Method and system for mangrove ecological network construction based on habitat constraints and composite resistance surface

Abstract

The application discloses a mangrove ecological network construction method and system based on habitat constraints and a composite resistance surface, and the method comprises the following steps: identifying core ecological source areas and general ecological source areas based on attribute indexes and connectivity indexes of candidate ecological source areas of mangrove habitats, and identifying stepping stone source areas based on the connectivity contribution and habitat proximity relationship of the remaining candidate ecological source areas; constructing a land-sea composite ecological resistance surface based on a coastal substrate, tidal hydrology, a shoreline engineering barrier and human activity interference; constructing an ecological connection constraint domain based on spatial distribution characteristics and habitat exclusion zones of mangrove habitats, setting an area outside the constraint domain as an impassable area, and applying the ecological connection constraint domain to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface; and extracting an ecological network based on the core, general and stepping stone source areas and the constraint-type ecological resistance surface. The application improves the integrity and spatial rationality of mangrove ecological network identification in a sea-land interlaced habitat.

Description

Technical Field

[0001] This invention relates to the field of ecological protection and spatial planning technology, and in particular to a method and system for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces. Background Technology

[0002] In coastal ecological protection and land spatial governance, ecological network construction is an important technical means to identify key ecological spaces and enhance ecosystem connectivity. Existing ecological network construction methods are mostly based on landscape ecology theory, achieving this by identifying ecological source areas, constructing ecological resistance surfaces, and extracting ecological corridors. However, when these methods are directly applied to mangrove habitats, which have significant land-sea transition characteristics, they often suffer from insufficient adaptability. On the one hand, existing source area identification methods rely heavily on patch area or single ecological quality indicators, easily overlooking small patches that play a crucial role in propagation or local habitat connection, resulting in an incomplete network node system. On the other hand, traditional resistance surface construction mainly considers factors such as terrestrial land use, topography, and human activities, making it difficult to characterize the unique ecological process constraints of the land-sea transition, such as tidal hydrology, intertidal continuity, and shoreline engineering barriers, leading to a mismatch between resistance values ​​and actual habitat conditions. Furthermore, existing corridor extraction algorithms typically search for the minimum cost path across the entire area, lacking spatial constraints on the shoreline distribution and nearshore hydrological dependence characteristics of mangrove habitats. This can easily generate unreasonable paths that lack ecological connectivity, such as those traversing built-up areas, hard shorelines, or deep-water areas offshore, reducing the guiding value of the identification results in conservation and restoration practices. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a method and system for constructing mangrove ecological networks based on habitat constraints and composite resistance surfaces, which realizes accurate identification and spatial optimization of mangrove habitat ecological networks.

[0004] This invention provides a method for constructing a mangrove ecological network based on habitat constraints and a composite resistance surface, the method comprising: Based on the attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological sources of mangrove habitats, core ecological sources and general ecological sources are identified, and stepping stone sources are identified based on the connectivity contribution and habitat proximity of the remaining candidate ecological sources. Based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—a land-sea composite ecological resistance surface is constructed. Based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, an ecological connection constraint domain is constructed. The area outside the ecological connection constraint domain is set as an impassable area. The ecological connection constraint domain is applied to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface. An ecological network is extracted based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface.

[0005] Furthermore, the attribute indicators include patch area, core area ratio, and habitat quality, and the connectivity indicators include structural connectivity index and probabilistic connectivity index; The attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological source areas based on mangrove habitats are used to identify core ecological source areas and general ecological source areas, including: Based on the patch area, the core area ratio, the habitat quality, and the comprehensive connectivity index, the source area importance index of each candidate ecological source area is calculated; Based on the comparison result between the source area importance index and the first preset classification threshold, the core ecological source area is identified; Based on the comparison result between the source importance index and the second preset classification threshold, the general ecological source is identified.

[0006] Furthermore, the identification of stepping stone sources based on the connectivity contribution and habitat proximity of the remaining candidate ecological source sites includes: Determine the ranking of connectivity contributions of the remaining candidate ecological source areas; When the connectivity contribution ranking of the remaining candidate ecological source is within the preset ranking threshold and meets at least one of the spatial proximity or hydrological proximity conditions with the core ecological source or general ecological source, the corresponding remaining candidate ecological source is determined as the stepping stone source.

[0007] Furthermore, the construction of a land-sea composite ecological resistance surface based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—includes: The following parameters were constructed: coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance. The coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance are standardized and weighted to generate the land-sea composite ecological resistance surface.

[0008] Furthermore, the coastal matrix resistance is assigned a value based on the terrestrial and coastal wetland matrix or marine matrix to which the grid cell belongs; The tidal hydrological resistance is constructed based on the spatial proximity of the intertidal zone and the frequency of flooding. The shoreline engineering barrier resistance is constructed based on shoreline type and engineering impact zone; The resistance to human activity interference is graded and assigned values ​​based on the intensity index of human activity interference.

[0009] Furthermore, the construction methods for the shoreline engineering barrier resistance include: The shoreline data is converted into a linear barrier grid with the same spatial resolution as the land-sea composite ecological resistance surface, and the preset width is extended to both sides of the shoreline to form an engineering impact zone. According to the shoreline type, the linear barrier grid and the grid cells within the engineering influence zone are assigned barrier resistance values, wherein the shoreline engineering barrier resistance only acts on the shoreline and its engineering influence zone. The shoreline types include at least one of the following: natural shoreline, semi-natural shoreline, ecological restoration shoreline, artificial shoreline, hard revetment, port and wharf shoreline, industrial shoreline, and reclaimed shoreline. Natural coastlines are assigned low barrier resistance values, semi-natural coastlines and ecologically restored coastlines are assigned medium barrier resistance values, artificial coastlines are assigned high barrier resistance values, hard revetments are assigned high barrier resistance values, and port and wharf coastlines, industrial coastlines and reclaimed coastlines are assigned the highest barrier resistance values.

[0010] Furthermore, the construction of an ecological connectivity constraint domain based on the spatial distribution characteristics of the mangrove habitat and habitat exclusion zones, setting areas outside the ecological connectivity constraint domain as impassable areas, and applying the ecological connectivity constraint domain to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface includes: The initial constraint domain is obtained by spatially merging the habitat patch neighborhood buffer zone, intertidal zone and coastal wetland space, and nearshore hydrological background neighborhood of the mangrove habitat. The habitat exclusion zone is removed from the initial constraint domain to obtain the ecological connectivity constraint domain; The region within the ecological connection constraint domain retains the resistance value of the land-sea composite ecological resistance surface, while the region outside the ecological connection constraint domain is assigned a preset maximum resistance value, thus generating the constraint-type ecological resistance surface.

[0011] Furthermore, the habitat exclusion zone includes at least one of the following: terrestrial space lacking hydrological connection with the coastal zone and intertidal zone, continuous high-density urban construction areas, large port terminals, port-adjacent industrial areas, offshore deep-water areas, and deep-water channels. The extraction of the ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface includes: Using the core ecological source area, the general ecological source area and the stepping stone source area as network nodes, and the constrained ecological resistance surface as the cost surface, the minimum cost path model is used to extract the ecological corridor skeleton. The constrained ecological resistance surface is converted into an electrical conductivity surface, and the cumulative current density of each grid cell is calculated using a circuit theory model. Based on the accumulated current density and local resistance distribution, ecological pinch points and ecological barrier points are identified. The ecological pinch point is the region where the cumulative current density ranking is within a preset pinch point threshold and there is no alternative channel, and the ecological obstacle point is the space where the local resistance is higher than the preset obstacle threshold and forms a bypassing or contraction effect on current diffusion.

