CN112418596B - Biodiversity protection planning method - Google Patents
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Abstract
The invention discloses a method for biodiversity protection planning, which comprises the following steps: 1) Determining a planning range and a planning granularity according to a set biodiversity protection planning condition; each planning range comprises one or more planning granularities, a planning granularity list is established according to each obtained planning granularity, and the species to be protected in the corresponding planning granularity are determined according to the range of each planning granularity; 2) Constructing a phylogenetic tree according to the species in each planning granularity to obtain a plurality of phylogenetic trees; 3) Calculating the phylogenetic diversity index of each phylogenetic tree, and generating a diversity index key value pair in a planning range; 4) And calculating the species diversity distribution of each planning range according to the diversity index key values, and determining a priority protection area according to the species diversity distribution. The method can quickly calculate the phylogenetic diversity index distribution of small-granularity units and determine a reasonable planning result.
Description
Technical Field
The invention belongs to the technical field of applied ecological information, and relates to a large-scale biodiversity protection planning method based on phylogenetic diversity indexes, which is mainly applied to the fields of dynamic planning and ecological protection of national parks, protected areas and protected areas.
Background
Biodiversity is the sum of characteristics and functions of all species and their variability in a region, genetic resources carried by each species, and the population (population), community (community), community (biome), phyla (biota), ecosystem (ecosystem) formed among the species, and the like, which are the basis for supporting the earth's life system. The nature-protected land refers to a land area or a sea area (Peng Yangjing, etc., 2018) for implementing long-term protection on important natural ecosystems, natural heritage, natural landscapes and natural resources, ecological functions and cultural values carried by the natural ecosystem and the natural heritage.
Since the first natural conservation area is established in 1956, natural conservation lands in China are rapidly constructed and developed, 12000 various natural conservation lands at all levels occupy about 18% of the land area, and play an important role in protecting biological diversity, guaranteeing ecological safety and the like in China. However, there are also problems of lack of strategy and planning of overall development of the natural protection, unreasonable spatial layout of the natural protection, severe fragmentation and islanding phenomena of the natural protection, low protection effect and the like, which affect the overall performance of the natural protection (Xu, weihua, et al.2019). In order to solve the problems, the nation steadily advances the reformation work of natural conservation ground under the background of ecological civilization construction, perfects the construction of a conservation ground system, proposes to establish a natural conservation ground system taking national parks as a main body, takes the establishment of national parks as a trigger, and solves the contradiction of natural conservation ground in China.
The delineation of protection zones and the formulation of protection strategies are often based on the idea that all species have equal protection value (valve-Wright et al,1991, posadas et al, 2001), however, the protection value is not the same among species due to historical differences (Faith, 1992, 2015, laity et al, 2015), and it is not comprehensive and accurate to conduct evaluation and formulate protection strategies based solely on species diversity (Knapp et al,2008 daru &leroux, 2016. As the phylogenetic diversity is not influenced by the change of the classification status, the functions of the ecosystem (Cadotte et al,2008 Flynn et al,2011 Srivastava et al, 2012) can be relatively well reflected and the loss rate (Sechrest et al, 2012) which is faster than the species diversity is added, so that the research and the evaluation of the phylogenetic diversity are more urgent. It is precisely because communities with high phylogenetic diversity are more stable, show higher productivity, possess more species of different trophic levels (Cadotte et al,2012, 2013, dinnange et al, 2012), when establishing a preferential protection zone, first of all care is taken to the zone with high phylogenetic diversity to protect as many evolutionary units as possible, thus ensuring an efficient preservation of the evolution history of the species within the region (Sechrest et al,2002 jetz et al,2012, shapcott et al, 2015. In addition, phylogenetic diversity of evolutionary dimensions can clearly reveal branches with special evolutionary histories or endangered (Isaac et al,2007 rosauer et al, 2009), providing scientific basis for establishing preferential protection regions or optimizing protection strategies. Biodiversity protection is to protect not only the regions that are abundant in existing species, but also the regions that are unique and abundant in the evolution history [ Chen Zhi, li Dezhu, 2018].
