CN106202852B - Space quantitative identification method for climate sensitive zone type of vegetation ecosystem - Google Patents
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Abstract
The invention discloses a novel space quantitative identification method for a climate sensitive zone type of a vegetation ecosystem, which comprises the following three steps: firstly, expanding an HLZ model classification system and constructing a judgment standard of a vegetation ecosystem climate sensitive zone type; secondly, performing spatial interpolation simulation on the climate data by using a high-precision curved surface modeling (HASM) method to obtain parameter data such as average biological temperature, average precipitation, potential evapotranspiration rate and the like on each grid; and finally, operating a space quantitative identification model of the type of the vegetation ecosystem climate sensitive zone, judging whether each grid unit belongs to the climate sensitive zone, and finishing the type assignment of the type of the vegetation ecosystem climate sensitive zone and the quantitative identification and rapid extraction of the space pattern of the vegetation ecosystem climate sensitive zone. The method can effectively carry out quantitative identification and extraction on the climate sensitive zone type and the spatial pattern of the vegetation ecosystem, and has strong operability and practicability.
Description
Technical Field
The invention relates to a space quantitative identification method for climate sensitive zone types of a vegetation ecosystem, which is suitable for the field of global climate change and ecological effect research.
Background
The vegetation ecosystem climate sensitive zone is used as an area most sensitive to climate change and human activities, more importantly, the species abundance of the vegetation ecosystem climate sensitive zone on the landscape level is higher than that of the adjacent non-sensitive zone area, and the space-time change condition of the ecosystem structure and pattern can reflect the influence of the climate change on the ecosystem more directly. The dynamic change and fluctuation of the boundary range of the climate sensitive zone of the vegetation ecosystem are the comprehensive response results of the land ecosystem to the natural climate change and the action of human activities. Therefore, the type of the climate sensitive zone of the vegetation ecosystem and the change of the spatial distribution pattern thereof need to be concerned more than those of a non-sensitive zone, and even to a certain extent, the space-time change of the climate sensitive zone of the vegetation ecosystem plays an important role in indicating the global change research. The space quantitative identification of the vegetation ecosystem climate sensitive zone type has important significance for improving global change adaptability strategy and slowing down the influence of climate change on the vegetation type and coverage change thereof.
At present, a great amount of observation statistical analysis and micro-scale process simulation are carried out on climate change response of a vegetation ecosystem at home and abroad, but the space analysis and quantitative identification of the vegetation ecosystem at the mesoscale and macro-scale are still in the starting stage. In addition, while considerable progress has been made in the quantitative analysis of the types of vegetation ecosystems and their patterns against the background of global climate change, these studies have rarely involved the quantitative identification and analysis studies of their climate sensitive zone types and their spatial distribution patterns. For example, although the Holdridge Life Zone (HLZ) model (Holdridge, l.r., 1947, Determination of world plant formats from simple simulation data. science105(2727), 367-368.) is currently widely used globally, it cannot be directly used for quantitative identification and simulation of climate sensitive zone types in vegetation ecosystems. Since the 20 th century 70 old generation scientists in China determine the three-level sensitive zone and the approximate range of the spatial distribution of the three-level sensitive zone according to a large amount of comprehensive geological investigation, statistical analysis and expert experience knowledge, most researchers do not quantitatively determine and analyze whether the researched range belongs to the climate sensitive zone and which type of climate sensitive zone of the vegetation ecosystem while researching the ecosystem sensitivity of the climate sensitive zone of the vegetation ecosystem. That is to say, domestic statistical analysis and research on vulnerability and climate sensitivity of the ecosystem in or adjacent to the sensitive zone area of the vegetation ecosystem are more, especially mainly focus on the field of systematic analysis and research on vegetation-climate interaction mechanisms, and quantitative identification and spatial analysis of the type of the climate sensitive zone of the vegetation ecosystem are very rare.
Therefore, in order to construct a space quantitative identification rule of the type of the vegetation ecosystem climate sensitive zone and realize quantitative extraction and space mapping of the space distribution pattern of the type of the vegetation ecosystem climate sensitive zone, a scientific and effective space quantitative identification method is urgently needed to be constructed. The invention provides a space analysis method suitable for quantitative identification of a vegetation ecosystem climate sensitive zone, aiming at the model limitation that the model parameters of an HLZ model are discrete points rather than continuous space grid units, and on the basis of the expansion of a model classification mechanism. The method not only makes up the defect that the original model only utilizes discrete point data as the input parameters of the model, but also can effectively carry out quantitative recognition and extraction on the climate sensitive zone type and the spatial distribution pattern of the vegetation ecological system through the expansion and derivation of the model judgment mechanism, and has strong operability.
