Natural wetland restoration method and system based on plant community adaptability adjustment

Abstract

The invention discloses a natural wetland restoration method and system based on plant community adaptability adjustment, and aims to improve the wetland restoration effect through optimization adjustment of a plant community structure. The method comprises the following steps: acquiring baseline data (such as geographical environment, plant community, hydrological condition and pollution condition) of a target natural wetland, and constructing a physical model based on the data; environment change simulation is carried out, the adaptability of plant communities is evaluated, and ecological function indexes are determined; adjusting a plant community structure according to an evaluation result, and formulating an adjustment scheme; wetland restoration is implemented, and a monitoring system is established; and obtaining a restoration effect in real time through a monitoring system, and optimizing a plant community structure adjustment scheme. According to the method, adaptability evaluation and monitoring feedback are combined, the ecological function of the wetland can be continuously improved, and the method is widely suitable for restoration and ecological restoration of the natural wetland and has high application value.

Description

Technical Field

[0001] This invention relates to the field of wetland restoration technology, and in particular to a method and system for natural wetland restoration based on the adaptive regulation of plant communities. Background Technology

[0002] Most existing wetland restoration technologies rely on physical and chemical methods, such as landfilling, sludge treatment, and chemical purification. These methods are often costly, time-consuming, and their restoration effects are difficult to sustain. In addition, traditional wetland restoration methods focus too much on water quality and hydrological conditions, neglecting the important role of wetland plant communities in the restoration process.

[0003] Plant communities play a crucial role in the restoration of natural wetlands, with their species, structure, and ecological functions directly influencing the ecological health and functional recovery of wetlands. However, due to factors such as climate change, hydrological variations, and pollution pressures, the natural recovery of traditional wetland plant communities is often limited, making it difficult for them to adapt to new environmental conditions. Therefore, how to adaptively regulate plant communities according to environmental changes to achieve efficient and sustainable wetland restoration has become a current research challenge and hot topic.

[0004] Currently, although some methods exist for wetland plant community regulation and wetland restoration, most lack systematic environmental adaptability assessment and dynamic regulation mechanisms. These methods cannot reflect the real-time interaction between plant communities and the environment, leading to unstable restoration outcomes and poor operability. Therefore, there is an urgent need for a wetland restoration method that combines environmental change prediction, plant adaptability assessment, and community structure optimization to achieve long-term restoration and continuous improvement of natural wetland ecological functions.

[0005] This invention proposes a method and system for natural wetland restoration based on plant community adaptive regulation. By integrating environmental change simulation, plant adaptability assessment, and community structure optimization and regulation, it provides a systematic, dynamic, and operable wetland restoration scheme. Summary of the Invention

[0006] To address at least one of the aforementioned technical problems, this invention proposes a method and system for restoring natural wetlands based on the adaptive regulation of plant communities.

[0007] The first aspect of this invention provides a method for restoring natural wetlands based on the adaptive regulation of plant communities, comprising: Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological conditions data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. The physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results. Based on the adaptive assessment results, the ecological function index of the current plant community structure is determined, and the current plant community structure is adjusted according to the ecological function index to construct a plant community structure adjustment scheme. Based on the plant community structure adjustment scheme, wetland restoration was carried out on the target natural wetland, and a wetland restoration monitoring system was constructed. The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the plant community structure adjustment optimization scheme.

[0008] In this scheme, the acquisition of baseline data of the target natural wetland to be restored includes geographical environmental data, current plant community structure data, and hydrological condition data of the target natural wetland. A physical model of the target natural wetland is then constructed based on the baseline data, specifically as follows: Geographic environmental data of the target natural wetland to be restored is obtained based on a geographic information system, including topographic and geomorphological data of the target natural wetland. The plant community structure sampling area of ​​the target natural wetland is selected based on stratified sampling method, plant multispectral data of the plant community structure sampling area are obtained, plant species of the target natural wetland are determined based on the plant multispectral data, and the distribution range of each plant species is determined. A preset number of survey plots are set in the distribution range of each plant species. Obtain plant information for each survey quadrat, including plant species, quantity, height, and coverage. Determine the plant community structure of the target natural wetland based on the plant information and distribution range of each survey quadrat, and obtain the current plant community structure data of the target natural wetland. Hydrological monitoring points are constructed at predetermined locations in the target natural wetland. Based on the hydrological monitoring points, water quality data, water level information, and water flow velocity and direction information of each hydrological monitoring point in the target natural wetland are obtained to obtain hydrological condition data. Obtain pollution data of the target natural wetland, including the location, degree, and type of pollution of the land and water bodies; The geographical environment data, current plant community structure data, hydrological condition data, and pollution status data of the target natural wetland are used as the baseline data of the target natural wetland. A three-dimensional terrain model of the target natural wetland is constructed based on the geographical environment data. The current plant community structure data, hydrological condition data, and pollution data are mapped into the three-dimensional terrain model to construct a physical model of the target natural wetland.

[0009] In this scheme, the physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results, specifically as follows: A list of plant species is constructed based on the current plant community structure data of the target natural wetland. The suitable environmental conditions and environmental regulation capacity data of each plant species in the list are obtained from the Internet. A plant growth model is constructed based on the L-System algorithm. Historical climate change data and historical hydrological change data of the target natural wetland over a preset time period are obtained. A climate change simulation model and a hydrological change simulation model of the target natural wetland are constructed. The climate change simulation model and the hydrological change simulation model are fitted to the historical climate change data and the historical hydrological change data. The climate change simulation model and the hydrological change simulation model are integrated with the physical model to construct an environmental change simulation model of the target natural wetland. An environmental condition change prediction model is constructed based on the LSTM algorithm. The historical climate change data and historical hydrological change data are divided into a training set and a prediction set according to a preset ratio. The training set is imported into the environmental condition change prediction model for training. The prediction set is imported into the environmental condition change prediction model after training to predict environmental condition changes within a preset time period in the future, thereby obtaining climate change prediction data and hydrological change prediction data. The plant growth model is integrated with the environmental change simulation model. The climate change prediction data and hydrological change prediction data are imported into the environmental change simulation model to simulate environmental conditions. Based on the plant growth model and the suitable environmental conditions and environmental regulation capacity data of plant species, the plant growth of the target natural wetland is simulated, and the plant growth in the future within a preset time period is predicted to obtain the plant growth prediction results. Based on the plant growth prediction results, determine the plant community evolution trend of the target natural wetland within a future preset time period, and evaluate the wetland ecological improvement index and pollution reduction index of the target natural wetland within the future preset time period based on the plant community evolution trend. The current plant community structure of the target natural wetland is assessed for its adaptability based on the wetland ecological enhancement index and pollution reduction index, resulting in an adaptability evaluation.

