CN114169673A - Multi-temporal lake wetland waterfowl community diversity inversion method and system - Google Patents

Multi-temporal lake wetland waterfowl community diversity inversion method and system Download PDF

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CN114169673A
CN114169673A CN202111262006.2A CN202111262006A CN114169673A CN 114169673 A CN114169673 A CN 114169673A CN 202111262006 A CN202111262006 A CN 202111262006A CN 114169673 A CN114169673 A CN 114169673A
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朱秀迪
李红清
江波
成波
柳雅纯
郝好鑫
王俊洲
陈晓娟
潘婷婷
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YANGTZE RIVER WATER RESOURCES PROTECTION SCIENCE RESEARCH INSTITUTE
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Abstract

The invention relates to a multi-time phase lake wetland waterfowl community diversity inversion method and a multi-time phase lake wetland waterfowl community diversity inversion system, wherein the monitored lake wetland is subjected to spatial rasterization processing by adopting a nearest spatial interpolation method according to waterfowl community diversity indexes of all monitoring points in each monitoring month, a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month is obtained, an optimal spatial capturing fishing net of the monitored lake wetland is constructed, wetland waterfowl diversity characteristics of adjacent spatial regions are comprehensively linked, the average value of the waterfowl community diversity indexes of all grids falling into each grid of the optimal spatial capturing fishing net is further calculated and converted into grid data to serve as the waterfowl community diversity indexes of the monitored lake wetland in each grid in each monitoring month, and finally a waterfowl community diversity index fishing net image of the monitored lake in each monitoring month in the monitoring period is formed, the dynamic inversion of the diversity of the overwintering aquatic bird community of the multi-temporal lake wetland is realized.

Description

Multi-temporal lake wetland waterfowl community diversity inversion method and system
Technical Field
The invention relates to the field of field animal ecology, in particular to a multi-temporal lake wetland waterfowl community diversity inversion method and system.
Background
At present, the existing dynamic evaluation means for community diversity of overwintering waterfowls in lake wetlands is mainly based on a sampling method of sampling point survey and a sampling line method of sampling line survey.
The sampling method is that several sampling parties are randomly selected from the habitat of the investigated population, the population density of each sampling party is calculated by counting the number of individuals in each sampling party, and the average value of the population densities of all the sampling parties is taken as the population density. In the sampling process, the probability of each individual being decimated in the whole is guaranteed to be equal as much as possible. Meanwhile, the sampling method requires that the selected individuals do not relate to other individuals and the random independent sampling, namely random sampling or simple random sampling, is satisfied. This method is subjective and is liable to lower the reliability of the investigation result, for example, in patent No. CN 105493858A.
The sample line method is mainly characterized in that sample lines are distributed at a set survey point according to the habitat type and the terrain, and the sample lines are not overlapped; the length of the sample line is preferably 1-3 km. Birds within about 200m on both sides of the sample band are observed through a telescope, a digital video camera, a digital camera and the like, and bird singing sound, flying postures, ecological habits, feather identification and the like are assisted. The name, the number and the distance from the center line of the found birds are carefully recorded, and the longitude and latitude, the altitude, the habitat, the length of a sample band, the flight path and other information of bird species discovery points are recorded by a track recorder. If birds are not observed but can be heard, the sound of the birds is recorded by a recording pen and is used as a basis for identifying species, and the line sampling method also has contingency and time-space discontinuity due to uncertainty of a survey point. In summary, although the two biodiversity investigation methods can complete the investigation of biodiversity in a certain area, the selection of the monitoring points is usually random due to the limitation of strong mobility of waterfowls, and cannot reflect the dynamic change process of vegetation diversity on the area on a time scale. In addition, the sample method and the sample line method can only monitor the types and the number of the waterfowls at limited points, so that the distribution condition of the waterfowl diversity cannot be continuously monitored in the regional space range.
