Mangrove forest suitable land evaluation method for mangrove forest ecological restoration

Abstract

The invention discloses a mangrove forest suitable land assessment method oriented to mangrove forest ecological restoration, relates to the field of mangrove forest ecological restoration methods, and provides a mangrove forest suitable land assessment method oriented to mangrove forest ecological restoration, which comprises monitoring plan making, detection content and method, monitoring process and operation specification, suitability model calculation method and the like. The method is suitable for mangrove forest ecological restoration monitoring, can accurately evaluate the suitability of the suitable land of the mangrove forest based on a habitat suitability model principle in combination with measurement of related parameters of nearby natural or artificial mud flats, effectively improves the success rate of ecological restoration afforestation of the mangrove forest, and provides a foundation for improving the coverage area of the mangrove forest of the coastal wetland. The nature-based carbon sequestration and sink increase amount is increased, and technical support is provided for promoting coast ecological safety and healthy sustainable development.

Description

Technical Field

[0001] The present invention relates to the field of mangrove ecological restoration methods, and in particular to a mangrove suitable forestland assessment method for mangrove ecological restoration. Background Art

[0003] Mangroves mainly inhabit tropical and subtropical coastline areas and have strict requirements for their growth habitats. In addition, the interweaving of sea and land dynamics and the complex and changeable geomorphic sedimentary environment make it difficult to carry out the assessment of suitable mangrove forest land. At present, various marine-related departments in my country are actively investing a lot of money to create mangroves to restore the ecological functions of coastal wetlands. The most important prerequisite for creating mangroves is to find suitable forest land for afforestation. The suitable forest land assessment method plays a key role in the monitoring and effect evaluation of mangrove ecological restoration. Through the assessment, the scientificity and effectiveness of mangrove ecological restoration can be ensured.

[0005] Due to the increasing scarcity of suitable mangrove tidal flats and the imperfect technical standards and specifications for mangrove ecological restoration in my country, most mangrove planting activities occur on the outer tidal flats of sheltered coastal projects. Due to the impact of human activities, habitat fragmentation, poor hydrodynamic exchange, and sewage discharge have caused these planned afforestation tidal flats to be not suitable for the growth of mangroves. The growth and distribution of mangroves are restricted by many factors such as topography, tidal level, seawater salinity, and climate. It is necessary to construct a multi-factor composite evaluation method to accurately identify and implement suitable tidal flat plots, achieve scientific mangrove creation, and steadily restore the area of ​​mangroves. At present, most evaluation methods are mainly based on a single factor to construct evaluation methods, and the constructed technical methods lack a reference system and are not credible enough, which brings great uncertainty to the evaluation results of suitable mangrove afforestation land. Summary of the invention

[0006] In response to the above-mentioned problems, the present invention selected a number of sedimentary environmental factor data and aboveground biomass of mangroves for key restoration in the reference system, effectively constructed an empirical relationship between different sedimentary environmental factor data and aboveground biomass of mangroves, and constructed a suitable forest land evaluation model based on the principle of habitat suitability model, which can greatly improve the success rate of mangrove afforestation and promote my country's coastal ecological security and sustainable and healthy development.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0008] A method for assessing suitable mangrove forest land for mangrove ecological restoration, characterized by comprising:

[0009] Step 1: Select the study area and divide it into the ground suitable forest land evaluation area and reference system;

[0010] Step 2: Conduct field surveys on the forestland suitable evaluation area and the reference system on the ground in step 1, and obtain field survey data on the forestland suitable evaluation area and the reference system on the ground;

[0011] Step 3: Obtain the multi-temporal satellite remote sensing images of the ground suitable forest land evaluation area and reference system in step 1, delineate the spatial suitable forest land evaluation area and reference system that match the field survey data in step 2 in the multi-temporal satellite remote sensing images, and perform vector marking respectively;

[0012] Step 4: Based on the field survey data in the reference system in step 2, a suitable forestland evaluation model is constructed;

[0013] Step 5: Input the field survey data of the suitable forest land evaluation area in step 2 into the suitable forest land evaluation model in step 4 for analysis to obtain the suitable forest land suitability evaluation results of the study area.

