, P-IBI in JS5 section_iThe lowest value (0.5), the highest P-IBI values (0.83) for sections JS19, JS22 and JS23, the P-IBI values for each section_iThe average P-IBI was 0.69, indicating that the aquatic ecosystem health of the midstream river segment of the yellow river was overall at a "sub-healthy" level.

Example 2 (comparative example):

through years of research of experts in various countries, the establishment of the biological integrity index is mature on the basis of theoretical basis and technical methods. More and more researchers adopt IBI indexes to evaluate the health condition of a water ecosystem, and the wide application shows the feasibility of the method.

However, the inventor finds that the IBI index still has the following problems on a theoretical basis or on a construction method due to the complexity of the structure and the richness of functions of the water ecosystem:

1) there is no complete database of candidate biological condition parameter indicators: as a country with wide water areas, an instructive parameter index database for evaluating the integrity of the water ecosystem of China needs to be established according to geographical and hydrological characteristics, and a basic platform is provided for evaluating the health of the water ecosystem of each water area; 2) the screening of candidate biological condition parameter indicators is not mature enough: most researchers do not clearly indicate the reason for selecting the candidate indexes when constructing the IBI, and the selection indexes are greatly influenced by human subjective factors; 3) the establishment of the evaluation standard should be more scientific: a unified standard suitable for a specific type of water ecosystem can be worked out by combining a plurality of cases, and the health conditions of similar water ecosystems in different regions can be conveniently considered under the same standard, so that the water ecosystem is comparable.

To further demonstrate the advantages of the evaluation method provided in example 1 of the present invention, P-IBI was calculated below using a conventional evaluation method for comparison. The method comprises the following specific steps:

1) determining candidate biological condition parameter indexes in an index library according to population characteristics of a research area; 2) selecting a reference point and an interference point, collecting parameter index data, and establishing an evaluation index system through analysis of the distribution range of the parameter index values, judgment capability analysis (sensitivity analysis) and correlation analysis; 3) determining each parameter index value and a calculation method of the IBI index, and respectively calculating the IBI index values of the reference point and the interference point. According to the research examples of plankton integrity indexes at home and abroad, in combination with the characteristics of the midstream river reach of the yellow river, 33 candidate parameters are selected according to the above principles, a box plot method is selected to test the candidate parameters, the numerical values of the reference point and the damaged point are compared in the 25% to 75% quantile value distribution range, and the overlapping conditions of 'box body' IQ (Interquartile range) and four quantiles are compared, so that the biological parameters with strong identification capability are preliminarily screened out: namely IQ is more than or equal to 2, the boxes have no overlap or the boxes have a small overlap but the median is outside the other box. Obtaining the following through preliminary screening: the number of zooplankton species, the number of protozoan species, the relative abundance of ciliates (M13), the number of diatom species, the number of fungi species, the relative abundance of fungi, the diversity of phytoplankton, the uniformity of phytoplankton, the abundance of phytoplankton, the diversity of zooplankton, the uniformity of zooplankton, and the abundance of zooplankton are 12 candidate indexes. The distribution range of the single index of the damaged point is analyzed, and the relative abundance of the fungi which lack the discrimination is deleted. Performing Pearson correlation analysis on the 11 parameters meeting the conditions, as shown in Table 1; in order to select the appropriate biological parameters as much as possible into the evaluation system, it is provided that if the correlation coefficient between the two parameters is > 0.75, one of the two parameters is selected.

TABLE 1 correlation analysis of candidate parameters

The core biological parameters were screened according to the above method. And finally, selecting five parameter indexes of relative abundance of ciliates, algae variety number, fungus variety number, phytoplankton abundance and zooplankton diversity as core indexes to construct a plankton evaluation system. Calculating a P-IBI value by adopting a ratio method, then based on the characteristics of the midstream river reach of the yellow river, carrying out five-equal-part grade division on the plankton integrity index lower than the 95% quantile value by taking the 95% quantile value (4.822) of the P-IBI value of a reference point as an optimal value according to the standard calculation result of each index, namely dividing the health state of the water ecosystem of the midstream river reach of the yellow river into five grades of 'poor', 'normal', 'sub-health' and 'health'.