[0012] Furthermore, the method is executed based on acquired multi-source spatial data, which includes at least one of mangrove habitat spatial distribution data, coastal wetland type data, land use data, intertidal zone spatial distribution data, shoreline type data, nearshore water system data, nighttime light data, point of interest data, and ecological environment quality data.

[0013] This invention also provides a mangrove ecological network construction system based on habitat constraints and composite resistance surfaces. This system is used to implement the aforementioned mangrove ecological network construction method based on habitat constraints and composite resistance surfaces. The mangrove ecological network construction system includes: An ecological source area identification module is used to identify core ecological source areas and general ecological source areas based on the attribute indicators and connectivity indicators of each candidate ecological source area in the candidate ecological source area set of mangrove habitats, and to identify stepping stone source areas based on the connectivity contribution and habitat proximity relationship of the remaining candidate ecological source areas. A composite resistance surface construction module is used to construct a land-sea composite ecological resistance surface based on four resistance factors: coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity interference. A constrained ecological resistance surface generation module is used to construct an ecological connection constraint domain based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, set the area outside the ecological connection constraint domain as an impassable area, and apply the ecological connection constraint domain to the land-sea composite ecological resistance surface to generate a constrained ecological resistance surface. An ecological network extraction module is used to extract an ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface.

[0014] This invention provides a method and system for constructing mangrove ecological networks based on habitat constraints and composite resistance surfaces. It identifies core and general ecological sources through a primary screening mechanism using attribute and connectivity indicators of candidate ecological sources within a set of candidate ecological sources in mangrove habitats. A secondary screening mechanism based on connectivity contribution and habitat proximity identifies stepping stone sources. This overcomes the shortcomings of traditional methods that rely solely on area or quality indicators, leading to the omission of small, critical patches, and improves the integrity and hierarchical rationality of the ecological source system. By integrating coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbances to construct a terrestrial-sea composite ecological resistance surface, it solves the problem that a single terrestrial factor cannot accurately characterize the constraints of ecological processes in the transitional marine-terrestrial habitat, enhancing the ecological explanatory power of the resistance surface. By constructing an ecological connectivity constraint domain and setting areas outside the domain as impassable, it spatially constrains the path search logic, effectively preventing ecological corridors from traversing built-up areas or deep-water areas off the coast—non-habitat spaces—significantly improving the spatial rationality of mangrove ecological network identification results and the directionality of protection and restoration practices. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces in Embodiment 1 of the present invention; Figure 2 This is a system architecture diagram of mangrove ecological network construction based on habitat constraints and composite resistance surfaces in Embodiment 2 of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In this invention, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, portions or combinations thereof disclosed in this specification, and are not intended to exclude the possibility that one or more other features, figures, steps, behaviors, components, portions or combinations thereof are present or added.

[0019] It should also be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] Example 1 Embodiment 1 of the present invention provides a method for constructing a mangrove ecological network based on habitat constraints and a composite resistance surface, the method comprising: Based on the attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological sources of mangrove habitats, core ecological sources and general ecological sources are identified, and stepping stone sources are identified based on the connectivity contribution and habitat proximity of the remaining candidate ecological sources. Based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—a land-sea composite ecological resistance surface is constructed. Based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, an ecological connection constraint domain is constructed. The area outside the ecological connection constraint domain is set as an impassable area. The ecological connection constraint domain is applied to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface. An ecological network is extracted based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface.

[0021] Specifically, such as Figure 1 As shown, Figure 1 The flowchart of the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces in Embodiment 1 of the present invention is shown, including the following steps: S101. Identify core ecological sources and general ecological sources based on the attribute indicators and connectivity indicators of each candidate ecological source in the set of candidate ecological sources of mangrove habitats, and identify stepping stone sources based on the connectivity contribution and habitat proximity of the remaining candidate ecological sources. In one optional implementation of this embodiment, the candidate ecological source area set typically consists of pre-processed and verified existing habitat patches. To avoid missing key small patches based solely on area or a single quality indicator, this step employs a dual identification mechanism. First, core ecological source areas and general ecological source areas are selected using attributes such as patch area, internal structural stability, and comprehensive connectivity, serving as the main framework of the ecological network. Second, for remaining candidate nodes that do not meet the classification criteria for core and general ecological source areas, they are not directly eliminated. Instead, their connectivity is further evaluated, and stepping stone source areas are identified by combining their spatial proximity to core or general ecological source areas with their proximity to hydrological spaces such as estuaries, tidal channels, and tidal waterways. Due to their spatial location, connectivity, or hydrological conditions, they can serve as relay links or local habitat connections between core ecological sources and general ecological sources. This approach ensures that even in areas with high habitat fragmentation, small patches that serve as relays for propagation or local habitat connections can be included in the network system, thereby improving the completeness and hierarchical rationality of ecological source identification.

[0022] Furthermore, the attribute indicators include patch area, core area ratio, and habitat quality, and the connectivity indicators include structural connectivity index and probabilistic connectivity index; The attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological source areas based on mangrove habitats are used to identify core ecological source areas and general ecological source areas, including: Based on the patch area, the core area ratio, the habitat quality, and the comprehensive connectivity index, the source area importance index of each candidate ecological source area is calculated; Based on the comparison result between the source area importance index and the first preset classification threshold, the core ecological source area is identified; Based on the comparison result between the source importance index and the second preset classification threshold, the general ecological source is identified.

[0023] Specifically, in the calculation process, the Source Area Importance Index (MSI) model is first constructed. In this embodiment, mangrove patches are used as foreground pixels, and non-mangrove areas are used as background pixels. The Morphological Spatial Pattern Analysis (MSPA) method is used to extract the core area inside the mangrove patches.

[0024] Among them, the Internal core proportion of each patch The calculation formula is:

[0025] In the formula, For the first The proportion of the core area of ​​each patch This represents the area of ​​the core region within the patch. This represents the total area of ​​the plaque. This indicator reflects the degree to which the plaque is affected by edge effects. The larger the value, the higher the proportion of the core habitat within the patch, the less the patch is affected by the edge effect, and the more stable the ecosystem structure.

[0026] Secondly, calculate the structural connectivity index of the patches. The calculation formula is:

[0027] In the formula, and The first The and the first The area or ecological weight of a mangrove patch plaque With plaque The shortest topological connection between them. The total area of ​​the study region is represented by n, and the number of candidate mangrove patches is represented by n. This index focuses on characterizing the physical connectivity of the landscape; a higher value indicates that the patch plays a stronger role in maintaining the integrity of the overall landscape structure.

[0028] Simultaneously, the probabilistic connectivity index of the patches is calculated. The calculation formula is:

[0029] In the formula, plaque With plaque The maximum probability of connection between them. Unlike structural connectivity, probabilistic connectivity takes into account the uncertainties in species dispersal or ecological flow transport, and is more reflective of the actual connectivity potential of ecological processes.

