Water use regulation method and system based on stable isotope diagnosis for alpine meadow

Abstract

The application discloses a method and system for regulating water use in alpine meadow based on stable isotope diagnosis, and relates to the technical field of alpine meadow ecological management and hydro-ecology. The method comprises the following steps: collecting environmental water and plant water samples, measuring hydrogen and oxygen stable isotope data, calculating line adjustment surplus and soil water surplus indexes; comparing the two indexes with preset stable fluctuation intervals to obtain fluctuation amplitudes and deviation degrees; identifying unstable critical states of plant water use and hydrological strategy types according to the two indexes, and determining the current warming intensity grade; when it is determined that the plant enters the unstable critical state, a corresponding nutrient gradient regulation scheme is selected according to the warming intensity grade for regulation; isotope data is reacquired, and a Bayesian mixture model is used to quantitatively evaluate the contribution rate of each water source; if the evaluation result does not reach the expected threshold, the nutrient gradient is dynamically adjusted according to the deviation of the contribution rate of the water source. Early warning and accurate regulation of the unstable critical state of plant water use are realized.

Description

Technical Field

[0001] The embodiments of the present invention relate to the fields of alpine meadow ecological management and hydroecology, and particularly to a method and system for regulating water use in alpine meadows based on stable isotope diagnostics. Background Technology

[0002] Alpine regions (such as the Qinghai-Tibet Plateau and the Qilian Mountains) are highly sensitive to global warming. Climate warming not only accelerates permafrost degradation but also exacerbates topsoil drought through increased evaporation, threatening the stability of alpine meadow ecosystems. As the dominant vegetation type in these regions, the plant water use strategies (i.e., the ability to obtain water from different soil depths and water sources) of alpine meadows are crucial in determining the ecosystem's resilience.

[0003] Traditional ecological restoration methods often rely on indiscriminate nutrient addition. However, in the context of global warming, inappropriate nutrient input can disrupt plant hydrological strategies. For example, excessive nitrogen addition may induce plants to become overly reliant on unstable surface water, making them more vulnerable to drought stress. Currently, there is a lack of ecological management methods that can use real-time isotope diagnostics and precise control of nitrogen-phosphorus ratios to guide plants to optimize water acquisition depth. Especially under extreme warming scenarios, how to use nutrients as a "lever" to induce deep root development to obtain stable water subsidies remains a technological gap.

[0004] Therefore, developing a management method and system that can accurately identify the hydrological status of plants and provide dynamic nutrient regulation solutions is of great significance for enhancing the ability of alpine ecosystems to cope with climate change. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and system for regulating water use in alpine meadows based on stable isotope diagnostics. By precisely delivering nutrient gradients, plants are induced to flexibly switch between shallow pulse capture and deep stable mining strategies, effectively alleviating surface soil drought stress caused by climate warming and enhancing the hydrological resilience and stability of alpine meadow ecosystems.

[0006] In a first aspect, embodiments of the present invention provide a method for regulating water use in alpine meadows based on stable isotope diagnostics, comprising: Real-time collection of environmental water and plant water samples within the alpine meadow ecosystem; determination of hydrogen and oxygen stable isotope data; calculation of linear regulation surplus and soil water surplus indices. The linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to obtain the fluctuation range and deviation of the linear adjustment surplus and soil water surplus indices. Based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indices, identify the instability critical state and hydrological strategy type of plant water use, and determine the current warming intensity level. When the plant is determined to have entered the unstable critical state, a corresponding nutrient gradient regulation scheme is selected for regulation based on the current warming intensity level obtained from the determination. After the regulation was implemented, hydrogen and oxygen stable isotope data of environmental water bodies and plant water were reacquired, and the contribution rate of each water source was quantitatively assessed using a Bayesian mixture model. If the assessment results do not reach the expected threshold, the currently implemented nutrient gradient will be dynamically adjusted based on the deviation in the proportion of water sources.

[0007] As a preferred implementation method, environmental water and plant moisture samples are collected in real time within the alpine meadow ecosystem. Hydrogen and oxygen stable isotope data are measured, and linear regulation surplus and soil water surplus indices are calculated, including: Rainfall samples, soil samples at different depth gradients, and plant stem samples were collected at a set frequency to serve as environmental water and plant moisture samples. Plant water and soil water were obtained by vacuum extraction of the collected samples, and the abundance values ​​of hydrogen and oxygen stable isotopes in the samples were determined by spectrometer. Based on the abundance values ​​of the hydrogen and oxygen stable isotopes, the linear regulation surplus and soil water surplus indices are calculated respectively. The line regulation surplus is used to characterize the degree to which plant water deviates from the local atmospheric precipitation line, and the soil water surplus is used to characterize the degree of isotopic shift of plant water relative to the local soil water line.

[0008] In a preferred embodiment, the linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to obtain the fluctuation amplitude and deviation of the linear adjustment surplus and soil water surplus indices, including: The linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to determine the magnitude and direction of each index's deviation from the median of the fluctuation range. When the value of any indicator exceeds its corresponding preset stable fluctuation range a certain number of times, the indicator is judged to have significant fluctuations. The degree of deviation of each indicator is determined based on the magnitude and direction of its deviation from the median of the corresponding fluctuation range, as well as the cumulative degree of significant fluctuation of the indicator. The degree of deviation is categorized into mild deviation, moderate deviation, and severe deviation.

[0009] In a preferred embodiment, based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indices, the instability critical state and hydrological strategy type of plant water use are identified, and the current warming intensity level is determined, including: When the degree of deviation reaches moderate or severe deviation, and the number of indicators with significant fluctuations or the cumulative amount of significant fluctuations of a single indicator exceeds a set threshold, the plant is determined to have entered an unstable critical state. The current warming intensity level is determined based on the deviation level mapping, and the current hydrological strategy type is simultaneously identified based on the offset direction of the plant waterline slope relative to the local atmospheric precipitation line and soil waterline, respectively. The slight deviation corresponds to a slight warming level, the moderate deviation corresponds to a moderate warming level, and the severe deviation corresponds to an extreme warming level.

