A method and platform for constructing a food web and analyzing the structural functions of a river ecosystem

Abstract

The present invention discloses a method and platform for constructing a food web of a river ecosystem and analyzing its structural functions. The method includes: automatically obtaining the measured results of the composition structure and biomass of the river ecosystem; constructing a predation matrix with benthic animals as the main body in the freshwater ecosystem; determining the food chain list in the food web system; calculating the structural characteristic parameters of the food web system and the trophic levels of each trophic group, constructing the input data of the food web analysis system, constructing a biomass flux matrix, constructing a food web system matrix, and solving the index of the stability of the food web system under preset conditions; selecting a single trophic group and calculating the change in the stability of the food web system to quantify the importance of the single trophic group to the food web system. The present invention can quickly construct the food web system of a sampling point and conduct systematic analysis, calculation, and visualization on the structural characteristics, functional characteristics, stability, and key species of the food web system.

Description

Technical Field

[0001] The present invention relates to the technical field of ecosystem food web construction, and particularly relates to a method and platform for constructing and analyzing the structure and function of a river ecosystem food web. Background Art

[0002] The structure and function of an ecosystem are one of the core research directions in ecology. As an explicit expression of an ecosystem, a food web can effectively reflect the diversity, structure, and function of the ecosystem, and quantify the material cycle and energy transfer processes in the ecosystem. Analyzing the structure and function of an aquatic food web can well serve work such as river and lake water quality monitoring, watershed health assessment, wetland ecological governance, invasive species prevention and control, and target species conservation.

[0003] The research on the structure of an aquatic food web takes constructing a food web predation relationship matrix as the core content, and calculates and statistics the structural indexes of the food web based on the predation relationship matrix. At present, constructing a food web predation relationship matrix generally adopts the sample measurement method, that is, the feeding habits are judged by measuring and analyzing actual biological samples, and the predation relationship matrix is constructed accordingly. The commonly used measurement and analysis methods include: (1) microscopic identification method of gastrointestinal contents; (2) gene metabarcoding analysis method of gastrointestinal contents; (3) characteristic fatty acid analysis method; and (4) C13, N15 stable isotope analysis method, etc. In addition, there is also the Allometric Diet Breadth Model (ADBM) which starts from the difference in the average size of species individuals, and theoretically models and calculates the predation relationships of various species in the food web. However, since the predation relationship theory supported by the difference in the average size of species individuals is not applicable to the group predation behavior of small individual species or the parasitic behavior of small individual species, the simulation accuracy of ADBM for the actual food web system is relatively low, and the matching rate is generally not higher than 65%.

[0004] The functional study of aquatic food webs focuses on calculating the material fluxes in the food web. The calculation of material fluxes is based on the biomass conservation equation. Currently, there are two sets of mainstream analysis products: (1) the fluxweb package based on the R language platform, and (2) the independently developed software Ecopath with Ecosim. The fluxweb package is a product centered around the calculation of material fluxes in food webs. The input parameters include: a) the predation relationship matrix, b) biomass, c) metabolic rate, and d) assimilation rate. When constructing biomass conservation, this product only calculates two biomass loss terms, predatory death and metabolic consumption, and does not consider the biomass loss caused by non-predatory death during the intergenerational changes of biological groups. Ecopath with Ecosim is a product centered around the calculation of material fluxes and structural succession in fish food webs. It has more input parameters, including: a) the predation relationship matrix, b) biomass, c) non-predatory mortality rate, d) assimilation rate, e) production conversion rate, f) immigration and emigration amounts, g) productivity / biomass ratio, h) productivity / predation ratio, etc. This product is mainly used for fish populations, and it is difficult to simulate large benthic invertebrate communities due to insufficient measurement parameters. In addition, the common problems of the above two products include: a) strictly requiring the predation relationship matrix as an input item, and it is impossible to carry out qualitative simulation and analysis for samples lacking predation relationships; b) lacking a food web system stability analysis module; and c) being unable to identify key species in the food web. Summary of the Invention

[0005] The present invention aims to solve at least to some extent the related technical problems in the food web model.

[0006] To this end, the object of the present invention is to propose a method for constructing and analyzing the structure and function of a river ecosystem food web. Based on the biomass conservation theory and supported by the R language platform, the construction and analysis of the structure and function of the river ecosystem food web improve the theoretical equation of the food web system with large benthic invertebrate communities as the core group on the basis of existing technologies / models. It adds a qualitative analysis module for the structure and function of the food web when the input of the predation relationship is missing, adds a food web stability analysis module based on the Lotka-Volterra model, and adds a key species identification module based on the stability of the food web system. By inputting field sampling data, the present invention can quickly construct the food web system of the sampling point and systematically analyze and simulate the structural characteristics, functional characteristics, stability, and key species of the food web system.

[0007] Another object of the present invention is to propose a platform for constructing and analyzing the structure and function of a river ecosystem food web.

[0008] To achieve the above object, on the one hand, the present invention provides a method for constructing a food web of a river ecosystem and analyzing its structural functions, including:

[0009] Obtaining the measured results of the composition structure and biomass of the river ecosystem; wherein, the river ecosystem includes multiple components such as primary productivity, organic detritus, and different types of benthic animals; constructing a predation matrix with the benthic animals as the main body in the freshwater ecosystem based on a classification library and a relationship library of trophic groups, or based on the measured results of multiple measurement analysis methods; wherein, the predation matrix includes: a first predation matrix and a second predation matrix; enumerating the food chains in the food web system based on the predation matrix to obtain a list of food chain tables, and calculating the structural characteristic parameters of the food web system; combining the measured results of the biomass and the characteristic parameters of the trophic groups to calculate the trophic levels of each trophic group, so as to construct the input data of the food web analysis system; based on the input data, solving the biomass fluxes of each trophic group according to the carrying capacity of the environment for the trophic groups to construct a biomass flux matrix; constructing a food web system matrix based on the biomass flux matrix; based on the food web system matrix, solving the index of the stability of the food web system under preset conditions; selecting a single trophic group, adjusting the biomass proportion of the single trophic group, and successively calculating the changes in the stability of the food web system to quantify the importance of the single trophic group to the food web system.

[0010] The method for constructing a food web of a river ecosystem and analyzing its structural functions according to the embodiments of the present invention can quickly construct the food web system of a sampling point, and systematically analyze and calculate the structural characteristics, functional characteristics, stability, and key species of the food web system.

