Method for evaluating the living environment of filter-feeding benthic animals and application thereof

Abstract

This invention relates to a method for assessing the habitat of filter-feeding benthic animals and its application, belonging to the field of aquatic ecological environment assessment technology. This invention provides a method for assessing the habitat of filter-feeding benthic animals, comprising the following steps: (1) measuring water body indicators, processing the data to obtain water body physicochemical indicator data W1, sediment environment indicator data W2, food resource indicator data W3, and biological behavior adaptation indicator data W4; (2) calculating the habitat suitability index SEI; (3) assessing whether small water bodies are suitable for the survival of filter-feeding benthic animals based on the habitat suitability index. This invention is highly targeted, comprehensive in its indicators, precise in its quantification, and widely applicable. It can be used for habitat suitability assessment, ecological restoration effect monitoring, and artificial rearing area selection, etc., and has high application value and is easy to promote and implement.

Description

Technical Field

[0001] This invention relates to the field of aquatic ecological environment assessment technology, and in particular to an assessment method for the living environment of filter-feeding benthic animals and its application. Background Technology

[0002] Filter-feeding benthic animals are an important component of aquatic ecosystems. By filtering pollutants such as phytoplankton and organic debris from water, they participate in the water cycle and purification process. Their survival status directly reflects the quality of the aquatic environment, making them important indicator organisms of aquatic ecological health. In recent years, the application of filter-feeding benthic animals in the ecological remediation of water pollution has become increasingly widespread. However, current methods for assessing the habitats of filter-feeding benthic animals still have significant shortcomings.

[0003] Existing methods for assessing benthic habitats primarily focus on evaluating the overall habitat diversity of benthic organisms, failing to design specific assessment indicator systems tailored to the unique physiological characteristics of filter-feeding benthic animals (filter feeding methods, habitat habits, and environmental adaptability). This results in a lack of specificity in assessments and the inappropriate selection of indicators. The survival of filter-feeding benthic animals depends on suitable aquatic physicochemical environments, substrate conditions, and food resources. Their feeding efficiency is also affected by the spatial distribution among individuals; close proximity can lead to interference with water flow, reducing nutrient intake efficiency. However, existing assessment methods do not consider the environmental adaptation requirements arising from these organisms' own behaviors.

[0004] Meanwhile, existing methods lack quantitative standards in the assessment process, relying mostly on qualitative descriptions. This makes it difficult to accurately classify the suitability of the habitat, and fails to provide scientific and operational technical support for the artificial rearing, habitat optimization, and ecological remediation of water pollution for filter-feeding benthic animals. Therefore, developing a targeted, comprehensive, quantitatively accurate method for assessing the habitat of filter-feeding benthic animals that takes into account seasonal dynamics and biological behavioral characteristics has become an urgent technical problem to be solved in the field of aquatic ecological environment assessment.

[0005] Based on this, the present invention is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide a method for assessing the habitat of filter-feeding benthic animals and its application, so as to solve the problem of limitations in existing methods for assessing the habitat of filter-feeding benthic animals.

[0007] To achieve the above-mentioned objectives, the present invention provides the following technical solution: This invention provides a method for assessing the habitat of filter-feeding benthic animals, comprising the following steps: (1) Collect and measure water body physicochemical indicators, bottom sediment environmental indicators, food resource indicators and biological behavior adaptation indicators of water samples, process the data, and obtain water body physicochemical indicator data W1, bottom sediment environmental indicator data W2, food resource indicator data W3 and biological behavior adaptation indicator data W4 respectively. (2) The survival environment suitability index (SEI) is calculated based on the water body physicochemical index data W1, the bottom sediment environment index data W2, the food resource index data W3, and the biological behavior adaptation index data W4. (3) Assess whether small water bodies are suitable for filter-feeding benthic animals based on the environmental suitability index.

[0008] Preferably, the water area to be measured in step (1) includes one of lakes, rivers, reservoirs and artificial wetlands.

[0009] Preferably, the formula for data processing in step (1) is: X'=(X-Xmin) / (Xmax-Xmin); In the formula, X' is the standardized index value, X is the average value of the index measurement, Xmin is the minimum value of the index measurement, and Xmax is the maximum value of the index measurement.