In recent years, with the rapid development of DNA barcode data, new generation sequencing technologies and computational tools, studies on the change, origin and protection of plant system compositions have been developed based on evolutionary relationships among species and depending on phylogenetic diversity and related parameters, and studies on the distribution patterns and formation reasons of biodiversity in different regions by integrating environmental factors or climate factors have been gradually conducted based on the spatial distribution of species (e.g., pio et al, 2014. However, due to the limitation of research foundation, the construction level of species distribution models in different regions is inconsistent with the evaluation book of environmental factors, some earlier-developed researches and technical methods cannot be well integrated into the research of phylogenetic diversity, and the sharing and integration of data still have great obstacles in China, so that the distribution mode of researching biological diversity on a large scale is limited (Cixiu celery & Li Li, 2017).
Therefore, in practical applications, particularly in implementation of national parks and protected areas implemented in large-scale ranges and small-granularity units, how to quickly calculate a reliable phylogenetic tree, how to quickly calculate the phylogenetic diversity index distribution of small-granularity units, and how to quickly present planning results are key problems to be solved. The invention provides a method for carrying out biological diversity protection planning based on phylogenetic diversity index, and implements related schemes based on Chinese plant species distribution and Chinese land plant phylogenetic big trees.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention aims to provide a method for carrying out biological diversity protection planning based on a phylogenetic diversity index, which comprises the following specific processes:
step A: determining the biodiversity protection planning condition: setting conditions of the planned range, the planned granularity and the like, determining planned granularity individuals and corresponding species in the range, and then executing the step B;
(1) Setting biodiversity protection conditions: setting a planned range, a planned granularity and the like;
the specification scope may be an administrative region type, such as province, city, or a combination thereof; it may also be manually selected, such as for a particular body of water, mountain area, or other area established for planning.
The planning granularity can be administrative region types, such as county-level administrative districts and the like; it may also be a grid, such as a 10km by 10km grid or other grid granularity;
(2) Screening and planning granularity individuals: calculating the inclusion range of all planning granularity individuals in the biodiversity planning enclosure to obtain a list { G1, G2, … Gi } containing each planning granularity individual, wherein i is the number of the planning granularity individual; gi is the area range of the ith planning granularity;
when the inclusion range of all planning granularity individuals in the biodiversity planning enclosure is calculated, the planning boundary processing method comprises the following steps: if the individual is based on the check area, the granularity individual at the planning boundary can be the planning strength individual if the individual is in the check area with the area more than or equal to 50 percent. And if the method is based on the administrative regions, determining planning granularity individuals according to the division data of the latest administrative regions of the countries.
(3) Calculating the species in the planning granularity individual range: calculating all species names under the range of each planning granularity individual;
when each planning granularity individual contains all the names of the wild species in the range, the species distribution is based on the distribution data of the wild species collection area, and the relevant projection transformation can be carried out according to the selected planning granularity mode (such as a grid mode or an administrative district mode); the format of the output wild species name is 'generic name + species name'.
And B: and (3) construction of a phylogenetic tree: and constructing a phylogenetic tree for all species of each planning granularity individual, and constructing the phylogenetic tree by taking the planning granularity as a unit. Then executing step C;
(1) Standardization of wild species directory: carrying out object name record standardization on all species names under the inclusion range of each planning granularity individual, and judging whether the species names are wild species or not; if the wild species is the local wild species, the wild species is reserved, and if the wild species is the non-local wild species, the wild species is deleted;
(2) Matching node elements: inquiring a basic phylogenetic big tree database for a standardized wild species directory to obtain a node element list and a mapping relation between the species directory list and the node element list by matching (according to the steps from a low-order element to a high-order element, for example, matching is carried out by firstly 'planting' and then 'belonging' and then 'subject');
(3) Acquiring a node element relation chain: retrieving the relationship chain of each node element from the basic phylogenetic big tree database to obtain the relationship chain of each node element;
(4) Calculating node element grouping relation: pairwise comparison and matching are carried out on all the obtained relationship chains from leaf nodes to form a grouping relationship of the node elements;
(5) Calculating the branch length of the node elements: calculating each node element and the corresponding new branch length of the group thereof in the phylogenetic tree according to the node weight and the species grouping relation of each node element in the node element list in the phylogenetic base big tree, and generating the phylogenetic tree corresponding to the node element list;
(6) Generating a phylogenetic tree of planning granularity individuals: and generating a phylogenetic tree of planning granularity individuals according to the phylogenetic tree corresponding to the node element list and the mapping relation between the species list and the node element list.
