A method for constructing a health assessment and early warning platform for alpine grassland ecosystems

Abstract

The present invention discloses a method for constructing a health assessment and early warning platform for an alpine grassland ecosystem, including: health assessment of an alpine grassland fragile ecosystem; construction of future scenarios of an alpine grassland fragile ecosystem and simulation of major ecological elements; and construction of an alpine grassland fragile alpine grassland ecosystem health assessment and early warning platform. The present invention implements ecosystem health assessment and early warning, thereby providing scientific and reasonable decision-making support to formulate targeted and precise intervention measures, making the overall plan and countermeasures for comprehensive ecological environment governance more scientific, regionalized and specific.

Description

Technical Field

[0001] The present invention relates to ecosystem technology, and in particular to a method for constructing a health assessment and early warning platform for a typical fragile alpine grassland ecosystem. Background Art

[0002] Different regions have their own unique ecological characteristics and major ecological and environmental problems. How to scientifically screen out early warning indicators of typical fragile ecosystems in a region and more accurately determine their thresholds is the main problem currently facing regional ecosystem security early warning.

[0003] At present, a lot of research has been done at home and abroad on the basic principles and methods of ecological security early warning, the concept and evaluation methods of ecosystem health, the application of ecosystem risk assessment and early warning characteristics, etc., and there is a trend of multidisciplinary intersection, adding ecosystem service modeling, ecological compensation system, ecological red line and other contents. However, the internal structure and process of different ecosystems themselves are quite different, resulting in huge differences in their assessment models and assessment systems, and there are generally problems of difficulty in promotion and replication. In addition, there are still some differences in the selection and quantification of indicators and the assignment of weights in ecosystem assessment, and there are problems such as strong subjectivity and complicated indicator systems, which make it difficult to realize the research results from theory to application.

[0004] Gannan alpine grassland is one of the most typical fragile ecosystems in Gansu. It is also an important water supply area for the Yellow River and the source of an important tributary of the Yangtze River. The vast natural grassland is a huge natural barrier to protect the ecological security of the Yellow River and Yangtze River basins. There are 27,300 km2 of natural grassland in the territory, accounting for about 70% of its total land area. In recent years, Gannan has implemented many key projects and policy measures for grassland ecological protection and construction, such as natural grassland grazing and grass restoration projects, grassland rodent control projects, desertified grassland (black soil beach) comprehensive management projects, and grassland subsidy policies, so as to curb the deterioration trend of the ecological environment of Gannan alpine grassland to a certain extent. However, the ecological "chronic disease" of Gannan alpine grassland degradation has not been completely cured. Therefore, it is urgent to carry out research and development and demonstration research on the health assessment and early warning technology of the fragile ecosystem of Gannan alpine grassland, make predictions on the reverse succession and degradation of the ecosystem, issue risk warnings in advance, and build an ecosystem health assessment and early warning platform to provide scientific and technological support for the protection and management of typical fragile ecosystems in Gansu and the formulation of targeted intervention measures.

[0005] In the past, a lot of research has been conducted on the methods of building a health assessment and early warning platform for alpine grassland ecosystems. However, due to the wide research field and rich content involved in ecosystem health research, the factors affecting the maintenance and development of ecosystems and their interrelationships are also relatively complex. At the same time, the internal structures and processes of different ecosystems themselves vary greatly. Most of the existing research on ecosystem health focuses on the analysis of the current situation, and the research on its changing trends and early warning is relatively weak. Ecosystem health assessment and risk early warning are still in the experimental and exploratory stage, and a set of mature methods have not yet been formed. By systematically combing the existing ecosystem health assessment methods and early warning technologies, and comprehensively analyzing the main technical methods, intellectual property rights and technical standards involved in the current ecosystem health assessment and risk early warning, it is found that these technologies and standards still have some problems in the application of fragile ecosystems in Gansu: there are huge differences in the assessment models and assessment systems of different ecosystems. Although there have been many achievements in the relevant patent authorization and standard formulation, there are generally problems that are difficult to promote and replicate; from the perspective of the achievements themselves, the assessment of ecosystem health is highly subjective and difficult to track and predict continuously; there are still some differences in the selection and quantification of indicators and the assignment of weights. Against the backdrop of the dual impacts of climate change and human activities, Gannan’s alpine grasslands and fragile ecosystems should fully draw on the advantages of relevant technologies and intellectual property rights, improve the technical system for evaluating the health of various ecosystems, develop distributed risk warning models and comprehensive prediction and early warning systems, and actively conduct health level assessments and early warnings of typical fragile ecosystems in Gansu. This is a practical technical need that needs to be urgently addressed in the process of optimizing and enhancing the intelligent management and sustainable development of regional ecosystems.

