Forest ecosystem litter leaf decomposition rate and leaf character correlation analysis method

Abstract

The invention belongs to the field of forest ecology, and discloses a forest ecosystem litter leaf decomposition rate and leaf character correlation analysis method which comprises the following steps: step 1, litter leaf sample collection and pretreatment; 2, designing and implementing a litter leaf decomposition experiment; step 3, leaf character determination; 4, calculating the decomposition rate; and step 5, correlation analysis. According to the method, the physical properties and the chemical properties of the litter leaves are systematically measured, and the relationship between the physical properties and the chemical properties and the decomposition rate is comprehensively analyzed, so that the driving factors of the decomposition rate and the ecological significance of the driving factors are disclosed. The method has high scientificity and practicability, and can provide important data support for functional research of a forest ecosystem.

Description

Technical Field

[0001] The present invention relates to the field of forest ecology, and specifically to a method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits. Background Art

[0002] Forest litter decomposition is an important link in the material cycle of the ecosystem and plays a key role in nutrient return and the maintenance of ecosystem functions. In a forest ecosystem, litter releases nutrients such as carbon, nitrogen, and phosphorus through decomposition, thus providing a necessary nutrient source for vegetation and soil microorganisms. However, current research on the relationship between litter decomposition rate and leaf traits is still not deep enough, especially how to systematically analyze the correlation mechanism between physical traits, chemical traits, and decomposition rate.

[0003] Existing research has shown that the physical traits of litter (such as specific leaf area, leaf thickness, water holding capacity, etc.) and chemical traits (such as carbon, nitrogen, phosphorus, and lignin content, etc.) have a significant impact on the decomposition rate. These traits determine the decomposability of litter and its adaptability to microbial decomposers. However, most studies only focus on the role of a single trait and lack a comprehensive analysis of the synergistic effects between multiple traits. In addition, the research objects mostly focus on specific forest types or tree species, and there is still no comprehensive understanding of the decomposition law of litter in forest ecosystems.

[0004] The present invention studies the effects of the physical and chemical traits of litter on the decomposition rate through field decomposition bag experiments combined with systematic determination of leaf traits, aiming to reveal its ecological driving mechanism and fill the gaps in the existing technology. This method not only has important significance for improving the accuracy of forest ecosystem function research but also provides a new scientific basis for the dynamic assessment of global forest ecosystem nutrient cycling. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits, comprising the following steps:

[0008] Step 1: Collection and pretreatment of litter samples:

[0009] Select several target tree species in the target forest ecosystem, randomly collect fresh litter from healthy trees, remove impurities, then perform drying treatment, weigh and group according to experimental requirements, and put the treated litter into standard decomposition bags;

[0010] Step 2. Design and implementation of the litter decomposition experiment:

[0011] Select several representative plots in the study area, evenly distribute the decomposition bags in the plots, recover the decomposition bags at fixed time intervals, measure the dry mass of the remaining litter, and record the dynamic of mass loss;

[0012] Step 3. Determination of leaf traits:

[0013] Determination of physical traits: including the determination of specific leaf area, leaf thickness, tensile strength, leaf toughness, standard water holding capacity and saturated water holding capacity;

[0014] Determination of chemical traits: including the determination of carbon, nitrogen, phosphorus, lignin and cellulose contents, and calculation of carbon-nitrogen ratio, nitrogen-phosphorus ratio, carbon-phosphorus ratio, lignin-nitrogen ratio and lignin-phosphorus ratio;

[0015] Step 4. Calculation of decomposition rate:

[0016] According to the litter residue mass data obtained from the decomposition experiment, use the Olson exponential decay model to calculate the decomposition rate:

[0017]

[0018] In the formula, t is time, M t is the remaining dry weight of the litter after decomposition for time t, M0 is the initial dry weight in the decomposition bag, α is the correction coefficient, k is the litter decomposition coefficient, and e is the natural constant;

[0019] Step 5. Correlation analysis:

[0020] Adopt the correlation analysis method to evaluate the relationship between physical traits and chemical traits and the decomposition rate, and reveal the main driving factors of the litter decomposition rate and their ecological significance.