Disclosure of Invention
The invention aims to provide a multi-temporal lake wetland aquatic bird community diversity inversion method and a multi-temporal lake wetland aquatic bird community diversity inversion system, so as to realize dynamic inversion of multi-temporal lake wetland overwintering aquatic bird community diversity.
In order to achieve the purpose, the invention provides the following scheme:
a multi-temporal lake wetland waterfowl community diversity inversion method comprises the following steps:
acquiring waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in a monitoring period; the monitoring data comprises the species and the population quantity of the waterfowls;
calculating the waterfowl community diversity index of each monitoring point in each monitoring month in a monitoring period according to the waterfowl community monitoring data;
according to the water bird community diversity index of all monitoring points in each monitoring month, carrying out space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method to obtain a water bird community diversity index grid image of the lake wetland monitored in each monitoring month;
constructing an optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum distribution uniformity of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed on the monitored lake wetland;
and calculating the average value of the waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data to serve as the waterfowl community diversity index of the lake wetland monitored in each monitoring month in each grid, and finally forming a waterfowl community diversity index fishing net image of the lake wetland monitored in each monitoring month in the monitoring period.
Optionally, the acquiring of the waterfowl community monitoring data of each monitoring point arranged on the monitored lake wetland in the monitoring period specifically includes:
determining the concentrated distribution points of the waterfowls as the monitoring points of the monitored lake wetland in each monitoring month according to the distribution characteristics of the waterfowls in each monitoring month in the monitoring period;
and monitoring and recording the aquatic bird community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
Optionally, according to the waterfowl community monitoring data, calculating a waterfowl community diversity index of each monitoring point in each monitoring month in a monitoring period, specifically including:
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure BDA0003326100590000031
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnThe Shannon-Wiener diversity index for the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000032
the individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
according to the Shannon-Wiener diversity index and the waterfowl variety of each monitoring point in each monitoring month, a formula is utilized
Figure BDA0003326100590000033
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure BDA0003326100590000034
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of the Simpson community of the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000035
number of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
Optionally, the constructing an optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by using the maximum value of the uniformity of the monitoring points distributed in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland specifically includes:
determining a plurality of side length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
according to the longitude and latitude of monitoring points distributed on the monitored lake wetland, a formula is utilized
Figure BDA0003326100590000036
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring pointsCounting; n is the total number of the fishing net grids containing the monitoring points;
and taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
A multi-temporal lake wetland waterfowl community diversity inversion system, the system comprising:
the waterfowl community monitoring data acquisition module is used for acquiring the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in the monitoring period; the monitoring data comprises the species and the population quantity of the waterfowls;
the waterfowl community diversity index calculation module is used for calculating the waterfowl community diversity index of each monitoring point in each monitoring month in the monitoring period according to the waterfowl community monitoring data;
the waterfowl community diversity index grid image obtaining module is used for carrying out space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method according to the waterfowl community diversity index of all the monitoring points in each monitoring month to obtain a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month;
the optimal space capturing fishing net constructing module is used for constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum distribution uniformity value of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland;
and the waterfowl community diversity index fishing net image forming module is used for calculating the average value of waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data to serve as the waterfowl community diversity index of the monitored lake wetland in each grid in each monitoring month, and finally forming the waterfowl community diversity index fishing net image of the monitored lake wetland in each monitoring month in the monitoring period.
