Method and system for evaluating protection effect and priority of protection area on freshwater fish habitat

Abstract

The invention belongs to the technical field of ecological environmental protection, and discloses a freshwater fish habitat protection effect and priority evaluation method in a protection area, and the method comprises the steps: employing the collinearity of VIF test variables, employing a MaxEnt algorithm to construct a species distribution model of each species in global sea river migration fishes, and simulating the habitat distribution based on a habitat model; according to the performance of the AUC and TSS evaluation model, simulation of the model is realized; according to the distribution information of the protection area, the stability of the sea-river migratory fish habitats outside and inside the protection area and the planning priority of the protection area are evaluated respectively. According to the method, the protection effect of the land protection area on the freshwater fish habitat and the protection area planning priority for the freshwater fish habitat are evaluated respectively, and the unbalance problem that in the prior art, freshwater fishes are often ignored in the protection area setting process is solved.

Description

Technical Field

[0001] This invention belongs to the field of ecological and environmental protection technology, and in particular relates to a method and system for evaluating the protection effect and priority of protected freshwater fish habitats in protected areas. Background Technology

[0002] In the context of climate change, freshwater ecosystems are affected far more severely than other ecosystems. As a key component of freshwater ecosystems, the protection of freshwater fish habitats has been a major concern both domestically and internationally. Furthermore, the protection of freshwater fish habitats is a strategically important task at the national level. Climate change is a primary cause of freshwater biodiversity loss and will intensify the impact of human activities on biodiversity. Existing protected areas primarily target terrestrial animals while neglecting freshwater fish; however, the protective umbrella effect provided by their habitat coverage may shield them from some of the impacts of climate change. Currently, there are no reported methods for assessing the protective effect of terrestrial protected areas on freshwater fish habitats, which hinders the protection of freshwater ecosystems and the planning of new protected areas. Constructing habitat models for target species based on species distribution models is an effective method for assessing habitat change, and combining this with analysis and comparison of protected area distribution can evaluate the protective effect of terrestrial protected areas on freshwater fish habitats.

[0003] Existing freshwater fish habitat protection strategies rarely consider the role of terrestrial protected areas or specifically plan protected areas, thus failing to effectively protect freshwater fish. Therefore, this type of protected area is of great significance for methods of assessing the effectiveness and priority of freshwater fish habitat protection.

[0004] Based on the above analysis, the problems and shortcomings of the existing technology are as follows:

[0005] Existing freshwater fish habitat protection strategies rarely consider the role of terrestrial protected areas or plan protected areas in a targeted manner, thus failing to effectively protect freshwater fish. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a method for evaluating the protection effect and priority of protected areas on freshwater fish habitats.

[0007] This invention is implemented as follows: A method for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats includes:

[0008] Step 1: Collect historical data on the presence and absence of the target freshwater fish species, and collect bioclimate data and human activity-related data that affect fish distribution to establish a variable set;

[0009] Step 2: Use the variance inflation factor (VIF) to test for collinearity of variables, and select the maximum entropy algorithm (MaxEnt) to construct a species distribution model of the target freshwater fish.

[0010] Step 3: Evaluate the performance of the species distribution model based on the area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS), and perform habitat simulation and prediction;

[0011] Step 4: Collect information and map the distribution of protected areas (PAs) to assess the protective effect of PAs on target freshwater fish habitats under the influence of climate change;

[0012] Step 5: Use the protection urgency factor (PU) to determine priority areas for protected areas (PAs) planning targeting freshwater fish species.

[0013] Furthermore, the specific steps of step 2 are as follows:

[0014] Step 2.1: Calculate the variance inflation factor (VIF) value for each factor in the variable set. A VIF value less than 5 indicates low variable collinearity, suitable for building a species distribution model. Conversely, a VIF value greater than 5 indicates high variable collinearity, requiring variable reselection. The formula for calculating the variance inflation factor (VIF) is as follows:

[0015]

[0016] In the formula, ---No. One environmental factor;

[0017] ---The sum of squares of the relative changes of this environmental factor with all other environmental factors;

[0018] Step 2.2: Use the set of variables that have passed the collinearity test to build a species distribution model using the maximum entropy algorithm (MaxEnt).

