A growth environment multi-factor comprehensive monitoring method and system based on ancient tree protection

Abstract

The application discloses a kind of based on the growth environment multi-factor comprehensive monitoring method and system of old tree protection, including step (S1) non-invasive perception network construction: in the crown layer area of old tree deployment meteorological monitoring unit, real-time acquisition photosynthetic active radiation intensity PAR and crown layer surface temperature T c ; with trunk as center, soil sensor array is radially laid in root distribution area, and soil volume water content θ and soil water potential are monitored in layers;Micro-invasive thermal diffusion probe is installed at the breast diameter of trunk, and xylem original liquid flow flux SF raw Is continuously measured, and initial liquid flow flux SF raw Calibration is carried out;Foundation interferometric radar is erected outside the protection zone, and three-dimensional spatial distribution point cloud P r Of root is obtained by surface scanning.This application can realize more comprehensive old tree monitoring, and timely find the existing abnormality of old tree environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological monitoring, in particular to a growth environment multi-factor comprehensive monitoring method and system based on ancient tree protection. BACKGROUND

[0002] As an important ecological, cultural and scientific research resource, the growth of ancient trees depends on complex environmental conditions and is easily affected by multi-dimensional factors such as meteorological changes, soil quality, mechanical interference, and microbial symbiotic state. Ancient trees have a long growth cycle and weak self-regulation ability. Environmental water stress, temperature stress, mechanical stress, and decline of mycorrhizal symbiotic network function can all lead to weakened growth, decreased structural stability, and even death of ancient trees. Therefore, accurate monitoring and scientific protection of the growth environment of ancient trees are of great significance.

[0003] However, the existing monitoring method for ancient tree protection has obvious limitations: traditional monitoring focuses on a single environmental factor and lacks comprehensive coverage of meteorological, soil, plant physiological, mechanical interference, and microbial symbiotic factors; during data collection, environmental factors such as altitude are not fully considered to interfere with monitoring accuracy, leading to measurement bias of key indicators; the quantification of stress degree lacks a dynamic adaptation mechanism, and the weight cannot be adjusted according to seasonal changes and tree physiological characteristics, making it difficult to truly reflect the actual stress state of ancient trees; at the same time, the function of mycorrhizal symbiosis is not included in the monitoring system, ignoring its important influence on physiological processes such as water absorption of ancient trees, and lacking scientific pre-visualization of structural stability after implementing control measures, leading to insufficient protection measures and poor protection effect. These problems make it difficult for the existing monitoring method to meet the needs of fine and intelligent protection of ancient trees, therefore, a growth environment multi-factor comprehensive monitoring method and system based on ancient tree protection is proposed. SUMMARY

[0004] In view of the defects in the prior art, the present application provides a growth environment multi-factor comprehensive monitoring method based on ancient tree protection, comprising the following steps:

[0005] Step (S1) non-invasive perception network construction:

[0006] Deploy a meteorological monitoring unit in the crown layer area of the ancient tree to continuously collect photosynthetically active radiation intensity PAR and crown surface temperature T c ;

[0007] Radially distribute a soil sensor array around the tree trunk in the root distribution area to monitor soil volumetric water content θ and soil water potential in layers;

[0008] Install a minimally invasive thermal diffusion probe at the breast height of the tree trunk to continuously measure xylem original liquid flow flux SF raw , and calibrate the original liquid flow flux SF raw .

[0009] A ground-based interferometric radar is erected on the periphery of the protection zone, and three-dimensional spatial distribution point cloud P of root system is obtained by ground surface scanning r ;

[0010] A three-axis accelerometer is installed at the base of the tree trunk to collect vibration signals in real time

[0011] A laser scanning device is deployed in the crown layer area to obtain three-dimensional spatial distribution point cloud P of the crown layer c ;

[0012] Micro-soil sampling points are set in the root distribution area outside the periphery of the tree crown projection area for monitoring mycorrhizal symbiotic network

[0013] Step (S2) multi-source data fusion calculation:

[0014] Through edge computing nodes, the data collected by the meteorological monitoring unit, soil sensor array, minimally invasive thermal diffusion probe, ground-based interferometric radar, three-axis accelerometer, laser scanning device, and micro-soil sampling assembly deployed in step (S1) are spatio-temporally registered to eliminate temporal and spatial scale differences

[0015] Dynamic weighting algorithm is used to fuse soil water potential related water stress data, crown heat stress related temperature stress data, and mechanical vibration related mechanical stress data to generate environmental health index EHI

[0016] Step (S3) closed-loop regulation and risk pre-play:

[0017] When EHI exceeds the preset threshold Γ, the targeted irrigation system or physical vibration isolation system is automatically triggered

[0018] Based on three-dimensional spatial distribution point cloud P of root system r and three-dimensional spatial distribution point cloud P of crown layer c A biomechanical model is constructed using finite element risk pre-play method to pre-play the structural stability under the regulation and control measures

[0019] Further, the calibration process of the original sap flow flux SF raw in step (S1) is as follows:

[0020] Elevation compensation function construction: establish a compensation function related to altitude H, which meets the physical law of systematic attenuation of original sap flow flux SF raw with increasing altitude, and obtains the altitude compensation function , which is specifically:

[0021] , H0 is the reference altitude; k H is the altitude compensation coefficient, k H>0, reflecting the decay rate of the altitude on the sap flow measurement value, determined by experiment, H is the actual altitude of the monitoring point; H0 is the reference altitude, as the reference benchmark for altitude compensation;

[0022] Implementing field calibration: the original sap flow flux SF raw combined with the probe calibration coefficient K and the altitude compensation function to calculate the calibrated sap flow flux SF cal , specifically: ;

[0023] Where K is the probe calibration coefficient, which is determined in advance by laboratory constant-flow calibration experiment.

[0024] Further, the generation process of the environmental health index EHI in the step (S2) includes the following steps:

[0025] Step 1, multi-dimensional stress quantification: for the soil water potential related water stress characteristics, the soil water content state and the tree transpiration response are integrated to calculate the water stress degree S w , the calculation formula is:

[0026] ;

[0027] Where θ is the soil volumetric water content, θ c is the wilting point water content of the tree species; SF cal is the calibrated sap flow flux, SFc is the sap flow flux reference value under the health state of the tree species, which is determined by the same region healthy ancient tree xylem sap flow monitoring experiment; α and β are tree species specific weight coefficients, respectively reflecting the contribution weight of soil water content and sap flow flux to water stress degree, both of which are determined by tree species water physiological response experiment;

[0028] For the crown thermal stress characteristics, the temperature stress degree S c is calculated based on the crown surface temperature T t ;

[0029] When , the calculation formula of the temperature stress degree S t is:

[0030] ;

[0031] When , S t =0;

[0032] Where is the crown temperature suitable for the growth of the tree species, is the maximum crown temperature tolerated by the tree species, both of which are determined by tree species temperature physiological response experiment;

[0033] Based on the characteristics of mechanical vibration data, the frequency-time domain energy integration method is used to calculate the mechanical stress degree S. m ;

[0034] Step 2, Dynamic Weight Allocation Mechanism: Based on seasonal variation patterns and tree species physiological characteristics, the Softmax function is used to dynamically allocate the weights of the three stress factors: water, temperature, and mechanical stress. The weight calculation formula is as follows:

[0035] ; ;

[0036] Among them, w i The corresponding water stress weights w w Or temperature stress weight w t Or mechanical stress weight w m C i The seasonal sensitivity coefficients for the three types of stress factors, i.e., C w C t With C m These are the seasonal sensitivity coefficients for three types of stress factors: moisture, temperature, and mechanical stress. These are normalized control parameters used to adjust the weight discrimination, and are set according to the seasonal physiological activity characteristics of tree species.