Optionally, the waterfowl community monitoring data acquisition module specifically includes:
the monitoring point determining submodule is used for determining the water bird concentrated distribution points as the monitoring points of the monitored lake wetland in each monitoring month according to the water bird distribution characteristics in each monitoring month in the monitoring period;
and the waterfowl community monitoring data recording submodule is used for monitoring and recording the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
Optionally, the waterfowl community diversity index calculation module specifically includes:
a Shannon-Wiener diversity index calculation submodule for utilizing a formula according to the species and the population quantity of the waterfowl in each monitoring month at each monitoring point
Figure BDA0003326100590000041
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnThe Shannon-Wiener diversity index for the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000042
the individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
the Pielou uniformity index calculation submodule is used for utilizing a formula according to the Shannon-Wiener diversity index and the waterfowl type of each monitoring point in each monitoring month
Figure BDA0003326100590000051
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
the Simpson community dominance index calculation submodule is used for utilizing a formula according to the type and population quantity of waterfowls in each monitoring month at each monitoring point
Figure BDA0003326100590000052
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of the Simpson community of the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000053
number of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
Optionally, the optimal space capturing fishing net building module specifically includes:
the edge length value determining submodule is used for determining a plurality of edge length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
the space uniformity index acquisition submodule is used for utilizing a formula according to the longitude and latitude of monitoring points distributed on the monitored lake wetland
Figure BDA0003326100590000054
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring points is respectively; n is the total number of the fishing net grids containing the monitoring points;
and the optimal space capturing fishing net constructing submodule is used for taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a multi-time-phase lake wetland waterfowl community diversity inversion method and a multi-time-phase lake wetland waterfowl community diversity inversion system, wherein the monitored lake wetland is subjected to spatial rasterization processing by adopting a nearest spatial interpolation method according to waterfowl community diversity indexes of all monitoring points in each monitoring month, a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month is obtained, an optimal spatial capturing fishing net of the monitored lake wetland is constructed, wetland waterfowl diversity characteristics in close spatial regions are comprehensively linked, the average value of the waterfowl community diversity indexes of all grids falling into each grid of the optimal spatial capturing fishing net is further calculated and converted into grid data to serve as the waterfowl community diversity indexes of the monitored lake wetland in each grid in each monitoring month, and finally a waterfowl community diversity index fishing net image of the monitored lake wetland in each monitoring month in the monitoring period is formed, the dynamic inversion of the diversity of the overwintering aquatic bird community of the multi-temporal lake wetland is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a multi-temporal lake wetland waterfowl community diversity inversion method provided by the invention;
FIG. 2 is a schematic diagram of a multi-temporal lake wetland waterfowl community diversity inversion method provided by the invention;
FIG. 3 is a spatial distribution diagram of initial monitoring points of a lake of rapeseed according to an embodiment of the present invention;
FIG. 4 is a distribution diagram of actual monitoring points of a lake vegetable according to an embodiment of the present invention; FIG. 4(a) is a distribution diagram of actual monitoring points from 2018 to 2019, and FIG. 4(b) is a distribution diagram of actual monitoring points from 2019 to 2020;
FIG. 5 is a diagram illustrating a Shannon-Wiener diversity index IDW spatial interpolation result of a lake waterfowl according to an embodiment of the present invention; FIG. 5(a) is a distribution diagram of diversity index of waterfowl Shannon-Wiener, and FIG. 5(b) is a diagram of IDW spatial interpolation result of diversity index of waterfowl Shannon-Wiener;
FIG. 6 is a diagram of a most suitable spatial capture fishing net provided by an embodiment of the present invention;
fig. 7 is a plot of changes in Shannon-Wiener index of diversity of aquatic bird communities in the annual overwintering period of 2018-2019 and 2019-2020 provided in the embodiment of the present invention; fig. 7(a) is a 2018-year-10-month waterfowl community diversity Shannon-Wiener index distribution diagram, fig. 7(B) is a 2018-year-11-month waterfowl community diversity Shannon-Wiener index distribution diagram, fig. 7(C) is a 2018-year-12-month waterfowl community diversity Shannon-Wiener index distribution diagram, fig. 7(D) is a 2019-year-01-month waterfowl community diversity Shannon-Wiener index distribution diagram, fig. 7(E) is a 2019-year-10-month waterfowl community diversity Shannon-Wiener index distribution diagram, fig. 7(F) is a 2019-year-11-month waterfowl index distribution diagram, fig. 7(G) is a 2019-year-12-month-12-month waterfowl community diversity Shannon-Wiener index distribution diagram, and fig. 7(H) is a 2020-year-01-year-month waterfowl community diversity index distribution diagram.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a multi-temporal lake wetland aquatic bird community diversity inversion method and a multi-temporal lake wetland aquatic bird community diversity inversion system, so as to realize dynamic inversion of multi-temporal lake wetland overwintering aquatic bird community diversity.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The invention provides a multi-temporal lake wetland waterfowl community diversity inversion method, which comprises the following steps of:
step 1, acquiring waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in a monitoring period; the monitoring data includes waterfowl species and population numbers.