[0019] Furthermore, the specific steps of step 3 are as follows:

[0020] Step 3.1: Run the species distribution model of the target freshwater fish ten times;

[0021] Step 3.2: Randomly select 70% of the total existing and missing data as the training set to fit the algorithm, and retain the remaining 30% for evaluating the algorithm performance;

[0022] Step 3.3: Evaluate on the assessment dataset using the Area Under the Receiver Working Characteristic Curve (AUC) and the True Skill Statistic (TSS);

[0023] Step 3.4: Use the established species distribution model to analyze the historical and future distribution of the target freshwater fish. Different scenarios Simulations and predictions were conducted to obtain habitat suitability for historical periods. and climate patterns Down Different scenarios at different times Habitat suitability .

[0024] Furthermore, the evaluation method in step 3.3 includes averaging the AUC and TSS from 10 model runs. If the model performs well, it is considered to have excellent performance; otherwise, more data on the distribution points of the target fish species needs to be collected or the modeling variables need to be reselected.

[0025] The formula for calculating TSS is as follows:

[0026]

[0027] In the formula, For model specificity, the calculation formula is as follows:

[0028]

[0029] The formula for calculating model sensitivity is:

[0030]

[0031] Furthermore, the specific steps of step 4 are as follows:

[0032] Step 4.1: Download protected area data for the target freshwater fish research area using the wdpar package in R language;

[0033] Step 4.2: Exclude protected areas that have not yet been implemented and protected areas with limited conservation value, replace protected areas represented by points with circular protected areas corresponding to their reported areas, and project the shapefiles of the protected areas onto the WGS84 coordinate system.

[0034] Step 4.3: Assess the habitat suitability of the target freshwater fish species over historical periods. and climate patterns Down Different scenarios at different times Habitat suitability By comparison, the proportion of habitats inside and outside protected areas that remained unchanged under climate change was calculated separately. and Thus, the protective effect of the protected area is achieved. The calculation formula is as follows:

[0035] (5)

[0036] (6)

[0037] (7)

[0038] In the formula, The conditions within the study area are The sum of the areas of all grids;

[0039] This is a binary map showing the distribution of protected areas; 1 indicates the existence of a protected area, and 0 indicates the absence of a protected area.

[0040] Habitat suitability during historical periods and climate patterns Down Different scenarios at different times Habitat suitability A value greater than 1 indicates a habitat; otherwise, it is not a habitat.

[0041] Furthermore, the specific steps of step 5 are as follows:

[0042] Step 5.1: Assess the habitat suitability of the target freshwater fish species over historical periods. and climate patterns Down Different scenarios at different times Habitat suitability The difference is used to prioritize the degradation of habitat suitability outside the protected area as an indicator for protected area planning. The calculation formula is as follows:

[0043]

[0044] In the formula, This represents the urgency of protecting the target freshwater fish species, with a value ranging from 0 to 1, where a higher value indicates greater urgency. It is used as a priority indicator for protected area planning, with higher urgency indicating higher priority.

[0045] Another objective of this invention is to provide a method for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats under the background of climate change. A system for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats under the background of climate change includes:

[0046] The variable set module is established to collect historical presence and absence data of target freshwater fish, and to collect bioclimate data and human activity-related data that affect fish distribution to establish the variable set;

[0047] The environmental factor testing module is used to test the collinearity of variables using the variance inflation factor (VIF) and select the maximum entropy algorithm (MaxEnt) to construct a species distribution model of the target freshwater fish.

[0048] The model simulation and prediction module is used to evaluate the performance of the model based on two evaluation indicators: the area under the subject working characteristic curve (AUC) and the true skill statistic (TSS), so as to realize the simulation and prediction of the habitat model.

[0049] The protected area protection role assessment module is used to assess the protective role of protected areas on freshwater fish habitats under climate change, based on the distribution information of protected areas within the target freshwater fish research area.

[0050] The protected area planning assessment module is used to assess the priority of protected area planning based on the degree of decline in the suitability of target freshwater fish habitats outside the protected area.