[0014] Furthermore, in step 1, the suitable forest land evaluation area is the light beach where artificial mangrove planting is planned to be carried out in the study area, and the reference system is the distribution area where natural mangroves exist or mangroves that have been successfully restored in the study area.

[0015] Furthermore, in step 2, the field survey data of the suitable forest land evaluation area and the reference system both include sedimentary environmental factor data, and the field survey data of the reference system also includes above-ground biomass of mangroves.

[0016] Furthermore, in step 2, the sedimentary environment factor data is obtained by the following method:

[0017] Step 2-1: In the suitable forest land assessment area or the cross section of the reference system where the mangrove community is distributed, sample plots are set up at low, medium and high tide levels, with one sample plot set up in each sample plot. Soil samples are collected in each sample plot with a depth of 10 cm. After the soil samples are taken out, they are frozen and stored;

[0018] Step 2-2: Measure the salinity, pH, elevation and average particle size of the soil sample in step 2-1 as sedimentary environment factor data.

[0019] Furthermore, in step 2-1, the specification of each sample plot is 10m×10m.

[0020] Furthermore, in step 4, the suitable forestland evaluation model is constructed by the following method:

[0021] Step 4-1: Normalize the aboveground biomass of mangroves in the reference system of step 2 to construct a suitability index. The calculation formula of the suitability index is as follows:

[0022]

[0023] Among them, SI is the suitability index, AGB is the aboveground biomass of mangroves, and AGB max is the maximum aboveground biomass of mangroves;

[0024] Step 4-2: Use a linear or nonlinear regression model to establish an empirical relationship model between the sedimentary environmental factor data of the reference system and the suitability index of step 4-1;

[0025] Step 4-3: Based on the empirical relationship model in step 4-2, construct the arithmetic mean method suitable forestland evaluation model and the geometric mean algorithm suitable forestland model based on the arithmetic mean method and the geometric mean algorithm respectively.

[0026] The beneficial effects of the present invention are as follows: compared with the prior art, the advantage of the present invention is that it reduces the workload of relying on artificial experience to assist afforestation, and selects a number of key mangrove restoration sedimentary environmental factor data and mangrove aboveground biomass in the reference system according to local conditions, and effectively constructs an empirical relationship between different sedimentary environmental factor data and mangrove aboveground biomass. Based on the principle of habitat suitability model, a suitable forest land evaluation model is constructed, which can greatly improve the success rate of mangrove afforestation and promote my country's coastal ecological security and sustainable and healthy development. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flowchart of the steps of a method for assessing suitable mangrove forest land for mangrove ecological restoration according to an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the planning of the afforestation project in the protected area according to a specific embodiment of the present invention;

[0029] Figure 3 It is a schematic diagram of a field investigation performed in a specific embodiment of the present invention;

[0030] Figure 4 It is a schematic diagram of the steps of performing remote sensing screening and classification and identification of land objects over the years according to a specific embodiment of the present invention;

[0031] Figure 5 It is a vector data distribution map of the reference system and the suitable forest land evaluation area range of the specific embodiment of the present invention;

[0032] Figure 6 1 is a schematic diagram of a curve of suitability fitting between environmental indicators and aboveground biomass of mangroves according to a specific embodiment of the present invention;

[0033] Figure 7 It is a schematic diagram of the assessment results of suitable forest land in the planning area of ​​the mangrove afforestation project in the study area of ​​the specific embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0035] See also Figure 1-Figure 7 The present application discloses a method for assessing suitable mangrove forest land for mangrove ecological restoration, comprising:

[0036] Step 1: Select the study area and divide it into the suitable forest land assessment areas (i.e. Figure 3 The evaluation area shown and Figure 5 assessment areas in the ) and reference systems;

[0037] Step 2: Conduct field surveys on the forestland suitable evaluation area and the reference system on the ground in step 1, and obtain field survey data on the forestland suitable evaluation area and the reference system on the ground;

[0038] Step 3: Obtain the multi-temporal satellite remote sensing images of the forestland suitable evaluation area and reference system on the ground in step 1, use the visual interpretation method to delineate the forestland suitable evaluation area and reference system in the space that matches the field survey data in step 2 in the multi-temporal satellite remote sensing images, and mark them with vectors respectively;

[0039] Step 4: Based on the field survey data in the reference system in step 2, a suitable forestland evaluation model is constructed;

[0040] Step 5: Input the field survey data of the suitable forest land evaluation area in step 2 into the suitable forest land evaluation model in step 4 for analysis to obtain the suitable forest land suitability evaluation results of the study area.