[0030] Based on this, the structural connectivity index and probability connectivity index Normalization was performed separately to construct the first... Comprehensive connectivity index of mangrove patches The calculation formula is:

[0031] In the formula, For the first The comprehensive connectivity index of individual mangrove patches; These are combination coefficients, with values ​​ranging from 0 to 1. This is the normalized value of the structural connectivity index. This is the normalized value of the probability connectivity index. It is calculated using the combination coefficients. Adjustments can balance the weight of structural and functional connections in the evaluation system.

[0032] Finally, the above indicators are normalized and then weighted and summed to obtain the mangrove source area importance index. The calculation formula is:

[0033] In the formula, For the first Normalized area values ​​of each patch. This represents the normalized value of the core region proportion of the plaque. This represents the normalized value for patch habitat quality. This represents the normalized value of the patch connectivity index. , , and The corresponding indicator weights.

[0034] Furthermore, the weights of the indicators can be determined using expert weighting, analytic hierarchy process (AHP), entropy weighting, combined weighting, or data-driven methods. In this embodiment, , , and The weighting of the core area proportion was appropriately increased by setting the weights to 0.25, 0.30, 0.25 and 0.20 respectively, which emphasizes the importance of habitat quality while maintaining the basic contributions of area and connectivity, thus avoiding a single indicator dominating the evaluation results.

[0035] In an optional implementation of this embodiment, the source importance index of each mangrove patch is obtained. Subsequently, based on the numerical distribution characteristics of MSI and the functional differences of different patches in the mangrove ecological network, candidate mangrove patches were classified and core ecological source areas, general ecological source areas, and stepping stone source area nodes were identified.

[0036] Specifically, based on the number, size differences, spatial fragmentation, and statistical distribution of MSI in mangrove patches within the study area, a first-level threshold T1 and a second-level threshold T2 are determined to classify core ecological source areas, general ecological source areas, and remaining candidate ecological source areas, where T1 > T2. The thresholds should not be fixed values ​​but should be dynamically generated based on the statistical distribution characteristics of MSI within the study area, and can be determined using methods such as quantile methods, natural breakpoint methods, and standard deviation classification methods.

[0037] The core ecological source area refers to mangrove patches with high comprehensive importance, a large proportion of internal core habitats, good habitat quality and good connectivity, and serves as the main node of the ecological network. Mangrove patches with a source importance index MSI not lower than the first classification threshold T1 are identified as core ecological source areas (MSI≥T1), which are used as the main nodes in the mangrove ecological network.

[0038] The general ecological source area refers to mangrove patches that have a certain scale, habitat quality and connectivity function, but whose comprehensive importance is lower than that of the core ecological source area, and serves as the secondary node of the ecological network. Mangrove patches with a source importance index MSI lower than the first classification threshold T1 and not lower than the second classification threshold T2 are identified as general ecological source areas (T2≤MSI<T1), which are used as the secondary nodes in the mangrove ecological network.

[0039] Finally, mangrove patches with a source importance index MSI lower than the second classification threshold T2 are provisionally designated as remaining candidate ecological source areas for secondary screening.

[0040] Further, the identifying stepping stone source areas based on the connectivity contribution and habitat proximity relationship of the remaining candidate ecological source areas includes: Determine the connectivity contribution ranking of the remaining candidate ecological source areas; When the connectivity contribution ranking of the remaining candidate ecological source areas is within the preset ranking threshold, and at least one of the spatial proximity condition or the hydrological proximity condition with the core ecological source area or the general ecological source area is satisfied, the corresponding remaining candidate ecological source area is determined as the stepping stone source area.

[0041] Specifically, the original intention of designing this secondary screening mechanism is to solve the problem that traditional methods only rely on comprehensive importance evaluation, which leads to the omission of key small patches. In the sea-land ecotone habitat, although some patches are small in area or low in habitat quality score, resulting in a low comprehensive importance index, they are often located in key positions between estuaries, tidal creeks or large patches, and undertake irreplaceable functions of propagule diffusion relay or local habitat connection. If they are directly eliminated according to the comprehensive importance threshold, structural fractures will occur in the ecological network. Therefore, this embodiment introduces the dual judgment logic of "connectivity contribution ranking + spatial / hydrological proximity". Among them, the connectivity contribution ranking is used to initially screen out candidates from the remaining nodes that still have high connection potential in the network topology structure, to ensure that the selected nodes have basic functional attributes; and the spatial proximity condition or hydrological proximity condition further verifies whether there is a real physical connection or hydraulic connection channel between the node and the core ecological source area, so as to avoid the wrong selection of invalid nodes that are only due to falsely high topological indicators but actually geographically isolated. Through this double check, not only the small relay nodes with important ecological functions are retained, but also the ecological rationality of the identification results is guaranteed.

[0042] Further, for the remaining mangrove patches whose source importance index is lower than the second classification threshold T2 (MSI<T2), they are not directly eliminated, but further subjected to stepping stone source determination. A stepping stone source refers to a mangrove patch with relatively low comprehensive patch importance, which can play a role in relay connection or local habitat connection between core ecological sources and general ecological sources due to its spatial location, connectivity or hydrological connection conditions. The stepping stone source shall meet the patch connectivity condition, and at least one of the spatial proximity condition or the tidal hydrological connection condition, specifically including: a) The mangrove patch has high connectivity, and its patch connectivity index Ci ranks in the top 60% of the remaining candidate patches; b) The shortest spatial distance between the mangrove patch and the adjacent core ecological source or general ecological source is not greater than the preset source proximity distance threshold; c) The shortest spatial distance between the mangrove patch and the estuary, tidal creek, tidal channel, intertidal zone or coastal wetland is not greater than the preset hydrological proximity distance threshold.

[0043] When a candidate mangrove patch satisfies condition a) and at least one of condition b) or condition c), it is determined as a stepping stone source. The proximity distance threshold can be determined by the average nearest neighbor distance of the candidate patches.

[0044] Through the above processing, a multi-level mangrove ecological source system is formed, with core ecological sources as the main body, general ecological sources as the supplement, and stepping stone sources as the relay.

[0045] S102. Construct a land-sea composite ecological resistance surface based on four resistance factors: coastal matrix, tidal hydrology, shoreline engineering barrier and human activity disturbance; In an optional implementation of this embodiment, since the ecological process of the land-sea ecotone is jointly affected by the dual environments of land and ocean, a single land use resistance factor on land is difficult to accurately characterize the actual cost of species diffusion or ecological flow operation. Therefore, this step introduces four dimensions of resistance evaluation factors. Among them, the coastal matrix resistance reflects the difference in basic suitability of different surface cover types for ecological processes; the tidal hydrological resistance describes the limiting effect of water exchange conditions such as tidal flooding frequency and intertidal zone proximity on habitat connection; the shoreline engineering barrier resistance quantifies the truncation effect of artificial structures such as hard shorelines and port facilities on ecological flow; the human activity disturbance resistance comprehensively characterizes the degree of human activity disturbance reflected by nighttime light intensity and point of interest density. Through standardized processing and weighted superposition of these four types of factors, the generated land-sea composite ecological resistance surface can more truly reflect the diffusion resistance distribution pattern of mangrove habitats in the land-sea ecotone space.

[0046] Furthermore, the construction of a land-sea composite ecological resistance surface based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—includes: The following parameters were constructed: coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance. The coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance are standardized and weighted to generate the land-sea composite ecological resistance surface.