[0037] Step 3, Index Synthesis Calculation: The environmental health index (EHI) is obtained by weighting and summing each stress level with its corresponding dynamic weight. The calculation formula is as follows:

[0038] ,and ;

[0039] Among them, W w W t With W m The weights for moisture, temperature, and mechanical stress are S, respectively. w S represents the degree of water stress. t S represents the degree of temperature stress. m The degree of mechanical stress.

[0040] Furthermore, the mechanical stress degree S is calculated using the frequency-time domain energy integration method. m The specific process is as follows:

[0041] Vibration signal acquisition and preprocessing:

[0042] The original vibration signal a(t) is acquired by a triaxial accelerometer at the base of the tree trunk. The signal is then subjected to a Fast Fourier Transform (FFT) to convert the time-domain signal into a frequency-domain signal, and the energy spectral density E(f) is obtained, where f is the signal frequency.

[0043] Destructive energy extraction and stress degree calculation:

[0044] Focusing on the dominant frequency band [f min ,f max ] of construction machinery vibration (determined by field spectrum analysis), the energy contribution of the dominant frequency band, i.e. the frequency domain integral result, is extracted by integrating the frequency energy spectrum density in the dominant frequency band within the continuous monitoring time window T, and the cumulative energy in the time domain is averaged to obtain the machinery stress degree S m , the calculation formula is: ;

[0045] The double integration process can effectively filter non-continuous interference signals such as instantaneous impact, and ensure that the quantification result reflects the actual stress degree of the ancient tree caused by machinery vibration.

[0046] Further, the triggering and running process of the physical vibration isolation system includes:

[0047] Trigger condition determination: real-time monitoring of machinery stress degree S m , when S m continuously exceeds the preset threshold δ and the duration reaches τ, the system automatically starts the physical vibration isolation control program; wherein the threshold δ is determined according to the mechanical tolerance threshold experiment of the ancient tree species, and the duration τ is set according to the persistence characteristics of construction vibration.

[0048] Vibration isolation trench construction deployment:

[0049] Based on the root three-dimensional spatial distribution point cloud P r , the main root distribution depth range is determined, and a ring-shaped vibration isolation trench is planned and excavated on the periphery of the root system, the trench depth is set to cover the main root distribution area, and the trench width is determined according to the construction space and vibration isolation requirements;

[0050] Vibration isolation material filling and attenuation effect verification: fill the vibration isolation trench with porous elastic materials (such as a mixture of rubber particles and ceramsite), and detect the system vibration attenuation rate η after filling, which needs to meet the following relationship:

[0051] ;

[0052] Where β is the acoustic attenuation coefficient of the filled material, which is pre-calibrated by laboratory sound wave transmission loss test, and d is the actual thickness of the filled layer; when the attenuation rate η reaches the preset safety standard, it is determined that the vibration isolation system is running effectively.

[0053] Further, the implementation process of the finite element risk pre-play is as follows:

[0054] Root crown model spatial registration: based on the root three-dimensional spatial distribution point cloud P r and the crown three-dimensional spatial distribution point cloud P c, and the space alignment is performed by using an iterative closest point algorithm to make the two in a unified coordinate system, to obtain a registered root crown coupling model, and a registration formula is: ;

[0055] wherein R is a rotation matrix, q is a translation vector, and the optimal transformation parameter is determined by minimizing the distance error between the point clouds, and the specific process is:

[0056] wherein R is a rotation matrix, q is a translation vector, and the optimal transformation parameter is determined by minimizing the distance error between the point clouds, and the specific process is: ;

[0057] This step establishes a complete root crown coupling geometric model for subsequent mechanical analysis;

[0058] Based on the registered root crown coupling model, morphological parameters (including crown width, projected area, and branch and leaf distribution density) are extracted, and wind load vectors are calculated in combination with real-time meteorological data , and the formula is: ;

[0059] wherein p is air density, C d is the air resistance coefficient of the crown layer (determined according to the crown shape characteristics of the tree species), v is the wind speed vector, and A n is the projected area vector of the crown layer in the vertical plane of the wind direction;

[0060] Structural mechanics performance solving: in the root crown coupling model in the unified coordinate system, wood mechanical property parameters (elastic modulus and Poisson's ratio) are introduced to construct a stiffness matrix K, and the structural response of the ancient tree under environmental load is evaluated by solving the static equilibrium equation, and the specific process is: Ku=Fwind+Fsoil

[0061] wherein u is the model node displacement vector, Fsoil is the interaction force between the root system and the soil, and is calculated based on the root-soil contact mechanics model; the structural stability after the implementation of the control measures is pre-forecasted through the distribution characteristics of the displacement vector u.

[0062] Further, the specific steps of the mycorrhizal symbiotic network monitoring are as follows:

[0063] Rhizosphere soil standard sampling: in the root distribution area (based on the root three-dimensional space distribution point cloud P r ) outside the crown projection area, surface soil samples are collected;

[0064] The sampling parameters are: depth ≤10cm, single sample mass ≤50g, and the distance between each sampling point is not less than 1.5m to ensure the representativeness of the sample;

[0065] Functional gene quantitative detection: The collected soil samples are subjected to mycorrhizal fungal functional gene analysis, and real-time fluorescent quantitative PCR technology is used to detect the copy number Ng of the target functional gene; wherein the primers used for PCR amplification are directed to the conserved ITS region of fungal ribosomal DNA, which is determined through previous mycorrhizal fungal specific sequence comparison experiments to ensure the specificity and accuracy of the detection.

[0066] Mycorrhizal efficiency index dynamic calculation: a time decay factor is introduced to construct the mycorrhizal efficiency index MEI, which is used to quantify the functional activity of the mycorrhizal symbiotic network, and the calculation formula of the mycorrhizal efficiency index MEI is: ;

[0067] Wherein, N g is the copy number of the target functional gene of mycorrhizal fungi in the soil sample, which is detected by real-time fluorescent quantitative PCR technology, N0is the copy number of the functional gene of mycorrhizal fungi under the healthy state of the tree species, which is determined by detecting the rhizosphere soil of the healthy ancient tree in the same region; k d is the time decay factor, which reflects the natural decay characteristics of mycorrhizal activity with sampling interval, which is determined according to the dynamic monitoring experiment of soil microbial community activity; t is the time interval from the last effective sampling;

[0068] The mycorrhizal efficiency index MEI is also used to participate in the correction process of water stress degree.

[0069] Further, the mycorrhizal efficiency index MEI participates in the correction process of water stress degree, which includes the following steps:

[0070] Correction trigger condition judgment: the calculated mycorrhizal efficiency index MEI is monitored in real time, and when MEI is lower than the preset threshold μ, the correction mechanism of water stress degree is automatically activated;

[0071] Wherein, the threshold μ is the critical activity value of the mycorrhizal symbiotic function of the tree species, which is determined by the mycorrhizal efficiency comparison experiment of healthy ancient trees and weakened ancient trees;

[0072] Coupling correction calculation: based on the activated correction mechanism, the original water stress degree S w is dynamically corrected by introducing the mycorrhizal symbiotic compensation term, and the corrected water stress degree S w ' is obtained, and the calculation formula is: ;

[0073] Wherein, γ is the compensation coefficient, which reflects the contribution rate of the mycorrhizal symbiotic network to the water absorption of the tree, which is determined by the comparison test of water use efficiency of the tree under different mycorrhizal infection degrees; the corrected S w ' can more accurately reflect the actual water stress state of the ancient tree under the damage of mycorrhizal function, and provide more accurate input parameters for the closed-loop regulation of step (S3).

