CN103870995B - A kind of alpine sandy land revegetation potential evaluation method - Google Patents
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Abstract
The invention discloses a kind of alpine sandy land revegetation potential evaluation method, comprise the steps: the habitat conditions for extremely frigid zones different kind sandy land, determine its revegetation target；Use analytic hierarchy process (AHP), set up the hierarchy Model of different kind sandy land revegetation Potential Evaluation；Utilize the hierarchy Model that described sand grassland revegetation potentiality is evaluated, development of judgment matrix, Mode of Level Simple Sequence list and total hierarchial sorting list；Use Field Using Fuzzy Comprehensive Assessment, carry out different kind sandy land revegetation potential comprehensive evaluation calculation.This alpine sandy land revegetation potential evaluation method, good and bad degree and the overall assessment of revegetation potentiality including 15 factors of evaluation can be exported respectively, can be Qinghai-Tibet Platean zones of different, the decision support method of dissimilar alpine sandy land revegetation policy making a kind of science of offer.
Description
Technical Field
The invention relates to the technical field of ecological protection and restoration, in particular to a method for evaluating vegetation restoration potential of alpine sandy land.
Background
The development of vegetation restoration potential evaluation is the basis of ecological restoration practice on hard and hard lands (degraded desertified land and engineering disturbed areas), and when facing a degraded ecosystem, the first consideration is to determine the capability of the degraded ecosystem to restore to a certain target ecosystem, namely to evaluate the restoration potential. Intensive recovery by the american committee for natural resources (UNRC), Cairns, and pendulat is an ideal state to restore the damaged ecosystem to a state prior to the disturbance. But this ideal situation is not possible due to limitations of real-world conditions such as lack of knowledge of the historical evolution of the ecosystem, too long recovery times, too high costs, etc. In vegetation restoration potential evaluation, information of a reference system is generally used to define a restoration target, and then the restoration potential of a restoration area is determined by measuring the distance between a degraded community and a reference community, and the restoration state is evaluated.
In recent years, some comprehensive evaluation models are applied to vegetation recovery potential evaluation in different types of areas such as mining areas in China, northern farming and pasturing staggered zones, and northern Qianxi karst areas, and particularly, the recovery degree and the recovery speed of species abundance and vegetation coverage along the newly-built Qinghai-Tibet railway are predicted by an analog survey method, so that a good effect is achieved. However, at present, no study is related to biodiversity change, community succession mechanism, space pattern of sand plant dominant population and response relation of space-time heterogeneity of sand plant with soil moisture and the like in the recovery process of sand vegetation in alpine valley under the condition of habitat stress, and the study is the premise and basis for carrying out comprehensive evaluation of the recovery potential of sand vegetation in alpine valley.
At present, researches and practices related to vegetation restoration and reconstruction of a degraded desertification ecosystem in a severe cold region of the Qinghai-Tibet plateau are mainly concentrated on a middle drainage basin of 'two rivers in one river' in the Tibet, a line of a Qinghai-Tibet railway, a source region of the three rivers, a Chadamu basin and the like. Research shows that due to unique high and cold climate and harsh natural conditions, the restoration of the Qinghai-Tibet plateau moving dune is very difficult only by natural force, and the vegetation restoration can be started quickly after the sand barriers are manually arranged. Since the 80 th century, the autonomous region is in regions such as the region near the Zhao Shu county, the Jedang town in the southern Shang county, the Lansai mountain county and the county of Shandong, Luo village to Nadong county, such as many rather the country, the adverse conditions such as high altitude, less rainfall, dry climate and the like are overcome, the continuous exploration of the work of preventing and controlling sand is carried out by constructing measures such as wind prevention and sand fixation forest, farmland protection forest, sand sealing and breeding forest and the like, and a certain positive effect is played on reducing the wind sand damage of traffic key roads and air port ports.
However, while the practical work accumulates abundant practical experience of preventing and controlling the sand storm disasters, more importantly, a plurality of bottleneck problems which need to be solved urgently for recovering the ecology of the sand land in the alpine valley are found, and the following aspects are highlighted: the method has the advantages that firstly, the types of the high-cold wind desertification land are various, the river bank flowing sand land and the hillside flowing sand land on the two sides of the valley are key areas for preventing and controlling the wind and sand disasters, and due to the restriction of habitat conditions, the vegetation recovery mechanism is completely different from the river beach sand land with better water conditions, so that the vegetation recovery potential evaluation of different types of sand lands is urgently needed to be developed; secondly, a comprehensive evaluation model of vegetation recovery potential in the alpine sandy land under the condition of habitat stress is constructed to provide a method basis for developing vegetation recovery potential evaluation of different types of sandy lands and different regions of the alpine valley.
Disclosure of Invention
The invention aims to provide a method for evaluating vegetation recovery potential in alpine sandy land, which aims to solve the problems. In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a method for evaluating vegetation restoration potential of alpine sandy land comprises the following steps:
determining a vegetation recovery target of the alpine region according to habitat conditions of different types of sand lands;
establishing a hierarchical structure model for evaluating the recovery potential of different types of sandy vegetation by using an analytic hierarchy process;
constructing a judgment matrix, a hierarchical single-rank sequence table and a hierarchical total rank table by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation;
and (4) carrying out comprehensive evaluation calculation on the recovery potential of the vegetation in different types of sandy land by using a fuzzy comprehensive evaluation method.
