CN111783305A - Water area ecosystem regulation and control method based on biological control - Google Patents
Water area ecosystem regulation and control method based on biological control Download PDFInfo
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Abstract
A water area ecosystem regulation and control method based on biological control relates to ecosystem regulation and control and management. The method comprises the following steps: 1) constructing an Ecopath model by using the obtained model functional group parameters, and carrying out network, energy flow and logistics distribution; 2) establishing a nutrition level spectrum, determining whether the nutrition level and the biomass of the ecosystem are characterized by nutrition level increase and biomass reduction, drawing a trend line with a log as a base, determining a functional group higher or lower than the trend line, and providing a theoretical basis for biological manipulation by using a 'peak clipping and valley filling' strategy; 3) for functional groups above or below the trend line, a "peak clipping and valley filling" strategy was performed, and a biological manipulation simulation was performed using the ecosmim model. Provides a biological control technical method for pertinently adjusting poor ecosystems such as eutrophication and the like, can improve the stability of the ecosystems and the regeneration capability of biological resources, and improves the whole ecological service.
Description
Technical Field
The invention relates to regulation and control of an ecosystem, in particular to a water area ecosystem regulation and control method based on biological manipulation based on an Ecopath model and a nutrition level spectrum theory.
Background
Ecosystem regulation or restoration is a method for helping a damaged, degenerated or destroyed ecosystem to restore its structure, function and service under the premise of obeying natural laws and social requirements. The essence of the method is that under the premise of obeying natural laws and social requirements and under the guidance of community succession theory, in the process of natural succession of a damaged ecological system, by means of technical means such as physics, chemistry and biology, unfavorable external interference pressure is overcome or eliminated, the load and pressure borne by the ecological system are relieved, the flowing process and the time-space order of the substance, energy and information inside the system and outside the system are adjusted, configured and optimized, the self-recovery capability and the reverse succession mechanism of the ecological system are combined, the direction and the speed of succession are regulated and changed, an active and ordered management mode and measure are created, the time for recovering or rebuilding the reasonable structure, the efficient function and the coordination relation of the ecological system is shortened, and the system is enabled to achieve the self-maintaining state. Currently, there are a series of physical, chemical and biological measures to treat eutrophication to promote ecological restoration. Compared with a physical-chemical comprehensive method, the bioremediation method has the advantages that the bioremediation effect is stable for a long time, and meanwhile, the bioremediation cost is relatively low. The biological manipulation method is already applied to lake restoration in some temperate regions, and the existing important biological manipulation methods comprise the following steps: 1. removing phytoplankton-feeding fish to control phytoplankton biomass, wherein the biomass of large phytoplankton feeding phytoplankton is increased after removing the zooplankton-feeding and benthic invertebrate-feeding fish; 2. removal of benthic omnivorous fish, which controls phytoplankton biomass, is a process of benthic filter-omnivorous fish (especially phytophagous-debris-fed fish in temperate waters, e.g. carp, tilapia), which can naturally reach the highest bearing capacity, removal of which can reduce biological disturbances and internal nutrient salt circulation; 3. the method is characterized in that carnivorous fishes are stocked to control the biomass of phytoplankton, and the process is to increase the fishes which are carnivorous to reduce the fishes which are carnivorous, and improve the biomass of the zooplankton and the food intake of the zooplankton; 4. controlling phytoplankton biomass by stocking the upper layer of phytophagous fishes to remove phytoplankton, especially blue algae; 5. removal and protection of macrophytes by planting submerged plants and maintaining high coverage of macrophytes by repelling herbivorous birds or fish; 6. cultivating herbivorous fish to control macrophytes, wherein the herbivorous fish (grass carp) is added to reduce excessive growth of submerged plants; 7. the introduction of the bivalve adds the filtering function of water by the filtering and eating function of the bivalve, so that the water body is cleaner.
