Mangrove forest ecosystem health evaluation method and mangrove forest ecosystem health evaluation system based on species level

Abstract

The invention discloses a mangrove forest ecosystem health evaluation method based on a species level. Acquiring a mangrove species distribution grid map of the sample plot; obtaining a condition index distribution map based on the soil physicochemical properties of the sample plot; acquiring an aboveground biomass spatial distribution diagram of the sample plot as a vital index distribution diagram; obtaining a plurality of landscape pattern index distribution diagrams based on the sample plot plant pattern, and calculating a tissue force index distribution diagram based on the corresponding weight; obtaining a resistance index and restoring force index distribution map based on the sample plot landscape pattern, and obtaining an elastic force index distribution map by combining the comprehensive pollution index distribution map; calculating an ecological health index distribution map based on the condition index distribution map, the vitality index distribution map, the tissue force index distribution map and the elastic force index distribution map; and based on superposition of the ecological health index distribution map and the mangrove species distribution grid map, obtaining health conditions and spatial distribution of different mangrove plants in the sample plot. And fine quantitative evaluation of ecological health of mangrove plants is realized.

Description

Technical Field

[0001] The present invention relates to the field of environmental protection technology, and more specifically to a mangrove ecosystem health assessment method and system based on species level. Background Art

[0002] Mangroves refer to wetland woody plant communities composed of evergreen shrubs or trees, mainly from the family Mangrove, distributed in tropical and subtropical coastal intertidal zones and estuaries. They play an important role in breaking waves and protecting embankments, resisting marine natural disasters, protecting biodiversity, and improving coastal ecological environments. Effectively conducting comprehensive evaluation studies on the health level of mangrove wetland ecosystems, analyzing the spatiotemporal dynamic changes in their health level, and exploring the driving factors that cause the destruction or degradation of mangrove wetland ecosystems not only provides technical support for the scientific protection and management of mangrove wetland resources, but also has important practical significance for maintaining the balance and sustainable development of regional ecosystems.

[0003] At present, the main models for evaluating the ecological health of mangrove wetlands include COR, CVOR, PSR and DPSIR. The scale of ecological health evaluation is mainly based on large and medium-sized scopes such as the whole country, river basin or specific ecological region, and there is a lack of wetland ecological health evaluation methods at a small scale. The indicators selected for constructing the model are mostly macro indicators such as GDP and population, and there is a lack of micro indicators that can reflect the change process of landscape pattern, such as landscape connectivity and landscape heterogeneity. The research results are mostly displayed as overall results or divided into small areas, which cannot reflect the spatial heterogeneity of the internal structure. All of the above indicate that the current research methods cannot accurately reflect the quality of the mangrove ecosystem at the species level; mangrove plants are one of the most important components of the mangrove wetland ecosystem. Because of their fixedness, many scholars believe that they are one of the most direct indicators reflecting the wetland ecological environment. However, the ecological health evaluation of mangrove wetlands based on the species scale is still blank.

[0004] Therefore, how to achieve a fine quantitative evaluation of the ecological health of mangrove species and then intuitively and accurately obtain the quality status of mangrove ecosystems is an urgent problem that technicians in this field need to solve. Summary of the invention

[0005] In view of this, the present invention provides a mangrove ecosystem health assessment method and system based on the species level, which realizes the fine quantitative assessment of mangrove ecological health at the species level, and thus can intuitively and accurately obtain the quality status of the mangrove ecosystem.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A species-based mangrove ecosystem health assessment method, including:

[0008] Select mangroves in the study area as sample plots, and obtain a mangrove species distribution grid map of the sample plots;

[0009] Obtaining a condition index distribution map based on the soil physical and chemical properties of the sample plot;

[0010] Based on the plant biomass of the sample plot, a spatial distribution map of aboveground biomass of the sample plot is obtained as a vitality index distribution map;

[0011] Based on the plant distribution pattern of the sample plot, multiple landscape pattern index distribution maps are obtained and the organizational index distribution map is calculated based on the corresponding weights;

[0012] Based on the landscape pattern of the sample plot, a resistance index distribution map and a resilience index distribution map are obtained, and the elasticity index distribution map is calculated in combination with the comprehensive pollution index distribution map;

[0013] An ecological health index distribution map is calculated based on the condition index distribution map, the vitality index distribution map, the organizational force index distribution map, and the elasticity index distribution map;

[0014] Based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map, the health status and spatial distribution of different mangrove plants in the sample site are obtained.

[0015] Preferably, the method for obtaining the mangrove species distribution grid map is:

[0016] Acquire radar laser point cloud data of the sample site;

[0017] Random forest and support vector machine are used to perform pixel-based mangrove species classification on the radar laser point cloud data to obtain a mangrove species distribution grid map with a preset resolution.