Preferably, the method for establishing the hierarchical structure model for evaluating the recovery potential of the sandy vegetation of different types by using the analytic hierarchy process specifically comprises the following steps:
selecting the four aspects of climate condition information, terrain condition information, soil condition information and current restoration situation information as basic indexes for evaluating vegetation restoration potential of the flowing sandy land of the alpine valley;
constructing different types of hierarchical structure models of sandy land vegetation recovery potential evaluation by adopting an analytic hierarchy process according to basic indexes of the vegetation recovery potential evaluation of the sandy land vegetation flowing in the alpine valley; the fuzzy evaluation is divided into three levels, namely a target layer A, a criterion layer B and an index layer C, wherein:
the target layer A is the highest level of the hierarchical structure, namely the evaluation value of the vegetation recovery potential of the flowing sand land of the alpine valley is realized; the criterion layer B is a main system layer for ensuring the realization of the overall target and is divided into climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4; the index layer is the most basic hierarchical structure and comprises specific evaluation factors of climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4;
wherein: the climate condition information B1 comprises an evaluation factor set of annual precipitation C1, annual average air temperature C2 and annual sunshine duration C3; the terrain condition information B2 comprises evaluation factor sets of an altitude C4, a gradient C5 and a slope direction C6; the soil condition information B3 comprises evaluation factor sets of soil moisture C7, soil pH value C8, soil organic matter C9, soil total nitrogen C10, soil texture C11 and sand dune ground temperature C12; the current restoration information B4 is suitable for evaluation factor sets of biological species selection C13, fence enclosure cultivation C14 and ground treatment C15;
the evaluation factor set is as follows: b1 ═ C1, C2, C3, B2 ═ C4, C5, C6, B3 ═ C7, C8, C9, C10, C11, C12, B4 ═ C13, C14, C15; a ═ B1, B2, B3, B4 }.
Preferably, a judgment matrix, a level single-row sequence list and a level total-row sequence list are constructed by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, and the method specifically comprises the following steps:
starting from an index layer in the hierarchical structure model for evaluating the sandy vegetation restoration potential, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each evaluation factor in the index layer to the basic index of the upper-level standard layer, calculating the weight value of each evaluation factor by adopting a square root method, carrying out normalization operation, and calculating after consistency check to obtain a weight set (B-C) of the index layer to the standard layer: w21, W22, W23, W24; establishing a hierarchical single-row sequence table according to the calculated weight values of the evaluation factors;
from the criterion layer in the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each basic index in the criterion layer to a target layer at the upper stage, solving the weight value of each basic index by adopting a square root method, carrying out normalization operation, and obtaining a weight set (A-B) of the criterion layer to the target layer by calculation after consistency test: w1; establishing a hierarchical single-row sequence table according to the calculated weight values of the basic indexes;
multiplying the weight value of the index layer relative to the standard layer by the weight value of the standard layer relative to the target layer to obtain the weight W occupied by each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land of the alpine valley; and establishing a hierarchical total ranking list according to the weight of each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land in the alpine valley.
Preferably, the comprehensive evaluation calculation of the recovery potential of the sandy vegetation of different types by using the fuzzy comprehensive evaluation method specifically comprises the following steps:
presetting comment threshold values corresponding to different levels for each evaluation factor;
determining vegetation recovery potential evaluation information of each evaluation factor in the flowing sandy land of the alpine valley according to the condition that the weight of each evaluation factor in the vegetation recovery potential evaluation value of the flowing sandy land of the alpine valley is within the range of the multi-level comment threshold;
determining a membership function:
after determining the corresponding assessment levels of the 15 evaluation factors in the evaluation information of the vegetation restoration potential of the flowing sand land in the alpine valley, establishing an evaluation standard system and a value interval list of the evaluation standard system in 5 levels, and determining membership functions of the 5 assessment levels of the evaluation factors;
selecting the evaluation standard system and the interval intermediate value of each evaluation factor in the value interval list of the evaluation standard system in 5 levels as the standard value of the index in each level, and calculating by utilizing the membership function to obtain the standard value Sij of the ith index in the jth level, wherein i is 1, 2, 3 … and 15; j ═ 1, 2, …, 5;
the membership function types of the 15 evaluation factors can be classified into 3 types, that is: (1) annual precipitation amount C1, soil moisture C7, soil organic matter C9, soil total nitrogen C10, slope direction C6, soil texture C11, fence sealing C14, biological species selection C13 and ground treatment C15 belong to withdrawal type for a membership function of grade 1;
(2) the elevation C4 and the gradient C5 belong to the abstinence type for the membership function of the level 1;
(3) the annual average air temperature C2, the annual sunshine hours C3, the soil pH value C8 and the sand dune ground temperature C12 belong to a symmetrical type for a membership function of the grade 1;
establishing a fuzzy evaluation matrix:
solving the membership degree of each evaluation factor belonging to different comment levels, and establishing a fuzzy evaluation matrix R;
the method comprises the following steps of setting i indexes participating in vegetation recovery potential evaluation, wherein a vegetation recovery potential evaluation standard consists of j levels, and because the vegetation recovery potential condition and the vegetation recovery potential grading standard are fuzzy, grading boundaries are properly divided by using membership degrees;
let Rij denote the possibility that the vegetation recovery potential value of the ith index can be evaluated as the jth grade, so that a fuzzy relation matrix R between the vegetation recovery potential evaluation index and the grade is formed; determining a fuzzy relation matrix R of an evaluation index layer of the vegetation restoration potential of the alpine sandy land according to an evaluation object measured value and an evaluation standard value of the vegetation restoration of the flowing sandy land and a membership function algorithm;
wherein m represents the number of evaluation indices i ═ 1, 2, … …, 15; n represents the vegetation restoration potential level, i.e. j is 1, 2, 3, 4, 5; the membership degree of i to j is the membership function;
constructing a fuzzy comprehensive evaluation model:
establishing a fuzzy comprehensive evaluation model:
wherein,is a fuzzy comprehensive operator, which is called fuzzy operator in fuzzy mathematics; fuzzy operators come in many forms, with the most common cases being the "size operators" and the "multiply-and-sum operators";
combining weight sets W21, W22, W23, W24 and W1 determined by an analytic hierarchy process, constructing a fuzzy comprehensive evaluation criterion layer model of vegetation recovery potential in the alpine sandy area based on a fuzzy comprehensive evaluation model, and obtaining a fuzzy relation matrix list of criterion layer evaluation;
according to the fuzzy relation matrix list evaluated by the criterion layer, obtaining membership values corresponding to different levels under the constraint of four different conditions, namely climate condition information B1, terrain condition information B2, soil condition information B3 and recovery status information B4, in the criterion layer, and judging the capability of vegetation recovery potential under four different conditions according to the membership values;
the fuzzy relation matrix of the criterion layer evaluation is as follows:
climate conditions:
topographic conditions:
the soil condition is as follows:
and (4) recovering the current situation:
determining a fuzzy comprehensive evaluation target layer model of the vegetation recovery potential in the alpine sand areas, and obtaining a fuzzy relation matrix list of target layer evaluation:
obtaining membership values of different grades corresponding to 15 evaluation factors specifically included in four conditions in the target layer according to the fuzzy relation matrix list evaluated by the target layer, and judging the capability of vegetation restoration potential under the specific evaluation factors under the four conditions according to the membership values corresponding to the evaluation factors;
the fuzzy relation matrix of the target layer evaluation is as follows:
preferably, the evaluation information of the vegetation restoration potential of the sand flowing in the alpine valley comprises five comment levels; in turn, strong, i.e., class I, strong, i.e., class II, generally, i.e., class III, weak, i.e., class IV, and very weak, i.e., class V.