[0011] To achieve the above object, on the other hand, the present invention provides a platform for constructing a food web of a river ecosystem and analyzing its structural functions, including:

[0012] A data acquisition module for obtaining the measured results of the composition structure and biomass of the river ecosystem; wherein, the river ecosystem includes multiple components such as primary productivity, organic detritus, and different types of benthic animals;

[0013] A predation matrix construction module for constructing a predation matrix with the benthic animals as the main body in the freshwater ecosystem based on a classification library and a relationship library of trophic groups, or based on the measured results of multiple measurement analysis methods; wherein, the predation matrix includes a first predation matrix and a second predation matrix;

[0014] A characteristic parameter calculation module for enumerating the food chains in the food web system based on the predation matrix to obtain a list of food chain tables, and calculating the structural characteristic parameters of the food web system;

[0015] An input data construction module, configured to calculate the trophic levels of each trophic group by combining the measured results of the biomass and the characteristic parameters of the trophic group, so as to construct the input data of the food web analysis system;

[0016] A flux matrix construction module, configured to solve the biomass fluxes of each trophic group based on the input data according to the carrying capacity of the environment for the trophic group, so as to construct a biomass flux matrix;

[0017] A food web system matrix construction module, configured to construct a food web system matrix based on the biomass flux matrix;

[0018] A stability index solving module, configured to solve the index of the food web system stability under preset conditions based on the food web system matrix;

[0019] An importance quantification module, configured to select a single trophic group, adjust the biomass proportion of the single trophic group, and successively calculate the change in the food web system stability, so as to quantify the importance of the single trophic group to the food web system.

[0020] The food web construction and structural function analysis platform for river ecosystem in the embodiment of the present invention can quickly construct the food web system of a sampling point, and systematically analyze and calculate the structural characteristics, functional characteristics, stability and key species of the food web system.

[0021] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, wherein:

[0023] Figure 1 is a flowchart of a method for constructing a food web and analyzing its structural functions in a river ecosystem according to an embodiment of the present invention;

[0024] Figure 2 is an architecture diagram of a food web construction and structural function analysis in a river ecosystem according to an embodiment of the present invention;

[0025] Figure 3 is a structural schematic diagram of a food web construction and structural function analysis platform for river ecosystem according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0027] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solution in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0028] Figure 1 It is a flowchart of a method for constructing a food web and analyzing the structural functions of a river ecosystem according to an embodiment of the present invention.

[0029] As Figure 1 shown, the method includes but is not limited to the following steps:

[0030] S1. Obtain the measured results of the composition structure and biomass of the river ecosystem; wherein, the river ecosystem includes multiple components such as primary productivity, organic detritus, and different types of benthic animals.

[0031] It can be understood that the present invention can obtain the measured results of the composition structure and biomass (generally measured in ash-free dry weight, unit g·m -2 ) of primary productivity, organic detritus, and macroinvertebrate benthic animals (hereinafter referred to as benthic animals) in the river ecosystem based on field investigations and sample collections.

[0032] S2. Based on the classification library and relationship library of trophic groups, or based on the measured results of multiple measurement analysis methods, construct a predation matrix with benthic animals as the main body in the freshwater ecosystem; wherein, the predation matrix includes: a first predation matrix and a second predation matrix.

[0033] Specifically, S2 includes the following steps:

[0034] S21. In the absence of measured results such as gastrointestinal content analysis and stable isotope analysis, rely on the data accumulated in the "trophic group classification library" and the "trophic group relationship library" to assist in constructing the predation matrix. Among them, the "trophic group classification library" contains a list of common benthic animal genera at the genus level, and divides each genus-level group into trophic groups in the form of "order-level classification + functional feeding group"; the "trophic group relationship library" contains the pairwise predation relationships of all trophic groups in the "trophic group classification library", stored in the form of a 0-1 matrix. For example, matrix element A ij = 1 indicates that group j preys on group i, A ji= 0 indicates that trophic group i does not prey on trophic group j. In particular, for genus-level groups and / or trophic groups not included in the "trophic group relationship database" and (or) the "trophic group relationship database", the database needs to be supplemented and improved before the auxiliary construction of the predation matrix can be carried out.

[0035] S22. In the case of having measured results such as gastrointestinal content analysis and stable isotope analysis, rely on the measured results to construct the predation matrix.

[0036] The predation matrix constructed in step S21 / S22 is an n-order square matrix, representing the pairwise predation relationships among n trophic groups. All elements in the predation matrix are non-negative numbers, A ji = 0 indicates that trophic group i does not prey on trophic group j, A ij = 1 and A kj = 0.5 indicates that trophic group j preys on both trophic group i and trophic group k simultaneously, and the predation preference for trophic group i is twice that for k. In particular, this method conducts food web analysis based on the assumption of unidirectional predation, that is, there can only be a single-directional predation relationship between two trophic groups (if A ij > 0, then A ji = 0) and the same trophic group cannot prey on itself (A ii = 0). The levels of trophic groups in the predation matrix gradually decrease from top to bottom (or from left to right), so the predation matrix is a strictly lower triangular matrix.

[0037] S3. Based on the predation matrix, enumerate the food chains in the food web system to obtain a list of food chain tables, and calculate the structural characteristic parameters of the food web system.

[0038] Specifically, S3 includes the following steps:

[0039] S31. Calculate the trophic group richness index, that is, count the total number of trophic groups in this food web system;

[0040] S32. Calculate the food chain-related indices, that is, obtain the indices after counting the list of food chain tables, including the total number of complete food chains (number of food chains), the maximum length, average length, and minimum length of food chains (all counted by the number of trophic groups in the food chain).

[0041] S33. Calculate the connectivity index, that is, quantify the complexity of the food web, with a value between 0 and 1. The larger the value, the more complex the food web:

[0042]

[0043] Among them, Connectence is the connectivity, n is the trophic group richness, and L is the actual number of connections in the food web. Each connection represents a predation relationship between a pair of trophic groups.

[0044] S4. Combine the measured results of biomass and the characteristic parameters of trophic groups to calculate the trophic levels of each trophic group, so as to construct the input data of the food web analysis system.

[0045] Specifically, S4 includes the following steps:

[0046] S41. Based on the predation matrix constructed in S2 and combined with the measured biomass data, calculate the trophic levels of each trophic group:

[0047]

[0048] Among them, TL j is the trophic level of the predatory group j, TL i is the trophic level of the prey group i, and m i is the biomass of the prey group. At the same time, it is defined that the trophic levels of primary productivity and organic detritus are both 1. When calculating the trophic level, it is carried out sequentially from bottom to top (or from right to left) along the predation matrix.

