Ecological evaluation method based on specific species of community

Abstract

The invention relates to the technical field of ecology, in particular to an ecological evaluation method based on community specific species, which comprises the following steps: S1, evaluating phytoplankton ecological indexes by selecting an evaluation criterion, and standardizing the phytoplankton ecological indexes; s2, on the basis of the ecological index SEI of the phytoplankton, determining the change amplitude grade of the ecological condition of the phytoplankton; and S3, establishing a standard for grading the ecological indexes of the phytoplankton on the basis of verification and analysis of historical monitoring data. The phytoplankton has high sensitivity to environmental change, the change of the community structure and number of the phytoplankton can quickly reflect the change of the water body environment, the water body pollution problem can be found in time by regularly monitoring the change condition of the phytoplankton, early warning can be given out, and the ecological evaluation method based on the phytoplankton is provided for related departments. The health condition of the water ecosystem can be comprehensively and systematically evaluated, and a scientific basis is provided for protection and management of water resources.

Description

Technical Field

[0001] The present invention relates to the technical field of ecology, and in particular to an ecological evaluation method based on specific species in a community. Background Art

[0002] Phytoplankton, also known as floating algae, is an important component of the aquatic ecosystem. They grow in the water, have chlorophyll and are able to live an autotrophic life. Phytoplankton do not have differentiation of roots, stems, and leaves, and their reproduction mainly relies on the nutritional division of cells, or through single-cell spores and zygotes. As primary producers in aquatic ecosystems, phytoplankton plays a vital role in maintaining the ecological balance of water bodies and providing the basis of the food chain.

[0003] At present, the ecological evaluation of phytoplankton communities mainly relies on the monitoring of phytoplankton species, quantity and distribution in water bodies. However, with the acceleration of industrialization and urbanization, water pollution problems are becoming increasingly serious, especially the phenomenon of excess nutrients and chemical pollution, which poses severe challenges to the stability and sustainability of aquatic ecosystems. Existing phytoplankton ecological evaluation methods mainly focus on the following aspects.

[0004] Single indicator monitoring: Existing technologies often use a single water quality indicator (such as nitrogen and phosphorus concentrations) as a reference for phytoplankton growth and distribution. This method fails to fully consider the diversity within the phytoplankton community and the interactions between species, resulting in a one-sided evaluation result and a lack of comprehensive understanding of the ecological health of the water body.

[0005] Traditional water quality monitoring methods: Traditional phytoplankton monitoring methods usually rely on manual sampling and microscopic observation. Although they can provide certain water quality information, the data acquisition cycle is long and the operation is complicated, resulting in limited real-time monitoring and dynamic evaluation capabilities.

[0006] Slow response to pollution: Traditional assessment methods are often unable to reflect the ecological changes caused by water pollution in real time and sensitively when responding to pollution changes. Changes in the types and numbers of phytoplankton may have a lag, so it is impossible to respond quickly to short-term pollution events.

[0007] Ignoring the role of specific species in phytoplankton communities: In existing technologies, most methods fail to fully consider the importance of certain specific species in phytoplankton communities in ecological assessment. Certain phytoplankton species are highly sensitive to environmental changes, and changes in their number and species can significantly reflect the ecological status of water bodies, but the role of these specific species has not been effectively highlighted in existing technologies.

[0008] Therefore, existing technologies have some obvious deficiencies in the ecological assessment of phytoplankton communities, especially in dynamic monitoring, species-specific analysis and pollution response, and there is still much room for improvement.

[0009] This paper innovatively combines the sensitivity of different species in the phytoplankton community to changes in the water ecological environment through an ecological evaluation method based on specific species in the community, and proposes an evaluation system that can reflect the health status of the water body in real time. This method not only solves the limitations of traditional single indicator monitoring, but also can quickly and accurately evaluate the stability and health status of the water ecosystem for different pollution situations, providing more scientific and efficient decision-making support for water quality protection and ecological governance. Summary of the invention

[0010] The main purpose of the present invention is to provide an ecological evaluation method based on specific species in a community to solve the problems raised in the related art.