[0021] Furthermore, the litter samples collected in Step 1 need to ensure the consistency of the source, the initial mass is unified when the processed samples are bagged, and the environmental factors are ensured to be consistent during the decomposition process.

[0022] Furthermore, the specific leaf area in Step 3 is calculated by the ratio of the single-sided leaf area of the litter to the dry weight, and the calculation formula is:

[0023]

[0024] In the formula, SLM is the specific leaf area, A is the total leaf area, and M is the leaf dry weight.

[0025] Further, in step 3, a vernier caliper is used to measure the leaf thickness. Multiple leaves of the same tree species are overlapped, and several points with approximately the same interval and avoiding the leaf veins are selected along the main vein direction for measurement. The average value of the thickness values of these several points is divided by the number of leaves to obtain the thickness of the group of leaves of this tree species; each tree species is measured multiple times, and finally the average value is taken as the leaf thickness of this tree species.

[0026] Further, the method for measuring the leaf toughness in step 3 is as follows: The soaked leaves of the same tree species are covered on a ring of appropriate size, and another ring with the same aperture size is added on the upper part of the leaves to fix the four sides of the leaves. A wire with an appropriate diameter and a flat cross-section is fixed on the tensiometer, and the instantaneous thrust when the wire pierces the leaves is recorded. Multiple leaves are measured in each group, and the measurement is repeated multiple times.

[0027] Further, the method for measuring the tensile strength in step 3 is as follows: After soaking the leaves of the same tree species, cut them into strips with a width of 0.5 - 1.0 cm while avoiding the leaf veins. One end is clamped and fixed with a clip, and the other end is fixed on the tensiometer. Pull the tensiometer until the leaves break, and record the instantaneous tensile force when the leaves break. Multiple leaves are measured in each group, and the measurement is repeated multiple times. The tensile strength is calculated according to the following formula:

[0028] TS = TF / W

[0029] In the formula, TS is the tensile strength, TF is the instantaneous tensile force when the leaves break, and W is the width of the strip cut from the leaves.

[0030] Further, the standard water holding capacity and saturated water holding capacity in step 3 are measured by the soaking method. The specific method is as follows: The fallen leaves are soaked in beakers filled with distilled water for 1 to 2 hours and 24 to 48 hours respectively. After taking them out, blot the surface moisture with absorbent paper, and then weigh the fallen leaves at this time with an analytical balance; The standard water holding capacity is the ratio of the difference between the leaf weight after soaking for 1 to 2 hours and the dry weight to the dry weight, and the saturated water holding capacity is the ratio of the difference between the leaf weight after soaking for 24 to 48 hours and the dry weight to the dry weight. The formula for calculating the standard water holding capacity is:

[0031]

[0032] In the formula, WHC standard is the standard water holding capacity, M1 is the leaf weight after soaking for 1 - 2 hours, and M is the leaf dry weight;

[0033] The formula for calculating the saturated water holding capacity is:

[0034]

[0035] In the formula, WHC saturated is the saturated water holding capacity, and M2 is the leaf weight after soaking for 24 - 48 hours.

[0036] Further, in step 4, the decomposition half-life and decomposition turnover period of the litter are calculated from the decomposition rate, and the calculation formula is:

[0037] t 0.5 = ln(0.5) / (-k)

[0038] t 0.95 = ln(0.95) / (-k)

[0039] In the formula, t 0.5 is the decomposition half-life of the litter, that is, the time taken for 50% of the litter to decompose, and t 0.95 is the decomposition turnover period of the litter, that is, the time taken for 95% of the litter to decompose, and k is the litter decomposition coefficient.