[0010] As a preferred implementation, the current hydrological strategy type is simultaneously identified based on the offset direction of the plant waterline slope relative to the local atmospheric precipitation line and soil waterline, including: The plant water line was obtained by fitting the stable isotope data of hydrogen and oxygen in the plant water, and the slope of the plant water line was obtained. If the slope of the plant waterline shifts toward the local atmospheric precipitation line, it is identified as an opportunistic strategy that primarily utilizes precipitation pulses and shallow soil water. If the slope of the plant waterline shifts towards the direction of the soil waterline, it is identified as a stable excavation strategy that primarily utilizes deep soil water or deep water sources.

[0011] In a preferred embodiment, when the plant is determined to have entered the instability critical state, a corresponding nutrient gradient regulation scheme is selected for regulation based on the determined current warming intensity level, including: When the current warming intensity level is mild or moderate, the first gradient regulation scheme is selected. The first gradient regulation scheme is to apply nitrogen and phosphorus nutrients to induce plant roots to establish an opportunistic strategy that mainly utilizes precipitation pulses and shallow soil water. When the current warming intensity level is extreme warming or severe drought, the second gradient regulation scheme is selected. The second gradient regulation scheme is to adjust the ratio of nitrogen and phosphorus nutrients to alleviate the metabolic restriction of root extension to deeper layers and induce the root system to turn to a stable digging strategy that utilizes deep soil water and deep water sources.

[0012] As a preferred implementation, based on the reacquired hydrogen and oxygen stable isotope data, a Bayesian mixture model is used to quantitatively assess the contribution rate of each water source, including: Precipitation, surface soil water, deep soil water, groundwater, and permafrost water in the aforementioned environmental water bodies are used as potential water source end-units. A Bayesian mixture model is constructed using the hydrogen and oxygen stable isotope data of each potential water source end-unit as the source input and the hydrogen and oxygen stable isotope data of the plant water as the mixing input. Set the iteration step size and chain number of the Markov chain Monte Carlo model, run the model until convergence, and output the contribution rate of each potential water source endmember to plant water and its confidence interval. The reliability of the evaluation result is determined based on the confidence interval width of the contribution rate. If the confidence interval width is less than a set threshold, the evaluation result is confirmed to be valid. If the confidence interval width is greater than or equal to the set threshold, the iteration step size is increased and the model is rerun until the confidence interval width is less than the set threshold.

[0013] In a preferred embodiment, if the evaluation result does not reach the expected threshold, the currently implemented nutrient gradient is dynamically adjusted based on the deviation of the water source ratio, including: The water source contribution rate of each potential water source end-member output by the Bayesian mixture model is compared with the expected contribution rate threshold corresponding to the current warming intensity level to determine the target water source end-member that has not reached the expected threshold and its deviation. Based on the deviation, the amount of nitrogen and / or phosphorus added in the currently executed nutrient gradient is corrected; The nutrient gradient is updated with the corrected nitrogen and phosphorus additions, and the nutrient gradient control scheme corresponding to the current warming intensity level is returned to be executed based on the updated nutrient gradient.

[0014] In a preferred embodiment, the amount of nitrogen and / or phosphorus added in the currently executed nutrient gradient is corrected based on the deviation, including: When the target water source end-unit is precipitation or surface soil water and its water source contribution rate does not reach the expected contribution rate threshold, the amount of nitrogen added is increased to enhance shallow lateral root development and precipitation pulse capture ability. When the target water source is deep soil water, groundwater, or permafrost water, and its water source contribution rate does not reach the expected contribution rate threshold, the amount of phosphorus added is increased and the amount of nitrogen added is controlled not to exceed the set upper limit, so as to enhance the deep root extension capacity.

[0015] Secondly, embodiments of the present invention also provide a water use regulation system for alpine meadows based on stable isotope diagnosis, used to execute the water use regulation method for alpine meadows based on stable isotope diagnosis described in any of the above embodiments, the system comprising: The multi-source data sensing module is used to collect environmental water and plant water samples in the alpine meadow ecosystem in real time, measure hydrogen and oxygen stable isotope data, and calculate linear regulation surplus and soil water surplus indicators. The fluctuation analysis module is used to compare the linear adjustment surplus and soil water surplus indices with their corresponding preset stable fluctuation ranges to obtain the fluctuation amplitude and deviation of the linear adjustment surplus and soil water surplus indices. The hydrological strategy diagnosis module is used to identify the instability critical state and hydrological strategy type of plant water use based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indicators, and to determine the current warming intensity level. The precise regulation decision module is used to select the corresponding nutrient gradient regulation scheme for regulation based on the current warming intensity level obtained from the determination when the plant is determined to have entered the unstable critical state. The effect evaluation module is used to reacquire hydrogen and oxygen stable isotope data of environmental water bodies and plant water after the implementation of regulation, and to quantitatively evaluate the contribution rate of each water source using a Bayesian mixture model. The feedback adjustment module is used to dynamically adjust the currently executed nutrient gradient based on the deviation of the water source ratio if the evaluation result does not reach the expected threshold.

[0016] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the alpine meadow water use regulation method based on stable isotope diagnosis as described in any embodiment of the present invention.

[0017] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the alpine meadow water use regulation method based on stable isotope diagnosis as described in any embodiment of the present invention.