The method specifically comprises the following steps:
determining the concentrated distribution points of the waterfowls as monitoring points of the lake wetland monitored in each monitoring month according to the distribution characteristics of the waterfowls in each monitoring month in the monitoring period;
and monitoring and recording the aquatic bird community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
And 2, calculating the waterfowl community diversity index of each monitoring point in each monitoring month in the monitoring period according to the waterfowl community monitoring data.
The method specifically comprises the following steps:
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure BDA0003326100590000071
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnThe Shannon-Wiener diversity index for the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000072
the individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
according to the Shannon-Wiener diversity index and the waterfowl variety of each monitoring point in each monitoring month, a formula is utilized
Figure BDA0003326100590000081
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure BDA0003326100590000082
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of the Simpson community of the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000083
number of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
And 3, performing space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method according to the waterfowl community diversity index of all the monitoring points in each monitoring month to obtain a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month.
And 4, constructing an optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum value of the distribution uniformity of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland.
The method specifically comprises the following steps:
determining a plurality of side length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
according to the longitude and latitude of monitoring points distributed on the monitored lake wetland, a formula is utilized
Figure BDA0003326100590000084
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring points is respectively; n is the total number of the fishing net grids containing the monitoring points;
and taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
And 5, calculating the average value of the waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data to serve as the waterfowl community diversity index of the lake wetland monitored in each monitoring month in each grid, and finally forming a waterfowl community diversity index fishing net image of the lake wetland monitored in each monitoring month in the monitoring period.
Referring to fig. 2, the specific implementation process of the present invention is as follows:
one-time-phase and multi-time-phase wetland waterfowl community geographic data acquisition
And setting overwintering waterfowl monitoring points at intervals of 1km from north to south by taking the geographical north-most end of the lake wetland as an initial point. And (3) taking a longitude and latitude grid unit and a wetland landscape unit as assistance, and monitoring overwintering aquatic birds in the lake wetland by means of 8-time binoculars and 20-60-time monocular in a target lake range. It is worth noting that the actual monitoring points and the initially distributed sampling points have certain deviation due to the influence of the fluctuation of the water level of the lake and the uncertainty of the distribution of the overwintering waterfowls, so that the specific monitoring points and the actual monitoring points are mainly distributed. The monitoring is carried out by adopting a manual observation mode, the monitoring content (manual observation) comprises basic information such as longitude and latitude of monitoring points, water bird species, population quantity and the like, the annual time monitoring range generally covers the wintering period (10 months-3 months next year), the monitoring frequency is not less than month, and the observation year is not less than 2 years. The monitoring range needs to cover the whole target lake.
Secondly, calculating the diversity index of wetland waterfowl community
And calculating the diversity index of the waterfowl community for each monitoring point based on the monitored waterfowl community basic database. The avian community diversity index includes a Shannon-Wiener diversity index (H), a Simpson community dominance (S) index, and a Pielou uniformity index (P). H. P, S is as follows:
Figure BDA0003326100590000091
Figure BDA0003326100590000092
Figure BDA0003326100590000093
and then, performing spatial rasterization processing on the station scale waterfowl community diversity index based on the nearest spatial interpolation method. The nearest space interpolation method is a conventional calculation method for performing space rasterization on space point data, and is widely applied to space rasterization related researches by domestic and foreign scholars and organizations.