Disclosure of Invention
The invention aims to provide a space quantitative identification method of a vegetation ecosystem climate sensitive zone type by correcting and expanding an HLZ model and combining other space simulation methods, so that the quantitative identification and the rapid extraction of the vegetation ecosystem climate sensitive zone type and the space distribution pattern on a macroscopic scale are realized, the scientific problem of how to quantitatively identify and extract the vegetation ecosystem climate sensitive zone type and the space distribution range thereof is solved, and a method and a technical support are provided for deeply researching and exploring the response of an ecosystem to global climate change. In order to achieve the purpose, the key technical scheme adopted by the invention comprises the following steps:
the whole technical process is mainly divided into three steps, firstly, the classification mechanism of an HLZ model is expanded, and the judgment standard of the type of the vegetation ecosystem climate sensitive zone is constructed; secondly, preprocessing climate data observed by a weather station for a long time, performing spatial simulation by using a high-precision curved surface modeling (HASM) method, and obtaining parameter data such as the average biological temperature of each year, the average precipitation of each year, the potential evapotranspiration ratio and the like on each grid unit in a research area on the basis of spatial statistical analysis; and finally, taking high-quality climate parameter spatial data and judgment standards of various climate sensitive zones as model input parameters, operating a spatial quantitative recognition and analysis model of the type of the climate sensitive zone of the vegetation ecosystem, and spatially realizing judgment, type assignment and spatial distribution pattern extraction of whether each grid unit belongs to the climate sensitive zone.
The method comprises the following steps of firstly, obtaining a judgment parameter for quantitatively identifying the type of a climate sensitive zone of a vegetation climate ecological system, and realizing the judgment through the following three steps;
1-1) expanding an HLZ model, and constructing a judgment standard for quantitatively identifying the type of a climate sensitive zone of a vegetation ecosystem;
1-2) dividing and defining the climate sensitive zone type of each vegetation ecosystem;
1-3) solving the boundary threshold value of each discrimination parameter of each type of vegetation ecosystem weather sensitive zone.
Secondly, acquiring climate data of high spatial resolution in a research area, and realizing the climate data through the following three steps;
2-1) collecting long-term observation data of a meteorological observation station in a research area, and converting the long-term observation data into spatial attribute data after preprocessing;
2-2) performing high-precision spatial simulation on the climate data by using a high-precision curved surface modeling method (HASM) to obtain annual average biological temperature data and annual average precipitation data;
2-3) obtaining average potential evapotranspiration ratio data by using a spatial statistical method.
And thirdly, space quantitative identification of the type of the climate sensitive zone of the vegetation ecosystem is realized through the following two steps.
3-1) establishing a space quantitative identification model of the vegetation ecosystem climate sensitive zone type, and quantitatively judging whether each grid of the research area belongs to a transition area or not to obtain space areas of various vegetation ecosystem climate sensitive zone types;
and 3-2) carrying out quantitative determination and assignment on the types and the spatial distribution of the climate sensitive zones of the vegetation ecosystems in the whole research area by using the boundary threshold of the types of the climate sensitive zones of each type of vegetation ecosystems, further obtaining the spatial distribution range of the climate sensitive zones of various types of vegetation ecosystems, and outputting the identification result.
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FIG. 1 is a schematic main flow diagram of the present invention
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
The invention discloses a space quantitative identification method of a vegetation ecosystem climate sensitive zone type, which comprises the following steps:
firstly, obtaining a judgment standard for quantitatively identifying the type of a climate sensitive zone of a vegetation climate ecological system;
secondly, obtaining climate parameter data with high spatial resolution;
and thirdly, space quantitative identification of the type of the climate sensitive zone of the vegetation ecosystem.
The specific steps are detailed below:
and obtaining judgment parameters for quantitatively identifying the type of the climate sensitive zone of the vegetation climate ecological system. On the basis of improving parameter formats and operation modes of HLZ models, regular triangles formed by intersecting average biological temperature, average rainfall and potential evapotranspiration rate scale lines in classification systems are defined as vegetation ecosystem climate sensitive zones (intersecting zones of adjacent regular hexagons in original HLZ models), so that a theoretical discrimination system of the vegetation ecosystem climate sensitive zone types is established. The specific calculation method comprises the following steps: calculating the boundary threshold value of the annual average biological temperature of the climate sensitive zone of each type of vegetation ecosystems according to the redefined vegetation ecosystem climate sensitive zone discrimination system (
Boundary threshold in ℃) and annual average precipitation
In mm) and a boundary threshold for potential evapotranspiration ratio: (
). For example, the boundary thresholds of the annual average biological temperature, the annual average precipitation and the potential evapotranspiration ratio of the climate sensitive zone types of the desert shrubs in the cold temperature zone, the grassland and the northern drought shrubs are respectively more than 6.0 ℃, less than 250mm and less than 2.00), so as to construct a judgment standard set for quantitatively identifying the boundary thresholds of the climate transition zone types of all vegetation ecosystems, wherein the whole set comprises the judgment standard values of the climate sensitive zone types of 49 vegetation ecosystems.
