A method for determining the continuity characteristics of river ecosystems

Abstract

This invention discloses a method for determining the continuity characteristics of river ecosystems, comprising the following steps: S1, firstly, selecting a river section within the river ecological loop area and setting up sampling points within that section; S2, collecting water samples to detect aquatic environmental data and identifying phytoplankton; S3, classifying the phytoplankton at each sampling point according to the total community, diatoms, green algae, and other phyla; S4, directly analyzing the spatiotemporal characteristics of the aquatic ecosystem using the Jaccard similarity index and the Bray-Curtis similarity index. This invention classifies phytoplankton communities according to four indicators: total community, diatoms, green algae, and other phyla, and uses the Jaccard similarity index and the Bray-Curtis similarity index, along with their indicative functions for the aquatic environment, for comprehensive analysis. This method is highly representative, resulting in more accurate results and providing important scientific basis for river aquatic ecological environment protection, post-dam construction ecological restoration, and the development of effective management measures.

Description

Technical Field

[0001] This invention relates to the field of ecological and environmental protection technology, specifically a method for determining the continuity characteristics of river ecosystems. Background Technology

[0002] More than half of the world's major rivers are affected by dam construction. Dam construction leads to river fragmentation, which seriously affects the ecological health of rivers. Phytoplankton are sensitive indicator organisms of changes in the aquatic environment and have been widely used in the study of the impact of river fragmentation. Existing related technologies mainly focus on the impact of individual dams or cascade reservoirs, while research and technologies for judging the continuity of rivers are rarely reported. In order to protect the river ecological environment and provide scientific data for river ecological restoration, it is urgent to carry out targeted research. At present, the Jaccard similarity index or Bray-Curtis similarity index is mainly used to conduct similarity analysis on the entire phytoplankton community to study the continuity of river ecosystems.

[0003] However, in current assessments of river continuous ecosystems, the Jaccard similarity index focuses on the analysis of similar species, while the Bray-Curtis similarity index focuses on the analysis of the abundance of similar species. In addition, the entire phytoplankton community is not representative enough of the continuous ecosystem, resulting in low accuracy. Summary of the Invention

[0004] This invention provides a method for determining the continuity characteristics of river ecosystems, which can effectively solve the problem mentioned in the background art that the current methods for determining the continuity of river ecosystems focus on the analysis of similar species, such as the Jaccard similarity index and the Bray-Curtis similarity index, which focus on the analysis of the abundance of similar species. In addition, the entire phytoplankton community is not representative enough for the continuous ecosystem, resulting in low accuracy.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for determining the continuity characteristics of a river ecosystem, comprising the following steps:

[0006] S1. First, select a section of the river within the river ecological ring area and set up sampling points within that section;

[0007] S2. Collect water samples to test aquatic environmental data and identify phytoplankton;

[0008] S3. Classify the phytoplankton at each sampling point according to the total community, diatoms, green algae and other phyla;

[0009] S4. Use the Jaccard similarity index and the Bray-Crutis similarity index to directly analyze the spatiotemporal characteristics of the aquatic ecosystem;

[0010] S5. Use RDA to analyze the relationship between each indicator and environmental data, and the relationship between the two similarity indices and environmental data;

[0011] S6. Use linear analysis to obtain the relationship between the two similarity indices and the distance.

[0012] S7. Using two similarity indices from the four indicators, perform SOM analysis to obtain the set delineated by spatiotemporal differences.

[0013] S8. Use LDA to analyze the set in the SOM results to obtain environmental factors that are sensitive to spatiotemporal changes;

[0014] S9. Based on the above analysis, the most suitable model for determining the continuity characteristics of rivers is derived, and the continuity of rivers is evaluated.

[0015] According to the above technical solution, in step S2, the water chemical data detected include total nitrogen, water temperature, pH, salinity, dissolved oxygen, total dissolved solids, redox potential, transparency, conductivity, specific conductivity, saturation, underwater luminescence, phosphate, total phosphorus, total nitrogen, nitrate nitrogen, nitrite nitrogen, ammonia nitrogen, and silicate.

[0016] According to the above technical solution, in S3, the other categories are phytoplankton phyla other than diatoms and green algae.