Compared with the prior art, the embodiment of the invention has the advantages that:
the invention provides a method for evaluating the vegetation recovery potential of alpine sandy land, which can be known by analyzing the principle: by using a layer-by-layer analysis method, the vegetation restoration potential evaluation model is constructed to serve as a decision support tool, so that basic information of an ecological restoration object can be provided for environment protection and forestry ecological construction workers. Based on a vegetation restoration potential evaluation model established by the research, on the basis of community succession stage division and restoration target determination, 15 evaluation indexes (namely evaluation factors) are selected from four constraint conditions (namely climate condition information B1, terrain condition information B2, soil condition information B3 and restoration status information B4), and the vegetation restoration potential evaluation of the flowing sand is developed. When fuzzy mathematics is used for dividing the recovery potential grades, the ambiguity of information is overcome, the quantization problems of quantitative and qualitative indexes in the vegetation recovery process are solved, and a comprehensive evaluation model of the vegetation recovery potential of the high and cold valley flowing sand is initially established. According to 15 evaluation factors (namely index values) of four aspects of specified weather conditions, terrain conditions, soil conditions and current restoration situations, through calculation, membership values of the four aspects in the criterion layer can be calculated and output respectively; and membership values of 15 evaluation factors included in the target layer; according to the membership value, four different conditions (four different aspects) of fuzzy comprehensive evaluation and the vegetation recovery potential under 15 evaluation factors can be obtained; the vegetation recovery potential can serve as evaluation data for a user, and guides and influences the evaluation and establishment of the vegetation recovery policy of the user on the alpine sandy land.
Drawings
Fig. 1 is a schematic flow chart of a method for evaluating vegetation restoration potential in alpine sandy land according to an embodiment of the present invention;
fig. 2 is a schematic structural relationship diagram of a hierarchical structure model for evaluating vegetation recovery potential of sand areas flowing in alpine valley in the method for evaluating vegetation recovery potential of alpine sand areas provided by the embodiment of the invention.
Detailed Description
The present invention will be described in further detail below with reference to specific embodiments and with reference to the attached drawings.
Referring to fig. 1, an embodiment of the present invention provides a method for evaluating vegetation recovery potential in alpine sandy land, including the following steps:
s100, determining a vegetation recovery target of the alpine region according to habitat conditions of different types of sand lands in the alpine region;
s200, establishing a hierarchical structure model for evaluating the recovery potential of different types of sandy vegetation by using an analytic hierarchy process;
s300, constructing a judgment matrix, a hierarchical single-rank sequence table and a hierarchical total rank table by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation;
and S400, carrying out comprehensive evaluation calculation on the recovery potential of the vegetation in the different types of sandy land by using a fuzzy comprehensive evaluation method.
In the embodiment of the invention, a vegetation restoration potential evaluation model is constructed by using a layer-by-layer analysis method and can be used as a decision support tool to provide basic information of ecological restoration objects for environment protection and forestry ecological construction workers. Based on a vegetation restoration potential evaluation model established by the research, on the basis of community succession stage division and restoration target determination, 15 evaluation indexes (namely evaluation factors) are selected from four constraint conditions (namely climate condition information B1, terrain condition information B2, soil condition information B3 and restoration status information B4), and the vegetation restoration potential evaluation of the flowing sand is developed. When fuzzy mathematics is used for dividing the recovery potential grades, the ambiguity of information is overcome, the quantization problems of quantitative and qualitative indexes in the vegetation recovery process are solved, and a comprehensive evaluation model of the vegetation recovery potential of the high and cold valley flowing sand is initially established. According to the four designated index values of the climate condition, the terrain condition, the soil condition and the current restoration situation, the overall evaluation of the four aspects and the degrees of superiority and inferiority and vegetation restoration potential of the 15 indexes can be respectively output through calculation.
In the step S200, the establishing of the hierarchical structure model for evaluating the recovery potential of the different types of sandy vegetation by using the analytic hierarchy process specifically includes the following steps:
selecting the four aspects of climate condition information, terrain condition information, soil condition information and current restoration situation information as basic indexes for evaluating vegetation restoration potential of the flowing sandy land of the alpine valley;
constructing different types of hierarchical structure models of sandy land vegetation recovery potential evaluation by adopting an analytic hierarchy process according to basic indexes of the vegetation recovery potential evaluation of the sandy land vegetation flowing in the alpine valley; the fuzzy evaluation is divided into three levels, namely a target layer A, a criterion layer B and an index layer C, wherein:
the target layer A is the highest level of the hierarchical structure, namely the evaluation value of the vegetation recovery potential of the flowing sand land of the alpine valley is realized;
the criterion layer B is a main system layer for ensuring the realization of the overall target and is divided into climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4; the index layer is the most basic hierarchical structure and comprises specific evaluation factors of climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4;
wherein: the climate condition information B1 comprises an evaluation factor set of annual precipitation C1, annual average air temperature C2 and annual sunshine duration C3; the terrain condition information B2 comprises evaluation factor sets of an altitude C4, a gradient C5 and a slope direction C6; the soil condition information B3 comprises evaluation factor sets of soil moisture C7, soil pH value C8, soil organic matter C9, soil total nitrogen C10, soil texture C11 and sand dune ground temperature C12; the current restoration information B4 is suitable for evaluation factor sets of biological species selection C13, fence enclosure cultivation C14 and ground treatment C15;
the evaluation factor set is as follows: b1 ═ C1, C2, C3, B2 ═ C4, C5, C6, B3 ═ C7, C8, C9, C10, C11, C12, B4 ═ C13, C14, C15; a ═ B1, B2, B3, B4 }.
