Environmental gradient threshold method for identifying functional traits of large benthonic animals in river

Abstract

The invention relates to an environmental gradient threshold method for identifying functional traits of large benthonic animals in a river, and belongs to the technical field of ecological environment. The method comprises the following steps: S1, sampling and identifying large benthonic animals in a river; s2, measuring physicochemical indexes of the river water body; s3, dividing functional traits of the macrobenthonic animals; s4, quantifying the characters of the macrobenthonic animals; s5, performing correlation analysis to screen important environmental factors; and S6, identifying the environmental gradient threshold value of the macrobenthonic animal character response. According to the method, environmental elements and benthonic animal functional characters are combined to find out the character indexes of the benthonic animals sensitive to the environment. And further quantifying the relationship between the environmental elements and the functional traits of the benthonic animals by determining the response range of the functional traits of the large benthonic animals to the environmental threshold.

Description

Technical Field

[0001] The invention belongs to the technical field of ecological environment, and relates to an environmental gradient threshold method for identifying functional traits of large benthic animals in rivers. Background Art

[0002] Benthic animals refer to aquatic animals that live at the bottom of the water body for all or most of their life history. In addition to settled and mobile ones, most of the forms of habitat are fixed on hard substrates such as rocks and buried in soft substrates such as mud and sand. In addition, there are benthic species that attach to the surface of plants or other benthic animals, as well as those that live in the intertidal zone. In terms of feeding methods, most of them feed on suspended matter and sediments. Most of them are invertebrates, and they are a complex ecological group. The benthic animal community structure is complex and diverse, with rich types of biological indexes, and is sensitive to different pollution and interference responses, which can comprehensively reflect the degree of disturbance of human interference activities on the river ecosystem. In the long process of evolution, benthic animals have evolved into hundreds of thousands of species with thousands of postures, and species of different categories have obvious differences in tolerance to environmental changes. Their responses to changes in the external environment vary greatly. Therefore, compared with other aquatic organisms (such as fish, algae, etc.), benthic animals have the following advantages as excellent indicator species for ecological assessment: 1) benthic animals are commonly found in rivers of different scales and have a wide range of activities; 2) Compared with plankton, benthic animals are larger in size, easy to collect, and require less manpower and material resources, and have low sampling costs; 3) Most benthic animals have a long life cycle, especially aquatic insects. Some larvae of the order Odonata need to live in the water for more than three years, and larvae of the order Ephemeroptera also need 1 to 3 years to grow into sub-adults. 4) At the same time, benthic animals have poor mobility and a relatively fixed range of activities. Researchers can detect information on the spatiotemporal changes in river ecological conditions over a longer time scale; 5) Benthic animals can respond quickly to changes in the ecological environment, and different groups have different sensitivities to external interference. Therefore, changes in the community structure of benthic animals can well reflect the impact of short-term environmental changes. In recent years, biological research has expanded from community species composition to the functional level. The use of functional traits to characterize functional composition and functional diversity is one of the hot spots in current benthic animal ecology research. A sentence is missing here to define and describe functional traits. Species functional traits are sensitive to environmental changes and have many potential indicative effects on the succession of communities and populations along environmental gradients. Previous work has generally ignored the evaluation of benthic functional traits and functional diversity, making it difficult to comprehensively, objectively and accurately reflect the ecological and environmental conditions of rivers. Moreover, the current research methods for the response of benthic animal traits to the environment are mostly focused on qualitative analysis, that is, analyzing the positive and negative correlation between a certain benthic animal and environmental factors, and rarely further determining the threshold range of environmental factors. A single qualitative analysis makes it difficult to accurately determine the tolerance threshold of organisms. Therefore, the method of this study will better identify the impact of functional characteristics on various stressors, obtain the quantitative response relationship between benthic animal functional traits and environmental gradients, and determine the threshold range of key environmental factors suitable for specific traits, which will help evaluate the health of river water ecosystems and have important theoretical and practical significance for indicating water environment management and water ecological restoration. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide an environmental gradient threshold method for identifying the functional traits of large benthic animals in rivers, to explore the functional trait indicators of benthic animals that are sensitive to the environment, and to provide more possibilities for using biological indicators to evaluate the environmental health of aquatic ecosystems.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for identifying environmental gradient thresholds of functional traits of river macrobenthic animals comprises the following steps:

[0006] S1. Sampling and identification of large benthic animals in rivers: Select several sampling points in the river and use a D-shaped scoop net to sample benthic animals at each sampling point. Rinse the collected samples with clean water and filter them with a sieve. The filtered samples are stored in a 75% ethanol solution and identified to species or genus using a microscope in the laboratory;

[0007] S2. Determination of physical and chemical indicators: Determination of physical and chemical indicators of river water bodies, including the following physical and chemical indicators: water temperature, dissolved oxygen, flow rate, water depth, river width, flow, total nitrogen, dissolved total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, dissolved total phosphorus, phosphate, and chemical oxygen demand;

[0008] S3. Functional trait classification: Based on river habitat attributes, select several functional traits and collect corresponding functional trait data;

[0009] S4. Quantification of benthic animal traits: A "fuzzy coding" procedure is used to encode each taxon according to its affinity for each trait modality. The fuzzy coding method is used to interpret multiple trait modalities of a single taxon, that is, a score range of 0 to 3 is used, where 0 indicates no affinity for a given trait category, 1 or 2 indicates partial affinity, and 3 indicates complete affinity. In this patent, in order to avoid deviations between different traits, the affinity scores for each trait are standardized so that their sum is equal to 1.

[0010] S5. Correlation analysis to screen the main environmental factors affecting benthic animals: Calculate the community weighted means (CWM) of each trait to obtain the relative abundance weighted value of each trait in each community, and highlight the dominant traits in the community. Then apply redundancy analysis (RDA) to environmental stressors and CWM to identify environmental factors that significantly affect the trait composition of benthic macroinvertebrates.

[0011] S6. Threshold identification of benthic traits responses: The TITAN package in R was used to determine the abundance-weighted thresholds of functional traits in response to each environmental stressor gradient by Threshold Indicator Taxa Analysis (TITAN).

[0012] The method should detect patterns and inflection points of trait abundance and frequency along environmental gradients, indicating increases and decreases of traits along the gradients, and the resulting maps should be used to determine threshold ranges for responses.

[0013] Collect and identify samples of benthic animals. Select several sampling points at the bottom of the stream and use a D-shaped scoop net to sample benthic animals at each sampling point. Rinse the collected samples with clean water and filter them with a sieve. The filtered samples are stored in a 75% ethanol solution and identified to species or genus using a microscope in the laboratory. The physical and chemical indicators of the collected water bodies are measured and collected. Specific indicators are added here. Based on the river habitat attributes, select several functional traits and collect the corresponding functional trait data. Based on these data, a "fuzzy coding procedure" was used to encode each taxon according to its affinity for each trait modality. The fuzzy coding method was used to interpret the multiple trait morphologies of a single taxon, that is, a score range of 0 to 3 was used, where 0 indicated no affinity for a given trait category, 1 or 2 indicated partial affinity, and 3 indicated complete affinity. In this patent, in order to avoid deviations between different traits, the affinity score of each trait was standardized so that its sum was equal to 1. Based on the fuzzy coding table obtained above, the community weighted mean (CWM) of each trait was calculated to obtain the relative abundance weighted value of each trait in each community, highlighting the dominant traits in the community. Redundancy analysis (RDA) was then applied to environmental stressors and CWM to identify those factors that significantly affect the functional composition of benthic macroinvertebrate communities.

[0014] Abundance-weighted threshold responses of functional traits relative to each environmental stressor gradient were determined by using Threshold Indicator Taxon Analysis (TITAN) in the “TITAN” software package. This method should detect patterns and inflection points of trait abundance and frequency along environmental gradients, indicating increases (Z+ scores) and decreases (Z- scores) of traits along the gradient. The resulting plots should be used to determine threshold ranges for responses.

