A method for evaluating and optimizing food webs in marine ecosystems

Abstract

The present invention belongs to the technical field of marine ecosystem research, and relates to a method for evaluating and optimizing the food web of a marine ecosystem. The method for evaluating the food web system of the ecosystem includes the following steps: S1, constructing an energy flow model of the food web of the marine ecosystem; S2, based on the above-established food web energy flow model, obtaining the energy flow relationship between each biological functional group, and quantifying the nutritional relationship and energy flow relationship between each organism in the marine ecosystem; for the target marine ecosystem, selecting other marine ecosystems with similar characteristics to the target marine ecosystem as controls, establishing a control marine ecosystem food web parameter database, and comparing it with the indicators of the control marine ecosystem food web structure and function evaluation to determine the level of the target marine ecosystem food web structure and function. The present invention has formulated a set of more scientific food web structure optimization paths to provide guidance for the development of food web optimization work.

Description

Technical Field

[0001] The present invention belongs to the technical field of marine ecosystem research, and relates to a marine ecological restoration and management method, and specifically to a marine ecosystem food web evaluation and optimization method. Background Art

[0002] The large individuals, high trophic levels, and important bottom economic species in the ecosystem are replaced by small individuals, low trophic levels, and lower middle and upper economic value species, resulting in a significant decline in the average trophic level of the ecosystem's fishery organisms, the loss of important node organisms in the ecosystem's food web, the break of the original food chain structure of the ecosystem, and the simplification of the food web structure. The food web dominates the flow of matter and energy in the ecosystem, drives primary and secondary production, waste decomposition, nutrient recovery and other processes, and is a core component of the ecosystem. The destruction of the food web of the offshore ecosystem has led to a reduction in the diversity, stability, and sustainability of the ecosystem, and the degradation of the ecosystem structure and function.

[0003] Carrying out the reproduction and release of marine biological resources to repair the food web structure of the marine ecosystem, and then repairing marine biological resources and improving the structure and function of the ecosystem, is one of the main ways to repair and conserve marine biological resources in my country. Most food web restoration activities based on resource reproduction only focus on the reproduction of a single species, and do not comprehensively consider the optimization effect of resource reproduction on the food web of the ecosystem from the different trophic levels of the ecosystem. It is easy to produce ecological consequences of losing one thing while focusing on another, and cannot achieve the effect of effectively optimizing the food web of the ecosystem. The unreasonable reproduction of a large number of marine aquatic biological seedlings leads to low efficiency of marine biological reproduction and release, overlapping ecological niches of reproduction organisms and wild species in the ecosystem, and the occupation of biological source elements and physical space by a large number of reproduction organisms. The number of wild populations is reduced, and the level of biological genetic diversity and environmental adaptability are reduced, which ultimately leads to further simplification of the food web structure and even causes the collapse of wild biological population resources. Comprehensively evaluating the food web structure of the marine ecosystem based on the ecosystem level, scientifically selecting the reproduction target species, and accurately evaluating the suitable reproduction density of the target species are important foundations for optimizing the food web structure of the marine ecosystem and improving the structure and function of the ecosystem, and play an important role in repairing and conserving my country's offshore marine biological resources.

[0004] At present, there is no effective technical method for optimizing the food web of marine ecosystems. Only Zheng Ting's master's thesis "Key Food Web Restoration Technology of Bohai Bay Nearshore Ecosystem" at Tianjin University in 2013 has a record of research on the restoration of the food web of Bohai Bay nearshore ecosystem. The study mainly used a method based on artificial reefs and hard slope roughening to restore the food web structure. This method is to restore the food web by restoring the marine habitat, but this method is costly and can only be carried out in small-scale offshore waters. Summary of the invention

[0005] One of the purposes of the present invention is to address the insufficient assessment of ecosystem food web characteristics and the lack of effective methods for assessing food web structure and function in current marine ecosystem food web restoration activities. The present invention establishes an ecosystem food web evaluation method.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] An ecosystem food web system evaluation method comprises the following steps:

[0008] S1. Construct a model of energy flow in the food web of marine ecosystems;

[0009] S2. Based on the food web energy flow model established above, quantify the nutritional relationship and energy flow relationship between organisms in the marine ecosystem; for the target marine ecosystem, select other marine ecosystems with similar characteristics to the target marine ecosystem as controls, and compare them with the indicators of food web structure and function evaluation of the control marine ecosystem to determine the level of food web structure and function of the target marine ecosystem, and then determine the modules that need to be further optimized and improved in the target marine ecosystem.

[0010] The method for constructing the marine ecosystem food web energy flow model comprises the following steps:

[0011] S11. Organisms are divided into functional groups according to the functions they perform in the marine ecosystem;

[0012] Functional groups are divided according to the functions that each organism performs in the marine ecosystem. Functional groups can be plankton, organic debris, a type of fish, a type of fish at a certain age, or a type of species with similar ecological characteristics. The niche characteristics such as the feeding habits, habitat space, movement patterns, and population structure of each organism in the marine ecosystem, the ratio of production to biomass, the ratio of food intake to biomass, and morphological characteristics are used as the basis for determining the functions that each organism performs in the ecosystem.

