A method of normalizing the proportion of plant water sources

Abstract

This invention relates to the field of plant water source ratio calculation technology, and discloses a normalized method for calculating the plant water source ratio, comprising the following steps: S1, data acquisition, determining the isotopic composition of xylem water and soil water in each layer through stable water isotope analysis; S2, contribution ratio calculation, calculating the contribution ratio of each soil layer to plant water; S3, water source score calculation, calculating the water source score WSS according to the formula; S4, evaluation and application, constructing the relationship with ecosystem variables through the WSS score. By normalizing the water source score WSS value from 0 to 1, and eliminating absolute depth differences through mathematical standardization, the research results of different regions or different soil stratification schemes are directly comparable, thereby solving the defect of traditional methods that cannot be compared horizontally due to the subjectivity of depth boundaries, and realizing an objective comparison of the degree of plant deep water dependence across regions.

Description

Technical Field

[0001] This invention relates to the field of plant water source ratio calculation technology, specifically a method for calculating the normalized plant water source ratio. Background Technology

[0002] Research on plant water sources is crucial for understanding plant strategies for adapting to environmental stress. Traditional methods rely on stable water isotopes (δ²H and δ¹H). 8 O) Analyze the proportion of soil moisture utilization by plants at different depths, but the results are difficult to compare across different studies due to the subjectivity of soil stratification (e.g., 0-10cm, 10-30cm, 30-50cm). In addition, existing technologies can only provide the proportion of soil contribution to plant water, and lack a unified quantitative indicator to comprehensively assess the degree of dependence of plants on deep or shallow water. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method for calculating the normalized proportion of plant water sources, which solves the problem that existing technologies lack a unified quantitative indicator to comprehensively assess the degree of dependence of plants on deep or shallow water.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for calculating the normalized proportion of plant water sources includes the following steps:

[0006] S1. Data acquisition: The isotopic composition of xylem water and soil water in each layer is determined by stable water isotope analysis.

[0007] S2. Contribution ratio calculation: Calculate the contribution ratio of each soil layer to plant water.

[0008] S3. Calculation of Moisture Source Score: The moisture source score WSS is calculated according to the formula.

[0009] S4. Evaluation of the application: constructing the relationship between WSS values ​​and ecosystem variables.

[0010] Preferably, in step S1, the stable water isotope analysis includes the determination of δ²H and δ¹H. 8 O isotope composition.

[0011] Preferably, in step S2, the contribution ratio is calculated using a Bayesian mixture model.

[0012] Preferably, in step S3, the formula is as follows:

[0013] ;

[0014] in:

[0015] n is the number of soil layers, with a value ≥2;

[0016] Ti is the median depth of the i-th soil layer;

[0017] Ci represents the contribution of the i-th soil layer to plant water, and its value ranges from 0 to 1.

[0018] Mn is the median depth of the deepest soil layer.

[0019] Preferably, the median depth Ti is determined by the following rule: for a soil layer of 0-20cm, Ti = 10cm.

[0020] Preferably, Mn is defined as follows: for the deepest soil layer of 80-100cm, Mn=90cm.

[0021] Preferably, the larger the WSS value, the more dependent the plant is on deep water sources.

[0022] Preferably, the smaller the WSS value, the more dependent it is on shallow water sources.

[0023] Preferably, the value of Ci is a decimal form ranging from 0 to 1.

[0024] Preferably, in step S4, constructing the relationship with ecosystem variables specifically includes: performing a correlation analysis between WSS values ​​and plant water use efficiency (WUE) indicators, wherein the WUE indicators are obtained by measuring the δ¹³C isotope composition of plant leaves.

[0025] This invention provides a method for calculating the normalized proportion of water sources in plants. It has the following beneficial effects:

[0026] 1. In this invention, the normalized values ​​of the water source score WSS value of 0-1 are eliminated by mathematical standardization to eliminate absolute depth differences, so that the research results of different regions or different soil stratification schemes are directly comparable. This solves the defect of traditional methods that cannot make horizontal comparisons due to the subjectivity of depth boundaries, and realizes an objective comparison of the degree of deep water dependence of plants across regions.

[0027] 2. This invention integrates the contribution ratio of soil moisture from multiple layers into a unified value through the single water source score WSS score, which comprehensively reflects the overall depth tendency of plant water source, simplifies the data analysis process, and supports the direct regression or correlation analysis of this indicator with other ecological elements such as water use efficiency, thus promoting the correlation research between plant water source and other indicators.