[0074] The growth environment multi-factor comprehensive monitoring system based on ancient tree protection comprises:

[0075] The perception layer comprises:

[0076] The meteorological monitoring unit is arranged in the ancient tree crown layer region and is used for collecting the photosynthetically active radiation intensity PAR and the crown layer surface temperature T c in real time.

[0077] The soil sensor array is radially arranged in the root distribution area with the trunk as the center and is used for monitoring the soil volume water content θ and the soil water potential in layers.

[0078] The minimally invasive thermal diffusion probe is installed at the breast height of the trunk and is used for continuously collecting the xylem sap flow flux SF raw .

[0079] The ground-based interferometric radar is erected at the periphery of the protection area and is used for obtaining the root three-dimensional spatial distribution point cloud P r by surface scanning.

[0080] The three-axis accelerometer is installed at the base of the trunk and is used for collecting vibration signals in real time.

[0081] The laser scanning device is arranged in the crown layer region and is used for obtaining the crown three-dimensional spatial distribution point cloud P c .

[0082] The micro soil sampling assembly is arranged in the rhizosphere region and is used for collecting rhizosphere soil samples to support the monitoring of the mycorrhizal symbiotic network.

[0083] The data processing layer comprises an edge computing node, and the edge computing node comprises:

[0084] The space-time registration unit is used for calibrating the time and space scales of the heterogeneous sensor data collected by the perception layer.

[0085] The dynamic weighted fusion unit is used for performing weight distribution on the water, temperature and mechanical stress factors based on a Softmax function and fusing the stress degrees to generate an environmental health index EHI.

[0086] The mycorrhizal efficiency calculation unit is used for quantitatively analyzing the mycorrhizal fungal functional gene copy number of the soil sample, calculating a mycorrhizal efficiency index MEI and a modified water stress degree S w ′.

[0087] The regulation and rehearsal layer comprises:

[0088] The closed-loop control subsystem includes a targeted irrigation module and a physical vibration isolation module, and is used for automatically triggering corresponding control measures when the EHI exceeds a preset threshold Gamma;

[0089] The finite element risk pre-play subsystem is used for pre-playing the structural stability of the ancient tree under the control measures based on the three-dimensional spatial distribution point cloud P of the root system r and the three-dimensional spatial distribution point cloud P of the canopy c The root-canopy coupled biomechanical model is constructed to pre-play the structural stability of the ancient tree under the control measures.

[0090] The beneficial effects of the present application are embodied in:

[0091] The growth environment multi-factor comprehensive monitoring method and system based on ancient tree protection break through the limitation of traditional single factor monitoring, and comprehensively reflect the complex environmental conditions of the growth of the ancient tree; the altitude compensation function is introduced for the liquid flow monitoring, accurate calibration is realized by combining the probe calibration coefficient, and the systematic interference of altitude on the measured value is eliminated; the dynamic weighting algorithm is used to distribute the water, temperature and mechanical stress factor weights according to the seasonal changes and the characteristics of the tree species, and the generated environmental health index can dynamically adapt to the physiological state of the ancient tree, and the quantitative result is more in line with the actual stress degree; the physical vibration isolation is based on the three-dimensional distribution of the root system to plan the annular vibration isolation ditch, fill the porous elastic material, and ensure the effect by verifying the attenuation rate, and the mechanical vibration influence is targetedly weakened; when the mycorrhizal efficiency index is lower than the threshold value, the water stress degree is dynamically corrected, the irrigation strategy is optimized, and the accuracy of the control measures is improved; based on the root-canopy coupled biomechanical model, the structural response under the wind load and the soil action force is pre-played by the finite element method, the spatial registration of the three-dimensional point cloud of the root system and the canopy is combined, the influence of the control measures on the structural stability of the ancient tree is evaluated in advance, blind intervention is avoided, and scientific basis is provided for the protection decision. BRIEF DESCRIPTION OF DRAWINGS

[0092] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or the prior art description. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual proportion.

[0093] Figure 1 The flowchart of the present application. DETAILED DESCRIPTION

[0094] The embodiments of the technical solutions of the present application will be described in detail below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, but cannot limit the protection scope of the present application.

[0095] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in the present application should be the usual meanings understood by the skilled in the art to which the present application belongs.

[0096] As Figure 1 shown, a growth environment multi-factor comprehensive monitoring method based on ancient tree protection includes the following steps:

[0097] Step (S1) non-invasive perception network construction:

[0098] Deploy meteorological monitoring units in the ancient tree canopy area, and collect the photosynthetically active radiation intensity PAR and the canopy surface temperature T c in real time.

[0099] Lay out a soil sensor array radially in the root distribution area with the trunk as the center, and monitor the soil volumetric water content θ and the soil water potential in layers.

[0100] Install a minimally invasive thermal diffusion probe at the breast height of the trunk, continuously measure the xylem sap flow flux SF raw , and calibrate the initial sap flow flux SF raw .

[0101] Erect a ground-based interferometric radar outside the protection area, and obtain the root three-dimensional spatial distribution point cloud P r by surface scanning.

[0102] Install a three-axis accelerometer at the base of the trunk, and collect vibration signals in real time.

[0103] Deploy a laser scanning device in the canopy area, and obtain the canopy three-dimensional spatial distribution point cloud P c .

[0104] Set up trace soil sampling points in the root distribution area outside the edge of the tree crown projection area for mycorrhizal symbiotic network monitoring.

[0105] Step (S2) multi-source data fusion calculation:

[0106] Through edge computing nodes, the data collected by the meteorological monitoring units, soil sensor arrays, minimally invasive thermal diffusion probes, ground-based interferometric radars, three-axis accelerometers, laser scanning devices, and trace soil sampling components deployed in step (S1) are spatio-temporally registered to eliminate time and spatial scale differences.

[0107] Use a dynamic weighting algorithm to fuse the soil water potential related water stress data, the canopy thermal stress related temperature stress data, and the mechanical vibration related mechanical stress data to generate an environmental health index EHI.

[0108] Step (S3) closed-loop regulation and risk pre-play:

[0109] When the EHI exceeds a preset threshold Γ, an automatic trigger is initiated for a targeted irrigation system or a physical vibration isolation system;

[0110] Based on the three-dimensional spatial distribution point cloud P r of the root system With the three-dimensional spatial distribution point cloud P c of the canopy A finite element risk pre-play method is used to construct a biomechanical model to pre-play the structural stability under the control measures.