[0013] For species that require special attention or organisms that have a significant impact on the structure and function of marine ecosystems, their functional group division should be as detailed as possible.

[0014] Marine ecosystem functional groups should include three functional groups: primary producers, consumers and organic debris, and should cover all biological and organic components in the marine ecosystem.

[0015] S12. Through conducting surveys on biological resources in marine ecosystems, collecting fishery catch data, and consulting literature, obtain data on various biological functional groups in marine ecosystems: including biomass of each biological functional group, ratio of production to biomass, ratio of food intake to biomass, biomass accumulation, migration, catch, food composition of each consumer organism, and proportion of undigested food;

[0016] S13, using the acquired data of each biological function group as input data, and establishing a marine ecosystem energy flow model based on the Ecopath model construction principle;

[0017] S14. Check and debug the energy balance of marine ecosystems.

[0018] Specifically, the specific basis for testing and debugging the energy balance of the marine ecosystem is to maintain a balance between the material or energy input and output of a certain biological functional group in the ecosystem, which is expressed by the following formula:

[0019]

[0020] in, B i Indicates functional group i of biomass; B j Indicates predator j of biomass; P / B) i Indicates functional group i The ratio of production to biomass; Q / B) j Indicates predator j The ratio of food intake to biomass; EE i Indicates functional group i Eco-nutrition efficiency; DC ji Indicates functional group i In Predator j The proportion of food in the diet; BA i Indicates functional group i bioaccumulation; Y i Indicates functional group i the amount of catch or harvest; E i Indicates functional group i The net migration of

[0021]

[0022] in, R i Indicates functional groupi The amount of breathing; U i Indicates functional group i The amount of undigested food.

[0023] Specifically, the method for debugging the established energy flow model is as follows: adjust the EE value by changing the food matrix, and the change of the food ratio each time does not exceed 5%, so that the EE value of each biological functional group is less than or equal to 1, and the ratio of production to respiration of each functional group P / R is not greater than 1. The biological functional group with greater swimming animal activity has a greater ratio of respiration to biomass R / B than the biological functional group with less attached organism activity. The food conversion efficiency of each biological functional group, the ratio of production to food intake P / Q, is between 0.1-0.3.

[0024] Furthermore, in S2, the indicators for evaluating the structure and function of the food web include: food web energy flow diversity index, average food chain path length, energy transfer efficiency between different integer trophic levels of the ecosystem; it can also include system connectivity index, system omnivory index, Finn's circulation index, average trophic level of fish catch, ratio of debris flow to herbivory flow, relative dominance, total primary production / total respiration, total primary production / total biomass, total biomass / total energy flow.

[0025] As a preferred method, in S2, based on the established food web energy flow model, the energy flow relationship between each biological functional group is obtained, and the food web structure and function are evaluated, mainly evaluating the diversity of the food web structure and the energy transfer efficiency between different trophic levels of the food web. Among them, the characterization parameters of diversity are: energy flow diversity index (i.e., food web energy flow diversity H) and average food chain path length (FML), and the characterization parameters of energy transfer efficiency are: energy transfer efficiency values ​​between different integer trophic levels of the ecosystem. That is, the three indicators of energy flow diversity index, average food chain path length, and energy transfer efficiency between different integer trophic levels of the ecosystem are used to evaluate the structure and function of the food web.

[0026] Among them, the diversity of food web energy flow ( H ) The calculation method of the index is:

[0027]

[0028] Q i Represents the flow of a unit of matter or energy through a functional group in an ecosystem ( i ) possibility.

[0029] The mean food chain path length (FML) is calculated as: FML=L / P , Lrepresents the number of all connection points in the food web, P Represents the number of all food chain paths in the food web.

[0030] The calculation method of the energy transfer efficiency from a certain trophic level to its adjacent higher trophic level in an ecosystem, that is, the energy transfer efficiency between different integer trophic levels in an ecosystem, is:

[0031] TE=(TC+TF) / (TR+TFL+TBI+TF+TC)

[0032] in, TE represents the energy transfer efficiency, TC represents the total food intake of organisms at this trophic level, TF represents the total catch at this trophic level, TR represents the total respiration of organisms at this trophic level, TFL It indicates the total amount of debris flowing to the organisms at this trophic level. TBI It represents the total biomass accumulation of this trophic level.

[0033] Furthermore, the present invention also provides a method for optimizing the food web of a marine ecosystem, which is as follows: when the evaluation indicators of the structure and function of the food web of a target marine ecosystem are worse than the range values ​​of the control ecosystem, it indicates that there is room for optimization of the ecosystem, and the structure and function of the food web can be optimized by respectively improving the values ​​of relevant indicators.