[0041] Among them, the forest land assessment area in step 1 is the tidal flat without vegetation, whether it is naturally formed or artificially filled, these tidal flats will serve as an important base for mangrove ecological restoration and construction projects;

[0042] The reference system is the distribution area of ​​natural mangroves or successfully restored mangroves in the study area, so as to provide a good reference for the ecological restoration and creation of mangroves.

[0043] Specifically, the field survey data of the suitable forest land evaluation area and the reference system in step 2 both contain sedimentary environmental factor data, and the field survey data of the reference system also contains aboveground biomass of mangroves.

[0044] More specifically, the field survey data of the reference system in step 2 is the aboveground biomass of mangroves. According to the Technical Regulations for Mangrove Ecological Monitoring HY / T 081-2005, a mangrove community survey (cross-section sampling method) was carried out. Within the cross-section of the mangrove community distribution, sampling plots were arranged at low, medium and high tide levels, and a 10m×10m sample plot was arranged in each sampling plot (such as Figure 3 BS1-BS3), use a 2m fiberglass tape to measure the trunk circumference (C) of each tree with a circumference greater than 4cm. The measurement is carried out at shoulder height, about 1.5m from the ground. The trunk circumference of the tree is measured to calculate the breast diameter (D), the calculation formula is:

[0045] D=C / π(1)

[0046] Measure plant height, which is the height from the ground to the highest point of the plant. Use visual inspection to investigate the plant height (m).

[0047] Based on the parameters of DBH and plant height, the aboveground biomass of different mangrove species was estimated according to the mangrove allometric equation.

[0048] The sedimentary environment factor data in step 2 are obtained by the following method:

[0049] Step 2-1: Sediment sampling: In the suitable forestland assessment area or the cross section of the reference system where the mangrove community is distributed, sample plots are set up at low, medium and high tide levels, with one sample plot set up in each sample plot. The size of each sample plot is 10m×10m. Soil cores are taken from each sample plot. From the surface of the soil core, soil samples are taken out at 10cm and stored in an incubator;

[0050] Step 2-2: Measure the salinity, pH, elevation and average particle size of the soil sample in step 2-1 as sedimentary environment factor data.

[0051] It should be noted that in step 2-2, soil salinity and pH experimental tests are carried out in accordance with the "Soil Testing Standard of the Agricultural Industry Standard of the People's Republic of China NY / T1121.1-2006".

[0052] Specifically, the suitable forestland evaluation model in step 4 is constructed by the following method:

[0053] Step 4-1: Normalize the aboveground biomass of mangroves in the reference system of step 2 to construct a suitability index. The calculation formula of the suitability index is as follows:

[0054]

[0055] Among them, SI is the suitability index, AGB is the aboveground biomass of mangroves, and AGB max is the maximum aboveground biomass of mangroves;

[0056] Assume AGB max The area with the highest mangrove biomass is considered to have a suitability index of 1, while the area with less mangrove biomass is considered to have a suitability index of 0;

[0057] Step 4-2: Use linear or nonlinear regression models to establish an empirical relationship model between the sedimentary environmental factor data of the reference system (such as elevation, salinity, pH, organic matter content, soil particle size, etc.) and the SI in step 4-1. The constructed model has a high degree of fit (high R value and passed the significance test P<0.05);

[0058] It should be noted that the use of linear or nonlinear regression models to establish empirical relationship models is obtained through data fitting. There is no fixed formula. The one with the best fit is used.

[0059] Step 4-3: Use the empirical relationship model in step 4-2 to construct an arithmetic mean method suitable forestland evaluation model and a geometric mean algorithm suitable forestland model based on the arithmetic mean method and the geometric mean algorithm, respectively. Compare the root mean square errors of the two models and select the best one for use.

