An ecosystem service threshold effect identification method

Abstract

The present application relates to the technical field of ecosystem service, and more particularly to a method for identifying threshold effect of ecosystem service. The method comprises the following steps: dividing the research area into grids, calculating the ecosystem service index value of the basic spatial unit, and selecting the main variable of the driving factor of the basic spatial unit; clustering the basic spatial unit into ecological hierarchical units, introducing a local adaptive bandwidth control mechanism, locally fitting the mutation relationship between the normalized ecosystem service index value and the normalized driving factor main variable, and obtaining the ecosystem service threshold of the ecological hierarchical unit; constructing the ecosystem service threshold dataset of the basic spatial unit, calculating the response offset factor of the basic spatial unit, and spatially correcting the ecosystem service threshold of the basic spatial unit. The method solves the problems of insufficient spatial heterogeneity processing, rigid bandwidth setting, local abnormal interference sensitivity and poor spatial consistency of the traditional method for identifying threshold effect of ecosystem service.

Description

Technical Field

[0001] This invention relates to the field of ecosystem service technology, and in particular to a method for identifying the threshold effect of ecosystem services. Background Technology

[0002] The ecosystem service threshold effect refers to the phenomenon where ecosystem service functions abruptly change when driving factors (such as land use intensity, normalized difference vegetation index, and human activity intensity index) reach a certain critical value. Accurately identifying ecosystem service thresholds is crucial for understanding ecosystem response mechanisms, implementing ecological environment zoning management, and formulating differentiated regulation strategies.

[0003] Currently, some studies have begun to focus on the threshold response phenomenon in ecosystem services and have attempted to model the abrupt relationship between driving factors and ecosystem services using piecewise linear and regression discontinuity models. However, traditional methods generally have the following shortcomings: (1) Insufficient handling of spatial heterogeneity: Ecosystems have complex spatial structures and significant ecological differences between different regions. Traditional threshold identification methods often fail to take into account spatial stratification features, resulting in insufficient model fitting ability and low threshold identification accuracy; (2) Rigid bandwidth setting: Fixed bandwidth or regression modeling without distinguishing regions is prone to misidentification or overfitting; (3) Sensitivity to local anomaly interference: In practical applications, local basic spatial units may have abnormal driving factor values ​​or observation errors, which can easily lead to local threshold shifts and affect the accuracy of the overall identification results; (4) Poor spatial consistency: Ecological thresholds have a certain degree of spatial continuity, but existing methods lack spatial regularization mechanisms, making it difficult to ensure a smooth transition of threshold changes between neighboring regions, resulting in a "break" phenomenon in the identification results.

[0004] Therefore, there is an urgent need to provide a new method for identifying the threshold effect of ecosystem services to solve the above problems. Summary of the Invention

[0005] This invention provides a method for identifying the threshold effect of ecosystem services, in order to solve the technical problems of insufficient spatial heterogeneity handling, rigid bandwidth setting, sensitivity to local anomalies, and poor spatial consistency in traditional methods for identifying the threshold effect of ecosystem services.

[0006] An ecosystem service threshold effect identification method of the present invention includes the following steps:

[0007] S1. Divide the study area into basic spatial units, calculate the ecosystem service index values ​​of the basic spatial units, and select the driving factor main variables of the basic spatial units; normalize the ecosystem service index values ​​and driving factor main variables of the basic spatial units to obtain normalized ecosystem service index values ​​and normalized driving factor main variables; cluster the basic spatial units into ecological stratification units, adopt a regression discontinuity model, and introduce a local adaptive bandwidth control mechanism to locally fit the mutation relationship between the normalized ecosystem service index values ​​and normalized driving factor main variables to obtain the ecosystem service threshold of the ecological stratification units.

[0008] S2. Based on the ecosystem service threshold of the ecological stratification unit, construct the ecosystem service threshold dataset of the basic spatial unit and calculate the response offset factor of the basic spatial unit; based on the response offset factor of the basic spatial unit, introduce a spatial neighborhood collaborative correction mechanism driven by response offset to spatially correct the ecosystem service threshold of the basic spatial unit and obtain the corrected ecosystem service correction threshold.

[0009] Preferably, S1 specifically includes:

[0010] Ecosystem service driving factors are introduced, and the explanatory power of these factors on ecosystem service index values ​​is calculated. Based on the explanatory power, the main variables of the driving factors for basic spatial units are determined.