[0006] The livestock overload rate in Gannan alpine grassland is close to 20%, and the imbalance between grass and livestock is still prominent. There are even degradation problems with desertification, black soil, soil erosion, shrinking wetland resources, and reduced biodiversity as the main signs. Therefore, in view of the sensitivity and instability of the fragile ecosystem of Gannan alpine grassland, as well as the new ecological and environmental problems currently and in the future, it is urgent to carry out research on the health assessment and prediction and early warning system of fragile ecosystems, understand the system and trade-off relationship between ecosystem service functions, develop typical fragile ecosystem evolution process reproduction, current status evaluation, change prediction and ecological early warning simulator, make predictions on the reverse succession and degradation of ecosystems, issue risk alerts in advance, and predict the spatial and temporal range and degree of harm of abnormal health conditions, so as to achieve ecosystem health assessment and early warning, thereby providing scientific and reasonable decision-making support to formulate targeted and precise intervention measures, so as to make the overall plan and countermeasures of comprehensive ecological and environmental governance more scientific, regionalized and specific. Summary of the invention

[0007] The main purpose of the present invention is to provide a method for constructing a health assessment and early warning platform for a typical fragile alpine grassland ecosystem, to conduct health assessment and early warning research and judgment on the fragile ecosystem of my country's alpine grassland, to form an ecosystem change prediction and early warning system, to develop a network-based early warning platform, to realize the dynamic evolution of key elements of fragile ecosystems and visualization of multi-dimensional early warning information, and to automatically identify and issue warnings for long-, medium- and short-term ecosystem disasters and risks, in order to provide a theoretical basis for the restoration and management of typical fragile ecosystems in my country's mountains, and to promote the construction of ecological civilization and sustainable development in my country's alpine mountains.

[0008] The technical solution adopted by the present invention is: a method for constructing a health assessment and early warning platform for an alpine grassland ecosystem, comprising:

[0009] Assessment of the health of alpine grassland fragile ecosystems;

[0010] Construction of future scenarios for alpine grassland fragile ecosystems and simulation of main ecological elements;

[0011] Construction of health assessment and early warning platform for alpine grassland fragile alpine grassland ecosystem.

[0012] Furthermore, the alpine grassland fragile ecosystem health assessment includes:

[0013] Based on the data of topography, climate, soil, vegetation, land use and socio-economics of Gannan alpine grassland, as well as field plot survey, location monitoring and other information, ArcGIS and ENVI were used to study the expert classifier criteria of alpine grassland and compare and analyze the spatiotemporal distribution and evolution characteristics of ecosystems.

[0014] Based on the principles of scientificity, representativeness, operability and systematicity, key risk factors were selected from the four aspects of ecosystem structure, function, environment and service as indicators for ecosystem health risk diagnosis. The comprehensive index method and efficacy coefficient method were used to construct the Gannan alpine grassland ecosystem health diagnosis model and health risk discrimination model, and the spatial distribution status and dynamic changes of health risks of typical vulnerable ecosystems in Gansu in recent years were systematically analyzed.