[0018] In summary, the present invention achieves the following beneficial effects: This invention utilizes a dual-indicator diagnostic system of linear regulation surplus (LC-excess) and soil water surplus (SW-excess) to effectively identify hydrologically vulnerable states caused by climate warming, enabling early warning of critical states of plant water use instability and providing a scientific basis for precise regulation. Furthermore, this invention is the first to propose using phosphorus to alleviate energy metabolism limitations during root extension into deeper layers, inducing deep root growth to obtain stable deep water sources. This provides a novel regulatory target and theoretical basis for adaptive management of alpine ecosystems under extreme climate conditions, realizing a paradigm shift in hydrological function regulation from passive damage to active adaptation in alpine meadow ecosystems, and providing scientific support for the hydrological and ecological restoration of ecologically vulnerable areas such as the Qinghai-Tibet Plateau and the Qilian Mountains. Attached Figure Description

[0019] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a flowchart of a method for regulating water use in alpine meadows based on stable isotope diagnostics, provided in an embodiment of the present invention. Figure 2 This is a decision tree framework diagram of adaptive ecological management strategies provided in the embodiments of the present invention; Figure 3 This is a schematic diagram of the structure of the alpine meadow water use regulation system based on stable isotope diagnosis provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0021] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as being processed sequentially, many of these operations (or steps) may be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operation is completed, but may also have additional steps not included in the figures. The process may correspond to a method, function, procedure, subroutine, subroutine, etc.

[0022] Example 1 like Figure 1 As shown, Embodiment 1 of the present invention provides a flowchart of a method 100 for regulating water use in alpine meadows based on stable isotope diagnostics. This method 100 specifically includes the following steps: Step S110: Collect environmental water and plant moisture samples in real time within the alpine meadow ecosystem, measure hydrogen and oxygen stable isotope data, and calculate linear regulation surplus and soil water surplus indices.

[0023] Specifically, the alpine meadow ecosystem involved in this embodiment is located in a typical permafrost edge zone, with an altitude range of 3000-4000m. The water recharge end-members include: precipitation, 0-10cm surface soil water, 10-20cm deep soil water, groundwater, and permafrost surface water. Plant samples were selected from local dominant species, including Kobresia alpineensis and Leymus chinensis. Their water is absorbed and transported through their root systems, reflecting the real-time utilization ratio of each water source by the plants.

[0024] Preferably, precipitation samples, soil samples at different depth gradients, and plant stem samples are collected at a set frequency to serve as environmental water and plant moisture samples, specifically including: (1) Collection of plant stem samples: During the plant growing season from May to September, collect stem samples of the target plants at the first set frequency, such as once a week. When sampling, select healthy plants, peel off the outer skin of the stem and leaf sheath, take the middle internode segment of the stem, quickly put it into a cryopreservation tube and seal it, place it in a portable refrigerator for storage, and transfer it to the laboratory for freezing and storage on the same day.

[0025] (2) Soil sample collection: Soil samples were collected at two depth gradients, 0-10cm and 10-20cm, using a soil auger at the second set frequency. Preferably, the second set frequency was once every 10 days. At least 3 replicates were collected for each depth gradient. After being mixed evenly, the samples were placed in sealed bags, the air was removed, the bags were sealed, and the samples were refrigerated. The geographical coordinates, sampling depth, soil temperature, and moisture content of each sampling point were recorded simultaneously.

[0026] (3) Precipitation sample collection: Within 1 hour after each precipitation event, use a standard rain gauge with a funnel to collect the precipitation in an open area of ​​the sample plot, and immediately transfer it to a high-density polyethylene bottle, seal it and store it in the refrigerator to prevent isotope fractionation deviation caused by evaporation. If the precipitation event lasts for more than 12 hours, collect samples in 6-hour segments to capture the temporal changes in isotope composition during the precipitation process.

[0027] As a preferred embodiment, the determination of stable hydrogen and oxygen isotope data includes the following steps: Soil water and plant water were extracted separately using vacuum extraction technology: the samples were placed in a vacuum extraction system at a vacuum level below 1×10⁻⁶. - Extraction was performed under 2 mbar conditions, with the extraction temperature controlled above 100°C to ensure complete release of adsorbed water from the soil and water from the plant tissue. The extraction time was no less than 90 minutes. The extracted water was collected by condensation in a liquid nitrogen cold trap (-196°C). After extraction, the water level in the collection tube was checked. If the water level was less than 1 mL, the extraction was considered a failure and a new sample had to be taken for extraction.

[0028] The abundance values ​​of stable hydrogen and oxygen isotopes in each sample were determined using a wavelength scanning cavity ring-down spectrometer. The results were expressed as parts per thousand (ppm) relative to the Vienna standard mean seawater. Each sample was measured at least three times, and the arithmetic mean was taken as the final result. If the standard deviation exceeded the instrument's accuracy range, the measurement had to be repeated.

[0029] As a preferred embodiment, based on the measured hydrogen and oxygen stable isotope abundance values, the linear regulation surplus and soil water surplus indices are calculated respectively: The line adjustment surplus LC-excess is calculated according to the following formula: ; Where a and b are the slope and intercept of the local atmospheric precipitation line, respectively, through the δ²H and δ¹ of the local precipitation sample. 8 The value of LC-excess is obtained by least-squares linear regression fitting of the O data. This value is used to characterize the degree to which plant water deviates from the local atmospheric precipitation line. A positive value of LC-excess indicates that plant water is enriched in heavy isotopes relative to the precipitation line, while a negative value indicates that plant water is depleted in light isotopes due to evaporation and fractionation. The larger the absolute value, the more significant the deviation.

[0030] The soil water surplus SW-excess is used to characterize the degree of isotopic shift of plant water relative to the local soil water line. It is calculated as the difference between the plant water δ²H and the soil water δ²H at the same depth. A positive SW-excess value indicates that the water absorbed by the plant is richer in heavy isotopes than the soil water in the same layer, while a negative value indicates that the plant preferentially uses water sources rich in light isotopes.

[0031] The plant water content is measured by δ²H and δ¹. 8 Using the O data as the ordinate and abscissa, a linear regression was performed to fit the plant waterline. The slope and intercept of the plant waterline were then obtained as input parameters for subsequent hydrological strategy type identification.

[0032] During the testing of each batch of samples, standard water samples from within the laboratory were simultaneously used for instrument calibration and drift correction to ensure the accuracy and comparability of the test data. The sampling time, sampling depth, geographical coordinates of the sampling point, and micrometeorological parameters of each sample were recorded to establish an isotope dataset, which serves as input for subsequent diagnostic analysis.