[0049] S42. Based on the predation matrix constructed in S2, it is necessary to combine the measured biomass data and assign values to the characteristic parameters of each trophic group according to existing research data, actual observation results and / or expert experience, so as to construct the complete input data of the food web analysis system. The characteristic parameters of trophic groups include: a) Mortality rate, referring to the non-predatory mortality rate (unit yr -1 ), b) Assimilation rate, referring to the proportion of the actual assimilated food amount of the trophic group in the predation amount. Correspondingly, 1 - assimilation rate refers to the proportion of the food amount that is not assimilated and excreted through the digestive system after ingestion in the predation amount. c) Production utilization rate, referring to the proportion of the amount actually used for biomass growth of the trophic group in the assimilated amount. Correspondingly, 1 - production utilization rate refers to the proportion of the amount metabolically consumed (such as respiration) by the trophic group in the assimilated amount. d) Carbon-nitrogen ratio, referring to the ratio of organic carbon and organic nitrogen of the trophic group, which is used for carbon-nitrogen flux conversion. In particular, if the actual sampling is repetitive sampling, when providing the measured biomass data, it can be randomly generated through Monte Carlo simulation. The specific method is as follows: a) Based on the results of repetitive sampling, statistically analyze the mean and variance of the biomass of each trophic group; b) Assume that the biomass of each trophic group conforms to the gamma distribution, then based on the statistically obtained mean and variance, the probability distribution function of the biomass of each trophic group can be calculated; c) Based on the calculated probability distribution function, conduct Monte Carlo simulation to randomly generate the biomass of each trophic group and participate in the subsequent food web system analysis and calculation; d) Repeat step c) a finite number of times, and after statistically analyzing the results of each food web system analysis and calculation, the statistical values of the required characteristic indicators can be obtained.

[0050] S5. Based on the input data, solve the biomass fluxes of each trophic group according to the environmental carrying capacity of the trophic group to construct a biomass flux matrix.

[0051] Specifically, S5 includes the following steps:

[0052] S51. For each trophic group, establish a differential equation of biomass conservation. For primary productivity P:

[0053]

[0054] Among them, X P is the biomass of primary productivity (g·m -2 ), t is time (yr -1 ), r P is the intrinsic growth rate of primary productivity (yr -1 ), K P is the maximum environmental carrying capacity for primary productivity (g·m -2 ), assumed to be 2 times the measured X P value, f n (X P ) is the predation function of consumer group n on primary productivity (yr -1 ), X n is the biomass of consumer group n (g·m -2 ).

[0055] For organic detritus D:

[0056]

[0057] Among them, X D is the biomass of organic detritus (g·m -2 ), t is time (yr -1 ), R D is the inherent exogenous input amount (g·m -2 ·yr -1 ), d i is the non-predatory mortality rate of consumer group i (yr -1 ), X i is the biomass of consumer group i (g·m -2 ), K i is the maximum environmental carrying capacity for consumer group i (g·m -2 ), assumed to be 2 times the measured X i value, a j is the assimilation rate of consumer group j for food, f j (X i ) is the predation function of consumer group j on consumer group i (yr -1 ), X jFor the biomass of consumer group j (g·m -2 ), f n (X D ) is the predation function of consumer group n on organic detritus (yr -1 ), and X n is the biomass of consumer group n (g·m -2 ).

[0058] For consumer group j:

[0059]

[0060] Among them, X j is the biomass of consumer group j (g·m -2 ), t is time (yr -1 ), a j is the assimilation rate of consumer group j for food, p j is the production utilization rate of consumer group j for assimilated food, f j (X m ) is the predation function of consumer group j on consumer group m (yr -1 ), X m is the biomass of consumer group m (g·m -2 ), d j is the non-predation mortality rate of consumer group j (yr -1 ), K j is the maximum carrying capacity of the environment for consumer group j (g·m -2 ), assumed to be 2 times the measured X j value, f n (X j ) is the predation function of consumer group n on consumer group j (yr -1 ), X n is the biomass of consumer group n (g·m -2 ).

[0061] S52. Based on the "system balance assumption", it is considered that the food web system is in a dynamic equilibrium state, that is, the biomass of each trophic group in the system no longer changes. Then, the three differential equations in S51 are changed into ordinary equations:

[0062] For the primary productivity P:

[0063]

[0064] For the organic detritus D:

[0065]

[0066] For consumer group j:

[0067]

[0068] S53. Based on the "one-way predation hypothesis", it is considered that there can only be a single-directional predation relationship between two trophic groups and the same trophic group cannot prey on itself. Then, according to the top-down (or left-to-right) order of the predation matrix constructed in S2, the biomass fluxes of each trophic group can be calculated in the gradient order from high to low trophic levels. For example, for the top predator group 1, since there are no other groups preying on group 1, the predation amount of group 1 on other groups is:

[0069]

[0070] where X m is the biomass of consumer group m (g·m -2 ), f 1 (X m ) is the predation function of consumer group 1 on consumer group m (yr -1 ), X 1 is the biomass of consumer group 1 (g·m -2 ), d 1 is the non-predatory mortality rate of consumer group 1 (yr -1 ), K 1 is the maximum carrying capacity of the environment for consumer group 1 (g·m -2 ), assumed to be 2 times the measured X 1 value, a 1 is the assimilation rate of consumer group 1 for food, and p 1 is the production utilization rate of consumer group 1 for assimilated food.

[0071] The predation amount of trophic group 1 on group i is linearly allocated with the product of the predation matrix coefficient constructed in S2 and the measured biomass of group i as the weight:

[0072]

[0073] where X i is the biomass of consumer group i (g·m -2 ), f 1 (X i ) is the predation function of consumer group 1 on consumer group i (yr -1 ), X 1 is the biomass of consumer group 1 (g·m -2 ), w i1 is the predation matrix coefficient of consumer group 1 on group i, w m1 is the predation matrix coefficient of consumer group 1 on group m, X m is the biomass of consumer group m (g·m -2),f 1 (X m ) is the predation function of consumer group 1 on consumer group m (yr -1 ).