[0011] In order to achieve the above object, according to one aspect of the present invention, an ecological evaluation method based on specific species in a community is provided, comprising the following steps.

[0012] S1: Evaluate the phytoplankton ecological indicators by selecting evaluation criteria and standardize the phytoplankton ecological indicators.

[0013] S2: Based on the SEI, the ecological index of phytoplankton, determine the level of change in the ecological status of phytoplankton.

[0014] S3: Establish standards for the classification of phytoplankton ecological indicators based on the verification and analysis of historical monitoring data.

[0015] Furthermore, the evaluation criteria in S1 are as follows: ≥80% is good, 60%≤~<80% is fair, and <60% is poor.

[0016] Furthermore, the steps for standardizing the phytoplankton ecological indicators in S1 are as follows.

[0017] S1.1: Collect data on various ecological indicators of phytoplankton species diversity, biomass, and chlorophyll content, and clean the data to ensure its accuracy and completeness.

[0018] S1.2: Select the Z-score standardization method based on the data distribution characteristics and evaluation requirements.

[0019] S1.3: Apply the selected Z-score normalization method to process the data to convert the raw data into pure dimensionless values.

[0020] Furthermore, the specific formula of the Z-score standardization method is: .

[0021] Among them, Z is the standardized value, x is an observation in the original data, μ is the mean of the original data, and σ is the standard deviation of the original data.

[0022] Furthermore, the specific steps of determining the grading of the range of change in the ecological status of phytoplankton based on the SEI of the phytoplankton in S2 are as follows.

[0023] S2.1: Collect ecological indicator data such as species composition, biomass, chlorophyll content, etc. of phytoplankton within a certain time range, and clean and preprocess the data to ensure data quality.

[0024] S2.2: Calculate the SEI value of phytoplankton from the collected data.

[0025] S2.3: Determine the classification criteria.

[0026] S2.4: Analyze the changing trends of phytoplankton ecological status through time series analysis methods.

[0027] S2.5: According to the change range of SEI value, the change of phytoplankton ecological status is determined into different levels.

[0028] Furthermore, the specific formula of the SEI value of phytoplankton in S2.2 is: .

[0029] Among them, H' is the Shannon-Wiener diversity index, which is calculated as follows: .

[0030] Where Σ represents the sum, pi is the ratio of the number of individuals of the i-th species to the total number of individuals, ln is the natural logarithm, and S is the total number of species in the phytoplankton community.

[0031] Furthermore, the classification standard in S2.3 is as follows: =≤n1 means no significant change, n1< ≤n2 means slight change, n2< ≤n3 is a significant change, >n3 indicates significant changes.

[0032] Furthermore, the specific steps of analyzing the changing trend of the phytoplankton ecological status by the time series analysis method in S2.4 are as follows.

[0033] S2.4.1: Clean and organize SEI data, handle missing values, outliers, or duplicate values, and use line graphs to visualize SEI data changes over time and preliminarily observe its trends.

[0034] S2.4.2: Use the moving average method in time series analysis to fit and predict the SEI data. Based on the fitting results, observe the trend of SEI values ​​over time to determine whether it is rising, falling, or remaining stable.

[0035] Furthermore, the specific steps of level division in S3 are as follows.

[0036] S3.1: Collect a large amount of historical monitoring data on the characteristics of different water environments and phytoplankton communities, and pre-process and clean the collected historical monitoring data.

[0037] S3.2: Analyze the preprocessed data to identify the key factors affecting phytoplankton communities.

[0038] S3.3: Determine the basic principles for the classification of phytoplankton ecological indicators.

[0039] S3.4: According to the determined classification principles, phytoplankton ecological indicators are divided into different levels.

[0040] S3.5: Verify the accuracy of the classification through actual monitoring data to ensure that the classification can truly reflect the ecological status of the phytoplankton community.

[0041] Furthermore, the specific principles of the grading are as follows: ≥75~100 indicates good ecological conditions, ≥50~<75 indicates fair ecological conditions, and 0~<50 indicates poor ecological conditions.