[0033] Step S120: Compare the linear adjustment surplus and soil water surplus indices with their corresponding preset stable fluctuation ranges to obtain the fluctuation range and deviation of the linear adjustment surplus and soil water surplus indices.

[0034] Specifically, this step, based on the linear regulation surplus and soil water surplus indices calculated in step S110, performs quantitative diagnosis and early warning of plant water use status by comparing them with a preset stable fluctuation range, including: The LC-excess and SW-excess indices calculated in step S110 are compared with their respective preset stable fluctuation ranges to determine the magnitude and direction of each index's deviation from the median of its corresponding fluctuation range. The preset stable fluctuation range is obtained through statistical analysis of historical monitoring data, for example, based on 3-5 years of continuous observation data from a non-warming control plot, with the mean ± 2 standard deviations used to determine the normal fluctuation range, representing the index fluctuation range of plants under normal growth conditions.

[0035] When the value of any indicator exceeds its corresponding preset stable fluctuation range a certain number of times, the indicator is considered to have experienced significant fluctuation. For example, when LC-excess or SW-excess exceeds its normal fluctuation range three times consecutively, it is considered to have experienced statistically significant fluctuation, indicating that the plant's water use status has deviated from the normal steady state.

[0036] LC-excess diagnosis: The LC-excess value calculated in step S110 is used to determine the degree to which plant water deviates from the local atmospheric precipitation line. If the LC-excess value continues to decrease and shows a significant negative value, it indicates that the plant is facing strong surface evaporation and fractionation pressure, and the water source tends to be single and unstable.

[0037] SW-excess diagnosis: The SW-excess value quantitatively characterizes the deviation of plant water absorption relative to the average soil water level, specifically the difference between plant water δ²H and soil water δ²H at the same depth. When SW-excess continuously deviates from zero and shows significant positive or negative values, it indicates that the layer from which the plant absorbs water has shifted significantly relative to the soil water at the same depth, reflecting changes in root water absorption depth or water source contribution structure.

[0038] In a preferred embodiment, the degree of deviation for each indicator is determined based on the magnitude and direction of its deviation from the median of the corresponding fluctuation range, as well as the cumulative degree of significant fluctuation of that indicator. The degree of deviation is categorized into three levels, from smallest to largest: Slight deviation: The index value exceeds the preset stable fluctuation range but has not exceeded the limit continuously or the number of consecutive exceedances has not reached the set threshold, indicating that the plant water use status has fluctuated slightly but is still within the self-regulating range. Moderate deviation: The number of times the index value exceeds the preset stable fluctuation range reaches the set threshold, and the deviation range increases significantly, indicating that the hydrological stability of the plant has begun to decline significantly, and attention should be paid and preparations should be made to start the control program. Severe deviation: The index value deviates significantly from the preset stable fluctuation range and is accompanied by continuous and significant fluctuations, indicating that the plant is facing severe water stress and the water source is becoming increasingly singular, requiring immediate control measures.

[0039] Based on the diagnostic results of LC-excess and SW-excess, a hydrological vulnerability warning is triggered when either indicator reaches a moderate or higher level of deviation. For example, in a control experiment, it was found that under warming but no fertilization conditions, the plant's LC-excess significantly decreased, reflecting its over-reliance on surface soil water, which is highly susceptible to meteorological disturbances. At this point, the system triggers a hydrological vulnerability warning and enters the instability critical state determination and warming intensity level identification stage in step S130.

[0040] Step S130: Based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indices, identify the instability critical state and hydrological strategy type of plant water use, and determine the current warming intensity level.

[0041] Specifically, this step, based on the fluctuation range and deviation of the LC-excess and SW-excess indices determined in step S120, simultaneously performs the determination of the instability critical state, the determination of the warming intensity level, and the identification of the hydrological strategy type.

[0042] Preferably, the instability critical state is determined by the following method: When the deviation of LC-excess or SW-excess reaches moderate or severe, and the number of indicators showing significant fluctuations or the cumulative significant fluctuation of a single indicator exceeds a set threshold, the plant is determined to have entered a critical state of instability. The specific determination rules are as follows: When any indicator reaches a moderate deviation or above, and the cumulative amount of significant fluctuations of that indicator (i.e. the cumulative number of times it exceeds the preset range) exceeds the set threshold, such as when it reaches more than 5 times, or when both indicators show significant fluctuations, the plant is judged to have entered an unstable critical state. The unstable critical state indicates that the plant's water use strategy has deviated from the normal steady state, and its self-regulation ability is insufficient to cope with the current environmental stress, so active nutrient regulation intervention needs to be initiated.

[0043] Preferably, the current warming intensity level is determined according to the deviation level determined in step S120 and a preset mapping relationship: Slight deviation from the corresponding mild warming level: This indicates that the plant's water use status is fluctuating slightly but is still within a self-regulating range and does not require immediate intervention. Moderate deviation from the corresponding moderate warming level: indicates that the hydrological stability of plants has begun to decline significantly, and it is necessary to prepare to initiate regulatory procedures. A significant deviation from the corresponding extreme warming level indicates that plants are facing severe water stress and require immediate regulatory measures.

[0044] This mapping relationship is established based on prior experimental data, such as calibration using isotope response curves from OTC experiments with different heating gradients.

[0045] Preferably, while determining the level of warming intensity, the current hydrological strategy type is simultaneously identified based on the offset direction of the vegetation waterline slope relative to the local precipitation line (LMWL) and soil water line (SWL), specifically including: First, linear regression is performed on the hydrogen and oxygen stable isotope data of plant water obtained in step S110 to fit the plant waterline and obtain its slope. The slope of the plant waterline is then compared with the slopes of the local atmospheric precipitation line and soil waterline, and the current hydrological strategy type is identified based on the comparison results.

[0046] If the slope of the plant waterline shifts toward the local atmospheric precipitation line, it is identified as an opportunistic strategy that mainly utilizes precipitation pulses and shallow soil water, indicating that the plant mainly relies on recent precipitation and surface soil water. If the slope of the plant waterline shifts towards the direction of the soil waterline, it is identified as a stable excavation strategy that mainly utilizes deep soil water, groundwater, or permafrost water, indicating that the plant mainly relies on a stable water source.