[0015] Based on the natural environment, socio-economic and ecological conditions of the Gannan alpine grassland ecosystem, multivariate data was used to select human impact risk sources such as soil erosion, grassland degradation, rodent damage, soil erosion, overgrazing and grazing carrying capacity, and a probabilistic loss degree model was used to evaluate the impact of different risk sources on the ecosystem, reveal the main risk sources of ecosystem health risks, determine the importance of each risk source and its threshold, quantify the impact of human activities and climate change on ecosystem health, and clarify the key driving factors of ecosystem health risks.

[0016] Furthermore, the construction of the future scenario of the alpine grassland fragile ecosystem and the simulation of the main ecological elements include:

[0017] Construction of future climate and human activity scenarios in typical fragile ecological areas: Based on socio-economic development and greenhouse gas emission scenarios, the nested global climate model-high-resolution regional climate model is driven to construct high-resolution future climate scenarios in typical fragile ecological areas;

[0018] Using the global weather forecast model as the background field, the WRF model is used to dynamically downscale and integrate real-time meteorological data to generate high-resolution medium-term and short-term meteorological scenarios for the protected area. The climate and meteorological prediction methods at three scales are integrated to form a technology for constructing long-term, medium-term and short-term climate and meteorological scenarios for ecologically fragile areas.

[0019] Based on the current status of human activities and ecosystems in typical fragile ecological zones, big data analysis technology is used to determine the corresponding development type and intensity level of human activities, and to construct a quantitative model of the constraints of natural conditions on the development of human activities and the impact of human activities on the basic elements of the earth's surface, forming a scenario of climate change and human activities in fragile ecological zones;

[0020] Research on the evolution mechanism of typical fragile ecosystems: Carry out ground and remote sensing monitoring of alpine grassland ecosystems, and form a basic data set for mechanism exploration, scale effect analysis, and ecosystem early warning model construction through field observation surveys, remote sensing data analysis, historical document compilation, comparative analysis research, data mining, and data assimilation. On this basis, based on the surface conditions and human activity scenarios, use the constructed long-term climate scenario simulation to analyze the development trend of the ecosystem and its main controlling factors, and identify potential threats to the ecosystem status and services;

[0021] Use medium-term meteorological scenarios to simulate the occurrence and development of the main controlling factors of the ecosystem and real-time system monitoring to estimate the deterioration of the ecological environment and disaster risks at the seasonal scale; use real-time system monitoring and short-term meteorological forecasts to predict sudden disasters such as land degradation, soil erosion, and grassland fires induced by extreme weather; and achieve spatiotemporal simulation and prediction of key elements of typical fragile ecosystems in the long, medium and short term based on process models;

[0022] Using the spatial state evaluation method, on the basis of historical background and current situation analysis, an ecological carrying capacity evaluation index system based on ecosystem health was constructed. The weight of each index was determined using the hierarchical analysis method. The regional ecological resilience, resource carrying index and social influence were evaluated in a graded manner. The regional ecological carrying capacity index was quantified, its spatial characteristics were clarified, and the regional water-carbon trade-off relationship under the influence of resource utilization and protection strategies of Gannan alpine grassland was explained.

[0023] Aiming at developing eco-hydrological process-ecosystem service coupling dynamics model for ecosystems, combined with the constructed long-, medium- and short-term climate and meteorological and human activity scenarios, a spatiotemporal dynamic simulation and prediction technology of ecosystem water-soil-air-biological elements based on physical process coupling was established to clarify the evolution trend and main controlling factors of ecosystem service functions;

[0024] Typical fragile ecosystem change early warning model and algorithm: Use the entropy method to select the most representative and sensitive factors of the ecological environment and ecosystem services in fragile areas; focus on ecosystem health risks and disasters, based on historical disaster information and basic ecological and environmental data, use machine learning to clarify the relationship between disaster index and natural environment and human interference factors, and identify major disaster-causing factors; develop a multi-dimensional, multi-time span early warning system and early warning model for ecosystem quality, ecosystem services, ecological disasters, etc. in fragile areas based on ecosystem monitoring and physical process simulation, integrate ecosystem sensitive factors and major disaster-causing factors to form early warning indicators, determine the type and weight of each indicator, and establish a risk early warning indicator system;

[0025] Based on the ecological function positioning, environmental quality standards and disaster risk levels, determine the thresholds of early warning indicators, set corresponding warning lines and establish early warning models; on the basis of system monitoring, model simulation and integrated analysis, establish early warning levels according to early warning indicators and warning lines, and determine the degree of ecosystem disaster risk; comprehensively consider early warning indicators, indicator warning lines, early warning models and warning levels, and build an early warning system for typical fragile ecosystem changes based on the conceptual model framework of ecological vulnerability assessment.