Third, construction of optimum space catching fishing net
In order to ensure that waterfowl monitoring points in different periods can be evenly distributed in each fishing net within the maximum limit, the monitoring points in each monitoring month are loaded into ArcMap10.5, square space capturing fishing nets with different side lengths are initially set in an experiment, and the side lengths of the square space capturing fishing nets are not less than 2 times of IDW (Inverse Distance Weighted) interpolation grid resolution (R) but not more than 50 times of the grid resolution. Setting square fishing nets with different side lengths by taking 2 times of the resolution of the pixel side length as an initial side length and 1 time as a step length. And constructing a spatially uniform index Ck'Uniformity C for depicting distribution of monitoring sites in fishing netk'The algorithm is as follows:
Figure BDA0003326100590000101
k' is the ratio of the side length of the fishing net to the IDW interpolation resolution; n is a radical ofk'xWhen the side length of the fishing net is k' times of the IDW interpolation grid, the number of monitoring points contained in the xth fishing net containing the waterfowl monitoring points is the number of the monitoring points contained in the xth fishing net;and n is the total number of the fishing nets containing the monitoring points.
When C is presentk'When the value is the global minimum value, it is recorded as CksThe side length of the corresponding fishing net is the most suitable side length of the fishing net, and the corresponding side length is RsThe calculation method is as follows:
Rs＝kSR
Rsis most suitable for the length of the fishing net side, ksTo fit to the spatial index CksThe ratio of the corresponding side length of the fishing net to the IDW interpolation resolution; r is IDW interpolated spatial resolution.
Fourthly, counting the diversity information of waterfowl communities in the wetland of the fishing net one by one
In finding the most suitable side length RsThen, constructing a rectangle with the boundary of the research range circumscribed and the side length of RsThe fishing net.
And calculating the average value of the wetland waterfowl community diversity information (H, S, P) corresponding to all grids with the IDW interpolation grid center longitude and latitude falling into the fishing net one by one.
And converting the vector data of the fishing net statistics into the side length RsThe data is a reversed high-resolution wetland waterfowl community diversity index which is continuous in time and space.
The final evaluation results were waterfowl diversity.
The method solves the problem that the diversity of multi-temporal waterfowl communities cannot be dynamically evaluated in situ, and is helpful for providing reasonable suggestions for protecting multi-temporal-spatial scale lake wetland overwintering waterfowls and habitats thereof.
A method for researching the dynamic change of overwintering aquatic bird community diversity in wetland of a rapeseed lake is provided by taking the rapeseed lake as a typical research area.
The brassica lake is an important winter migratory bird overwintering habitat and a centralized gathering area in the middle and lower reaches of Yangtze river, and a plurality of key birds are distributed in the lake area, so that the brassica lake is one of important overwintering areas and rest areas of east Asia-Australian migratory birds such as white haired cranes, oriental white geraniums, wild gooses and swans, and has important significance for protecting an ecosystem and biodiversity.
Firstly, laying waterfowl monitoring points every 1km from north to south initially in the whole lake (in the same experimental research range) of the rapeseed lake, and initially setting 17 monitoring points (figure 3). And carrying out wetland waterfowl monitoring in the range of the whole lake of the rape lake by taking the longitude and latitude grid unit and the wetland landscape unit as the auxiliary units. When the initial preset monitoring points are distributed in a water bird centralization mode, the monitoring points are the monitoring points. If no water bird is centrally distributed, the system is driven to a centralized distribution area with water birds for monitoring and recording monitoring points
And then adjusting the positions of the monitoring points according to the actual distribution condition of the waterfowls, and recording basic information such as the longitude and latitude, the species and the population number of the waterfowl community monitoring points. The monitoring time periods are two overwintering periods from 10 months in 2018 to 1 month in 2019, and from 10 months in 2019 to 1 month in 2020. The actual monitoring sample number will be different from the initial set point because of reasons such as water level change and bird inhabitation randomness, and this time monitoring point actual distribution is as shown in fig. 4.