[0010] In this scheme, the step of importing the climate change prediction data and hydrological change prediction data into the environmental change simulation model for environmental condition simulation, and simulating the plant growth of the target natural wetland based on the plant growth model and the suitable environmental conditions and environmental regulation capacity data of plant species, specifically involves: Calculate the annual average temperature and annual precipitation of the target natural wetland for the next year based on the climate change prediction data and hydrological change prediction data. If the annual average temperature value is greater than the preset temperature threshold, the simulated value of the plant growth model for the plant photosynthetic efficiency is reduced, and the reduction coefficient of the simulated value is determined based on the suitable environmental conditions data of each plant species. Acquire the relationship data between phenological period and temperature for each plant species in the target natural wetland. Based on the relationship data and climate change prediction data, predict the time range of advance or lag of the phenological period for each plant species. If the number of days of advance of the phenological period is greater than the preset phenological advance threshold, adjust the reproductive body germination time parameter in the plant community structure data of the plant growth model. If the number of days of lag of the phenological period is greater than the preset phenological lag threshold, correct the flowering duration parameter in the plant community structure data. If the annual precipitation value is greater than the preset precipitation threshold, the duration of water accumulation at different locations in the target natural wetland is predicted based on the climate change prediction data and hydrological change prediction data. Based on the plant waterlogging tolerance data, if the plant's waterlogging tolerance duration is less than the predicted water accumulation duration, the plant is marked as a plant affected by waterlogging in the plant community structure data, and its competitiveness parameter in the community is reduced. If the plant's waterlogging tolerance duration is greater than the predicted water accumulation duration and greater than the preset waterlogging tolerance advantage threshold, its reproduction and diffusion parameter in the community is increased. The parameters of the plant growth model were optimized based on the reduction coefficient, propagation time parameter, flowering duration parameter, competitiveness parameter, and propagation and diffusion parameter.

[0011] In this scheme, the step of determining the ecological function index of the current plant community structure based on the adaptive assessment results, adjusting the current plant community structure based on the ecological function index, and constructing a plant community structure adjustment scheme specifically involves: Obtain restoration target data for the target natural wetland, including restoration degree of plant area coverage, restoration degree of plant population richness, pollution restoration degree, and restoration duration target; obtain the influence weight information of each restoration target on the ecological function index. Based on the adaptive assessment results, determine the restoration capacity of the current plant community structure of the target natural wetland for each restoration target, divide the target natural wetland into N sub-regions, and calculate the ecological function index of the current plant community structure of each sub-region based on the restoration capacity and the influence weight information. Based on the restoration target data, the ecological function index threshold is determined, and sub-regions with ecological function indices less than the ecological function index threshold are marked to obtain the areas where the plant community structure needs to be optimized. Based on the climate condition data of the target natural wetland, obtain the suitable plants of the target natural wetland, obtain the ecological function data of each suitable plant, and construct a suitable plant database by combining the suitable plants and ecological function data. Based on the ecological function index, the type of ecological defect in the area to be optimized is determined. Based on the type of ecological defect, plant species are matched in the suitable plant database to identify plant types with complementary ecological functions to the type of ecological defect and label them as community structure optimization plants. The number and density of plants for optimizing community structure in each sub-region are determined based on the ecological defect type and the ecological function index. Based on the optimized plant quantity and density according to the community structure, the current plant community structure of each sub-region is adjusted to obtain a plant community structure adjustment scheme.

[0012] In this scheme, the wetland restoration of the target natural wetland according to the plant community structure adjustment scheme and the construction of a wetland restoration monitoring system are specifically as follows: The plant community structure adjustment scheme is used to restore the target natural wetland, and wetland restoration monitoring data of each sub-region in the target natural wetland is obtained under various environmental characteristics. Calculate the Euclidean distance between wetland restoration monitoring data in each sub-region, determine the similarity between wetland restoration monitoring data in each sub-region based on the Euclidean distance, and construct a similarity matrix; Based on the similarity matrix, sub-regions with similarity greater than a preset value are merged through data monitoring to obtain merged sub-regions; One of the merged sub-regions is randomly selected as the representative monitoring area. Wetland restoration monitoring sensors are deployed in the representative monitoring area, and a wetland restoration monitoring system is constructed based on the deployed wetland restoration monitoring sensors.

[0013] In this scheme, the restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system, and the plant community structure adjustment scheme is optimized based on the restoration effect to obtain an optimized plant community structure adjustment scheme, specifically as follows: The wetland restoration monitoring system acquires periodic wetland restoration monitoring data of the target natural wetland according to a preset time period, and determines the restoration degree requirement within each preset time period based on the restoration target data of the target natural wetland. The periodic wetland restoration monitoring data are compared with the restoration level requirements to evaluate the restoration effect of the target natural wetland within a preset time period; If the repair effect of a preset number of time periods does not meet the repair requirements, the interaction relationship between each plant species in each sub-region is obtained. If there is a competitive relationship between plant species, the dominant plant species is retained, and the plant species that compete with the dominant plant species are replaced to obtain the plant community structure adjustment and optimization scheme.