[0017] According to the above technical solution, in step S5, when analyzing the relationship between each indicator and environmental data, the Jaccard similarity index and the Bray-Curtis similarity index of each indicator are used together.

[0018] The environmental data is the absolute value of the difference between hydration data at adjacent points;

[0019] When analyzing the relationship between two similarity indices and environmental data, single similarity indices for total community, diatoms, chlorophytes, and other phyla are used together.

[0020] According to the above technical solution, after the LDA analysis is completed, a comparison chart of LDA analysis of the total community, diatoms, chlorophytes, and other phyla is drawn, and a comparison chart of LDA analysis of the Jaccard community similarity index and the Bray-Curtis community similarity index is drawn.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0022] 1. This invention found that phytoplankton phyla other than diatoms and green algae have a higher explanatory power for continuous river ecosystems. In the study of continuous river ecosystems, the total community had an explanatory power of 53.33%, diatoms had an explanatory power of 47.50%, green algae had an explanatory power of 55.83%, and other phyla had an explanatory power of 67.50%. The analysis of the explanatory power of different phyla makes the analysis of ecosystem continuity more detailed and accurate.

[0023] 2. This invention found that in studies using community similarity indices to analyze continuous river ecosystems, the Jaccard community similarity index explained 50.00% of the data, while the Bray-Curtis community similarity index explained 53.33%. Combining the two similarity indices makes the analysis results more accurate.

[0024] 3. This invention covers the relationship between the entire phytoplankton community and individual phyla and river ecosystems, and analyzes the indicators of each phylum and environmental data, as well as the two similarity indices and environmental data, thereby improving the sensitivity to the environment. Based on the results of this invention, a more effective method will be provided for the study of continuous river ecosystems.

[0025] In summary, this study comprehensively analyzed phytoplankton communities using four indicators: total community, diatoms, green algae, and other phyla. The analysis employed the Jaccard similarity index and the Bray-Curtis similarity index, along with their indicative functions for the aquatic environment. This approach yielded highly representative and accurate results, providing crucial scientific evidence for river aquatic ecological environment protection, post-dam ecological restoration, and the development of effective management measures. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 This is a flowchart illustrating the steps of the river ecosystem continuity analysis of this invention;

[0028] Figure 2 A map was created to show the sampling points, taking the Dongjiang River as an example;

[0029] Figure 3 Spatiotemporal characteristics of Jaccard similarity indices for the total community, diatoms, chlorophytes, and other phyla, taking the Dongjiang River as an example;

[0030] Figure 4 Spatiotemporal characteristics of Bray-Curtis similarity indices for the total community, diatoms, chlorophytes, and other phyla, taking the Dongjiang River as an example;

[0031] Figure 5 RDA analysis of Jaccard similarity index and Bray-Curtis similarity index, taking Dongjiang River as an example;

[0032] Figure 6 RDA analysis was conducted on the total community, diatoms, chlorophytes, and other phyla, taking the Dongjiang River as an example;

[0033] Figure 7 The results of linear analysis of Jaccard similarity index and distance for the total community, diatoms, chlorophytes, and other phyla are shown, taking the Dongjiang River as an example.

[0034] Figure 8 The results of linear analysis of Bray-Curtis similarity index versus distance for the total community, diatoms, chlorophytes, and other phyla are shown, taking the Dongjiang River as an example.

[0035] Figure 9 SOM and LDA analyses of the Jaccard similarity index and Bray-Curtis similarity index are performed, taking the Dongjiang River as an example.

[0036] Figure 10 SOM and LDA analyses were performed on the total community, diatoms, chlorophytes, and other phyla, using the Dongjiang River as an example. Detailed Implementation

[0037] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0038] Example: Figure 1 As shown, the present invention provides a technical solution, a method for determining the continuity characteristics of a river ecosystem, comprising the following steps:

[0039] S1. First, select a section of the river within the river ecological ring area and set up sampling points within that section;

[0040] S2. Collect water samples to test aquatic environmental data and identify phytoplankton;

[0041] S3. Classify the phytoplankton at each sampling point according to the total community, diatoms, green algae and other phyla;

[0042] S4. Use the Jaccard similarity index and the Bray-Crutis similarity index to directly analyze the spatiotemporal characteristics of the aquatic ecosystem;