And secondly, calculating waterfowl diversity indexes of the monitored months from monitoring point to monitoring point based on the monitored basic information of the waterfowl community, wherein the waterfowl diversity indexes comprise Shannon-Wiener diversity index (H), Simpson community dominance (S) index and Pielou uniformity index (P).
And thirdly, converting the monitored water bird diversity point cloud information into a grid image with the resolution of 0.001 degrees by using an IDW interpolation module in ArcGIS 10.5. The interpolation range is a circumscribed rectangle which can cover the lake and lake regions of the rapeseed and all the monitoring points, and the result is taken as an example of the Shannon-Wiener diversity index of the waterfowl in 2018 and 10 months (figure 5).
And fourthly, setting square space catching fishing nets with different side lengths by taking 0.002 degrees as an initial side length, constructing the most suitable space index C for describing the distribution uniformity of all monitoring stations in the fishing nets, and finally selecting 0.01 degrees as the most suitable side length to construct the fishing nets when the side length reaches 0.01 degrees.
Fifthly, constructing a fishing net with the side length of 0.01 degrees based on a Create Fishnet module of ArcGIS10.5, calculating the weighted average value of IDW interpolation points falling in the fishing net according to the wetland water bird community diversity information (H, S, P) of the fishing net one by one, and converting the vector data counted by the fishing net into a high-resolution water bird space-time dynamic change graph with the side length of 0.01 degrees. FIG. 7 shows the diversity Shannon-Wiener index change of waterfowl community in the year overwintering period of the rapeseed lake in 2018 and 2019 and 2020.
The invention relates to a high-resolution wetland waterfowl community diversity inversion method, which mainly captures wetland waterfowl diversity characteristics of a fishing net space comprehensive link close spatial region by constructing an optimal space, and further provides a scientific technical method for wide-range comparative evaluation of fine-scale waterfowl diversity characteristics.
The invention also provides a multi-temporal lake wetland waterfowl community diversity inversion system, which comprises:
the waterfowl community monitoring data acquisition module is used for acquiring the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in the monitoring period; monitoring data comprises species and population quantity of waterfowls;
the waterfowl community diversity index calculation module is used for calculating the waterfowl community diversity index of each monitoring point in each monitoring month in the monitoring period according to the waterfowl community monitoring data;
the waterfowl community diversity index grid image obtaining module is used for carrying out space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method according to the waterfowl community diversity index of all the monitoring points in each monitoring month to obtain a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month;
the optimal space capturing fishing net constructing module is used for constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum distribution uniformity value of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland;
the waterfowl community diversity index fishing net image forming module is used for calculating the average value of waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data, using the grid data as the waterfowl community diversity index of the monitored lake wetland in each grid in each monitoring month, and finally forming the waterfowl community diversity index fishing net image of the monitored lake wetland in each monitoring month in the monitoring period.
The waterfowl community monitoring data acquisition module specifically comprises:
the monitoring point determining submodule is used for determining the water bird concentrated distribution points as the monitoring points of the lake wetland monitored by each monitoring month according to the water bird distribution characteristics of each monitoring month in the monitoring period;
and the waterfowl community monitoring data recording submodule is used for monitoring and recording the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
The waterfowl community diversity index calculation module specifically comprises:
a Shannon-Wiener diversity index calculation submodule for utilizing a formula according to the species and the population quantity of the waterfowl in each monitoring month at each monitoring point
Figure BDA0003326100590000131
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnShannon-Wiener diversity index, Z, for the m-th monitoring point in the n-th monitoring monthi mnThe individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
the Pielou uniformity index calculation submodule is used for utilizing a formula according to the Shannon-Wiener diversity index and the waterfowl type of each monitoring point in each monitoring month
Figure BDA0003326100590000132
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
the Simpson community dominance index calculation submodule is used for utilizing a formula according to the type and population quantity of waterfowls in each monitoring month at each monitoring point
Figure BDA0003326100590000133
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of the Simpson community of the mth monitoring point in the nth monitoring month,
Figure BDA0003326100590000134
number of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
The optimal space catches the fishing net and constructs the module, specifically includes:
the edge length value determining submodule is used for determining a plurality of edge length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
the space uniformity index acquisition submodule is used for utilizing a formula according to the longitude and latitude of monitoring points distributed on the monitored lake wetland
Figure BDA0003326100590000141
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring points is respectively; n is the total number of the fishing net grids containing the monitoring points;