[0010] Preferably, the measurement data of the water body physicochemical indicators in step (1) include dissolved oxygen DO, pH, water temperature T, conductivity EC, total nitrogen TN, total phosphorus TP and chemical oxygen demand COD; The formula for calculating the water body physicochemical index data W1 is as follows: W1 = 0.08 × DO value + 0.06 × pH value + 0.05 × T value + 0.04 × EC value + 0.05 × TN value + 0.03 × TP value + 0.02 × COD value.

[0011] Preferably, the measurement data of the sediment environmental indicators in step (1) include sediment particle size D, sediment organic carbon content SCO, and sediment porosity. ; The formula for calculating the sediment environmental index data W2 is as follows: W2 = 0.08 × D value + 0.09 × SCO value + 0.08 × value.

[0012] Preferably, the measurement data of the food resource indicators in step (1) include phytoplankton biomass Chl-a and organic detritus content OC; The formula for calculating the food resource index data W3 is as follows: W3 = 0.13 × Chl-a value + 0.12 × OC value.

[0013] Preferably, the measurement data of the biological behavior adaptation index in step (1) includes the average distance M between filter-feeding benthic animals and the population density P; The formula for calculating the biological behavior adaptation index W4 is as follows: W4 = 0.8 × M value + 0.04 × P value.

[0014] Preferably, the formula for calculating the Environmental Suitability Index (SEI) in step (2) is as follows: SEI = W1 + W2 + W3 + W4.

[0015] Preferably, the evaluation method described in step (3) is as follows: a. When the environmental suitability index is greater than or equal to 0.6 and less than or equal to 1.0, it is suitable for filter-feeding benthic animals to survive; b. When the environmental suitability index is less than 0.6, it is not suitable for filter-feeding benthic animals to survive, and the living environment needs to be improved.

[0016] This invention provides the application of the aforementioned assessment method in methods for improving water pollution.

[0017] The present invention has the following technical effects and advantages: 1. Highly targeted: This invention is specifically designed to evaluate the physiological characteristics, feeding methods and habitat habits of filter-feeding benthic animals. It adds biological behavior adaptation indicators (inter-individual spacing and population density), fully considers the impact of spatial distribution among filter-feeding benthic animals on feeding efficiency, solves the problem of insufficient targeting of existing methods, and the evaluation results are more in line with the survival needs of filter-feeding benthic animals. 2. Comprehensive indicators: Covering four major categories of indicators: water physicochemical properties, sediment environment, food resources, and biological behavior adaptation, comprehensively covering the core influencing factors on the survival of filter-feeding benthic animals, avoiding the one-sidedness of single-indicator assessment, and improving the comprehensiveness and accuracy of the assessment. 3. Precise Quantification: The Analytic Hierarchy Process (AHP) is used to determine the weights of the indicators, and the suitability index is calculated by combining the weighted summation method. Clear grading standards are established, transforming qualitative assessment into quantitative assessment, avoiding errors in subjective judgment, and making the assessment results more scientific and operable. 4. Wide range of applications: It is applicable to the assessment of the living environment of filter-feeding benthic animals in various water bodies (lakes, rivers, reservoirs, artificial wetlands, etc.). It can be used for habitat suitability assessment, monitoring of ecological restoration effects, screening of artificial breeding areas, etc. It has high application value and is easy to promote and implement. Attached Figure Description

[0018] Figure 1 This is a flowchart of the evaluation method. Detailed Implementation

[0019] This invention provides a method for assessing the habitat of filter-feeding benthic animals, comprising the following steps: (1) Collect and measure water samples of water body physicochemical indicators, bottom sediment environmental indicators, food resource indicators and biological behavior adaptation indicators, process the data to obtain water body physicochemical indicator data W1, bottom sediment environmental indicator data W2, food resource indicator data W3 and biological behavior adaptation indicator data W4 respectively. (2) The survival environment suitability index (SEI) is calculated based on the water body physicochemical index data W1, the bottom sediment environment index data W2, the food resource index data W3, and the biological behavior adaptation index data W4. (3) Assess whether small water bodies are suitable for filter-feeding benthic animals based on the environmental suitability index.