[0047] In summary, based on the above judgment results, the following three diagnostic parameters are output simultaneously: (1) Instability critical state indicator: Yes / No, serving as the master switch for whether to initiate the control program; (2) Current warming intensity level: mild warming level / moderate warming level / extreme warming level, which serves as the basis for selecting the first or second gradient control scheme in subsequent steps; (3) Current hydrological strategy type: opportunistic strategy / stable mining strategy, as auxiliary verification information for the selection of control strategy.

[0048] Step S140: When it is determined that the plant has entered the unstable critical state, the corresponding nutrient gradient regulation scheme is selected for regulation based on the current warming intensity level obtained from the determination.

[0049] Specifically, this step performs graded nutrient regulation based on the instability critical state indicator output in step S130 and the current warming intensity level. Once the plant is determined to have entered an instability critical state, the corresponding nutrient gradient regulation scheme is selected according to the current warming intensity level.

[0050] As a preferred embodiment, combined with Figure 2As shown, when the current warming intensity level is mild or moderate, the first gradient regulation scheme is selected. The first gradient regulation scheme is to apply nitrogen and phosphorus nutrients to induce plant roots to establish an opportunistic strategy that mainly utilizes precipitation pulses and shallow soil water. When the current warming intensity level is extreme warming or severe drought, the second gradient regulation scheme is selected. The second gradient regulation scheme is to adjust the ratio of nitrogen and phosphorus nutrients to alleviate the metabolic restriction of root extension to deeper layers and induce the root system to turn to a stable digging strategy that utilizes deep soil water and deep water sources.

[0051] As a preferred embodiment, the first gradient control scheme specifically includes: adding 10g m - ² yr - ¹ Nitrogen fertilizer (N 10 ) Collaborative 5g m - ² yr - ¹ The addition of phosphorus fertilizer (P5) and moderate nitrogen significantly optimizes the development of oblique lateral roots in plants, enhancing their water-capturing capacity during the post-precipitation window. Low phosphorus addition maintains the basal metabolic needs of the roots without inducing excessive downward root growth. The synergistic effect of these two factors results in plants exhibiting a high degree of opportunistic utilization. Furthermore, experimental data confirm that under this regulation, the slope of the plant waterline converges towards the atmospheric precipitation line, and the contribution of instantaneous precipitation to plant water use increases from the baseline level to over 14.7%, indicating that plants have successfully established an opportunistic strategy primarily utilizing precipitation pulses and shallow soil water.

[0052] When warming intensity reaches extreme warming or severe drought occurs, with extremely dry topsoil and unreliable shallow water sources, a second-gradient regulation plan should be implemented: increasing the proportion of phosphorus fertilizer to 15g / m³. - ² yr - ¹(P 15 ), and control nitrogen fertilizer at a low level of 5g m - ² yr - ¹. Phosphorus, as the core of energy metabolism, can alleviate the metabolic limitations of roots extending into deeper, denser soil layers. Low nitrogen levels prevent plants from becoming overly reliant on unstable surface water sources, ensuring that energy for root growth is preferentially allocated to deeper layers. Experimental results show that under this regulation, the slope of the plant waterline decreased to approximately 6.03, reflecting a large-scale shift of water sources towards deeper soil water and deeper water sources. The combined contribution rate of deep water sources (10-20cm soil water, groundwater, and permafrost water) steadily increased to over 55%, effectively avoiding the risk of drought-induced death due to high surface temperatures.

[0053] Nutrients are applied by surface spreading or strip application, with concentrated application in mid-to-late May at the beginning of the growing season, or 50% applied in mid-May and early July respectively, to improve nutrient utilization efficiency.

[0054] Step S150: After the regulation is performed, hydrogen and oxygen stable isotope data of environmental water and plant water are reacquired, and the contribution rate of each water source is quantitatively assessed using a Bayesian mixture model.

[0055] Specifically, after the nutrient regulation scheme in step S140 is completed, this step involves resampling and using a Bayesian mixture model to quantitatively assess the water source of the regulated plants in order to verify the regulation effect.

[0056] As a preferred embodiment, the re-collection and isotope determination of the regulated sample specifically includes: After the nutrient application in step S140 is completed, a set response period, such as 2-4 weeks, is allowed to ensure that the plant roots produce a physiological response to the nutrient addition. Following the same sampling protocol as in step S110, precipitation samples, soil samples at different depth gradients, and plant stem samples are collected again. The sampling frequency and operation method remain consistent with S110 to ensure the comparability of data before and after the adjustment. The newly collected samples are then vacuum-extracted, and their hydrogen and oxygen stable isotope abundance values ​​are determined using a spectrometer. The determination method and accuracy requirements are the same as in step S110.

[0057] The reacquired stable isotope data of hydrogen and oxygen in environmental water bodies were used as potential water source end-units, specifically including: precipitation, surface soil water, deep soil water, groundwater, and permafrost water, totaling five potential water source end-units. Next, using the stable hydrogen and oxygen isotope data of each potential water source end-member as the source input and the stable hydrogen and oxygen isotope data of the plant water as the mixed input, a Bayesian mixture model was constructed. The model included two error structures: residual error and process error. The residual error described the natural variation and measurement error of the isotopic composition within the source end-member; the process error described the random variation between different individuals or between different sampling time points. A mean model or a concentration-dependent model was selected based on the data characteristics.

[0058] Set the iteration step size and chain number of the Markov chain Monte Carlo method, run the model until convergence, and output the contribution rate of each potential water source endmember to plant water use and its confidence interval. By comparing the dynamic changes of the contribution ratio of each water source before and after regulation, the guiding effect of different gradient regulation schemes on plant water use strategies can be intuitively evaluated.