and the optimal space capturing fishing net constructing submodule is used for taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (8)

1. A multi-temporal lake wetland waterfowl community diversity inversion method is characterized by comprising the following steps:
acquiring waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in a monitoring period; the monitoring data comprises the species and the population quantity of the waterfowls;
calculating the waterfowl community diversity index of each monitoring point in each monitoring month in a monitoring period according to the waterfowl community monitoring data;
according to the water bird community diversity index of all monitoring points in each monitoring month, carrying out space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method to obtain a water bird community diversity index grid image of the lake wetland monitored in each monitoring month;
according to the longitude and latitude of monitoring points distributed in the monitored lake wetland, the maximum value of the distribution uniformity of the monitoring points in the fishing net is taken as an optimization target, and the optimal space capturing fishing net of the monitored lake wetland is constructed in the waterfowl community diversity index grid image;
and calculating the average value of the waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data to serve as the waterfowl community diversity index of the lake wetland monitored in each monitoring month in each grid, and finally forming a waterfowl community diversity index fishing net image of the lake wetland monitored in each monitoring month in the monitoring period.
2. The multi-temporal lake wetland waterfowl community diversity inversion method according to claim 1, wherein the obtaining of the waterfowl community monitoring data of each monitoring point laid on the monitored lake wetland in the monitoring period specifically comprises:
determining the concentrated distribution points of the waterfowls as the monitoring points of the monitored lake wetland in each monitoring month according to the distribution characteristics of the waterfowls in each monitoring month in the monitoring period;
and monitoring and recording the aquatic bird community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
3. The multi-temporal lake wetland waterfowl community diversity inversion method according to claim 1, wherein the method for calculating the waterfowl community diversity index of each monitoring point in each monitoring month in a monitoring period according to the waterfowl community monitoring data specifically comprises:
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure FDA0003326100580000021
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnThe Shannon-Wiener diversity index for the mth monitoring point in the nth monitoring month,
Figure FDA0003326100580000022
the individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
according to the Shannon-Wiener diversity index and the waterfowl variety of each monitoring point in each monitoring month, a formula is utilized
Figure FDA0003326100580000023
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
according to the species and population quantity of the waterfowl in each monitoring month at each monitoring point, utilizing a formula
Figure FDA0003326100580000024
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of Simpson community of the mth monitoring point in the nth monitoring month, Ni mnNumber of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
4. The multi-temporal lake wetland waterfowl community diversity inversion method according to claim 1, wherein the method for constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum distribution uniformity of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland specifically comprises the following steps:
determining a plurality of side length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
according to the longitude and latitude of monitoring points distributed on the monitored lake wetland, a formula is utilized
Figure FDA0003326100580000025
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring points is respectively; n is the total number of the fishing net grids containing the monitoring points;
and taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
5. The multi-temporal lake wetland waterfowl community diversity inversion system is characterized by comprising:
the waterfowl community monitoring data acquisition module is used for acquiring the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in the monitoring period; the monitoring data comprises the species and the population quantity of the waterfowls;
the waterfowl community diversity index calculation module is used for calculating the waterfowl community diversity index of each monitoring point in each monitoring month in the monitoring period according to the waterfowl community monitoring data;
the waterfowl community diversity index grid image obtaining module is used for carrying out space rasterization processing on the monitored lake wetland by adopting a nearest space interpolation method according to the waterfowl community diversity index of all the monitoring points in each monitoring month to obtain a waterfowl community diversity index grid image of the monitored lake wetland in each monitoring month;
the optimal space capturing fishing net constructing module is used for constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image by taking the maximum distribution uniformity value of each monitoring point in the fishing net as an optimization target according to the longitude and latitude of the monitoring points distributed in the monitored lake wetland;
and the waterfowl community diversity index fishing net image forming module is used for calculating the average value of waterfowl community diversity indexes of all grids in each grid of the optimal space capturing fishing net, converting the average value into grid data to serve as the waterfowl community diversity index of the monitored lake wetland in each grid in each monitoring month, and finally forming the waterfowl community diversity index fishing net image of the monitored lake wetland in each monitoring month in the monitoring period.