[0026] Furthermore, the construction of the alpine grassland vulnerable alpine grassland ecosystem health assessment and early warning platform includes:

[0027] Based on the potential risk identification and health assessment indicator system of alpine grassland ecosystem, a typical ecological problem assessment model for the study area is established. According to relevant national standards and regional ecological function positioning, early warning indicators, early warning values ​​and warning lines are set for typical ecological problems, and an object-based distributed early warning model is constructed.

[0028] In the future scenario, based on the mid- and long-term forecast results of prominent ecological problems in fragile ecosystems, the warning model is used to determine the warning situation and identify the time, location and frequency of different warning situations of various ecological problems;

[0029] The overall framework of the system follows the J2EE architecture and network service development model, and the structure adopts the browser / server development architecture model;

[0030] The system will consist of five layers: user layer, application service layer, business support layer, data resource layer and basic platform layer. Its main functions are the comprehensive management of monitoring data, comprehensive services of early warning information, and prediction and early warning of future scenarios.

[0031] The system design is guided by the prediction and early warning of potential risks to the health of fragile ecosystems in the Gannan alpine grassland. It comprehensively uses WebGIS, spatial database management, spatial data visualization, problem-oriented programming framework, future scenario prediction and simulation technology, system integration and other technologies to build a web-based early warning platform with the characteristics of versatility, versatility, scalability and practicality; it integrates long-term and short-term climate scenarios and human activity scenario databases, basic ecological environment databases, and key ecological problem monitoring, health assessment indicators and distributed early warning model construction technologies in fragile ecosystems to build a web-based early warning platform for the fragile ecosystem of the Gannan alpine grassland.

[0032] Advantages of the present invention:

[0033] In view of the sensitivity and instability of the fragile ecosystem of the alpine grassland, as well as the new ecological and environmental problems currently and in the future, the present invention urgently needs to carry out research on the fragile ecosystem health assessment and prediction and early warning system, recognize the system and trade-off relationship between ecosystem service functions, and develop a typical fragile ecosystem evolution process reproduction, current status evaluation, change prediction and ecological early warning simulator to predict the reverse succession and degradation of the ecosystem, issue risk alerts in advance, and predict the temporal and spatial scope and degree of harm of abnormal health conditions, realize ecosystem health assessment and early warning, thereby providing scientific and reasonable decision-making support to formulate targeted and precise intervention measures, making the overall plan and countermeasures for comprehensive ecological and environmental governance more scientific, regionalized and specific.

[0034] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0036] Figure 1 It is a framework diagram of the method for constructing a health assessment and early warning platform for an alpine grassland ecosystem of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] refer to Figure 1 , a specific experimental plan for the construction of a typical fragile alpine grassland ecosystem health assessment and early warning platform:

[0039] 1. Health assessment of the vulnerable ecosystem of the Gannan alpine grassland