[0043] S5. Use RDA to analyze the relationship between each indicator and environmental data, and the relationship between the two similarity indices and environmental data;

[0044] S6. Use linear analysis to obtain the relationship between the two similarity indices and the distance;

[0045] S7. Using two similarity indices of the four indicators together, perform SOM analysis to obtain the set divided by spatiotemporal differences;

[0046] S8. Use LDA to analyze the set in the SOM results to obtain environmental factors that are sensitive to spatiotemporal changes;

[0047] S9. Based on the above analysis, the most suitable model for determining the continuity characteristics of rivers is derived, and the continuity of rivers is evaluated.

[0048] like Figure 2As shown, this invention established 59 sampling points in 13 sections of the middle and lower reaches of the Dongjiang River, including Fengshuba (FSB), Longtan (LT), Renkeng (RK), Luoyingkou (LYK), Suleiba (SLB), Zhentouzhai (ZTZ), Liucheng (LC), Lankou (LK), Huangtian (HT), Mujing (MJ), Fengguang (FG), Likou (LIK), and Dongjiang (DJ). Phytoplankton samples were collected at each sampling point, and water chemical data were analyzed, including: water temperature (WT), pH, salinity, dissolved oxygen (DO), total dissolved solids (TDS), oxidation-reduction potential (OPR), transparency, conductivity (cond), specific conductivity, dissolved oxygen saturation (DO saturation), underwater light, phosphate (PO4), total phosphorus (TP), total nitrogen (TN), nitrate nitrogen (NO3), nitrite nitrogen (NO2), ammonia nitrogen (NH4), and silicate (SiO4). The sampling periods were November 2018 (dry season) and July 2019 (high water season). Phytoplankton at each sampling point were categorized into four groups: total community, diatoms, green algae, and other algae (phytoplankton groups other than diatoms and green algae). The Jaccard similarity index and the Bray-Curtis similarity index were used for comprehensive analysis. The specific processing steps are as follows: Spatiotemporal feature analysis is performed directly using the Jaccard similarity index and Bray-Curtis similarity index of each indicator; RDA analysis is conducted on the Jaccard similarity index and Bray-Curtis similarity number of each of the four indicators with environmental data, and then RDA analysis is conducted again on the Jaccard similarity index and Bray-Curtis similarity number of each indicator with environmental data to obtain and verify the sensitivity of each indicator to environmental data; linear regression analysis is conducted on the distance between the Jaccard similarity index of each indicator and the corresponding sample point, and then linear regression analysis is conducted again on the distance between the Bray-Curtis similarity number of each indicator and the corresponding sample point; SOM analysis is conducted on the Jaccard similarity index and Bray-Curtis similarity number of each of the four indicators with environmental data, and then SOM analysis is conducted again on the Jaccard similarity index and Bray-Curtis similarity number of each indicator with environmental data to obtain several sets of similarity between sampling points; LDA analysis is conducted on the sets obtained from the SOM analysis with environmental factors to obtain the relationship between each set and the environmental data and the explanatory power of each model.

[0049] Note: The environmental data used in the above analysis are the absolute values ​​of the differences in hydration data between adjacent sites; the Jaccard similarity index reflects the degree of species similarity; the Bray-Curtis similarity index reflects the degree of similarity in biomass of the same algal species.

[0050] The spatiotemporal characteristics of the Dongjiang River, such as Figure 3-4 As shown, from Figure 3 It can be seen that the total community, diatoms, and green algae can still show seasonal differences in the upstream due to the influence of the dam, while other relatively disadvantaged groups have basically lost their seasonal differences; however, in the middle and lower reaches, none of the four indicators showed obvious seasonal differences or upstream and downstream spatial differences. Figure 4 The law of reaction and Figure 3 Generally similar, but with different species of green algae. Figure 3 The patterns vary considerably, indicating that the dam has a significant impact on the biomass of certain species of green algae, but not to the point of causing the affected species to disappear.

[0051] Figure 3 , Figure 4 Comprehensive analysis shows that diatoms are the most dominant species in this watershed. Due to the impact of the dam, the original spatial and temporal differences in the middle and lower reaches have been lost, and the water exhibits a wave-like repetitive pattern starting from the dam.