[0018] Preferably, the method for obtaining the conditional index distribution graph is:

[0019] Obtaining surface soil samples from different spatial areas of the sample plot;

[0020] Based on the surface soil sample, the pH value, soil organic matter, total phosphorus, total nitrogen and total potassium of the sample plot are obtained as soil property data;

[0021] Based on the corresponding soil property data, a spatial distribution map of each soil property is obtained by kriging interpolation, and converted into a spatial grid map of corresponding resolution;

[0022] After establishing a corresponding membership function model based on the soil property data, standardization processing is performed to obtain dimensionless soil property data;

[0023] Based on the importance of each dimensionless soil property data to the sample plot, the AHP hierarchical analysis method is used to obtain the corresponding indicator weight;

[0024] The conditional index distribution map is obtained by performing calculations based on the spatial grid map of each soil property and the corresponding index weights.

[0025] Preferably, the method for obtaining the vitality index distribution map is:

[0026] Based on the sample plot, a plurality of standard sample plots are obtained, and a predetermined number of standard sample plots are randomly selected for field investigation to obtain the wood density and corresponding diameter at breast height of all mangrove tree species;

[0027] Obtaining the aboveground biomass of the corresponding species of mangrove based on the wood density and the corresponding breast height diameter;

[0028] Constructing a random forest model based on all of the aboveground biomass combined with spectral parameters of remote sensing images;

[0029] The aboveground biomass spatial distribution map is obtained based on the random forest model inversion as the vitality index distribution map.

[0030] Preferably, the method for obtaining the organizational force index distribution map is:

[0031] Based on the plant community characteristics of the sample plot, a moving window method is used to obtain a variety of landscape pattern index distribution maps;

[0032] The landscape pattern index distribution maps include: Shannon diversity index distribution map SHDI, Shannon evenness index distribution map SHEI, patch cohesion index distribution map COHESION, landscape aggregation index distribution map CONTAG, landscape shape index distribution map LSI and perimeter-area fractal dimension index distribution map PAFRAC;

[0033] Based on the importance of each landscape pattern index distribution map to the sample plot, the AHP hierarchical analysis method is used to obtain the corresponding index weight;

[0034] The organizational strength index distribution map is obtained based on each of the landscape pattern index distribution maps and the corresponding indicator weights.

[0035] Preferably, the tissue force index distribution diagram O is:

[0036]

[0037] Preferably, the method for obtaining the elasticity index distribution map is:

[0038] Converting the land use distribution map based on the sample plot into a raster layer;

[0039] Based on the grid layer and the weighted calculation according to different land use types, a resilience coefficient distribution map Resil and a resistance coefficient distribution map Resist of the sample plot are obtained;

[0040] Obtaining a distribution map of soil heavy metal content in the sample plot;

[0041] Obtaining an average single pollution index of each heavy metal based on the soil heavy metal content distribution map;

[0042] Obtaining a comprehensive pollution index based on the average single pollution index;

[0043] Obtaining the comprehensive pollution index distribution map INPI based on the comprehensive pollution index;

[0044] The elasticity index distribution map is obtained by calculating according to corresponding weights based on the restoration coefficient distribution map, the resistance coefficient distribution map and the comprehensive pollution index distribution map.

[0045] Preferably, the elasticity index distribution diagram R is specifically:

[0046] R=0.7×(0.7×Resil+0.3×Resist)+0.3×INPI.

[0047] Preferably, it is characterized in that the ecological health index distribution map EHI is specifically:

[0048] EHI=0.25×C+0.25×V+0.25×O+0.25×R;

[0049] The health status includes five ecological health levels: very weak (0-0.2), weak (0.2-0.4), moderate (0.4-0.6), strong (0.6-0.8) and very strong (0.8-1.0).

[0050] A mangrove ecosystem health assessment system based on species level, comprising: a first distribution map acquisition module, a second distribution map acquisition module, a third distribution map acquisition module, a fourth distribution map acquisition module, a fifth distribution map acquisition module, a layer overlay analysis module, and a result output module;

[0051] The first distribution map acquisition module is used to select mangroves in the study area as sample plots and obtain a mangrove species distribution grid map of the sample plots;

[0052] The second distribution map acquisition module is used to obtain the condition index distribution map of the sample plot based on the soil physical and chemical properties of the sample plot;

[0053] The third distribution map acquisition module is used to acquire the aboveground biomass spatial distribution map of the sample plot as the vitality index distribution map based on the plant biomass of the sample plot;

[0054] The fourth distribution map acquisition module is used to acquire multiple landscape pattern index distribution maps based on the plant distribution pattern of the sample plot and calculate the organizational index distribution map based on the corresponding weights;

[0055] The fifth distribution map acquisition module is used to acquire a resistance index distribution map and a resilience index distribution map based on the landscape pattern of the sample plot, and calculate an elasticity index distribution map in combination with the comprehensive pollution index distribution map;

[0056] The layer overlay analysis module is used to calculate the ecological health index distribution map based on the condition index distribution map, the vitality index distribution map, the organizational force index distribution map and the elasticity index distribution map;

[0057] The result output module is used to obtain the health status and spatial distribution of different mangrove plants in the sample site based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map.