[0020] In this invention, the water area to be measured in step (1) includes one of lakes, rivers, reservoirs and artificial wetlands.

[0021] Preferably, the formula for data processing in step (1) is: X'=(X-Xmin) / (Xmax-Xmin); In the formula, X' is the standardized index value, X is the average value of the index measurement, Xmin is the minimum value of the index measurement, and Xmax is the maximum value of the index measurement.

[0022] In this invention, the measurement data of the water body physicochemical indicators in step (1) include dissolved oxygen DO, pH, water temperature T, conductivity EC, total nitrogen TN, total phosphorus TP and chemical oxygen demand COD; The formula for calculating the water body physicochemical index data W1 is as follows: W1 = 0.08 × DO value + 0.06 × pH value + 0.05 × T value + 0.04 × EC value + 0.05 × TN value + 0.03 × TP value + 0.02 × COD value.

[0023] In this invention, the measurement data of the sediment environmental indicators in step (1) include sediment particle size D, sediment organic carbon content SCO, and sediment porosity. ; The formula for calculating the sediment environmental index data W2 is as follows: W2 = 0.08 × D value + 0.09 × SCO value + 0.08 × value.

[0024] In this invention, the measurement data of the food resource indicators in step (1) include phytoplankton biomass Chl-a and organic detritus content OC; The formula for calculating the food resource index data W3 is as follows: W3 = 0.13 × Chl-a value + 0.12 × OC value.

[0025] In this invention, the measurement data of the biological behavior adaptation index in step (1) includes the average distance M between filter-feeding benthic animals and the population density P; The formula for calculating the biological behavior adaptation index W4 is as follows: W4 = 0.8 × M value + 0.04 × P value.

[0026] In this invention, the formula for calculating the Survival Environment Suitability Index (SEI) in step (2) is as follows: SEI = W1 + W2 + W3 + W4.

[0027] In this invention, the evaluation method described in step (3) is as follows: a. When the environmental suitability index is greater than or equal to 0.6 and less than or equal to 1.0, the environment is suitable for filter-feeding benthic animals. b. When the environmental suitability index is less than 0.6, it is not suitable for filter-feeding benthic animals to survive, and the living environment needs to be improved.

[0028] This invention provides the application of the aforementioned assessment method in methods for improving water pollution.

[0029] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0030] The evaluation process for this application is as follows: Figure 1 As shown.

[0031] Example 1

[0032] Taking a scenic waterway in a city as the evaluation object, the specific steps are as follows: (1) Physicochemical indicators of water body: Dissolved oxygen (DO) (mg / L), pH, water temperature (T) (°C) and conductivity (EC) (μS / cm) were measured at 30 random locations in the river using a portable water quality monitor. The average value was taken. Then, 10 mL water samples were taken from 3 random locations in the river. After mixing, the total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) were measured according to the methods specified in "Determination of Total Nitrogen in Water by Alkaline Potassium Persulfate Digestion Ultraviolet Spectrophotometry" (HJ636-2012), "Determination of Total Phosphorus in Water by Ammonium Molybdate Spectrophotometry" (GB11893-89) and "Determination of Chemical Oxygen Demand in Water by Dichromate Method" (HJ828-2017). Ten sets of data were measured for each indicator and the average value was taken.

[0033] Substrate environmental indicators: Nine samples (10g each) of surface geological material from the riverbed were collected, mixed, and the particle size D (mm) of the substrate was determined using a laser particle size analyzer. The organic carbon content SCO (%) of the substrate was determined according to the method specified in "Determination of Soil Organic Carbon by Potassium Dichromate Oxidation-Spectrophotometry" (HJ615-2011). The porosity of the substrate was determined using a fully automated mercury porosimeter. (%), each indicator was measured 10 times and the average value was taken.