In addition to the above-mentioned biological manipulation methods, at present, biological manipulation is mainly used to restore and purify water, relieve eutrophication, and focus on the algae control effect of organisms, and is used in freshwater lakes or reservoir ecosystems, such as: (1) huzhongjun and the like (Chinese patent publication No. CN110845013A) utilize an Ecopath model and a multi-nutrition-level biological control technology to establish a shallow lake ecosystem regulation and stable maintenance method for shallow vegetation recovery and wetland reconstruction. (2) Zhanglie et al (Chinese patent publication No. CN110563278A) use a non-classical biological manipulation method to introduce filter-feeding fishes and pre-magnetize the water area to inhibit the activity of algae cells and increase the digestion rate of filter-feeding fishes to algae, thereby achieving the effect of treating phytoplankton. (3) Yangyang et al (Chinese patent publication No. CN108793410A) analyzes the current ecological system energy flow mode and the primary production amount of the lowest maintenance system operation based on an Ecopath ecological system model, and develops a eutrophic water body remediation method combining the ecological system model and a biological control technology by utilizing the biological control technology for controlling the downlink effect of fish-adding consumers. The target ecosystem of the above-mentioned restoration or regulation technology only focuses on ecosystems such as freshwater lakes, rivers, reservoirs, etc., however, in recent years, under the influence of more serious human activities, the ecosystems such as offshore gulf, estuary, lagoons, etc., the events such as water eutrophication and red tide, etc. frequently occur, and the biodiversity and ecosystem structure and function are threatened, and a regulation and control method of the ecosystem of the water area mainly based on bioremediation is urgently needed to solve the increasingly prominent environmental and ecological problems.
Based on the method, before ecological system regulation or biological manipulation is actually carried out, quantitative evaluation needs to be carried out on a target ecological system, energy flow trend and energy flow size are analyzed, and then biological manipulation simulation is carried out by using a model. The Ecopath ecological model is used as an important component of EwE modeling software for static balance analysis of ecological network and energy flow, and has been widely used in recent years, in addition to that, the ecosmim model in EwE can be used to simulate the dynamic change of the ecological system with time. The diagnosis after the analysis of the ecosystem needs a nutrition level spectrum to be completed, and a biological manipulation situation simulation taking 'peak clipping and valley filling' as a special diagnosis is carried out by combining an Ecosim model. The nutrition level spectrum is developed from a particle size spectrum, and the particle size spectrum represents a relation curve between biomass or biomass and particle size, so that the nutrition level spectrum is an important way for researching the characteristics of an ecosystem. Then, for a particular ecosystem, the biomass distribution on each size fraction will follow a certain law. In an aquatic ecosystem, the size of the size fraction of an organism is almost positively correlated with the nutrient level, and the size fraction of the organism is larger as the nutrient level is increased. Thus, for a particular ecosystem, biomass decreases in the ascending trophic level. Therefore, the biological manipulation method taking 'peak clipping and valley filling' as a strategy can bring a more targeted scheme for the diagnosis and control of the ecological system and the restoration of the water body.
Disclosure of Invention
The invention aims to provide a water area ecological system regulation and control method based on biological control, aiming at an ecological system with obvious water eutrophication, biological resources and ecological degradation.
The invention comprises the following steps:
1) constructing an Ecopath model by using the obtained model functional group parameters, and carrying out network, energy flow and logistics distribution;
2) establishing a nutrition level spectrum, determining whether the nutrition level and the biomass of the ecosystem are characterized by nutrition level increase and biomass reduction, drawing a trend line with a log as a base, determining a functional group higher or lower than the trend line, and providing a theoretical basis for biological manipulation by using a 'peak clipping and valley filling' strategy;
3) for functional groups above or below the trend line, a "peak clipping and valley filling" strategy was performed, and a biological manipulation simulation was performed using the ecosmim model.