[0047] Specifically, this embodiment constructs a land-sea composite ecological resistance surface that simultaneously considers coastal matrix, intertidal tidal hydrological conditions, shoreline engineering barriers, and human activity disturbances. This resistance surface is used to characterize the relative degree of obstruction by different spatial units to the potential spread of mangrove propagules, ecological connectivity between patches, and restoration and expansion processes. This construction system breaks through the limitations of traditional methods that rely solely on terrestrial land use factors. Addressing the unique environmental heterogeneity of the land-sea transition zone, it establishes a four-dimensional evaluation framework encompassing substrate suitability, water exchange conditions, physical barrier effects, and the intensity of anthropogenic stress, thereby significantly improving the accuracy and objectivity of the resistance surface in characterizing mangrove habitat ecological processes.

[0048] In an optional implementation of this embodiment, the land-sea composite ecological resistance surface The calculation formula is:

[0049] In the formula, This represents the combined land-sea ecological resistance value. For coastal matrix resistance, For tidal hydrological resistance, Obstacles to shoreline engineering Obstacles to human activities , , and These are the corresponding resistance weights. In a preferred embodiment, considering that the coastal matrix is ​​the basic carrier for species survival and dispersal, its weights are... Set to 0.50; tidal hydrological conditions are a key limiting factor distinguishing marine-terrestrial transitional habitats from purely terrestrial habitats, with a weight of 0.50. Set to 0.20; shoreline engineering barriers have a strong local blocking effect but their spatial coverage is relatively limited, weight Set to 0.10; human activity disturbance is used as the background stress factor, with a weight of Set to 0.20. All resistance factors must be normalized to a value range of 1-100 before being superimposed, where 1 represents the lowest relative resistance and 100 represents the highest relative resistance.

[0050] Furthermore, for coastal matrix resistance, values ​​are assigned based on the terrestrial and coastal wetland or marine matrix to which the grid cell belongs, where the first... Coastal matrix resistance per grid cell The calculation formula is:

[0051] In the formula, The coastal matrix resistance of the i-th grid cell, For the matrix resistance of terrestrial and coastal wetlands, Let L represent the marine matrix resistance, L be the set of terrestrial and coastal wetland matrix, and M be the set of marine matrix. This marine-terrestrial dichotomy assignment strategy fully considers the differentiated dependence of mangrove habitats on different matrices in the marine-terrestrial transition zone.

[0052] Furthermore, Table 1 below presents an optimal matrix resistance assignment scheme for mangrove habitats and its ecological implications: Table 1

[0053] For terrestrial and coastal wetland substrates, the basic resistance is determined based on land use or land cover type and coastal wetland type. Mangroves are assigned the lowest resistance, with a resistance value of 1. Natural coastal wetlands, including tidal flats, mudflats, salt marshes, and other natural or semi-natural wetland spaces closely related to mangrove expansion or ecological connectivity, are assigned resistance values ​​of 5-10. Artificial wetlands, including aquaculture ponds, reclaimed fishponds, reclaimed wetlands, and general water bodies, possess some restoration potential but are currently affected by human intervention, are assigned a resistance value of 20-30. Farmland, grasslands, shrubs, bare land, and other spaces with weaker connections to mangrove ecological processes but not entirely hardened are assigned a resistance value of 65-85. Construction land, roads, ports, impermeable surfaces, and other artificially hardened spaces are assigned high resistance, with a resistance value of 100.

[0054] For marine matrix, based on its proximity to the shoreline and intertidal zone, it is divided into estuarine tidal channels and nearshore shallow water space, general nearshore waters, and offshore deep water space. Estuarine tidal channels and nearshore shallow water space refers to the waters located within 100 meters of the shoreline in estuaries and tidal channels. This space has a relatively direct hydrological connection with mangroves, the intertidal zone, or the shoreline, which is conducive to the potential dispersal of propagules with tidal currents, thus imparting low resistance, with a value of 10-20. General nearshore waters refer to marine spaces located more than 100 meters but less than 300 meters from the shoreline. This space is still within the nearshore influence range, but its direct connection with mangrove patches and the intertidal zone is relatively weak, imparting moderate resistance (resistance value 30-60). The offshore or deep-water area refers to the sea area that is more than 300 meters away from the nearest coastline. This type of water is far from mangrove patches, intertidal zone and coastline, and is usually not the main spatial range of mangrove coastal spread and nearshore ecological connection, and is therefore subject to high resistance (resistance value 85-100).

[0055] Furthermore, for tidal hydrological resistance, a model is constructed based on intertidal spatial proximity and flooding frequency, where the first... Tidal hydrological resistance of each grid cell The calculation formula is:

[0056] In the formula, For the first Tidal hydrological resistance of each grid cell, For resistance based on the spatial proximity of the intertidal zone, For flood frequency-based drag, Norm indicates that the calculated results are normalized to a drag value range of 1-100.

[0057] Among them, the intertidal space adjacent resistance Calculated using a continuous distance attenuation function:

[0058] In the formula, For the first The distance from each grid unit to the nearest intertidal space. This refers to the distance attenuation parameter. It has a clear physical meaning, and its value is usually determined by the average width of the intertidal zone within the study area, reflecting the rate at which the influence of tidal hydrology decreases with distance. A larger value indicates a wider hydrological radiation range in the intertidal zone, and areas far from the intertidal zone can still maintain a lower resistance growth; conversely, a smaller value indicates that the hydrological influence is limited to a narrow nearshore area.

[0059] When the grid is located inside the intertidal zone ( =0), the resistance takes a minimum of 1; as the distance increases, the resistance increases exponentially and approaches 100.

[0060] In addition, flooding frequency As a correction term, the calculation formula is:

[0061] In the formula, For the first The flooding frequency of each grid cell, This represents the number of times the raster cell is identified as a water body in multi-temporal remote sensing imagery. This represents the number of valid observations for this grid cell.

[0062] Based on the characteristic that mangroves are generally suitable for distribution in periodically flooded spaces but not for long-term dry or deep-water spaces, the flooding frequency is converted into flooding frequency resistance. The hierarchical values ​​are assigned as shown in Table 2 below: Table 2

[0063] Resistance based on flooding frequency Following the principle of non-linear grading: long-term dry dew zone ( <0.10) and long-term flooded areas ( ≥0.90) imparts high resistance of 80-100; periodically flooded areas (0.30≤ The design assigns low drag of 5-15 to areas with a drag coefficient of <0.70; while medium drag is assigned to areas with low and high frequency flooding. This design precisely characterizes the ecological requirement of mangrove habitats for "moderate flooding," avoiding the misjudgment of long-term flooded or long-term arid areas as suitable passageways.

[0064] Furthermore, regarding shoreline engineering barriers, construction methods are based on shoreline type and the engineering impact zone, including: The shoreline data is converted into a linear barrier grid with the same spatial resolution as the land-sea composite ecological resistance surface, and the preset width is extended to both sides of the shoreline to form an engineering impact zone. The linear barrier grid and the grid cells within the engineering influence zone are assigned barrier resistance values ​​according to the shoreline type, wherein the shoreline engineering barrier resistance acts only on the shoreline and its engineering influence zone.

[0065] Specifically, the preset width setting should take into account the actual disturbance range of the engineering facilities to the surrounding hydrological environment and biological behavior. For example, in a specific application scenario, the grid width can be extended to both sides by one grid width (such as 30m) to simulate the engineering impact zone.