[0051] Another object of the present invention is to provide a computer device including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0052] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0053] Another objective of this invention is to provide an information data processing terminal, which includes the aforementioned system for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0054] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0055] First,

[0056] This invention provides a method for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats, addressing the imbalance in existing protected area planning that primarily focuses on terrestrial organisms. Through a systematic approach, including data collection, variable testing, model building, assessment of protected area effects and planning priorities, a comprehensive evaluation and quantitative analysis of the protective role of protected areas in freshwater fish habitats is achieved. This method provides a scientific basis for developing protection and management strategies.

[0057] First, this invention establishes a variable set by collecting historical data on the presence and absence of target freshwater fish communities, as well as bioclimatic data and human activity-related data influencing fish distribution. The diversity and completeness of this data provide a solid foundation for the accuracy of the subsequent model. By using the variance inflation factor (VIF) to test for multicollinearity among variables, the reliability and scientific rigor of the model are further enhanced. The constructed species distribution model can simulate fish habitat distribution, thereby accurately clarifying the patterns of freshwater fish habitat change under climate change.

[0058] Secondly, this invention employs two evaluation metrics—the area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS)—to assess model performance and enable simulation and prediction. This process not only ensures the model's efficiency and accuracy but also guarantees the stability and reliability of the results through multiple runs and evaluations. By calculating the proportion of habitats remaining unchanged both inside and outside protected areas under climate change, the protective role of protected areas on habitats is accurately assessed and quantified, providing a reliable basis for scientific evaluation.

[0059] Finally, this invention quantitatively assesses the urgency of freshwater fish habitat protection through priority indicators in protected area planning, providing crucial data support for the formulation of protection and management measures. Compared to traditional methods, this invention achieves significant technological advancements in data processing, model building, and results analysis.

[0060] In summary, this invention, through a systematic data processing and model building approach, successfully addresses the problem of unclear effectiveness of terrestrial protected areas in protecting freshwater fish habitats in existing technologies. Its significant technological advancements are reflected in improved prediction accuracy and model reliability, providing a scientific basis and practical tool for the protection and management of freshwater ecosystems. The widespread application of this method will have a profound impact on freshwater ecological conservation.

[0061] This invention successfully solves multiple technical problems in the planning of freshwater fish habitat protection areas through a series of key parameters, algorithms, and mathematical models, achieving significant technological progress. First, this invention establishes a comprehensive set of variables using historical data on existing and missing points, as well as bioclimatic data and data related to human activities. The stability and scientific validity of the model are ensured by testing for multicollinearity of variables using the variance inflation factor (VIF). This process overcomes the inaccuracy problem caused by multicollinearity in traditional methods, significantly improving the accuracy and efficiency of variable selection.

[0062] Secondly, this invention introduces a species distribution model and combines it with the maximum entropy algorithm (MaxEnt) to construct a fish habitat model. The model's performance is evaluated using two metrics: the area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS), thus achieving both simulation and prediction. This method overcomes the problem of insufficient predictive power of single models in existing technologies, significantly improving the model's predictive accuracy and stability.

[0063] In assessing the protective effectiveness of protected areas, this invention proposes an innovative comparative method that independently analyzes the climate change resilience of habitats both inside and outside the protected area. By calculating habitat suitability changes under climate patterns and utilizing simulation results from historical time-period models, the protective effect of the protected area on freshwater fish habitats is evaluated. This method effectively solves the problem of difficulty in determining the protective effect of terrestrial habitats on freshwater fish habitats in traditional methods, providing a valuable reference for the planning of protected areas for freshwater fish habitats.

[0064] Finally, this invention quantitatively assesses the urgency of freshwater fish habitat protection using priority indicators for protected area planning. This quantitative assessment method not only identifies specific protected area gaps but also helps determine the priority of protected area establishment within the study area, thus providing crucial data support for the formulation of protection and management measures. Compared to traditional methods, this invention achieves significant technological advancements in data processing, model building, and results analysis, significantly improving the scientific rigor and practicality of freshwater ecosystem protection and management.

[0065] second,

[0066] Existing protected area planning primarily focuses on terrestrial organisms while neglecting the incidental protection role and urgency of freshwater fish. This invention can serve as an important reference for assessing the benefits of protected areas. Furthermore, it can improve the efficiency of freshwater ecosystem protection and save human and material resources.

[0067] Existing protected area planning techniques mainly consider terrestrial biodiversity and land costs, neglecting the habitat distribution and diversity loss of freshwater fish. This invention fills the gap in protected area planning techniques regarding the protection of freshwater fish habitats.