[0040] Further, in step 5, Pearson correlation analysis is used for the correlation analysis to clarify the influence of different leaf traits on the litter decomposition rate, and the calculation formula is:

[0041]

[0042] In the formula, r is the Pearson correlation coefficient, and its value range is from -1 to 1, indicating the strength and direction of the linear correlation between two variables. n is the sample size, x i and y i are the i-th observation values, corresponding to variables X and Y respectively, and are the sample means of variables X and Y.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows: By systematically measuring the physical and chemical properties of the litter and comprehensively analyzing their relationship with the decomposition rate, the present invention reveals the driving factors of the decomposition rate and their ecological significance. This method has high scientificity and practicability, and can provide important data support for the study of forest ecosystem functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 FIG. is a schematic flow chart of a method for analyzing the correlation between the litter decomposition rate and leaf traits in a forest ecosystem provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment

[0047] The present invention selects the broad-leaved Korean pine forest in Changbai Mountain as the target forest ecosystem, and the specific steps are as follows:

[0048] Step 1: Collection and pretreatment of litter samples of target tree species:

[0049] Select several target tree species in the broad-leaved Korean pine forest of the target forest ecosystem, randomly collect fresh litter from healthy trees, remove impurities, then conduct drying treatment, weigh and group according to experimental requirements, and put the treated litter into standard decomposition bags.

[0050] Among them, the collected litter samples need to ensure the consistency of the source, the initial mass of the treated samples remains unified when bagging, and the environmental factors are ensured to be consistent during the decomposition process.

[0051] Step 2: Design and implementation of litter decomposition experiment:

[0052] Select several representative plots in the research area, and evenly distribute the decomposition bags in the plots. During the decomposition process, recover the decomposition bags at fixed time intervals, measure the dry mass of the remaining litter, and record the dynamic mass loss.

[0053] Step 3: Determination of leaf traits:

[0054] Determination of physical traits: including specific leaf area, leaf thickness, leaf toughness, tensile strength, standard water holding capacity and saturated water holding capacity (Table 1), which are measured using standard experimental equipment.

[0055] Among them, the specific leaf area is calculated by the ratio of the single-sided leaf area of the litter to the dry weight:

[0056]

[0057] In the formula, SLM is the specific leaf area, A is the total leaf area, and M is the dry weight of the leaf.

[0058] Preferably, when measuring the leaf area, use a scanner to scan the collected intact and unshriveled fresh litter. Each tree species collects no less than 30 leaves each time, and each sample is scanned 3 times to ensure the accuracy of the data. After scanning, put the litter into an envelope and place it in an oven at 75 °C to dry to a constant weight, and then accurately measure the dry weight with an analytical balance.

[0059] Further, a vernier caliper is used to measure the leaf thickness. Five leaves of the same tree species are overlapped together. The number of leaves can be selected as needed. Three points with approximately the same interval along the main vein direction and avoiding the leaf veins are selected for measurement. The number of measurement points can be selected as needed. After taking the average value of the thickness values of these three points and dividing it by 5, the thickness of this group of leaves of this tree species is obtained. Each tree species is measured multiple times, preferably 3 times, and finally the average value is taken as the leaf thickness of this tree species.

[0060] Further, for the determination of leaf toughness, the soaked leaves of the same tree species are covered on a ring of appropriate size, and another ring with the same aperture size is added on the upper part of the leaves to fix the four sides of the leaves, trying to avoid having leaf veins in the ring. A wire with an appropriate diameter and a flat cross-section is fixed on the tensiometer, and the instantaneous thrust when the wire pierces the leaf is recorded. Multiple leaves are measured in each group, preferably 10 leaves, and repeated multiple times, preferably 3 times.

[0061] Further, for the determination of tensile strength, the leaves of the same tree species are soaked and then cut into strips with a width of 0.5 - 1.0 cm, preferably 0.6 cm, avoiding the leaf veins, with one end clamped and fixed with a clip, and the other end fixed on the tensiometer. The tensiometer is pulled until the leaf breaks, and the instantaneous tensile force when the leaf breaks is recorded. Multiple leaves are measured in each group, preferably 10 leaves, and repeated multiple times, preferably 3 times. The tensile strength is calculated according to the following formula:

[0062] TS = TF / W

[0063] In the formula, TS is the tensile strength, TF is the instantaneous tensile force when the leaf breaks, and W is the width of the strip cut from the leaf.