[0074] For consumer group 2 that is only preyed on by consumer group 1, its predation amount on other trophic groups is as follows:

[0075]

[0076] Among them, X m is the biomass of consumer group m (g·m -2 ), f 2 (X m ) is the predation function of consumer group 2 on consumer group m (yr -1 ), X 2 is the biomass of consumer group 2 (g·m -2 ), d 2 is the non-predatory mortality rate of consumer group 2 (yr -1 ), K 2 is the maximum carrying capacity of the environment for consumer group 2 (g·m -2 ), assumed to be 2 times the measured X 2 value, a 2 is the assimilation rate of consumer group 2 for food, p 2 is the production utilization rate of consumer group 2 for assimilated food, f 1 (X 2 ) is the predation function of consumer group 1 on group 2 (yr -1 ), X 1 is the biomass of consumer group 1 (g·m -2 ).

[0077] S54. According to the method described in S53, the total predation amount (g·m -2 ·yr -1 ) of each trophic group on other groups can be calculated in the order from the highest to the lowest trophic level, denoted as the array F, and the predation amount (g·m -2 ·yr -1 ) of each trophic group on a specific group, denoted as the matrix P). Among them, the array element F j represents the total predation amount of trophic group j on other groups, and the matrix element P ij represents the predation amount of trophic group j on group i. The matrix P is also called the biomass flux matrix.

[0078] S6. Based on the biomass flux matrix, construct a food web system matrix.

[0079] Specifically, S6 includes the following steps:

[0080] S61. Construct the Jacobian matrix El of the food web system, where the element El ij represents the action intensity of taxon j on taxon i:

[0081]

[0082] where, X i is the biomass of consumer taxon i (g·m -2 ), t is time (yr -1 ), X j is the biomass of consumer taxon j (g·m -2 ). For two consumer taxa, since only the predation relationship is considered for the interaction between taxa in this case, based on the "unidirectional predation assumption", there are the following three situations: a) If taxon i preys on taxon j, then El ij > 0 and El ji < 0; b) If taxon i is preyed on by taxon j, then El ij < 0 and El ji > 0; c) If there is no predation relationship between taxon i and taxon j, then El ij = El ji = 0.

[0083] S62. According to the calculation method given in S61, for two consumer taxa i and j, assuming that taxon j preys on taxon i, the corresponding Jacobian matrix elements El ij and El ji are respectively:

[0084]

[0085]

[0086] where, X i is the biomass of consumer taxon i (g·m -2 ), X j is the biomass of consumer taxon j (g·m -2 ), f j (X i ) is the predation function of consumer taxon j on consumer taxon i (yr -1 ), P ij is the predation amount of trophic taxon j on taxon i calculated according to S53 (g·m -2 ·yr -1 ), a j is the assimilation rate of consumer taxon j to food, and p j is the production utilization rate of consumer taxon j to the assimilated food.

[0087] S63. For the primary productivity P, assuming that the consumer group i preys on the primary productivity P, the corresponding elements El of the Jacobian matrix Pi and El iP are respectively:

[0088]

[0089]

[0090] Among them, X P is the biomass of the primary productivity P (g·m -2 ), X i is the biomass of the consumer group i (g·m -2 ), f i (X P ) is the predation function of the consumer group i on the primary productivity P (yr -1 ), P Pi is the predation amount of the trophic group i on the primary productivity P calculated according to S53 (g·m -2 ·yr -1 ), a i is the assimilation rate of the consumer group i to food, and p i is the production utilization rate of the consumer group i to the assimilated food.

[0091] S64. For the consumer group i and the primary productivity P, assuming that the intensity of its action on itself is linearly s times its non-predatory mortality rate, the corresponding elements El of the Jacobian matrix ii and El PP are respectively:

[0092] El ii =-sd i

[0093] El PP =-sd P

[0094] Among them, d i is the non-predatory mortality rate of the consumer group i (yr -1 ), and d P is the non-predatory mortality rate of the primary productivity P (yr -1 ). For the same food web system, it is assumed that the s values of each consumer group and the primary productivity are the same.

[0095] S65. For the organic detritus, it can be divided into coarse particulate organic detritus CD and fine particulate organic detritus FD according to its particle size. Assuming that the consumer group i preys on the coarse particulate organic detritus CD and the fine particulate organic detritus FD, the corresponding elements El of the Jacobian matrix CDi 、EliCD , El FDi and El iFD are respectively:

[0096]

[0097]

[0098]

[0099]

[0100] Among them, d i is the non - predatory mortality rate of consumer group i (yr -1 ), X i is the biomass of consumer group i (g·m -2 ), K i is the maximum carrying capacity of the environment for consumer group i (g·m -2 ), a i is the assimilation rate of consumer group i for food, f i (X j ) is the predation function of consumer group i on its preyed - upon trophic group j (including coarse particulate organic detritus CD and fine particulate organic detritus FD) (yr -1 ), a m is the assimilation rate of consumer group m that preys on consumer group i for food, f m (X i ) is the predation function of consumer group m on consumer group i (yr -1 ), X m is the biomass of consumer group m (g·m -2 ), X CD is the biomass of coarse particulate organic detritus CD (g·m -2 ), X FD is the biomass of fine particulate organic detritus FD (g·m -2 ), P ji is the predation amount of consumer group i on its preyed - upon trophic group j (including coarse particulate organic detritus CD and fine particulate organic detritus FD) calculated according to S53 (g·m -2 ·yr -1 ), P im is the predation amount of consumer group m on consumer group i calculated according to S53 (g·m -2 ·yr -1 ), p i is the production utilization rate of consumer group i for the assimilated food.

[0101] S66, for organic detritus (including coarse particulate organic detritus CD and fine particulate organic detritus FD), the elements El of the corresponding Jacobian matrix with primary productivity P CDP , El PCD , El FDP and El PFD are respectively:

[0102]

[0103] El PCD = 0

[0104]

[0105] El PFD = 0

[0106] where d P is the non-predatory mortality rate of primary productivity P (yr -1 ), X P is the biomass of primary productivity P (g·m -2 ), K P is the maximum carrying capacity of the environment for primary productivity P (g·m -2 ), a i is the assimilation rate of food by consumer group i that feeds on primary productivity P, f i (X P ) is the predation function of consumer group i on primary productivity P (yr -1 ), X CD is the biomass of coarse particulate organic detritus CD (g·m -2 ), X FD is the biomass of fine particulate organic detritus FD (g·m -2 ), P Pi is the predation amount of consumer group i on primary productivity P calculated according to S53 (g·m -2 ·yr -1 ).