[0015] The invention has the beneficial effect of determining the abundance-weighted threshold response of functional traits relative to each environmental stressor gradient using the Threshold Indicator Taxon Analysis (TITAN) in the "TITAN" software package. The method should detect the change pattern and inflection point of trait abundance and frequency along the environmental gradient, indicating the increase (Z+ score) and decrease (Z- score) of the trait along the gradient. The resulting graph is then used to determine the threshold range of the response.

[0016] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0018] Figure 1 The benthic animal traits selected in the specific embodiments of the present invention;

[0019] Figure 2 It is the result of the relationship between the traits and environmental factors in the specific embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0021] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0022] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0023] This study uses biostatistics to provide a method to determine the range of responses of benthic animal traits to environmental factors and explore indicators of benthic animal traits that are sensitive to the environment. The specific steps include:

[0024] (1) Compile and organize the benthic animal species classification density data and environmental data of each sampling point in a river at different times: specific indicators include: water temperature, dissolved oxygen, flow rate, water depth, river width, flow, total nitrogen, dissolved total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, dissolved total phosphorus, phosphate, and chemical oxygen demand.

[0025] (2) For the selection of functional traits of macrobenthic animals, this study mainly focused on three aspects: life history characteristics, resistance and resilience characteristics, and morphological and ecological characteristics. These characteristics were further divided into 8 functional traits (including size, body length, chemical properties, time to adulthood, activity habits, body morphology, exoskeleton protection structure, breathing method, and feeding type), 28 patterns, such as Figure 1 and Figure 2Information on biological traits was obtained from online databases: The Marine Life Information Network (http: / / www.marlin.ac.uk / biotic / ), World Register of Marine Species (http: / / www.marinespecies.org / ), Marine Species Traits (http: / / www.marinespecies.org / traits / index.php), Arctic Traits (https: / / www.univie.ac.at / arctictraits), Polychaete Traits (http: / / polytraits.lifewatchgreece.eu / polytraits). When information on a taxon was missing, data from the same genus or family were referenced. A fuzzy coding method was used to code each taxon according to its affinity for each pattern. This method explains multiple trait patterns for a taxon using a score range of 0 to 3, where 0 indicates no affinity for a given pattern category, 1 or 2 indicates partial affinity, and 3 indicates full affinity. To avoid bias between different patterns, the affinity scores of each trait pattern were normalized so that their sum equaled 1.

[0026] (3) Calculation of community weighted mean trait value: For the overall functional trait composition of benthic animals, this study constructed a Euclidean distance matrix based on the community weighted mean trait value (CWM). The dominant traits were also mainly judged based on the CWM value. The CWM calculation was based on two data tables: the community composition table (sample point × species) and the functional trait table (species × trait).

[0027] CWM calculation formula:

[0028]

[0029] In the formula, S is the number of species in the community, p i is the relative density of the i-th species, x i is the trait value of the ith species.

[0030] CWM calculation is implemented in the function “dbFD” in the R language package FD.

[0031] (4) Screening for traits significantly correlated with environmental factors: This study first determined the environmental factors significantly correlated with species composition through redundancy analysis (RDA). The steps of redundancy analysis include: Through redundancy analysis, it was found that total nitrogen (p<0.05), ammonia nitrogen (p<0.05), nitrate nitrogen (p<0.05), total phosphorus (p<0.05), dissolved total nitrogen (p<0.05), dissolved total phosphorus (p<0.05), and chemical oxygen demand (p<0.05) were significantly related to the functional traits of benthic animals.

[0032] (5) This study used Threshold Indicator Taxa Analysis (TITAN) to further determine the gradient range of the response of functional traits to environmental factors. The TITAN method detects the change patterns and inflection points of trait abundance and frequency along the environmental gradient, indicating the increase (Z+ score) and decrease (Z- score) of traits along the environmental gradient. Higher Z-score values ​​indicate that the trait has a greater affinity for a specific gradient range. TITAN estimates the purity and reliability properties of functional traits based on 500 to 1000 resampling combinations by the proportion of times the functional trait obtains the same classification in each bootstrap replication. Purity refers to the proportion of resamplings in which Z+ or Z- changes according to the observed value during the entire resampling process, and reliability is the proportion of resamplings in which the indicator value is significant (p<0.05). The purity and reliability of the traits shown in this study were both greater than 0.9. The TITAN method was implemented using the "TITAN" package in the R language.