[0111] The calibration process of the original sap flow flux SF raw in step (S1) is as follows:

[0112] Elevation compensation function construction: establish a compensation function related to the altitude H , which meets the physical law of systematic attenuation of the original sap flow flux SF raw with the increase of altitude, and obtains the altitude compensation function , specifically:

[0113] , H0 is the reference altitude; k H is the altitude compensation coefficient, k H > 0, reflecting the attenuation rate of altitude on the sap flow measurement value, which is determined by experiment, H is the actual altitude of the monitoring point; H0 is the reference altitude as the reference for altitude compensation;

[0114] Implement field calibration: combine the original sap flow flux SF raw collected by the minimally invasive thermal diffusion probe with the probe calibration coefficient K and the altitude compensation function to calculate the calibrated sap flow flux SF cal , specifically: ;

[0115] Where K is the probe calibration coefficient, which is determined in advance by laboratory constant-flow calibration experiment;

[0116] By constructing the altitude compensation function and implementing field calibration, the systematic interference of altitude on xylem sap flow flux measurement is solved, and the accuracy and reliability of the sap flow monitoring data are significantly improved. Sap flow flux is a core indicator reflecting tree water absorption, transpiration state and growth vigor, and its measurement accuracy directly affects the calculation of water stress degree, the generation of environmental health index and the effectiveness of subsequent control measures. The calibration process quantifies the attenuation effect of altitude on the measurement value, ensuring the comparability and authenticity of ancient tree sap flow data in different altitude regions, providing key basic data support for multi-factor comprehensive monitoring and precise protection.

[0117] Assuming that the reference altitude H0 of a certain area is 500 meters, and a certain ancient tree grows at an actual altitude H = 1500 meters, the altitude compensation coefficient kH = 0.0001 / m (reflecting the rate of attenuation of sap flow measurements per 1m of elevation gain).

[0118] First, calculate the elevation compensation function:

[0119] ;

[0120] If the original sap flow flux SF raw = 80 kg / h, and the probe calibration coefficient K = 1.1 is determined by laboratory constant flow calibration.

[0121] After calibration, the sap flow flux is SF cal = K·SF raw ·f(H) = 1.1 x 80 x 0.9 = 79.2 kg / h.

[0122] If no elevation calibration is performed, and SF raw x K = 88 kg / h is used directly, the tree sap flow flux will be overestimated, resulting in a lower calculation of water stress, and the tree is mistakenly considered to have sufficient water, which may delay targeted irrigation and other control measures; the calibrated data 79.2 kg / h is closer to the actual sap flow state, and can accurately support water stress assessment and subsequent protection decisions.

[0123] The generation process of the environmental health index EHI in the step (S2) includes the following steps:

[0124] Step 1, multi-dimensional stress quantification: for soil water potential related water stress characteristics, the soil water content and tree transpiration response are combined to calculate the water stress S w , and the calculation formula is:

[0125] ;

[0126] Where θ is the soil volumetric water content, θ c is the wilting point water content of the tree species; SF cal is the calibrated sap flow flux, SF c is the sap flow flux baseline value under the health state of the tree species, which is determined by monitoring the sap flow of healthy ancient trees in the same area; and α and β are tree species specific weight coefficients, reflecting the contribution weight of soil water content and sap flow flux to water stress, respectively, which are determined by tree water physiological response experiments.

[0127] For crown thermal stress characteristics, the temperature stress S c is calculated based on the crown surface temperature T t ;

[0128] When , the temperature stress S tThe calculation formula is:

[0129] ;

[0130] When S t =0;

[0131] Wherein is the canopy temperature suitable for the growth of the tree species, is the canopy maximum temperature tolerated by the tree species, both determined by the tree species temperature physiological response test;

[0132] For mechanical vibration data characteristics, the frequency domain-time domain energy integral method is used to calculate the mechanical stress degree S m ;

[0133] Step 2, dynamic weight distribution mechanism: according to the seasonal variation law and the physiological characteristics of tree species, the weights of the three types of stress factors of water, temperature and mechanical are dynamically distributed by using the Softmax function, and the weight calculation formula is:

[0134] , ;

[0135] Wherein, w i corresponds to the water stress weight w w or the temperature stress weight w t or the mechanical stress weight w m ; C i is the seasonal sensitivity coefficient of the three types of stress factors, that is, C w , C t and C m are the seasonal sensitivity coefficients of the three types of stress factors of water, temperature and mechanical; is a normalized control parameter, which is used to adjust the weight differentiation degree, and is set according to the seasonal physiological activity characteristics of tree species;

[0136] Step 3, exponential synthesis calculation: the weighted sum of each stress degree and the corresponding dynamic weight is obtained to obtain the environmental health index EHI, and the calculation formula is:

[0137] , and ;

[0138] Wherein, W w , W t and W m are the water, temperature and mechanical stress weights, S w is the water stress degree, S t is the temperature stress degree, and S m is the mechanical stress degree;

[0139] Specific quantification methods are designed for three key environmental stress factors: water, temperature, and machinery, covering the core influences of the soil, plant, and atmosphere continuum and external interference, avoiding the limitations of single stress assessment, and comprehensively capturing the environmental pressure faced by ancient trees. Based on seasonal changes and tree physiological characteristics, the weights of the three types of stress factors are dynamically allocated through the Softmax function, allowing the EHI to adapt to the different sensitivities of ancient trees to environmental factors in different seasons. The evaluation results are more in line with actual physiological needs. By weighted summation, multidimensional stress is integrated into a single EHI, realizing the quantitative expression of environmental health status, providing clear and operable judgment basis for subsequent closed-loop control, and improving the precision and effectiveness of protection measures.

[0140] Taking adult camphor trees in a certain region as an example in the summer high-temperature season:

[0141] Water stress degree S w : Camphor wilt point water content θ c = 15%, current soil volumetric water content θ = 20%; healthy sap flow reference value SF c = 100 kg / h, calibrated sap flow SF cal = 90 kg / h; tree species-specific weights α = 0.6, β = 0.4.

[0142] Substitute into the formula: S w = max(0, 1 - 0.6 x 20% / 15% - 0.4 x 90 / 100) = max(0, 1 - 0.8 - 0.36) = max(0, -0.16) = 0 (water is sufficient, no stress).

[0143] Temperature stress degree S t : Camphor suitable crown temperature = 25℃, maximum tolerance temperature = 35℃, current crown temperature T c = 32℃> .

[0144] Substitute into the formula: S t = max(0, (32 - 35) / (25 - 35)) = max(0, -3 / -10) = 0.3, moderate temperature stress exists.

[0145] Mechanical stress degree S m : Through frequency-time domain integration calculation, construction vibration is weak, S m = 0.1;

[0146] Seasonal sensitivity coefficients: water C w = 0.3, temperature C t = 0.8, machinery C m = 0.2; normalization parameter a = 0.5;

[0147] Weight calculation:

[0148]

[0149]

[0150] Exponential synthesis: EHI = 0.27 x 0 + 0.397 x 0.3 + 0.333 x 0.1 = 0 + 0.119 + 0.033 = 0.152.

[0151] The dynamic weight mechanism of the case gives higher weight to temperature stress due to the high summer temperature sensitivity coefficient, and the calculated EHI more accurately reflects the actual pressure of high temperature on camphor trees, providing a more reasonable basis for triggering crown cooling or shading regulation.

[0152] The frequency-time energy integration method is used to calculate the mechanical stress degree S m The specific process is as follows:

[0153] Vibration signal acquisition and pretreatment:

[0154] The original vibration signal a(t) is collected by the triaxial accelerometer at the base of the tree trunk, and the signal is subjected to fast Fourier transform (FFT) to convert the time domain signal to frequency domain signal to obtain the energy spectrum density E(f), where f is the signal frequency.