In the step S300, a judgment matrix, a hierarchical single-row sequence table and a hierarchical total-row sequence table are constructed by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, and the method specifically includes the following steps:
starting from an index layer in the hierarchical structure model for evaluating the sandy vegetation restoration potential, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each evaluation factor in the index layer to the basic index of the upper-level standard layer, calculating the weight value of each evaluation factor by adopting a square root method, carrying out normalization operation, and calculating after consistency check to obtain a weight set (B-C) of the index layer to the standard layer: w21, W22, W23, W24; establishing a hierarchical single-row sequence table according to the calculated weight values of the evaluation factors;
from the criterion layer in the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each basic index in the criterion layer to a target layer at the upper stage, solving the weight value of each basic index by adopting a square root method, carrying out normalization operation, and obtaining a weight set (A-B) of the criterion layer to the target layer by calculation after consistency test: w1; establishing a hierarchical single-row sequence table according to the calculated weight values of the basic indexes;
multiplying the weight value of the index layer relative to the standard layer by the weight value of the standard layer relative to the target layer to obtain the weight W occupied by each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land of the alpine valley; and establishing a hierarchical total ranking list according to the weight of each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land in the alpine valley.
In the step S400, the comprehensive evaluation calculation of the recovery potential of the vegetation in different types of sandy land by using the fuzzy comprehensive evaluation method specifically includes the following steps:
presetting a comment threshold value corresponding to multiple levels for each evaluation factor;
determining vegetation recovery potential evaluation information of each evaluation factor in the flowing sandy land of the alpine valley according to the condition that the weight of each evaluation factor in the vegetation recovery potential evaluation value of the flowing sandy land of the alpine valley is within the range of the multi-level comment threshold;
determining a membership function;
establishing a fuzzy evaluation matrix;
constructing a fuzzy comprehensive evaluation model;
establishing a fuzzy comprehensive evaluation model; combining weight sets W21, W22, W23, W24 and W1 determined by an analytic hierarchy process, constructing a fuzzy comprehensive evaluation criterion layer model of vegetation recovery potential in the alpine sandy area based on a fuzzy comprehensive evaluation model, and obtaining a fuzzy relation matrix list of criterion layer evaluation;
according to the fuzzy relation matrix list evaluated by the criterion layer, obtaining membership values corresponding to different levels under the constraint of four different conditions, namely climate condition information B1, terrain condition information B2, soil condition information B3 and recovery status information B4, in the criterion layer, and judging the capability of vegetation recovery potential under four different conditions according to the membership values;
the fuzzy relation matrix of the criterion layer evaluation is as follows:
climate conditions:
topographic conditions:
the soil condition is as follows:
and (4) recovering the current situation:
determining a fuzzy comprehensive evaluation target layer model of the vegetation recovery potential in the alpine sand areas, and obtaining a fuzzy relation matrix list of target layer evaluation:
obtaining membership values of different grades corresponding to 15 evaluation factors specifically included in four conditions in the target layer according to the fuzzy relation matrix list evaluated by the target layer, and judging the capability of vegetation restoration potential under the specific evaluation factors under the four conditions according to the membership values corresponding to the evaluation factors;
evaluation of the target layerThe fuzzy relation matrix of (1) is:
preferably, the evaluation information of the vegetation restoration potential of the sand flowing in the alpine valley comprises five comment levels; in turn, strong, i.e., class I, strong, i.e., class II, generally, i.e., class III, weak, i.e., class IV, and very weak, i.e., class V.
The following is a detailed description of the above steps in the practice of embodiments of the invention:
the invention aims to: the method for evaluating the vegetation recovery potential in the alpine region is provided aiming at the problems that the vegetation recovery potential in different regions and different types of alpine sandy lands of the Qinghai-Tibet plateau is unclear, the evaluation method is basically blank, ecological recovery of the alpine sandy lands, effective prevention and control of valley sand storm disasters and the like are seriously restricted.
1. Evaluation object determination and type partitioning
Selecting 3 types of river beach flowing sand, river bank flowing sand and hillside flowing sand, and evaluating the vegetation recovery potential of different types of flowing sand of high and cold valleys in the middle trip of Yaluzan river, wherein the basic conditions are as follows:
(1) river shoal flowing sand land: the soil moisture is influenced by rainfall, river water level withering change and river valley sand wind activity, and the main types of the soil moisture comprise a flowing dune, a sand belt, a sand covering river beach land, a gentle gravel land and the like.
(2) River bank flowing sand land: the soil water is mainly supplied by rainfall and is less influenced by the change of river water level, and the main types of the soil water comprise crescent flowing sand dunes, low sand belts, flat gravel lands and grid sand dunes.
(3) Mountain slope flowing sand land: the movable sand land is distributed on the hills on both sides of the river valley, the midstream of the Yalu-Tibetan river is mainly distributed on the north bank, the soil moisture is mainly supplied by rainfall and is not influenced by the change of the river water level, and the main types of the movable sand dunes, the latticed sand dunes, the gravel land with a certain gradient and the like are included. The slope of the sand field is large, a windward slope, a leeward slope and a field between dunes can be divided, and the top of the sand dunes is not obvious and is often connected with the leeward slope and the windward slope.
2. Vegetation restoration targeting
On the basis of dividing vegetation succession stages (bare sand, sparse herbaceous, shrub transition and shrub community), determining vegetation recovery targets of sand of different types of alpine valleys based on natural geography outline of a research area according to vegetation succession sequences (pioneer stage, development stage and top community), namely establishing vegetation coverage capable of self-sustaining and plant community with stable ecological function.
3. Evaluation method for vegetation recovery potential
Firstly, a hierarchical structure, a structural judgment matrix, a hierarchical single ordering and consistency check thereof, a hierarchical total ordering and consistency check thereof of vegetation recovery potential evaluation are established by using an analytic hierarchy process, and the hierarchical ordering and the consistency check thereof are calculated by math software Matlab programming.