[0014] A second aspect of the present invention also provides a natural wetland restoration system based on plant community adaptive regulation. The system includes a memory and a processor. The memory includes a program for a natural wetland restoration method based on plant community adaptive regulation. When the processor executes the program for the natural wetland restoration method based on plant community adaptive regulation, it performs the following steps: Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological conditions data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. The physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results. Based on the adaptive assessment results, the ecological function index of the current plant community structure is determined, and the current plant community structure is adjusted according to the ecological function index to construct a plant community structure adjustment scheme. Based on the plant community structure adjustment scheme, wetland restoration was carried out on the target natural wetland, and a wetland restoration monitoring system was constructed. The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the plant community structure adjustment optimization scheme.

[0015] This invention discloses a method and system for natural wetland restoration based on plant community adaptive regulation, aiming to improve wetland restoration effects through optimized regulation of plant community structure. The method includes the following steps: acquiring baseline data of the target natural wetland (such as geographical environment, plant community, hydrological conditions, and pollution status), and constructing a physical model based on this data; conducting environmental change simulations to assess the adaptability of the plant community and determine ecological function indices; adjusting the plant community structure according to the assessment results and formulating an adjustment plan; implementing wetland restoration and establishing a monitoring system; and acquiring the restoration effect in real time through the monitoring system and optimizing the plant community structure adjustment plan. This method, combining adaptive assessment and monitoring feedback, can continuously improve the ecological function of wetlands, is widely applicable to the restoration and ecological recovery of natural wetlands, and has high application value. Attached Figure Description

[0016] Figure 1A flowchart of a natural wetland restoration method based on plant community adaptive regulation according to the present invention is shown; Figure 2 The flowchart illustrating the wetland restoration monitoring system constructed according to the present invention is shown; Figure 3 The flowchart of the plant community structure adjustment and optimization scheme obtained by the present invention is shown; Figure 4 A block diagram of a natural wetland restoration system based on plant community adaptive regulation according to the present invention is shown. Detailed Implementation

[0017] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0019] Figure 1 The flowchart of a natural wetland restoration method based on plant community adaptive regulation according to the present invention is shown.

[0020] like Figure 1 As shown, the first aspect of this invention provides a method for restoring natural wetlands based on adaptive regulation of plant communities, comprising: S102, Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological condition data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. S104, simulate environmental changes in the physical model, and conduct an adaptive assessment of the current plant community structure of the target natural wetland based on the environmental change simulation to obtain the adaptive assessment results; S106, Determine the ecological function index of the current plant community structure based on the adaptive assessment results, adjust the current plant community structure based on the ecological function index, and construct a plant community structure adjustment scheme; S108, according to the plant community structure adjustment scheme, wetland restoration is carried out on the target natural wetland, and a wetland restoration monitoring system is constructed; S110, based on the real-time acquisition of the restoration effect of the target natural wetland by the wetland restoration monitoring system, the plant community structure adjustment scheme is optimized according to the restoration effect to obtain the plant community structure adjustment optimization scheme.

[0021] It should be noted that by acquiring baseline data of the target natural wetland to construct a physical model, and then simulating environmental changes based on the physical model, the adaptability of the current plant community structure can be assessed. Environmental change simulation can predict fluctuations in different climates and hydrological conditions. Through adaptability assessment, the tolerance and responsiveness of the plant community to these potential environmental changes can be quantified. The assessment results clearly reveal the performance of dominant, inferior, and key species in the current plant community structure under different environmental pressures. Based on the adaptability assessment results, an ecological function index is calculated. This index comprehensively reflects the performance of the plant community structure in maintaining wetland ecosystem services. Based on the ecological function index, the shortcomings and advantages of the current plant community structure in fulfilling its ecological functions can be accurately identified. Furthermore, by adjusting the plant community structure, an optimized plant community structure adjustment plan can be constructed. Through data continuously collected by the wetland restoration monitoring system, and based on a dynamic optimization mechanism using real-time monitoring data, the plant community structure can continuously adapt to the actual conditions during the wetland restoration process.

[0022] According to an embodiment of the present invention, the step of obtaining baseline data of the target natural wetland to be restored, wherein the baseline data includes geographical environmental data, current plant community structure data, and hydrological condition data of the target natural wetland, and constructing a physical model of the target natural wetland based on the baseline data, specifically involves: Geographic environmental data of the target natural wetland to be restored is obtained based on a geographic information system, including topographic and geomorphological data of the target natural wetland. The plant community structure sampling area of ​​the target natural wetland is selected based on stratified sampling method, plant multispectral data of the plant community structure sampling area are obtained, plant species of the target natural wetland are determined based on the plant multispectral data, and the distribution range of each plant species is determined. A preset number of survey plots are set in the distribution range of each plant species. Obtain plant information for each survey quadrat, including plant species, quantity, height, and coverage. Determine the plant community structure of the target natural wetland based on the plant information and distribution range of each survey quadrat, and obtain the current plant community structure data of the target natural wetland. Hydrological monitoring points are constructed at predetermined locations in the target natural wetland. Based on the hydrological monitoring points, water quality data, water level information, and water flow velocity and direction information of each hydrological monitoring point in the target natural wetland are obtained to obtain hydrological condition data. Obtain pollution data of the target natural wetland, including the location, degree, and type of pollution of the land and water bodies; The geographical environment data, current plant community structure data, hydrological condition data, and pollution status data of the target natural wetland are used as the baseline data of the target natural wetland. A three-dimensional terrain model of the target natural wetland is constructed based on the geographical environment data. The current plant community structure data, hydrological condition data, and pollution data are mapped into the three-dimensional terrain model to construct a physical model of the target natural wetland.