[0066] Furthermore, the shoreline type includes at least one of the following: natural shoreline, semi-natural shoreline, ecological restoration shoreline, artificial shoreline, hard revetment, port and wharf shoreline, industrial shoreline, and reclaimed shoreline. Natural coastlines are assigned low barrier resistance values, semi-natural coastlines and ecologically restored coastlines are assigned medium barrier resistance values, artificial coastlines are assigned high barrier resistance values, hard revetments are assigned high barrier resistance values, and port and wharf coastlines, industrial coastlines and reclaimed coastlines are assigned the highest barrier resistance values.

[0067] Specifically, different types of shorelines reflect varying degrees of artificial modification and ecological barrier effects, with the following resistance classifications: natural shorelines (such as mangrove shorelines and muddy shorelines) are assigned low barrier resistance values ​​of 1-5; semi-natural shorelines and ecologically restored shorelines are assigned medium barrier resistance values ​​of 15-30; artificial shorelines (such as aquaculture dikes) are assigned high barrier resistance values ​​of 45-65; rigid revetments (such as concrete embankments) are assigned high barrier resistance values ​​of 70-90; and port and wharf shorelines, industrial shorelines, and reclaimed shorelines are assigned the highest barrier resistance values ​​of 90-100. This mechanism, by transforming linear shorelines into area-like influence zones and refining their classification, effectively addresses the problem in traditional methods where shoreline barrier effects are simplified to a single line or ignored, truly reflecting the interception and compression effects of artificial shorelines on ecological flows.

[0068] Furthermore, for resistance to human activity interference, a tiered value is assigned based on the human activity interference intensity index, where the human activity interference intensity index... The calculation formula is:

[0069] In the formula, For the first The intensity of human activity interference in each grid cell. To normalize nighttime light intensity, This is to normalize the density of points of interest. Nighttime light data can macroscopically reflect regional energy consumption and urbanization levels, while point-of-interest data can finely depict the spatial agglomeration of specific human activity facilities such as commerce, transportation, and industry. Combining the two can comprehensively characterize the spatiotemporal distribution of non-rigid anthropogenic disturbances.

[0070] More based on The resistance rating is assigned using a five-level classification system: low human activity disturbance area, <0.20, assign a value of 10-20; for areas with low human activity interference, 0.20≤ <0.40, assign a value of 20-40; in the area of ​​moderate human activity disturbance, 0.40≤ <0.60, assign a value of 40-65; in areas with higher human activity interference, 0.60≤ <0.80, assign a value of 65-85; high human activity interference area. ≥0.80, assigned a value of 85-100. This classification system ensures that the gradual negative impacts of human activities on ecological processes are quantitatively expressed, rather than a simple binary opposition.

[0071] It should be noted that, through the synergistic quantification and weighted fusion of the above four dimensions, the land-sea composite ecological resistance surface constructed in this embodiment not only covers the environmental constraints unique to the land-sea transition zone, but each element also possesses a clear physical or ecological meaning and a standardized calculation method. This highly structured resistance evaluation system, on the one hand, enhances the reproducibility and horizontal comparability of the technical solution across different research areas, and on the other hand, provides a high-precision cost basis for the subsequent delineation of ecological connectivity constraint domains and network extraction, fundamentally overcoming the technical shortcomings of traditional single-terrestrial resistance surfaces in representing distortions in land-sea transition habitats.

[0072] S103. Based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, construct an ecological connection constraint domain, set the area outside the ecological connection constraint domain as an impassable area, and apply the ecological connection constraint domain to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface. In one optional implementation of this embodiment, this is a key step that distinguishes this application from existing technologies. In traditional methods, path search is often conducted across the entire domain, easily generating false corridors that traverse built-up areas or deep-water areas far from the shore, which do not conform to ecological principles. To solve this problem, this step first merges the habitat patch neighborhood, intertidal wetland space, and nearshore hydrological associated areas into an initial feasible domain based on the shoreline distribution characteristics of mangrove habitats. Then, habitat exclusion zones lacking ecological restoration potential, such as high-density urban construction areas and deep-water channels, are removed, resulting in a precise ecological connectivity constraint domain. Subsequently, all grid cells outside this constraint domain are forcibly assigned a maximum resistance value or marked as impassable, retaining only the original composite resistance value within the constraint domain. Through this spatial masking mechanism, the search range of subsequent network extraction algorithms is limited from the source, ensuring that the generated ecological corridors always lie within a reasonable space that meets the survival and dispersal conditions of mangrove habitats.

[0073] Furthermore, the construction of an ecological connectivity constraint domain based on the spatial distribution characteristics of the mangrove habitat and habitat exclusion zones, setting areas outside the ecological connectivity constraint domain as impassable areas, and applying the ecological connectivity constraint domain to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface includes: The initial constraint domain is obtained by spatially merging the habitat patch neighborhood buffer zone, intertidal zone and coastal wetland space, and nearshore hydrological background neighborhood of the mangrove habitat. The habitat exclusion zone is removed from the initial constraint domain to obtain the ecological connectivity constraint domain; The region within the ecological connection constraint domain retains the resistance value of the land-sea composite ecological resistance surface, while the region outside the ecological connection constraint domain is assigned a preset maximum resistance value, thus generating the constraint-type ecological resistance surface.

[0074] Specifically, the construction of the ecological connectivity constraint domain adopts Boolean operation logic, and the calculation formula is as follows:

[0075] In the formula, This serves as a constraint zone for mangrove ecological connectivity. As a buffer zone for mangrove patches, It is an intertidal zone and coastal wetland space. The nearshore hydrological context includes natural shorelines, estuaries, tidal channels, tidal channels, or nearshore shallow water buffer zones. This is a rigid exclusion region.

[0076] More importantly, this formula embodies the idea of ​​combining "positive suitability space superposition" with "negative repulsion space elimination." Among them, Based on the existing habitat patch boundaries, the buffer distance is extended outward to include potential spaces that may be naturally expanded or artificially restored in the surrounding area. The buffer distance can be set according to the research scale, for example, 20-200m at the local scale. It encompasses basic habitat spaces such as intertidal zone, tidal flats, and salt marshes, and forms the foundation of ecological connectivity; This is constructed based on natural shorelines, estuaries, tidal channels, or nearshore shallow water spaces, aiming to incorporate channel spaces with tidal hydrological connections, with buffer distances of, for example, 50-200 meters. The union of these three constitutes the initial potential connectivity space. However, simply superimposing them may still include areas lacking ecological functions; therefore, rigid exclusion zones must be removed. Habitat exclusion zones include at least one of the following: terrestrial spaces lacking hydrological connection to the coastal and intertidal zones; continuous high-density urban development areas; large port terminals; port-adjacent industrial areas; offshore deep-water areas; and deep-water channels. This subtraction method effectively isolates geographically proximate areas that are completely isolated in ecological function, ensuring the confined area... It is a collection of pure spaces with the potential for genuine ecological connectivity.

[0077] Furthermore, after obtaining the ecological connectivity constraint domain, it needs to be applied to the aforementioned land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface. The calculation formula is as follows:

[0078] In the formula, For grid cells The constrained ecological resistance value, This represents the land-sea combined ecological resistance value for the corresponding grid cell. This serves as a constraint zone for mangrove ecological connectivity. Indicates a unit that is impassable.