[0042] Compared with the prior art, the present invention has the following beneficial effects: phytoplankton is highly sensitive to environmental changes, and changes in its community structure and quantity can quickly reflect changes in the water environment. By regularly monitoring changes in phytoplankton, water pollution problems can be discovered in a timely manner and early warnings can be issued. Through an ecological evaluation method based on phytoplankton, relevant departments can comprehensively and systematically assess the health status of water ecosystems, provide a scientific basis for the protection and management of water resources, and provide strong support for taking countermeasures. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The method flow chart of the preferred embodiment is shown in FIG. DETAILED DESCRIPTION

[0044] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0045] Reference Figure 1The present invention provides an ecological evaluation method based on specific species in a community, comprising the following steps.

[0046] S1: Evaluate the phytoplankton ecological indicators by selecting evaluation criteria and standardize the phytoplankton ecological indicators.

[0047] S2: Based on the SEI, the ecological index of phytoplankton, determine the level of change in the ecological status of phytoplankton.

[0048] S3: Establish standards for the classification of phytoplankton ecological indicators based on the verification and analysis of historical monitoring data.

[0049] The specific evaluation criteria in S1 are: ≥80% is good, 60%≤~<80% is fair, and <60% is poor.

[0050] The steps for standardizing phytoplankton ecological indicators in S1 are as follows.

[0051] S1.1: Collect data on various ecological indicators of phytoplankton species diversity, biomass, and chlorophyll content, and clean the data to ensure its accuracy and completeness.

[0052] S1.2: Select the Z-score standardization method based on the data distribution characteristics and evaluation requirements.

[0053] S1.3: Apply the selected Z-score normalization method to process the data to convert the raw data into pure dimensionless values.

[0054] The specific formula of the Z-score standardization method is: .

[0055] Among them, Z is the standardized value, x is an observation in the original data, μ is the mean of the original data, and σ is the standard deviation of the original data.

[0056] The specific steps for determining the grading of the magnitude of changes in the ecological status of phytoplankton based on the SEI of the phytoplankton in S2 are as follows.

[0057] S2.1: Collect ecological indicator data such as species composition, biomass, chlorophyll content, etc. of phytoplankton within a certain time range, and clean and preprocess the data to ensure data quality.

[0058] S2.2: Calculate the SEI value of phytoplankton from the collected data.

[0059] S2.3: Determine the classification criteria.

[0060] S2.4: Analyze the changing trends of phytoplankton ecological status through time series analysis methods.

[0061] S2.5: According to the change range of SEI value, the change of phytoplankton ecological status is determined into different levels.

[0062] The specific formula for the SEI value of phytoplankton in S2.2 is: .

[0063] Among them, H' is the Shannon-Wiener diversity index, which is calculated as follows: .

[0064] Where Σ represents the sum, pi is the ratio of the number of individuals of the i-th species to the total number of individuals, ln is the natural logarithm, and S is the total number of species in the phytoplankton community.

[0065] The specific classification standards in S2.3 are: =≤n1 means no significant change, n1< ≤n2 means slight change, n2< ≤n3 is a significant change, >n3 indicates significant changes.

[0066] The specific steps for analyzing the changing trend of phytoplankton ecological status by time series analysis method in S2.4 are as follows.

[0067] S2.4.1: Clean and organize SEI data, handle missing values, outliers, or duplicate values, and use line graphs to visualize SEI data changes over time and preliminarily observe its trends.

[0068] S2.4.2: Use the moving average method in time series analysis to fit and predict the SEI data. Based on the fitting results, observe the trend of SEI values ​​over time to determine whether it is rising, falling, or remaining stable.

[0069] The specific steps of level division in S3 are as follows.

[0070] S3.1: Collect a large amount of historical monitoring data on the characteristics of different water environments and phytoplankton communities, and pre-process and clean the collected historical monitoring data.

[0071] S3.2: Analyze the preprocessed data to identify the key factors affecting phytoplankton communities.

[0072] S3.3: Determine the basic principles for the classification of phytoplankton ecological indicators.

[0073] S3.4: According to the determined classification principles, phytoplankton ecological indicators are divided into different levels.

[0074] S3.5: Verify the accuracy of the classification through actual monitoring data to ensure that the classification can truly reflect the ecological status of the phytoplankton community.