[0023] It should be noted that the three-dimensional terrain model constructed based on topographic data obtained from a geographic information system can intuitively present the spatial morphology and topographic relief of wetlands. By mapping the current plant community structure data into it, the model can accurately present the distribution pattern, quantity, and growth status of different plant species in three-dimensional space. It can intuitively assess the spatial heterogeneity and niche distribution of plant communities. The integration of hydrological data enables the model to simulate the dynamic changes of water in wetlands, including the impact of seasonal fluctuations in water level and changes in water flow speed and direction on the wetland ecosystem. The integration of pollution data further improves the model's characterization of wetland ecological stressors, and can intuitively show the distribution range and concentration gradient of pollution in wetlands. This helps to predict pollution diffusion trends and assess the effectiveness of different remediation strategies for pollution reduction.

[0024] According to an embodiment of the present invention, the step of simulating environmental changes in the physical model and conducting an adaptive assessment of the current plant community structure of the target natural wetland based on the environmental change simulation to obtain the adaptive assessment results is specifically as follows: A list of plant species is constructed based on the current plant community structure data of the target natural wetland. The suitable environmental conditions and environmental regulation capacity data of each plant species in the list are obtained from the Internet. A plant growth model is constructed based on the L-System algorithm. Historical climate change data and historical hydrological change data of the target natural wetland over a preset time period are obtained. A climate change simulation model and a hydrological change simulation model of the target natural wetland are constructed. The climate change simulation model and the hydrological change simulation model are fitted to the historical climate change data and the historical hydrological change data. The climate change simulation model and the hydrological change simulation model are integrated with the physical model to construct an environmental change simulation model of the target natural wetland. It's important to note that the L-System (Lindenmeier System) is a parallel rewriting system based on string rewriting, used to simulate morphogenesis processes such as plant growth. First, for each plant in the list of plant species, an initial state is determined based on its suitable environmental conditions and environmental regulation capabilities. This initial state can be represented by a string, where characters represent different structural parts of the plant (such as stems, leaves, branches, etc.) or growth stages. Then, a set of production rules is defined. These rules describe how the plant grows and changes under different conditions. For example, a simple rule might be "If there is currently a stem node, with a certain probability, a new branch and a leaf will be produced." At each time step, the string is rewritten according to the rules, and the new string represents the plant's new state after a growth stage. For example, the initial string might represent the simple structure of a seedling; after several time steps of rewriting, the string becomes increasingly complex, representing morphological changes in the plant over time, such as the growth of more branches and leaves, and an increase in stem length. By repeatedly performing this process and combining parameters such as plant growth rate and growth cycle (which can also be obtained from data on suitable environmental conditions and environmental regulation capacity), a plant growth model that can simulate the growth process of plants in an ideal environment can be constructed. The suitable environmental conditions and environmental regulation capacity data include temperature, light, water (flood and drought tolerance), and soil (pH, fertility, texture). Environmental regulation capacity data includes soil regulation (nitrogen fixation, improving soil structure) and water purification (absorbing and transforming nutrients, adsorbing and degrading pollutants). The climate change data and historical hydrological change data include multi-year temperature (daily, monthly, and annual averages, extreme values, seasonal variations) and precipitation (precipitation amount, seasonal distribution, intensity). Historical hydrological change data covers water level, flow rate changes, and water quality (pollutant type and concentration changes) at different monitoring points.

[0025] An environmental condition change prediction model is constructed based on the LSTM algorithm. The historical climate change data and historical hydrological change data are divided into a training set and a prediction set according to a preset ratio. The training set is imported into the environmental condition change prediction model for training. The prediction set is imported into the environmental condition change prediction model after training to predict environmental condition changes within a preset time period in the future, thereby obtaining climate change prediction data and hydrological change prediction data. The plant growth model is integrated with the environmental change simulation model. The climate change prediction data and hydrological change prediction data are imported into the environmental change simulation model to simulate environmental conditions. Based on the plant growth model and the suitable environmental conditions and environmental regulation capacity data of plant species, the plant growth of the target natural wetland is simulated, and the plant growth in the future within a preset time period is predicted to obtain the plant growth prediction results. Based on the plant growth prediction results, determine the plant community evolution trend of the target natural wetland within a future preset time period, and evaluate the wetland ecological improvement index and pollution reduction index of the target natural wetland within the future preset time period based on the plant community evolution trend. The current plant community structure of the target natural wetland is assessed for its adaptability based on the wetland ecological enhancement index and pollution reduction index, resulting in an adaptability evaluation.

[0026] It should be noted that the LSTM (Long Short-Term Memory) algorithm, after being trained on historical climate change data (such as multi-year temperature and precipitation sequences) and historical hydrological change data (including water level fluctuations and flow changes), can accurately capture the long-term trends, seasonal patterns, and periodic variations in these environmental conditions. For precipitation and hydrological conditions, it can predict the cycles of precipitation abundance and scarcity, as well as the trends in water level rise and fall. Based on the wetland ecological enhancement index and pollution reduction index, it can assess the adaptability of the current plant community structure of a target natural wetland, accurately pinpointing its performance in wetland ecological function and pollution purification. In cases where the pollution reduction index is unsatisfactory, it can be analyzed whether the plant community's ability to absorb and transform specific pollutants is insufficient, or whether an unreasonable plant community structure leads to poor water flow, affecting the water body's self-purification process. Based on these analyses, targeted optimization schemes for the plant community structure can be proposed. Higher wetland ecological enhancement and pollution reduction indices indicate higher adaptability.