[0034] For example, three indicators, namely, the diversity of energy flow in the food web, the average food chain path length, and the energy transfer efficiency, are selected to characterize the structure and function of the food web. When the values ​​of one or several indicators are relatively low compared with the range values ​​of the control ecosystem, indicating that the ecosystem has room for optimization, the structure and function of the food web can be optimized by increasing the values ​​of the relevant indicators. The specific improvement methods are: when the diversity of energy flow in the food web of the ecosystem is low, the diversity of the food chain of the ecosystem is improved by increasing the biomass of the functional groups with more connections with other organisms in the medium effective trophic level (generally 2 and 3 effective trophic levels), thereby improving the diversity of energy flow in the food web of the ecosystem; when the average food chain path length of the ecosystem is low, the length of the food chain is improved by increasing the biomass of the top predators of the ecosystem; when the energy transfer efficiency between different integer trophic levels in the food web of the ecosystem is low, the energy transfer efficiency is improved by increasing the biomass of the predators in the ecosystem that flow to the functional groups with larger detritus. Furthermore, the method of increasing the biomass can be enhancement and release.

[0035] The calculation method of effective trophic level is: TL j =1+∑ i ( DC ij × TL i )

[0036] TL j Represents functional group ( j ) trophic level, TL i Represents functional group ( i ) trophic level, DC ij Represents the prey ( i ) in the predator ( j ) in the food composition.

[0037] The effective trophic level categories of each functional group are divided as follows: 1-1.5 (excluding 1.5), belonging to the first effective trophic level category, 1.5-2.5 (excluding 2.5), belonging to the second effective trophic level category, 2.5-3.5 (excluding 3.5), belonging to the third effective trophic level category, 3.5-4.5 (excluding 4.5), belonging to the fourth effective trophic level category.

[0038] The connectivity refers to the number of functional groups that have a direct nutritional relationship (i.e. predator and prey) around a functional group in the established ecosystem food web.

[0039] Furthermore, when screening the target species for proliferation and release, at least one target species for proliferation is selected from each trophic level (except the first trophic level, where the target species for proliferation may or may not be selected depending on the situation), and a multi-trophic level combination proliferation method is established.

[0040] Furthermore, when carrying out stocking enhancement with the goal of improving the diversity of energy flow in the ecosystem, the target species for enhancement are mainly selected from organisms at the medium effective trophic level (generally the 2nd and 3rd effective trophic levels). First, 3-4 species with high enhancement potential are selected, and then species with high connectivity are selected from the above 3-4 functional groups. Finally, 1-2 enhancement species are determined in each medium effective trophic level.

[0041] When selecting target species for proliferation with the goal of increasing the average food chain path length of the ecosystem, we mainly focus on organisms at high trophic levels, first identify 2-3 species with higher proliferation potential within the trophic level, and then select 1-2 suitable proliferation species (preferably species with the first and second highest proliferation potential);

[0042] For trophic levels with low energy transfer efficiency, first determine 1-2 species in the adjacent trophic levels that flow to the larger amount of debris in the lower trophic level, then determine 2-3 main predators of this species, and then select 1-2 predators with the first and second highest proliferation potential as proliferation species to improve the system's utilization efficiency of the species' productivity.

[0043] The method for determining the proliferation potential is: firstly, the biological carrying capacity of the species is calculated using the food web energy flow model, and then the biological proliferation potential is characterized based on the difference between the biological carrying capacity of the species and the existing biomass.

[0044] The calculation method of the biocarrying capacity is: based on the established ecosystem food web energy flow model, the biomass of a certain biological functional group at the critical point of energy flow balance of the marine ecosystem is calculated to obtain the biocarrying capacity. The calculation method is as follows: the critical point of energy flow balance of the marine ecosystem is: gradually increase the biomass of the target biological functional group for biocarrying capacity evaluation. When the EE value of another biological functional group in the ecosystem is equal to 1, this is the critical point of energy flow balance of the ecosystem; the target biological carrying capacity of the marine ecosystem is the biomass of the biological functional group corresponding to the critical point of energy flow balance.

[0045] Further, the method for determining the appropriate proliferation density of the proliferation organisms is as follows:

[0046] First, the proliferation potential of the proliferating organisms is obtained based on the biological carrying capacity of the proliferating functional group and the existing biological stock. Then, the maximum sustainable proliferation density of the proliferating organisms is calculated in combination with the target size to be achieved by the proliferating organisms and the survival rate of the proliferating organisms. The specific calculation method is:

[0047] D M =(B C -B N ) / B IND / S T

[0048] D M Represents the maximum sustainable proliferation density of the target organism. B C is the target biocapacity for growth, B N is the existing stock of the target organism for growth, B IND It is the target biomass to be achieved by the individual organisms. S T is the survival rate of proliferating organisms during the proliferation period.