[0075] The specific principles for grading are: ≥75~100 means good ecological conditions, ≥50~<75 means fair ecological conditions, and 0~<50 means poor ecological conditions.

[0076] In this embodiment, the ecological evaluation method based on community-specific species is as follows: First, the phytoplankton ecological indicators are evaluated by selecting an evaluation benchmark, and the phytoplankton ecological indicators are standardized; the evaluation benchmark is specifically: ≥80% is good, 60%≤~<80% is general, and <60% is poor. The steps of standardization are as follows: S1.1: Collect various ecological indicator data of phytoplankton species diversity, biomass, and chlorophyll content, and clean the data to ensure the accuracy and completeness of the data; data cleaning includes removing outliers, duplicate values ​​or missing values, and performing necessary conversions or interpolations. S1.2: According to the distribution characteristics of the data and the evaluation requirements, select the Z-score standardization method; the Z-score standardization method is a commonly used data standardization processing technology, which can convert the original data into a dimensionless value with a mean of 0 and a standard deviation of 1, thereby eliminating the dimension differences between different indicators, so that the data can be directly compared and analyzed. S1.3: Apply the selected Z-score standardization method to process the data, thereby converting the original data into a dimensionless pure value. The specific formula of the Z-score standardization method is: .

[0077] Among them, Z is the standardized value, x is an observation in the original data, μ is the mean of the original data, and σ is the standard deviation of the original data. Based on the SEI, the ecological index of phytoplankton, the grading of the change range of the ecological status of phytoplankton is determined; the specific steps for grading the change range of the ecological status of phytoplankton are: S2.1: Collect ecological indicator data such as species composition, biomass, chlorophyll content, etc. of phytoplankton within a certain time range, and clean and pre-process the data to ensure data quality; including the processing of outliers, standardization or normalization of data, etc. S2.2: Calculate the SEI value of phytoplankton based on the collected data; S2.3: Determine the grading standard; the specific grading standard is: =≤n1 means no obvious change, n1< ≤n2 means slight change, n2< ≤n3 is a significant change, >n3 is a significant change. S2.4: Analyze the changing trend of phytoplankton ecological conditions through time series analysis methods; the specific steps are: S2.4.1: Clean and organize SEI data, handle missing values, outliers or duplicate values, use line charts to visualize the changes of SEI data over time, and preliminarily observe its trend. S2.4.2: Use the moving average method in the time series analysis method to fit and predict the SEI data. According to the fitting results, observe the changing trend of SEI values ​​over time to determine whether it is rising, falling or stable. S2.5: According to the amplitude of change of SEI values, the changes in phytoplankton ecological conditions are determined to different levels. The specific formula for SEI value is: .

[0078] Among them, H' is the Shannon-Wiener diversity index, which is calculated as follows: .

[0079] Among them, Σ represents summation, pi is the proportion of the number of individuals of the i-th species to the total number of individuals, ln is the natural logarithm, and S is the total number of species in the phytoplankton community. Then, the standard for the grading of phytoplankton ecological indicators is established based on the verification and analysis of historical monitoring data. The specific steps of grading are: S3.1: Collect a large amount of historical monitoring data on the characteristics of different water environments and phytoplankton communities, and preprocess and clean the collected historical monitoring data; the data comes from long-term environmental monitoring projects, scientific research experiments or public databases. Preprocessing and cleaning include eliminating outliers, missing values ​​or erroneous data to ensure the quality and consistency of the data. S3.2: Analyze the preprocessed data to find out the key factors affecting the phytoplankton community; the key factors include temperature, pH value, nutrient concentration, etc. S3.3: Determine the basic principles for the grading of phytoplankton ecological indicators; the specific principles of grading are: ≥75~100 means good ecological conditions, ≥50~<75 means general ecological conditions, and 0~<50 means poor ecological conditions. S3.4: Classify phytoplankton ecological indicators into different levels according to the determined classification principles; S3.5: Verify the accuracy of the classification through actual monitoring data to ensure that the classification can truly reflect the ecological status of the phytoplankton community.

