CN-121980288-A - Method and device for evaluating stability of water ecological environment based on community diversity

CN121980288ACN 121980288 ACN121980288 ACN 121980288ACN-121980288-A

Abstract

The invention discloses a community diversity-based water ecological environment stability evaluation method and device, and belongs to the technical field of water ecological environment monitoring and evaluation. The method comprises the steps of collecting environmental parameters and community data of a plurality of sampling points of a target water area, respectively calculating an environmental distance matrix and a community dissimilarity matrix among samples, constructing a prediction model which takes the environmental distance as an independent variable and the community dissimilarity as a dependent variable, calculating the expected community dissimilarity of the target sample by using the prediction model, comparing the expected community dissimilarity with an actual measurement value, and quantifying the ecological stability of the water area where the target sample is located according to the deviation of the environment distance matrix and the community dissimilarity matrix. The invention establishes objective association of environmental pressure and community response through a zero model based on a space substitution time theory, and solves the problems that the traditional stability evaluation is highly dependent on long time sequence monitoring data, has long evaluation period and is difficult to compare across points. The method is suitable for rapid evaluation under a single sampling scene, has objective evaluation results, and can be widely applied to ecological health evaluation and pollution early warning of water areas such as rivers, lakes, reservoirs and the like.

Inventors

LIN LI
GAO YU
PAN XIONG
DONG LEI
BAI FANG
LIN JIAXIN
YANG DONGYANG

Assignees

长江水利委员会长江科学院

Dates

Publication Date: 20260505
Application Date: 20260409

Claims (10)

1. The water ecological environment stability evaluation method based on community diversity is characterized by comprising the following steps of: S1, collecting environmental parameter data and community data of a plurality of sampling points in a target water area; S2, calculating an environmental distance matrix among samples according to the environmental parameter data; s3, calculating a community dissimilarity matrix among samples according to the community data; s4, constructing a prediction model by taking the environment distance matrix as an independent variable and the community dissimilarity matrix as a dependent variable, and calculating the expected community dissimilarity of the target sample by using the prediction model; s5, comparing the expected community dissimilarity with the actually observed community dissimilarity for the target sample, and quantifying the ecological stability of the water area where the target sample is located according to the comparison result.
2. The method according to claim 1, wherein the environmental parameter data comprises water temperature, pH value, dissolved oxygen, nutrient salt concentration, pollutant concentration, comprehensive water quality index, wherein the nutrient salt concentration comprises total nitrogen, total phosphorus, nitrate nitrogen, ammonia nitrogen and nitrite nitrogen, the pollutant concentration comprises various heavy metal concentration, organic matter concentration and new pollutant concentration, the comprehensive water quality index comprises Chemical Oxygen Demand (COD) and Biochemical Oxygen Demand (BOD), the community data comprises species relative abundance information, namely different species classifications and population sizes, the community data is obtained according to different characteristics of organisms, is obtained by microscopic counting screening and morphological identification methods for aquatic plankton and benthos, is obtained by sonar detection for fish, is obtained by environmental DNA, high throughput sequencing or macro-genome analysis for microorganisms in soil and sediment, and is obtained by an underwater in-situ imager and an algae artificial intelligence analyzer for phytoplankton.
3. The method of claim 1, wherein the computing of the environmental distance matrix comprises performing a normalization process on the environmental parameter data and computing the distance between samples using either Euclidean distance or Manhattan distance algorithms, wherein the normalization process comprises scaling to the [0,1] interval by Min-max normalization and using a logarithmic normalization computation, and wherein the computing of the community dissimilarity matrix comprises computing the community dissimilarity between samples based on an algorithm selected from the group consisting of Bray-Curtis dissimilarity, jaccard dissimilarity, spransen dissimilarity, and Unifrac dissimilarity.
4. The method of claim 1, wherein the step S4 of constructing a predictive model includes using at least one of a linear regression model, a generalized linear model, a generalized dissimilarity model, a random forest, or XGBoost to establish a quantitative relationship between environmental distance and community dissimilarity.
5. The method according to claim 1, wherein the step S5 specifically includes: Calculating the deviation between the expected community dissimilarity and the actually observed community dissimilarity based on the expected community dissimilarity of the target sample, wherein the expected community dissimilarity is an expected value, and the actually observed community dissimilarity is an actual measured value; determining an ecological stability quantized value according to the ratio of the deviation to the expected value, wherein the quantized value has a value range of [ -1, 1]; if the measured value is smaller than the expected value, the ecological stability of the water area is judged to be stronger; the measured value is obtained by calculating the average value of community dissimilarity between the sample and all other samples.
6. An apparatus for evaluating the stability of an ecological environment of water based on community diversity, characterized in that it is applied to the method of any one of claims 1 to 5, said apparatus comprising: the data acquisition module is used for acquiring environmental parameter data and community data of a plurality of sampling points in the target water area; The environment distance calculation module is used for calculating an environment distance matrix among the samples according to the environment parameter data; the community dissimilarity calculating module is used for calculating a community dissimilarity matrix among the samples according to community data; The model construction module is used for constructing a prediction model by taking the environment distance matrix as an independent variable and the community dissimilarity matrix as a dependent variable; The prediction module is used for calculating the expected community dissimilarity of the target sample by using the prediction model; and the stability quantifying module is used for comparing the expected community dissimilarity with the community dissimilarity actually observed for the target sample, and quantifying the ecological stability of the water area where the target sample is positioned according to the comparison result.
7. The apparatus of claim 6, wherein the environmental distance calculation module includes a normalization unit and a distance calculation unit for normalizing environmental parameter data and calculating an environmental distance between samples.
8. An apparatus according to claim 6, wherein the community dissimilarity calculation module calculates the community dissimilarity using at least one algorithm selected from the group consisting of Bray-Curtis dissimilarity, jaccard dissimilarity, branstensen dissimilarity and Unifrac dissimilarity.
9. The apparatus of claim 6, wherein the model building module uses at least one of a linear regression model, a generalized linear model, a generalized dissimilarity model, a random forest, or XGBoost to build a predictive model between environmental distance and community dissimilarity.
10. The apparatus of claim 6, wherein the stability quantization module is specifically configured to: Calculating the deviation between the expected community dissimilarity and the actually observed community dissimilarity based on the expected community dissimilarity of the target sample, wherein the expected community dissimilarity is an expected value, and the actually observed community dissimilarity is an actual measured value; determining an ecological stability quantized value according to the ratio of the deviation to the expected value, wherein the quantized value has a value range of [ -1, 1]; if the measured value is smaller than the expected value, the ecological stability of the water area is judged to be stronger; the measured value is obtained by calculating the average value of community dissimilarity between the sample and all other samples.