[0049] The methods for calculating the survival rate of proliferating organisms are:

[0050] 1) Obtain the survival rate of the proliferated organisms directly through the propagation and release experiment;

[0051] 2) For organisms that are not convenient to directly obtain the survival rate of the propagated organisms through propagation and release experiments, the period from the start of propagation and release to the growth of the propagated organisms to the target size ( L 0-T The survival rate of ) is calculated as follows:

[0052] The period from the start of proliferation and release to the growth of the proliferated organisms to the target size is subdivided, the mortality coefficient of the target organisms in each time period is calculated, and then the survival rate of the target organisms in each stage is calculated, and finally the total survival rate of the target organisms during the entire proliferation period is obtained.

[0053] The specific steps are:

[0054] S31. Determine the relationship between the natural mortality coefficient of proliferating organisms and their individual size: M T =M R ×（L R / L T ） , where: M T It indicates the mortality coefficient of proliferating organisms at a certain individual size. M R is the mortality coefficient of the proliferating organisms when they mature (annual mortality coefficient), L R To increase the length of mature organisms, L T To increase the length of an organism at a certain individual size. M T Divide by L 0-T (Unit: year), that is, obtain the mortality coefficient of the target organism during this time period.

[0055] The calculation method of the mortality coefficient of mature individuals is: M=K 0.65 ×L ∞ -0.279 ×T c 0.463 , where: M Represents the natural death coefficient, the unit is per year ( / year); K is the biological growth coefficient in the VBGF growth equation, in units of per year ( / year); L ∞ is the progressive total length, in centimeters (cm); T c is the annual average water temperature in degrees Celsius (℃).

[0056] S32. Calculate the time required for the target organism to grow from the size of the proliferated individual to the target body length, using the following calculation method:

[0057] 1) When conditions permit for carrying out growth experiments to determine the required growth time, the time required for the propagated organisms to grow from the size of the propagated individuals to the target body length can be directly measured based on the propagation and release experiments.

[0058] 2) In the absence of conditions to carry out growth experiments to determine the required growth time, the target organism's body length-time growth equation can be used for indirect calculation. The specific method is as follows:

[0059]

[0060] L ∞ is the average progressive body length; L t is the average body length at age t; k is the growth parameter; t 0 is the assumed theoretical starting age of growth, and e refers to a natural constant.

[0061] Calculate the age of the target organism at the proliferation individual size and the target size, and thus obtain the time required from the proliferation individual size to the target individual size;

[0062] S33, subdividing the period of time and calculating the death coefficient of the target organisms in each age group M x .

[0063] S34, then determine the survival rate of the target organisms in each age group, the specific calculation method is: A=e (-Mx) , A represents the survival rate, e is a natural constant, M x is the mortality coefficient M of the target organism in each age group x

[0064] S35. Multiply the survival rates of the proliferating organisms at each age stage to obtain the total survival rate of the organisms during the entire proliferating period, that is, the total survival rate from the size of the proliferating individual to the target size and age.

[0065] Specifically, compared with the existing technology, this technology can produce the following positive effects:

[0066] (1) In view of the insufficient assessment of ecosystem food web characteristics in current marine ecosystem food web restoration activities, the present invention establishes a food web energy flow model to effectively evaluate the structural and functional characteristics of the food web and determine the advantages and disadvantages of the food web structure and function.

[0067] (2) Compared with the prior art, the present invention adopts a method based on stocking and restocking, which is aimed at restoring the biological resources of the ecosystem to repair the food web. In terms of effect, the present method can be used to carry out marine ecosystem food web restoration work on a larger scale in bays and offshore areas. It can be seen that all the methods in the present invention can repair a wider range of sea areas. In addition, in terms of specific implementation, the cost of the stocking and restocking method adopted by the present invention is much lower than the cost of placing artificial reefs within a unit area. Therefore, the economic cost of the present invention is lower. In terms of implementation effect, the present invention can also be used in combination with the prior art, for example, it can further optimize the structure and function of the ecosystem food web based on the existing technology such as the habitat creation of artificial reef construction (Zheng Ting 2013).

[0068] (3) In response to the problem that there is a lack of sufficient and reasonable basis for the formulation of food web restoration plans in current marine ecosystem food web restoration activities, the present invention has developed a relatively scientific food web structure optimization path to provide guidance for the implementation of food web optimization work.