[0064] Further, the standard water holding capacity and saturated water holding capacity are determined by the soaking method. The fallen leaves are soaked in beakers filled with distilled water for 1 to 2 hours and 24 to 48 hours, preferably 1 hour and 24 hours. After taking them out, the surface moisture is blotted dry with absorbent paper, and then the weight of the fallen leaves at this time is weighed with an analytical balance. The standard water holding capacity is the ratio of the difference between the leaf weight after soaking for 1 to 2 hours and the dry weight to the dry weight, and the saturated water holding capacity is the ratio of the difference between the leaf weight after soaking for 24 to 48 hours and the dry weight to the dry weight. The calculation formula for the standard water holding capacity is:

[0065]

[0066] In the formula, WHC standard is the standard water holding capacity, M1 is the leaf weight after soaking for 1 to 2 hours, and M is the dry weight of the leaf.

[0067] The calculation formula for the saturated water holding capacity is:

[0068]

[0069] Wherein, WHC satureated is the saturated water holding capacity, M2 is the leaf weight after soaking for 24 to 48 hours, and M is the dry weight of the leaf.

[0070] Table 1 Physical properties of litter of different tree species

[0071]

[0072] Chemical property determination: including the contents of carbon, nitrogen, phosphorus, lignin and cellulose, and calculating the relevant stoichiometric ratios, including carbon-nitrogen ratio, nitrogen-phosphorus ratio, carbon-phosphorus ratio, lignin-nitrogen ratio and lignin-phosphorus ratio (Table 2).

[0073] Furthermore, the initial contents of carbon, nitrogen, phosphorus, lignin and cellulose are measured, and the stoichiometric ratios such as carbon-nitrogen ratio, nitrogen-phosphorus ratio, carbon-phosphorus ratio, lignin-nitrogen ratio and lignin-phosphorus ratio are further calculated. First, the litter is crushed by a grinder and then passed through a 60-mesh sieve to ensure the uniformity of the sample. The total carbon and total nitrogen contents in the litter are measured using a total elemental analyzer. After the sample is digested, the total phosphorus content in the litter is measured by the molybdenum-antimony anti-colorimetric method using an ultraviolet spectrophotometer. The initial lignin and cellulose contents in the litter are measured by the acid washing method, which can accurately separate and measure the contents of lignin and cellulose and provide reliable data for subsequent analysis.

[0074] Table 2 Chemical properties of litter of different tree species

[0075]

[0076] Step 4, Decomposition rate calculation:

[0077] According to the litter residue mass data obtained from the decomposition experiment, the decomposition rate is calculated using the Olson exponential decay model:

[0078]

[0079] Wherein, t is the time, M t is the remaining dry weight of the litter after decomposition for time t, M0 is the initial dry weight in the decomposition bag, α is the correction coefficient, k is the litter decomposition coefficient, and e is the natural constant;

[0080] Furthermore, the decomposition half-life and decomposition turnover period of the litter are estimated from the decomposition rate:

[0081] t 0.5 = ln(0.5) / (-k)

[0082] t 0.95 = ln(0.95) / (-k)

[0083] Wherein, t 0.5is the half-life of litter decomposition, that is, the time taken for 50% of the litter to decompose, t 0.95 is the turnover period of litter decomposition, that is, the time taken for 95% of the litter to decompose, and k is the litter decomposition coefficient.

[0084] Table 3 Olson negative exponential decay model of litter decomposition of different tree species