[0058] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method and system for evaluating the health of a mangrove ecosystem based on species level, which has the following beneficial effects:

[0059] 1. The present invention is a refined evaluation method based on the species level, which can realize the ecological health status and spatial distribution analysis of different mangrove plant types on a small scale, and can accurately and quantitatively evaluate the quality of mangrove ecosystems, provide a reference for the current evaluation of the effectiveness of mangrove wetland restoration, and adjust the plant community configuration and improve the habitat environmental factors accordingly, thereby improving the quality of mangrove ecosystems and providing guidance for subsequent mangrove restoration activities.

[0060] 2. Compared with traditional field sample surveys, it saves time and cost, and the operation platform is built based on remote sensing big data, which is simple, convenient and more universal.

[0061] 3. Comprehensively consider multiple indicator coefficients to establish a mangrove wetland health assessment method and system, visualize and accurately display the ecological health status of different plants and their spatial analysis, which can show the spatial heterogeneity within the same study area, further develop and improve the mangrove wetland ecological health assessment system, and thus more effectively guide the protection and restoration of the mangrove wetland ecosystem. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0063] Figure 1 A flow chart of a mangrove ecosystem health assessment method based on species level provided by the present invention.

[0064] Figure 2 This is a mangrove species distribution grid map provided in Example 2 of the present invention.

[0065] Figure 3 This is the ecological health index distribution map provided in Example 2 of the present invention.

[0066] Figure 4 This is a statistical diagram of the health status of different mangrove communities provided in Example 2 of the present invention.

[0067] Figure 5 This is a schematic diagram of the spatial distribution of the health conditions of different mangrove communities provided in Example 2 of the present invention.

[0068] Figure 6 A schematic diagram of the structure of a mangrove ecosystem health assessment system based on species level provided by the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] Example 1

[0071] like Figure 1 As shown, the embodiment of the present invention discloses a method for evaluating the health of a mangrove ecosystem based on species level, including:

[0072] Select mangroves in the study area as sample plots, and obtain the mangrove species distribution grid map of the sample plots;

[0073] The condition index distribution map was obtained based on the soil physical and chemical properties of the sample plot;

[0074] Based on the plant biomass of the sample plots, the spatial distribution map of the aboveground biomass of the sample plots is obtained as the vitality index distribution map;

[0075] Based on the plant distribution pattern of the sample plot, multiple landscape pattern index distribution maps are obtained and the organizational index distribution map is calculated based on the corresponding weights;

[0076] Based on the landscape pattern of the sample plot, the distribution map of resistance index and the distribution map of resilience index are obtained, and the distribution map of elasticity index is calculated by combining the distribution map of comprehensive pollution index;

[0077] The ecological health index distribution map is calculated based on the condition index distribution map, vitality index distribution map, organizational index distribution map and elasticity index distribution map;

[0078] Based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map, the health status and spatial distribution of different mangrove plants in the sample site were obtained.

[0079] Example 2

[0080] The embodiment of the present invention discloses a method for evaluating the health of a mangrove ecosystem based on species level, comprising:

[0081] Mangroves in the study area were selected as sample plots, and the mangrove species distribution grid map of the sample plots was obtained.

[0082] Preferably, the method for obtaining the mangrove species distribution grid map is:

[0083] Obtain radar laser point cloud data of the sample site;

[0084] Random forest and support vector machine were used to perform pixel-based mangrove species classification on radar laser point cloud data to obtain a mangrove species distribution grid map with a preset resolution.

[0085] Preferably, the preset resolution of this embodiment is 2M, and a small island with mangroves is used as a sample plot of the research area to obtain a mangrove species distribution grid map of the sample plot, such as Figure 2 shown.

[0086] The condition index distribution map was obtained based on the soil physical and chemical properties of the sample plot.