[0027] According to an embodiment of the present invention, the step of importing the climate change prediction data and hydrological change prediction data into the environmental change simulation model for environmental condition simulation, and simulating the plant growth of the target natural wetland based on the plant growth model and the suitable environmental conditions and environmental regulation capacity data of plant species, specifically includes: Calculate the annual average temperature and annual precipitation of the target natural wetland for the next year based on the climate change prediction data and hydrological change prediction data. If the annual average temperature value is greater than the preset temperature threshold, the simulated value of the plant growth model for the plant photosynthetic efficiency is reduced, and the reduction coefficient of the simulated value is determined based on the suitable environmental conditions data of each plant species. Acquire the relationship data between phenological period and temperature for each plant species in the target natural wetland. Based on the relationship data and climate change prediction data, predict the time range of advance or lag of the phenological period for each plant species. If the number of days of advance of the phenological period is greater than the preset phenological advance threshold, adjust the reproductive body germination time parameter in the plant community structure data of the plant growth model. If the number of days of lag of the phenological period is greater than the preset phenological lag threshold, correct the flowering duration parameter in the plant community structure data. It should be noted that different plant species have varying tolerances and adaptation ranges to temperature. When a certain threshold is exceeded, plant growth may be inhibited or its ecological functions may be altered, thereby affecting the overall wetland plant community structure and ecosystem stability. By reducing the simulated photosynthetic efficiency of plant growth models and determining the reduction coefficient based on the suitable environmental conditions for each plant species, the degree of decline in photosynthetic capacity of different plants under high temperatures can be reflected more accurately. This helps to more realistically simulate the slowdown in plant growth rate under rising temperature scenarios, thereby predicting changes in plant community productivity and their impact on ecological functions such as the carbon cycle of wetland ecosystems at the model level. For example, some temperature-sensitive herbaceous plants may experience a significant decrease in photosynthetic efficiency, leading to reduced biomass accumulation. Model simulations can predict the cascading effects of this change on wetland vegetation cover and ecosystem service functions. Temperature changes significantly affect plant phenology; for instance, rising spring temperatures may advance phenological stages such as germination and flowering, while delayed autumn temperature drops may postpone leaf fall and dormancy. When the predicted advance in phenological stages exceeds a preset threshold, adjusting the propagule germination time parameter in the plant community structure data of the plant growth model can accurately reflect the earlier initiation of the plant reproductive cycle in the model. This helps simulate changes in the pace of plant community renewal and their impact on seed bank dynamics and seedling competition patterns in wetland ecosystems. When the phenological lag exceeds a preset threshold, correcting the flowering duration parameter in the plant community structure data can reflect the impact of prolonged or shortened flowering periods on reproductive success rates in the model.

[0028] If the annual precipitation value is greater than the preset precipitation threshold, the duration of water accumulation at different locations in the target natural wetland is predicted based on the climate change prediction data and hydrological change prediction data. Based on the plant waterlogging tolerance data, if the plant's waterlogging tolerance duration is less than the predicted water accumulation duration, the plant is marked as a plant affected by waterlogging in the plant community structure data, and its competitiveness parameter in the community is reduced. If the plant's waterlogging tolerance duration is greater than the predicted water accumulation duration and greater than the preset waterlogging tolerance advantage threshold, its reproduction and diffusion parameter in the community is increased. The parameters of the plant growth model were optimized based on the reduction coefficient, propagation time parameter, flowering duration parameter, competitiveness parameter, and propagation and diffusion parameter.

[0029] It is important to note that changes in precipitation patterns are a key characteristic of climate change. In wetland areas, a significant increase in precipitation can exacerbate waterlogging and lead to flooding. Different plants have varying tolerances to flooding, which can alter the competitive landscape within wetland plant communities. By predicting the duration of waterlogging at different locations in target natural wetlands based on climate change and hydrological change data, and combining this with plant flood tolerance data, we can label plants affected by flooding and reduce their competitiveness parameters within the community. This allows us to realistically simulate the reshaping effect of flooding on plant community structure in the model. Through this simulation, we can predict the succession direction of wetland plant communities, such as the transition from communities dominated by flood-intolerant plants to flood-tolerant plant communities, and the impact of this transition on wetland ecosystem functions. For plants whose flood tolerance duration exceeds the predicted waterlogging duration and is above the preset flood tolerance advantage threshold, increasing their reproduction and dispersal parameters within the community helps to reflect the competitive advantage and expansion trend of these plants under flooding conditions in the model. This study can predict the succession of dominant species in wetland plant communities and the enhancing effect of new plant community structures on wetland ecosystem functions. For example, the dominance of flood-tolerant plants with high water purification capabilities may improve the wetland's removal efficiency of nutrients such as nitrogen and phosphorus. The plant flood tolerance data was obtained from the internet, and the competitiveness parameters include growth rate parameters.

[0030] According to an embodiment of the present invention, the step of determining the ecological function index of the current plant community structure based on the adaptive assessment results, adjusting the current plant community structure based on the ecological function index, and constructing a plant community structure adjustment scheme specifically includes: Obtain restoration target data for the target natural wetland, including restoration degree of plant area coverage, restoration degree of plant population richness, pollution restoration degree, and restoration duration target; obtain the influence weight information of each restoration target on the ecological function index. Based on the adaptive assessment results, determine the restoration capacity of the current plant community structure of the target natural wetland for each restoration target, divide the target natural wetland into N sub-regions, and calculate the ecological function index of the current plant community structure of each sub-region based on the restoration capacity and the influence weight information. Based on the restoration target data, the ecological function index threshold is determined, and sub-regions with ecological function indices less than the ecological function index threshold are marked to obtain the areas where the plant community structure needs to be optimized. Based on the climate condition data of the target natural wetland, obtain the suitable plants of the target natural wetland, obtain the ecological function data of each suitable plant, and construct a suitable plant database by combining the suitable plants and ecological function data. Based on the ecological function index, the type of ecological defect in the area to be optimized is determined. Based on the type of ecological defect, plant species are matched in the suitable plant database to identify plant types with complementary ecological functions to the type of ecological defect and label them as community structure optimization plants. The number and density of plants for optimizing community structure in each sub-region are determined based on the ecological defect type and the ecological function index. Based on the optimized plant quantity and density according to the community structure, the current plant community structure of each sub-region is adjusted to obtain a plant community structure adjustment scheme.