In step 1), the specific method for constructing the Ecopath model by using the obtained model functional group parameters to perform network, energy flow and logistics distribution may be:
(1.1) the Ecopath model firstly needs to divide the functional groups according to the actual ecosystem situation, and needs to accord with the following principle: simplifying a food net, and merging the populations with high ecological niche overlapping according to methods such as food composition, feeding mode, statistical classification of fishery catch and the like; the number of the debris groups is more than or equal to 1; the functional groups basically cover the whole process of energy flow of the ecosystem, and a certain functional group cannot be ignored due to lack of partial data, especially dominant species or key species or top-level predators and the like need to be considered;
(1.2) basic parameters of the Ecopath model are input, three of four parameters of B (biomass), P/B (production amount/biomass), Q/B (consumption amount/biomass) and EE (ecological nutrition conversion efficiency) need to be input into each functional group, the first three parameters are mainly input into the model, and the model can automatically output a fourth parameter value; in addition, the model also needs a feeding property matrix to reflect the predation relationship in the ecosystem;
and (1.3) analyzing the nutrient structure in the target ecosystem and energy flow distribution among all nutrient levels, and intuitively obtaining energy flow paths among all functional groups through an energy flow diagram.
In step 3), performing a 'peak clipping and valley filling' strategy for the functional groups higher or lower than the trend line, performing biological manipulation simulation by using an Ecosim model, and replacing 'peak clipping and valley filling' by using fishing or seedling propagation and releasing in actual operation; the method comprises the following specific steps:
(3.1) constructing a biological control Ecosim model, wherein the Ecosim model is based on the Ecopath model, besides input parameters of the Ecopath model, a vulnerability relation index is also required to be input, and the numerical value represents the influence of the increase of the biomass of predators on the predation mortality of prey;
(3.2) according to the conclusion of the ecosystem nutrition level spectrum, taking a 'peak clipping and valley filling' measure to the functional group which is higher or lower than the trend line for carrying out biological manipulation, and carrying out 'valley filling' biological manipulation scene simulation on the functional group which is lower than the trend line and carrying out 'peak clipping' biological manipulation scene simulation on the functional group which is higher than the trend line.
(3.3) according to the 'peak clipping and valley filling' biological manipulation simulation result of the Ecosim model, in the practical application process, catching organisms higher than the trend line as a 'peak clipping' biological manipulation strategy, and performing seedling proliferation and releasing on organisms lower than the trend line as a 'valley filling' biological manipulation strategy.
The method mainly comprises the steps of constructing an Ecopath model, analyzing network, energy flow and logistics, quantitatively evaluating an ecosystem, and analyzing the trend and the size of the energy flow in the system; constructing a nutrient level spectrum based on the functional group nutrient level and biomass relation, diagnosing and analyzing the balance of the ecosystem, drawing a trend line with a log as a base, and paying attention to the functional group higher or lower than the trend line; constructing an Ecosim model, and performing biological manipulation simulation by taking a 'peak clipping and valley filling' measure on a functional group higher or lower than a trend line; and performing biological manipulation simulation by using an Ecosim model, applying a simulation result to actual biological manipulation, fishing organisms higher than the trend line as a 'peak clipping' biological manipulation strategy, and performing seedling proliferation and releasing on organisms lower than the trend line as a 'valley filling' biological manipulation strategy. The invention provides a biological control technical method for pertinently adjusting poor ecological systems such as eutrophication and the like, which can improve the stability of the ecological systems and the regeneration capacity of biological resources and improve the overall ecological service.
Drawings
Fig. 1 shows the structure and energy flow diagram of a food net of an ecosystem of a certain water area.
Fig. 2 is a map of the nutrition level of an ecosystem of a certain water area. Biomass decreases with increasing nutritional grade; the nutrition level is increased from right to left; the dotted line in the figure is a trend line.
FIG. 3 is a comparison of phytoplankton removal rates for a combination of manipulations, crab manipulations, and single species manipulations.
Detailed Description
The following examples will further illustrate the present invention with reference to the accompanying drawings.
The embodiment of the invention comprises the following steps:
1) constructing an Ecopath model by using the parameters of the obtained model functional group, and carrying out network, energy flow and logistics distribution;
(1.1) the Ecopath model firstly needs to divide the functional groups according to the actual ecosystem situation, and needs to accord with the following principle: simplifying a food net, and merging the populations with high ecological niche overlapping according to methods such as food composition, feeding mode, statistical classification of fishery catch and the like; the number of the debris groups is more than or equal to 1; the functional groups are to cover the whole process of energy flow of the ecosystem basically, and certain functional groups cannot be ignored due to lack of partial data, and particularly, dominant species or key species or top-level predators and the like need to be considered.