[0059] Finally, the reliability of the evaluation results is determined based on the width of the confidence interval for the contribution rate: If the confidence interval width is less than the set threshold, for example, if the confidence interval width is less than 30%, then the evaluation result is confirmed to be valid, indicating that the model has sufficient accuracy in estimating the water source contribution rate. If the confidence interval width is greater than or equal to the set threshold, the model is rerun after increasing the iteration step size until the confidence interval width is less than the set threshold.

[0060] After reliability verification, the contribution rate of each potential water source endmember to plant water and its confidence interval are output as the quantitative evaluation result of the regulation effect.

[0061] Step S160: If the evaluation result does not reach the expected threshold, the currently implemented nutrient gradient is dynamically adjusted according to the deviation of the water source ratio.

[0062] Specifically, this step compares the contribution rate of each water source and its confidence interval output in step S150 with the expected contribution rate threshold corresponding to the current warming intensity level, and dynamically adjusts the nutrient gradient according to the deviation to form a closed-loop feedback.

[0063] In a preferred embodiment, the water source contribution rate of each potential water source end-member output by the Bayesian mixture model in step S150 is compared with the expected contribution rate threshold corresponding to the current warming intensity level: When implementing the first-gradient regulation scheme, the expected contribution rate threshold is a precipitation contribution rate of ≥14.7%. If the precipitation contribution rate does not reach this threshold, it indicates that the lateral root promotion effect of nitrogen is not fully utilized and adjustments are needed. When implementing the second-gradient regulation scheme, the expected contribution rate threshold is that the combined contribution rate of deep water sources (10-20cm deep soil water, groundwater, and permafrost water) is ≥55%. If the combined contribution rate of deep water sources does not reach this threshold, it indicates that the deep-seated induction effect of phosphorus has not been fully exerted and adjustments are required.

[0064] Identify the target water source end-member that did not meet the expected threshold and its deviation. For example, if, under extreme warming scenarios, the combined contribution rate of deep water sources after regulation is only 45%, then the target water source end-member is the deep water source end-member, with a deviation of -10%.

[0065] In a preferred embodiment, based on the deviation, a quantitative correction is made to the amount of nitrogen and / or phosphorus added in the currently executed nutrient gradient, specifically including: When the target water source is precipitation or surface soil water and its water source contribution rate does not reach the expected contribution rate threshold, increase the nitrogen addition amount, for example, by 2-3 g·m³ per adjustment. - ²·yr - ¹, to enhance shallow lateral root development and the ability of plants to capture rainfall pulses. Nitrogen is a key nutrient element for lateral root development, and moderate nitrogen supplementation can expand the absorption area of ​​shallow roots and improve the plant's interception efficiency of rainfall pulses.

[0066] When the target water source is deep soil water, groundwater, or permafrost water, and its water source contribution rate does not reach the expected contribution rate threshold, increase the amount of phosphorus added and control the amount of nitrogen added to not exceed the set upper limit, for example, 15 g·m³. - ²·yr - ¹, to enhance the ability of deep roots to extend. As a core element of energy metabolism, phosphorus can alleviate the metabolic limitations of roots extending to deeper layers and promote vertical root elongation; at the same time, nitrogen should be controlled to prevent plants from reducing carbon allocation in deep roots due to sufficient nitrogen.

[0067] In a preferred embodiment, the nutrient gradient is updated with the corrected nitrogen and phosphorus addition amounts, and the nutrient gradient control scheme corresponding to the current warming intensity level in step S140 is returned based on the updated nutrient gradient, that is, the nutrient delivery is re-executed, and a new round of control-evaluation-feedback loop is entered.

[0068] If the evaluation results still fail to reach the expected threshold after multiple iterations, the current corrected nutrient gradient will be maintained, and the response characteristics will be recorded as a reference for subsequent management decisions. At the same time, a prompt message will be issued to remind managers to conduct manual intervention evaluation.

[0069] In addition, after each adjustment cycle, the results of this round of adjustment are recorded and updated to the isotope database as the data basis for subsequent adjustment strategy optimization.

[0070] In summary, this embodiment achieves proactive adaptive management of water use strategies in alpine meadows through a complete technical path including isotope diagnosis, instability critical state determination, warming intensity classification, gradient nutrient regulation, MixSIAR effect evaluation, and dynamic adjustment feedback. The decision-making logic framework of the entire management process is as follows: Figure 2 As shown: First, the fluctuation range and deviation of the LC-excess and SW-excess indices are used to determine whether the instability critical state has been entered; if the instability critical state has been entered, the first or second gradient control scheme is selected according to the warming intensity level; after control, the contribution rate of each water source is quantified by the MixSIAR model; if the expected threshold is not reached, the nitrogen and phosphorus addition amounts are adjusted differently according to the deviation of the target water source end-unit, and the control is re-executed.

[0071] Based on the above embodiments, the present invention achieves the following beneficial effects: (1) This invention introduces the dual indicators of linear regulation surplus (LC-excess) and soil water surplus (SW-excess) into the field of alpine meadow ecological management for the first time. By using hydrogen and oxygen stable isotope technology to quantitatively characterize the structure of plant water sources and the degree of influence from evaporation, it solves the technical problem that traditional methods cannot identify plant hydrological vulnerability in real time. The fluctuation amplitude and deviation of LC-excess and SW-excess can reflect the early signals of plant succession from normal state to unstable critical state in advance, providing a scientific quantitative basis for triggering nutrient regulation.

[0072] (2) This invention is the first to construct a graded nutrient regulation scheme for different warming intensities: under mild / moderate warming scenarios, through N 10 The synergistic addition of P5 induces plants to establish an opportunistic strategy primarily utilizing precipitation pulses and shallow soil water, increasing precipitation use efficiency by approximately 149% and raising the precipitation contribution rate from the baseline level to over 14.7%. Under extreme warming or severe drought scenarios, synergistic low-nitrogen gradient regulation induces deeper root extension, stabilizing the combined contribution rate of deep water sources to over 55%, and reducing the plant waterline slope to approximately 6.03. This method overcomes the limitations of the indiscriminate, one-size-fits-all approach to fertilization in traditional ecological restoration.