[0033] Table 1 is an example of preparing the original environment data set in a specific embodiment of the present invention;

[0034] Table 1

[0035]

[0036]

[0037] Table 2 is an example of preparing a benthic animal species classification dataset in a specific embodiment of the present invention;

[0038] Table 2

[0039]

[0040] Table 3 is a fuzzy coded data set of benthic animal traits selected in a specific embodiment of the present invention;

[0041] Table 3

[0042]

[0043]

[0044] Table 4 shows the environmental factors significantly correlated with trait composition screened by RDA;

[0045] Table 4

[0046] <![CDATA[r 2 ]]> p-value COD 0.0992492 0.089 DO 0.0690167 0.175 <![CDATA[NH4 + ]]> 0.3308831 0.001 <![CDATA[NO3 - ]]> 0.2377814 0.003 pH 0.0272962 0.501 Q 0.0455546 0.326 T 0.1152497 0.051 TN 0.2628854 0.003 TP 0.2019392 0.007 Chla 0.0031012 0.934 <![CDATA[PO4 3- ]]> 0.1840476 0.009 DTP 0.1925107 0.006 DTN 0.2836443 0.002

[0047] Table 5 shows the range of the threshold responses of traits to environmental factors in specific embodiments of the present invention.

[0048] Table 5

[0049]

[0050]

[0051] The present invention uses a specific embodiment to demonstrate how to apply the method to identify the environmental gradient threshold of the functional traits of river macrobenthic animals.

[0052] 1. Sampling and identification of river macrobenthic animals (S1):

[0053] The researchers selected 10 sampling points in a river, covering different habitat types of the river, such as the upper reaches, midstream, lower reaches, and tributaries.

[0054] At each sampling point, benthic animals were sampled using a D-shaped dip net, and sampling was repeated three times at each sampling point.

[0055] After sampling, the samples are rinsed with clean water and filtered through a sieve to remove impurities.

[0056] The filtered samples were stored in 75% ethanol solution and brought back to the laboratory for identification.

[0057] In the laboratory, samples are identified to species or genus using a microscope, and the number of individuals of each species is recorded.

[0058] 2. Determination of physical and chemical indicators of river water (S2):

[0059] The researchers used a water quality analyzer to measure the physical and chemical indicators of the water at each sampling point, including:

[0060] Water temperature, dissolved oxygen, flow rate, water depth, river width, flow, total nitrogen, dissolved total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, dissolved total phosphorus, phosphate and chemical oxygen demand. The measurement results were recorded in a table for subsequent analysis.

[0061] 3. Functional traits of macrobenthic animals (S3):

[0062] The researchers selected eight functional traits based on river habitat attributes and collected data on the corresponding functional traits for each species. These functional traits include:

[0063] The data on size, length, chemosensitivity, time to adulthood, activity habits, body morphology, exoskeleton protection structure, breathing method, feeding type, and functional traits were obtained from online databases and literature.

[0064] 4. Quantification of benthic animal traits (S4):

[0065] The researchers used a "fuzzy coding" procedure to code each species according to its affinity for each trait modality.

[0066] The encoding range is 0 to 3, where 0 indicates no affinity, 1 or 2 indicates partial affinity, and 3 indicates full affinity.

[0067] To avoid bias between different traits, the affinity scores for each trait were normalized so that their sum equaled 1.

[0068] 5. Screening of important environmental factors by correlation analysis (S5):

[0069] The researchers calculated the community weighted mean (CWM) of each trait to obtain the relative abundance weight of each trait in each community.

[0070] Redundancy analysis (RDA) was then applied to environmental stressors and CWM to identify environmental factors that significantly influenced the trait composition of benthic macroinvertebrates.