(1.2) basic parameters of the Ecopath model are input, three of the four parameters of B (biomass), P/B (production amount/biomass), Q/B (consumption amount/biomass) and EE (ecological nutrition transformation efficiency) need to be input into each functional group, generally, the EE value is difficult to estimate, so the first three parameters are mainly input into the model, and the fourth parameter value is automatically output by the model. In addition, the model requires a feeding matrix reflecting predation relationships within the ecosystem.
And (1.3) analyzing the nutrient structure in the target ecosystem and energy flow distribution among all nutrient levels, and intuitively obtaining energy flow paths among all functional groups through an energy flow diagram.
2) Establishing a nutrition level spectrum, determining whether the nutrition level and the biomass of the ecosystem are characterized by nutrition level increase and biomass reduction, drawing a trend line with a log as a base, focusing on a functional group higher or lower than the trend line, and providing a theoretical basis for biological manipulation by utilizing a 'peak clipping and valley filling' strategy in the third step.
3) For functional groups higher or lower than the trend line, a 'peak clipping and valley filling' strategy is carried out, biological manipulation simulation is carried out by using an Ecosim model, and actual operation can replace 'peak clipping and valley filling' by using fishing or seedling proliferation and releasing.
(3.1) constructing a biological control Ecosim model, wherein the model is based on an Ecopath equilibrium model, besides input parameters of the Ecopath model, a vulnerability relation index is also input, and the numerical value represents the influence of the increase of the biomass of predators on the predation mortality of prey.
(3.2) according to the conclusion of the ecosystem nutrition level spectrum, taking a 'peak clipping and valley filling' measure to the functional group which is higher or lower than the trend line for carrying out biological manipulation, and carrying out 'valley filling' biological manipulation scene simulation on the functional group which is lower than the trend line and carrying out 'peak clipping' biological manipulation scene simulation on the functional group which is higher than the trend line.
(3.3) according to the 'peak clipping and valley filling' biological manipulation simulation result of the Ecosim model, in the practical application process, catching organisms higher than the trend line as a 'peak clipping' biological manipulation strategy, and performing seedling proliferation and releasing on organisms lower than the trend line as a 'valley filling' biological manipulation strategy.
In order to clearly understand the actual content of the invention, the following specific embodiments are given to explain the invention in detail for providing a water ecosystem regulation method based on biological manipulation.
(1) An Ecopath model of a certain water area is constructed, and the functional group settings are shown in table 1:
TABLE 1 Ecopath model function set of ecosystem in a certain water area
(2) The input parameters of each functional group of the Ecopath model are determined by methods such as field investigation, empirical formula calculation and other similar ecosystem functional group parameter references, three of the four parameters are mainly input, the model can automatically output the fourth parameter, the input and output values of the lake model parameters are shown in table 2, the food matrix is mainly analyzed by gastric content and stable isotope, and the input data are shown in table 3.
TABLE 2 Ecopath model parameter input/output table
Note: the bold font is added to the table as the output value.
TABLE 3 Ecopath model food habit composition matrix
(3) The distribution of the energy flows of the functional groups of the ecosystem of a certain water area over the nutrient levels is shown in table 4. In a water ecosystem, both organic debris and energy flow of primary producers are distributed at a first nutrient level; the second nutrition level is completely distributed in large benthonic animals (hirsuts, telepodites and bivalves), zooplankton and bryozoans, most of omnivorous fishes, shrimps, crabs, tilapia, mullets and phytophagous fishes are distributed in the third nutrition level, and a small part of omnivorous fishes are distributed in the second nutrition level. Top predators, including carnivorous fish and seabirds, have their energy flows primarily concentrated in the third and fourth nutritional levels.