And (5) repeating the steps (1) to (6) to obtain the phylogenetic tree with branch length of each planning granularity individual.
The preparation process of the basic phylogenetic big tree database comprises the following steps: firstly, segmenting and reconstructing a file of a system evolution basic big tree, recording segmentation times and segmentation weight, converting the segmentation times and the segmentation weight into a binary tree data structure, and recording a relationship chain of each node element and storing the relationship chain into a database.
And C: and (3) constructing a phylogenetic diversity index:
(1) Calculating the individual diversity index of the planning granularity: firstly, respectively aiming at a phylogenetic tree of each species in each planning granularity individual, calculating a phylogenetic diversity index: the phylogenetic tree for each planning granularity individual represents the length of the species evolution history by the length of the branch, and the phylogenetic diversity of one planning granularity is the sum PDi of the branch lengths of all the species in the region on the phylogenetic tree.
(2) Generating a diversity index key value pair in a planning range: then summarizing to obtain a set of parameters including each planning granularity individual and a corresponding phylogenetic diversity index key value pair { Gi: PDi };
step D: biodiversity planning online mapping: and visually presenting the phylogenetic diversity index of each planning granularity in a geographic information system:
(1) Establishing a planning granularity individual planning index: firstly, the planning index is standardized to obtain the planning index PLi of each planning granularity unit area. B, calculating to obtain the type of the planning granularity set according to the step A, and judging whether the area is a uniform area, if the area of the planning granularity is the equal area A, the normalized key value pair of each individual planning granularity and the planning index thereof is { Gi: PLi } = { Gi: PDi/A }; if the areas of the planning granularity are not equal, the area Ai of each planning granularity individual is used for obtaining a normalized key value pair { Gi: PLi } = { Gi (PDi/Ai) } of each planning granularity individual and a planning index thereof;
(2) Normalization process planning index: normalizing all the values of the PLi to obtain a { Gi: PLNi } key value pair, and finally obtaining the value of PLNi within the range of 0-1;
(3) And (3) establishing a rendering color: and calculating the color corresponding to each planning granularity individual in the gradient value according to a color gradient algorithm, and finally obtaining the mapping relation between each planning granularity individual and the corresponding RGB color to form a { Gi: RGBi } key value pair set.
(4) Constructing a planning granularity individual boundary service: b, constructing a vector map service of each individual planning granularity, and reading the individual boundary of each planning granularity according to the planning range and the planning granularity in the step A to form the map service;
(5) Rendering into a graph: and according to the boundary range, performing color filling on each planning granularity individual according to { Gi: RGBi } coloring data, and rendering into a picture.
Step E: establishing a priority protection area: and according to different planning targets and coloring gradients, carrying out planning and establishment of the biodiversity protection area and generation of a corresponding data product. On one hand, a protection area can be determined and mapped according to the color distribution and the continuity degree of the coloring gradient through the visual map obtained in the step D; on the other hand, the proportion of the protection area in the planned area can be set, and a corresponding protection area is selected to form a diagram according to the value of PLi.
(1) Establishing a planning proportion: when the planning target is the protection area proportion S in the planning region, firstly, carrying out descending order arrangement according to the PLi to obtain a list of planning granularity arranged according to the PLi descending order;
(2) Calculation of the priority protection list: then selecting corresponding planning granularity from the top, and summing the granularity to obtain a total area Ab, so that the ratio of the total area Ab to the total planning area Az is greater than or equal to S, namely
Ak is the area of any one of k priority protection planning granularity individuals selected to meet the conditions, and Ai is the area of any one planning granularity individual in the planning range to obtain a priority protection planning granularity individual list;
(3) Priority protection granular individual boundary services: reading boundary services of k priority protection planning granularity individuals, and performing highlighted color display on the boundaries;
(4) And (3) generation of a priority protection map product: and finally, generating a map data product of the established priority protection planning area, and printing the map data product into a png format data file for storage.
The invention also provides a server characterized by comprising a memory and a processor, the memory storing a computer program configured to be executed by the processor, the computer program comprising instructions for carrying out the steps of the above method.
The invention also provides a computer-readable storage medium, on which a computer program is stored, characterized in that the computer program realizes the steps of the above-mentioned method when being executed by a processor.