[0028] 3. This invention employs median depth weighted accumulation and deepest layer normalization calculation to avoid subjective differences in soil stratification boundary selection, ensuring consistency and universality of calculation results under different stratification schemes, and improving the reliability of the method in heterogeneity studies.

[0029] 4. The method of this invention is applicable to vegetation restoration strategy formulation in the field of ecology, efficient water management in the field of agriculture, and water source tracking research in the field of hydrology. It provides an operable decision-making basis for ecosystem management through WSS quantitative indicators and supports the needs of cross-disciplinary water resource optimization. Attached Figure Description

[0030] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0031] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Please see the appendix Figure 1 This invention provides a method for calculating the normalized ratio of plant water sources, comprising the following steps:

[0033] S1. Data acquisition: The isotopic composition of xylem water and soil water in each layer is determined by stable water isotope analysis.

[0034] S2. Contribution ratio calculation: Calculate the contribution ratio of each soil layer to plant water.

[0035] S3. Calculation of Moisture Source Score: The moisture source score WSS is calculated according to the formula.

[0036] S4. Evaluation of the application: constructing the relationship between WSS values ​​and ecosystem variables.

[0037] In step S1, stable water isotope analysis includes the determination of δ²H and δ¹⁸H. 8 O isotope composition.

[0038] Specifically, stable water isotope analysis was performed using vacuum extraction to obtain xylem moisture from plants and soil water samples from various layers. A high-precision laser isotope analyzer was then used to determine the hydrogen (δ²H) and oxygen (δ¹H) content of the samples. 8The stable isotopic composition of O was used to clarify the isotopic characteristics of plant water absorption pathways and soil water sources. In practice, typical plants were selected to collect xylem water samples, and soil water samples were collected in layers at predetermined depths (e.g., 0-20cm, 20-50cm). All samples were purified by freeze-drying and vacuum distillation, and then δ²H and δ¹⁸H were precisely measured using a laser spectrometer. 8 The O ratio was measured three times for each sample and the average value was taken to ensure data reliability. Finally, a stable isotope dataset of plants and soil water sources in each layer was established, providing basic data for subsequent calculation of the water contribution ratio.

[0039] In step S2, the contribution ratio is calculated using a Bayesian mixture model.

[0040] Specifically, when using a Bayesian mixture model to calculate the contribution ratio, it is necessary to consider the δ²H and δ¹H of the xylem water in plants. 8 The O isotope value is used as the input of the mixture, and the isotope data and concentration dependence of soil water in each layer are also input. The running parameters such as the number of Markov chains and the number of iterations are set. The model outputs the contribution ratio of each soil layer to plant water through the running process. This ratio is presented in the form of a decimal from 0 to 1, which can reflect the probability distribution of the contribution of soil water in each layer.

[0041] In step S3, the formula is as follows:

[0042] ;

[0043] in:

[0044] n is the number of soil layers, with a value ≥2;

[0045] Ti is the median depth of the i-th soil layer;

[0046] Ci represents the contribution of the i-th soil layer to plant water, and its value ranges from 0 to 1.

[0047] Mn is the median depth of the deepest soil layer.

[0048] Specifically, the root water absorption depth assessment in step S3 needs to be achieved through a discretized integral formula: First, based on soil stratification measurement data, the median depth Ti of each layer and the median depth Mn of the deepest layer are obtained. At the same time, the contribution ratio Ci of each layer output in step S2 is called. Then, the above parameters are substituted into the formula to calculate the total score WSS. The specific calculation formula is that WSS is equal to the summation of i from 1 to n. The summation term is composed of the median depth Ti of the i-th soil layer multiplied by the contribution ratio Ci of that layer and divided by the median depth Mn of the deepest layer. In actual operation, the product of Ti and Ci needs to be calculated layer by layer according to the soil stratification order and the results are superimposed. Finally, the result is uniformly divided by Mn to obtain the standardized root water absorption depth score. This process is performed independently three times for each research object and the arithmetic mean is taken as the final evaluation result, thus realizing the quantitative characterization of plant root water absorption depth.

[0049] The rule for determining the median depth Ti is: for the 0-20cm soil layer, Ti=10cm.