As can be seen from fig. 1, the Ecopath model of the water ecosystem includes 17 functional groups, five food chain paths are provided, starting from macroalgae, periphyton, phytoplankton, benthic microalgae and debris, the size of the circle in the figure represents the biomass of the corresponding functional group, the description of the two connected functional groups shows the predation relationship and the energy flow path, the thickness of the connection line represents the energy flow, the position of the functional group is determined by the nutritional level of the functional group, and the ordinate represents the nutritional level (i.e., fractional nutritional level).
TABLE 4 distribution of functional groups of ecosystem in Integrated Nutrition level (relative flow)
(4) The number of orders of magnitude of biomass of the nearly-ashore lagoon ecosystem is 4, and is 0.1-100, and the orders of magnitude of the biomass is narrower than that of a marine ecosystem. The nutrient level spectrum of a water area ecosystem generally shows a descending trend along with the increase of the nutrient level, the slope of the trend line of the current year is 0.18 and is higher than the normal slope range (5-10 percent), the biomass size fluctuates along with the increase of the nutrient level, and R is2A value of 0.23 indicates that the biomass of the entire ecosystem is concentrated in a partial trophic level. The biomass of crabs, tilapia, mullet, polychaetes and bivalves in the ecosystem is significantly higher than the trend line, while the biomass of carnivorous, planktonic, omnivorous, zooplankton and podophylls is significantly lower than the trend line. These functional groups are the functional groups of interest for performing biological manipulations. Fig. 2 shows a map of the annual trophic level of an ecosystem in a water area. Biomass decreases with increasing nutritional grade; the nutrition level is increased from right to left; the dotted line in the figure is a trend line.
(5) The vulnerability index is a necessary input parameter when the ecosmi model carries out biological manipulation scene simulation, the range of the vulnerability (Vulnerabilities) of the dominant species of the carnivorous fishes in the vulnerability (Vulnerabilities) value of the ecological system is 32-52, and the average value of the vulnerability (Vulnerabilities) is 40. Similarly, the values of the functional groups of plankton-feeding fishes, omnivorous fishes, mullets and tilapia were set to 15, 25, 30 and 30, respectively (table 5).
TABLE 5 vulnerability index (Vulnerabilities) between ecosystems predators and predators
(6) Situational simulation of biological manipulation of ecosystems in a body of water, based on the operability of functional groups, i.e.Performing 'grain filling' operation scene simulation on carnivorous fishes and omnivorous fishes in a certain water area; performing 'peak clipping' biological manipulation scene simulation on crab, mullet and tilapia functional groups; and carrying out comprehensive manipulation scene simulation on the ecosystem, namely combining the two manipulation methods. By comparison, it can be found that the removal rate of phytoplankton by the comprehensive manipulation is higher than that of the crab manipulation (fig. 3), and the removal rate of the phytoplankton can be improved by about 2.7-3.5% by the comprehensive manipulation. The removal rate of phytoplankton can reach 12.8 percent by using comprehensive manipulation. Comparing the removal rate of the phytoplankton comprehensively manipulated with the sum of the removal rates of the phytoplankton manipulated by the two functional groups respectively, and finding that the removal rate of the crabs is more than 28t/km2The effect of the comprehensive manipulation is larger than the superposition effect after the respective manipulations. To achieve' 1+1>2 "in the composition.
Claims (3)
1. A water area ecosystem regulation and control method based on biological manipulation is characterized by comprising the following steps:
1) constructing an Ecopath model by using the obtained model functional group parameters, and carrying out network, energy flow and logistics distribution;
2) establishing a nutrition level spectrum, determining whether the nutrition level and the biomass of the ecosystem are characterized by nutrition level increase and biomass reduction, drawing a trend line with a log as a base, determining a functional group higher or lower than the trend line, and providing a theoretical basis for biological manipulation by using a 'peak clipping and valley filling' strategy;
3) for functional groups above or below the trend line, a "peak clipping and valley filling" strategy was performed, and a biological manipulation simulation was performed using the ecosmim model.