[0031] It should be noted that by determining the ecological function index based on the restoration target data and corresponding impact weight information, a precise quantitative assessment of the ecological function of the target natural wetland plant community structure is achieved. For example, by clarifying the weights of targets such as plant area coverage, species richness, and pollution remediation degree, and comprehensively considering the restoration capacity of the current plant community structure for each target, the ecological function index of each sub-region can be accurately calculated. This allows for a clear positioning of the functional status of plant communities in different wetland areas, accurately identifying functional weaknesses, i.e., areas where the plant community structure needs optimization. Based on the climatic conditions of the target natural wetland, suitable plants are selected and a database is constructed, fully considering local climate adaptability to ensure the survival and healthy growth of introduced plants. By matching plants for community structure optimization in the suitable plant database according to the type of ecological defects in the areas to be optimized, plant species with complementary ecological functions can be accurately selected. The planting quantity and density of plants for community structure optimization are determined based on the type of ecological defects and the ecological function index, allowing for the customization of plant community structure adjustment schemes that meet the actual needs of each sub-region. This customized scheme avoids indiscriminate planting, rationally allocates plant resources, and ensures the optimal adjustment of the plant community structure under limited space and resource conditions.

[0032] Figure 2 A flowchart illustrating the wetland restoration monitoring system constructed according to the present invention is shown.

[0033] According to an embodiment of the present invention, the step of wetland restoration of the target natural wetland based on the plant community structure adjustment scheme and the construction of a wetland restoration monitoring system specifically includes: S202, Obtain the plant community structure adjustment scheme to carry out wetland restoration of the target natural wetland, and obtain wetland restoration monitoring data of each sub-region in the target natural wetland under various environmental characteristics; S204, calculate the Euclidean distance between wetland restoration monitoring data in each sub-region, determine the similarity between wetland restoration monitoring data in each sub-region based on the Euclidean distance, and construct a similarity matrix; S206, Based on the similarity matrix, sub-regions with similarity greater than a preset value are merged through data monitoring to obtain merged sub-regions; S208, randomly select one of the merged sub-regions as the monitoring representative region, deploy wetland restoration monitoring sensors in the monitoring representative region, and construct a wetland restoration monitoring system based on the deployed wetland restoration monitoring sensors.

[0034] It should be noted that by calculating the Euclidean distance between wetland restoration monitoring data in sub-regions and constructing a similarity matrix, the similarity between data from different sub-regions can be quickly and effectively quantified. Based on this, data monitoring of sub-regions with similarity values ​​greater than a preset value is merged, achieving the integration of regions with similar ecological characteristics and restoration processes, reducing data redundancy and monitoring workload. For example, in some geographically adjacent sub-regions with similar environmental conditions within wetlands, the trends in plant community structure changes after adjustment may be quite similar. Merging them into a merged sub-region for unified management and monitoring avoids repetitive and inefficient individual monitoring of each sub-region, improving the overall efficiency of wetland restoration monitoring. Randomly selecting a representative monitoring area within the merged sub-region to deploy wetland restoration monitoring sensors and construct a monitoring system further optimizes the monitoring layout while ensuring comprehensiveness and accuracy. Because the sub-regions within the merged sub-region have high similarity, the data from the selected representative monitoring area can largely reflect the wetland restoration status of the entire merged sub-region.

[0035] Figure 3 The flowchart of the plant community structure adjustment and optimization scheme obtained by the present invention is shown.

[0036] According to an embodiment of the present invention, the step of acquiring the restoration effect of the target natural wetland in real time based on the wetland restoration monitoring system, and optimizing the plant community structure adjustment scheme based on the restoration effect to obtain an optimized plant community structure adjustment scheme, specifically includes: S302, according to the wetland restoration monitoring system, periodic wetland restoration monitoring data of the target natural wetland are obtained according to a preset time period, and the restoration degree requirement in each preset time period is determined according to the restoration target data of the target natural wetland. S304, compare the periodic wetland restoration monitoring data with the restoration degree requirements to evaluate the restoration effect of the target natural wetland within a preset time period; S306, if the repair effect of a preset number of time periods does not meet the repair requirements, obtain the interaction relationship between each plant species in each sub-region. If there is a competitive relationship between plant species, retain the dominant plant species and replace the plant species that compete with the dominant plant species to obtain the plant community structure adjustment and optimization scheme.

[0037] It should be noted that by acquiring periodic wetland restoration monitoring data through a wetland restoration monitoring system at preset time intervals and comparing it with the required restoration level, the restoration effect of the target natural wetland at each stage can be accurately assessed. This quantitative assessment can promptly identify whether the restoration work deviates from the expected goals. When poor restoration results are found and plant competition exists, retaining the dominant plant species and replacing the competing plant species helps optimize the plant community structure. Dominant plant species usually have better adaptability and ecological function potential under current environmental conditions; retaining them can maintain some stability and functional basis of the community. Replacing competing plant species can introduce plants that can better symbiotically coexist with the dominant species or have complementary ecological functions, avoiding excessive consumption of internal resources through competition and improving the overall resource utilization efficiency and ecological function of the plant community.

[0038] Figure 4 A block diagram of a natural wetland restoration system based on plant community adaptive regulation according to the present invention is shown.

[0039] A second aspect of the present invention also provides a natural wetland restoration system 4 based on plant community adaptive regulation. The system includes a memory 41 and a processor 42. The memory includes a program for a natural wetland restoration method based on plant community adaptive regulation. When the processor executes the program for the natural wetland restoration method based on plant community adaptive regulation, it performs the following steps: Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological conditions data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. The physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results. Based on the adaptive assessment results, the ecological function index of the current plant community structure is determined, and the current plant community structure is adjusted according to the ecological function index to construct a plant community structure adjustment scheme. Based on the plant community structure adjustment scheme, wetland restoration was carried out on the target natural wetland, and a wetland restoration monitoring system was constructed. The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the plant community structure adjustment optimization scheme.