[0069] (4) In the current process of biological resource proliferation and food web restoration, the selection of proliferation target species is relatively blind, and there is a lack of a scientific and reasonable selection method. The present invention uses the food web energy flow model to quantify the structural characteristics of the ecosystem food web, and targets the imperfections in the food web structure and function, with the goal of improving the diversity of the food web structure and the energy transfer efficiency function, combined with the biological proliferation potential assessment to screen the proliferation target species, and establishes a multi-trophic level matching proliferation biological screening method with the goal of repairing the food web. This method is more scientific and reasonable than the current common methods, more operational, and has a clearer purpose. This method fully considers the proliferation potential of the proliferation organisms and their role in optimizing the food web structure of the ecosystem, and greatly avoids the phenomenon that the selected proliferation species have an insignificant proliferation effect due to too low proliferation potential and insignificant optimization of the ecosystem structure and function, which may have a large negative consequence.

[0070] (5) Compared with the current common operation methods, the method for evaluating and determining the proliferation density of species released by the present invention proposes a set of operational and quantifiable evaluation technologies. By effectively evaluating the appropriate proliferation density, it avoids the past practice of judging the proliferation density based solely on experience and lacking scientific evaluation methods, which may lead to excessive proliferation density, resulting in squeezing of wild populations, mass death of proliferating organisms, low proliferation efficiency, and other problems, thereby reducing ecological risks and economic losses. It can be seen that the present invention improves the optimization and restoration of food webs based on proliferation release. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A flow chart of the method for optimizing the food web of a marine ecosystem according to the present invention; DETAILED DESCRIPTION

[0072] The following examples are provided to facilitate a better understanding of the present invention, but are not intended to limit the present invention. The experimental methods in the following examples are conventional methods unless otherwise specified.

[0073] Example 1

[0074] This embodiment uses the food web evaluation and optimization method of the artificial fish reef ecosystem in Laizhou Bay as an example. It can be understood that the ecosystem food web evaluation and optimization method of the present invention can also be applied to other ecosystems.

[0075] Firstly, the biological functional groups of the artificial fish reef ecosystem in Laizhou Bay were divided according to the functions of each organism in the marine ecosystem; the niche characteristics such as the feeding habits, habitat space, movement patterns and population structure, P / B, Q / B values, morphological characteristics of each organism in the marine ecosystem were used as the basis for determining the functions of each organism in the ecosystem.

[0076] The divided marine ecosystem functional groups include three types of functional groups: primary producers, consumers and organic debris, covering all biological and organic components of the marine ecosystem.

[0077] Based on the survey of biological resources of the artificial reef ecosystem in Laizhou Bay from 2019 to 2020, the ecosystem is divided into 27 biological functional groups, including flathead scorpionfish, bigeye mullet, spotted sea bass, black sea bream, etc. The biological composition of each biological functional group is shown in Table 1 below:

[0078] Table 1 Biological composition of each biological functional group in the artificial reef ecosystem of Laizhou Bay

[0079]

[0080] Next, the input parameter file of the energy flow model of the artificial reef ecosystem in Laizhou Bay was established;

[0081] Based on the survey data of biological resources of artificial reef ecosystem in Laizhou Bay, the biomass parameters of each biological functional group of artificial reef ecosystem in Laizhou Bay were obtained, and the biomass parameters of each biological functional group of artificial reef ecosystem in Laizhou Bay were obtained by consulting literature and combining empirical formulas. P / B , Q / B The biomass of each biological functional group, P / B , Q / B The parameter values ​​are shown in Table 2 below:

[0082] Table 2 Input parameters of each biological function group in the artificial reef area of ​​Laizhou Bay

[0083]

[0084] Next, by conducting experiments such as stomach content analysis and stable isotope analysis, and combining relevant literature data, we obtained the food composition parameters of each consumer biological functional group in the artificial fish reef ecosystem of Laizhou Bay. The food composition matrix of each consumer biological functional group in the artificial fish reef ecosystem of Laizhou Bay is shown in Tables 3 and 4 below:

[0085] Table 3 Bio-food composition matrix of consumers in the artificial reef area of ​​Laizhou Bay (Part 1)

[0086]

[0087] Table 4 Bio-food composition matrix of consumers in the artificial reef area of ​​Laizhou Bay (lower)

[0088]

[0089] After inputting the biomass, P / B value, Q / B value, food composition and other parameters of each biological functional group of the artificial fish reef ecosystem in Laizhou Bay, the energy flow model of the artificial fish reef ecosystem in Laizhou Bay was obtained.

[0090] On this basis, the food web parameters such as the average food chain path length, energy flow diversity, and energy transfer efficiency between different trophic levels of the ecosystem food web are calculated, and compared based on the established parameter library of similar ecosystems.

[0091] Table 5 Debris inflow, trophic level and connectivity of each functional group in the artificial reef ecosystem of Laizhou Bay

[0092]

[0093] Table 6 Food web diversity parameters of artificial reef ecosystem in Laizhou Bay

[0094] parameter Numeric unit Average path length 3.54 / Energy flow diversity index 1.67 /

[0095] It can be seen from Table 6 that the average food chain path length of the Laizhoulai artificial reef ecosystem is 3.54, and the energy flow diversity level is 1.67.