[0085] Tree species Model Decomposition rate (k) <![CDATA[T 0.5 > <![CDATA[T 0.95 > Betula platyphylla <![CDATA[102.20e -0.53t > 0.53 1.31 5.65 Acer mandshuricum <![CDATA[104.20e -0.75t > 0.75 0.92 3.99 Ulmus davidiana var. japonica <![CDATA[100.98e -0.51t > 0.51 1.36 5.89 Populus ussuriensis <![CDATA[101.05e -0.62t > 0.62 1.11 4.80 Juglans mandshurica <![CDATA[99.47e -0.48t > 0.48 1.44 6.22 Pinus koraiensis <![CDATA[100.90e -0.24t > 0.24 2.86 12.37 Maackia amurensis <![CDATA[101.90e -0.63t > 0.63 1.10 4.75 Phellodendron amurense <![CDATA[104.63e -1.05t > 1.05 0.66 2.85 Tilia mandshurica <![CDATA[102.07e -0.70t > 0.62 1.12 4.84 Quercus mongolica <![CDATA[102.5e -0.42t > 0.42 1.67 7.21 Acer triflorum <![CDATA[102.89e -0.62t > 0.62 1.13 4.86 Acer mono <![CDATA[103.11e -0.84t > 0.84 0.82 3.54 Populus davidiana <![CDATA[101.48e -0.58t > 0.58 1.21 5.20 Fraxinus mandshurica <![CDATA[102.85e -1.00t > 1.00 0.69 2.99 Tilia amurensis <![CDATA[103.55e -0.89t > 0.54 1.28 5.52

[0086] Step 5, Correlation analysis:

[0087] Analyze the relationship between physical and chemical properties and decomposition rate, and use correlation analysis and statistical methods to evaluate the impact of different leaf traits on decomposition rate.

[0088] The analysis results of litter and leaf traits of the target forest ecosystem, the broad-leaved Korean pine forest in Changbai Mountain, show that nitrogen content (r = 0.52), cellulose content (r = 0.55) are positively correlated with decomposition rate, and leaf thickness (r = -0.67), tensile strength (r = -0.61), carbon content (r = -0.52), carbon-nitrogen ratio (r = -0.62), carbon-phosphorus ratio (r = -0.62), lignin-nitrogen ratio (r = -0.65) and lignin-phosphorus ratio (r = -0.58) are negatively correlated with decomposition rate. Specific leaf area (r = 0.34), leaf toughness (r = -0.42), standard water holding capacity (r = 0.05), saturated water holding capacity (r = 0.48), phosphorus content (r = 0.44), lignin content (r = -0.45), nitrogen-phosphorus ratio (r = -0.17) have no significant correlation with decomposition rate.

[0089] Furthermore, Pearson correlation analysis is used for the correlation analysis to clarify the impact of different leaf traits on the litter decomposition rate.

[0090]

[0091] In the formula, r is the Pearson correlation coefficient, and its value range is from -1 to 1, indicating the strength and direction of linear correlation between two variables. n is the sample size, x i and y i are the i-th observation values, corresponding to variables X and Y respectively, and are the sample means of variables X and Y.

[0092] When r = 1, it indicates that the two variables are completely positively correlated; when r = -1, it indicates completely negative correlation; when r = 0, it indicates no linear correlation. When |r| ≥ 0.5, it indicates that the two variables are strongly correlated. When |r| < 0.5, the correlation is extremely weak or there is no correlation.

[0093] The above embodiments have elaborated in detail the specific implementation process of the research method on the correlation between the decomposition rate of forest litter and leaf traits based on physical and chemical traits of the present invention, demonstrating key technical steps such as sample collection and pretreatment, decomposition experiment design and implementation, leaf trait measurement, decomposition rate calculation, and correlation analysis. Through standardized experimental procedures and rigorous statistical analysis, the present invention systematically reveals the driving effects of the physical traits of litter (such as specific leaf area, leaf thickness, etc.) and chemical traits (such as carbon, nitrogen, phosphorus contents and their stoichiometric ratios) on the decomposition rate, and clarifies the main factors affecting the decomposition rate and their ecological significance.

[0094] The present invention has strong universality and can be applied to the decomposition research of litter of different tree species and forest types. Its operation process is standardized, and the data collection is accurate and reliable, which can effectively analyze the decomposition dynamics of litter and provide a scientific basis for the research on the material cycle and nutrient dynamics of forest ecosystems. This method not only provides innovative methods and tools for the research in the fields of forest ecology, ecological restoration, and soil nutrient management, but also provides an important reference for understanding the key driving mechanisms of the litter decomposition process, and has broad application prospects and practical values.

