CN-116894204-B - Forestation optimization method based on degradation risk avoidance and ecosystem service promotion

CN116894204BCN 116894204 BCN116894204 BCN 116894204BCN-116894204-B

Abstract

The invention discloses a forestation optimization method based on degradation risk avoidance and ecosystem service promotion, which comprises a forest degradation risk region type and distribution identification process, a potential forestation region identification process based on forest degradation risk avoidance, a typical ecosystem service evaluation process, a forestation pattern and a tree species optimization process. The method has the beneficial effects that the technical scheme is based on the thought of forest degradation risk avoidance and ecological system service promotion, potential forestation areas are identified on the basis of analyzing forest degradation risk, and forestation patterns and forestation tree species optimization are developed by taking various ecological system service promotion as target subareas, so that a forestation optimization technical system is finally formed, guidance is provided for forestation planning management in northern China areas, forestation degradation risk can be avoided to a certain extent, and regional ecological system service promotion with multiple integration of carbon fixation and water lifting is realized on the basis of water and soil conservation and wind prevention and sand fixation service promotion.

Inventors

TENG YANMIN
SU MEIRONG
ZHAN JINYAN
YANG YING
YU CHUNXUE

Assignees

东莞理工学院

Dates

Publication Date: 20260508
Application Date: 20230714

Claims (5)

1. The afforestation optimization method based on degradation risk avoidance and ecosystem service promotion is characterized by comprising a forest degradation risk region type and distribution identification process, a potential afforestation region identification process based on forest degradation risk avoidance, a typical ecosystem service evaluation process, an afforestation pattern and tree species optimization process; In the forest degradation risk area type and distribution identification process, identifying the forest degradation risk area type, the forest degradation risk level and the forest degradation risk distribution from three aspects of forest leaf area index change, climate fluctuation sensitivity and soil moisture change; In the identification process of the potential forestation area based on forest degradation risk avoidance, geoSOS-FLUS software is adopted to conduct forestation risk area identification and forestation suitability assessment, a potential forestation area identification decision frame is constructed, the potential forestation area comprises a forestation area and a forestation area, the forestation area which is not suitable is removed, and the type and the distribution of the potential forestation area are finally determined; In the typical ecosystem service evaluation process, a water source conservation service is evaluated by adopting a InVEST model water production module, a water and soil conservation service is evaluated by adopting a general soil loss equation (RUSLE), a wind prevention and sand fixation service is evaluated by adopting a modified wind erosion equation (RWEQ), a carbon fixation service is evaluated by adopting a Carnegie-Ames-Stanford Approach (CASA) model by taking a net primary productivity as an agent index; in the afforestation pattern and tree species optimization process, evaluating the wind erosion and water erosion amount of soil for years based on RUSLE model and RWEQ model, calculating the average value of the wind erosion and water erosion amount for years, and dividing the area into a water and soil loss leading area, a wind and sand erosion leading area, a common leading area and other areas; in the optimization process of the forestation patterns and tree species, on the basis of water and soil conservation and wind and sand fixation service promotion, the aims of maximizing carbon fixation and minimizing water consumption are achieved, optimization functions are respectively constructed in different types of forestation areas, and different weights and multiple ecological system service promotion scene schemes are set; in the afforestation pattern and tree species optimization process, a plane optimization module in GeoSOS software is adopted to identify afforestation priority areas, 10%, 20% and 30% of the areas of potential afforestation areas are selected in different types of areas to serve as areas to be optimized, and then the first 10% -30% key areas for preferentially developing afforestation are identified, and afforestation pattern optimization is firstly developed from the whole potential afforestation areas, and then is respectively developed from suitable afforestation areas and suitable irrigation areas; In the optimization process of the forestation patterns and tree species, main forestation tree species in each ecological risk type leading area are identified, the main forestation tree species are evaluated from the aspects of degradation risk, ecological system service supply capacity and economic benefit, different weights are set for 3 dimensions according to regional characteristics, and the optimal forestation tree species combination in each region is screened to construct a hybrid forest.
2. The forestation optimization method based on degradation risk avoidance and ecosystem service promotion according to claim 1, wherein in the leaf area index change analysis, a unitary linear regression trend analysis method is adopted to identify a time-space evolution trend of a forest leaf area index after forestation, trend analysis and significance inspection of the leaf area index are completed through MATLAB software, and residual analysis is adopted to identify a forest degradation risk area caused by a driving type and natural factors of forest degradation.
3. The forestation optimization method based on degradation risk avoidance and ecosystem service promotion of claim 1, wherein in the climate fluctuation sensitivity analysis, the spatial distribution of the highly sensitive area is identified based on a multiple linear relationship between the average value fluctuation of the forest normalized vegetation index (NDVI) of the forestation area of the last 5 years and the average value fluctuation of the climate factors including the air temperature and drought index, and the sensitivity of the forest to the climate fluctuation is evaluated.
4. The forestation optimization method based on degradation risk avoidance and ecosystem service promotion according to claim 1, wherein in the soil moisture variation analysis, evolution characteristics of soil moisture content after forestation are identified by adopting unitary linear regression trend analysis based on soil moisture data, trend analysis and saliency detection of the soil moisture are completed based on MATLAB software, and further a region with the remarkably reduced soil moisture content caused by forestation is spatially identified based on residual analysis.
5. The forestation optimization method based on degradation risk avoidance and ecosystem service promotion according to claim 1, wherein in the forestation risk area identification, typical forest degradation caused by climate factors and forest and bush distribution data of potential degradation risk areas are extracted, and different types of forestation risk area distribution is identified by adopting GeoSOS-FLUS software in combination with regional climate, topography, soil and hydrologic information, in the forestation suitability assessment, spatial distribution of undegraded forests and bushes is extracted, and forestation suitability assessment is carried out by adopting GeoSOS-FLUS software in combination with regional climate, topography, soil and hydrologic information, and suitable forestation area and suitable bush area spatial distribution is identified.