[0011] Preferably, S1 specifically includes:

[0012] In the implementation of the local adaptive bandwidth control mechanism, the fitting performance of the discontinuity regression model under different bandwidths is evaluated, and the Bayesian information standard score is obtained.

[0013] Preferably, S1 specifically includes:

[0014] In the implementation of the local adaptive bandwidth control mechanism, a spatial regularization smoothing term is introduced by combining the Bayesian information standard score value to construct a bandwidth collaborative optimization objective function; the spatial regularization smoothing term is obtained by calculating the bandwidth changes between adjacent ecological stratification units.

[0015] Preferably, S1 specifically includes:

[0016] The optimal bandwidth for the ecological stratification unit is obtained by minimizing the bandwidth co-optimization objective function; the optimal bandwidth is then re-inputted into the regression discontinuity model as a control parameter to obtain the ecosystem service threshold of the ecological stratification unit.

[0017] Preferably, S2 specifically includes:

[0018] Based on the normalized driving factor main variables of the basic spatial unit and the ecosystem service threshold of the ecological stratification unit to which the basic spatial unit belongs, an ecosystem service threshold dataset of the basic spatial unit is constructed.

[0019] Preferably, S2 specifically includes:

[0020] Based on the ecosystem service threshold dataset of basic spatial units, the adjacency weight of basic spatial units is introduced, the squared fitting residual of the basic spatial unit and the squared fitting residual of the adjacent basic spatial units are calculated, and the response offset factor of the basic spatial unit is obtained.

[0021] Preferably, S2 specifically includes:

[0022] In the implementation of a response offset-driven spatial neighborhood collaborative correction mechanism, the corrected ecosystem service correction threshold is calculated based on the response offset factor of the basic spatial unit, combined with the current ecosystem service threshold of the basic spatial unit and the ecosystem service threshold of the neighborhood.

[0023] The beneficial effects of the technical solution of the present invention are:

[0024] This invention introduces a local adaptive bandwidth control mechanism, which can ensure good fitting performance of the regression model at breakpoints within each ecological stratification unit, while controlling the bandwidth differences between spatially adjacent ecological stratification units, effectively improving the spatial stability and regional consistency of ecosystem service threshold identification results.

[0025] This invention proposes a spatial neighborhood collaborative correction mechanism driven by response offset. By fusing response offset factors and spatial neighborhood information, it effectively suppresses the spatial boundary abruptness of ecosystem service threshold identification results, and realizes continuous modeling and high-precision spatial identification of ecosystem service thresholds. Attached Figure Description

[0026] Figure 1 This is a flowchart of an ecosystem service threshold effect identification method according to the present invention. Detailed Implementation

[0027] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. 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.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0029] The following description, in conjunction with the accompanying drawings, details the specific scheme of the ecosystem service threshold effect identification method provided by this invention.

[0030] See attached document Figure 1 The diagram illustrates a flowchart of an ecosystem service threshold effect identification method according to an embodiment of the present invention, which includes the following steps:

[0031] S1. Divide the study area into basic spatial units, calculate the ecosystem service index values ​​of the basic spatial units, and select the driving factor main variables of the basic spatial units; normalize the ecosystem service index values ​​and driving factor main variables of the basic spatial units to obtain normalized ecosystem service index values ​​and normalized driving factor main variables; cluster the basic spatial units into ecological stratification units, adopt a regression discontinuity model, and introduce a local adaptive bandwidth control mechanism to locally fit the mutation relationship between the normalized ecosystem service index values ​​and normalized driving factor main variables to obtain the ecosystem service threshold of the ecological stratification units.

