Ecosystem services are the direct or indirect benefits that humans obtain from nature. They can be divided into four categories: supply services, cultural services, regulation services, and support services. They are of great significance to the improvement of human well-being and are regarded as connecting society and ecosystems bridge. Since the launch of the Millennium Ecosystem Assessment (MA), ecosystem services have become a research hotspot in academia, and great progress has been made in how ecosystem service functions are transformed into economic value. However, under the dual drive of global warming and accelerated land use change, the ecological environment continues to deteriorate in exchange for short-term economic benefits. Therefore, as an ecosystem degrades, so does its ability to provide goods and services. In addition, in the process of landscape space planning, it is necessary to pay attention to the coordination and trade-off relationship between ecosystem services, and give priority to ecosystem services with economic value, in order to achieve both ecological benefits and socioeconomic benefits. Given the lack of economic value of some ecosystem services, such as aesthetic, cultural, and therapeutic values, managers and ecologists consider them of low importance and are often not considered in planning decisions. At the same time, due to the intangibility of the social value of ecosystem service functions and the dependence on the subjective perception of beneficiaries, it is difficult to evaluate or quantify them, which makes it difficult to incorporate the social value of ecosystem service functions into planning and resource management.
The equivalent factor method is to classify the ecosystem service functions, construct the value equivalent of various service functions of different types of ecosystems with quantifiable standards, and evaluate the distribution area of the ecosystem. This method has less data, is more intuitive and easy to use, and is applicable to Assessment of the value of ecosystem services at regional and global scales. The InVEST model based on the GIS platform is based on spatial data, quantifies various ecosystem service functions and expresses them in the form of maps, realizes the spatialization and dynamics of the quantitative evaluation of ecosystem service functions, and is highly scalable. A number of applied researches have been carried out abroad, and it is the most mature and most widely used ecosystem service value evaluation model. The SolVES model (Social Values for Ecosystem Services) is called the Ecosystem Service Social Value Model. It is a geographic information system application program jointly developed by the US Geological Survey and Colorado State University. The purpose of developing this model is mainly for ecosystem services. The social value in the service function is spatially analyzed and quantitatively evaluated. The evaluation result does not show the total value in the form of currency, but uses the value index to express the level of social value. The model consists of three sub-modules, which are the social value module of ecosystem service function, the value mapping module and the value conversion mapping module. The value transfer module can transfer data to another research area that lacks survey data based on the existing research results, and generate a predicted value index map of the new research area. This module can be used independently and conveniently.
Describe the equivalent factor method, InVEST model, SolVES model and their principles used to evaluate the value of ecosystem services. Through the study of this course, you will learn the principles and operation methods of the three models:
How to obtain and prepare model data; how to perform equivalent factor conversion;
How to use the InVEST model to evaluate ecosystem service functions and value;
How to import the collected social survey data into the database (SQL), combined with the sum of the amount of money assigned to each social value type by the respondents (that is, the weight index),
How to use the built-in kernel density analysis tool to perform weighted kernel density analysis on the marked social value points to get the "kernel density surface" and "maximum grid value";
How to use the "average nearest neighbor statistics" tool embedded in the SolVES model to count the clustering spatial distribution of social value points;
How to use the model to divide the "Kernel Density Surface" by the "Maximum Raster Value" and normalize the result to a "Value Index Surface";
How to combine environmental variable data to start the MaxEnt maximum entropy model to predict the spatial distribution of social value points and realize the mapping of social value
How to conduct spatial analysis and statistical analysis on model results; how to conduct coupling analysis on model results.
You will also learn the basic methods of QGIS\PostgreSQL\ARCGIS\MAXENT \InVEST model\SolVES model \R language, and use the advantages of various platforms to expand and analyze the social value of ecosystem services : such as obtaining the corresponding social value distribution map based on different environmental variables , and analyze the distribution characteristics of social value in space ; study the collinearity of environmental variables; study the impact of environmental variables on the spatial distribution of social value , and deeply analyze the relationship between each environmental variable and different types of social value ; Study the contribution of each environmental variable to social value , so as to further determine which environmental factors contribute more to social value , etc. It will also summarize the current research results, research hotspots, advantages and disadvantages of the model based on relevant application cases, and look forward to its future development trend, so as to provide reference for the better application of the ecosystem service value estimation model to the social value evaluation of ecosystem service functions .