[0040] This invention discloses a method and system for natural wetland restoration based on plant community adaptive regulation, aiming to improve wetland restoration effects through optimized regulation of plant community structure. The method includes the following steps: acquiring baseline data of the target natural wetland (such as geographical environment, plant community, hydrological conditions, and pollution status), and constructing a physical model based on this data; conducting environmental change simulations to assess the adaptability of the plant community and determine ecological function indices; adjusting the plant community structure according to the assessment results and formulating an adjustment plan; implementing wetland restoration and establishing a monitoring system; and acquiring the restoration effect in real time through the monitoring system and optimizing the plant community structure adjustment plan. This method, combining adaptive assessment and monitoring feedback, can continuously improve the ecological function of wetlands, is widely applicable to the restoration and ecological recovery of natural wetlands, and has high application value.

[0041] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0042] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0043] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0044] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for restoring natural wetlands based on the adaptive regulation of plant communities, characterized in that, Includes the following steps: Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological conditions data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. The physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results. Based on the adaptive assessment results, the ecological function index of the current plant community structure is determined, and the current plant community structure is adjusted according to the ecological function index to construct a plant community structure adjustment scheme. Based on the plant community structure adjustment scheme, wetland restoration was carried out on the target natural wetland, and a wetland restoration monitoring system was constructed. The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the plant community structure adjustment optimization scheme.

2. The method for natural wetland restoration based on plant community adaptive regulation according to claim 1, characterized in that, The process involves acquiring baseline data of the target natural wetland to be restored. This baseline data includes geographical environmental data, current plant community structure data, and hydrological condition data of the target natural wetland. A physical model of the target natural wetland is then constructed based on this baseline data. Specifically: Geographic environmental data of the target natural wetland to be restored is obtained based on a geographic information system, including topographic and geomorphological data of the target natural wetland. The plant community structure sampling area of ​​the target natural wetland is selected based on stratified sampling method, plant multispectral data of the plant community structure sampling area are obtained, plant species of the target natural wetland are determined based on the plant multispectral data, and the distribution range of each plant species is determined. A preset number of survey plots are set in the distribution range of each plant species. Obtain plant information for each survey quadrat, including plant species, quantity, height, and coverage. Determine the plant community structure of the target natural wetland based on the plant information and distribution range of each survey quadrat, and obtain the current plant community structure data of the target natural wetland. Hydrological monitoring points are constructed at predetermined locations in the target natural wetland. Based on the hydrological monitoring points, water quality data, water level information, and water flow velocity and direction information of each hydrological monitoring point in the target natural wetland are obtained to obtain hydrological condition data. Obtain pollution data of the target natural wetland, including the location, degree, and type of pollution of the land and water bodies; The geographical environment data, current plant community structure data, hydrological condition data, and pollution status data of the target natural wetland are used as the baseline data of the target natural wetland. A three-dimensional terrain model of the target natural wetland is constructed based on the geographical environment data. The current plant community structure data, hydrological condition data, and pollution data are mapped into the three-dimensional terrain model to construct a physical model of the target natural wetland.

3. The method for restoring natural wetlands based on plant community adaptive regulation according to claim 1, characterized in that, An environmental change simulation was performed on the physical model, and an adaptive assessment of the current plant community structure of the target natural wetland was conducted based on the environmental change simulation. The adaptive assessment results are as follows: A list of plant species is constructed based on the current plant community structure data of the target natural wetland. The suitable environmental conditions and environmental regulation capacity data of each plant species in the list are obtained from the Internet. A plant growth model is constructed based on the L-System algorithm. Historical climate change data and historical hydrological change data of the target natural wetland over a preset time period are obtained. A climate change simulation model and a hydrological change simulation model of the target natural wetland are constructed. The climate change simulation model and the hydrological change simulation model are fitted to the historical climate change data and the historical hydrological change data. The climate change simulation model and the hydrological change simulation model are integrated with the physical model to construct an environmental change simulation model of the target natural wetland. An environmental condition change prediction model is constructed based on the LSTM algorithm. The historical climate change data and historical hydrological change data are divided into a training set and a prediction set according to a preset ratio. The training set is imported into the environmental condition change prediction model for training. The prediction set is imported into the environmental condition change prediction model after training to predict environmental condition changes within a preset time period in the future, thereby obtaining climate change prediction data and hydrological change prediction data. The plant growth model is integrated with the environmental change simulation model. The climate change prediction data and hydrological change prediction data are imported into the environmental change simulation model to simulate environmental conditions. Based on the plant growth model and the suitable environmental conditions and environmental regulation capacity data of plant species, the plant growth of the target natural wetland is simulated, and the plant growth in the future within a preset time period is predicted to obtain the plant growth prediction results. Based on the plant growth prediction results, determine the plant community evolution trend of the target natural wetland within a future preset time period, and evaluate the wetland ecological improvement index and pollution reduction index of the target natural wetland within the future preset time period based on the plant community evolution trend. The current plant community structure of the target natural wetland is assessed for its adaptability based on the wetland ecological enhancement index and pollution reduction index, resulting in an adaptability evaluation.