Compared with the prior art, the invention has the following positive effects:
the invention provides a method for carrying out biological diversity protection planning based on a phylogenetic diversity index, which is characterized in that a wild species phylogenetic tree is applied, a phylogenetic tree with planning granularity as a unit is quickly constructed, the phylogenetic diversity index is calculated, and online drawing of biological diversity planning is further carried out.
Drawings
FIG. 1 is a workflow diagram of a method for biodiversity protection planning based on phylogenetic diversity index;
FIG. 2 is a process flow diagram of a method of performing a biodiversity protection plan in an embodiment.
Detailed Description
The invention is further described by the following specific embodiments in conjunction with the accompanying drawings.
Referring to fig. 1, the specific process of the method for planning biodiversity protection based on phylogenetic diversity index described in this embodiment is:
step A: determining the biodiversity protection planning condition: carrying out condition setting on the planned range, the planned granularity and the like, determining the planned granularity individual and the corresponding species in the range, and then executing the step B;
(1) Setting biodiversity protection conditions: this embodiment is exemplified by the planning setting in which the planning range is yunnan province and the planning granularity is a prefectural administrative district.
(2) Screening and planning granularity individuals: the inclusion ranges of all the planned granularity individuals in the biodiversity planning enclosure are calculated, and a list { G1, G2, … Gi }, i of which is the number of each planned granularity individual, is obtained, and in this embodiment, the numbers are sorted by the first letter of the names of the counties in Yunnan province, and the data of which is shown in table 1.
(3) Calculating the species in the planning granularity individual range: the names of all species in the range included in each county are calculated, and the output is output in the format of "generic name + species name" in table 2.
When calculating all the names of the wild species in the range contained by each planned granularity individual, the species distribution of the embodiment is based on the distribution data of the wild species collection place, the wild species distribution data used in the embodiment is sorted by Chinese plant journal, and the administrative region division is based on a national administrative region information query platform (http:// xzqh.mca.gov.cn/map); and carrying out regional projection transformation aiming at the historical distribution regional name and the current county-level administrative district related to the Chinese plant lineage.
And B: and (3) construction of a phylogenetic tree: and constructing a phylogenetic tree for all species of each planning granularity individual, and constructing the phylogenetic tree by taking the planning granularity as a unit. Then executing step C; in this example, phylogenetic trees of wild species were constructed in units of county-level row and district in Yunnan province.
(1) Standardization of wild species directory: standardizing the name of all species in the range of each county to judge whether the species are wild species (the judging condition of the embodiment is that the species are not included in the name of the species in Chinese plant journal, namely judge not to be the wild species [ the name of the plant species which can be cultivated or is foreign ]);
(2) Matching node elements: the method comprises the steps of inquiring a basic Phylogenetic big tree database for a standardized wild species directory to obtain a node element list and a mapping relation between a species directory list and the node element list (matching is carried out according to the steps from a low-order element to a high-order element (such as ' planting ' and then ' belonging to ' family '), wherein the basic evolutionary big tree adopted by the embodiment is a family-level unit full-coverage (Hu H, liu B, liang Y S, et al. An updated Chinese vascular plant tree of life: a Phylogenetic diversity locations accessed [ J ]. Journal of Systematics and Evolution, 2020.), and the obtained mapping relation is ' complete species matching ' or ' typical genus matching ');
(3) Acquiring a node element relation chain: retrieving the relationship chain of each node element from the basic phylogenetic big tree database to obtain the relationship chain of each node element;
(4) Calculating node element grouping relation: comparing and matching all the obtained relationship chains from leaf nodes to form a grouping relationship of the node elements;
(5) Calculating the branch length of the node elements: calculating the new branch length of each node element and the corresponding group thereof in the phylogenetic development tree according to the node weight and the species grouping relation of each corresponding node element in the phylogenetic basic big tree;
(6) Generating a phylogenetic tree: the phylogenetic trees with branch length obtained by the cyclic recursion steps (3) - (5) for each planning granularity individual are shown in table 3.
And (5) repeating the steps (1) to (6) to obtain the phylogenetic tree with branch length of each planning granularity individual.
