13 results about "Ecological process" patented technology

The present application relates to the technical field of ecological environment, in particular to a water ecological system evaluation system and method based on a water habitat coupling mechanism model. The technical problem is to integrate key ecological mechanisms while maintaining high computational efficiency. The system includes: an input layer that receives measured data related to the water environment of the target water habitat; a configuration layer that selects several indicators from the geographic indicators, hydrological indicators, hydrodynamic indicators and meteorological indicators input by the input layer, and configures multiple different environmental factors; key ecological processes are integrated through selective mechanism coupling, and interspecific competition factors are configured for algae and biological interaction factors are configured for fish; the simulation layer uses a differential evolution algorithm to automatically calibrate and optimize the parameters configured by the configuration layer; obtain the spatial and temporal changes of aquatic plants, algae and fish; the output layer outputs the spatial distribution results of the three species of aquatic plants, algae and fish, and provides suggestions for scenario analysis results and environmental economic balance decision-making.

The application provides a kind of microbial population evolution monitoring method and device based on magnetic field intensity regulation, related to microbial monitoring field, through multi-source sensor real-time collection microbial community, methane production, magnetic field parameter and environmental working condition data, construct supervision data set, establish dynamics model containing magnetic field influence function, and adopt supervision learning to carry out parameter online identification and rolling prediction, finally through optimization algorithm real-time adjustment magnetic field parameter, realize the closed-loop optimization control of microbial permeability process.The application adopts the above-mentioned microbial population evolution monitoring method and device based on magnetic field intensity regulation, has the advantages of strong real-time, high interpretability, good engineering implementability, etc., is suitable for coal seam microbial permeability, coalbed gas production optimization and mine ecological process evaluation and other application scenarios.

The application discloses a natural ecosystem authenticity determination method and device, relates to the technical field of ecological evaluation, and comprises the following steps: acquiring land use data of a research area, and calculating an ecological structure authenticity index; identifying a natural reference area based on ecological environment zoning and the ecological structure authenticity index; acquiring ecosystem service data, and calculating an ecological process authenticity index and an ecological function authenticity index based on the natural reference area; acquiring species distribution data, and calculating a biological and indicator species authenticity index; acquiring human activity data, and calculating a human disturbance intensity index; and finally, normalizing and weightedly fusing the indexes to obtain a natural ecosystem authenticity comprehensive index. The application solves the problems of single dimension, neglect of regional natural benchmark differences and lack of a multi-factor comprehensive framework of the existing evaluation method, and significantly improves the scientific nature of natural reserve management.

The application provides a bionic colon micro-ecological monitoring and adjusting system and method based on an electronic nose, relates to the field of in-vitro intestinal fermentation simulation and micro-ecological process control, and comprises the following steps: a bionic colon culture module provides an anaerobic continuous flow fermentation environment for intestinal flora and generates headspace gas reflecting the metabolic state of the flora; a gas sensing module outputs a multi-dimensional response signal after pre-treating the headspace gas; a processing module performs compensation processing and feature extraction on the multi-dimensional response signal, compares the feature representation with a steady-state odor fingerprint reference model, obtains the deviation degree and drift direction of the current micro-ecological state, and generates a differential regulation instruction; and a regulation execution module adjusts the substrate supply amount, liquid dilution rate and pH of the bionic colon culture module respectively according to the differential regulation instruction. The application realizes long-term online monitoring and self-adaptive adjustment of the micro-ecological state in the continuous flow bionic colon culture process.

This invention discloses a comprehensive monitoring method and system for the ecological health of garden wetlands based on hyperspectral imaging, belonging to the field of ecological environment remote sensing monitoring technology. It acquires hyperspectral image data and corresponding climate data of the target garden wetland at multiple temporal phases, extracts ecological characterization features of vegetation, water bodies, and soil, and accumulates and converts the climate data into a climate-driven sequence. Based on the climate-driven sequence, it determines the boundary points of ecological response stages, constructs an ecological process scale, and maps multi-temporal observation data from calendar time to the ecological process scale. Then, it performs non-uniform rearrangement and collaborative correction on the initial ecological process sequence to obtain a stable ecological response feature sequence. Based on this, it extracts change trajectories, identifies abnormal change segments, and generates ecological health status evaluation results and early warning information. This invention can reduce misjudgments caused by phenological shifts.

The application discloses a kind of plant evaluation methods for water area surrounding green land: S1, the dust-retention capacity parameter of candidate plant and the rain nutrient enrichment parameter of penetration are acquired;S2, plants are divided into two categories of high / low dust-retention capacity, while calculating nutrient flux enrichment multiple, and divided into two categories of high / low leaching risk according to threshold value;S3, construct two-dimensional evaluation matrix, and plants are divided into corresponding risk quadrant.The method includes two ecological processes of dust-retention and leaching into a unified quantitative framework, for the first time reveals the function coordination and trade-off relationship between air purification and water environment protection, without relying on fixed threshold value, through clustering analysis and environmental benchmark linkage to realize the dynamic division of risk quadrant, provides reproducible, migratory scientific evaluation tool for water area surrounding green land plant screening.