[0096] Table 7 Energy transfer efficiency between different trophic levels in the artificial reef ecosystem of Laizhou Bay

[0097]

[0098] Table 8 Biocapacity values ​​of important functional groups of artificial reef ecosystem in Laizhou Bay

[0099]

[0100] Compared with similar marine ecosystems (see Table 9), the average path length in this system is at a higher level, but it is still a certain distance away from the relevant values ​​of ecosystems in the perfect stage, indicating that there is room for further optimization, while its energy flow diversity is at a lower level and has a lot of room for optimization. That is, the diversity of the ecosystem food web can be further optimized by optimizing the average path length and energy flow diversity.

[0101] Table 9 Thresholds for each index level obtained by collecting food web indices of similar ecosystems around the world

[0102]

[0103] Note: D / H: ratio of debris flow to herbivory flow; TE: energy transfer efficiency between different integer trophic levels of the ecosystem; H: diversity of energy flow in the food web; A / C: relative dominance; CI: connectivity index; SOI: system omnivory index; FCI: Finn's cycle index; FML: average food chain path length; TPP / TR: total primary production / total respiration; TPP / TB: total primary production / total biomass; TB / TST: total biomass / total energy flow

[0104] In the ecosystem, the energy transfer efficiency between the 3rd and 4th trophic levels is only 6.71%, far lower than the 10% average value of general marine ecosystems. The correlation value between the 2nd and 3rd trophic levels is 11.48%, which is between average and good, and there is room for further optimization. In addition, a large amount of energy substances in phytoplankton and mud debris in the first trophic level of the ecosystem are not directly used by high trophic level organisms in the system and flow to the debris group. Therefore, they can be further utilized to improve the energy transfer efficiency between the 1st and 2nd trophic levels.

[0105] Optimization of food chain path length: The two functional groups with the highest trophic levels in the ecosystem are Hypsilophobia philippinarum and Lateolabrax japonicus. Hypsilophobia philippinarum has higher proliferation potential and connectivity with other functional groups than Lateolabrax japonicus, so it was selected as the target species for proliferation.

[0106] Optimize energy flow diversity: Among the organisms at the third medium trophic level in the ecosystem, the functional groups with greater proliferation potential are red snails, large benthic crustaceans and mantis shrimps. Among them, the organism with higher connectivity is the large benthic crustaceans, and this species was selected as the target species for proliferation; among the organisms at the second medium trophic level, the functional groups with greater proliferation potential are sea cucumbers and oysters. Among them, the organism with higher connectivity is the oyster, and the oyster was selected as the target species for proliferation.

[0107] Optimize the efficiency of energy flow transfer: In the ecosystem, the energy transfer efficiency between the 3rd and 4th trophic levels is relatively low. In the 3rd trophic level, the two biological functional groups with the largest amount of debris flow are red snails and moon jellyfish. Since moon jellyfish have no special predators and the main predator of red snails is octopus, octopus was selected as the main target species for proliferation. The energy transfer efficiency between the 2nd and 3rd trophic levels is relatively high, but there is still room for optimization. In the 2nd trophic level, the organism with the largest amount of debris flowing to it is the oyster, and its main predator is the red snail, so it was selected as the main target species for proliferation; in the 1st trophic level, the functional group with the largest amount of debris flowing to it is phytoplankton and sediment debris, and its main predators are zooplankton, benthic bacteria, heart-shaped sea urchins, other shrimps and crabs, red snails, sea cucumbers and other species. Considering that zooplankton, benthic bacteria, heart-shaped sea urchins, and other shrimps and crabs cannot be artificially propagated, the main target species selected for proliferation are red snails and sea cucumbers. Among these two species, the proliferation potential of sea cucumbers is significantly higher than that of red snails, so sea cucumbers were selected as the main target species for proliferation.

[0108] Taking all the above factors into consideration, the target species for enhancement finally selected include the flathead catfish, large benthic crustaceans, octopus, oyster, red snail, and sea cucumber.

[0109] Suitable proliferation density of target species in artificial reef area of ​​Laizhou Bay:

[0110] Assessment of the suitable proliferation density of S. philippinarum in the artificial reef area of ​​Laizhou Bay: First, the annual mortality coefficient of the proliferation population of S. philippinarum was calculated. Based on the relationship between the natural mortality rate and individual size of S. philippinarum, the total mortality rate was calculated when the proliferation population of S. philippinarum grew to a certain individual size.

[0111] Calculation method of natural mortality of Scorpionfish:

[0112] M=K 0.65 ×L ∞ -0.279 ×T c 0.463

[0113] Where: M Represents the natural mortality rate, in units of year ( / year); K is the biological growth coefficient in the VBGF growth equation, in units of per year ( / year); L ∞ is the progressive total length, in centimeters (cm); Tc is the annual average water temperature in degrees Celsius (℃). kThe value and asymptotic total length (cm) were 0.576 and 43.71cm respectively (calculated based on the asymptotic body length of 36.72cm). The annual average water temperature was 15℃, and the annual mortality coefficient of Xu's flathead was calculated to be 0.8264.