And secondly, carrying out comprehensive evaluation on the recovery potential of the vegetation in different types of flowing sand lands by using a fuzzy comprehensive evaluation method.
4. Construction of vegetation recovery potential comprehensive evaluation model
A. Selecting evaluation indexes:
in order to enable a vegetation recovery potential evaluation index system to reflect the vegetation recovery capability of different types of flowing sand lands of high and cold valleys more scientifically, objectively and reasonably. The following principles should be followed in the selection process of the evaluation index. (1) The substantivity is as follows: the factors selected should have a direct effect on vegetation recovery. (2) Universality: during vegetation restoration, some factor changes will respond equally to vegetation restoration. (3) Feasibility: when selecting the evaluation index, an index with relatively simple calculation should be selected.
4 aspects of climate conditions, terrain conditions, soil conditions, current restoration situations and the like are selected as basic indexes for evaluating the vegetation restoration potential of the flowing sand land of the alpine valley (figure 2). A hierarchical structure model for evaluating the vegetation recovery potential of different types of flowing sand is constructed by adopting an analytic hierarchy process, and fuzzy evaluation is divided into three levels, namely a target layer (A), a criterion layer (B) and an index layer (C). The evaluation factor set is as follows: b1 ═ C1, C2, C3, B2 ═ C4, C5, C6, B3 ═ C7, C8, C9, C10, C11, C12, B4 ═ C13, C14, C15; a ═ B1, B2, B3, B4 }.
The target layer is the highest level of the hierarchical structure, namely the evaluation of the vegetation recovery potential of different types of flowing sand lands of the alpine valley is realized; the criterion layer is a main system layer for ensuring the realization of the overall target and is divided into a climate condition, a terrain condition, a soil condition, a current recovery situation and the like; the index layer is the most basic hierarchical structure and comprises all factors for evaluating the vegetation recovery potential, and the factors are direct measurable factors for evaluating the vegetation recovery potential of the flowing sand land of the alpine valley.
B. Determination of the index weight:
and (3) calculating a weight value by comparing the relative importance of each two evaluation indexes by adopting an Analytic Hierarchy Process (AHP), and establishing a weight set W of each evaluation index in the vegetation restoration potential evaluation.
And (3) from the index layer, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each index to the previous layer, solving and normalizing the weight of each index, and obtaining a weight set of the index layer to the criterion layer after consistency check. The weight set of the criterion layer to the target layer is determined in the same way. And obtaining weight sets W21, W22, W23 and W24 of the index layer to the criterion layer and a weight set W1 of the criterion layer to the target layer by an analytic hierarchy process.
(1) Structural judgment matrix
And (4) integrating related documents and expert scoring results to obtain judgment matrixes of the target layer, the standard layer and the index layer. The judgment matrix and weight of each index of the criterion layer relative to the target layer are shown in table 1.
Table 1: target layer-criterion layer (A-B) judgment matrix and calculation result
Calculated lambdamax4.1560, the off-consistency index CI is 0.0520, and the consistency index CR is 0.0578<0.1. According to the weight of each index, the evaluation of the vegetation recovery potential of the sand flowing in the alpine valley is greatly influenced by the weather conditions and the soil conditions.
(2) Hierarchical single ordering
The method firstly stratifies complex evaluation problems and decomposes the problems into different composition factors according to the nature of the problems and the target to be achieved.
Table 2: criterion layer-index layer (B-C) judgment matrix and calculation result
(3) And (3) overall hierarchical ordering:
the weight of each specific index relative to the criterion layer is multiplied by the weight of the criterion layer relative to the target layer, so that the weight of each index in the vegetation restoration potential evaluation of the flowing sand land of the alpine valley can be obtained (table 3). Among all indexes, the indexes with the weight occupying the first five positions are annual precipitation, soil moisture, enclosure cultivation, annual average temperature and sand dune ground temperature.
To sum up, the weight sets W21, W22, W23 and W24 of the index layer to the criterion layer are W21 ═ (0.6483, 0.2297, 0.1220), W22 ═ 0.3325, 0.1396, 0.5278, W23 ═ (0.4628, 0.0597, 0.0994, 0.0994, 0.0494, 0.2293), and W24 ═ 0.5396, 0.2970, 0.1634, respectively; the set of weights W1 for the criterion layer to the target layer is (0.4041, 0.0833, 0.3188, 0.1938).
Table 3: evaluation index weight of vegetation restoration potential of flowing sand land of alpine valley
C. Establishment of evaluation criteria:
(1) determination of comment set:
the comment set is a set of various evaluation results made by the evaluator on the evaluation object, and is denoted by V. The evaluation criterion is determined according to actual requirements, and the general grade is divided into 3 grades to 9 grades, namely a comment set V ═ { V1, V2, … …, Vm } (3 ≦ m ≦ 9). In the evaluation of the vegetation recovery potential of different types of flowing sand areas in alpine and cold valleys, let V ═ I, II, III, IV, V, and each comment represents { strong, general, weak, and very weak } respectively, and they represent 5 levels of the vegetation recovery potential from high to low. The weather condition and the terrain condition determine the satisfaction degree of vegetation growth on the flowing sandy land of the alpine valley to the congenital condition, and the soil condition and human interference activities determine the satisfaction degree of vegetation growth on the acquired condition. If the innate and acquired conditions of vegetation growth can be better met, vegetation growth is considered easier and the potential for vegetation restoration is greater.
(2) Establishment of an evaluation standard system:
according to the influence of each index on the vegetation recovery potential of the sand land flowing in the alpine valley, referring to expert opinions, an evaluation standard system and a value range of the evaluation standard system in 5 grades are determined (table 4).
TABLE 4 evaluation index section for vegetation recovery potential in flowing sand of high and cold valley
Note:＊indicating the expert scoring range.