[0040] First, based on the topography, climate, soil, vegetation, land use and socio-economic data of Gannan alpine grassland, as well as field plot surveys, positioning monitoring and other information, ArcGIS and ENVI and other software were used to study the expert classifier criteria (related indicators and thresholds, etc.) of the alpine grassland, and to compare and analyze the spatiotemporal distribution and evolution characteristics of the ecosystem. Secondly, based on the principles of scientificity, representativeness, operability and systematicity, key risk factors were selected from the four aspects of ecosystem structure, function, environment and service as indicators for ecosystem health risk diagnosis. The comprehensive index method and efficacy coefficient method were used to construct the Gannan alpine grassland ecosystem health diagnosis model and health risk discrimination model, and the spatial distribution status and dynamic changes of health risks of typical vulnerable ecosystems in Gansu in recent years were systematically analyzed. Finally, based on the natural environment, socio-economic and ecological conditions of the Gannan alpine grassland ecosystem, multivariate data was used to select human impact risk sources such as soil erosion, grassland degradation (black soil beach), rodent damage, soil erosion, overgrazing and grazing carrying capacity, and a probabilistic loss degree model was used to evaluate the impact of different risk sources on the ecosystem, revealing the main risk sources of ecosystem health risks, determining the importance of each risk source and its threshold; quantifying the impact of human activities and climate change on ecosystem health, and clarifying the key driving factors of ecosystem health risks.

[0041] Based on the identification of the spatiotemporal variation characteristics and potential risks of the fragile ecosystem of the Gannan alpine grassland, according to the characteristics of the ecological functions and vulnerability of the Gannan grassland, and in accordance with the principle of mutual complementation and improvement among the indicators, a set of comprehensive health evaluation indicators including resistance, resilience / resilience, vitality, organization, productivity, biodiversity, integrity, buffering capacity, carbon sink capacity, water conservation capacity, and biological supply capacity were initially selected. Based on the currently commonly used biological model of vitality-organization-resilience (VOR) ecosystem health assessment, the ecological service function was introduced as a system component to reflect the impact of changes in ecosystem processes on its ecological functions, and the model construction and debugging were completed, providing a method for comprehensively reflecting and quantifying the health status of the Gannan alpine grassland ecosystem. In order to fully consider the impact of human activities (especially agricultural and animal husbandry development) and rodent damage on the health and stability of the Gannan alpine grassland ecosystem, the pressure-state-response (PSR) model of the Gannan grassland area was constructed and debugged, which comprehensively considered the impact of climate change, human activities and environmental stress on the evolution of the health status of the Gannan grassland ecosystem, in order to explore the current health status and maintenance mechanism of the Gannan grassland ecosystem.

[0042] 2. Construction of future scenarios for the fragile ecosystem of the Gannan alpine grassland and simulation of main ecological elements

[0043] Construction of future climate and human activity scenarios in typical fragile ecological zones: Based on socio-economic development and greenhouse gas emission scenarios, the nested global climate model (GCM)-high-resolution regional climate model (RCM) is driven to construct high-resolution future climate scenarios in typical fragile ecological zones; with the global weather forecast model (GFS) as the background field, the WRF model is used to dynamically downscale and integrate real-time meteorological data to generate high-resolution medium-term (month to year) and short-term (day to week) meteorological scenarios for protected areas; the climate and meteorological prediction methods at three scales are integrated to form a technology for constructing long-, medium- and short-term climate and meteorological scenarios in fragile ecological zones. Based on the current status of human activities and ecosystems in typical fragile ecological zones, big data analysis technology is used to determine the corresponding development type and intensity level of human activities, and a quantitative model of the constraints of natural conditions (climate and topography) on the development of human activities and the impact of human activities on basic surface elements (land use structure and hydrological connectivity, etc.) is constructed to form climate change and human activity scenarios in fragile ecological zones.

[0044] Research on the evolution mechanism of typical fragile ecosystems: Ground and remote sensing monitoring of Gannan alpine grassland ecosystems is carried out. Through field observation surveys, remote sensing data analysis, historical document compilation, comparative analysis, data mining and data assimilation, a basic data set is formed for mechanism exploration, scale effect analysis, and ecosystem early warning model construction. On this basis, according to the surface conditions and human activity scenarios, the development trend of ecosystems and their main controlling factors is analyzed by constructing long-term (more than 10 years) climate scenarios to identify the potential threats to ecosystem status and services; the occurrence and development of the main controlling factors of ecosystems are simulated by medium-term meteorological scenarios and real-time system monitoring to estimate seasonal ecological environment deterioration and disaster risks; real-time system monitoring and short-term meteorological forecasts are used to predict sudden disasters such as land degradation, soil erosion, and grassland fires induced by extreme weather (heavy precipitation, strong winds, drought, etc.); the spatiotemporal simulation and prediction of key elements of typical fragile ecosystems in the long, medium and short term based on process models are realized, and research on the evolution mechanism of ecosystems is carried out.