[0032] The study area was divided into grids according to a fixed spatial resolution (e.g., 1km × 1km) to obtain... The first basic spatial unit, denoted as the... The basic spatial unit is ,in This represents the index of the basic spatial unit; based on ecosystem service functions, such as provisioning services, regulating services, and cultural services, the basic spatial unit is calculated using existing ecosystem service assessment models. Ecosystem service index value For example, for the supply service function, the basic spatial unit is calculated using the existing InVEST model. The water yield; based on ecosystem service driving factors, such as human activity intensity index, normalized vegetation index, land use intensity, population density, and transportation distance, a set of candidate variables for driving factors is constructed, which are obtained through existing ecosystem research; for basic spatial units Ecosystem service index values ​​obtained under any one ecosystem service function are used to calculate basic spatial units using existing geographic detector methods. The impact of each ecosystem service driver on the ecosystem service index value Explanatory power, i.e. Value, select the one with the largest Value-driven ecosystem service drivers as basic spatial units Driving factor main variables ; for basic spatial units Driving factor main variables and ecosystem service index values The normalization process was performed using the min-max standardization method to obtain the normalized driving factor main variables. and normalized ecosystem service index values Based on the normalized driving factor main variables and normalized ecosystem service index values ​​of the basic spatial units, the existing K-means clustering method is used to divide the basic spatial units into... The first ecological stratification unit, denoted as the... Each ecological stratification unit is ,in , representing the ecological hierarchical unit index; the ecological hierarchical unit It consists of a set of basic spatial units The spatial subsets formed possess ecological homogeneity;

[0033] In each ecological stratification unit Internally, based on ecological hierarchical units A point-level sample set was constructed using normalized driving factor main variables and normalized ecosystem service index values ​​for all basic spatial units. Existing regression discontinuity models were used to locally fit the abrupt change relationships between the normalized driving factor main variables and normalized ecosystem index values. Finally, the ecological stratification units were obtained by minimizing the sum of squared residuals. The ecosystem service threshold is defined as the critical point at which ecosystem service drivers cause abrupt changes in ecosystem services. Specifically, to coordinate the local fitting accuracy and spatial consistency of the regression model for the breakpoints of each ecological stratification unit, a local adaptive bandwidth control mechanism is introduced, using existing Bayesian information standards to control different bandwidths. The fitting performance of the regression discontinuity model was evaluated to obtain the Bayesian information standard score. Simultaneously, to control the smoothness of bandwidth changes between spatially adjacent ecological stratification units, a spatial regularization smoothing term was introduced, and a bandwidth co-optimization objective function was constructed, as shown in the following formula:

[0034]

[0035] in, This represents the objective function for bandwidth co-optimization. This represents the ecological hierarchical unit index. The number of ecological stratification units; Indicates the first Ecological stratification unit The bandwidth is used to control the local fitting range of the regression discontinuity model. A candidate set of bandwidths is set based on the ecosystem service threshold identification requirements, such as... ; The Bayesian Information Criterion score is used to measure the bandwidth performance of a regression discontinuity model. The smaller the value, the better the fit of the regression discontinuity model. This represents the sum of the Bayesian information standard scores for the study area; This is a spatial regularization smoothing term used to penalize the bandwidth difference between adjacent ecological strata in space. The smaller the value, the closer the bandwidth between adjacent ecological strata in space, and the smoother the spatial transition. , is the regularization smoothing coefficient, which is obtained by tuning using the existing cross-validation method; Indicates the relationship with the first Ecological stratification unit A set of indexes for spatially adjacent ecological stratification units. , indicating ecological stratification unit Spatially adjacent ecological stratification units The index is used to determine whether they are adjacent based on the existing Queen adjacency rules; This is a bandwidth difference penalty term used to limit the magnitude of bandwidth changes between adjacent ecological stratification units, ensuring the smoothness of spatial transition. The smaller the value, the better the spatial continuity. Representing ecological stratification units and The normalized bandwidth, which is obtained by analyzing the ecological stratification units. bandwidth and ecological stratification units bandwidth The results were obtained by performing min-max standardization separately.

[0036] The above formula introduces a local adaptive bandwidth control mechanism, which can ensure good fitting performance of the regression model at breakpoints within each ecological stratification unit, while controlling the bandwidth difference between spatially adjacent ecological stratification units, effectively improving the spatial stability and regional consistency of the ecosystem service threshold identification results.

[0037] By minimizing bandwidth, the objective function is co-optimized. To obtain ecological stratification units Optimal bandwidth ; Optimal bandwidth As control parameters, they are re-inputted into the regression discontinuity model to obtain ecological stratification units. Ecosystem service threshold ;

[0038] S2. Based on the ecosystem service threshold of the ecological stratification unit, construct the ecosystem service threshold dataset of the basic spatial unit and calculate the response offset factor of the basic spatial unit; based on the response offset factor of the basic spatial unit, introduce a spatial neighborhood collaborative correction mechanism driven by response offset to spatially correct the ecosystem service threshold of the basic spatial unit and obtain the corrected ecosystem service correction threshold.