[0087] Preferably, the method for obtaining the conditional index distribution graph is:

[0088] Obtain surface soil samples from different spatial areas of the sample plot;

[0089] Based on the surface soil samples, the pH value, soil organic matter, total phosphorus, total nitrogen and total potassium of the sample plot were obtained as soil property data;

[0090] Based on the corresponding soil property data, the spatial distribution map of each soil property is obtained through Kriging interpolation and converted into a spatial grid map of corresponding resolution;

[0091] After establishing the corresponding membership function model based on the soil property data, the dimensionless soil property data is obtained by standardization.

[0092] Based on the importance of each dimensionless soil property data to the sample site, the AHP hierarchical analysis method was used to obtain the corresponding indicator weights;

[0093] The conditional index distribution map is obtained based on the spatial grid map of each soil property and the corresponding index weights.

[0094] Preferably, freeze drying is performed on the surface soil samples using a freeze dryer (NH-A18N-80, Ninghuai Instrument, China), ground, and passed through a 0.149 mm sieve. In order to remove the carbonate washed out, about 0.50 g of soil sample is acidified using 20 mL 1.0 M HCl, and then washed three to four times with distilled water until a neutral pH is reached. Organic carbon concentration is measured using a TC analyzer (Thermo Electron EL, Germany). Based on soil organic carbon (SOC) converted into soil organic matter (SOM), the conversion factor is 1.724.

[0095] Preferably, total nitrogen (TN) is determined by an elemental analyzer (Vario MAX; Elementar, Germany); total phosphorus (TP) is determined by HF-HClO4 digestion and then molybdenum antimony colorimetry; total potassium (TK) is determined by flame photometry; and soil pH is measured in a 1:2.5 (w / w) soil suspension using an Orion3-star digital portable pH meter.

[0096] Preferably, after the experimental data of various soil properties are obtained through testing, the spatial distribution map of the various soil property data in the entire sample site (2M resolution) is obtained through Kriging interpolation.

[0097] Preferably, the effect of pH value on mangrove health conforms to the peak value function, and the peak membership function is adopted, and its standardized processing formula is as follows:

[0098]

[0099] The impact of SOM, TP, TN and TK indicators on mangrove health conforms to the upper limit rule function, and adopts the upper-type membership function. The standardized processing formula is as follows:

[0100]

[0101] Among them, x1, x2, x3 and x4 are the inflection point values ​​of the corresponding soil property functions.

[0102] Preferably, the inflection point values ​​of the corresponding soil property functions in this embodiment are shown in Table 1:

[0103] Table 1 Inflection point values ​​of corresponding soil property functions

[0104]

[0105] Preferably, based on the spatial distribution map of each soil property and the corresponding membership weight, a raster calculator is used in GIS to finally obtain a conditional index distribution map C:

[0106] C=0.2×pH+0.2×SOM+0.2×TN+0.2×TP+0.2×TK.

[0107] Based on the plant biomass of the sample plot, the spatial distribution map of the aboveground biomass of the sample plot is obtained as the vitality index distribution map.

[0108] Preferably, the method for obtaining the vitality index distribution map is:

[0109] Based on the sample plot division, multiple standard sample plots were obtained according to the plant community type and its spatial distribution. A predetermined number of standard sample plots were randomly selected for field survey to obtain the wood density and corresponding breast diameter of all mangrove tree species;

[0110] The aboveground biomass of the corresponding mangrove plants was obtained based on the wood density and the corresponding DBH;

[0111] A random forest model was constructed based on all aboveground biomass combined with the spectral parameters of remote sensing images;

[0112] The spatial distribution map of aboveground biomass was inverted based on the random forest model as the vitality index distribution map.

[0113] Preferably, in this embodiment, the sample plots are divided according to tree species and forest age, and 39 standard sample plots (10m×10m) are randomly selected, each of which is more than 20m away from the edge of the forest to eliminate marginal effects. Field surveys are conducted in each standard sample plot. All mangrove plants are identified, the number of each species is recorded, and the wood density and corresponding diameter at breast height of all mangrove tree species are obtained;

[0114] The aboveground biomass W of mangroves of the corresponding species was obtained based on wood density and corresponding DBH. top :

[0115] W top =0.251ρD 2.46 ;

[0116] Where ρ represents the wood density (g cm -3 ), D represents DBH (cm), and the wood density and DBH of different mangrove species are from field plot survey data. The biomass of all standing trees was calculated using the general allometric equation.

[0117] Preferably, R is constructed based on all aboveground biomass combined with the spectral parameters of remote sensing images. 2 >0.5 Random Forest Model, R 2 It is an index to measure the quality of the model; the spatial distribution map of aboveground biomass is inverted based on the random forest model as the vitality index distribution map V.

[0118] Preferably, the hyperspectral remote sensing data of the sample site in this embodiment includes 8 spectral bands, including four classic bands (ie, red, blue, green and near infrared) and four newly developed bands (ie, coast, yellow, red edge and near infrared 2).