Fig. 7 is a graph showing comparison results of comparison of evaluation results of two different plankton integrity index methods (the evaluation method proposed by the present invention used in example 1, and the evaluation method in the prior art used in example 2) in the midstream of the yellow river in the example of the present invention. As can be seen from fig. 7, the plankton integrity indexes calculated by the two methods are significantly correlated, and the correlation coefficient is as high as 0.884. As can be seen from the figure, the health level of most sections is consistent, and the evaluation results of only three sections JS10, JS18 and JS25 differ by one grade, which shows that the plankton integrity evaluation method of the invention is suitable and the evaluation results are reliable.

In summary, the plankton integrity index (P-IBI) in example 1 according to the present invention can be well applied to the evaluation of the health status of the freshwater ecosystem.

Compared with the prior art, the method for evaluating the health of the fresh water ecosystem, provided by the embodiment of the invention, at least has the following advantages:

1. the evaluation method provided by the application firstly provides the relative abundance of anaerobic species and the species network modularization coefficient, takes the two indexes as the representative indexes for evaluating the integrity of the plankton, combines the representative indexes with the existing representative indexes, makes up the neglect of the water ecological function in the evaluation in the prior art, can comprehensively reflect the influence of environmental changes on the abundance, species diversity, pollution sensitivity, pollution tolerance and water ecological function of the plankton species, and improves the evaluation accuracy.

2. According to the evaluation method, the number of the classified unit species, the Shannon-Wienner diversity index, the relative abundance of pollution sensitive species, the relative abundance of anaerobic species and the species network modularization coefficient are taken as representative indexes of the integrity of the plankton, the index screening process of the integrity index of the plankton is simplified, the health condition of a fresh water ecosystem can be quickly, accurately and sensitively reflected, and a flow domain manager can be facilitated to implement accurate and effective treatment measures.

3. According to the evaluation method, the high-throughput sequencing analysis method is applied to the field of plankton, compared with a microscopic examination method (i.e. a method for analyzing organisms by using a microscope) in the prior art, the problems of high requirements on taxonomic identification experience, low accuracy caused by human errors and system errors, complex operation process, low efficiency and the like in the microscopic examination method can be perfectly solved, and the effects of no need of taxonomic identification experience, high accuracy, simple operation process and high efficiency are achieved.

4. Compared with the conventional screening parameter index method, the evaluation method provided by the invention has the advantage that the correlation obtained by evaluation can reach 0.8 in independent evaluation, so that the evaluation method provided by the invention has higher reliability.

In addition, in the evaluation method provided by the invention, the sampling points are selected based on a large-range water sample for sampling so as to improve the evaluation accuracy; and based on the consideration of water ecological function factors, species network modularization coefficients are introduced to comprehensively reflect the health state of the fresh water ecosystem, and the evaluation accuracy is further improved. Meanwhile, the inventor provides an evaluation index of the relative abundance of anaerobic species in the experimental process so as to accurately reflect the pollution tolerance of plankton, so that a scientific, accurate and artificial-error-free evaluation result can be obtained when the P-IBI value is calculated.

The applicant states that the present invention is illustrated by the detailed process flow of the present invention through the above examples, but the present invention is not limited to the above detailed process flow, that is, it does not mean that the present invention must rely on the above detailed process flow to be implemented. It will be understood by those skilled in the art that any simple modification, equivalent substitution of each raw material and addition of auxiliary components, selection of specific modes and the like, of the product of the present invention falls within the scope and disclosure of the present invention.

For simplicity of explanation, the method embodiments are described as a series of acts or combinations, but those skilled in the art will appreciate that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are preferred embodiments and that the acts and elements referred to are not necessarily required to practice the invention.

The method for evaluating the health of the fresh water ecosystem provided by the invention is described in detail, a specific example is applied in the method to explain the principle and the implementation mode of the invention, and the description of the example is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.