[0079] Furthermore, for grids within the constraint domain, their original composite resistance values ​​are retained to reflect subtle differences in habitat quality; for grids outside the constraint domain, preset maximum resistance values ​​are assigned. In practice, This value is typically set to a value that approaches infinity within the limits of computer computation. This assignment strategy mathematically constructs an absolute barrier, preventing subsequent minimum-cost path algorithms or circuit theory models from traversing these regions during the search process, thus fundamentally eliminating the generation of false corridors.

[0080] Furthermore, the habitat exclusion zone includes at least one of the following: terrestrial space lacking hydrological connection with the coastal zone and intertidal zone, continuous high-density urban construction areas, large port terminals, port-adjacent industrial areas, offshore deep-water areas, and deep-water channels.

[0081] S104. Based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface, extract the ecological network.

[0082] In an optional implementation of this embodiment, after completing the node system construction and resistance surface constraint processing, this step uses the identified core ecological source areas, general ecological source areas, and stepping stone source areas as network nodes, and the constrained ecological resistance surface as the cost basis. A minimum cost path model or circuit theory model is used to calculate the potential connection channels between nodes. Since the search space is strictly limited to the ecological connection constraint domain, the extracted ecological corridors not only satisfy the mathematical optimal solution of minimizing cumulative resistance, but also conform to the ecological law that mangrove habitats depend on the intertidal zone and are distributed along the coastline. The final output ecological network can be further used to identify key ecological pinch points and obstacle points, providing a scientific basis for the precise implementation of ecological protection and restoration projects.

[0083] Furthermore, the extraction of the ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface includes: Using the core ecological source area, the general ecological source area and the stepping stone source area as network nodes, and the constrained ecological resistance surface as the cost surface, the minimum cost path model is used to extract the ecological corridor skeleton. The constrained ecological resistance surface is converted into an electrical conductivity surface, and the cumulative current density of each grid cell is calculated using a circuit theory model. Based on the accumulated current density and local resistance distribution, ecological pinch points and ecological barrier points are identified. The ecological pinch point is the region where the cumulative current density ranking is within a preset pinch point threshold and there is no alternative channel, and the ecological obstacle point is the space where the local resistance is higher than the preset obstacle threshold and forms a bypassing or contraction effect on current diffusion.

[0084] Specifically, the process of extracting the ecological network based on core ecological source areas, general ecological source areas, stepping stone source areas, and constrained ecological resistance surfaces includes two complementary stages. The first stage uses core ecological source areas, general ecological source areas, and stepping stone source areas as network nodes, and constrained ecological resistance surfaces as cost surfaces, employing a minimum-cost path model to extract the ecological corridor framework. The formula for calculating the minimum cumulative resistance is:

[0085] In the formula, For ecological source area S i With S j The minimum cumulative resistance value between them This represents the distance traveled when the path passes through the kth grid cell. denoted as the constrained ecological resistance value of the k-th grid cell, where n is the number of grid cells traversed by the path.

[0086] It should be noted that, since the search space has been... With strict constraints, the path calculated by this model not only satisfies the mathematical optimality of minimizing cumulative resistance, but also necessarily lies within a space that meets the survival conditions of mangrove habitats, avoiding the fallacy of paths detouring or crossing the deep sea in traditional methods.

[0087] Furthermore, the second stage involves converting the constrained ecological resistance surface into an electrically conductive surface and using a circuit theory model to calculate the cumulative current density of each grid cell in order to identify key connectivity points.

[0088] Specifically, the first step is to perform conductivity conversion, calculated using the following formula:

[0089] In the formula, Let be the conductance of the grid cell (x, y). This represents the constrained ecological resistance value for the corresponding grid cell.

[0090] Subsequently, the diffusion process of ecological flow between nodes was simulated, and the first... Cumulative current density of each grid cell The calculation formula is:

[0091] In the formula, For the first The cumulative current density of each grid cell ( , ) For the source region, the connection between s and t is through the first... The current value of each grid cell. The cumulative current density reflects the frequency and intensity of a spatial cell's use in all potential connection paths. Compared to a single minimum cost path, it can more comprehensively characterize the redundancy and vulnerability of the ecological network.

[0092] Furthermore, based on cumulative current density and local resistance distribution, ecological pinch points and ecological obstacle points can be further identified. Ecological pinch points are areas where the cumulative current density ranks within a preset pinch point threshold and lacks alternative pathways. In a preferred embodiment, the preset pinch point threshold can be set to the top 30%, i.e., selecting the top 30% of areas with the highest current density as key pinch points. These areas are often the converging choke points of ecological flows; damage to them will lead to a sharp decline in network connectivity, thus making them priority areas for protection. Ecological obstacle points are spaces where local resistance exceeds a preset obstacle threshold and creates a bypassing or contraction effect on current diffusion. Although these areas are located within the constrained domain, poor local environmental conditions or human interference restrict the smooth passage of ecological flows. Identifying these obstacle points can provide precise target locations for ecological restoration projects, such as reducing local resistance through measures like reforestation of ponds and removal of hard revetments, thereby improving the overall network connectivity efficiency.

[0093] In an optional implementation of this embodiment, the method is executed based on acquired multi-source spatial data, which includes at least one of mangrove habitat spatial distribution data, coastal wetland type data, land use data, intertidal zone spatial distribution data, shoreline type data, nearshore water system data, nighttime light data, point of interest data, and ecological environment quality data.

[0094] Specifically, these data constitute the necessary input prerequisites for constructing a multi-level ecological source system, quantifying the land-sea composite resistance surface, and delineating ecological connectivity constraint domains.

[0095] Furthermore, to ensure that multi-source heterogeneous data can be processed under a unified spatiotemporal reference, the acquired raw data needs to be standardized and preprocessed. The preprocessing process mainly includes projection transformation, spatial registration, resolution resampling, vector to raster conversion, outlier removal, and spatial range clipping. First, all data are unified to the same projection coordinate system to avoid spatial position offsets caused by inconsistencies in coordinate systems. Second, a unified spatial resolution is determined according to the research scale, and resampling is performed. For continuous variables such as elevation, slope, light index, and ecological quality index, bilinear interpolation or cubic convolution methods are used for resampling to maintain the gradual change characteristics of the values; for categorical variables such as land use type, wetland type, and shoreline type, the nearest neighbor method is used for resampling to prevent category distortion caused by mixed pixels. Third, special outlier processing is performed on the mangrove habitat spatial distribution data. Only false patches confirmed to be caused by classification errors or noise are removed, while real small mangrove habitat patches are strictly preserved, because these small patches are the key objects for identifying the stepping stone source areas in the aforementioned embodiments. Finally, all layers are cropped according to the boundaries of the study area to ensure that each data layer is fully aligned in space.

[0096] In summary, Embodiment 1 of this invention provides a method for constructing a mangrove ecological network based on habitat constraints and a composite resistance surface. It identifies core and general ecological sources through a primary screening mechanism using attribute and connectivity indicators of candidate ecological sources within a set of candidate ecological sources in mangrove habitats. A secondary screening mechanism based on connectivity contribution and habitat proximity identifies stepping stone sources. This overcomes the shortcomings of traditional methods that rely solely on area or quality indicators, leading to the omission of small, critical patches, and improves the integrity and hierarchical rationality of the ecological source system. By integrating coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbances to construct a terrestrial-sea composite ecological resistance surface, it solves the problem that a single terrestrial factor cannot accurately characterize the constraints of ecological processes in the transitional marine-terrestrial habitat, enhancing the ecological explanatory power of the resistance surface. By constructing an ecological connectivity constraint domain and setting areas outside the domain as impassable, it spatially constrains the path search logic, effectively preventing ecological corridors from traversing built-up areas or deep-water areas off the coast—non-habitat spaces—significantly improving the spatial rationality of the mangrove ecological network identification results and the directionality of protection and restoration practices.