[0119] Based on the plant pattern of the sample plot, multiple landscape pattern index distribution maps are obtained and superimposed based on the corresponding weights to obtain the organizational index distribution map.

[0120] Preferably, the method for obtaining the organizational strength index distribution map is:

[0121] Based on the sample plots, the landscape pattern index at the plant community species level is obtained, and then the moving window method is used to obtain the distribution maps of multiple landscape pattern indices with a predetermined resolution;

[0122] The landscape pattern index distribution maps include: Shannon diversity index distribution map SHDI, Shannon evenness index distribution map SHEI, patch cohesion index distribution map COHESION, landscape aggregation index distribution map CONTAG, landscape shape index distribution map LSI and perimeter-area fractal dimension index distribution map PAFRAC;

[0123] Based on the importance of each landscape pattern index distribution map to the sample plot, the AHP hierarchical analysis method was used to obtain the corresponding index weights;

[0124] The organizational index distribution map is obtained based on the distribution maps of various landscape pattern indices and the corresponding indicator weights.

[0125] Preferably, ecosystem organizing force refers to the structural stability of the ecosystem, which is related to the spatial pattern.

[0126] Preferably, the landscape pattern index is calculated based on the sample plot using a moving window method using five windows of different resolutions, namely 1×1m, 5×5m, 1×1m, 10×10m and 2×2m. In this embodiment, a 2m×2m window is used to calculate the six landscape pattern index distribution maps of the entire sample plot. This size is suitable for the study area and can be used to reflect the differences in the landscape pattern of plant communities.

[0127] Preferably, the Shannon diversity index SHDI is a widely used indicator for measuring community ecological diversity. The Shannon diversity index is more susceptible to different patch types than the Simpson index; Shannon diversity index SHDI:

[0128]

[0129] Among them, P i represents the proportion of the excellent patch type in the landscape, and m represents the number of patch types.

[0130] Preferably, the Shannon evenness index SHEI is an index for measuring patch diversity, which is determined by the distribution ratio of different species in the landscape. The higher this value, the more uniform the landscape composition:

[0131]

[0132] Preferably, the patch cohesion index COHESION reflects the spatial connection and aggregation degree among patches of the same type, and is one of the important indexes for evaluating the landscape pattern and ecological process. The larger the value, the closer the spatial connection among patches and the higher the aggregation degree:

[0133]

[0134] Among them, P * ij represents the perimeters of patches i and j, and a * ij represents the area of the j-th patch in the landscape type i; Z represents the total area of the entire landscape.

[0135] Preferably, the landscape contagion index CONTAG is an index for measuring the aggregation degree of patch distribution in the landscape. It is based on the spatial distribution pattern of patches and reflects the proximity degree and spatial aggregation among patches:

[0136]

[0137] g ik represents the number of adjacencies (connections) between the pixels of patch types i and k, j = 1,..., n patches; i = 1,..., m patch types (categories), characterizing patch connectivity 0 < CONTAG ≤ 1. The higher the value, the stronger the patch connectivity and the healthier the ecosystem.

[0138] Preferably, the landscape shape index LSI is based on the perimeter and area of patches and characterizes the complexity of the landscape patch shape. If the shape of a patch is more complex, its landscape structure is also equally complex:

[0139]

[0140] Among them, E represents the total length of the patch boundaries in the landscape, and A represents the total area of the landscape.

[0141] The preferred perimeter-area fractal dimension index PAFRAC measures the non-integer dimension of irregular geometric shapes in the landscape, reflecting the complexity of these shapes. Index values ​​close to 1 indicate simpler patch shapes that are less potentially affected by human activities:

[0142]

[0143] a ij represents the plaque area, p ij represents the perimeter of the plaque, and n represents the total number of plaques.

[0144] Preferably, an index distribution diagram corresponding to the sample plot is obtained based on the above-mentioned various indexes.

[0145] Preferably, based on the distribution maps of various landscape pattern indices and the corresponding index weights, a grid calculator is used in GIS to obtain the distribution map of the organizational index O:

[0146]

[0147] The resistance index distribution map and the resilience index distribution map were obtained based on the landscape pattern of the sample plot, and the elasticity index distribution map was calculated by combining the comprehensive pollution index distribution map.