Description

Forestation optimization method based on degradation risk avoidance and ecosystem service promotion Technical Field The invention relates to the technical field of homeland space optimization methods, in particular to a forestation optimization method based on degradation risk avoidance and ecosystem service promotion. Background The large-scale forestation engineering is developed in the northern China, various ecological system services are effectively improved, but the unreasonable forestation areas and tree species selection lead to large-area forest degradation (as shown in figure 1) in the main forestation areas in the northern China, the forest degradation areas are mainly characterized by low forestation survival rate, slow growth and development, regional water resource overdrawing, soil carbon loss and the like, the ecological and economic benefits of forestation are severely limited, so that the suitability assessment of large-scale forestation is currently and widely focused, but the identification of the suitable areas of the forestation is often only considered for ecological suitability, the problem of forest degradation risk is not considered, and the method is particularly important for the main forestation areas in the northern China with higher forest degradation risk, on the other hand, the investment cost can be effectively reduced through the optimization identification of the multi-objective optimization forestation patterns, the various ecological system services are cooperatively improved, and the forestation patterns and the tree species are required to be reasonably optimized under the continuous forestation in the future, and the method is optimized to improve various ecological system services in the northern China, and the method has a certain practical reference value for future forestation work in the northern China. Disclosure of Invention The invention aims to solve the problems, and designs a forestation optimizing method based on degradation risk avoidance and ecosystem service promotion so as to reduce forestation degradation risk, realize regional ecosystem service promotion integrating carbon fixation and water lifting based on water and soil conservation and wind prevention and sand fixation service promotion, and provide guidance for forestation planning implementation in a main forestation area in northern China. The technical scheme of the invention for achieving the purpose is that the forestation optimization method based on degradation risk avoidance and ecosystem service promotion comprises a forest degradation risk region type and distribution identification process, a potential forestation region identification process based on forest degradation risk avoidance, a typical ecosystem service evaluation process, a forestation pattern and tree species optimization process. As a further description of the technical scheme, in the forest degradation risk zone type and distribution identification process, the forest degradation risk zone type, the forest degradation risk zone level and the forest degradation risk zone distribution are identified from three aspects of forest leaf area index change, climate fluctuation sensitivity and soil moisture change. As a further description of the technical scheme, in the forest degradation risk area type and distribution identification process, based on the forest Leaf Area Index (LAI) of the forestation area, a unitary linear regression trend analysis method is adopted to identify the trend of forest LAI along with time, and after data is preprocessed, the trend analysis and the significance test of the LAI are completed through MATLAB software, wherein the main calculation formula is as follows: in the formula, The method is characterized in that the method is forest LAI change rate, n is year number, and X i is an ith year LAI value; Is positive to indicate that the overall trend is rising, Negative indicates a generally decreasing trend; Further, residual analysis is adopted to identify the driving type of forest degradation and a forest degradation risk area caused by natural factors. And (3) performing multiple linear regression fitting on the forest LAI and the air temperature and the rainfall to obtain a predicted value of the forest LAI. The predicted value is the forest LAI value which should be applied to the area under the influence of the change of air temperature and precipitation. Subtracting the predicted value from the actual value of the forest LAI to obtain the influence of human factors on the variation of the forest LAI, wherein the calculation formula is as follows: ε=LAI True value -LAI Predictive value wherein epsilon is a residual error value, namely the influence of human activities on LAI. Human activity promotes LAI elevation when epsilon >0, and results in LAI depression when epsilon <0. As a further description of the technical scheme, in the forest degradation risk zone type and distribution iden