D. Determination of membership functions:
the correct construction of membership functions is the key to fuzzy recognition. The establishment of membership functions does not have a mature and effective method at present, and most establishment methods are still based on experience and experiments. The methods for determining the membership degree of each index to the vegetation recovery potential grade (comment set) are different, and for different evaluation indexes, the expression of the membership function is different. For simplicity of calculation, it is considered to be a linear variation. The membership functions U (x) can be classified into the following 3 types:
(1) type of withdrawal: i.e., the larger x, the larger the value of U (x);
(2) and (3) ring-on type: i.e., the smaller x, the larger the value of U (x);
(3) symmetry: i.e., the values of x and u (x) are parabolic in shape.
The membership function types of the 15 evaluation factors can be classified into 3 types, that is: (1) annual precipitation amount C1, soil moisture C7, soil organic matter C9, soil total nitrogen C10, slope direction C6, soil texture C11, fence sealing C14, biological species selection C13 and ground treatment C15 belong to withdrawal type for a membership function of grade 1;
(2) the elevation C4 and the gradient C5 belong to the abstinence type for the membership function of the level 1;
(3) the annual average air temperature C2, annual sunshine hours C3, soil pH C8 and sand dune ground temperature C12 are symmetrical to the membership function of grade 1, and the type is intermediate proper.
And determining 5 grades of membership functions according to five grades of evaluation criteria of each index. The division of each index interval of vegetation recovery evaluation of the flowing sand land of the alpine valley determined in the embodiment of the invention is shown in a table 4. Selecting the interval intermediate value of each index in the table 4 as a standard value of the index in each level (table 5), and obtaining a standard value Sij of the ith index in the jth level, wherein i is 1, 2, 3 … and 15; j is 1, 2, …, 5.
Table 5: standard value of vegetation recovery evaluation index in various grades for alpine valley flowing sand land
(1) The formula of the membership function of the ring type is as follows:
wherein,the indexes i of the 1 st, k (k is 2, 3, 4) th and 5 th stages are membership functions, respectively. SikIndicating the standard value of the k-th order of the index i. x is the number ofiIndicates the measured value of the index.
(2) The membership function formula of the ring type is:
(3) the symmetric membership function formula is:
E. establishing a fuzzy evaluation matrix:
in evaluation of vegetation restoration potential, various specific indexes affecting vegetation restoration are objects to be evaluated. And (3) solving the membership degrees of different comments of each index belonging to the comment set by using the theoretical basis of fuzzy mathematics and necessary computational analysis, and establishing a fuzzy evaluation matrix R.
The index participating in the evaluation of the vegetation recovery potential is set to be i, the evaluation standard of the vegetation recovery potential consists of j levels, and the classification limit is proper to be classified by using the membership degree because the vegetation recovery potential condition and the classification standard of the vegetation recovery potential are fuzzy. Let Rij denote the possibility that the vegetation restoration potential value of the ith index can be evaluated as the jth grade (i.e. the membership degree of i to j, and the relationship between i and j is a membership function), so that a fuzzy relationship matrix R between the vegetation restoration potential evaluation index and the grade is formed.
Wherein m represents an evaluation index number i of 1, 2, … …, 15; n represents the vegetation restoration potential level, i.e., j ═ 1, 2, 3, 4, 5.
And determining a fuzzy relation matrix of an evaluation index layer of vegetation recovery potential of the high and cold valley, the beach flowing sand land, the bank flowing sand land and the hillside flowing sand land according to the evaluation object measured value and the evaluation standard value of vegetation recovery of the flowing sand land and a membership function algorithm (table 6).
Table 6: fuzzy relation matrix of index layer
F. Constructing a fuzzy comprehensive evaluation model:
the principle of hierarchical fuzzy comprehensive evaluation is as follows: and firstly, evaluating from the lowest layer, regarding the evaluation result of each layer as an evaluation set of the indexes of the upper layer to form an index evaluation matrix of the higher layer, and then comprehensively evaluating the higher layer until the evaluation of the highest layer is finished. When a hierarchical structure model is constructed, indexes considered in each layer are required to meet independence, and no dependency relationship exists. Therefore, the evaluation algorithm of each layer is the same, namely the fuzzy comprehensive evaluation model is as follows:
wherein,is a fuzzy synthesis operator, called fuzzy operator in fuzzy mathematics. Fuzzy operators come in many forms, with the most common cases being the "size operators" and the "multiply-and-sum operators".
Combining weight sets W21, W22, W23, W24 and W1 determined by a analytic hierarchy process, and constructing a fuzzy comprehensive evaluation criterion layer model of vegetation recovery potential in the flowing sand of the alpine valley based on a fuzzy comprehensive evaluation model as follows:
climate conditions:
topographic conditions:
the soil condition is as follows:
and (4) recovering the current situation:
the fuzzy comprehensive evaluation target layer model for the vegetation recovery potential of the sand flowing in the alpine valley is as follows:
for example, the following steps are carried out:
according to the method, aiming at the vegetation recovery potential of different types of flowing sand lands in alpine and cold river valleys, the fuzzy relation matrix evaluated on the criterion layer is shown in a table 7, and the fuzzy relation matrix evaluated on the target layer is shown in a table 8. And determining the strength of the vegetation recovery potential of different types of flowing sand lands of the alpine valley according to the maximum membership principle.
From the evaluation results of the criterion layer (table 7), the vegetation recovery potentials of the beach flowing sand land, the bank flowing sand land and the mountain slope flowing sand land under the constraint of the climate conditions are all the highest grade I membership degree (0.6483), and the vegetation recovery potentials are strong. Under the constraint of terrain conditions, the membership degrees of grade III revegetation potentials of the beach flowing sand land and the bank flowing sand land are the maximum (0.5471 and 0.5629 respectively), and the revegetation potentials are general; the grade I membership of the vegetation restoration potential of the hillside flowing sand land is the largest (0.3167), and the restoration potential is strong. The grade II membership of the vegetation restoration potential of the flowing sand of the beach under the restriction of the soil condition is the maximum (0.2962), and the restoration potential is strong; the grade IV of the revegetation potential of the riverbank flowing sand land has the maximum membership degree (0.5299), and the revegetation potential is weaker; grade III of the vegetation restoration potential of the hillside flowing sand is the highest in membership degree (0.4176), and the restoration potential is general. The grade II membership of the restoration potential of the vegetation of the riverbank flowing sand land under the restriction of the restoration status quo is the maximum (0.7986), and the restoration potential is strong; the grade III membership of the revegetation potential of the riverbank flowing sand land is the largest (0.6538), and the revegetation potential is general; grade II of vegetation restoration potential of the hillside flowing sand land has the largest membership degree (0.6297), and the restoration potential is stronger.