Theoretical basis and analysis of research hotspots
Introduction to Ecosystem Services and Ecosystem Service Value
Ecosystem service value research method
Research Hotspots of Ecosystem Service Value
Visual Analysis of Citespace Literature
VOSviewer document visual analysis
Spatial data source and preprocessing
Introduction to Spatial Data
ArcGIS Pro data collection and analysis
Data loading and database construction
Space coordinate system establishment and selection
Spatial data collection and storage
map symbol design
Map layout design and research area map making
Environmental element data acquisition and preprocessing
Introduction to data types and acquisition methods
Introduction to Remote Sensing Cloud Computing Platform
PIE ENGINE Grammar Introduction
Training based on PIE ENGINE data acquisition
Data processing training based on PIE ENGINE
Estimation and Analysis of Ecological Service Value Based on Value Equivalent Factor Method
Estimation of Ecological Service Value Based on Value Equivalent Factor Method
Spatial data source and processing
Ecosystem Type Classification
Ecosystem service function type
Estimation method of ecosystem service function value
Spatial Statistical Analysis Based on ARCGIS
Spatio-temporal variation analysis of ecosystem service value
The impact of land use on the value of ecosystem services
Characteristic analysis of land use transfer
Ecosystem carbon storage function and value assessment based on InVEST model
Ecosystem service function evaluation model based on InVEST carbon module
Introduction to InVEST Models
InVEST Carbon Module Introduction
Model parameter interpretation and data preparation
- Model running and result analysis
- InVEST Blue Carbon Ecosystem Service Value Estimation
Evaluating the social value of ecosystem services based on the SolVES model
SolVES 4.0 Model Environment Configuration
SolVES 4.0 model function introduction
QGIS 3.8.2 installation configuration
PostgreSQL 11.7 installation configuration
PostGIS 2.5.3 installation configuration
Maxent 3.4.1 installation configuration
Install the SolVES 4.0 plugin
load sample data
Note: SolVES 4.0 was developed and tested on systems running Microsoft Windows 10 Enterprise Edition with 64-bit processors. The software listed above is required to run Solution 4.0. Additionally, the Java Runtime must be available on the system running Solution 4.0 in order to access and run Maxent 3.4.1.
SolVES 4.0 model run
New Project
data analysis tools
Principles of Survey Data Analysis
Survey data analysis parameter selection and setting
1. Transfer Value Tool
l Transfer value calculation principle
l Transfer Value Tool Parameter Selection
Analysis of model running results
Users generate composite reports that map social value and related environmental indicators based on the results of current projects or previously completed projects.
The map layout contains selected value index maps, including study area boundaries and selected backgrounds. The map title includes project name, survey group, and social value type.
Continuous data is displayed in the form of a line graph. Categorical data are displayed as scatterplots. The x-axis labels of the scatterplot have integer values for the specified categories.
AUC values, mean nearest neighbor statistics, and maximum index scores are included in the map layout for all results generated by the Analyze Survey Data tool.
1. SolVES model performance test
l Maxent model principle
l Maxent model parameters and operation
MaxEnt result analysis:
Based on the AUC data generated by the MaxEnt model, the performance of the model operation is tested for reliability and fitness, and the area under the Maxent curve and the variable contribution are interpreted and adjusted.
Transfer Value Results Analysis:
When the study area has a similar biophysical and social context to the main study area, but survey data are not available, a value transfer mapping model can be used, accessed through the transfer value tool, relying on Maxent's Solve the statistical models generated in the analysis.
SolVES 4.0 model data preparation and storage
Tabular Data Types and Formatting and Loading
The "id" field and the "geom" field (in the case of vector data) are managed by PostgreSQL and should not be included when preparing user-supplied data for loading into the solver database.
2. Spatial data loading
1. Acquisition of social survey data
l Understand the characteristics and satisfaction of the interviewees
l Ask respondents to assign social value and mark corresponding social value points.
l Collect social background and demographic data of respondents
The source and processing of spatial data
Geospatial data includes Shapefiles and raster datasets of the study area:
l The STUDY_AREA Shapefile needs to study the boundary elements of the area;
l SURVEY_POINTS data is based on questionnaire digitization;
l The raster dataset is the extraction of environmental elements in the research area;
l For SURVERY_POINTS data and STUDY_AREA data, use the kernel density analysis tool of ArcGIS to operate on the two data, and output the overall spatial distribution map of social value.
- SolVES model processing data
Perform average nearest neighbor analysis on the SURVERY_POINTS data to obtain the average nearest neighbor ratio (R-ratio) and standard deviation (Z-score), highlighting the importance of each value in the region;
- Using the SolVES model to statistically integrate the hypothetical scores assigned to each social value by the respondents collected from the questionnaire, a spatially explicit map with a 10-point value index (VI) is generated to determine each social value The importance of type.
- Group the respondents, import the corresponding socio-demographic characteristics data and spatial data into the model, use the value index output by normalized calculation as the weight, and output the spatial distribution map of each social value in the entire research area, and these A graph of the relationships that exist between value distributions and environmental variables.
Correlation Analysis of Environmental Variables and Social Value
Multicollinearity test of environmental variables
- R environment configuration and basic syntax
- correlation analysis
- variance inflation factor analysis
Statistical Analysis
Statistical Analysis of Landscape Types Using ArcGIS Zonal Statistical Tool
Spatial Distribution of Major Social Value Types
Analysis of the Influence of Environmental Variables on Social Value
Conduct a correlation analysis on the selected landscape types under the social value points marked by the interviewees, get the public's favorite landscape type, and analyze the influencing factors of the landscape type and social value;
5. Analysis of the contribution rate of environmental variables
The contribution of each environmental variable can be obtained according to the contribution rate of the environmental variables obtained from the operation of MaxEnt
6. Spatial autocorrelation analysis
The relationship between the distance variable and VI was judged according to Moran's I, p value and z score.
7. Analysis of the effectiveness of social value transfer of ecosystem services
SCI Thesis Writing and Expanding Case Analysis
Analysis of paper writing skills and submission strategies
Biodiversity value assessment of national parks from the perspective of social-ecological coupling analysis
- Case training:
- Habitat quality assessment based on InVEST model
Evaluating Trade-Off and Synergies of Ecosystem Services Values of a Representative Resources-Based Urban Ecosystem