[0060] Specifically, the calculation formula of HSI is as follows:

[0061] Geometric mean method

[0062] Arithmetic mean HSI AM =(SI1+S12+...SI i-1 +SI i ) / i

[0063] Among them, SI i This is the empirical relationship model constructed using the sedimentary environmental element data of the reference system in step 4-2.

[0064] It should be noted that the root mean square error (RMSE) is a commonly used indicator to measure the difference between the model prediction value and the actual observation value, which is used to evaluate the degree of fit of the model on the given data.

[0065] The smaller the RMSE value, the higher the prediction accuracy of the model. Ideally, it is close to zero, indicating that the model perfectly predicts the data. However, due to the existence of randomness and data variation, it is impossible to completely eliminate errors, so the RMSE should be as small as possible, but it does not need to be too low.

[0066] Therefore, this application compares the RMSE values ​​of the suitable forestland evaluation model using the arithmetic mean method and the suitable forestland model using the geometric mean algorithm, and selects the model with the smaller RMSE value for use.

[0067] On-site sampling is used to obtain tidal flat sediment environmental indicators in the forestland suitable evaluation area, and interpolation calculations are performed. Combined with the comprehensive assessment method of forestland suitable, the suitability of mangrove afforestation in the forestland suitable evaluation area is evaluated to obtain the suitability index of the forestland suitable evaluation area. This application considers that an area above 0.5 is suitable for mangrove establishment, and the survival probability of the planted mangroves is high.

[0068] Example

[0069] The present invention takes the mangrove sample plots and Sentinel-2 satellite images investigated recently as examples to provide a method for assessing suitable mangrove forest land for mangrove ecological restoration, and illustrates the above steps of the present invention by examples;

[0070] Area Selection

[0071] According to the planning outline of the protected area and visits and surveys, appropriate forestland suitable for evaluation areas are selected. The forestland suitable for evaluation areas must meet the following requirements: (1) the area is designated as afforestation project land, and (2) there is native forest distribution in the surrounding area as a reference system.

[0072] Site investigation

[0073] During the first period of low tide on a cloudless, sunny day, on-site vegetation plot surveys and sediment soil sampling were carried out. Survey plots were arranged according to the reference system, the scope of the evaluation area, and the distribution characteristics of mangroves. Each plot had an area of ​​10m×10m. The plant height, breast diameter, and basal diameter of the mangrove plants in each plot were measured, the land feature type and vegetation type of the study area were obtained, and sediment samples were collected in the plots.

[0074] Obtain photos of different types of land features in the study area (including mangroves, beach, water bodies, etc.) and record the locations of the land features; arrange mangrove ecological survey plots according to the scope of the study area and the distribution characteristics of mangroves, with each plot measuring 10m×10m, measure the plant height, breast diameter, and basal diameter of mangrove plants in each plot, and obtain field survey data on land feature types and vegetation types in the study area and mangrove ecological survey plots;

[0075] In a certain area of ​​Guangdong, a field survey was carried out in April 2024. High, medium and low tide sampling sites were set, namely BS1, BS2 and BS3. The area of ​​each sample plot was 10m×10m. The plant height, breast diameter and basal diameter of the mangrove plants in the sample plot were measured, and different vegetation types were recorded. This survey was mainly based on the communities of Avicennia marina and Sonneratia apetala. In order to calculate the aboveground biomass, according to the reference data, the allometric growth equation was:

[0076] Sonneratia apetala-W top =0.034×(D 2 H) 0.966 , (R 2 =0.915,n=25,Dmax =56.5cm)

[0077] Avicennia marina-W top =0.07612×(D 2 H)-0.222424, (R 2 =0.983)

[0078] W top is the aboveground biomass, D is the breast diameter parameter (cm), H is the plant height (m), and D max is the upper limit breast diameter parameter of the formula, and n is the number of samples.

[0079] The surface 10 cm sediments were collected from different forest samples and stored at low temperature.