[0155] Damage energy extraction and stress degree calculation:

[0156] Focus on the dominant frequency band [f min ,f max ] of construction machinery vibration (this frequency band is determined by field construction machinery spectrum analysis), within the continuous monitoring time window T, first integrate the frequency energy spectrum density in the dominant frequency band to extract the energy contribution of the frequency band, i.e. the frequency domain integral result, then average the cumulative energy in the time domain to obtain the mechanical stress degree S m , the calculation formula is:

[0157]

[0158] Among them, the double integration process can effectively filter out non-persistent interference signals such as instantaneous impact, and ensure that the quantification result reflects the actual stress degree of mechanical vibration on ancient trees;

[0159] In summer, an adult camphor tree is subjected to mechanical vibration due to surrounding road construction, and the triaxial accelerometer at the base of the tree trunk collects vibration signals in real time, which needs to be calculated by the frequency-time energy integration method to calculate the mechanical stress degree S m And the synthesis of the environmental health index (EHI) provides the mechanical stress parameter.

[0160] Vibration signal acquisition and pretreatment:​​​

[0161] The triaxial accelerometer collects the original vibration signal a(t), and the signal is subjected to fast Fourier transform (FFT) to convert it into a frequency domain signal and obtain the energy spectrum density E(f), where f is the signal frequency.

[0162] Through spectral analysis of field construction machinery (such as excavators and road rollers), it is determined that the dominant frequency band of such machinery vibration is [f min ,f max ] = [10 Hz, 50 Hz]. This frequency band vibration has the most significant impact on the root system and trunk structure of camphor trees.

[0163] Damage energy extraction and stress degree calculation:

[0164] Set the continuous monitoring time window T = 30 minutes = 1800 seconds (covering the typical duration of construction vibration).

[0165] Frequency domain energy integration: integrate the energy spectrum density E(f) in the dominant frequency band [10 Hz, 50 Hz] to extract the energy contribution of this frequency band, and obtain the relationship between the cumulative energy at each time and time .

[0166] Time domain energy averaging: integrate the frequency domain integration results in the time window T, and then divide by T to obtain the mechanical stress degree S m .

[0167] Assuming that the time domain cumulative energy after frequency domain integration is = 180, which is obtained by actual measurement and integration calculation of the sensor;

[0168] At this time = 1 / 1800 x 180 = 0.1.

[0169] The triggering and running process of the physical vibration isolation system includes:

[0170] Trigger condition determination: real-time monitoring of the mechanical stress degree S m , when S m continuously exceeds the preset threshold δ and the duration reaches τ, the system automatically starts the physical vibration isolation control program; wherein the preset threshold δ is determined according to the mechanical tolerance threshold experiment of ancient tree species, and the duration τ is set according to the persistence characteristics of construction vibration.

[0171] Vibration isolation trench construction deployment:

[0172] Based on the three-dimensional spatial distribution point cloud P r of the root system, the main root distribution depth range is determined, and a ring-shaped vibration isolation trench is planned and excavated on the periphery of the root system. The trench depth is set to cover the main root distribution area, and the trench width is determined according to the construction space and vibration isolation requirements;

[0173] Vibration isolation material filling and attenuation effect verification: Fill the vibration isolation trench with porous elastic materials such as a mixture of rubber particles and ceramic particles. After filling, detect the system vibration attenuation rate η, which needs to meet the following relationship:

[0174] η = 1 - exp(-β·d);

[0175] Where β is the acoustic attenuation coefficient of the filled material, which is calibrated in advance through laboratory sound transmission loss test, d is the actual thickness of the filling layer; When the attenuation rate η reaches the preset safety standard, it is determined that the vibration isolation system is effective;

[0176] Through the double triggering conditions of continuous threshold value exceeding of mechanical stress degree and duration, filter transient impact and other non-durable interference, ensure that the vibration isolation system only starts when the ancient tree faces substantial and continuous mechanical threat, reduce unnecessary construction cost and disturbance to the growth environment of the ancient tree;

[0177] Based on the three-dimensional spatial distribution point cloud of root system, the ring-shaped vibration isolation trench is planned, and the trench depth accurately covers the main root distribution area, avoiding the problem of insufficient protection or excessive construction caused by unknown root distribution in traditional vibration isolation measures, and maximizing the reduction of the influence of vibration on the key root system of the ancient tree.

[0178] Calculate the vibration attenuation rate through the acoustic attenuation coefficient and the filling thickness, and compare it with the preset safety standard to ensure that the actual effect after filling the vibration isolation material meets the standard, so that the vibration isolation measures are upgraded from "empirical construction" to quantitative verification scientific protection, and the effectiveness of mechanical stress prevention and control is significantly improved;

[0179] If the construction intensity of the surrounding road of a certain adult camphor tree increases in summer, the mechanical vibration intensifies, and the three-axis accelerometer at the base of the tree trunk monitors the mechanical stress degree S m Rises, it needs to be evaluated whether to trigger the physical vibration isolation system.

[0180] Trigger condition determination:

[0181] Camphor tree mechanical tolerance threshold experiment determination: The mechanical stress degree threshold δ = 0.2, exceeding this value may cause structural damage to the trunk and root system, the duration τ = 10 minutes, set according to the construction vibration persistence characteristics, to avoid false triggering of transient vibration.

[0182] Real-time monitoring shows that the construction vibration causes S m Rises to 0.25 and remains continuously for 12 minutes, which exceeds τ = 10 minutes, meets the triggering condition, and the system automatically starts the physical vibration isolation control program.

[0183] Vibration isolation trench construction deployment:

[0184] Based on the three-dimensional spatial distribution point cloud P rAnalysis, the main roots of camphor trees are mainly distributed in the range of 0.6-1.5 meters below the ground surface. In order to cover the main root distribution area, a ring-shaped vibration isolation trench is planned to be dug at a distance of 1 meter from the periphery of the root system, the trench depth is set to 1.8 meters, which is slightly deeper than the maximum depth of the main roots, to ensure the vibration isolation effect, and the trench width is determined as 0.6 meters according to the construction space.

[0185] Vibration isolation material filling and attenuation effect verification:

[0186] Fill the mixed porous elastic material of rubber particles and ceramsite into the vibration isolation trench, the laboratory sound wave transmission loss test pre-calibrates the acoustic attenuation coefficient of the material β = 0.4 / m, and the actual filling layer thickness d = 0.5 m.

[0187] Calculate the vibration attenuation rate: η = 1 - exp(-β·d) = 1 - exp(-0.4×0.5) = 1 - exp(-0.2) ≈ 1 - 0.8187 = 0.1813, i.e. 18.13%.

[0188] The preset safety standard is that the vibration attenuation rate is greater than or equal to 15%, and the actual attenuation rate is 18.13%, which meets the standard, and it is determined that the vibration isolation system is effective and significantly reduces the transmission of construction vibration to the root system;

[0189] If the above mechanism is not used, it may be misstarted due to instantaneous vibration exceeding the standard, or it may not be sufficient for vibration protection due to the depth of the vibration isolation trench not covering the main roots; and the present scheme precisely triggers, targets the root system for construction, and verifies the effect, avoiding ineffective intervention and ensuring that the vibration attenuation meets the standard, effectively protecting camphor trees from long-term damage caused by continuous construction vibration.