[0045] Using the spatial state evaluation method, on the basis of historical background and current situation analysis, an ecological carrying capacity evaluation index system based on ecosystem health is constructed. The weight of each index is determined by using the hierarchical analysis method, and the regional ecological resilience, resource carrying index and social influence are evaluated in a graded manner. The regional ecological carrying capacity index is quantified, its spatial characteristics are clarified, and the regional water-carbon trade-off relationship under the influence of resource utilization and protection strategies (grazing, grazing ban, etc.) of Gannan alpine grassland is explained. On the basis of clarifying the mechanism of ecosystem evolution, the eco-hydrological process-ecosystem service coupling dynamic model is further developed for the ecosystem. Combined with the constructed long-, medium- and short-term climate and meteorological and human activity scenarios, the spatiotemporal dynamic simulation and prediction technology of ecosystem water-soil-air-biological elements based on physical process coupling is established to clarify the evolution trend and main controlling factors of ecosystem service functions.

[0046] Early warning models and algorithms for changes in typical fragile ecosystems: Use the entropy method to select the most representative and sensitive factors of the ecological environment and ecosystem services in fragile areas; focus on ecosystem health risks and disasters, based on historical disaster information and basic ecological and environmental data, use machine learning to clarify the relationship between disaster index and natural environment and human interference factors, and identify major disaster-causing factors; develop a multi-dimensional, multi-time span early warning system and early warning model for ecosystem quality, ecosystem services, ecological disasters, etc. in fragile areas based on ecosystem monitoring and physical process simulation, integrate ecosystem sensitive factors and major disaster-causing factors to form early warning indicators, determine the type (positive or negative evolution) and weight of each indicator, and establish a risk early warning indicator system. According to the ecological function positioning, environmental quality standards and disaster risk levels, the thresholds of early warning indicators are determined, corresponding warning lines are set, and early warning models (such as vulnerability index, disaster risk, deterioration trend and deterioration speed, etc.) are established; on the basis of system monitoring, model simulation and integrated analysis, according to early warning indicators and warning lines, early warning levels (blue, yellow, orange and red) are established to determine the degree of disaster risk in the ecosystem; based on the "sensitivity-resilience-pressure" ecological vulnerability assessment conceptual model framework, the early warning indicators, indicator warning lines, early warning models and early warning levels are integrated to build a typical fragile ecosystem change early warning system. From the aspects of system integration, database construction and GIS technology integration, object-based distributed early warning models and algorithms are developed.

[0047] 3. Construction of a health assessment and early warning platform for the vulnerable alpine grassland ecosystem in Gannan

[0048] Based on the identification of potential risks and the determination of the health assessment indicator system for the Gannan alpine grassland ecosystem, an assessment model for typical ecological problems (such as grassland desertification, soil erosion, water conservation, etc.) in the study area was established. According to relevant national standards and regional ecological function positioning, early warning indicators, early warning values ​​and warning lines were set for typical ecological problems, and an object-based distributed early warning model was constructed. In the future scenario, based on the medium- and long-term prediction results of prominent ecological problems in fragile ecosystems, the warning model was used to determine the warning situation, identify the time, location and frequency of different warning situations of various ecological problems, and realize the medium- and long-term prediction and early warning of Gannan grassland ecological problems.