[0080] Laboratory test analysis

[0081] The soil samples were dried and ground, and an appropriate amount of soil samples were taken and mixed according to the soil-liquid ratio of 1:2.5 and 1:5 respectively. After 3-5 minutes of shaking and stirring, the mixture was placed for 30 minutes. The salinity probe and pH mudflat of the WTW-Multi 3630IDS water quality meter were inserted under the liquid surface until the water quality meter value was stable, and the readings were recorded.

[0082] Some samples were used for sediment particle size analysis using a Mastersizer laser particle size analyzer (Malvern 3000, UK). About 0.2 g of sediment sample was put into a beaker, and 10% HCl solution was added to cover the sample. The sample was stirred with a glass rod to allow it to react fully to remove impurities such as inorganic carbon in the sediment. The acid was washed with water until it was neutral. Subsequently, 10% H2O2 was added to allow it to react fully to remove organic matter. Finally, 3 to 5 mL of 0.5 mol L-1 sodium hexametaphosphate solution was added and stirred to allow it to mix fully. After standing for 24 hours, the frequency data of each particle size was measured on the machine.

[0083] The percentage of clay, silt and sand is divided according to the Uden-Wentworth particle size distribution, where the boundary particle size between clay and silt is 0.004 mm, and the boundary particle size between silt and sand is 0.063 mm. The average particle size Mz of the sediment is calculated using the Fork-Ward diagram method, and the calculation formula is as follows:

[0084]

[0085] In the formula They represent the cumulative percentages of 16%, 50%, 84% and the corresponding particle sizes respectively.

[0086] Sentinel-2 satellite image processing

[0087] Sentinel-2 is an important optical remote sensing satellite in the Copernicus program series jointly implemented by the European Commission and the European Space Agency. It has 13 spectral bands (as shown in Table 1). We selected images near the field sampling survey period and historical image data, and used band numbers 4, 3, and 2 to fuse them into true color images. Combined with the field survey ground feature information, the reference system range and the suitable forestland evaluation area in the image were visually interpreted and delineated, such as Figure 5 shown.

[0088] Table 1 Spectral band parameters of Sentinel-2 satellite camera

[0089]

[0090]

[0091] HSI model construction

[0092] Based on the survey results of aboveground biomass (AGB) in the reference system area, the SI index was obtained by normalization processing. The calculation formula is as follows:

[0093]

[0094] Where AGB is the biomass of the vegetation survey plot, AGB max It is the maximum biomass of the vegetation survey plot. The larger the biomass, the higher the suitability of the forest land, that is, the higher the SI.

[0095] SI and sedimentary environment index data were constructed in the reference system sample plot. The data fitting diagram is shown in the figure, and the fitting results are shown in Table 2.

[0096] Table 2 SI equation fitting results

[0097]

[0098] The results in Table 2 show that only the SI index equation of pH factor was not constructed successfully, while other environmental indicators were constructed successfully.

[0099] The HSI model is constructed using the arithmetic mean method and the geometric mean method, as shown below:

[0100] HSI AM =(SI S +SI DEM +SI Mz ) / 3

[0101]

[0102] HSI AM :SI s Empirical modeling of salinity indicators, SI sEmpirical modeling of salinity indicators, SI DEM Empirical modeling of elevation indicators, SI MZ Empirical modeling of the average sediment grain size index.

[0103] Model Validation

[0104] Based on the sediment environment test data of the assessment area, the two constructed HSI models were used to calculate the suitability index of the forest land for the planned afforestation project in the assessment area, and the field survey data (BS4, BS5, BS6) were used to verify the model. The root mean square error (RMSE) was used to evaluate the accuracy of the biomass inversion model. RMSE is a measure of the deviation between the predicted value and the measured value. The smaller the value, the higher the accuracy of the prediction model; the most accurate forest land assessment model was selected, and the RMSE calculation formula is as follows:

[0105]

[0106] RMSE stands for root mean square error, yi stands for the predicted value of sample i, and y 0 i represents the measured value of sample i, and n represents the number of samples.

[0107] The model validation results are shown in the following table.

[0108] Model validation results table

[0109]

[0110]

[0111] According to the model verification results, HSI is selected AM Serves as a model for assessing suitable forestland for afforestation projects in the region.