[0034] Food resource indicators: 10 mL water samples were taken from 3 random locations in the river, mixed and concentrated by centrifugation, and the phytoplankton biomass Chl-a (μg / L) was determined according to the method specified in "Determination of Chlorophyll a in Water Quality by Spectrophotometry" (HJ897-2017). The organic debris content OC (mg / L) was determined by drying method. Each indicator was measured 10 times and the average value was taken.

[0035] Biological behavior adaptation indicators: Three areas (0.5m × 0.5m) were randomly selected in the river channel. Snails and freshwater mussels were collected using a Sober net. The sample size was recorded, and the population density P (individuals / m²) was calculated. 2 Meanwhile, three areas were randomly selected for underwater observation and measurement of the distance between snails and freshwater mussels. The average value was taken to obtain the average distance M (cm) between filter-feeding benthic animals. Each indicator was measured 10 times and the average value was taken.

[0036] Outliers were removed using the 3σ principle, missing data were supplemented using linear interpolation, and all indicator data were standardized using the min-max standardization method to eliminate the influence of units. The specific methods are as follows: X'=(X-Xmin) / (Xmax-Xmin) Where X' is the standardized indicator value, X is the indicator average, Xmin is the minimum value of the indicator, and Xmax is the maximum value of the indicator.

[0037] The data processing results for water body physicochemical indicators, sediment environment indicators, food resource indicators, and biological behavior adaptation indicators are shown in Tables 1 to 4.

[0038] Table 1. Data processing results of water body physicochemical indicators

[0039] Table 2. Data processing results of sediment environmental indicators

[0040] Table 3. Data processing results for food resource indicators

[0041] Table 4. Data processing results of biological behavioral adaptation indicators

[0042] The Analytic Hierarchy Process (AHP) was used to determine the weights of each measured indicator among the water body physicochemical indicators, sediment environment indicators, food resource indicators, and biological behavior adaptation indicators. A judgment matrix was constructed and a consistency test was performed (CR < 0.1, test passed). The final weights of each measured indicator among the water body physicochemical indicators, sediment environment indicators, food resource indicators, and biological behavior adaptation indicators are as follows: The weights of the physicochemical indicators of water bodies are as follows: dissolved oxygen (DO) (0.08), pH (0.06), water temperature (T) (0.05), electrical conductivity (EC) (0.04), total nitrogen (TN) (0.05), total phosphorus (TP) (0.03), and chemical oxygen demand (COD) (0.02). Weights of sediment environmental indicators: sediment particle size D (0.08), sediment organic carbon content SCO (0.09), and sediment porosity. (0.08); Weights of food resource indicators: phytoplankton biomass Chl-a (0.13) and organic detritus content OC (0.12). Weights of biological behavioral adaptation indicators: mean inter-individual spacing M (0.06) and population density P (0.04) in filter-feeding benthic animals. Based on the determined weights of each measurement index, the water body physicochemical index data W1, sediment environment index data W2, food resource index data W3, and biological behavior adaptation index data W4 are calculated separately, using the following formulas: Water physicochemical index data W1: 0.85×0.08+0.80×0.06+0.75×0.05+0.70×0.04+0.70×0.05+0.60×0.03+0.75×0.02=0.2495; Seabed environmental index data W2: 0.80×0.08+0.75×0.09+0.90×0.08=0.2035; Food resource index data W3: 0.90×0.13+0.85×0.12=0.219; Biological behavior adaptation index data W4: 0.80×0.06+0.75×0.04=0.078.

[0043] (2) The survival environment suitability index (SEI) is calculated based on the water body physicochemical index data W1, the sediment environment index data W2, the food resource index data W3, and the biological behavior adaptation index data W4. The calculation formula is as follows: The environmental suitability index (SEI) is calculated as follows: SEI = W1 + W2 + W3 + W4 = 0.2495 + 0.2035 + 0.219 + 0.078 = 0.75.

[0044] (3) The survival environment suitability index (SEI) of the landscape river is 0.75. A random area (0.5m×0.5m) of the landscape river was selected, and filter-feeding benthic snails were introduced and marked. The survival status of the snails was observed every 15 days. After three months of continuous observation, it was found that the survival status of the introduced snails was good.