4. The natural wetland restoration method based on plant community adaptive regulation according to claim 3, characterized in that, The process involves importing the climate change prediction data and hydrological change prediction data into the environmental change simulation model for environmental condition simulation. Specifically, the plant growth of the target natural wetland is simulated based on the plant growth model, suitable environmental conditions data for plant species, and environmental regulation capacity data. Calculate the annual average temperature and annual precipitation of the target natural wetland for the next year based on the climate change prediction data and hydrological change prediction data. If the annual average temperature value is greater than the preset temperature threshold, the simulated value of the plant growth model for the plant photosynthetic efficiency is reduced, and the reduction coefficient of the simulated value is determined based on the suitable environmental conditions data of each plant species. Acquire the relationship data between phenological period and temperature for each plant species in the target natural wetland. Based on the relationship data and climate change prediction data, predict the time range of advance or lag of the phenological period for each plant species. If the number of days of advance of the phenological period is greater than the preset phenological advance threshold, adjust the reproductive body germination time parameter in the plant community structure data of the plant growth model. If the number of days of lag of the phenological period is greater than the preset phenological lag threshold, correct the flowering duration parameter in the plant community structure data. If the annual precipitation value is greater than the preset precipitation threshold, the duration of water accumulation at different locations in the target natural wetland is predicted based on the climate change prediction data and hydrological change prediction data. Based on the plant waterlogging tolerance data, if the plant's waterlogging tolerance duration is less than the predicted water accumulation duration, the plant is marked as a plant affected by waterlogging in the plant community structure data, and its competitiveness parameter in the community is reduced. If the plant's waterlogging tolerance duration is greater than the predicted water accumulation duration and greater than the preset waterlogging tolerance advantage threshold, its reproduction and diffusion parameter in the community is increased. The parameters of the plant growth model were optimized based on the reduction coefficient, propagation time parameter, flowering duration parameter, competitiveness parameter, and propagation and diffusion parameter.

5. The method for natural wetland restoration based on plant community adaptive regulation according to claim 1, characterized in that, The process involves determining the ecological function index of the current plant community structure based on the adaptive assessment results, adjusting the current plant community structure according to the ecological function index, and constructing a plant community structure adjustment scheme. Specifically: Obtain restoration target data for the target natural wetland, including restoration degree of plant area coverage, restoration degree of plant population richness, pollution restoration degree, and restoration duration target; obtain the influence weight information of each restoration target on the ecological function index. Based on the adaptive assessment results, determine the restoration capacity of the current plant community structure of the target natural wetland for each restoration target, divide the target natural wetland into N sub-regions, and calculate the ecological function index of the current plant community structure of each sub-region based on the restoration capacity and the influence weight information. Based on the restoration target data, the ecological function index threshold is determined, and sub-regions with ecological function indices less than the ecological function index threshold are marked to obtain the areas where the plant community structure needs to be optimized. Based on the climate condition data of the target natural wetland, obtain the suitable plants of the target natural wetland, obtain the ecological function data of each suitable plant, and construct a suitable plant database by combining the suitable plants and ecological function data. Based on the ecological function index, the type of ecological defect in the area to be optimized is determined. Based on the type of ecological defect, plant species are matched in the suitable plant database to identify plant types with complementary ecological functions to the type of ecological defect and label them as community structure optimization plants. The number and density of plants for optimizing community structure in each sub-region are determined based on the ecological defect type and the ecological function index. Based on the optimized plant quantity and density according to the community structure, the current plant community structure of each sub-region is adjusted to obtain a plant community structure adjustment scheme.

6. The method for restoring natural wetlands based on plant community adaptive regulation according to claim 1, characterized in that, The process of restoring the target natural wetland according to the plant community structure adjustment scheme and constructing a wetland restoration monitoring system specifically includes: The plant community structure adjustment scheme is used to restore the target natural wetland, and wetland restoration monitoring data of each sub-region in the target natural wetland is obtained under various environmental characteristics. Calculate the Euclidean distance between wetland restoration monitoring data in each sub-region, determine the similarity between wetland restoration monitoring data in each sub-region based on the Euclidean distance, and construct a similarity matrix; Based on the similarity matrix, sub-regions with similarity greater than a preset value are merged through data monitoring to obtain merged sub-regions; One of the merged sub-regions is randomly selected as the representative monitoring area. Wetland restoration monitoring sensors are deployed in the representative monitoring area, and a wetland restoration monitoring system is constructed based on the deployed wetland restoration monitoring sensors.

7. The method for natural wetland restoration based on plant community adaptive regulation according to claim 1, characterized in that, The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the optimized plant community structure adjustment scheme, which is as follows: The wetland restoration monitoring system acquires periodic wetland restoration monitoring data of the target natural wetland according to a preset time period, and determines the restoration degree requirement within each preset time period based on the restoration target data of the target natural wetland. The periodic wetland restoration monitoring data are compared with the restoration level requirements to evaluate the restoration effect of the target natural wetland within a preset time period; If the repair effect of a preset number of time periods does not meet the repair requirements, the interaction relationship between each plant species in each sub-region is obtained. If there is a competitive relationship between plant species, the dominant plant species is retained, and the plant species that compete with the dominant plant species are replaced to obtain the plant community structure adjustment and optimization scheme.

8. A natural wetland restoration system based on plant community adaptive regulation, characterized in that, The natural wetland restoration system based on plant community adaptive regulation includes a storage device and a processor. The storage device includes a program for a natural wetland restoration method based on plant community adaptive regulation. When the processor executes the program for the natural wetland restoration method based on plant community adaptive regulation, it performs the following steps: Obtain baseline data of the target natural wetland to be restored. The baseline data includes geographical environment data, current plant community structure data, hydrological conditions data, and pollution status data of the target natural wetland. Construct a physical model of the target natural wetland based on the baseline data. The physical model is subjected to environmental change simulation, and the current plant community structure of the target natural wetland is assessed for adaptability based on the environmental change simulation to obtain the adaptability assessment results. Based on the adaptive assessment results, the ecological function index of the current plant community structure is determined, and the current plant community structure is adjusted according to the ecological function index to construct a plant community structure adjustment scheme. Based on the plant community structure adjustment scheme, wetland restoration was carried out on the target natural wetland, and a wetland restoration monitoring system was constructed. The restoration effect of the target natural wetland is obtained in real time by the wetland restoration monitoring system. Based on the restoration effect, the plant community structure adjustment scheme is optimized to obtain the plant community structure adjustment optimization scheme.

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