And acquiring high-spatial resolution climate parameter data. The spatial resolution and the data precision of the climate data are directly related to the accuracy of the quantitative identification of the type of the climate sensitive zone of the vegetation ecosystem. According to the method, a HASM method with climate data spatial simulation precision far higher than that of traditional classical interpolation models such as an inverse distance weighting model (IDW), a triangulation network model (TIN), a Kriging model (Kriging) and a Spline interpolation model (Spline) is selected, and high-precision spatial simulation of annual average biological temperature and average rainfall is achieved. The HASM method is a method for modeling a curved surface by applying the basic theorem of the curved surface theory to solve the error problem of the conventional curved surface modeling method. For spatial grid (x)i，yj) I is greater than or equal to 0 and less than or equal to I +1, and J is greater than or equal to 0 and less than or equal to J +1, and the HASM method based on the Gaussian equation can be expressed as a least squares problem of equality constraints (Yue TX. surface modeling: high Accuracy and High speed methods.New York: CRC Press, 2011):
in the formula (1), S is belonged to RK×(I*J)And t ∈ RK×1Respectively is a sampling matrix and a sampling vector, and K is the number of sampling points.
On the basis of obtaining high spatial resolution grid data of the annual average biological temperature and the average precipitation in the research area range, a scatter statistical empirical formula (Holdridge, L.R., 1947.Determination of world plant formats from spatial distribution data 105(2727), 367 and 368.) among the annual average biological temperature, the average precipitation and the potential evapotranspiration ratio is applied to spatial statistical analysis, and corresponding potential evapotranspiration ratio spatial distribution data in the research area range are obtained through calculation, so that high spatial resolution and high-precision climate parameter data required by a vegetation ecosystem climate sensitive zone type spatial quantitative identification model are finally obtained. The spatial calculation formula of the corrected potential evapotranspiration ratio according to the annual average biological temperature and the average precipitation can be expressed as:
PER (x, y), MAB (x, y) and TAP (x, y) in equation (2) are the potential evapotranspiration ratio, the annual average biological temperature and the potential evapotranspiration ratio of the spatial grid unit (x, y), respectively.
And (4) quantitatively identifying the type of the climate sensitive zone of the vegetation climate ecosystem. In the implementation process of the step, firstly, a spatial analysis model of the climate sensitive zone type of the vegetation ecosystem on the grid level is constructed according to the discrimination standard value of the climate sensitive zone type of the 49-type vegetation ecosystem established in the step one, and a spatial discrimination calculation formula can be expressed as follows:
VECSZ (x, y) in equation (3) represents the assignment type of vegetation ecosystem climate sensitive zone of spatial grid cell (x, y) point. When PER (x, y), MAB (x, y) and TAP (x, y) at the space grid unit (x, y) do not meet the discrimination standard of any type of vegetation ecosystem climate sensitive zone type, the VECSZ (x, y) value at the space grid unit (x, y) is assigned to be 0, which indicates that the vegetation ecosystem type at the grid unit (x, y) does not belong to the climate sensitive zone; assigning the VECSZ (x, y) value at the spatial grid cell (x, y) to a corresponding climate sensitive zone type if the PER (x, y), MAB (x, y) and TAP (x, y) at the grid cell (x, y) meet the criteria for any of the 49-class vegetation ecosystem climate sensitive zone types. In the model and all quantitative judging processes, the model and all the quantitative judging processes are realized by utilizing program design and algorithm programming on a grid level, and the model and all the quantitative judging processes are compared with an identification standard set of a vegetation ecosystem climate sensitive zone type by utilizing an identification standard and a judging rule, so that each grid unit is judged, identified and assigned until the judgment and identification of all the grid units are completed. Finally, the quantitative identification of the types of the climate sensitive zones and the spatial distribution patterns of all vegetation ecosystems in the whole research area is obtained.