[0068] Freshwater ecosystems are among the fastest-decreasing ecosystems in terms of biodiversity, with fish being a crucial component. Under the influence of climate change and human activities, fish habitats are rapidly degrading, leading to a sharp decline in fish populations. The conservation of freshwater fish has long been a challenge both domestically and internationally. This invention proposes a protected area assessment and planning method specifically for freshwater fish, which can improve the efficiency of freshwater fish habitat protection. Attached Figure Description

[0069] Figure 1This is a flowchart of the method for evaluating the protection effect and priority of protected areas for freshwater fish habitats provided in the embodiments of the present invention.

[0070] Figure 2 This is a detailed flowchart of the method for assessing the protection effect and priority of protected areas for freshwater fish habitats provided in this embodiment of the invention.

[0071] Figure 3 This is a global map showing the distribution of migratory fish species in oceans and rivers, provided in an embodiment of the present invention.

[0072] Figure 4 This is a global map of marine and river migratory fish species richness provided in an embodiment of the present invention.

[0073] Figure 5 This is a map showing the urgency and priority of establishing global marine migratory fish sanctuaries, provided in an embodiment of the present invention.

[0074] Figure 6 This is a structural diagram of the protection effect and priority assessment system for freshwater fish habitats provided in an embodiment of the present invention. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0076] like Figure 1 , Figure 2 As shown in the figure, the method for assessing the protection effect and priority of protected areas for freshwater fish habitats provided by an embodiment of the present invention includes the following steps:

[0077] S101: Collect historical data on the presence and absence of the target freshwater fish community, and collect bioclimatic data and human activity-related data that affect fish distribution to establish a variable set;

[0078] S102: Using the variance inflation factor (VIF) to test for collinearity of variables, the maximum entropy algorithm is selected to construct a species distribution model of the target freshwater fish.

[0079] S103: Evaluate the performance of species distribution models based on the Area Under the Analytical Characteristic (AUC) and the True Skill Statistic (TSS) for habitat simulation and prediction;

[0080] S104: Collect information and map the distribution of PAs in the protected area, and assess the protective effect of PAs on the target freshwater fish habitat under the influence of climate change;

[0081] S105: Use the protection urgency factor (PU) to determine priority areas for planning protected areas (PAs) targeting freshwater fish species.

[0082] The specific steps of S102 provided in this embodiment of the invention are as follows:

[0083] Step 2.1: Calculate the variance inflation factor (VIF) value for each factor in the variable set. If the VIF value is less than 5, it indicates low variable collinearity, which can be used to build a species distribution model; conversely, it indicates high variable collinearity, requiring reselection of variables. The formula for calculating the variance inflation factor (VIF) value is as follows:

[0084]

[0085] In the formula, ---No. One environmental factor;

[0086] ---The sum of squares of the relative changes of this environmental factor with all other environmental factors;

[0087] Step 2.2: Use the set of variables that have passed the collinearity test to build a species distribution model using the maximum entropy algorithm (MaxEnt).

[0088] The specific steps of S103 provided in this embodiment of the invention are as follows:

[0089] Step 3.1: Run the species distribution model of the target freshwater fish ten times;

[0090] Step 3.2: Randomly select 70% of the total existing and missing data as the training set to fit the algorithm, and retain the remaining 30% for evaluating the algorithm performance;

[0091] Step 3.3: Evaluate on the assessment dataset using the Area Under the Receiver Working Characteristic Curve (AUC) and the True Skill Statistic (TSS);

[0092] Step 3.4: Use the established species distribution model to analyze the historical and future distribution of the target freshwater fish. Different scenarios Simulations and predictions were conducted to obtain habitat suitability for historical periods. and climate patterns Down Different scenarios at different times Habitat suitability .

[0093] The specific steps of S104 provided in this embodiment of the invention are as follows:

[0094] Step 4.1: Download protected area data for the target freshwater fish research area using the wdpar package in R language;

[0095] Step 4.2: Exclude protected areas that have not yet been implemented and protected areas with limited conservation value, replace protected areas represented by points with circular protected areas corresponding to their reported areas, and project the shapefiles of the protected areas onto the WGS84 coordinate system.