[0114] The relationship between the natural mortality rate of Xu's flatfish and its individual size is: M T =M R ×（L R / L T ）

[0115] Where: M T It represents the mortality rate of the flatfish at a certain individual size. M R is the mortality rate of Xu's flatfish when it matures. L R is the body length of the mature flathead mullet. L T The body length of the flatfish when it reaches its target size.

[0116] According to the technical guide for harvesting marine ranch fishery resources, the minimum catchable length of the flatfish is 200mm. Based on the empirical formula of the length and weight of the flatfish: W=1.750×10 -5 ×L 3.084 (r 2 =0.990, p <0.05), W is body weight (g), L is body length (mm), and the body weight is 219.86g. The growth equation of the flathead mullet is: Lt=367.211×[1-e -0.576(t+0.399) ] , calculated by this formula, the age of the catchable flatfish is 1.68 years. According to survey data, the length of the released flatfish for reproduction is 3.35-7cm (total length 4-8cm), and the corresponding age is: 0.58-0.77 years. The maturity age of the flatfish is about 3 years, at which time its mature body length is about 285.13mm. Taking 0.01 years as a unit, the mortality coefficient of the flatfish in each 0.01 year period from 0.58 to 0.77 years is calculated as: 0.83 / 0.01=0.0083. Further considering the effect of individual size on the mortality rate of the flatfish, the mortality coefficient between each 0.01 year from 0.58 to 1.68 years is calculated as M=0.0083* （L R / L T ）, and then, based on the mortality coefficient of each 0.01a, the survival rate A of each 0.01a is calculated as follows: A=e (-M) Therefore, the survival rate of the proliferated Scorpionfish (total length 40 mm, theoretical age 0.58 years) during the period 0.58 years to 1.68 years can be calculated as A 0.58a-1.68a =A 0.58a ×A （0.58+0.01）a …×A （0.58+0.01n）a …×A 1.68a =0.0737; the survival rate of the proliferating Scorpionfish (total length 80 mm, theoretical age 0.77 years) during the period of 0.77 years to 1.68 years can be calculated as A 0.77a-1.68a = A 0.77a ×A （0.77+0.01）a …×A （0.77+0.01n）a… ×A 1.68a =0.1780.

[0117] Based on the biological carrying capacity and current stock of the artificial reef area in Laizhou Bay, its proliferation potential is calculated to be: 0.40t / km 2 The artificial reef area of ​​Laizhou Bay is 33.33 km 2 The total growth capacity is calculated to be 13.33t, or 1.33×10 7 g. The target weight of the flatfish is 219.86 g, so the maximum number of flatfish that can be increased is: 6.40×10 4 If the total length of the released individual is 4 cm, based on its survival rate (0.0737), the appropriate release rate of the released individual can be calculated to be 8.68×10 5 ind(2.61×10 4 ind / km 2 ); If the total length of the released individual of the Xu's flatfish is 8 cm, based on its survival rate (0.1780), the appropriate release rate of Xu's flatfish can be calculated to be 3.60×10 5 ind(1.08×10 4 ind / km 2 ).

[0118] Assessment of the suitable proliferation density of sea cucumbers in the artificial reef area of ​​Laizhou Bay: According to the proliferation-harvesting monitoring data conducted by researchers in the artificial reef area, about 100 sea cucumbers (average individual size 3.33g) were propagated in the artificial reef area. Two years later, the individual size of sea cucumbers reached 100-200 (average individual size 45g). During this period, the survival rate of sea cucumbers was about 0.65. This was used as the survival rate data of sea cucumbers during the proliferation period to calculate the suitable proliferation density of sea cucumbers. Based on the biological carrying capacity and existing stock of sea cucumbers in the artificial reef area of ​​Laizhou Bay, its proliferation potential was calculated to be: 250 t / km 2 The suitable individual size of sea cucumbers for harvest is about 45g. Taking this as the final target weight of sea cucumbers for proliferation, the maximum number of sea cucumbers that can be increased is calculated as: 5.6×10 6 ind / km 2 According to the survival rate (0.65), the appropriate amount of sea cucumber for reproduction can be calculated to be 8.62×10 6 ind / km 2 .