[0190] The implementation process of the finite element risk pre-play is as follows:

[0191] Root crown model space registration: based on root system three-dimensional space distribution point cloud P r and crown three-dimensional space distribution point cloud P c , the iterative closest point algorithm is used for space alignment to make them in a unified coordinate system, and the registered root crown coupling model is obtained, and the registration formula is: ;

[0192] wherein R is a rotation matrix, q is a translation vector, and the optimal transformation parameters are determined by minimizing the distance error between the point clouds:

[0193] wherein R is a rotation matrix, q is a translation vector, and the optimal transformation parameters are determined by minimizing the distance error between the point clouds, specifically: ;

[0194] This step establishes a complete root crown coupling model for subsequent mechanical analysis;

[0195] Morphological parameters (including crown width, projected area, branch and leaf distribution density) are extracted from the registered root-crown coupled model, and wind load vector is calculated combined with real-time meteorological data , the formula is: ;

[0196] Where, p is the air density, C d is the air resistance coefficient of the crown layer, which is determined by the crown shape characteristics of the tree species, v is the wind speed vector, A n is the projected area vector of the crown layer in the vertical plane of the wind direction;

[0197] Structural mechanics performance solution: In the root-crown coupled model of the unified coordinate system, the wood mechanics characteristic parameters (elastic modulus, Poisson's ratio) are introduced to construct the stiffness matrix K, and the structural response of the ancient tree under the environmental load is evaluated by solving the static equilibrium equation, which is: Ku=Fwind+Fsoil;

[0198] Where, u is the model node displacement vector, Fsoil is the interaction force between the root and the soil (calculated based on the root-soil contact mechanics model); the structural stability after the implementation of the control measures is predicted through the distribution characteristics of the displacement vector u;

[0199] The spatial registration of root and crown three-dimensional point clouds is performed by the iterative closest point algorithm, and the two are unified to the same coordinate system to construct a complete root-crown coupled geometric model, eliminating the limitations of traditional single structure analysis and ensuring the geometric accuracy of the mechanics analysis; Based on the registered crown shape parameters (such as crown width, projected area) combined with real-time meteorological data to calculate wind load, wood mechanics characteristic parameters are introduced to construct the stiffness matrix, so that the simulation of environmental load is more in line with the actual stress state of the ancient tree, and the error of empirical evaluation is avoided; By solving the static equilibrium equation, the node displacement distribution of the model is obtained, which can evaluate the structural response after the implementation of the control measures in advance, identify the potential fracture and inclination risk, avoid secondary damage caused by blind intervention, and provide quantitative verification basis for the effectiveness of the protection measures;

[0200] For example, an adult camphor tree in summer needs to be evaluated for its structural stability under strong wind environment after being regulated by a physical vibration isolation system, and whether the vibration isolation measures affect the root anchoring ability.

[0201] Root-crown model spatial registration:

[0202] Collect root three-dimensional spatial distribution point cloud P r (main root distribution depth 0.6-1.5 meters) and crown three-dimensional spatial distribution point cloud P c (crown width 8m x 10m), and use the iterative closest point algorithm for registration.

[0203] The optimal rotation matrix R and translation vector q are determined by minimizing the distance error between the point clouds, and the registered root point cloud P is obtained r ′=R·P r The root crown model is placed in a unified coordinate system with the trunk base as the origin, and a complete root crown coupling geometric model is constructed.

[0204] Wind load vector calculation:

[0205] Morphological parameters are extracted from the registered canopy model: the projected area of the canopy on the wind direction vertical plane An=25m 2 , the canopy air resistance coefficient C d =0.8 (experimental determination of camphor crown shape characteristics); Real-time weather data shows that the wind speed ||v||=10m / s, and the air density p=1.225kg / m 3 ;

[0206] =1 / 2×0.8×102×25=1225N;

[0207] Structural mechanics performance solution:

[0208] The mechanical parameters of camphor wood are introduced: elastic modulus =10GPa, Poisson's ratio =0.3, and the stiffness matrix K is constructed; Based on the root-soil contact mechanics model, the interaction force between root and soil Fsoil=800N (upward fixation force) is calculated.

[0209] Solving the static equilibrium equation Ku=Fwind+Fsoil, the model node displacement vector u is obtained, and the calculation shows that the maximum displacement of the canopy is 0.15 meters, and the displacement of the root anchoring area is less than 0.02 meters, which are within the safety threshold (maximum allowable displacement 0.3 meters).

[0210] If the above pre-play method is not used, only by experience to judge the influence of strong wind on camphor tree, it may underestimate the root fixation capacity or overestimate the wind damage risk; And this scheme verifies the root fixation capacity of the vibration isolation measure through root crown coupling modeling, real wind load simulation and displacement analysis, and the structural stability of camphor tree under the current strong wind is verified, and no additional reinforcement is needed, which provides a scientific basis for protection decision.

[0211] The specific steps of monitoring the mycorrhizal symbiotic network are as follows:

[0212] Rhizosphere soil sampling: in the root distribution area outside the canopy projection area (based on the root three-dimensional spatial distribution point cloud P r Determine the sampling range), collect surface soil samples;

[0213] The sampling parameters are: depth ≤10cm, single sample mass ≤50g, and the distance between each sampling point is not less than 1.5m to ensure the representativeness of the sample;

[0214] Functional gene quantitative detection: The mycorrhizal fungal functional gene analysis was carried out on the collected soil samples, and the real-time fluorescent quantitative PCR technology was used to detect the copy number Ng of the target functional gene; wherein the primers used for PCR amplification are directed to the conserved ITS region of fungal ribosomal DNA (the region is determined through the previous mycorrhizal fungal specific sequence comparison experiment) to ensure the specificity and accuracy of the detection.

[0215] Mycorrhizal efficiency index dynamic calculation: the time decay factor is introduced to construct the mycorrhizal efficiency index MEI, which is used to quantify the functional activity of the mycorrhizal symbiotic network, and the calculation formula of the mycorrhizal efficiency index MEI is:

[0216] Wherein, N g is the copy number of the target functional gene of mycorrhizal fungi in the soil sample, which is detected by real-time fluorescent quantitative PCR technology, N0 is the copy number of the mycorrhizal functional gene of the tree species in a healthy state, which is determined by detecting the rhizosphere soil of the healthy ancient tree in the same region; kd is the time decay factor, which reflects the natural decay characteristics of the mycorrhizal activity with the sampling interval, which is determined according to the dynamic monitoring experiment of soil microbial community activity; t is the time interval from the last effective sampling;

[0217] The mycorrhizal efficiency index MEI is also used to participate in the correction process of water stress degree;

[0218] The key soil microbial factor of mycorrhizal fungi is included in the monitoring of the growth environment of ancient trees, which breaks through the limitation of traditional focus on meteorology, soil physical and chemical indicators, enriches the evaluation dimension of the health status of ancient trees from the perspective of plant and microbial symbiotic function, and more comprehensively reflects the microecological environment of the growth of ancient trees; accurately quantify the mycorrhizal activity and dynamically reflect the functional state: the real-time fluorescent quantitative PCR technology is used to quantitatively detect the functional gene of mycorrhizal fungi, and the time decay factor is introduced to construct MEI, which realizes the quantitative and dynamic evaluation of the functional activity of the mycorrhizal symbiotic network, avoids subjective experience judgment, and makes the microbial functional state measurable and traceable; MEI can directly participate in the correction process of water stress degree, provide microbial basis for accurate judgment of the actual water absorption capacity of ancient trees, solve the problem of ignoring the auxiliary water absorption function of mycorrhizae in traditional water stress evaluation, and make the monitoring results more in line with the physiological reality of ancient trees;

[0219] For example, an adult camphor tree needs to be monitored and evaluated through the mycorrhizal symbiotic network after physical vibration isolation and irrigation control in summer, so as to provide basis for the correction of water stress degree.

[0220] ​Rhizosphere soil standard sampling: Based on the three-dimensional spatial distribution point cloud of root system, the sampling range is determined as the root distribution area outside the outer edge of the tree crown projection area. Three micro soil sampling points are set, and the sampling parameters strictly follow the standard: depth 8 cm (≤10 cm), single sample mass 45 g (≤50 g), sampling point spacing 2 m (≥1.5 m), to ensure sample representativeness.