The preparation process of the basic phylogenetic big tree database comprises the following steps: firstly, segmenting and reconstructing a file of a system evolution basic big tree, recording segmentation times and segmentation weight, converting the file into a binary tree data structure, recording a relationship chain of each element, and storing the relationship chain of each element in a database, wherein the specific method refers to SoTree (Meng Z, li JH, yang T, lin L, et al. SoTree: an automated phenyl analysis tool for engineering from big tree 2015 IEEE International Conference on Smart City, chengdu 2015, 792-797.);
and C: and (3) constructing a phylogenetic diversity index:
(1) Calculating the individual diversity index of the planning granularity: firstly, respectively aiming at a phylogenetic tree of each species in planning granularity individual, calculating a phylogenetic diversity index: the phylogenetic tree for each planning granularity individual expresses the length of the species evolution history by the length of the branch, and the phylogenetic diversity of one planning granularity is the sum PDi of the branch lengths of all the species in the region on the phylogenetic tree.
(2) Generating a diversity index key value pair in a planning range: then summarizing to obtain a set of parameters including each planning granularity individual and a corresponding phylogenetic diversity index key value pair { Gi: PDi };
step D: biodiversity planning online mapping: and visually presenting the individual biodiversity index of each planning granularity in a geographic information system:
(1) Establishing a planning granularity individual planning index: firstly, carrying out standardized calculation on a planning index PLi, obtaining the type of the planning granularity set in the step A, judging whether the area is uniform, if so, judging whether the area is uniform, and if so, planning in a grid mode, wherein each standardized individual planning granularity and the key value pair of the planning index thereof are { Gi: PLi } = { Gi: PDi }; if the areas are non-uniform areas, assuming that the area of each individual planning granularity is Ai, obtaining a key value pair { Gi: PLi } = { Gi (PDi/Ai) } of each individual planning granularity and the planning index thereof, wherein data samples in the embodiment are shown in table 4, for example;
(2) Normalization process planning index: normalizing all the values of the PLi to obtain a { Gi: PLNi } key value pair, wherein the value of PLNi is in the range of 0-1; the normalization was PLNi = (PLNi-min (PLN))/(max (PLN) -min (PLN));
(3) And (3) establishing a rendering color: and calculating the corresponding color of each planning granularity individual in the color gradient according to a color gradient algorithm, and finally obtaining the mapping relation of the RGB color of each planning granularity individual to form a { Gi: RGBi } key value pair set.
Firstly, taking several values according to gradient in the range of 0-1 to form a set C = { C1, C2, C3, …, cn } to respectively color, so as to gradually change in the colors;
then, determining the values of x and y according to the value of PLNi (x and y are from the set C and PLNi is between x and y), namely determining a color value interval [ x, y ];
and finally, calculating the color value corresponding to each Gi: the color corresponding to the minimum value of the interval [ x, y ] is represented by Colorx = rgb (rx, gx, bx), and the color corresponding to the maximum value y of the interval is Colory = rgb (ry, gy, by), so the color corresponding to the PLNi in the interval is RGBi = rgb { rx + factor (ry-rx), gx + factor (gy-gx), bx + factor (by-bx) }, wherein the factor represents the relative position of the PLNi in the interval [ x, y ], and can be obtained by (PLNi-x)/(y-x).
In this embodiment, several values such as C = {0,0.25,0.5,0.75,1} are taken in a gradient within the range of 0 to 1, and the colors are respectively given as: rgb {44,123,182}, rgb {171,217,233}, rgb {255,255,191}, rgb {253,174,97}, rgb {215,25,28} to fade in these colors;
if the PLN value of bingchuan county is 0.6174, then [ x, y ] = [0.5,0.75], then Colorx = rgb {255,255,191}; color = rgb {253,174,97}; factor = (0.6174-0.5)/(0.75-0.5) =0.4696; then the corresponding color values are found by the formula as RGB bingchuan county = RGB { round _ half _ up (255 +0.4696 (253-255)), round _ half _ up (255 +0.4696 (174-255)), round _ half _ up (191 +0.4696 (97-191)) } = RGB (254,217,147). Where round _ half _ up is rounded up.
(4) Constructing a planning granularity individual boundary service: constructing a vector map service of planning granularity individuals, reading the individual boundary of each planning granularity and a corresponding color-giving value { Gi: RGBi } according to the planning area and the planning granularity in the step A to form the map service, and constructing the vector map county-level boundary service by applying mapnik V3 (https:// mapnik.org) in the embodiment;
(5) Rendering into a graph: layers built by map services are added by Openlayers V6 (https:// openlayers.org), namely, a planning layer with gradient color endowment can be displayed at a browser end, and the planning layer can be magnified or zoomed out to be viewed under different resolution scales.