[0045] Example 2

[0046] An assessment was conducted on a polluted river in a certain area, following the method described in Example 1. The final measured environmental suitability index was 0.524. A random area (0.5m × 0.5m) of the river was selected, and filter-feeding benthic snails were introduced and marked. The survival status of the snails was observed every 15 days for 3 consecutive months. During the second observation, it was found that the introduced snails had died.

[0047] Example 3

[0048] An assessment was conducted on a slightly polluted lake in a certain area, following the method described in Example 1. The final measured environmental suitability index was 0.62. A random area (0.5m × 0.5m) of the lake was selected, and filter-feeding benthic snails were introduced and marked. The survival status of the snails was observed every 15 days for 3 consecutive months. The results showed that the introduced snails were in good condition.

[0049] Example 4

[0050] Based on the combined results of Examples 1-3, the threshold for the Environmental Suitability Index (SEI) was determined to be 0.6. When the SEI is greater than or equal to 0.6 and less than or equal to 1.0, the living environment is suitable for filter-feeding benthic animals. When the SEI is less than 0.6, the living environment is not suitable for filter-feeding benthic animals and the living environment needs to be improved.

[0051] The present invention provides a method for assessing the habitat of filter-feeding benthic animals, comprising the following steps: (1) Collect water samples from the water body and measure the physicochemical indicators (dissolved oxygen DO, pH, water temperature T, electrical conductivity EC, total nitrogen TN, total phosphorus TP and chemical oxygen demand COD), bottom sediment environmental indicators (bottom sediment particle size D, bottom sediment organic carbon content SCO and bottom sediment porosity Φ), food resource indicators (plankton biomass Chl-a and organic detritus content OC) and biological behavior adaptation indicators (average distance between filter-feeding benthic animals M and population density P). Process the data and then calculate the water body physicochemical indicator data W1, bottom sediment environmental indicator data W2, food resource indicator data W3 and biological behavior adaptation indicator data W4 respectively. The formula for data processing is: X'=(X-Xmin) / (Xmax-Xmin) Where X' is the standardized indicator value, X is the indicator average, Xmin is the minimum value of the indicator, and Xmax is the maximum value of the indicator. The formula for calculating the physicochemical index data W1 of water bodies is as follows: W1=0.08×DO+0.06×pH+0.05×T+0.04×EC+0.05×TN+0.03×TP+0.02×COD; The formula for calculating the sediment environmental index data W2 is as follows: W2 = 0.08 × D + 0.09 × SCO + 0.08 × ; The formula for calculating the food resource index data W3 is as follows: W3 = 0.13 × Chl - a + 0.12 × OC; The formula for calculating the biological behavior fit index W4 is as follows: W4 = 0.8 × M + 0.04 × P.

[0052] (2) The survival environment suitability index (SEI) is calculated based on the water body physicochemical index data W1, the bottom sediment environment index data W2, the food resource index data W3, and the biological behavior adaptation index data W4. The formula for calculating the Survival Environment Suitability Index (SEI) is as follows: SEI = W1 + W2 + W3 + W4.

[0053] (3) The method for assessing whether small water bodies are suitable for the survival of filter-feeding benthic animals based on the survival environment suitability index is as follows: a. When the environmental suitability index is greater than or equal to 0.6 and less than or equal to 1.0, it is suitable for filter-feeding benthic animals to survive; b. When the environmental suitability index is less than 0.6, it is not suitable for filter-feeding benthic animals to survive, and the living environment needs to be improved.