[0112] (1) Assessment of suitable mangrove forest land

[0113] The assessment area is based on the sample points set in the intertidal zone profile (PG1-PG5) and the model validation data (BS4-BS6), such as Figure 7 shown.

[0114] The evaluation results of mangrove suitable forest land are shown in Table 3. Habitat model theory generally believes that HSI values ​​greater than 0.5 indicate that the environment is suitable for the target organisms to inhabit. The HSI of suitable forest land evaluation areas PG2-PG5 AM The values ​​were all above 0.6, indicating that the environment provided by the tidal flats between PG2 and PG5 is suitable for the growth of mangroves, and the survival rate of mangrove afforestation is high, while the HSI in the PG1 area is AM The value is less than 0.5, indicating that the suitability of mangrove afforestation habitat in this tidal flat area is poor and the tidal flat habitat needs to be further improved.

[0115] Table 3 Evaluation results of suitable forest land in the evaluation area

[0116]

[0117] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for assessing suitable mangrove forest land for mangrove ecological restoration, characterized in that: include: Step 1: Select the study area and divide it into the ground suitable forest land evaluation area and reference system; Step 2: Conduct field surveys on the forestland suitable evaluation area and the reference system on the ground in step 1, and obtain field survey data on the forestland suitable evaluation area and the reference system on the ground; Step 3: Obtain the multi-temporal satellite remote sensing images of the ground suitable forest land evaluation area and reference system in step 1, delineate the spatial suitable forest land evaluation area and reference system that match the field survey data in step 2 in the multi-temporal satellite remote sensing images, and perform vector marking respectively; Step 4: Based on the field survey data in the reference system in step 2, a suitable forestland evaluation model is constructed; Step 5: Input the field survey data of the suitable forest land evaluation area in step 2 into the suitable forest land evaluation model in step 4 for analysis to obtain the suitable forest land suitability evaluation results of the study area.

2. The method for assessing suitable mangrove forest land for mangrove ecological restoration according to claim 1, characterized in that: In step 1, the suitable forest land evaluation area is the light beach where artificial mangrove planting is planned in the study area, and the reference system is the distribution area of ​​natural mangroves or successfully restored mangroves in the study area.

3. The method for assessing suitable mangrove forest land for mangrove ecological restoration according to claim 1, characterized in that: In step 2, the field survey data of the suitable forest land evaluation area and the reference system both include sedimentary environmental factor data, and the field survey data of the reference system also includes above-ground biomass of mangroves.

4. The method for assessing suitable mangrove forest land for mangrove ecological restoration according to claim 3, characterized in that: In step 2, the sedimentary environment factor data is obtained by the following method: Step 2-1: In the suitable forest land assessment area or the cross section of the reference system where the mangrove community is distributed, sample plots are set up at low, medium and high tide levels, with one sample plot set up in each sample plot. Soil samples are collected in each sample plot with a depth of 10 cm. After the soil samples are taken out, they are frozen and stored; Step 2-2: Measure the salinity, pH, elevation and average particle size of the soil sample in step 2-1 as sedimentary environment factor data.

5. The method for assessing suitable mangrove forest land for mangrove ecological restoration according to claim 4, characterized in that: In step 2-1, the specification of each sample plot is 10m×10m.

6. The method for assessing suitable mangrove forest land for mangrove ecological restoration according to claim 1, characterized in that: In step 4, the suitable forestland evaluation model is constructed by the following method: Step 4-1: Normalize the aboveground biomass of mangroves in the reference system of step 2 to construct a suitability index. The calculation formula of the suitability index is as follows: Among them, SI is the suitability index, AGB is the aboveground biomass of mangroves, and AGB max is the maximum aboveground biomass of mangroves; Step 4-2: Use a linear or nonlinear regression model to establish an empirical relationship model between the sedimentary environmental factor data of the reference system and the suitability index of step 4-1; Step 4-3: Based on the empirical relationship model in step 4-2, construct the arithmetic mean method suitable forestland evaluation model and the geometric mean algorithm suitable forestland model based on the arithmetic mean method and the geometric mean algorithm respectively.

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