[0080] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. An ecological assessment method based on specific species in a community, characterized in that: The steps include: S1: Evaluate phytoplankton ecological indicators by selecting evaluation criteria and standardize phytoplankton ecological indicators; S2: Based on the SEI, the ecological index of phytoplankton, the grading of the change range of the ecological status of phytoplankton is determined; S3: Establish standards for the classification of phytoplankton ecological indicators based on the verification and analysis of historical monitoring data.

2. The ecological assessment method based on specific species in a community according to claim 1, characterized in that: The evaluation criteria in S1 are as follows: ≥80% is good, 60%≤~<80% is fair, and <60% is poor.

3. The ecological assessment method based on specific species in a community according to claim 2, characterized in that: The steps of standardizing the phytoplankton ecological indicators in S1 are as follows: S1.1: Collect data on various ecological indicators of phytoplankton species diversity, biomass, and chlorophyll content, and clean the data to ensure its accuracy and completeness; S1.2: Select the Z-score standardization method based on the data distribution characteristics and evaluation requirements; S1.3: Apply the selected Z-score normalization method to process the data to convert the raw data into pure dimensionless values.

4. The ecological assessment method based on specific species in a community according to claim 3, characterized in that: The specific formula of the Z-score standardization method is: Among them, Z is the standardized value, x is an observation in the original data, μ is the mean of the original data, and σ is the standard deviation of the original data.

5. The ecological assessment method based on specific species in a community according to claim 1, characterized in that: The specific steps of determining the grading of the ecological status change range of phytoplankton based on the phytoplankton ecological index SEI in S2 are: S2.1: Collect ecological indicator data such as species composition, biomass, chlorophyll content, etc. of phytoplankton within a certain time range, and clean and pre-process the data to ensure data quality; S2.2: Calculate the SEI value of phytoplankton from the collected data; S2.3: Determine the classification criteria; S2.4: Analyze the changing trend of phytoplankton ecological status by time series analysis method; S2.5: According to the change range of SEI value, the change of phytoplankton ecological status is determined into different levels.

6. The ecological assessment method based on specific species in a community according to claim 5, characterized in that: The specific formula for the SEI value of phytoplankton in S2.2 is: Among them, H' is the Shannon-Wiener diversity index, which is calculated as follows: Where Σ represents the sum, pi is the ratio of the number of individuals of the i-th species to the total number of individuals, ln is the natural logarithm, and S is the total number of species in the phytoplankton community.

7. The ecological assessment method based on specific species in a community according to claim 6, characterized in that: The specific classification standards in S2.3 are: =≤n1 means no significant change, n1< ≤n2 means slight change, n2< ≤n3 is a significant change, >n3 indicates significant changes.

8. The ecological assessment method based on specific species in a community according to claim 7, characterized in that: The specific steps of analyzing the changing trend of phytoplankton ecological status by time series analysis method in S2.4 are: S2.4.1: Clean and organize SEI data, handle missing values, outliers, or duplicate values, use line graphs to visualize SEI data changes over time, and preliminarily observe its trend; S2.4.2: Use the moving average method in time series analysis to fit and predict the SEI data. Based on the fitting results, observe the trend of SEI values ​​over time to determine whether it is rising, falling, or remaining stable.

9. The ecological assessment method based on specific species in a community according to claim 1, characterized in that: The specific steps of the level division in S3 are: S3.1: Collect a large amount of historical monitoring data on the characteristics of different water environments and phytoplankton communities, and pre-process and clean the collected historical monitoring data; S3.2: Analyze the preprocessed data to identify the key factors affecting phytoplankton communities; S3.3: Determine the basic principles for the classification of phytoplankton ecological indicators; S3.4: Classify phytoplankton ecological indicators into different levels according to the determined classification principles; S3.5: Verify the accuracy of the classification through actual monitoring data to ensure that the classification can truly reflect the ecological status of the phytoplankton community.

10. The ecological assessment method based on specific species in a community according to claim 9, characterized in that: The specific principles for the grading are: ≥75~100 means good ecological conditions, ≥50~<75 means fair ecological conditions, and 0~<50 means poor ecological conditions.

Images