[0148] Preferably, the method for obtaining the elasticity index distribution map is:

[0149] Based on the remote sensing images of the sample plots, the land use distribution map is interpreted and converted into a raster layer of a predetermined resolution;

[0150] Based on the grid layer and the weight assignment of different land use types, the distribution map of the resilience coefficient Resil and the distribution map of the resistance coefficient Resist of the sample plot are obtained;

[0151] Obtaining soil heavy metal content based on surface soil samples

[0152] Based on the corresponding soil heavy metal content, the spatial distribution map of each heavy metal was obtained by kriging interpolation and converted into a 2M soil heavy metal content distribution map;

[0153] Based on the soil heavy metal content distribution map, the average single pollution index of each heavy metal is obtained;

[0154] Based on the average single pollution index, a comprehensive pollution index is obtained;

[0155] Based on the comprehensive pollution index, we get the comprehensive pollution index distribution map INPI;

[0156] Based on the recovery coefficient distribution map, the resistance coefficient distribution map and the comprehensive pollution index distribution map, calculations are performed according to corresponding weights to obtain the elasticity index distribution map.

[0157] Preferably, resilience reflects the resilience of the ecosystem and is used to measure resistance and self-recovery to external influences (disturbance). If external disturbances severely damage the natural ecosystem, resilience should be emphasized; or if external disturbances do not significantly exceed the self-regulation capacity of the natural ecosystem, resistance should be given priority, resistance is given a low weight (0.3), and resilience is given a high weight (0.7).

[0158] Preferably, according to the landscape characteristics of the sample plot, the resilience coefficient Resil and the resistance coefficient Resist applied to each landscape type are as shown in Table 2:

[0159] Table 2 Resilience and resistance coefficients corresponding to different landscape types

[0160]

[0161] Preferably, the threat posed by some special pollutants such as heavy metals to mangrove habitats is considered and included in the resilience index. Soil was collected in the field, and 0.13 g of soil was digested with 8 ml HNO3 and 2 ml HF in a microwave digestion instrument (MARSTM6). The metal element content in the soil was determined by inductively coupled plasma mass spectrometry (IPC-MS Agilent 7700), and the distribution map of the content of 6 heavy metals in the sample site was obtained according to the Kriging interpolation method. According to the toxicological characteristics of each heavy metal, the grid calculator was used in GIS to further calculate the Nemerow comprehensive pollution index, and the calculation formula is as follows:

[0162]

[0163] In the formula, Represents the average single pollution index of various heavy metals, P i,max is the maximum pollution index. The single pollution index refers to the ratio of the measured value of heavy metals in the study area to the corresponding background value.

[0164] Preferably, the background value of heavy metal content in the islands in this embodiment is shown in Table 3:

[0165] Table 3 Background value of heavy metal content

[0166]

[0167] Preferably, the AHP hierarchical analysis method is used to calculate the index weights corresponding to the recovery coefficient distribution map, the resistance coefficient distribution map and the comprehensive pollution index distribution map, and the elasticity index distribution map is calculated using a grid calculator in GIS:

[0168] R=0.7×(0.7×Resil+0.3×Resist)+0.3×INPI.

[0169] The ecological health index distribution map is calculated based on the condition index distribution map, vitality index distribution map, organizational index distribution map and elasticity index distribution map.

[0170] Preferably, a grid calculator is used in GIS to substitute the four standardized indices of condition index, vitality index, organizational index and elasticity index into the calculation formula of ecological health index (EHI):

[0171] EHI=0.25×C+0.25×V+0.25×O+0.25×R.

[0172] Based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map, the health status and spatial distribution of different mangrove plants in the sample site were obtained.

[0173] Preferably, Figure 3-5 As shown in the figure, the overlay analysis function of ArcGIS10.6 software is used to overlay the ecological health index distribution map with the mangrove species distribution grid map to obtain the health status of each mangrove plant and its spatial distribution.

[0174] Preferably, the health status includes five ecological health levels: very weak (0-0.2), weak (0.2-0.4), moderate (0.4-0.6), strong (0.6-0.8) and very strong (0.8-1.0).

[0175] Preferably, the proportion of health status and the specific spatial location of its distribution can also be obtained, which provides a research method for understanding the health status and spatial distribution of different species in the sample plot and provides a reliable reference for the refined management of mangroves.

[0176] Example 3

[0177] like Figure 6 As shown, a mangrove ecosystem health assessment system based on species level includes: a first distribution map acquisition module, a second distribution map acquisition module, a third distribution map acquisition module, a fourth distribution map acquisition module, a fifth distribution map acquisition module, a layer overlay analysis module, and a result output module;

[0178] The first distribution map acquisition module is used to select mangroves in the study area as sample plots and obtain a mangrove species distribution grid map of the sample plots;

[0179] A second distribution map acquisition module is used to obtain a condition index distribution map of the sample plot based on the soil physical and chemical properties of the sample plot;

[0180] A third distribution map acquisition module is used to acquire a spatial distribution map of aboveground biomass of the sample plot based on the plant biomass of the sample plot as a vitality index distribution map;