Step E: establishing a priority protection area: and according to different planning targets and coloring gradients, carrying out biodiversity protection area planning establishment and corresponding data product generation. On one hand, a protection area can be determined and mapped according to the color distribution and the continuity degree of the coloring gradient through the visual map obtained in the step D; on the other hand, the proportion of the protection area in the planned area can be set, and a corresponding protection area is selected to form a diagram according to the value of PLi. The present embodiment generally describes the yunnan provincial protection area ratio as 18%, and includes the following steps:
(1) Establishing a planning proportion: when the planning target is that the proportion of the protected area in the planned area is S =18%, firstly performing descending arrangement according to the PLi to obtain a list of planning granularity arranged according to the PLi in the descending arrangement;
(2) Calculation of the priority protection list:then, the corresponding planning granularity is selected from the above to be added to obtain the total area Ab, so that the ratio of the total area Ab to the total planning area Az is more than or equal to 18 percent, namely
Ak is the area of any one of k priority protection planning granularity individuals selected to meet the conditions, and Ai is the area of any one planning granularity individual in the planning range to obtain a priority protection planning granularity individual list;
(3) Priority protection granular individual boundary services: reading k priority protection planning granularity individuals, namely boundary services of priority protection counties, and performing highlighted color display on the boundaries;
(4) And (3) generation of a priority protection map product: and finally, generating a map data product of the established priority protection planning area, and printing the map data product into a png format data file for storage.
Table 1: output data example for setting planning range and planning granularity in embodiment
Table 2: within-individual species output data examples per planning granularity in an embodiment
Table 3: examples of phylogenetic tree data with branch lengths for each planning granularity individual
Table 4: in embodiments, PD output data examples within an individual per planning granularity
The above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person skilled in the art can modify the technical solution of the present invention or substitute the same without departing from the spirit and scope of the present invention, and the scope of the present invention should be determined by the claims.
Claims (6)
1. A method of biodiversity protection planning, comprising the steps of:
1) Determining a planning range and a planning granularity according to the set biodiversity protection planning condition; each planning range comprises one or more planning granularity, a planning granularity list { G1, G2, … Gi } is established according to each obtained planning granularity, and the species to be protected in the corresponding planning granularity is determined according to the range of each planning granularity; wherein Gi is the region range of the ith planning granularity;
2) Constructing a phylogenetic tree according to the species in each planning granularity to obtain i phylogenetic trees; the construction method of the phylogenetic tree comprises the following steps: 21 Carrying out object name record standardization on the species names in the planned particle size range, and judging whether the species names are wild species; if the species is a local wild species, the species is reserved, otherwise, the species is deleted; obtaining a list of species lists; carrying out segmentation reconstruction on the file of the phylogenetic basic big tree, recording the segmentation times and the segmentation weight, converting the phylogenetic basic big tree into a binary tree data structure, and storing a relationship chain of each node element in the phylogenetic basic big tree into a basic phylogenetic big tree database; 22 Querying the basic phylogenetic big tree database according to the standardized wild species name in the species directory list, matching to obtain a node element list, and recording the mapping relationship between the species directory list and the node element list; 23 Retrieving the relationship chain of each node element in the node element list from the base phylogenetic treelike database; 24 Comparing every two obtained relation chains, and if the two relation chains are matched, dividing node elements corresponding to the two matched relation chains into a group to obtain a grouping relation of the node elements; 25 According to the node weight and the species grouping relationship of each node element in the node element list in the phylogenetic basis big tree, calculating each node element and the corresponding new branch length of the group in the phylogenetic tree, and generating the phylogenetic tree corresponding to the node element list; 26 Generating a phylogenetic tree corresponding to the planning granularity individual according to the phylogenetic tree corresponding to the node element list and the mapping relation;
3) Calculating the phylogenetic diversity index of each phylogenetic tree, and generating a diversity index key value pair in a planning range; wherein, the diversity index key value pair corresponding to the ith planning granularity Gi is { Gi: PDi }, and PDi is a phylogenetic diversity index calculated according to the phylogenetic tree of the planning granularity Gi;
4) Calculating the species diversity distribution of each planning range according to each diversity index key value, and determining a priority protection area according to the species diversity distribution; the method for determining the preferential protection area comprises the following steps: 41 According to the planning index of unit area of the planning granularity, performing descending arrangement on the planning granularity to obtain a planning granularity list of descending arrangement; 42 K priority protection plan granularities are selected according to the sequence and the areas of the k priority protection plan granularities are summed to obtain a total area Ab, so that the ratio of the total area Ab to the total area Az of the plan range is greater than or equal to S, namely
Ak is the area of any one of k priority protection planning granularity individuals selected to meet the conditions, and Ai is the area of any one planning granularity individual in the planning range; s is a set protection area proportion in a planning area; 43 Read the boundary service of the k priority protection planning granularity individuals, perform highlight color display on the boundary, and establish a priority protection area.