[0049] The overall framework of the system follows the J2EE architecture and network service development model, and the structure adopts the browser / server (B / S) development architecture model. The system will consist of five layers: user layer, application service layer, business support layer, data resource layer and basic platform layer. Its main functions are the comprehensive management of monitoring data, comprehensive services of early warning information and prediction and early warning of future scenarios. The system design is guided by the prediction and early warning of potential risks to the health of the fragile ecosystem of the Gannan alpine grassland. It comprehensively uses WebGIS, spatial database management, spatial data visualization, problem-oriented programming framework, future scenario prediction and simulation technology, system integration and other technologies to build a network-based early warning platform with the characteristics of versatility, multi-functionality, scalability and practicality. Integrating long-term and short-term climate scenarios and human activity scenario databases, basic ecological environment databases, and key ecological problem monitoring, health assessment indicators and distributed early warning model construction technologies in fragile ecosystems in fragile ecosystems in fragile ecosystems, a network-based early warning platform for fragile ecosystems in fragile ecosystems in Gannan is built to realize the long-term and short-term prediction and analysis of meteorological data of Gannan alpine grassland, long-term prediction of spatiotemporal evolution of ecological environment, result analysis, graphic display and warning situation identification.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for constructing a health assessment and early warning platform for an alpine grassland ecosystem, characterized in that: include: Assessment of the health of alpine grassland fragile ecosystems; Construction of future scenarios for alpine grassland fragile ecosystems and simulation of main ecological elements; Construction of a health assessment and early warning platform for the vulnerable alpine grassland ecosystem; The alpine grassland vulnerable ecosystem health assessment includes: Based on the data of topography, climate, soil, vegetation, land use and socio-economics of Gannan alpine grassland, as well as field plot survey and location monitoring, ArcGIS and ENVI were used to study the expert classifier criteria of alpine grassland and compare and analyze the spatiotemporal distribution and evolution characteristics of ecosystems. Based on the principles of scientificity, representativeness, operability and systematicity, key risk factors were selected from the four aspects of ecosystem structure, function, environment and service as indicators for ecosystem health risk diagnosis. The comprehensive index method and efficacy coefficient method were used to construct the Gannan alpine grassland ecosystem health diagnosis model and health risk discrimination model, and the spatial distribution status and dynamic changes of health risks of typical vulnerable ecosystems in Gansu in recent years were systematically analyzed. In view of the natural environment, socio-economic and ecological conditions of the Gannan alpine grassland ecosystem, we used multivariate data to select risk sources of human impact, such as soil erosion, grassland degradation, rodent damage, soil erosion, overgrazing and grazing carrying capacity. We used a probabilistic loss model to evaluate the impact of different risk sources on the ecosystem, reveal the main risk sources of ecosystem health risks, determine the importance of each risk source and its threshold; quantify the impact of human activities and climate change on ecosystem health, and clarify the key driving factors of ecosystem health risks; The construction of the future scenario of the alpine grassland fragile ecosystem and the simulation of the main ecological elements include: Construction of future climate and human activity scenarios in typical fragile ecological areas: Based on socio-economic development and greenhouse gas emission scenarios, the nested global climate model-high-resolution regional climate model is driven to construct high-resolution future climate scenarios in typical fragile ecological areas; Using the global weather forecast model as the background field, the WRF model is used to dynamically downscale and integrate real-time meteorological data to generate high-resolution medium-term and short-term meteorological scenarios for the protected area. The climate and meteorological prediction methods at three scales are integrated to form a technology for constructing long-term, medium-term and short-term climate and meteorological scenarios for ecologically fragile areas. Based on the current status of human activities and ecosystems in typical fragile ecological zones, big data analysis technology is used to determine the corresponding development type and intensity level of human activities, and to construct a quantitative model of the constraints of natural conditions on the development of human activities and the impact of human activities on the basic elements of the earth's surface, forming a scenario of climate change and human activities in fragile ecological zones; Research on the evolution mechanism of typical fragile ecosystems: Carry out ground and remote sensing monitoring of alpine grassland ecosystems, and form a basic data set for mechanism exploration, scale effect analysis, and ecosystem early warning model construction through field observation surveys, remote sensing data analysis, historical document compilation, comparative analysis research, data mining, and data assimilation. On this basis, based on the surface conditions and human activity scenarios, use the constructed long-term climate scenario simulation