[0107] S67, for coarse particulate organic detritus CD and fine particulate organic detritus FD, the elements El of the corresponding Jacobian matrix for their interaction CDFD and El FDCD are respectively:

[0108]

[0109]

[0110] where a i is the assimilation rate of food by consumer group i that feeds on coarse particulate organic detritus CD and fine particulate organic detritus FD, fi (X FD ) is the predation function of consumer group i on fine particulate organic detritus FD (yr -1 ), f i (X CD ) is the predation function of consumer group i on coarse particulate organic detritus CD (yr -1 ), X CD is the biomass of coarse particulate organic detritus CD (g·m -2 ), X FD is the biomass of fine particulate organic detritus FD (g·m -2 ), P FDi is the predation amount of consumer group i on fine particulate organic detritus FD calculated according to S53 (g·m -2 ·yr -1 ), P CDi is the predation amount of consumer group i on coarse particulate organic detritus CD calculated according to S53 (g·m -2 ·yr -1 ).

[0111] S68. For coarse particulate organic detritus CD and fine particulate organic detritus FD, the Jacobian matrix elements El CDCD and El FDFD corresponding to their self-action intensities are respectively:

[0112]

[0113]

[0114] Among them, a i is the assimilation rate of consumer group i that feeds on coarse particulate organic detritus CD and fine particulate organic detritus FD, f i (X FD ) is the predation function of consumer group i on fine particulate organic detritus FD (yr -1 ), f i (X CD ) is the predation function of consumer group i on coarse particulate organic detritus CD (yr -1 ), X CD is the biomass of coarse particulate organic detritus CD (g·m -2 ), X FD is the biomass of fine particulate organic detritus FD (g·m -2 ), P FDi is the predation amount of consumer group i on fine particulate organic detritus FD calculated according to S53 (g·m -2 ·yr -1 ), P CDiThe predation amount of consumer group i on coarse particulate organic detritus CD (g·m -2 ·yr -1 ).

[0115] S7. Based on the food web system matrix, solve the index of the food web system stability under preset conditions.

[0116] Specifically, S7 includes the following steps:

[0117] S71. Given the initial values s 1 = 0 and s 2 = 1, respectively use s 1 and s 2 to substitute the s value in the Jacobian matrix El constructed by S6, and obtain El 1 and El 2 . Calculate the eigenvalues of El 1 and El 2 , and assume that the real parts corresponding to their largest eigenvalues are EV 1 and EV 2 .

[0118] S72. Judge the positive and negative of EV 1 and EV 2 , and accordingly adjust the assignment of s 1 and s 2 . Specifically: a) If EV 1 < 0 and EV 2 < 0, then reduce s 1 again and assign it as s 1 –0.5×(s 2 –s 1 ); b) If EV 1 > 0 and EV 2 > 0, then enlarge s 2 again and assign it as s 2 +0.5×(s 2 –s 1 ); c) If EV 1 > 0 and EV 2 < 0, then reassign s 1 as 0.5×(s 1 +s 2 ).

[0119] S73. Repeat the above steps and end the calculation when one of the following four situations occurs: a) When EV 1 = 0 or EV 2 = 0, the food web system stability characteristic index s c is equal to the corresponding s 1 or s2 value; b) When EV 1 > 0 and EV 2 < 0 and s 2 –s 1 < 0.001 (or other custom small value), the stability characteristic index s of the food web system c = 0.5×(s 1 + s 2 ); c) When s 1 is too small or s 2 is too large and the corresponding EV 1 or EV 2 cannot be solved, the food web system is unstable; d) When the number of repeated calculations exceeds 1,000,000 times (or other custom large value), the food web system is unstable.

[0120] S74, the s value calculated from S73 can quantitatively characterize the stability characteristics of the food web system: the smaller the s c value, the higher the stability of the food web system. c The smaller the value, the higher the stability of the food web system.

[0121] S8, select a single trophic group, adjust the biomass proportion of the single trophic group, and calculate the change in the stability of the food web system successively to quantify the importance of the single trophic group to the food web system.

[0122] Specifically, S8 includes the following steps:

[0123] S81, select the trophic group i in the food web system and construct a biomass gradient vector V at intervals of 10% i = {X i , 90%X i , 80%X i , 70%X i , 60%X i , 50%X i , 40%X i , 30%X i , 20%X i , 10%X i , 0}.

[0124] S82, according to the method given in S42, reconstruct the complete input data of the food web analysis system. Among them, the biomass of the trophic group i is set along the V i gradient direction, and other data are not adjusted.

[0125] S83, according to the methods given in S5–S7, calculate the stability S c value of the food web system under the input settings of S82.

[0126] S84, along Vi Adjust the biomass input value of trophic group i in the changing direction, repeat S82–S83, and calculate the food web system stability vector S corresponding to V i . ci Using V i as the abscissa and S ci as the ordinate, plot a line graph to obtain the response law of the food web system stability to the biomass change of trophic group i.

[0127] In S85, reselect another trophic group j in the food web system, repeat S81–S84, and obtain the response law of the food web system stability to the biomass change of trophic group j.

[0128] In S86, compare the stability response curves of trophic groups i and j, and compare the importance levels of trophic groups i and j to the food web system stability. The importance level is jointly affected by two factors: trophic group and biomass change ratio. At a certain determined biomass change ratio (e.g., the biomass of both trophic groups i and j drops to 80% of the original biomass): a) If S ci <S cj <S c0 , then the reduction of the biomass of both trophic groups i and j will cause the improvement of the food web system stability, and the importance level of trophic group i to the food web system is higher than that of trophic group j; b) If S ci <S c0 <S cj and |S ci –S c0 |>|S cj –S c0 |, then the reduction of the biomass of trophic group i will cause the improvement of the food web system stability, while the reduction of the biomass of trophic group j will cause the reduction of the food web system stability, and the importance level of trophic group i to the food web system is higher than that of trophic group j; c) If S ci >S cj >S c0 , then the reduction of the biomass of both trophic groups i and j will cause the reduction of the food web system stability, and the importance level of trophic group i to the food web system is higher than that of trophic group j. Among them, S ci , S cj , and S c0 are the food web system stabilities after the biomass change of trophic group i, after the biomass change of trophic group j, and the original one, respectively.

[0129] In S87, according to the method given in S85–S86, compare the importance levels of all trophic groups to the food web system stability, and identify the trophic group with the highest importance level as the key trophic group of this food web system.

[0130] Further, the overall architecture diagrams of S1–S8 are as shown in Figure 2 the following figures.