[0097] Example 2 Embodiment 2 of the present invention provides a mangrove ecological network construction system based on habitat constraints and composite resistance surfaces. The mangrove ecological network construction system based on habitat constraints and composite resistance surfaces is used to implement the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces described in Embodiment 1. The system includes an ecological source area identification module, a composite resistance surface construction module, a constraint-type ecological resistance surface generation module, and an ecological network extraction module.

[0098] In one optional implementation of this embodiment, such as Figure 2 As shown, Figure 2 The diagram shows the system architecture of the mangrove ecological network construction based on habitat constraints and composite resistance surfaces in Embodiment 2 of the present invention, which includes the following modules: Ecological source area identification module 10 is used to identify core ecological source areas and general ecological source areas based on the attribute indicators and connectivity indicators of each candidate ecological source area in the candidate ecological source area set of mangrove habitats, and to identify stepping stone source areas based on the connectivity contribution and habitat proximity relationship of the remaining candidate ecological source areas. The composite resistance surface construction module 20 is used to construct a land-sea composite ecological resistance surface based on four resistance factors: coastal matrix, tidal hydrology, shoreline engineering barriers and human activity interference. A constrained ecological resistance surface generation module 30 is used to construct an ecological connection constraint domain based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, set the area outside the ecological connection constraint domain as an impassable area, and apply the ecological connection constraint domain to the land-sea composite ecological resistance surface to generate a constrained ecological resistance surface. Ecological network extraction module 40 is used to extract the ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area and the constrained ecological resistance surface.

[0099] In summary, Embodiment 2 of this invention provides a mangrove ecological network construction system based on habitat constraints and composite resistance surfaces. This system implements the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces described in Embodiment 1. It identifies core and general ecological sources through a primary screening mechanism using attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological sources in mangrove habitats. A secondary screening mechanism based on connectivity contribution and habitat proximity identifies stepping stone sources. This overcomes the shortcomings of traditional methods that rely solely on area or quality indicators, leading to the omission of small, critical patches, and improves ecological... The integrity and hierarchical rationality of the source area system; by integrating coastal matrix, tidal hydrology, shoreline engineering barriers and human activity interference to construct a land-sea composite ecological resistance surface, the problem that a single terrestrial factor cannot accurately characterize the constraints of ecological processes in the marine-terrestrial transitional habitat is solved, and the ecological explanatory power of the resistance surface is enhanced; by constructing an ecological connectivity constraint domain and setting the area outside the domain as impassable, the path search logic is constrained in terms of spatial scope, effectively avoiding ecological corridors from crossing non-habitat spaces such as built-up areas or deep-water areas on the far shore, and significantly improving the spatial rationality of mangrove ecological network identification results and the orientation of protection and restoration practices.

[0100] Example 3 To more clearly verify the effectiveness and practicality of the technical solution of this application, the following description uses a mangrove ecosystem in a nature reserve in my country as a specific application scenario for mangrove habitats. It should be understood that this application scenario is merely an exemplary verification of the technical solution of this application and is not a limitation on the scope of protection of this application. Other mangrove habitat areas with similar marine-terrestrial transitional characteristics can be implemented by referring to the parameter configuration and processing logic of this embodiment.

[0101] In this application scenario, the study area covers a typical estuarine and intertidal complex habitat. The spatial resolution of the multi-source spatial data is uniformly set to 30m, and the projected coordinate system adopts WGS84 UTM 49N to meet the accuracy requirements for ecological network construction at the local scale. Based on the method flow described in the aforementioned Example 1, the following steps were executed sequentially: S101 multi-level ecological source area identification, S102 construction of land-sea composite ecological resistance surface, S103 delineation of ecological connectivity constraint domains, and S104 extraction of constraint-type ecological networks.

[0102] In the S101 multi-level ecological source area identification stage, a multi-level ecological source area system was identified from the verified existing mangrove patches within the study area by substituting the source area importance index (MSI) calculation formula and a secondary screening mechanism. A total of 77 ecological source areas were ultimately identified. Among them, there were 10 core ecological source areas, mainly including large, contiguous habitats with complete internal structures such as the Futian Mangrove Nature Reserve and the Mai Po Nature Reserve; 43 general ecological source areas, mostly medium-sized patches distributed along the coast; and 24 stepping stone source areas. Although these nodes did not meet the core or general standards in terms of area or overall quality, they were successfully retained due to their location in key positions such as estuaries, tidal channels, or between large patches, based on a dual judgment of connectivity contribution ranking and spatial / hydrological proximity conditions. This result directly verifies that the secondary screening mechanism based on connectivity and habitat proximity in this application can effectively avoid the omission of key small patches and significantly improve the integrity of the ecological source area system.

[0103] In the S102-S103 resistance surface construction stage, a land-sea composite ecological resistance surface and a constrained ecological resistance surface were generated respectively. The land-sea composite ecological resistance surface without spatial constraints exhibits high-resistance areas widely distributed in urban built-up areas and offshore waters; while the constrained ecological resistance surface is formed by superimposing ecological connectivity constraint domains. Comparison shows that the constrained resistance surface forcibly sets habitat exclusion zones such as land lacking hydrological connections, high-density built-up areas, port terminals, and offshore deep-water areas as impassable areas, thus precisely shrinking the effective computational space to a narrow, elongated strip region that conforms to the coastal distribution and tidal dependence characteristics of mangroves. This spatial masking mechanism eliminates the possibility of subsequent path search algorithms performing invalid calculations in non-habitat spaces from the outset.

[0104] In the S104 ecological network extraction phase, based on the aforementioned 77 ecological source areas and constrained ecological resistance surfaces, a combination of minimum cost path model and circuit theory model was used to identify 105 ecological corridors with a total length of approximately 22.47 km. Simultaneously, 21 key ecological choke points and 26 ecological barrier points were identified. The extracted ecological corridor framework closely follows the distribution of coastlines, tidal channels, and estuarine wetlands. All connecting paths are located within the ecological connectivity constraint domain, completely avoiding the ecologically unhealthy phenomena common in traditional methods, such as corridors crossing built-up areas or deep-water channels. Among these, the 21 ecological choke points are mainly distributed at the confluence of tidal channels and in narrow connecting areas between protected areas, serving as crucial points for maintaining network connectivity; the 26 ecological barrier points are mostly located around artificial shorelines or aquaculture ponds, indicating priority targets for future ecological restoration.

[0105] The verification results from the above application scenarios demonstrate that the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces provided in this application can accurately identify multi-level ecological source systems and construct a resistance evaluation base that conforms to actual ecological processes when dealing with mangrove habitats with significant land-sea transition attributes. Furthermore, the spatial constraint mechanism ensures the ecological rationality of the network identification results. Compared to traditional methods without constraints, the ecological network generated by this scheme not only mathematically satisfies optimal connectivity but also realistically reflects the diffusion and connection patterns of mangrove habitats in physical space, providing a spatial decision-making basis with high practical guiding value for coastal ecological protection and restoration projects.