The invention discloses a phytoplankton community stability evaluation method based on cascade reservoir influence. The method comprises the following steps: step 1, river reach division and sample collection; step 2, community structure and diversity analysis; step 3, analyzing a community construction mechanism; step 4, co-occurrence network construction and stability evaluation; step 5, environment driving factor modeling; and step 6, performing multi-group comparative analysis. According to the method, multi-dimensional analysis of a community structure, a construction mechanism, network stability and environment driving factors is integrated, and a complete evaluation chain is formed; a neutral community model and a co-occurrence network analysis method are introduced, and the influence mechanism of the cascade reservoir is revealed from the angles of the ecological process and interaction; the method is suitable for river and reservoir systems of different scales and different types, and is especially suitable for ecological assessment of areas without data or with less data; the method has important theoretical and practical values for scientifically guiding ecological scheduling and biodiversity protection of the drainage basin.

This invention provides a method and system for reconstructing three-dimensional chlorophyll a concentration in the ocean based on deep learning. The method first acquires multi-source input data from the target sea area, including bio-optical parameters, vertical physical profile data, and geographic coordinates. Then, the multi-source data is preprocessed and feature fused to form a unified-dimensional input feature vector. This vector is then input into a trained deep neural network model, whose hidden layers include a spatial attention mechanism module and a residual correction structure module, to output predicted chlorophyll a concentration values ​​at multiple discrete depth layers. Finally, a three-dimensional chlorophyll a concentration field is reconstructed based on these predicted values. This invention integrates multi-source heterogeneous data and, by introducing an attention mechanism and residual structure, significantly improves the accuracy and spatiotemporal characterization capability of three-dimensional reconstruction of complex nonlinear marine ecological processes, providing reliable technical support for marine primary productivity estimation, carbon flux research, and ecosystem dynamic monitoring.

The application discloses a kind of salinization wetland vegetation recovery method based on gradient moisture control, first, according to moisture gradient, degraded wetland is divided into three levels of moisture zone, namely low moisture zone, medium moisture zone and high moisture zone, and according to moisture zoning, vegetation recovery scheme is formulated, based on the quantitative relationship between soil moisture content and vegetation aboveground biomass, water supplement measures are formulated, and soil is improved through salt-nutrient synergistic control.The application innovatively integrates hydrological engineering and ecological process control, breaks through the differentiated water supply mode, realizes the synergistic effect of increasing soil and salt inhibition, provides a replicable recovery paradigm for semi-arid region wetlands, and provides a quantifiable natural solution for coping with land desertification and climate change.

The application discloses a method for predicting the carbon sink promotion effect of natural forest tending, and belongs to the technical field of forest carbon sink prediction. The application is used for solving the problem of scientifically evaluating the future carbon sink of natural forest tending. The application comprises the following steps: setting a target sampling sample plot, conducting field basic information investigation, establishing forest carbon pools including arbor biomass carbon pool, litter carbon pool, dead wood carbon pool and soil organic carbon pool, calculating the initial carbon storage of the forest carbon pool as the basic data of the natural forest, based on the growth law of the forest and the carbon cycle mechanism of the ecological system, simulating the dynamic change of the carbon storage of the forest stand by using an ecological process model, predicting the carbon storage change of the four forest carbon pools of the natural forest after tending, and based on the obtained carbon storage change of the four forest carbon pools of the natural forest after tending, estimating the carbon sink generated in the forest growth process of the natural forest after tending and the forest land quality index. The application realizes the synergistic promotion of the ecological function and the carbon sink function of the forest.

The present application provides a kind of prairie human settlement environment ecological space identification method and system, it is related to computer vision and ecological space analysis technical field, obtains the continuous video stream of prairie containing different function partition and time span, dynamic scene analysis is carried out to the video stream unit therein, the interactive action and state change of scene element are identified, and video stream scene interaction sequence is generated;Based on the interaction information in the video stream scene interaction sequence, associate ecological core element and derivative element, and construct ecological element dynamic correlation model;Video stream scene interaction sequence is input into the ecological element dynamic correlation model operation, and the trajectory of the change of ecological space form is output, generates preliminary identification result, and the model parameters are updated from this, obtain calibrated model and again operation generates final identification result.The present application solves the problem that traditional static method cannot capture the dynamic interaction of ecological process, realizes the dynamic, accurate and adaptive identification of prairie ecological space.

This invention belongs to the field of intelligent decision-making technology for ecological environment, specifically disclosing a reinforcement learning-based system for simulating ecological environment evolution and evaluating planning schemes. This invention constructs a closed-loop technical architecture integrating mechanism-driven simulation, data-driven perception, and intelligent decision optimization. This architecture models planning schemes as intelligent agents capable of interacting with the environment and continuously learning, enabling the system to perform sequential decision optimization and dynamic performance evaluation of complex adaptive management strategies while maintaining the physical consistency of ecological processes and environmental quality evolution. The system tightly couples ecological dynamics models, environmental pollution diffusion models, and reinforcement learning intelligent agents, driving strategy optimization through a multi-objective reward function that includes both ecosystem service enhancement and environmental quality improvement, achieving dynamic intervention and adaptive evaluation within a unified spatiotemporal grid. This application supports interpretable and robust decision-making for complex ecological environment planning schemes.