6. The multi-temporal lake wetland waterfowl community diversity inversion system according to claim 5, wherein the waterfowl community monitoring data acquisition module specifically comprises:
the monitoring point determining submodule is used for determining the water bird concentrated distribution points as the monitoring points of the monitored lake wetland in each monitoring month according to the water bird distribution characteristics in each monitoring month in the monitoring period;
and the waterfowl community monitoring data recording submodule is used for monitoring and recording the waterfowl community monitoring data of each monitoring point distributed in the monitored lake wetland in each monitoring month by using a telescope.
7. The multi-temporal lake wetland waterfowl community diversity inversion system according to claim 5, wherein the waterfowl community diversity index calculation module specifically comprises:
a Shannon-Wiener diversity index calculation submodule for utilizing a formula according to the species and the population quantity of the waterfowl in each monitoring month at each monitoring point
Figure FDA0003326100580000041
Calculating the Shannon-Wiener diversity index of each monitoring point in each monitoring month; wherein HmnThe Shannon-Wiener diversity index for the mth monitoring point in the nth monitoring month,
Figure FDA0003326100580000042
the individual proportion of the number of the ith species in the population in the nth monitoring month for the mth monitoring point;
the Pielou uniformity index calculation submodule is used for utilizing a formula according to the Shannon-Wiener diversity index and the waterfowl type of each monitoring point in each monitoring month
Figure FDA0003326100580000043
Calculating the Pielou uniformity index of each monitoring point in each monitoring month; wherein, PmnPielou uniformity index, L, for the m-th monitoring point in the n-th monitoring monthmnThe total population number of the population of the mth monitoring point in the nth monitoring month;
the Simpson community dominance index calculation submodule is used for utilizing a formula according to the type and population quantity of waterfowls in each monitoring month at each monitoring point
Figure FDA0003326100580000044
Calculating the index of the dominance degree of the Simpson community of each monitoring point in each monitoring month; wherein S ismnThe index of the dominance of the Simpson community of the mth monitoring point in the nth monitoring month,
Figure FDA0003326100580000045
number of i species in N monitoring month for m monitoring point, NmnNumber of all species in the community for the m-th monitoring point in the n-th monitoring month.
8. The multi-temporal lake wetland waterfowl community diversity inversion system according to claim 5, wherein the optimal space capturing fishing net construction module specifically comprises:
the edge length value determining submodule is used for determining a plurality of edge length values of the side length of the fishing net grid according to the grid resolution of the waterfowl community diversity index grid image;
the space uniformity index acquisition submodule is used for utilizing a formula according to the longitude and latitude of monitoring points distributed on the monitored lake wetland
Figure FDA0003326100580000046
Obtaining a space uniformity index when the side length of the fishing net grid is the length value of each side; wherein, CkThe spatial uniformity index is the spatial uniformity index when the side length of the fishing net grid is a side length value k; n is a radical ofk1、Nkx、NknWhen the side length of each fishing net grid is a side length value k, the number of monitoring points contained in the 1 st, x th and n th fishing net grids containing waterfowl monitoring points is respectively; n is the total number of the fishing net grids containing the monitoring points;
and the optimal space capturing fishing net constructing submodule is used for taking the side length value corresponding to the minimum value of all the space uniformity indexes as the side length of the most suitable fishing net grid, and constructing the optimal space capturing fishing net of the monitored lake wetland in the waterfowl community diversity index grid image according to the side length of the most suitable fishing net grid.
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