From the evaluation result of the target layer (table 8), the grade II membership of the restoration potential of the vegetation in the flowing sand of the river beach is the maximum (0.2869), and the restoration potential is strong; the grade IV of the revegetation potential of the riverbank flowing sand is the highest in membership degree (0.3296), and the revegetation potential is weaker; the grade I membership of the vegetation restoration potential of the hillside flowing sand land is the largest (0.2884), and the restoration potential is strong.
Table 7: fuzzy relation matrix of criterion layer
Table 8: fuzzy relation matrix of target layer
It should be noted that the membership belongs to the concept in the fuzzy evaluation function: the fuzzy comprehensive evaluation is a very effective multi-factor decision method for comprehensively evaluating things influenced by various factors, and is characterized in that the evaluation result is not absolutely positive or negative, but is represented by a fuzzy set.
It should be noted that the vegetation restoration potential evaluation model is constructed as a decision support tool, and can provide basic information of ecological restoration objects for environment protection and forestry ecological construction workers. The vegetation recovery potential evaluation model established based on the research shows that the evaluation result of the model can objectively and accurately reflect the vegetation recovery potentials of different types of flowing sand lands of the alpine valley through qualitative verification of actual conditions, and can provide core technical support for developing an evaluation system for the vegetation recovery potentials of the sand lands in the alpine regions, so that scientific decision basis can be provided for developing the vegetation recovery practices of different regions and different types of sand lands in the Qinghai-Tibet plateau by related departments of China and places.
Therefore, on the basis of community succession stage division and restoration target determination, 15 evaluation indexes are selected from four constraint conditions, and restoration potential evaluation of vegetation in the flowing sand is developed. When fuzzy mathematics is used for dividing the recovery potential grades, the ambiguity of information is overcome, the quantization problems of quantitative and qualitative indexes in the vegetation recovery process are solved, and a comprehensive evaluation model of the vegetation recovery potential of the high and cold valley flowing sand is initially established. According to the 15 evaluation factors (namely 15 index values) of the four aspects of the designated climate condition, the designated terrain condition, the designated soil condition and the designated current restoration situation, the overall evaluation of the four aspects and the degrees of superiority and inferiority and vegetation restoration potential of the 15 evaluation factors can be respectively output through calculation.
Obviously, the method for evaluating the vegetation recovery potential of the alpine sandy land establishes a target, evaluation indexes and evaluation standards for artificially promoting vegetation recovery of the alpine sandy land, establishes a comprehensive evaluation model of the vegetation recovery potential of the alpine sandy land under the habitat stress condition, and solves each evaluation factor to obtain the evaluation index weight of the vegetation recovery potential of the alpine valley flowing sandy land; determining a comment threshold value corresponding to each preset grade of evaluation factors; and determining the evaluation information of the vegetation recovery potential of the evaluation factors in the flowing sandy land of the alpine valley according to the condition that the weight of the evaluation factors in the evaluation value of the vegetation recovery potential of the flowing sandy land of the alpine valley is within the range of the multi-level comment threshold, and obtaining the overall evaluation of the quality degree and the vegetation recovery potential of 15 indexes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (2)
1. A method for evaluating vegetation restoration potential of alpine sandy land is characterized by comprising the following steps:
determining a vegetation recovery target of the alpine region according to habitat conditions of different types of sand lands;
establishing a hierarchical structure model for evaluating the recovery potential of different types of sandy vegetation by using an analytic hierarchy process;
constructing a judgment matrix, a hierarchical single-rank sequence table and a hierarchical total rank table by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation;
carrying out comprehensive evaluation calculation on the recovery potential of the vegetation in different types of sandy land by using a fuzzy comprehensive evaluation method;
the method for establishing the hierarchical structure model for evaluating the recovery potential of the vegetation in the sandy land by using the analytic hierarchy process specifically comprises the following steps:
selecting the four aspects of climate condition information, terrain condition information, soil condition information and current restoration situation information as basic indexes for evaluating vegetation restoration potential of the flowing sandy land of the alpine valley;
constructing different types of hierarchical structure models of sandy land vegetation recovery potential evaluation by adopting an analytic hierarchy process according to basic indexes of the vegetation recovery potential evaluation of the sandy land vegetation flowing in the alpine valley; the hierarchical structure model for evaluating the sandy vegetation restoration potential can be divided into three levels, namely a target layer A, a criterion layer B and an index layer C, wherein:
the target layer A is the highest level of the hierarchical structure, namely the evaluation value of the vegetation recovery potential of the flowing sand land of the alpine valley is realized;
the criterion layer B is a main system layer for ensuring the realization of the overall target and is divided into climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4; the index layer is the most basic hierarchical structure and comprises specific evaluation factors of climate condition information B1, terrain condition information B2, soil condition information B3 and current recovery information B4;
wherein: the climate condition information B1 comprises an evaluation factor set of annual precipitation C1, annual average air temperature C2 and annual sunshine duration C3; the terrain condition information B2 comprises evaluation factor sets of an altitude C4, a gradient C5 and a slope direction C6; the soil condition information B3 comprises evaluation factor sets of soil moisture C7, soil pH value C8, soil organic matter C9, soil total nitrogen C10, soil texture C11 and sand dune ground temperature C12; the current restoration information B4 is suitable for an evaluation factor set of biological species selection C13, fence enclosure cultivation C14 and ground treatment C15, wherein the evaluation factor set is a set formed by 15 evaluation factors;
the evaluation factor set is as follows: b1 ═ C1, C2, C3, B2 ═ C4, C5, C6, B3 ═ C7, C8, C9, C10, C11, C12, B4 ═ C13, C14, C15; a ═ B1, B2, B3, B4 };
constructing a judgment matrix, a level single-row sequence list and a level total-row sequence list by using the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, and specifically comprising the following steps of:
starting from an index layer in the hierarchical structure model for evaluating the sandy vegetation restoration potential, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each evaluation factor in the index layer to the basic index of the upper-level standard layer, solving the weight value of each evaluation factor, carrying out normalization operation, and calculating to obtain a weight set (B-C) of the index layer to the standard layer after consistency test: w21, W22, W23, W24; establishing a hierarchical single-row sequence table according to the calculated weight values of the evaluation factors;
from the criterion layer in the hierarchical structure model for evaluating the recovery potential of the sandy vegetation, forming a judgment matrix by adopting a pairwise comparison mode according to the importance of each basic index in the criterion layer to a target layer at the upper stage, solving the weight value of each basic index, carrying out normalization operation, and obtaining a weight set (A-B) of the criterion layer to the target layer through calculation after consistency test: w1; establishing a hierarchical single-row sequence table according to the calculated weight values of the basic indexes;
multiplying the weight value of the index layer relative to the standard layer by the weight value of the standard layer relative to the target layer to obtain the weight W occupied by each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land of the alpine valley; establishing a hierarchical total ranking list according to the weight of each evaluation factor in the evaluation value of the vegetation restoration potential of the flowing sand land of the alpine valley;
the comprehensive evaluation calculation of the recovery potential of the vegetation in the sandy land of different types by using the fuzzy comprehensive evaluation method specifically comprises the following steps:
presetting comment threshold values corresponding to different levels for each evaluation factor;
determining vegetation recovery potential evaluation information of each evaluation factor in the flowing sandy land of the alpine valley according to the condition that the weight of each evaluation factor in the vegetation recovery potential evaluation value of the flowing sandy land of the alpine valley is within the range of the multi-level comment threshold;
determining a membership function:
after determining the corresponding assessment levels of the 15 evaluation factors in the evaluation information of the vegetation restoration potential of the flowing sand land in the alpine valley, establishing an evaluation standard system and a value interval list of the evaluation standard system in 5 levels, and determining membership functions of the 5 assessment levels of the evaluation factors;
selecting the evaluation standard system and the interval intermediate value of each evaluation factor in the value interval list of the evaluation standard system in 5 levels as the standard value of the index in each level, and calculating by utilizing the membership function to obtain the standard value Sij of the ith index in the jth level, wherein i is 1, 2, 3 … and 15; j ═ 1, 2, …, 5;
the membership function types of the 15 evaluation factors can be classified into 3 types, that is: (1) annual precipitation amount C1, soil moisture C7, soil organic matter C9, soil total nitrogen C10, slope direction C6, soil texture C11, fence sealing C14, biological species selection C13 and ground treatment C15 belong to withdrawal type for a membership function of grade 1;
(2) the elevation C4 and the gradient C5 belong to the abstinence type for the membership function of the level 1;
(3) the annual average air temperature C2, the annual sunshine hours C3, the soil pH value C8 and the sand dune ground temperature C12 belong to a symmetrical type for a membership function of the grade 1;
establishing a fuzzy evaluation matrix:
solving the membership degree of each evaluation factor belonging to different comment levels, and establishing a fuzzy evaluation matrix R;
the method comprises the following steps of setting i indexes participating in vegetation recovery potential evaluation, wherein a vegetation recovery potential evaluation standard consists of j levels, and because the vegetation recovery potential condition and the vegetation recovery potential grading standard are fuzzy, grading boundaries are properly divided by using membership degrees;
let Rij denote the possibility that the vegetation recovery potential value of the ith index can be evaluated as the jth grade, so that a fuzzy relation matrix R between the vegetation recovery potential evaluation index and the grade is formed; determining a fuzzy relation matrix R of an evaluation index layer of the vegetation restoration potential of the alpine sandy land according to an evaluation object measured value and an evaluation standard value of the vegetation restoration of the flowing sandy land and a membership function algorithm;
wherein m represents the number of evaluation indices i ═ 1, 2, … …, 15; n represents the vegetation restoration potential level, i.e. j is 1, 2, 3, 4, 5; the membership degree of i to j is the membership function;
constructing a fuzzy comprehensive evaluation model:
establishing a fuzzy comprehensive evaluation model:
wherein,is a fuzzy comprehensive operator, which is called fuzzy operator in fuzzy mathematics; fuzzy operators come in many forms, with the most common cases being the "size operators" and the "multiply-and-sum operators";
combining weight sets W21, W22, W23, W24 and W1 determined by an analytic hierarchy process, constructing a fuzzy comprehensive evaluation criterion layer model of vegetation recovery potential in the alpine sandy area based on a fuzzy comprehensive evaluation model, and obtaining a fuzzy relation matrix list of criterion layer evaluation;
according to the fuzzy relation matrix list evaluated by the criterion layer, obtaining membership values corresponding to different levels under the constraint of four different conditions, namely climate condition information B1, terrain condition information B2, soil condition information B3 and recovery status information B4, in the criterion layer, and judging the capability of vegetation recovery potential under four different conditions according to the membership values;
the fuzzy relation matrix of the criterion layer evaluation is as follows:
climate conditions:
topographic conditions:
the soil condition is as follows:
and (4) recovering the current situation:
determining a fuzzy comprehensive evaluation target layer model of the vegetation recovery potential in the alpine sand areas, and obtaining a fuzzy relation matrix list of target layer evaluation:
obtaining membership values of different grades corresponding to 15 evaluation factors specifically included in four conditions in the target layer according to the fuzzy relation matrix list evaluated by the target layer, and judging the capability of vegetation restoration potential under the specific evaluation factors under the four conditions according to the membership values corresponding to the evaluation factors;
the fuzzy relation matrix of the target layer evaluation is as follows:
2. the method of claim 1, wherein the method comprises the steps of,
the evaluation information of the vegetation restoration potential of the flowing sand land of the alpine valley comprises five comment levels; in turn, strong, i.e., class I, strong, i.e., class II, generally, i.e., class III, weak, i.e., class IV, and very weak, i.e., class V.
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