[0131] According to the method for constructing a food web of a river ecosystem and analyzing its structural functions according to an embodiment of the present invention, a food web system of a sampling point can be quickly constructed, and the structural characteristics, functional characteristics, stability, and key species of the food web system can be systematically analyzed and calculated.

[0132] To implement the above embodiments, as shown in Figure 3 the following figures, in this embodiment, a platform 10 for constructing a food web of a river ecosystem and analyzing its structural functions is further provided. The platform 10 includes: a data acquisition module 100, a predation matrix construction module 200, a characteristic parameter calculation module 300, an input data construction module 400, a flux matrix construction module 500, a food web system matrix construction module 600, a stability index solution module 700, and an importance quantification module 800.

[0133] The data acquisition module 100 is configured to obtain the measured results of the composition structure and biomass of a river ecosystem; wherein, the river ecosystem includes primary productivity, organic detritus, and various types of benthic animals.

[0134] The predation matrix construction module 200 is configured to construct a predation matrix mainly composed of benthic animals in a freshwater ecosystem based on a classification library and a relationship library of trophic groups, or based on the measured results of various measurement analysis methods; wherein, the predation matrix includes: a first predation matrix and a second predation matrix.

[0135] The characteristic parameter calculation module 300 is configured to enumerate the food chains in the food web system based on the predation matrix to obtain a food chain list, and calculate the structural characteristic parameters of the food web system.

[0136] The input data construction module 400 is configured to calculate the trophic levels of each trophic group by combining the measured results of biomass and the characteristic parameters of the trophic groups, so as to construct the input data of the food web analysis system.

[0137] The flux matrix construction module 500 is configured to solve the biomass flux of each trophic group based on the input data according to the carrying capacity of the environment for the trophic groups, so as to construct a biomass flux matrix.

[0138] The food web system matrix construction module 600 is configured to construct a food web system matrix based on the biomass flux matrix.

[0139] The stability index solution module 700 is configured to solve the index of the food web system stability under preset conditions based on the food web system matrix.

[0140] The importance quantification module 800 is used to select a single trophic group, adjust the biomass proportion of the single trophic group, and successively calculate the changes in the stability of the food web system, so as to quantify the importance of the single trophic group to the food web system.

[0141] According to the food web construction and structural function analysis platform of the river ecosystem in the embodiment of the present invention, the food web system of the sampling point can be quickly constructed, and the structural characteristics, functional characteristics, stability and key species of the food web system can be systematically analyzed and calculated.

[0142] It should be noted that the foregoing explanation of the embodiments of the method for constructing and analyzing the structural function of the food web of the river ecosystem also applies to the food web construction and structural function analysis platform of the river ecosystem in this embodiment, and will not be repeated here.

[0143] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0144] In the description of this specification, the description with reference to terms such as "an embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0145] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for constructing a food web of a river ecosystem and analyzing its structural functions, characterized in that, it includes the following steps: S1. Obtain the measured results of the composition structure and biomass of the river ecosystem; wherein, the river ecosystem includes multiple of primary productivity, organic detritus, and different types of benthic animals; S2. Based on the classification library and relationship library of trophic groups, construct a predation matrix with the benthic animals as the main body in the freshwater ecosystem; wherein, the predation matrix is the first predation matrix; wherein, the trophic group classification library includes: dividing each genus-level group in the genus-level list of benthic animals into trophic groups based on order-level classification and functional feeding groups; the trophic group relationship library includes: the pairwise predation relationships of all trophic groups in the trophic group classification library, stored in the form of a 0-1 matrix; in the case of having the measured results of the multiple measurement analysis methods, construct a second predation matrix according to the measured results; wherein, both the first predation matrix and the second predation matrix are n-order square matrices, representing the pairwise predation relationships between n trophic groups; S3. Based on the predation matrix, enumerate the food chains in the food web system to obtain a food chain list, and calculate the structural characteristic parameters of the food web system; S4. Combine the measured results of the biomass and the characteristic parameters of the trophic groups to calculate the trophic levels of each trophic group to construct the input data of the food web analysis system; S5. Based on the input data, solve the biomass fluxes of each trophic group according to the environmental carrying capacity for the trophic groups to construct a biomass flux matrix; wherein, the biomass flux matrix includes at least the flux of organic detritus; S6. Based on the biomass flux matrix, construct a food web system matrix; wherein, the food web system matrix includes at least organic detritus; S7. Based on the food web system matrix, solve the index of the stability of the food web system under preset conditions; S8. Select a single trophic group, adjust the biomass proportion of the single trophic group, and successively calculate the changes in the stability of the food web system to quantify the importance of the single trophic group to the food web system; S5 further includes: S51. For each trophic group, establish a differential equation for biomass conservation. For primary productivity P it is as follows: Among them, X P is the biomass of primary productivity, t is time, r P is the intrinsic growth rate of primary productivity, K P is the maximum carrying capacity of the environment for primary productivity, assumed to be 2 times the measured X P value, f n ( X P ) is the predation function of the consumer group n on primary productivity, X n is the biomass of the consumer group n ; For organic debris D it is the case that: wherein, X D is the biomass of organic detritus, t is time, R D is the inherent exogenous input amount, d i is the consumer group i of non-predatory mortality rate, X i is the consumer group i of biomass, K i is the environment's maximum carrying capacity for the consumer group i , assumed to be 2 times the measured X i value, is the consumer group j of food assimilation rate, f j ( X i ) is the consumer group j of the consumer group i of the predation function, X j is the consumer group j of biomass, f n ( X D ) is the consumer group n of the predation function on organic detritus, X n is the consumer group n of biomass; For the consumer group j : where, X j is the biomass of the consumer group j ; t is time; is the assimilation rate of the consumer group j to food; p j is the production utilization rate of the consumer group j to the assimilated food; f j ( X m ) is the predation function of the consumer group j to the consumer group m ; X m is the biomass of the consumer group m ; d j is the non-predation mortality rate of the consumer group j ; K j is the maximum carrying capacity of the environment for the consumer group j , assumed to be twice the measured X j value; f n ( X j ) is the predation function of the consumer group n to the consumer group j ; X n is the biomass of the consumer group n ; S52. Based on the preset system balance, transform the three differential equations in S51 into ordinary equations: For primary productivity P it is the case that: For organic debris D it is the case that: For consumer groups j For: S53. Based on the one-way predation assumption, it is considered that there can only be a single-directional predation relationship between two trophic groups and the same trophic group cannot prey on itself, then calculate the biomass fluxes of each trophic group in the top-down order of the predation matrix constructed in S2 along the gradient order of decreasing trophic level; S54. According to the method of S53, calculate the total predation amount of each trophic group on other groups in the order from high to low trophic level, denoted as an array F , and the predation amount of each trophic group on a specific group, denoted as a matrix P； where the array element F j represents the total predation amount of the trophic group j on other groups, and the matrix element P ij represents the predation amount of the trophic group j on the group i , and the matrix P is also called the biomass flux matrix; S6 further includes: S61, constructing the Jacobian matrix of the food web system El , where the element El ij represents the action intensity of taxon j on taxon i : Among them, X i is the biomass of the consumer group i , t is time, X j is the biomass of the consumer group j .