[0050] Specifically, the median depth Ti of the soil layer needs to be standardized according to the geometric center principle: for each soil layer, regardless of whether its thickness is uniform, the Ti value is taken as the arithmetic mean of the depths of the upper and lower boundaries of the layer. For example, Ti for the 0-20 cm soil layer is (0+20) / 2=10 cm. In practice, Ti is calculated independently for each layer based on the depth boundaries of each layer measured in the field. This rule also applies to non-uniform stratification, such as Ti for the 20-50 cm soil layer, which is (20+50) / 2=35 cm. This ensures that the Ti value is logically consistent and has an accurate physical meaning under different sampling schemes.

[0051] Mn is defined as follows: for the deepest soil layer of 80-100cm, Mn=90cm.

[0052] Specifically, the standardized median depth Mn of the deepest soil layer must be calculated based on its geometric center: take the arithmetic mean of the upper and lower limits of the measured depth range of that layer. For example, if the deepest layer is 80-100 cm, then Mn=(80+100) / 2=90 cm. If the layer changes to 70-110 cm, then Mn=(70+110) / 2=90 cm needs to be recalculated. This method ensures that Mn always represents the spatial reference position of the deepest water source and provides a standardized coefficient with a clear physical meaning for the denominator of the WSS formula.

[0053] A higher WSS value indicates that the plant is more dependent on deep water sources; a lower WSS value indicates that the plant is more dependent on shallow water sources.

[0054] Specifically, the WSS value directly reflects the depth of the plant's water source. Specifically: a WSS close to the maximum value of 1 indicates that the plant mainly relies on deep soil water. In this case, the contribution of deep water sources in the formula numerator is high (Ci) and its depth value is also high (Ti), dominating the calculation result. A WSS close to the minimum value of 0 indicates that the plant mainly relies on shallow soil water. In this case, the contribution of shallow water sources is high (Ci), but its shallow depth value (Ti) suppresses the cumulative value in the formula numerator. The value of Ci ranges from 0 to 1 in decimal form.

[0055] Specifically, this decimal form ensures that the contribution ratio Ci mathematically meets the requirements of a normalized probability distribution, enabling subsequent WSS calculations to have standardized dimensions and cross-comparability.

[0056] In step S4, the specific steps for establishing relationships with ecosystem variables include: performing a correlation analysis between WSS values ​​and plant water use efficiency (WUE) indicators, where the WUE indicators are obtained by measuring the δ¹³C isotope composition of plant leaves.

[0057] Specifically, a quantitative correlation model was established between plant water source score (WSS) and water use efficiency (WUE) converted from leaf δ¹³C. This breakthrough revealed the response mechanism of plant water absorption depth strategy and physiological efficiency. Deep water source dependent plants with high WSS stably acquire soil water, optimize stomatal regulation, and positively drive WUE through positive δ¹³C values. This finding can be directly translated into drought-resistant variety screening criteria and precision irrigation systems.

[0058] Example:

[0059] Study subject: Acacia leucantha in the lower reaches of the Jinsha River; soil layers: 0-20cm (shallow), 20-50cm (middle), 50-100cm (deep).

[0060] S1: Data Acquisition

[0061] Sampling operation

[0062] Plant xylem water: During the growing season, collect corky branches from 4-8 healthy plants, scrape off the outer bark, and immediately collect xylem water samples using a vacuum extraction system.

[0063] Stratified soil water: Using a soil auger, three replicate samples were taken from three layers (0-20cm, 20-50cm, 50-100cm) and soil water was extracted by centrifugation.

[0064] Isotope determination was performed using a laser isotope analyzer to measure the δ²H and δ¹ of all samples. 8 The O component value is calculated by taking the average of three measurements for each sample.

[0065] Result record:

[0066] Water content in the xylem of *Acacia leucantha*: δ²H = -65‰, δ¹ 8 O=-8.5‰

[0067] Soil water isotope characteristics:

[0068] soil layer 0-20cm 20-50cm 50-100cm Median Depth Ti Ti=10cm Ti=35cm Mn=75cm δ²H mean -45‰ -60‰ -75‰ δ1 8 O mean -6.0‰ -8.0‰ -10.0‰

[0069] S2: Contribution Ratio Calculation

[0070] Model parameter settings

[0071] Using the Bayesian mixture model MixSIAR, the input is:

[0072] Mixture: δ²H and δ¹ of Leucaena xylem 8 O value

[0073] Water source: Isotopic data and concentration dependence of water in three soil layers

[0074] Operating parameters: 3 Markov chains, 10,000 iterations, and 5,000 pre-burn-in cycles.