[0071] The analysis results showed that total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, dissolved total nitrogen, dissolved total phosphorus, and chemical oxygen demand were significantly correlated with the functional traits of benthic animals.

[0072] 6. Identification of environmental gradient thresholds for macrofauna trait responses (S6):

[0073] We used the TITAN approach to determine abundance-weighted thresholds for functional traits in response to each environmental stressor gradient using threshold indicator taxon analysis.

[0074] This method detects patterns and inflection points in trait abundance and frequency along environmental gradients, indicating increases (Z+ scores) and decreases (Z- scores) of traits along the gradient.

[0075] The researchers used the resulting graph to determine the threshold range for the response.

[0076] Result analysis:

[0077] The results showed that different functional traits responded differently to environmental gradients.

[0078] For example, some traits are very sensitive to the concentrations of total nitrogen and ammonia nitrogen, and their abundance will drop significantly when the concentration exceeds a certain threshold.

[0079] Other traits are more tolerant to changes in COD concentrations.

[0080] The method provided by the invention can effectively identify the environmental gradient threshold of the functional traits of river macrobenthic animals.

[0081] This method can help researchers better understand the response mechanism of benthic animal functional traits to environmental changes and provide a scientific basis for river ecological environment evaluation and management.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for identifying environmental gradient thresholds of functional traits of river macrobenthic animals, characterized by: The following steps are involved: S1. Sampling and identification of large benthic animals in rivers: Select several sampling points in the river, use a dip net to sample benthic animals at each sampling point, rinse, filter and preserve the collected samples, and identify the samples to species or genus using a microscope in the laboratory; S2. Determination of physical and chemical indicators of river water bodies: Determination of physical and chemical indicators of river water bodies, including water temperature, dissolved oxygen, flow rate, water depth, river width, flow, total nitrogen, dissolved total nitrogen, ammonia nitrogen, nitrate nitrogen, total phosphorus, dissolved total phosphorus, phosphate, and chemical oxygen demand; S3. Functional trait classification of macrobenthic animals: Based on the river habitat attributes, select several functional traits and collect corresponding functional trait data; S4. Quantification of benthic traits: A "fuzzy coding" procedure was used to code each taxon according to its affinity to each trait modality and to standardize the coding scores so that their sum equals 1; S5. Screening of important environmental factors by correlation analysis: Calculate the community weighted means (CWM) of each trait to obtain the relative abundance weighted values ​​of each trait in each community, highlight the dominant traits in the community, and then apply redundancy analysis (RDA) to environmental stressors and CWM to identify environmental factors that significantly affect the trait composition of benthic macroinvertebrates; S6. Identification of environmental gradient thresholds for macrobenthic trait responses: Use the Threshold Indicator Taxa Analysis (TITAN) method to determine the abundance-weighted thresholds of functional traits in response to each environmental stressor gradient, and detect the change patterns and inflection points of trait abundance and frequency along the environmental gradient to determine the threshold range of the response.

2. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S1, the scoop net is a D-shaped scoop net.

3. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In said S3, functional traits include life history characteristics, resistance and resilience characteristics, as well as morphological and ecological characteristics.

4. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S4, the fuzzy coding method explains multiple trait patterns of a certain taxonomic group through a score range of 0 to 3, where 0 indicates no affinity to a given pattern category, 1 or 2 indicates partial affinity, and 3 indicates full affinity.

5. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S5, RDA was applied to environmental stressors and CWM to identify factors that significantly influenced the functional composition of benthic macroinvertebrate communities.

6. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S6, the TITAN method detects the changing patterns and inflection points of trait abundance and frequency along environmental gradients, indicating the increase, i.e., Z+ score, and decrease, i.e., Z- score, of traits along environmental gradients.

7. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S6, the TITAN method estimates the purity and reliability attributes of functional traits based on 500 to 1000 resampling combinations by the proportion of times the functional traits obtain the same classification in each bootstrap replication.

8. The environmental gradient threshold method for identifying functional traits of river macrobenthic animals according to claim 1, characterized in that: In S6, the finally obtained result graph is used to determine the threshold range of the response.

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