[0181] A fourth distribution map acquisition module is used to acquire a plurality of landscape pattern index distribution maps based on the plant distribution pattern of the sample plot and calculate the organization index distribution map based on the corresponding weights;

[0182] The fifth distribution map acquisition module is used to obtain a resistance index distribution map and a resilience index distribution map based on the landscape pattern of the sample plot, and calculate an elasticity index distribution map in combination with the comprehensive pollution index distribution map;

[0183] A layer overlay analysis module is used to calculate an ecological health index distribution map based on a condition index distribution map, a vitality index distribution map, an organizational index distribution map, and an elasticity index distribution map;

[0184] The result output module is used to obtain the health status and spatial distribution of different mangrove plants in the sample site based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map.

[0185] Preferably, the process of implementing each functional module in this implementation corresponds one-to-one to the above method, and will not be repeated here.

[0186] Example 4

[0187] Based on the same inventive concept, the present invention also provides a computer device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0188] Memory, used to store computer programs;

[0189] The processor, when used to execute the program stored in the memory, can implement a mangrove ecosystem health assessment method based on species level as in Example 1 or 2.

[0190] The electronic device may include: a processor, a communications interface, a memory, and a communications bus, wherein the processor, the communications interface, and the memory communicate with each other via the communications bus. The processor may call logic instructions in the memory to execute a mangrove ecosystem health assessment method based on species level in Embodiment 1 or 2.

[0191] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0192] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method and system for evaluating the health of a mangrove ecosystem based on species level, which has the following beneficial effects:

[0193] 1. The present invention is a refined evaluation method based on the species level, which can realize the ecological health status and spatial distribution analysis of different mangrove plant types on a small scale, and can accurately and quantitatively evaluate the quality of mangrove ecosystems, provide a reference for the current evaluation of the effectiveness of mangrove wetland restoration, and adjust the plant community configuration and improve the habitat environmental factors accordingly, thereby improving the quality of mangrove ecosystems and providing guidance for subsequent mangrove restoration activities.

[0194] 2. Compared with traditional field sample surveys, it saves time and cost, and the operation platform is built based on remote sensing big data, which is simple, convenient and more universal.

[0195] 3. Comprehensively consider multiple indicator coefficients to establish a mangrove wetland health assessment method and system, visualize and accurately display the ecological health status of different plants and their spatial analysis, which can show the spatial heterogeneity within the same study area, further develop and improve the mangrove wetland ecological health assessment system, and thus more effectively guide the protection and restoration of the mangrove wetland ecosystem.

[0196] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0197] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the health of mangrove ecosystems based on species level, characterized in that: include: Select mangroves in the study area as sample plots, and obtain a mangrove species distribution grid map of the sample plots; Obtaining a condition index distribution map based on the soil physical and chemical properties of the sample plot; Based on the plant biomass of the sample plot, a spatial distribution map of aboveground biomass of the sample plot is obtained as a vitality index distribution map; Based on the plant distribution pattern of the sample plot, multiple landscape pattern index distribution maps are obtained and the organizational index distribution map is calculated based on the corresponding weights; Based on the landscape pattern of the sample plot, a resistance index distribution map and a resilience index distribution map are obtained, and the elasticity index distribution map is calculated in combination with the comprehensive pollution index distribution map; An ecological health index distribution map is calculated based on the condition index distribution map, the vitality index distribution map, the organizational force index distribution map, and the elasticity index distribution map; Based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map, the health status and spatial distribution of different mangrove plants in the sample site are obtained.

2. The method for evaluating the health of mangrove ecosystems based on species level according to claim 1 is characterized in that: The method for obtaining the mangrove species distribution grid map is: Acquire radar laser point cloud data of the sample site; Random forest and support vector machine are used to perform pixel-based mangrove species classification on the radar laser point cloud data to obtain a mangrove species distribution grid map with a preset resolution.

3. The method for evaluating the health of mangrove ecosystems based on species level according to claim 2 is characterized in that: The method for obtaining the conditional index distribution graph is: Obtaining surface soil samples from different spatial areas of the sample plot; Based on the surface soil sample, the pH value, soil organic matter, total phosphorus, total nitrogen and total potassium of the sample plot are obtained as soil property data; Based on the corresponding soil property data, a spatial distribution map of each soil property is obtained by kriging interpolation, and converted into a spatial grid map of corresponding resolution; After establishing a corresponding membership function model based on the soil property data, standardization processing is performed to obtain dimensionless soil property data; Based on the importance of each dimensionless soil property data to the sample plot, the AHP hierarchical analysis method is used to obtain the corresponding indicator weight; The conditional index distribution map is obtained by performing calculations based on the spatial grid map of each soil property and the corresponding index weights.