[0075] Output

[0076] Contribution percentage Ci (in decimal form) for each layer:

[0077] Shallow layer (0-20cm): C1=0.15 (range 0.12-0.18)

[0078] Middle layer (20-50cm): C2=0.25 (range 0.21-0.29)

[0079] Deep layers (50-100cm): C3=0.60 (range 0.55-0.65)

[0080] S3: Moisture Source Score Calculation

[0081] Formula calculation:

[0082]

[0083] Results: WSS=0.737 is close to the theoretical maximum value of 1, indicating that the *Acacia leucantha* plant strongly depends on deep soil water sources (50-100cm). Furthermore, the subjective differences in soil stratification schemes were eliminated through standardized median depth and normalized calculations, ensuring that comparable water source scores can be calculated based on stable water isotope data, regardless of whether the soil is homogeneous for field crops or heterogeneous for orchards.

[0084] Example 1 Operational Item Explanation: Collect xylem moisture samples

[0085] Because isotopic fractionation occurs in green plant tissues during photosynthetic metabolism, their water isotope composition cannot accurately reflect the water source signals absorbed by the roots. However, the water isotope composition of the water transport channels in the suberized xylem is stable and highly consistent with the soil water absorbed by the roots.

[0086] Collecting xylem moisture samples ensures the removal of chlorophyll-containing green tissues and prevents organic matter from releasing volatile compounds that contaminate the water sample during vacuum extraction. The xylem vessels' moisture comes directly from soil water absorbed by the roots and does not undergo transpiration fractionation. The suberized tissue cells have a stable structure, and the water extraction process is less prone to isotope exchange reactions. This ensures the accuracy of the water source score (WSS) calculation, enabling this method to obtain reliable water use depth assessment results in different vegetation types, such as crops and economic orchards.

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the normalized proportion of plant water sources, characterized in that, Includes the following steps: S1. Data acquisition: The isotopic composition of xylem water and soil water in each layer is determined by stable water isotope analysis. S2. Contribution ratio calculation: Calculate the contribution ratio of each soil layer to plant water. S3. Calculation of Moisture Source Score: The moisture source score WSS is calculated according to the formula. S4. Evaluation of the application: constructing the relationship between WSS values ​​and ecosystem variables.

2. The method for calculating the normalized plant water source ratio according to claim 1, characterized in that, In step S1, the stable water isotope analysis includes the determination of δ²H and δ¹H. 8 O isotope composition.

3. The method for calculating the normalized plant water source ratio according to claim 1, characterized in that, In step S2, the contribution ratio is calculated using a Bayesian mixture model.

4. The method for calculating the normalized plant water source ratio according to claim 1, characterized in that, In step S3, the formula is as follows: ; in: n is the number of soil layers, with a value ≥2; Ti is the median depth of the i-th soil layer; Ci represents the contribution of the i-th soil layer to plant water, and its value ranges from 0 to 1. Mn is the median depth of the deepest soil layer.

5. The method for calculating the normalized plant water source ratio according to claim 4, characterized in that, The rule for determining the median depth Ti is as follows: for a soil layer of 0-20cm, Ti = 10cm.

6. The method for calculating the normalized plant water source ratio according to claim 4, characterized in that, The definition of Mn is: for the deepest soil layer of 80-100cm, Mn=90cm.

7. The method for calculating the normalized plant water source ratio according to claim 4, characterized in that, The higher the WSS value, the more dependent the plant is on deep water sources.

8. The method for calculating the normalized plant water source ratio according to claim 4, characterized in that, A smaller WSS value indicates a greater reliance on shallow water sources.

9. The method for calculating the normalized plant water source ratio according to claim 4, characterized in that, The value of Ci is a decimal number ranging from 0 to 1.

10. The method for calculating the normalized plant water source ratio according to claim 1, characterized in that, In step S4, the construction of the relationship with ecosystem variables specifically includes: performing a correlation analysis between WSS values ​​and plant water use efficiency (WUE) index, wherein the WUE index is obtained by measuring the δ¹³C isotope composition of plant leaves.

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