Table of contents
Practical technical application of R language in the field of ecological environment
Application of Meta-analysis in the field of ecological environment
Application of MATLAB in Ecological Environment Data Processing and Analysis
Practical technical application of R language in the field of ecological environment
As an emerging statistical software, R language is popular all over the world with its characteristics of open source, freedom and free. The research content in the field of ecological environment is extensive, and the data are often diverse and complex. It is the advantage of R to use R language to conduct multivariate statistical analysis, discover laws and explore mechanisms from complex phenomena. To this end, this tutorial takes diverse ecological environment data such as fish, insects, hydrology, and terrain as examples. Based on the introduction of basic operations in R language, multiple programs such as vegan, ade4, adespatial, stats, cluster, and dendextend are used. Package analysis of data distribution, correlation, regression, clustering, sorting, spatial structure and community diversity, etc., interpretation of the results and ecological significance, and integration of data analysis and graphing display, guide readers to be able to use systematically R language conducts multi-faceted analysis and exploration in the field of ecological environment.
Topic 1 Basic operation and grammar of R language
1. Acquisition and installation
of R 2. Data types of R
3. Functions of R
4. Loading and use of R packages
Topic 2 Exploratory Data Analysis
Case 1: Abundance analysis of different species
Case 2: Spatial distribution of different species in the quadrat
Case 3: Environmental data maps such as hydrology and topography
Environment variable bubble chart
Topic Three Correlation Analysis
1. Correlation analysis between different variables
2. Differences and distance matrix between different species
3. Graphical correlation matrix
Pearson correlation diagram of different environmental factors
Topic four regression analysis
1. Use lm() to fit the regression model
2. Univariate and multiple linear regression
3. Polynomial regression
4. Regression diagnosis
5. Select the best regression model
Regression diagnostic plot of biomass to each factor
Topic 5 Cluster Analysis
Case: Different types of clustering and comparison between sample plots
(single connection, full connection, average aggregation clustering (UPGMA), Ward minimum variance clustering, etc.)
Two Clustering Trees and Their Comparison
Topic 6 Ranking analysis
1. Principal component analysis (PCA)
2. Correspondence analysis (CA)
3. Principal coordinate analysis (PCoA)
4. Non-metric multidimensional scaling analysis (NMDS)
Topic 7 Data Spatial Analysis
1. Overview of Spatial Structure and Spatial Analysis
2. Multivariate Trend Surface Analysis
3. Spatial Variables and Spatial Modeling Based on Characteristic Roots
4. Multi-scale Ordering (MSO)
Topic 8 Biodiversity analysis
1. Sparsity analysis of biological communities
2. Alpha, beta and gamma diversity of biological communities
3. Community functional diversity, functional composition and pedigree diversity
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Application of Meta-analysis in the field of ecological environment
In terms of theory, the selection and calculation of Meta-analysis effect size, heterogeneity test, data structure, fixed effect and random effect model, data information acquisition and bias analysis, data filling and other knowledge are systematically sorted out. In terms of practice, combined with specific cases, the functions of MetaWin software are introduced one by one, and how to export and interpret the results is fully explained. Master the basic ideas and basic steps of Meta analysis of related issues in the field of ecological environment, and have the ability to solve practical problems through step-by-step explanations and computer operations.
[Expert]: Hu Enzhu (associate professor), the lecturer is from universities and research institutes in key countries. He has applied meta-analysis methods for many years and published more than 20 SCI/EI papers. Presided over 5 vertical scientific research projects including the National Natural Science Foundation of China.
Introduction to Meta Analysis
1. Introduction to Meta Analysis
2. Current Situation and Development Trend
3. Basic Idea
4. Common Software
Meta analysis case - step ①
1. Meta analysis topic selection
2. Literature collection and preliminary screening
3. Database establishment
4. Data integration
Basic theory of Meta analysis
1. Effect value selection, calculation and conversion
2. Combined effect value calculation and heterogeneity test
3. Unstructured data, grouped data, continuous data
4. Random effect model
Meta analysis case - step ②
1. Selection and calculation of effect value
2. Calculation of combined effect value
3. Parametric model and non-parametric model
4. Group analysis and Meta regression (univariate, bivariate)
5. Cumulative/decreasing Meta Analysis
6. Model comparison (Model Building)
7. Interpretation of results
Literature bias and sampling test
1, graphic analysis method
2, rank correlation test method
3, unsafe number
4, correction of biased results - "Trim and Fill"
Graphic drawing
1, forest map
2, funnel map
3, weighted histogram and Gaussian fitting
4, normal quantile map
Application of MATLAB in Ecological Environment Data Processing and Analysis
Systematically learn MATLAB programming visualization and drawing-and data processing applications in the ecological environment, master various data processing and analysis and present explanations in the form of practical cases, and become familiar with data processing and analysis methods faster, and further improve the ability of scientific researchers A higher understanding and practical application of artificial intelligence and its MATLAB implementation methods.
[Expert]: Mr. Zhu (associate professor), has long been engaged in ecosystem management, global change ecology, ecological model and remote sensing, climate change, ecological environment data processing and analysis. Published many SCI/EI papers. Presided over a number of various vertical scientific research projects such as the National Natural Science Foundation of China.
Topic 1 Key points for getting started with MATLAB programming
: learning introduction, case demonstration, software interface, basic grammar, basic operations, etc.
Topic 2
Key points for getting started with MATLAB programming: script writing, function calling, loop control, code debugging, file reading and writing, etc.
Topic three MATLAB visualization and drawing
points: interactive drawing, programming drawing, time series data, 3D data, animation production, etc.
Topic 4 Time series data processing and case analysis
Key points: time scale, smooth interpolation, statistical analysis, parameter fitting, etc.
Case: Time series long-term observation data analysis of field stations, etc.
Topic 5.
Key points of image and video data processing and case analysis: file type, feature extraction, image classification, image matching, video processing, etc.
Case: Field vegetation phenology camera observation data analysis, etc.
Topic 6 Map vector data processing and case analysis
Key points: Geospatial data, map projection and transformation, map visualization, etc.
Case: Vegetation patch dynamic observation data analysis, etc.
Topic 7 Remote sensing image data processing and case analysis
Key points: non-imaging spectrum, UAV aerial photography, satellite remote sensing image, etc.
Case: Vegetation hyperspectral data processing, UAV/satellite image processing, etc.
Topic 8 3D point cloud data processing and case analysis
Key points: point cloud file reading and writing, visual analysis, point cloud data processing, etc.
Case: UAV lidar point cloud data processing and analysis, etc.
Topic 9 Eco-environment numerical model and case analysis
Key points: Eco-environmental system process model, differential equation construction and solution, etc.
Case: Ecosystem model construction and numerical simulation, etc.
Topic 10 Review and Q&A Discussion
Key Points: Knowledge Points Sorting, Summary and Q&A