[0096] Step 4.3: Assess the habitat suitability of the target freshwater fish species over historical periods. and climate patterns Down Different scenarios at different times Habitat suitability By comparison, the proportion of habitats inside and outside protected areas that remained unchanged under climate change was calculated separately. and Thus, the protective effect of the protected area is achieved. The calculation formula is as follows:

[0097] (5)

[0098] (6)

[0099] (7)

[0100] In the formula, The conditions within the study area are The sum of the areas of all grids;

[0101] This is a binary map showing the distribution of protected areas; 1 indicates the existence of a protected area, and 0 indicates the absence of a protected area.

[0102] Habitat suitability during historical periods and climate patterns Down Different scenarios at different times Habitat suitability A value greater than 1 indicates a habitat; otherwise, it does not.

[0103] The specific steps of S105 provided in this embodiment of the invention are as follows:

[0104] Step 5.1: Assess the habitat suitability of the target freshwater fish species over historical periods. and climate patterns Down Different scenarios at different times Habitat suitability The difference is used to prioritize the degradation of habitat suitability outside the protected area as an indicator for protected area planning. The calculation formula is as follows:

[0105] (8)

[0106] In the formula, It represents the urgency of protecting the target freshwater fish, with a value ranging from 0 to 1. The higher the value, the higher the urgency. It is used as a priority indicator for protected area planning, with a higher urgency indicating a higher priority.

[0107] like Figure 6 As shown in the figure, an embodiment of the present invention provides a system for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats, including:

[0108] The variable set module is established to collect historical presence and absence data of target freshwater fish, and to collect bioclimatic data and human activity-related data that affect fish distribution to establish the variable set;

[0109] The environmental factor testing module is used to test the collinearity of variables using the variance inflation factor (VIF) and select the maximum entropy algorithm to construct a species distribution model of the target freshwater fish.

[0110] The model simulation and prediction module is used to evaluate the performance of the model based on two evaluation indicators: the area under the subject's working characteristic curve (AUC) and the true skill statistic (TSS), and to realize the simulation and prediction of the habitat model.

[0111] The protected area protection role assessment module is used to assess the protective role of protected areas on freshwater fish habitats under climate change, based on the distribution information of protected areas within the target freshwater fish research area.

[0112] The protected area planning assessment module is used to assess the priority of protected area planning based on the degree of decline in the suitability of target freshwater fish habitats outside the protected area.

[0113] Another object of the present invention is to provide a computer device including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0114] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0115] Another objective of this invention is to provide an information data processing terminal, which includes the aforementioned system for assessing the effectiveness and priority of protected areas for freshwater fish habitat protection under the background of climate change.

[0116] Specific implementation of the present invention:

[0117] The study area of ​​this example ( Figure 3 This includes seven regions: Asia, Oceania, Africa, North America, and South America. Because protected areas primarily target terrestrial animals and often neglect freshwater fish, and freshwater ecosystems are among the most vulnerable ecosystems, protecting and restoring freshwater fish habitats is extremely difficult. Therefore, assessing the protective role of protected areas in freshwater fish habitats and developing targeted protected area plans is of great significance. Since anadromous fish require both terrestrial and marine environments to complete their life cycle, and their habitats are large or their migration routes are long, this invention presents a method for assessing the effectiveness and priority of protected areas in protecting freshwater fish habitats. Taking 275 anadromous fish species globally as examples, a distribution model of 429 fish species in seven different study regions was constructed based on the MaxEnt algorithm. The protective role and urgency of protected areas for these fish habitats were assessed to help formulate better freshwater fish habitat protection strategies. The specific process is as follows:

[0118] Historical location data of migratory fish species in oceans and rivers worldwide from 2001 to 2020 were collected, and these locations were classified and summarized by species, then filtered into 7 study areas. Figure 3 The modeling unit was selected from only the marine migratory fish species with more than 5 historical locations in a single study area. 1000 background points were generated using a randomization method and merged into the overall dataset. Global-scale seasonality of temperature (BIO4), seasonality of precipitation (BIO15), dam density (DD), and human footprint (HFP) data were collected as the modeling factor set. Before modeling, the variance inflation factor (VIF) was used to perform a collinearity test on the modeling factors to ensure VIF < 5. The merged dataset and modeling factor set were input to run 429 models for 275 fish species 10 times (based on the MaxEnt algorithm). Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS) (mean AUC > 0.9, TSS > 0.75). The outputs of the 429 models for 275 fish species were stacked to obtain the species richness of marine migratory fish species in 7 study areas. Figure 4 Based on the distribution of protected areas, the stability index (i.e., the proportion of habitats that remain unchanged under climate change) and priority index (conservation urgency) of freshwater fish habitats inside and outside the protected areas were calculated respectively. Figure 5 ).