[0052] RDA analysis results are as follows Figure 5-6 As shown, from Figure 5 As can be seen, the four indicators have a certain positive correlation with PO4 and TN in terms of species similarity; from Figure 6 It can be seen that, in terms of similarity in biomass of the same type of algae, diatoms and total community are positively correlated with PO4, other phyla are positively correlated with TN, and green algae are somewhat positively correlated with NO2.

[0053] from Figure 6 The results show that species similarity and biomass similarity of the same algae in the total community are both positively correlated with PO4, with species similarity showing the strongest correlation with PO4; biomass similarity of the same algae in diatoms is positively correlated with PO4; species similarity in green algae is positively correlated with PO4, and biomass similarity of the same algae is positively correlated with TP; other phyla show that species similarity is positively correlated with TN.

[0054] The results of the linear regression analysis are as follows Figure 7-8 As shown, during the high-water season, distance was related to the total community (p < 0.05, r² = 0.099) Figure 7 A) Chlorophyta (p < 0.05, r² = 0.098) Figure 7E) A significant positive correlation was found between distance and the number of green algae based on the Jaccard index; during the dry season, distance was significantly negatively correlated with the number of green algae based on the Jaccard index (p < 0.05, r² = 0.095). Figure 7 F), the distance was significantly positively correlated with other categories based on the Jaccard index (p < 0.05, r² = 0.126). Figure 7 During the high-water season, distance was significantly positively correlated with diatom phylum based on the Bray-Curtis index (p < 0.05, r² = 0.112). Figure 8 C).

[0055] SOM and LDA analysis results are as follows: Figure 9-10 As shown, based on species similarity, they were divided into three groups: J1 (sampling groups at points across and near the dam during the high-water season), J2 (sampling groups at points across and near the dam during the low-water season), and J3 (sampling groups at points between the dams). Group J1 showed a positive correlation with light; Group J2 showed a positive correlation with total nitrogen (TN); and Group J3 showed a positive correlation with phosphorus oxidase (PO4). Based on similarity in biomass of the same algal species, they were divided into four groups: B1 (sampling groups at points between the dams during the high-water season), B2 (sampling groups at points across the dam during the high-water season), B... Groups B1 and B4 (near-dam and across-dam sampling sites during the dry season) were used to determine the total community index. Group B1 showed a positive correlation with dissolved oxygen (DO); Group B4 showed a positive correlation with total nitrogen (TN); and Group B2 showed a positive correlation with nitrogen (NO2). Based on species similarity and biomass analysis of the same algal species, the total community index was further divided into three groups: Group C1 (inter-dam sampling sites during the high-water season), Group C2 (across-dam and near-dam sampling sites), and Group C3 (inter-dam sampling sites during the dry season). Group C3 showed a positive correlation with dissolved oxygen (PO4). Correlation; Group C1 was positively correlated with light; Group C2 was negatively correlated with DO; Diatoms were divided into three groups based on their phylum indices: Group D1 (sampling group across the dam), Group D2 (sampling group near the dam), and Group D3 (sampling group between the dams), with Group D2 showing a positive correlation with PO4; Groups D1 and D3 showed a negative correlation with PO4; Chlorophyta were divided into three groups based on their phylum indices: Group G1 (sampling group across and near the dam), Group G2 (sampling group between the dams), and Group G3 (sampling group withered algae). The sampling points near the dam during the flood season were divided into three groups: group G3 was positively correlated with PO4; group G1 was negatively correlated with TP; and group G2 was positively correlated with conductivity. Other indicators were further divided into three groups: group O1 (sampling points between dams during the high-water season), group O2 (sampling points across and between dams), and group O3 (sampling points near the dam during the low-water season). Group O2 was positively correlated with TDS; group O1 was positively correlated with NO2; and group O3 was positively correlated with TN.

[0056] The LDA analysis results of samples from 15 sections of the middle and lower reaches of the Dongjiang River in this example are shown in Table 1. Among the two similarity indices, the explanation rates of the Bray-Curtis similarity index and the Jaccard similarity index are not significantly different. Among the four indicators, the explanation rates from high to low are: other phyla, green algae, total community, and diatoms.