[0054] As can be seen from the above embodiments, the present invention provides a method for assessing the living environment of filter-feeding benthic animals and its application. The present invention is highly targeted: it specifically designs an assessment index system based on the physiological characteristics, feeding methods, and habitat habits of filter-feeding benthic animals, and adds biological behavioral adaptation indicators (inter-individual spacing, population density), fully considering the impact of spatial distribution among individuals on feeding efficiency, thus solving the problem of insufficient targeting in existing methods. The assessment results are more closely aligned with the survival needs of filter-feeding benthic animals. The indicators are comprehensive: they cover four major categories of indicators: water physicochemical properties, substrate environment, food resources, and biological behavioral adaptation, comprehensively covering the core influencing factors on the survival of filter-feeding benthic animals and avoiding reliance on single indicators. To address the limitations of one-sided assessments, this method enhances the comprehensiveness and accuracy of evaluations; it achieves precise quantification by employing the analytic hierarchy process (AHP) to determine indicator weights and combining this with the weighted summation method to calculate the suitability index, establishing clear grading standards, transforming qualitative assessments into quantitative ones, avoiding errors from subjective judgments, and making the assessment results more scientific and operable; and it has wide applicability, suitable for assessing the habitats of filter-feeding benthic animals in various water bodies (lakes, rivers, reservoirs, artificial wetlands, etc.), and can be used for habitat suitability assessment, monitoring the effects of ecological restoration, and selecting artificial rearing areas, demonstrating high application value and ease of promotion and implementation.

[0055] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for assessing the habitat of filter-feeding benthic animals, characterized in that, Includes the following steps: (1) Collect and measure water body physicochemical indicators, bottom sediment environmental indicators, food resource indicators and biological behavior adaptation indicators of water samples, process the data, and obtain water body physicochemical indicator data W1, bottom sediment environmental indicator data W2, food resource indicator data W3 and biological behavior adaptation indicator data W4 respectively. (2) The survival environment suitability index (SEI) is calculated based on the water body physicochemical index data W1, the bottom sediment environment index data W2, the food resource index data W3, and the biological behavior adaptation index data W4. (3) Assess whether small water bodies are suitable for filter-feeding benthic animals based on the environmental suitability index.

2. The evaluation method according to claim 1, characterized in that, The water area to be measured in step (1) includes one of the following: lake, river, reservoir and artificial wetland.

3. The evaluation method according to claim 1, characterized in that, The formula for data processing in step (1) is: X'=(X-Xmin) / (Xmax-Xmin); In the formula, X' is the standardized index value, X is the average value of the index measurement, Xmin is the minimum value of the index measurement, and Xmax is the maximum value of the index measurement.

4. The evaluation method according to claim 1, characterized in that, The physicochemical indicators of the water body mentioned in step (1) include dissolved oxygen (DO), pH, water temperature (T), conductivity (EC), total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). The formula for calculating the water body physicochemical index data W1 is as follows: W1 = 0.08 × DO value + 0.06 × pH value + 0.05 × T value + 0.04 × EC value + 0.05 × TN value + 0.03 × TP value + 0.02 × COD value.

5. The evaluation method according to claim 1, characterized in that, The sediment environmental indicators mentioned in step (1) include sediment particle size D, sediment organic carbon content SCO, and sediment porosity. ; The formula for calculating the sediment environmental index data W2 is as follows: W2 = 0.08 × D value + 0.09 × SCO value + 0.08 × value.

6. The evaluation method according to claim 1, characterized in that, The food resource indicators mentioned in step (1) include phytoplankton biomass (Chl-a) and organic detritus content (OC); The formula for calculating the food resource index data W3 is as follows: W3 = 0.13 × Chl-a value + 0.12 × OC value.

7. The evaluation method according to claim 1, characterized in that, The biological behavior adaptation indicators mentioned in step (1) include the average inter-individual spacing M and population density P of filter-feeding benthic animals; The formula for calculating the biological behavior adaptation index W4 is as follows: W4 = 0.8 × M value + 0.04 × P value.

8. The evaluation method according to claim 1, characterized in that, The formula for calculating the Environmental Suitability Index (SEI) mentioned in step (2) is as follows: SEI = W1 + W2 + W3 + W4.

9. The evaluation method according to claim 1, characterized in that, The evaluation method described in step (3) is as follows: a. When the environmental suitability index is greater than or equal to 0.6 and less than or equal to 1.0, it is suitable for filter-feeding benthic animals to survive; b. When the environmental suitability index is less than 0.6, it is not suitable for filter-feeding benthic animals to survive, and the living environment needs to be improved.

10. The application of the assessment method according to any one of claims 1 to 9 in methods for improving water pollution.

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