[0039] To further improve the spatial accuracy of ecosystem service threshold identification results, an ecosystem service threshold dataset for basic spatial units is constructed based on the ecosystem service threshold of ecological hierarchical units. ,in, Represents the basic spatial unit Normalized driving factor main variables , represents the basic spatial unit index, , representing the basic spatial unit Ecological stratification unit The ecosystem service threshold below, This represents the ecological hierarchical unit index. It is a basic spatial unit mapping function used to map basic spatial units to their respective ecological hierarchical units;

[0040] To mitigate the interference of local anomalies in basic spatial units on the ecosystem service threshold identification results, a fitting residual abnormality metric function is constructed. The response offset factor of the basic spatial unit is obtained by calculating the weighted average of the deviations between the squared fitting residuals of the basic spatial unit and the squared fitting residuals of its adjacent basic spatial units. The formula is as follows:

[0041]

[0042] in, Basic space unit The response offset factor is used to measure the basic spatial unit. The deviation between the fitting residuals of the model and the fitting residuals of adjacent basic spatial units, wherein the fitting residuals are obtained by subtracting the normalized driving factor main variables from the ecosystem service threshold. This explains the basic spatial unit. The squared residual value of the fitted area is significantly higher than that of the squared residual value of the neighborhood area, indicating that the basic spatial unit There may be abnormal driving factors causing interference; the basic spatial unit should be reduced during the correction process. The impact of the ecosystem service threshold on the ecosystem service correction threshold. This explains the basic spatial unit. The squared residual value of the fitted sample is significantly lower than that of the squared residual value of the neighborhood sample, indicating that there may be abnormal driving factors in the neighborhood. The influence of the neighborhood needs to be reduced during the correction process. This indicates that the squared residuals of the two models are essentially the same, and no significant correction is needed. These are tolerance thresholds set by professional technicians, with a range of values ​​ranging from [value missing]. ; Representation and basic spatial unit The set of indexes of directly adjacent basic spatial units, i.e. the set of neighborhood indexes, is used to determine whether they are adjacent by the existing Queen adjacency rules; , in order to be related to the basic spatial unit Adjacent basic spatial unit index; as the basic space unit and Adjacency weights, based on basic spatial units and The coordinates are calculated using the inverse distance weighting method; the closer the spatial distance, the greater the adjacency weight. as the basic space unit The square of the fitting residuals between the normalized driving factor main variables and the ecosystem service threshold; Represents the basic spatial unit The normalized residuals between the driving factor main variables and the ecosystem service threshold are used to reflect how far the current ecosystem service status of the basic spatial unit is from the abrupt change threshold and in which direction it is moving away. A value of 0 indicates that the basic spatial unit It is in a critical state of sudden change. If the value is negative, it indicates that the basic spatial unit is in a critical state of sudden change. The critical point for mutation has not yet been reached. If the value is positive, it indicates that the basic spatial unit has not yet been reached. It has exceeded the mutation threshold and is in a post-mutation state; , Representing the basic spatial units Basic spatial unit The normalized driving factor main variables; , Representing the basic spatial units Basic spatial unit Ecosystem service threshold;

[0043] To improve the spatial stability and consistency of ecosystem service threshold identification results and avoid threshold shifts caused by anomalies in local basic spatial units, a spatial neighborhood collaborative correction mechanism driven by response shift is proposed. This mechanism uses a response shift factor to control the weighted average of the ecosystem service threshold of the current basic spatial unit and its neighboring ecosystem service thresholds, spatially correcting the ecosystem service threshold of the basic spatial unit to obtain the corrected ecosystem service threshold. The formula is as follows:

[0044]