[0119] The above description is only an example of the present invention and is not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for optimizing a marine ecosystem food web, comprising the following steps: S1. Constructing a marine ecosystem food web energy flow model. The method for constructing the marine ecosystem food web energy flow model comprises the following steps: S11. Organisms are divided into functional groups according to the functions they perform in the marine ecosystem; S12. Obtain data on each biological functional group in the marine ecosystem: including the biomass of each biological functional group, the ratio of production to biomass, the ratio of food intake to biomass, biomass accumulation, migration, catch, food composition of each consumer organism, and the proportion of undigested food; S13, using the acquired data of each biological function group as input data, and establishing a marine ecosystem energy flow model based on the Ecopath model construction principle; S14. Check and debug the energy balance of marine ecosystems; S2. Based on the above-established food web energy flow model, quantify the nutritional relationship and energy flow relationship between organisms in the marine ecosystem; For the target marine ecosystem, select other marine ecosystems with similar characteristics to the target marine ecosystem as controls, and compare the indicators of food web structure and function evaluation with those of the control marine ecosystem to determine the level of food web structure and function of the target marine ecosystem; When the indicators of the food web structure and function evaluation of the target marine ecosystem are worse than the range values ​​of the control ecosystem, it indicates that there is room for optimization of the indicator, and the structure and function of the food web can be optimized by improving the values ​​of the relevant indicators; The method to improve the relevant index values ​​is to increase the number of species for stocking. When selecting the target species for stocking, at least one target species should be selected from each trophic level except the first trophic level, and a multi-trophic level-based stocking method should be established. The screening method for target species for stocking is as follows: when stocking is carried out with the goal of increasing the diversity of energy flows, species with high connectivity are selected from species with the highest stocking potential, and finally, 1-2 stocking species are selected for each trophic level except the first and highest trophic levels; When selecting target species for proliferation with the goal of increasing the average food chain path length, first select 2-3 species with proliferation potential in the top 2 or top 3 in the high trophic level, and then select 1-2 suitable species from them as proliferation species; for trophic levels with low energy transfer efficiency, first determine 1-2 species in the adjacent trophic levels with the first and second largest amount of debris flowing to the low trophic level, then determine 2-3 main predators of the species, and then select 1-2 predators with proliferation potential in the first and second places as proliferation species; The method for determining the appropriate proliferation density of proliferating organisms is as follows: First, the proliferation potential of the proliferating organisms is obtained based on the carrying capacity of the proliferating organisms and the existing biological stock. Then, the maximum sustainable proliferation density of the proliferating organisms is calculated in combination with the target size to be achieved by the proliferating organisms and the survival rate of the proliferating organisms. The specific calculation method is: D M =(B C -B N ) / B IND / S T D M Represents the maximum sustainable proliferation density of the target organism. B C is the target biocapacity for growth, B N is the existing stock of the target organism for proliferation, B IND It is the target biomass to be achieved by the individual organisms. S T is the survival rate of proliferating organisms during the proliferation period; The method for calculating the survival rate of the proliferated organisms is: obtaining the survival rate of the proliferated organisms through a proliferation and release experiment; for organisms for which it is not convenient to directly obtain the survival rate of the proliferated organisms through a proliferation and release experiment, the method for calculating the survival rate during the period from the start of proliferation and release to the growth of the proliferated organisms to the target size is as follows: subdividing the period from the start of proliferation and release to the growth of the proliferated organisms to the target size, calculating the mortality coefficient of the target organisms in each time period, and then calculating the survival rate of the target organisms in each stage, and finally obtaining the total survival rate of the target organisms during the entire proliferation period.

2. The method for optimizing the food web of a marine ecosystem according to claim 1, characterized in that: In S2, the indicators for evaluating the structure and function of the food web are: food web energy flow diversity index, average food chain path length, energy transfer efficiency between different integer trophic levels of the ecosystem, system connectivity index, system omnivory index, Finn's circulation index, average trophic level of fish catch, ratio of debris flow to herbivory flow, relative dominance, total primary production / total respiration, total primary production / total biomass, and total biomass / total energy flow.

3. The method for optimizing the food web of a marine ecosystem according to claim 1, characterized in that: For organisms that are not convenient to directly obtain the survival rate of the propagated organisms through propagation and release experiments, the method for determining the total survival rate of the target organisms during the propagation period is as follows: S31. Determine the relationship between the natural mortality coefficient of proliferating organisms and their individual size; S32. Calculate the time required for the target organism to grow from the size of the proliferated individual to the target body length: 1) If conditions permit, the time required for the growth of the propagated organisms to grow from the propagated individual size to the target body length can be directly measured based on the propagation and release experiment to determine the required growth time; 2) If it is impossible to carry out growth experiments to determine the required growth time, the target organism's body length-time growth equation can be used for indirect calculation to obtain the age of the target organism at the increased individual size and the target size, thereby obtaining the time required for the increase in the individual size to reach the target individual size; S33, subdividing the period of time, and calculating the mortality coefficient of the target organisms in each age group; S34. Determine the survival rate of target organisms in each age group; S35. Multiply the survival rates of the proliferating organisms at each age stage to obtain the total survival rate of the organisms during the entire proliferating period, that is, the total survival rate from the size of the proliferating individual to the target size and age.

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