[0221] Functional gene quantitative detection: The mycorrhizal fungal functional gene analysis is performed on the collected soil samples, and the real-time fluorescent quantitative PCR technology is used to detect the target functional gene copy number. The results show that the average target gene copy number N g =3.2×10 5 copies / g soil.

[0222] The benchmark value of the mycorrhizal functional gene copy number of the healthy camphor tree is:

[0223] N0=5.0×10 5 copies / g soil, which is determined by detecting the rhizosphere soil of the healthy ancient tree in the same area.

[0224] Mycorrhizal efficiency index MEI calculation:

[0225] The time interval t from the last effective sampling is 15 days, and the time decay factor k d =0.02 / day of the mycorrhizal of the camphor tree in the region is determined by the soil microbial community activity dynamic monitoring experiment.

[0226] Substitute the formula: , and calculate MEI≈−0.1938×0.7408≈−0.1436.

[0227] The mycorrhizal efficiency index MEI participates in the correction process of the water stress degree, including the following steps:

[0228] Correction trigger condition judgment: Real-time monitoring of the calculated mycorrhizal efficiency index MEI, when MEI is lower than the preset threshold μ, the correction mechanism of the water stress degree is automatically activated;

[0229] Wherein, the threshold μ is the critical activity value of the mycorrhizal symbiotic function of the tree species, which is determined by the mycorrhizal efficiency comparison experiment of the healthy ancient tree and the weakened ancient tree;

[0230] Coupling correction calculation: Based on the activated correction mechanism, the original water stress degree S w is dynamically corrected by introducing the mycorrhizal symbiotic compensation term, and the corrected water stress degree S w ′ is obtained, and the calculation formula is: ;

[0231] Wherein, γ is the compensation coefficient, reflecting the contribution rate of the mycorrhizal symbiotic network to tree water absorption, determined through comparative experiments on tree water use efficiency under different degrees of mycorrhizal infection; the corrected S w It can more accurately reflect the actual water stress state of ancient trees under the condition of impaired mycorrhizal function, and provide more precise input parameters for the closed-loop regulation of step (S3);

[0232] Mycorrhizal symbiotic networks can assist ancient trees in absorbing water. When mycorrhizal function is impaired, i.e., when the Mycorrhizal Intake (MEI) decreases, the actual water absorption capacity of the ancient tree will decline, a factor that traditional water stress assessments do not consider. By triggering correction through MEI and dynamically introducing a mycorrhizal symbiotic compensation term, the corrected water stress assessment more accurately reflects the actual water status of ancient trees under abnormal microbial function, avoiding underestimation of stress risk. The correction mechanism is activated only when the MEI is below a critical threshold, specifically responding to scenarios where mycorrhizal function is impaired. This approach does not interfere with water assessment under normal mycorrhizal conditions and can provide more accurate input parameters for irrigation and other control measures when the microecological balance is disrupted, thus improving the adaptability of protection measures.

[0233] If a mature camphor tree in summer has an MEI of approximately -0.1436 (lower than the healthy baseline) as measured by mycorrhizal monitoring, the water stress level needs to be adjusted to provide an accurate basis for subsequent regulation.

[0234] Corrected trigger condition determination:

[0235] The critical activity value (threshold μ) of the mycorrhizal symbiotic function of camphor trees was determined to be μ=0.2 through a comparative experiment between healthy and weakened ancient trees (MEI below this value indicates that mycorrhizal function is significantly impaired).

[0236] Real-time monitoring shows that MEI≈-0.1436<μ=0.2 meets the correction trigger condition, automatically activating the moisture stress correction mechanism.

[0237] Coupled correction calculation: Original water stress degree S w The value is 0, which, based on soil moisture content and liquid flow rate, indicates sufficient moisture.

[0238] The compensation coefficient γ was determined to be 0.2 through experiments with different degrees of mycorrhizal infection, reflecting the contribution rate of mycorrhizae to the water absorption of camphor trees.

[0239] Substitute into the correction formula:

[0240] = ;

[0241] Without a correction mechanism, the original S will be used. w =0, mistakenly assuming sufficient water for the camphor tree, which may delay irrigation adjustments; while the corrected S wThe value of ≈0.3436 accurately reflects the actual water stress caused by impaired mycorrhizal function. The reduced water absorption capacity of mycorrhizae means that even if the soil moisture content meets the standard, trees still face the potential risk of insufficient water. This provides a more reasonable basis for the subsequent activation of targeted irrigation systems and avoids the neglect of hidden stress caused by abnormal microecological function.

[0242] A comprehensive monitoring system for the growth environment of ancient trees, based on multi-factor monitoring, includes:

[0243] The perception layer includes:

[0244] Meteorological monitoring units, deployed in the canopy area of ​​ancient trees, are used to collect real-time data on photosynthetically active radiation (PAR) and canopy surface temperature (T). c ;

[0245] A soil sensor array is arranged radially around the tree trunk in the root distribution area to monitor soil volumetric water content θ and soil water potential in layers.

[0246] A minimally invasive thermal diffusion probe, installed at the trunk diameter at breast height (DBH), is used to continuously collect the original sap flow rate (SF) in the xylem. raw ;

[0247] Ground-based interferometric radar, installed outside the protected area, is used to obtain a three-dimensional spatial distribution point cloud of the root system P through surface scanning. r ;

[0248] A triaxial accelerometer is installed at the base of the tree trunk to collect vibration signals in real time.

[0249] Laser scanning equipment, deployed in the canopy region, is used to acquire a three-dimensional spatial distribution point cloud P of the canopy. c ;

[0250] A micro-soil sampling component, placed in the rhizosphere, is used to collect rhizosphere soil samples to support the monitoring of mycorrhizal symbiotic networks;

[0251] The data processing layer includes edge computing nodes, which include:

[0252] The spatiotemporal registration unit is used to calibrate the time and space scale of heterogeneous sensor data collected by the perception layer.

[0253] The dynamic weighted fusion unit is used to assign weights to moisture, temperature and mechanical stress factors based on the Softmax function, and fuse the stress levels to generate the Environmental Health Index (EHI).

[0254] The mycorrhizal efficacy calculation unit is used to quantitatively analyze the copy number of functional genes of mycorrhizal fungi in soil samples, and to calculate the mycorrhizal efficacy index (MEI) and the corrected water stress level (S). w ′;

[0255] The control and pre-simulation layer includes:

[0256] The closed-loop control subsystem includes a targeted irrigation module and a physical vibration isolation module, which are used to automatically trigger corresponding control measures when EHI exceeds the preset threshold Γ.

[0257] The finite element risk simulation subsystem is used for the simulation of root system three-dimensional spatial distribution point cloud P. r P, a point cloud of three-dimensional spatial distribution of the canopy c A root-crown coupled biomechanical model was constructed to simulate the structural stability of ancient trees under regulatory measures.