2. The method of claim 1, wherein said phylogenetic diversity index for each of said phylogenetic trees is calculated by: and expressing the length of species evolution history by the length of the branch in the phylogenetic tree, and calculating the sum PDi of the lengths of the branches on the phylogenetic tree as the phylogenetic diversity index of the phylogenetic tree.
3. The method of claim 2, wherein when pairwise aligning the resulting relationship chains, matching node elements in the two relationship chains occurs in order from a lower order element to a higher order element.
4. The method of claim 1, wherein the phylogenetic diversity index for each planning granularity is visualized in a geographic information system according to diversity index key assignments by:
51 Calculating a planning index of each planning granularity unit area to obtain a standardized diversity index key value pair of each planning granularity; the normalized diversity index key value pair corresponding to the planning granularity Gi is { Gi: PLi }; pli is a planning index of a unit area of planning granularity Gi;
52 Normalizing the normalized diversity index key value pair of each planning granularity;
53 According to a color gradient algorithm, calculating that each planning granularity is a corresponding color in the gradient value to obtain a mapping relation between each planning granularity and RGB colors, and forming a key value pair set; wherein, the key value pair { Gi: RGBi } corresponding to the planning granularity Gi in the key value pair set is RGBi which is the RGB color corresponding to the normalization value PlNi corresponding to the Pli;
54 According to the planning range and the planning granularity, reading each individual boundary of the planning granularity to form vector map service corresponding to the planning granularity;
55 According to the boundary range of each planning granularity, carrying out color filling on the individual with the corresponding planning granularity according to the color-endowing data corresponding to each planning granularity in the set by the key value and rendering the individual into a picture.
5. A server, comprising a memory and a processor, the memory storing a computer program configured to be executed by the processor, the computer program comprising instructions for carrying out the steps of the method according to any one of claims 1 to 4.
6. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 4.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104573405A (en) * | 2014-12-22 | 2015-04-29 | 中国科学院计算机网络信息中心 | Phylogenetic tree rebuilding method for building sub trees on basis of big trees |
| CN106844688A (en) * | 2017-01-23 | 2017-06-13 | 环境保护部南京环境科学研究所 | The plant habitat analyzed based on space overlapping and GAP protects red line demarcation method |
| WO2019087373A1 (en) * | 2017-11-02 | 2019-05-09 | 富士通株式会社 | Animal habitat value assessment system, animal habitat value assessment method, and animal habitat value assessment program |
| CN110852532A (en) * | 2019-11-26 | 2020-02-28 | 浙江大学 | Natural protected area system integration and boundary delineation method |
-
2020
- 2020-10-12 CN CN202011084995.6A patent/CN112418596B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104573405A (en) * | 2014-12-22 | 2015-04-29 | 中国科学院计算机网络信息中心 | Phylogenetic tree rebuilding method for building sub trees on basis of big trees |
| CN106844688A (en) * | 2017-01-23 | 2017-06-13 | 环境保护部南京环境科学研究所 | The plant habitat analyzed based on space overlapping and GAP protects red line demarcation method |
| WO2019087373A1 (en) * | 2017-11-02 | 2019-05-09 | 富士通株式会社 | Animal habitat value assessment system, animal habitat value assessment method, and animal habitat value assessment program |
| CN110852532A (en) * | 2019-11-26 | 2020-02-28 | 浙江大学 | Natural protected area system integration and boundary delineation method |
Non-Patent Citations (1)
| Title |
|---|
| 系统发育多样性在植物区系研究与生物多样性保护中的应用;慈秀芹等;《生物多样性》;20170215(第02期);第72-78页 * |
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