[0106] The foregoing has provided a detailed description of a method and system for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces provided by the present invention. Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0107] Furthermore, the embodiments of the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces, characterized in that, The method includes: Based on the attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological sources of mangrove habitats, core ecological sources and general ecological sources are identified, and stepping stone sources are identified based on the connectivity contribution and habitat proximity of the remaining candidate ecological sources. Based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—a land-sea composite ecological resistance surface is constructed. Based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, an ecological connection constraint domain is constructed. The area outside the ecological connection constraint domain is set as an impassable area. The ecological connection constraint domain is applied to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface. An ecological network is extracted based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface.

2. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 1, characterized in that, The attribute indicators include patch area, core area ratio, and habitat quality; the connectivity indicators include structural connectivity index and probabilistic connectivity index. The attribute and connectivity indicators of each candidate ecological source in the set of candidate ecological source areas based on mangrove habitats are used to identify core ecological source areas and general ecological source areas, including: Based on the patch area, the core area ratio, the habitat quality, and the comprehensive connectivity index, the source area importance index of each candidate ecological source area is calculated; Based on the comparison result between the source area importance index and the first preset classification threshold, the core ecological source area is identified; Based on the comparison result between the source importance index and the second preset classification threshold, the general ecological source is identified.

3. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 2, characterized in that, The identification of stepping stone sources based on the connectivity contribution and habitat proximity of remaining candidate ecological sources includes: Determine the ranking of connectivity contributions of the remaining candidate ecological source areas; When the connectivity contribution ranking of the remaining candidate ecological source is within the preset ranking threshold and meets at least one of the spatial proximity or hydrological proximity conditions with the core ecological source or general ecological source, the corresponding remaining candidate ecological source is determined as the stepping stone source.

4. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 1, characterized in that, The land-sea composite ecological resistance surface, constructed based on four resistance factors—coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity disturbance—includes the following: The following parameters were constructed: coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance. The coastal matrix resistance, tidal hydrological resistance, shoreline engineering barrier resistance, and human activity disturbance resistance are standardized and weighted to generate the land-sea composite ecological resistance surface.

5. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 4, characterized in that, The coastal matrix resistance is assigned a value based on the terrestrial and coastal wetland matrix or marine matrix to which the grid cell belongs; The tidal hydrological resistance is constructed based on the spatial proximity of the intertidal zone and the frequency of flooding. The shoreline engineering barrier resistance is constructed based on shoreline type and engineering impact zone; The resistance to human activity interference is graded and assigned values ​​based on the intensity index of human activity interference.

6. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 5, characterized in that, The methods for constructing shoreline engineering barriers include: The shoreline data is converted into a linear barrier grid with the same spatial resolution as the land-sea composite ecological resistance surface, and the preset width is extended to both sides of the shoreline to form an engineering impact zone. According to the shoreline type, the linear barrier grid and the grid cells within the engineering influence zone are assigned barrier resistance values, wherein the shoreline engineering barrier resistance only acts on the shoreline and its engineering influence zone. The shoreline types include at least one of the following: natural shoreline, semi-natural shoreline, ecological restoration shoreline, artificial shoreline, hard revetment, port and wharf shoreline, industrial shoreline, and reclaimed shoreline. Natural coastlines are assigned low barrier resistance values, semi-natural coastlines and ecologically restored coastlines are assigned medium barrier resistance values, artificial coastlines are assigned high barrier resistance values, hard revetments are assigned high barrier resistance values, and port and wharf coastlines, industrial coastlines and reclaimed coastlines are assigned the highest barrier resistance values.

7. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 1, characterized in that, The step of constructing an ecological connectivity constraint domain based on the spatial distribution characteristics of the mangrove habitat and habitat exclusion zones, setting areas outside the ecological connectivity constraint domain as impassable areas, and applying the ecological connectivity constraint domain to the land-sea composite ecological resistance surface to generate a constraint-type ecological resistance surface includes: The initial constraint domain is obtained by spatially merging the habitat patch neighborhood buffer zone, intertidal zone and coastal wetland space, and nearshore hydrological background neighborhood of the mangrove habitat. The habitat exclusion zone is removed from the initial constraint domain to obtain the ecological connectivity constraint domain; The region within the ecological connection constraint domain retains the resistance value of the land-sea composite ecological resistance surface, while the region outside the ecological connection constraint domain is assigned a preset maximum resistance value, thus generating the constraint-type ecological resistance surface.

8. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 7, characterized in that, The habitat exclusion zone includes at least one of the following: terrestrial space lacking hydrological connection with the coastal zone and intertidal zone, continuous high-density urban construction areas, large port terminals, port-adjacent industrial areas, offshore deep-water areas, and deep-water channels. The extraction of the ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface includes: Using the core ecological source area, the general ecological source area and the stepping stone source area as network nodes, and the constrained ecological resistance surface as the cost surface, the minimum cost path model is used to extract the ecological corridor skeleton. The constrained ecological resistance surface is converted into an electrical conductivity surface, and the cumulative current density of each grid cell is calculated using a circuit theory model. Based on the accumulated current density and local resistance distribution, ecological pinch points and ecological barrier points are identified. The ecological pinch point is the region where the cumulative current density ranking is within a preset pinch point threshold and there is no alternative channel, and the ecological obstacle point is the space where the local resistance is higher than the preset obstacle threshold and forms a bypassing or contraction effect on current diffusion.

9. The method for constructing a mangrove ecological network based on habitat constraints and composite resistance surfaces as described in claim 1, characterized in that, The method is executed based on acquired multi-source spatial data, which includes at least one of mangrove habitat spatial distribution data, coastal wetland type data, land use data, intertidal zone spatial distribution data, shoreline type data, nearshore water system data, nighttime light data, point of interest data, and ecological environment quality data.

10. A mangrove ecological network construction system based on habitat constraints and composite resistance surfaces, wherein the mangrove ecological network construction system based on habitat constraints and composite resistance surfaces is used to implement the mangrove ecological network construction method based on habitat constraints and composite resistance surfaces as described in any one of claims 1-9, characterized in that, The mangrove ecological network construction system based on habitat constraints and composite resistance surfaces includes: An ecological source area identification module is used to identify core ecological source areas and general ecological source areas based on the attribute indicators and connectivity indicators of each candidate ecological source area in the candidate ecological source area set of mangrove habitats, and to identify stepping stone source areas based on the connectivity contribution and habitat proximity relationship of the remaining candidate ecological source areas. A composite resistance surface construction module is used to construct a land-sea composite ecological resistance surface based on four resistance factors: coastal matrix, tidal hydrology, shoreline engineering barriers, and human activity interference. A constrained ecological resistance surface generation module is used to construct an ecological connection constraint domain based on the spatial distribution characteristics of the mangrove habitat and the habitat exclusion zone, set the area outside the ecological connection constraint domain as an impassable area, and apply the ecological connection constraint domain to the land-sea composite ecological resistance surface to generate a constrained ecological resistance surface. An ecological network extraction module is used to extract an ecological network based on the core ecological source area, the general ecological source area, the stepping stone source area, and the constrained ecological resistance surface.

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