[0258] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A multi-factor comprehensive monitoring method for growth environment based on ancient tree protection, characterized in that: Includes the following steps: Step (S1) Non-invasive sensory network construction: In the ancient tree crown layer area, the meteorological monitoring unit is arranged, and the photosynthetically active radiation intensity PAR and the crown layer surface temperature T are collected in real time c ; A soil sensor array is arranged radially in the root distribution area with the tree trunk as the center to monitor the soil volumetric water content θ and soil water potential in layers. A minimally-invasive thermal dissipation probe was installed at breast height to continuously measure sap flow velocity in the xylem (SF) raw and calibrated raw . A ground-based interferometric radar is erected on the periphery of the protected area, and a three-dimensional spatial distribution point cloud P of root systems is obtained by surface scanning r ; A triaxial accelerometer was installed at the base of the tree trunk to collect vibration signals in real time. Deploying a laser scanning device in the canopy area to obtain a three-dimensional spatial distribution point cloud P of the canopy c ; Micro-soil sampling points were set up in the root distribution area at the outer edge of the canopy projection area for mycorrhizal symbiotic network monitoring; Step (S2) Multi-source data fusion calculation: The data collected by the meteorological monitoring unit, soil sensor array, minimally invasive heat diffusion probe, ground-based interferometric radar, triaxial accelerometer, laser scanning equipment, and micro-soil sampling component deployed in step (S1) are spatiotemporally registered through edge computing nodes to eliminate differences in time and space scales. A dynamic weighted algorithm was used to fuse soil water potential-related water stress data, canopy thermal stress-related temperature stress data, and mechanical vibration-related mechanical stress data to generate the Environmental Health Index (EHI). Step (S3) Closed-loop control and risk simulation: When EHI exceeds the preset threshold Γ, the targeted irrigation system or physical vibration isolation system will be automatically triggered. Based on the three-dimensional spatial distribution point cloud P of root system r With the three-dimensional spatial distribution point cloud P of canopy c A biomechanical model is constructed by using a finite element risk pre-play method to pre-play the structural stability under the regulation and control measures. The mechanical stress data is the mechanical stress degree S m， The mechanical stress degree S is calculated by using the frequency domain-time domain energy integration method m The specific process is as follows: Vibration signal acquisition and preprocessing: The original vibration signal a(t) was collected by a triaxial accelerometer at the base of the tree trunk. The signal was then subjected to a fast Fourier transform to convert the time domain signal into a frequency domain signal, and the energy spectral density E(f) was obtained, where f is the signal frequency. Destructive energy extraction and stress degree calculation: Focus on the dominant frequency band of construction machinery vibration min ,f max ] Within the continuous monitoring time window T, the energy contribution of the dominant frequency band is extracted by integrating the frequency domain energy spectrum density in the dominant frequency band, i.e. the frequency domain integration result, and the cumulative energy in the time domain is averaged to obtain the mechanical stress degree Sm. 2.The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 1, characterized in that: The step (S1) of the original liquid flow flux SF raw The calibration process is as follows: Elevation compensation function construction: establish a compensation function related to the altitude H , meet the original liquid flow flux SF raw Physical law of systematic attenuation, get the elevation compensation function ; Implementing field calibration: the raw liquid flux SF raw combined with the probe calibration coefficient K and the altitude compensation function to obtain the calibrated liquid flux SF cal . 3.The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 1, characterized in that: The process of generating the Environmental Health Index (EHI) in step (S2) includes the following steps: Step 1, Multi-dimensional stress quantification: Water stress degree S is calculated by integrating soil water status and tree transpiration response for soil water potential related water stress characteristics w ; For the characteristics of thermal stress in the canopy, based on the canopy surface temperature T c Calculate the temperature stress degree S t ; For mechanical vibration data characteristics, the frequency domain-time domain energy integration method is used to calculate the mechanical stress degree S m ; Step 2, Dynamic weight allocation mechanism: Based on the seasonal variation pattern and the physiological characteristics of tree species, the Softmax function is used to dynamically allocate the weights of the three stress factors of water, temperature and mechanical stress. Step 3, Index Synthesis Calculation: The environmental health index EHI is obtained by weighting and summing each stress degree with its corresponding dynamic weight.

4. The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 1, characterized in that: The triggering and operation process of the physical vibration isolation system includes: Trigger condition determination: real-time monitoring of mechanical stress degree S m When S m When continuously exceeding the preset threshold δ and the duration reaching τ, the system automatically starts the physical isolation control program; Construction arrangement of vibration isolation trench: based on root three-dimensional spatial distribution point cloud P r The distribution depth range of the main root is determined, a ring-shaped vibration isolation trench is planned and excavated outside the root system, the trench depth is set to cover the main root distribution area, and the trench width is determined according to the construction space and vibration isolation requirements; Verification of vibration isolation material filling and attenuation effect: Fill the vibration isolation trench with porous elastic material. After filling, test the vibration attenuation rate η of the system. If η meets the preset conditions, the verification is successful.

5. The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 1, characterized in that: The implementation process of the finite element risk simulation is as follows: Root-shoot model spatial registration: based on root three-dimensional spatial distribution point cloud P r and canopy three-dimensional spatial distribution point cloud P c , using iterative closest point algorithm for spatial alignment, so that both are in a unified coordinate system, registration to obtain the registered root-shoot coupling model; Based on the registered root crown coupling model, morphological parameters are extracted, and wind load vectors are calculated in combination with real-time meteorological data ; Structural mechanical performance determination: In the root-crown coupling model with a unified coordinate system, the stiffness matrix K is constructed by introducing the mechanical property parameters of wood, and the structural response of ancient trees under environmental loads is evaluated by solving the static equilibrium equation.

6. The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 1, characterized in that: The specific steps for monitoring the mycorrhizal symbiotic network are as follows: Rhizosphere soil sampling specifications: Collect surface soil samples from the root distribution area at the outer edge of the canopy projection area, and the sampling must meet the preset requirements; Quantitative detection of functional genes: Mycorrhizal fungi functional gene analysis was performed on the collected soil samples, and the copy number Ng of the target functional gene was detected by real-time fluorescence quantitative PCR technology; Dynamic calculation of mycorrhizal efficacy index: The mycorrhizal efficacy index MEI is constructed by introducing a time decay factor to quantify the functional activity of mycorrhizal symbiotic networks; The mycorrhizal efficacy index MEI is also used in the process of correcting for water stress.

7. The multi-factor comprehensive monitoring method for growth environment based on old tree protection according to claim 6, characterized in that: The process by which the mycorrhizal efficacy index (MEI) participates in the correction of water stress includes the following steps: The correction trigger condition judgment: real-time monitoring of the calculated mycorrhizal efficiency index MEI, when the MEI is lower than the preset threshold μ, the correction mechanism of water stress degree is automatically activated; Wherein, the threshold μ is the critical activity value of the mycorrhizal symbiotic function of the tree species, which is determined by the mycorrhizal efficiency comparison experiment of healthy ancient trees and weakened ancient trees; Coupling correction calculation: based on the activated correction mechanism, the original water stress degree S w is dynamically corrected by introducing the mycorrhizal symbiotic compensation term, and the corrected water stress degree S w is an input parameter for closed-loop regulation of step (S3).

8. A growth environment multi-factor comprehensive monitoring system based on ancient tree protection, the monitoring system is based on the monitoring method of claims 1-7, characterized in that: Including: The perception layer includes meteorological monitoring units deployed in the canopy, radial soil sensor arrays in the root zone, minimally invasive thermal diffusion probes at the breast height of the tree trunk, ground-based interferometric radar outside the protection zone, three-axis accelerometers at the base of the tree trunk, canopy laser scanning equipment, and micro-soil sampling components in the rhizosphere; The data processing layer includes edge computing nodes, including time-space registration units, dynamic weighted fusion units, and mycorrhizal efficiency calculation units; The regulation and pre-play layer includes a closed-loop control subsystem and a finite element risk pre-play subsystem.

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