[0057] Table 1. LDA analysis results of samples from 15 sections of the middle and lower reaches of the Dongjiang River.

[0058]

[0059]

[0060] Among the two similarity indices, the Bray-Curtis similarity index and the Jaccard similarity index had similar explanatory power. Among the four indices, the explanatory power, from highest to lowest, was: other phyla, Chlorophyta, total community, and Diatoms. This was particularly evident in physicochemical properties. Figure 3-4 ) and space ( Figure 5-6 This is reflected in all aspects, with the explanation rate of other categories differing from that of the total community by 14.70%, indicating that traditional research methods are not sensitive to environmental changes. In this case, due to the obstruction of the dam, the phytoplankton community exhibited fragmented and repetitive spatial characteristics, which were particularly evident in the middle and lower reaches. Among the environmental factors that were most correlated with the phytoplankton similarity index, PO4 and TN were the most significant.

[0061] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for determining the continuity characteristics of a river ecosystem, characterized in that: It comprises the following steps: S1, first select a river section in the river ecological ring area, and set a sampling point in the river section; S2, collect water samples to detect water environment data, and identify phytoplankton; S3, classify the phytoplankton at each sampling point according to four indexes, i.e., total community, diatom, chlorophyta and other phyla; S4, directly analyze the spatial and temporal characteristics of the aquatic ecosystem by using Jaccard similarity index and Bray-Curtis similarity index; S5, analyze the relationship between each index and environmental data by using RDA, specifically, RDA analysis is performed on the Jaccard similarity index and the Bray-Curtis similarity number of the four indexes and the environmental data, and then RDA analysis is performed on the Jaccard similarity index and the Bray-Curtis similarity number of each index and the environmental data, to obtain and verify the sensitivity of each index to the environmental data; S6, obtain the relationship between the two similarity indexes and the distance by using linear analysis, specifically, linear regression analysis is performed on the Jaccard similarity index of each index and the corresponding sampling point distance, and then linear regression analysis is performed on the Bray-Curtis similarity number of each index and the corresponding sampling point distance; S7, comprehensively use the two similarity indexes of the four indexes to perform SOM analysis, to obtain a set divided by the spatial and temporal differences, and then perform SOM analysis on the Jaccard similarity index and the Bray-Curtis similarity number of the four indexes and the environmental data, and perform SOM analysis on the Jaccard similarity index and the Bray-Curtis similarity number of each index and the environmental data, to obtain several sets of similarity degrees between the sampling points; S8, analyze the sets in the SOM result by using LDA, to obtain the environmental factors sensitive to the spatial and temporal changes, perform LDA analysis on the sets obtained by the SOM analysis and the environmental factors, to obtain the relationship between each set and the environmental data and the interpretation rate of each model, after the LDA analysis is completed, draw the LDA analysis comparison chart of the total community, diatom, chlorophyta and other phyla, and draw the LDA analysis comparison chart of the Jaccard community similarity index and the Bray-Curtis community similarity index; S9, comprehensively obtain the most suitable model for determining the river continuity characteristics by the above analysis, and evaluate the river continuity.

2. The method for determining the characteristics of the continuity of the river ecosystem according to claim 1, characterized in that, In the S2, the detection of water chemical data includes total nitrogen, water temperature, pH, salinity, dissolved oxygen, total dissolved solids, oxidation-reduction potential, transparency, conductivity, specific conductivity, saturation, underwater light intensity, phosphate, total phosphorus, total nitrogen, nitrate nitrogen, nitrite nitrogen, ammonia nitrogen and silicate.

3. The method for determining the characteristics of the continuity of the river ecosystem according to claim 1, characterized in that, In the S3, the other phyla are other phyla of phytoplankton except diatom and chlorophyta.

4. The method for determining the characteristics of the continuity of the river ecosystem according to claim 1, characterized in that, In the S5, the Jaccard similarity index and the Bray-Curtis similarity index of each index are used together when analyzing the relationship between each index and the environmental data; The environmental data is the absolute value of the difference between the water data of adjacent points. In the analysis of the relationship between the two similarity indices and environmental data, the single similarity indices of the total community, Bacillariophyta, Chlorophyta and other taxa were used together.

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