[0119] BIO4, BIO15, DD, and HFP all passed the collinearity test, with VIF values ​​less than 5. The median AUC and TSS of all models in the seven study regions were above 0.92 and 0.75, respectively, indicating excellent model performance. Figure 4 This indicates that Oceania and Southeast Asia are the richest regions for migratory fish species. The existence of protected areas can significantly enhance habitat stability, increasing the proportion of stable habitats by 5% to 27%. Figure 5 This indicates that North America is a region where conservation is urgently needed, with up to 4.21105 square kilometers of habitat lost for 10 to 20 species of migratory fish species.

[0120] River migratory fish (including sturgeon) are important economic fish species. They need to migrate between ocean and freshwater to complete their life cycle. Protected areas need to be established along their migration routes to strengthen their protection and prevent the endangered situation of the Chinese sturgeon from happening again.

[0121] This invention innovatively proposes a method for assessing the protection effect and priority of protected areas on freshwater fish habitats, evaluating the protective role of terrestrial protected areas on freshwater fish and the priority areas for protected area planning. Figure 5 This can improve the efficiency of freshwater fish habitat protection.

[0122] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0123] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for assessing the effectiveness of protected areas in protecting freshwater fish habitats and determining protection priorities, characterized in that, Includes the following steps: Step 1: Collect historical data on the presence and absence of the target freshwater fish community, and collect bioclimatic variables and human activity variables that affect the distribution of fish to establish a variable set; Step 2: Test for multicollinearity of the variable set based on the variance inflation factor (VIF) and remove variables with a VIF greater than 5; Step 3: Construct a distribution model of the target freshwater fish species using the maximum entropy algorithm; Step 4: The performance of the species distribution model is evaluated using the Area Under the Receiver Operating Characteristic (AUC) and the True Skill Statistic (TSS), and habitat suitability under historical and future climate scenarios is simulated based on the evaluation results. Step 5: Obtain spatial distribution data of protected areas within the study area and analyze the protective role of protected areas in protecting the target freshwater fish habitat under climate change conditions; Step 6: Calculate the protection urgency coefficient PU, and determine the priority areas for protected area planning based on the coefficient.

2. The method as described in claim 1, characterized in that, The threshold for the variance inflation factor (VIF) mentioned in step two is five.

3. The method as described in claim 1, characterized in that, In step four, a random sampling method is used to divide all existing and missing data into a training set and an evaluation set. The training set accounts for 70% of the total data, and the evaluation set accounts for 30%.

4. The method as described in claim 1, characterized in that, The spatial distribution data of the protected areas mentioned in step five is downloaded from a public database. Point-like protected areas are converted into circular polygons of the same area based on their reported area. All vector data of protected areas are uniformly projected to the WGS 84 coordinate system.

5. An evaluation system for implementing the method of claim 1, characterized in that, include: The module includes a variable set construction module, a collinearity test module, a species distribution model module, a protected area role assessment module, and a priority planning module. The modules work together to perform the steps described in claim 1.

6. The evaluation system as described in claim 5, characterized in that, The collinearity test module is configured to automatically remove a variable when the variance inflation factor (VIF) of the detected variable is higher than five.

7. The evaluation system as described in claim 5, characterized in that, The species distribution model module includes a simulation submodule, which is configured to output habitat suitability raster data under multiple climate scenarios.

8. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, causes the processor to perform the method of claim 1.

9. An electronic device comprising a processor and a memory, the memory storing instructions which, when executed by the processor, are used to implement the method of claim 1.

10. An information data processing terminal, comprising a display component, an input component, and the evaluation system of claim 5, wherein the information data processing terminal is configured to graphically display the protection effect of the protected area on freshwater fish habitat and output priority planning results.

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