The research result of the method for identifying and automatically extracting the climate sensitive zone type and the spatial distribution of the national vegetation ecosystem shows that the simulation result of the method can well and automatically identify and extract the three-level climate sensitive zone and the spatial distribution of the Chinese vegetation ecosystem, which are pre-researched in China by scientists such as leaf Vaccinium uliginosum and the like (the leaf Vaccinium uliginosum is compiled mainly, the pre-research in China global changes, Beijing: weather publisher, 1992), namely: 1) a vegetation ecosystem and a climate sensitive zone/farming and pasturing interlaced zone, which is in transition from arid/semiarid climate extending from the east of inner Mongolia to the southwest of Qinghai-Tibet plateau to southeast humid/semihumid monsoon climate, are called as a first-level sensitive zone; 2) desert/grassland/alpine vegetation ecosystem sensitive belts from the west side of the Ordos plateau to the vicinity of Lanzhou/Xining and from the north foot of the Qinghai-Tibet plateau to the border of the west of China are called secondary sensitive belts; 3) the vegetation ecosystems climate sensitive zones distributed in the eastern forest vegetation area of China from north to south among the coniferous forest in the cold temperate zone/the coniferous broadleaf mixed forest in the warm zone/the deciduous broadleaf forest in the warm zone/the evergreen broadleaf forest in the subtropical zone/the rainforest in the tropical zone are called as three-level sensitive zones. The method can automatically identify and extract the climate sensitive zones of the three vegetation ecosystems, and can also automatically identify and extract the climate sensitive zones of the alpine vegetation ecosystems distributed in the Qinghai-Tibet plateau.
Claims (1)
1. A space quantitative identification method for a vegetation ecosystem climate sensitive zone type comprises the following steps:
the method comprises the following steps of firstly, obtaining a judgment parameter for quantitatively identifying the type of a climate sensitive zone of a vegetation climate ecosystem, and realizing the judgment through the following three steps:
1-1) expanding an HLZ model, and constructing a judgment standard for quantitatively identifying the type of a climate sensitive zone of a vegetation ecosystem;
1-2) dividing and defining the climate sensitive zone type of each vegetation ecosystem;
1-3) solving the boundary threshold value of each discrimination parameter of each type of vegetation ecosystem weather sensitive zone;
and secondly, acquiring climate data of high spatial resolution of the research area, and realizing the following three steps:
2-1) collecting long-term observation data of a meteorological observation station in a research area, and converting the long-term observation data into spatial attribute data after preprocessing;
2-2) carrying out high-precision space simulation on the climate data by using a high-precision curved surface modeling (HASM) method to obtain annual average biological temperature data and annual average precipitation data, wherein the high-precision curved surface modeling (HASM) method carries out curved surface modeling by using a curved surface theory basic theorem and aims at a space grid (x)i，yj) I is more than or equal to 0 and less than or equal to I +1, J is more than or equal to 0 and less than or equal to J +1, and the high-precision curve modeling method based on the Gaussian equation can be expressed as a least square problem of equation constraint:
in which S is an element of RK×(I*J)And t ∈ RK×1Respectively is a sampling matrix and a sampling vector, and K is the number of sampling points;
2-3) applying a spatial statistical method according to the formula
Obtaining average potential evapotranspiration ratio data, wherein PER (x, y), MAB (x, y) and TAP (x, y) are respectively the potential evapotranspiration ratio, the annual average biological temperature and the annual average precipitation of a spatial grid unit (x, y), wherein a scatter point statistical empirical formula among the annual average biological temperature, the annual average precipitation and the potential evapotranspiration ratio is applied to the spatial statistical method, corresponding potential evapotranspiration ratio spatial distribution data in a research area range are obtained through calculation, and the high-spatial-resolution climate data required by the vegetation ecosystem climate sensitive zone type spatial quantitative identification model is obtained；
And thirdly, space quantitative identification of the type of the climate sensitive zone of the vegetation ecosystem is realized by the following two steps:
3-1) establishing a space quantitative identification model of the vegetation ecosystem climate sensitive zone type, and quantitatively judging whether each grid of the research area belongs to a transition area or not to obtain space areas of various vegetation ecosystem climate sensitive zone types;
and 3-2) quantitatively judging and assigning the types and the spatial distribution of the climate sensitive zones of the vegetation ecosystems in the whole research area by using the boundary threshold of the types of the climate sensitive zones of each type of the vegetation ecosystems, assigning VECSC (x, y) values at the spatial grid units (x, y) to the types of the climate sensitive zones of the vegetation ecosystems according to whether PER (x, y), MAB (x, y) and TAP (x, y) meet the judgment standard of any climate sensitive zone of the vegetation ecosystems, further obtaining the spatial distribution range of the climate sensitive zones of various vegetation ecosystems, and outputting the identification result.
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