2. A water ecosystem control method based on biological manipulation as claimed in claim 1, wherein in step 1), the concrete method for constructing Ecopath model by using the obtained model functional group parameters to perform network and energy flow and logistics distribution comprises:
(1.1) the Ecopath model firstly needs to divide the functional groups according to the actual ecosystem situation, and needs to accord with the following principle: simplifying a food net, and merging the populations with high ecological niche overlapping according to methods such as food composition, feeding mode, statistical classification of fishery catch and the like; the number of the debris groups is more than or equal to 1; the functional groups basically cover the whole process of energy flow of the ecosystem, and a certain functional group cannot be ignored due to lack of partial data, especially dominant species or key species or top-level predators and the like need to be considered;
(1.2) basic parameters of the Ecopath model are input, three of four parameters of B (biomass), P/B (production amount/biomass), Q/B (consumption amount/biomass) and EE (ecological nutrition conversion efficiency) need to be input into each functional group, the first three parameters are mainly input into the model, and the model can automatically output a fourth parameter value; in addition, the model also needs a feeding property matrix to reflect the predation relationship in the ecosystem;
and (1.3) analyzing the nutrient structure in the target ecosystem and energy flow distribution among all nutrient levels, and intuitively obtaining energy flow paths among all functional groups through an energy flow diagram.
3. A method as claimed in claim 1 wherein in step 3) said "load shifting" strategy comprises the steps of:
(3.1) constructing a biological control Ecosim model, wherein the Ecosim model is based on the Ecopath model, besides input parameters of the Ecopath model, a vulnerability relation index is also required to be input, and the numerical value represents the influence of the increase of the biomass of predators on the predation mortality of prey;
(3.2) according to the conclusion of the ecosystem nutrition level spectrum, adopting a 'peak clipping and valley filling' measure to carry out biological manipulation on the functional groups which are higher or lower than the trend line, carrying out 'valley filling' biological manipulation scenario simulation on the functional groups which are lower than the trend line, and carrying out 'peak clipping' biological manipulation scenario simulation on the functional groups which are higher than the trend line;
(3.3) according to the 'peak clipping and valley filling' biological manipulation simulation result of the Ecosim model, in the practical application process, catching organisms higher than the trend line as a 'peak clipping' biological manipulation strategy, and performing seedling proliferation and releasing on organisms lower than the trend line as a 'valley filling' biological manipulation strategy.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113505913A (en) * | 2021-06-03 | 2021-10-15 | 武汉大学 | Reservoir optimal scheduling decision method and device for stability of aquatic community system |
| CN116090229A (en) * | 2023-01-16 | 2023-05-09 | 上海勘测设计研究院有限公司 | Lake eutrophication organism control method, system and medium based on EwE model |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107804914A (en) * | 2017-11-13 | 2018-03-16 | 华北电力大学 | A kind of method based on food web regulation and control lake alga eruption |
| CN110845013A (en) * | 2019-10-30 | 2020-02-28 | 上海海洋大学 | Method for regulating and stably maintaining ecological system of shallow lake |
-
2020
- 2020-07-06 CN CN202010641468.4A patent/CN111783305A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107804914A (en) * | 2017-11-13 | 2018-03-16 | 华北电力大学 | A kind of method based on food web regulation and control lake alga eruption |
| CN110845013A (en) * | 2019-10-30 | 2020-02-28 | 上海海洋大学 | Method for regulating and stably maintaining ecological system of shallow lake |
| CN111252898A (en) * | 2019-10-30 | 2020-06-09 | 上海海洋大学 | Method for regulating and stably maintaining ecological system of shallow lake |
Non-Patent Citations (1)
| Title |
|---|
| 郑磊: "基于生态模型的筼筜湖生物操纵情景模拟研究", 《中国优秀博硕士学位论文全文数据库(硕士) 工程科技Ⅰ辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113505913A (en) * | 2021-06-03 | 2021-10-15 | 武汉大学 | Reservoir optimal scheduling decision method and device for stability of aquatic community system |
| CN113505913B (en) * | 2021-06-03 | 2022-07-05 | 武汉大学 | Reservoir optimal scheduling decision method and device for stability of aquatic community system |
| CN116090229A (en) * | 2023-01-16 | 2023-05-09 | 上海勘测设计研究院有限公司 | Lake eutrophication organism control method, system and medium based on EwE model |
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