[0073] (3) This invention breaks through the traditional cognitive limitation of nutrient management focusing only on the above-ground growth of plants, and for the first time reveals the ecological mechanism by which phosphorus promotes the vertical elongation of plant roots to obtain stable deep water sources by alleviating the energy metabolism limitation when roots extend into deep and dense soil layers. In the field of alpine meadow ecological management, this invention for the first time positions phosphorus as an energy lever for deep root development, providing a new regulatory target for the adaptive management of alpine ecosystems under extreme climate conditions.

[0074] (4) This invention uses the MixSIAR Bayesian mixture model to quantitatively assess the contribution rate of each water source after regulation, and dynamically adjusts the nitrogen and phosphorus gradients based on the assessment results, thus realizing a paradigm shift in hydrological function regulation from passive damage to active adaptation. This closed-loop iterative mechanism ensures that the regulation strategy can be continuously optimized according to the actual plant response, significantly improving the long-term resilience and stability of alpine meadow ecosystems under the background of climate warming.

[0075] (5) This invention achieves hydrological function restoration through proactive guidance of water use strategies, rather than relying on large-scale engineering interventions or indiscriminate fertilization, and is applicable to ecologically fragile areas such as the Qinghai-Tibet Plateau and the Qilian Mountains. Physical management aids such as micro-topography modification and organic amendments can further enhance soil water retention capacity, forming a synergistic gain in ecological benefits and restoration efficiency, and providing a replicable and scalable technology for the near-natural restoration of degraded alpine meadow grasslands.

[0076] Example 2 Figure 3 This is a schematic diagram of the structure of the alpine meadow water use regulation system based on stable isotope diagnosis provided in Embodiment 2 of the present invention, as shown below. Figure 3 As shown, the system includes: The multi-source data sensing module 310 is used to collect environmental water and plant water samples in the alpine meadow ecosystem in real time, measure hydrogen and oxygen stable isotope data, and calculate linear regulation surplus and soil water surplus indicators. The fluctuation analysis module 320 is used to compare the linear adjustment surplus and soil water surplus indices with their corresponding preset stable fluctuation ranges to obtain the fluctuation amplitude and deviation of the linear adjustment surplus and soil water surplus indices. The hydrological strategy diagnosis module 330 is used to identify the instability critical state and hydrological strategy type of plant water use based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indicators, and to determine the current warming intensity level. The precise regulation decision module 340 is used to select a corresponding nutrient gradient regulation scheme for regulation based on the current warming intensity level obtained from the determination when the plant is determined to have entered the unstable critical state. The effect evaluation module 350 is used to reacquire hydrogen and oxygen stable isotope data of environmental water and plant water after the implementation of regulation, and to quantitatively evaluate the contribution rate of each water source using a Bayesian mixture model. The feedback adjustment module 360 ​​is used to dynamically adjust the currently executed nutrient gradient based on the deviation of the water source ratio if the evaluation result does not reach the expected threshold.

[0077] The alpine meadow water use regulation system based on stable isotope diagnosis provided in the embodiments of the present invention can execute the alpine meadow water use regulation method based on stable isotope diagnosis provided in any of the embodiments of the present invention. It has the corresponding functions and beneficial effects of executing the alpine meadow water use regulation method based on stable isotope diagnosis. For detailed process, please refer to the relevant operations of the alpine meadow water use regulation method based on stable isotope diagnosis in the foregoing embodiments.

[0078] Example 3 Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, and may also represent various forms of mobile devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the invention described and / or claimed herein.

[0079] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0080] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0081] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the alpine meadow water use regulation method based on stable isotope diagnostics described above.

[0082] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0083] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for regulating water use in alpine meadows based on stable isotope diagnostics, characterized in that, include: Real-time collection of environmental water and plant water samples within the alpine meadow ecosystem; determination of hydrogen and oxygen stable isotope data; calculation of linear regulation surplus and soil water surplus indices. The linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to obtain the fluctuation range and deviation of the linear adjustment surplus and soil water surplus indices. Based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indices, identify the instability critical state and hydrological strategy type of plant water use, and determine the current warming intensity level. When the plant is determined to have entered the unstable critical state, a corresponding nutrient gradient regulation scheme is selected for regulation based on the current warming intensity level obtained from the determination. After the regulation was implemented, hydrogen and oxygen stable isotope data of environmental water bodies and plant water were reacquired, and the contribution rate of each water source was quantitatively assessed using a Bayesian mixture model. If the assessment results do not reach the expected threshold, the currently implemented nutrient gradient will be dynamically adjusted based on the deviation in the proportion of water sources.

2. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 1, characterized in that, Real-time collection of environmental water and plant moisture samples within the alpine meadow ecosystem; determination of hydrogen and oxygen stable isotope data; calculation of linear regulation surplus and soil water surplus indices, including: Rainfall samples, soil samples at different depth gradients, and plant stem samples were collected at a set frequency to serve as environmental water and plant moisture samples. Vacuum extraction was performed on the collected environmental water and plant water samples to obtain plant water and soil water, and the abundance values ​​of hydrogen and oxygen stable isotopes in the samples were determined using a spectrometer. Based on the abundance values ​​of the hydrogen and oxygen stable isotopes, the linear regulation surplus and soil water surplus indices are calculated respectively. The line regulation surplus is used to characterize the degree to which plant water deviates from the local atmospheric precipitation line, and the soil water surplus is used to characterize the degree of isotopic shift of plant water relative to the local soil water line.

3. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 2, characterized in that, The linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to obtain the fluctuation amplitude and deviation of the linear adjustment surplus and soil water surplus indices, including: The linear adjustment surplus and soil water surplus indices are compared with their corresponding preset stable fluctuation ranges to determine the magnitude and direction of each index's deviation from the median of the fluctuation range. When the value of any indicator exceeds its corresponding preset stable fluctuation range a certain number of times, the indicator is judged to have significant fluctuations. The degree of deviation of each indicator is determined based on the magnitude and direction of its deviation from the median of the corresponding fluctuation range, as well as the cumulative degree of significant fluctuation of the indicator. The degree of deviation is categorized into mild deviation, moderate deviation, and severe deviation.

4. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 3, characterized in that, Based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indices, identify the instability critical state and hydrological strategy type of plant water use, and determine the current warming intensity level, including: When the degree of deviation reaches moderate or severe deviation, and the number of indicators with significant fluctuations or the cumulative amount of significant fluctuations of a single indicator exceeds a set threshold, the plant is determined to have entered an unstable critical state. The current warming intensity level is determined based on the deviation level mapping, and the current hydrological strategy type is simultaneously identified based on the offset direction of the plant waterline slope relative to the local atmospheric precipitation line and soil waterline, respectively. The slight deviation corresponds to a slight warming level, the moderate deviation corresponds to a moderate warming level, and the severe deviation corresponds to an extreme warming level.

5. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 4, characterized in that, Based on the offset direction of the plant waterline slope relative to the local atmospheric precipitation line and soil waterline, the current hydrological strategy type is simultaneously identified, including: The plant water line was obtained by fitting the stable isotope data of hydrogen and oxygen in the plant water, and the slope of the plant water line was obtained. If the slope of the plant waterline shifts toward the local atmospheric precipitation line, it is identified as an opportunistic strategy that primarily utilizes precipitation pulses and shallow soil water. If the slope of the plant waterline shifts towards the direction of the soil waterline, it is identified as a stable excavation strategy that primarily utilizes deep soil water or deep water sources.

6. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 5, characterized in that, When the plant is determined to have entered the aforementioned instability critical state, a corresponding nutrient gradient regulation scheme is selected for regulation based on the determined current warming intensity level, including: When the current warming intensity level is mild or moderate, the first gradient regulation scheme is selected. The first gradient regulation scheme is to apply nitrogen and phosphorus nutrients to induce plant roots to establish an opportunistic strategy that mainly utilizes precipitation pulses and shallow soil water. When the current warming intensity level is extreme warming or severe drought, the second gradient regulation scheme is selected. The second gradient regulation scheme is to adjust the ratio of nitrogen and phosphorus nutrients to alleviate the metabolic restriction of root extension to deeper layers and induce the root system to turn to a stable digging strategy that utilizes deep soil water and deep water sources.

7. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 1, characterized in that, Based on the reacquired stable isotope data of hydrogen and oxygen, a Bayesian mixture model was used to quantitatively assess the contribution rate of each water source, including: Precipitation, surface soil water, deep soil water, groundwater, and permafrost water in the aforementioned environmental water bodies are used as potential water source end-units. A Bayesian mixture model is constructed using the hydrogen and oxygen stable isotope data of each potential water source end-unit as the source input and the hydrogen and oxygen stable isotope data of the plant water as the mixing input. Set the iteration step size and chain number of the Markov chain Monte Carlo model, run the model until convergence, and output the contribution rate of each potential water source endmember to plant water and its confidence interval. The reliability of the evaluation result is determined based on the confidence interval width of the contribution rate. If the confidence interval width is less than a set threshold, the evaluation result is confirmed to be valid. If the confidence interval width is greater than or equal to the set threshold, the iteration step size is increased and the model is rerun until the confidence interval width is less than the set threshold.

8. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 7, characterized in that, If the assessment results do not meet the expected threshold, the currently implemented nutrient gradient will be dynamically adjusted based on the deviation in the water source ratio, including: The water source contribution rate of each potential water source end-member output by the Bayesian mixture model is compared with the expected contribution rate threshold corresponding to the current warming intensity level to determine the target water source end-member that has not reached the expected threshold and its deviation. Based on the deviation, the amount of nitrogen and / or phosphorus added in the currently executed nutrient gradient is corrected; The nutrient gradient is updated with the corrected nitrogen and phosphorus additions, and the nutrient gradient control scheme corresponding to the current warming intensity level is returned to be executed based on the updated nutrient gradient.

9. The method for regulating water use in alpine meadows based on stable isotope diagnostics according to claim 8, characterized in that, Based on the deviation, the amount of nitrogen and / or phosphorus added in the currently executed nutrient gradient is corrected, including: When the target water source end-unit is precipitation or surface soil water and its water source contribution rate does not reach the expected contribution rate threshold, the amount of nitrogen added is increased to enhance shallow lateral root development and precipitation pulse capture ability. When the target water source is deep soil water, groundwater, or permafrost water, and its water source contribution rate does not reach the expected contribution rate threshold, the amount of phosphorus added is increased and the amount of nitrogen added is controlled not to exceed the set upper limit, so as to enhance the deep root extension capacity.

10. A water use regulation system for alpine meadows based on stable isotope diagnostics, characterized in that, The system is used to implement the alpine meadow water use regulation method based on stable isotope diagnosis according to any one of claims 1-9, the system comprising: The multi-source data sensing module is used to collect environmental water and plant water samples in the alpine meadow ecosystem in real time, measure hydrogen and oxygen stable isotope data, and calculate linear regulation surplus and soil water surplus indicators. The fluctuation analysis module is used to compare the linear adjustment surplus and soil water surplus indices with their corresponding preset stable fluctuation ranges to obtain the fluctuation amplitude and deviation of the linear adjustment surplus and soil water surplus indices. The hydrological strategy diagnosis module is used to identify the instability critical state and hydrological strategy type of plant water use based on the fluctuation range and deviation of the linear regulation surplus and soil water surplus indicators, and to determine the current warming intensity level. The precise regulation decision module is used to select the corresponding nutrient gradient regulation scheme for regulation based on the current warming intensity level obtained from the determination when the plant is determined to have entered the unstable critical state. The effect evaluation module is used to reacquire hydrogen and oxygen stable isotope data of environmental water bodies and plant water after the implementation of regulation, and to quantitatively evaluate the contribution rate of each water source using a Bayesian mixture model. The feedback adjustment module is used to dynamically adjust the currently executed nutrient gradient based on the deviation of the water source ratio if the evaluation result does not reach the expected threshold.

Images