Description

Method and device for evaluating stability of water ecological environment based on community diversity Technical Field The invention relates to the technical field of water ecological environment monitoring and evaluation, in particular to a method and a device for evaluating the stability of water ecological environment based on community diversity, which are suitable for ecological health evaluation and pollution early warning of water areas such as rivers, lakes, reservoirs and the like. Background The water ecosystem is a core component of the maintenance earth life support system and is directly related to drinking water safety, biodiversity protection and climate regulation. Along with the acceleration of industrialization and urban process, the problems of water pollution, eutrophication, ecological environment fragmentation and the like are increasingly serious. The method for rapidly and accurately evaluating the ecological stability of the water is a key technical requirement for realizing the accurate treatment of the water area and promoting the construction of ecological civilization. At present, the water ecological stability quantification method is mainly divided into three types, namely an environmental parameter index method, a biomarker method and a community time sequence analysis method. (1) The environmental parameter index method takes WQI water quality index calculation as an example, relies on physicochemical indexes such as pH, dissolved oxygen and the like, but cannot reflect the response of a biological community to surrounding habitats. (2) The biomarker method, such as fish diversity investigation, requires long-term species investigation, has higher cost and poorer timeliness, and the obtained result can only reflect diversity change of the community of interest, and does not comprehensively consider the difference of habitat conditions. (3) The community time sequence analysis method can calculate the change of alpha diversity and beta diversity of the community through multiple sampling detection, so as to quantify the change of diversity on the time sequence and reflect the stability of different areas at different time points, but the emphasis is on the stability fluctuation condition of single points on a continuous time scale, and the stability difference between different sampling points cannot be directly compared, so that the stability difference between different sampling points cannot be surrounded in different spaces and different points, and a targeted environment protection and ecological restoration strategy is provided. The method is characterized in that (1) the stability is deduced through the spatial heterogeneity of community environmental conditions, for example, the hypothesis of using space to replace time in ecology is adopted, and (2) the objective analysis of the fixed flow is carried out on the relation between the environmental pressure and the community structure response, so that subjective threshold setting is avoided. Based on ecological definition, the concept of communities includes populations of different species and each individual therein, and is therefore suitable as a subject of stress in the reaction environment. When the environmental pressure exceeds the fluctuation threshold value which can be borne by the system, the community structure deviates from the structure corresponding to the current environment, namely, the expected value. Therefore, the invention simulates community distance differences caused by differences of different environmental factors by constructing a community structure zero model corresponding to environmental conditions, and calculates the deviation between the actually observed community diversity and the predicted value to be used as a quantification method of stability. The water ecological stability evaluation method which integrates the environmental parameters and the communities and only needs single sampling is developed, has great application value for realizing the rapid analysis of the water environment ecological stability, and can also provide a standardized tool for the ecological restoration engineering effect evaluation. Disclosure of Invention The invention aims to make up the defects of the current water ecological environment stability evaluation technology, and provides a water environment ecological stability evaluation method and device based on zero model comparison based on the diversity of community composition structures, so as to solve the dependence on time sequences in the traditional method and avoid the deviation introduced by subjectivity of threshold setting. A water ecological environment stability evaluation method based on community diversity comprises the following steps: S1, collecting environmental parameter data and community data of a plurality of sampling points in a target water area; S2, calculating an environmental distance matrix among samples according to the env