4. The method for evaluating the health of mangrove ecosystems based on species level according to claim 3 is characterized in that: The method for obtaining the vitality index distribution map is: Based on the sample plot, a plurality of standard sample plots are obtained, and a predetermined number of standard sample plots are randomly selected for field investigation to obtain the wood density and corresponding diameter at breast height of all mangrove tree species; Obtaining the aboveground biomass of the corresponding species of mangrove based on the wood density and the corresponding breast height diameter; Constructing a random forest model based on all of the aboveground biomass combined with spectral parameters of remote sensing images; The aboveground biomass spatial distribution map is obtained based on the random forest model inversion as the vitality index distribution map.

5. The method for evaluating the health of mangrove ecosystems based on species level according to claim 4 is characterized in that: The method for obtaining the organizational strength index distribution map is: Based on the plant community characteristics of the sample plot, a moving window method is used to obtain a variety of landscape pattern index distribution maps; The landscape pattern index distribution maps include: Shannon diversity index distribution map SHDI, Shannon evenness index distribution map SHEI, patch cohesion index distribution map COHESION, landscape aggregation index distribution map CONTAG, landscape shape index distribution map LSI and perimeter-area fractal dimension index distribution map PAFRAC; Based on the importance of each landscape pattern index distribution map to the sample plot, the AHP hierarchical analysis method is used to obtain the corresponding index weight; The organizational strength index distribution map is obtained based on each of the landscape pattern index distribution maps and the corresponding indicator weights.

6. The method for evaluating the health of mangrove ecosystems based on species level according to claim 5 is characterized in that: The organizational strength index distribution diagram O is:

7. The method for evaluating the health of mangrove ecosystems based on species level according to claim 6 is characterized in that: The method for obtaining the elasticity index distribution map is: Converting the land use distribution map based on the sample plot into a raster layer; Based on the grid layer and the weighted calculation according to different land use types, a resilience coefficient distribution map Resil and a resistance coefficient distribution map Resist of the sample plot are obtained; Obtaining a distribution map of soil heavy metal content in the sample plot; Obtaining an average single pollution index of each heavy metal based on the soil heavy metal content distribution map; Obtaining a comprehensive pollution index based on the average single pollution index; Obtaining the comprehensive pollution index distribution map INPI based on the comprehensive pollution index; The elasticity index distribution map is obtained by calculating according to corresponding weights based on the restoration coefficient distribution map, the resistance coefficient distribution map and the comprehensive pollution index distribution map.

8. The method for evaluating the health of mangrove ecosystems based on species level according to claim 7 is characterized in that: The elasticity index distribution diagram R is specifically: R=0.7×(0.7×Resil+0.3×Resist)+0.3×INPI.

9. The method for evaluating the health of mangrove ecosystems based on species level according to claim 8 is characterized in that: The ecological health index distribution map EHI is specifically as follows: EHI=0.25×C+0.25×V+0.25×O+0.25×R; The health status includes five ecological health levels: very weak (0-0.2), weak (0.2-0.4), moderate (0.4-0.6), strong (0.6-0.8) and very strong (0.8-1.0).

10. A mangrove ecosystem health assessment system based on species level, applied to a mangrove ecosystem health assessment method based on species level as claimed in any one of claims 1 to 9, characterized in that: include: A first distribution map acquisition module, a second distribution map acquisition module, a third distribution map acquisition module, a fourth distribution map acquisition module, a fifth distribution map acquisition module, a layer overlay analysis module, and a result output module; The first distribution map acquisition module is used to select mangroves in the study area as sample plots and obtain a mangrove species distribution grid map of the sample plots; The second distribution map acquisition module is used to obtain a condition index distribution map based on the soil physical and chemical properties of the sample plot; The third distribution map acquisition module is used to acquire the aboveground biomass spatial distribution map of the sample plot as the vitality index distribution map based on the plant biomass of the sample plot; The fourth distribution map acquisition module is used to acquire multiple landscape pattern index distribution maps based on the plant distribution pattern of the sample plot and calculate the organizational index distribution map based on the corresponding weights; The fifth distribution map acquisition module is used to acquire a resistance index distribution map and a resilience index distribution map based on the landscape pattern of the sample plot, and calculate an elasticity index distribution map in combination with the comprehensive pollution index distribution map; The layer overlay analysis module is used to calculate the ecological health index distribution map based on the condition index distribution map, the vitality index distribution map, the organizational force index distribution map and the elasticity index distribution map; The result output module is used to obtain the health status and spatial distribution of different mangrove plants in the sample site based on the overlay analysis of the ecological health index distribution map and the mangrove species distribution grid map.

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