2. The method according to claim 1, characterized in that, S6 further includes: S62. According to the calculation method given in S61, for two consumer groups i and j , assuming that the group j predates on the group i , then the corresponding Jacobian matrix elements El ij and El ji are respectively: Among them, X i is the biomass of the consumer group i . X j is the biomass of the consumer group j . f j ( X i ) is the predation function of the consumer group j on the consumer group i . P ij is the predation amount of the trophic group j for the group i calculated according to S53, is the assimilation rate of the consumer group j to food, p j is the production utilization rate of the consumer group j to the assimilated food; S63, for primary productivity P , assuming the consumer group i predates on the primary productivity P , then the corresponding Jacobian matrix elements El Pi and El iP are respectively: Among them, X P is the primary productivity P biomass, X i is the biomass of the consumer group i biomass, f i ( X P ) is the consumer group i for the primary productivity P predation function, P Pi is the trophic group calculated according to S53 i for the primary productivity P predation amount, is the consumer group i assimilation rate of food, p i is the consumer group i production utilization rate of assimilated food; S64, for the consumer group i and primary productivity P , assuming that the intensity of its effect on itself is linear to its non-predatory mortality s times, then the corresponding Jacobian matrix elements El ii and El PP are respectively: Among them, d i is the non-predation mortality rate of the consumer group i , d P is the non-predation mortality rate of the primary productivity P . For the same food web system, it is assumed that the s values of each consumer group and the primary productivity are the same; S65. For organic detritus, it is divided into coarse particulate organic detritus CD and fine particulate organic detritus FD . Assuming that the consumer group i predates on coarse particulate organic detritus CD and fine particulate organic detritus FD , then the corresponding elements of the Jacobian matrix El CDi , El iCD , El FDi and El iFD are respectively: Among them, d i is the non-predatory mortality rate of the consumer group i , X i is the biomass of the consumer group i , K i is the maximum carrying capacity of the environment for the consumer group i , is the assimilation rate of the consumer group i to food, f i ( X j ) is the predation function of the consumer group i on the trophic group j it preys on, is the assimilation rate of the consumer group i that feeds on the consumer group m to food, f m ( X i ) is the predation function of the consumer group m on the consumer group i , X m is the biomass of the consumer group m , X CD is the biomass of coarse particulate organic detritus CD , X FD is the biomass of fine particulate organic detritus FD , P ji is the predation amount of the consumer group i calculated according to S53 for the trophic group j it preys on, P im is the predation amount of the consumer group m calculated according to S53 on the consumer group i , p i is the production utilization rate of the consumer group i for the assimilated food; S66, for organic detritus, the corresponding Jacobian matrix elements with primary productivity P are El CDP , El PCD , El FDP and El PFD respectively as follows: Among them, d P is the primary productivity P of the non-predatory mortality rate, X P is the primary productivity P of the biomass, K P is the maximum carrying capacity of the environment for the primary productivity P ; is the assimilation rate of the consumer group P that feeds on the primary productivity i for food, f i ( X P ) is the predation function of the consumer group i on the primary productivity P ; X CD is the biomass of the coarse particulate organic detritus CD ; X FD is the biomass of the fine particulate organic detritus FD ; P Pi is the predation amount of the consumer group i on the primary productivity P calculated according to S53; S67, for coarse particulate organic debris CD and fine particulate organic debris FD , the Jacobian matrix elements corresponding to the interaction El CDFD and El FDCD are respectively: Among them, is the consumer group that feeds on coarse particulate organic detritus CD and fine particulate organic detritus FD The assimilation rate of food by i f i ( X FD ) is the consumer group i The predation function on fine particulate organic detritus FD f i ( X CD ) is the consumer group i The predation function on coarse particulate organic detritus CD X CD is the biomass of coarse particulate organic detritus CD X FD is the biomass of fine particulate organic detritus FD P FDi is the predation amount of the consumer group i on fine particulate organic detritus FD calculated according to S53, P CDi is the predation amount of the consumer group i on coarse particulate organic detritus CD calculated according to S53;​​​​​ S68, for coarse particulate organic debris CD and fine particulate organic debris FD , the Jacobian matrix elements corresponding to the intensity of their own action El CDCD and El FDFD are respectively: Among them, is the consumer group that feeds on coarse particulate organic detritus CD and fine particulate organic detritus FD The assimilation rate of food for i the consumer group, f i ( X FD ) is the predation function of the consumer group i on fine particulate organic detritus FD , f i ( X CD ) is the predation function of the consumer group i on coarse particulate organic detritus CD , X CD is the biomass of coarse particulate organic detritus CD , X FD is the biomass of fine particulate organic detritus FD , P FDi is the predation amount of the consumer group i on fine particulate organic detritus FD calculated according to S53, P CDi is the predation amount of the consumer group i on coarse particulate organic detritus CD calculated according to S53.

3. The method according to claim 1, characterized in that, S3 includes: S3.

1. Based on the food web system, calculate the richness index of the trophic groups; S3.

2. Calculate the relevant indicators of the food chain based on the food chain list; wherein, the relevant indicators of the food chain include the number of complete food chains, the maximum length, the average length, and the minimum length of the food chains. S3.

3. Quantify the complexity of the food web system and calculate the connectance index, with a value between 0 and 1: Among them, Connectence is the connectivity degree, n is the trophic group richness, L is the actual number of connections existing in the food web, and each connection represents a predation relationship existing between a pair of trophic groups.

4. According to the method described in claim 1, wherein, S4 further includes: S4.

1. Calculate the trophic levels of each trophic group based on the predation matrix and in combination with the measured results of the biomass; Among them, TL j is the trophic level of the predator group j ; TL i is the trophic level of the prey group i ; m i is the biomass of the prey group. The trophic levels of primary productivity and organic detritus are both 1; S4.