to analyze the development trend of the ecosystem and its main controlling factors, and identify potential threats to the ecosystem status and services; Use medium-term meteorological scenarios to simulate the occurrence and development of the main controlling factors of the ecosystem and real-time system monitoring to estimate the deterioration of the ecological environment and disaster risks at the seasonal scale; use real-time system monitoring and short-term meteorological forecasts to predict sudden disasters such as land degradation, soil erosion, and grassland fires induced by extreme weather; and achieve spatiotemporal simulation and prediction of key elements of typical fragile ecosystems in the long, medium and short term based on process models; Using the spatial state evaluation method, on the basis of historical background and current situation analysis, an ecological carrying capacity evaluation index system based on ecosystem health was constructed. The weight of each index was determined using the hierarchical analysis method. The regional ecological resilience, resource carrying index and social influence were evaluated in a graded manner. The regional ecological carrying capacity index was quantified, its spatial characteristics were clarified, and the regional water-carbon trade-off relationship under the influence of resource utilization and protection strategies of Gannan alpine grassland was explained. Aiming at developing eco-hydrological process-ecosystem service coupling dynamics model for ecosystems, combined with the constructed long-, medium- and short-term climate and meteorological and human activity scenarios, a spatiotemporal dynamic simulation and prediction technology of ecosystem water-soil-air-biological elements based on physical process coupling was established to clarify the evolution trend and main controlling factors of ecosystem service functions; Early warning model and algorithm for changes in typical fragile ecosystems: Use the entropy method to select the most representative and sensitive factors of the ecological environment and ecosystem services in fragile areas; focus on ecosystem health risks and disasters, based on historical disaster information and basic ecological and environmental data, use machine learning to clarify the relationship between disaster index and natural environment and human interference factors, and identify major disaster-causing factors; develop a multi-dimensional, multi-time span early warning system and early warning model for ecosystem quality, ecosystem services, and ecological disasters in fragile areas based on ecosystem monitoring and physical process simulation, integrate ecosystem sensitive factors and major disaster-causing factors to form early warning indicators, determine the type and weight of each indicator, and establish a risk early warning indicator system; According to the ecological function positioning, environmental quality standards and disaster risk levels, determine the threshold of early warning indicators, set corresponding warning lines and establish early warning models; on the basis of system monitoring, model simulation and integrated analysis, establish early warning levels according to early warning indicators and warning lines to determine the degree of ecosystem disaster risk; comprehensively consider early warning indicators, indicator warning lines, early warning models and early warning levels, and build an early warning system for typical fragile ecosystem changes based on the conceptual model framework of ecological vulnerability assessment; The construction of the alpine grassland vulnerable alpine grassland ecosystem health assessment and early warning platform includes: Based on the potential risk identification and health assessment indicator system of alpine grassland ecosystem, a typical ecological problem assessment model for the study area is established. According to relevant national standards and regional ecological function positioning, early warning indicators, early warning values ​​and warning lines are set for typical ecological problems, and an object-based distributed early warning model is constructed. In the future scenario, based on the mid- and long-term forecast results of prominent ecological problems in fragile ecosystems, the warning model is used to determine the warning situation and identify the time, location and frequency of different warning situations of various ecological problems; The overall framework of the system follows the J2EE architecture and network service development model, and the structure adopts the browser / server development architecture model; The system will consist of five layers: user layer, application service layer, business support layer, data resource layer and basic platform layer. Its main functions are the comprehensive management of monitoring data, comprehensive services of early warning information, and prediction and early warning of future scenarios. The system design is guided by the prediction and early warning of potential risks to the health of fragile ecosystems in the Gannan alpine grassland. It comprehensively uses WebGIS, spatial database management, spatial data visualization, problem-oriented programming framework, future scenario prediction and simulation technology, and system integration technology to build a web-based early warning platform with the characteristics of versatility, versatility, scalability and practicality; it integrates long-term and short-term climate scenarios and human activity scenario databases, basic ecological environment databases, and key ecological problem monitoring, health assessment indicators and distributed early warning model construction technology in fragile ecosystems to build a web-based early warning platform for the Gannan alpine grassland fragile ecosystem.

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