[0045] in, Basic space unit Revised ecosystem service correction threshold; Represents the basic spatial unit Ecosystem service threshold; , as the current basic spatial unit The retention weighting coefficient of the ecosystem service threshold, when hour, At this point, reduce the basic space unit The impact of the ecosystem service threshold on the ecosystem service correction threshold enhances the neighborhood correction effect when hour, At this time, the basic spatial unit is enhanced. The impact of the ecosystem service threshold on the ecosystem service correction threshold reduces the neighborhood correction effect when hour, At this time, the basic space unit Ecosystem service threshold Weighted average of its neighboring ecosystem service thresholds The retention weights are basically balanced; The response offset sensitivity coefficient is obtained through cross-validation. Basic space unit Response offset factor; Represents the basic spatial unit In the neighborhood, all adjacent basic spatial units The weighted average of the ecosystem service thresholds; Represents the basic spatial unit The number of adjacent basic spatial units in the neighborhood; Represents the basic spatial unit The set of neighborhood indexes; , in order to be related to the basic spatial unit Adjacent basic spatial unit index; Basic space unit Adjacent basic space unit The adjacency weight; Represents the basic spatial unit Ecosystem service threshold;

[0046] The above formula proposes a spatial neighborhood collaborative correction mechanism driven by response offset. By fusing response offset factor and spatial neighborhood information, it effectively suppresses the spatial boundary abruptness of ecosystem service threshold identification results, and realizes continuous modeling and high-precision spatial identification of ecosystem service threshold.

[0047] In summary, a method for identifying the threshold effect of ecosystem services has been developed.

[0048] The order of the embodiments is for illustrative purposes only and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0049] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0050] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for identifying the ecosystem service threshold effect, characterized in that, Includes the following steps: S1. Divide the study area into basic spatial units, calculate the ecosystem service index values ​​of the basic spatial units, and select the main variables of the driving factors of the basic spatial units; The ecosystem service index values ​​and the driving factor main variables of the basic spatial units are normalized to obtain the normalized ecosystem service index values ​​and the normalized driving factor main variables. Basic spatial units are clustered into ecological stratification units. A regression discontinuity model is adopted, and a local adaptive bandwidth control mechanism is introduced to locally fit the abrupt change relationship between the normalized ecosystem service index value and the normalized driving factor main variable. The fitting performance of the regression discontinuity model under different bandwidths is evaluated to obtain the Bayesian information standard score. Combining the Bayesian information standard score, a spatial regularization smoothing term is introduced to construct a bandwidth co-optimization objective function. By minimizing the bandwidth co-optimization objective function, the optimal bandwidth of the ecological stratification unit is obtained. The optimal bandwidth is then re-inputted into the regression discontinuity model as a control parameter to obtain the ecosystem service threshold of the ecological stratification unit. The spatial regularization smoothing term is obtained by calculating the bandwidth change between adjacent ecological stratification units. S2. Based on the ecosystem service threshold of the ecological hierarchical unit, construct the ecosystem service threshold dataset of the basic spatial unit, and calculate the response offset factor of the basic spatial unit; Based on the response offset factor of the basic spatial unit, a spatial neighborhood collaborative correction mechanism driven by response offset is introduced to spatially correct the ecosystem service threshold of the basic spatial unit, and obtain the corrected ecosystem service correction threshold.

2. The method for identifying the ecosystem service threshold effect according to claim 1, characterized in that, S1 specifically includes: Ecosystem service driving factors are introduced, and the explanatory power of these factors on ecosystem service index values ​​is calculated. Based on the explanatory power, the main variables of the driving factors for basic spatial units are determined.

3. The method for identifying the ecosystem service threshold effect according to claim 1, characterized in that, S2 specifically includes: Based on the normalized driving factor main variables of the basic spatial unit and the ecosystem service threshold of the ecological stratification unit to which the basic spatial unit belongs, an ecosystem service threshold dataset of the basic spatial unit is constructed.

4. The method for identifying the ecosystem service threshold effect according to claim 3, characterized in that, S2 specifically includes: Based on the ecosystem service threshold dataset of basic spatial units, the adjacency weight of basic spatial units is introduced, the squared fitting residual of the basic spatial unit and the squared fitting residual of the adjacent basic spatial units are calculated, and the response offset factor of the basic spatial unit is obtained.

5. The method for identifying the ecosystem service threshold effect according to claim 4, characterized in that, S2 specifically includes: In the implementation of a response offset-driven spatial neighborhood collaborative correction mechanism, the corrected ecosystem service correction threshold is calculated based on the response offset factor of the basic spatial unit, combined with the current ecosystem service threshold of the basic spatial unit and the ecosystem service threshold of the neighborhood.

Images