2. If the actual sampling is repetitive sampling, randomly generate it through Monte Carlo simulation when providing the measured results of the biomass: a) Based on the repetitive sampling results, statistically analyze the mean and variance of the biomass of each trophic group; b) Assume that the probability distribution of the biomass of each trophic group is a gamma distribution, and calculate the probability distribution function based on the statistically obtained mean and variance; c) Based on the probability distribution function, conduct Monte Carlo simulation to randomly generate the biomass of each trophic group, and conduct food web system analysis and calculation; d) Repeat step c) a preset number of times, and after statistically analyzing the results of multiple food web system analysis and calculations, obtain the statistical value of the characteristic index.

5. According to the method described in claim 1, wherein, S7 includes: S7.1, Given the initial values s 1 = 0 and s 2 = 1, and respectively use s 1 and s 2 to substitute the values in the Jacobian matrix constructed by S6 El in s to respectively obtain El 1 and El 2 ; Calculate El 1 and El 2 for the eigenvalues, and assume that the real parts corresponding to their largest eigenvalues are respectively EV 1 and EV 2 ; S7.2, determine the positive and negative of EV 1 and EV 2 , and make corresponding adjustments to the assignment of s 1 and s 2 : a) If EV 1 < 0 and EV 2 < 0, then reduce s 1 again and assign it as s 1 – 0.5 × ( s 2 – s 1 ); b) If EV 1 > 0 and EV 2 > 0, then enlarge s 2 again and assign it as s 2 + 0.5 × ( s 2 – s 1 ); c) If EV 1 > 0 and EV 2 < 0, then re - assign s 1 as 0.5 × ( s 1 + s 2 ); S7.

3. Repeat the above steps and end the calculation when one of the following four situations occurs: a) When EV 1 = 0 or EV 2 = 0, the stability characteristic index s c of the food web system is equal to the corresponding s 1 or s 2 value with the real part of the largest eigenvalue being 0; b) When EV 1 > 0 and EV 2 < 0 and s 2 – s 1 < 0.001, the stability characteristic index s c of the food web system = 0.5 × ( s 1 + s 2 ); c) When s 1 is less than the first threshold or s 2 is greater than the second threshold and the corresponding EV 1 or EV 2 cannot be solved, the food web system is unstable; d) When the number of repeated calculations exceeds the preset number, the food web system is unstable; S7.4, which is calculated from S7.3 s c The value is quantified to characterize the stability characteristics of the food web system.

6. According to the method described in claim 1, wherein, S8 includes: S8.1, select the trophic groups in the food web system i , construct a biomass gradient vector at 10% intervals V i = { X i , 90% X i , 80% X i , 70% X i , 60% X i , 50% X i , 40% X i , 30% X i , 20% X i , 10% X i , 0}; S8.2, reconstruct the complete input data of the food web analysis system according to the steps of S4.2; among them, the biomass of the i trophic group is set along the V i gradient direction. S8.

3. Calculate the stability of the food web system under the input settings of S8.2 according to the steps of S5–S7. S c Value; S8.4, along V i the changing direction, adjust the biomass input value of the trophic group i and repeat S8.2–S8.3 to calculate the food web system stability vector corresponding to V i ; S ci ; S8.5, reselect other trophic groups in the food web system j , repeat S8.1–S8.4 to obtain the response law of the food web system stability to the j biomass change of trophic groups; S8.6, Compare trophic groups i and j 's stability response curves to determine the relative importance of trophic groups i and j to the stability of the food web system; S8.

7. According to the steps of S8.5–S8.6, compare the importance levels of all trophic groups to the stability of the food web system, and identify the trophic group with the highest importance level as the key trophic group of the food web system.

7. According to the method described in claim 1, wherein, S5.3 includes: For the top predator group 1, the predation amount of group 1 on other groups is: Among them, f 1 ( X m ) is the predation function of consumer group 1 on consumer group m . X 1 is the biomass of consumer group 1, d 1 is the non-predation mortality rate of consumer group 1, K 1 is the maximum carrying capacity of the environment for consumer group 1, assumed to be 2 times the measured X 1 value, is the assimilation rate of consumer group 1 for food, p 1 is the production utilization rate of consumer group 1 for assimilated food; Predation amount of trophic group 1 on the group i is linearly allocated with the product of the predation matrix coefficient and the measured biomass of the group i as the weight: Among them, f 1 ( X i ) is the predation function of consumer group 1 on consumer group i , and w i1 is the predation matrix coefficient of consumer group 1 on group i , and w m1 is the predation matrix coefficient of consumer group 1 on group m . For the consumer group 2 that is only preyed on by the consumer group 1, its predation amount on other trophic groups is: Among them, f 2 ( X m ) is the predation function of consumer group 2 on consumer group m . The predation function X 2 is the biomass of consumer group 2, d 2 is the non-predation mortality rate of consumer group 2, K 2 is the maximum carrying capacity of the environment for consumer group 2, assumed to be twice the measured X 2 value, is the assimilation rate of consumer group 2 for food, p 2 is the production utilization rate of consumer group 2 for assimilated food, f 1 ( X 2 ) is the predation function of consumer group 1 on group 2.

8. A river ecosystem food web construction and structural function analysis platform based on the method described in claim 1, wherein, it includes: A data acquisition module for acquiring the composition structure of the river ecosystem and the measured results of the biomass; wherein, the river ecosystem includes multiple components such as primary productivity, organic detritus, and different types of benthic animals. A predation matrix construction module for constructing a predation matrix mainly based on the benthic animals in the freshwater ecosystem based on the classification library and relationship library of trophic groups; wherein, the predation matrix is the first predation matrix. A characteristic parameter calculation module for enumerating the food chain list in the food web system based on the predation matrix and calculating the structural characteristic parameters of the food web system. An input data construction module for calculating the trophic levels of each trophic group by combining the measured results of the biomass and the characteristic parameters of the trophic groups to construct the input data of the food web analysis system. A flux matrix construction module, which is used to solve the biomass fluxes of the respective trophic groups based on the carrying capacity of the environment for the trophic groups according to the input data, so as to construct a biomass flux matrix; A food web system matrix construction module, which is used to construct a food web system matrix based on the biomass flux matrix; A stability index solving module, which is used to solve the index of the stability of the food web system under preset conditions based on the food web system matrix; An importance quantification module, which is used to select a single trophic group, adjust the biomass proportion of the single trophic group, and calculate the changes in the stability of the food web system successively, so as to quantify the importance of the single trophic group to the food web system.

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