[0095] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits, characterized in that, It includes the following steps: Step 1. Collection and pretreatment of litter samples: Select several target tree species in the target forest ecosystem, randomly collect fresh litter from healthy trees, remove impurities, dry them, weigh and group them according to experimental requirements, and put the treated litter into standard decomposition bags; Step 2. Design and implementation of litter decomposition experiment: Select several representative plots in the study area, evenly distribute the decomposition bags in the plots, recover the decomposition bags at fixed time intervals, measure the dry mass of the remaining litter, and record the dynamic of mass loss; Step 3. Determination of leaf traits: Determination of physical traits: It includes the determination of specific leaf area, leaf thickness, tensile strength, leaf toughness, standard water holding capacity and saturated water holding capacity; Determination of chemical traits: It includes the determination of carbon, nitrogen, phosphorus, lignin and cellulose contents, and calculation of carbon-nitrogen ratio, nitrogen-phosphorus ratio, carbon-phosphorus ratio, lignin-nitrogen ratio and lignin-phosphorus ratio; Step 4. Calculation of decomposition rate: According to the litter residue mass data obtained from the decomposition experiment, use the Olson exponential decay model to calculate the decomposition rate: where t is the time, M t is the remaining dry weight of the decomposed litter after time t, M0 is the initial dry weight in the decomposition bag, α is the correction coefficient, k is the litter decomposition coefficient, and e is the natural constant; Step 5. Correlation analysis: Adopt the correlation analysis method to evaluate the relationship between physical traits and chemical traits and the decomposition rate, and reveal the main driving factors of the litter decomposition rate and their ecological significance.

2. The method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that The litter samples collected in Step 1 need to ensure the consistency of the source. The initial mass of the treated samples should be unified when bagging, and ensure the consistency of environmental factors during the decomposition process.

3. The method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, wherein In Step 3, the specific leaf area is calculated by the ratio of the single-sided leaf area of the litter to the dry weight, and the calculation formula is: In the formula, SLM is the specific leaf area, A is the total leaf area, and M is the leaf dry weight.

4. A method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that, In Step 3, the leaf thickness is measured using a vernier caliper. Overlap multiple leaves of the same tree species, select several points with approximately the same interval and avoiding the leaf veins along the main vein direction for measurement. Divide the average value of the thickness values of these several points by the number of leaves to obtain the thickness of the leaves of this group of this tree species; Repeat the measurement multiple times for each tree species, and finally take the average value as the leaf thickness of this tree species.

5. A method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that, The method for determining the leaf toughness in Step 3 is: Cover the wet leaves of the same tree species on a ring of appropriate size, add another ring with the same aperture size on the upper part of the leaves to fix the four sides of the leaves, fix a wire with appropriate diameter and flat cross-section on the tensiometer, and record the instantaneous thrust when the wire pierces the leaves. Measure multiple leaves in each group and repeat multiple times.

6. The method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, wherein The method for determining the tensile strength in Step 3 is: After wetting the leaves of the same tree species, cut them into strips with a width of 0.5 - 1.0 cm avoiding the leaf veins. Clamp one end with a clip and fix the other end on the tensiometer. Pull the tensiometer until the leaf breaks, and record the instantaneous tensile force when the leaf breaks. Measure multiple leaves in each group and repeat multiple times. The tensile strength is calculated according to the following formula: TS = TF / W In the formula, TS is the tensile strength, TF is the instantaneous tensile force when the leaf breaks, and W is the width of the strip cut from the leaf.

7. A method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that In step 3, the standard water holding capacity and saturated water holding capacity are measured by the soaking method. The specific method is as follows: Immerse the litter leaves in beakers filled with distilled water for 1 to 2 hours and 24 to 48 hours respectively. After taking them out, blot the surface moisture with absorbent paper, and then weigh the litter leaves at this time with an analytical balance. The standard water holding capacity is the ratio of the difference between the leaf weight after soaking for 1 to 2 hours and the dry weight to the dry weight, and the saturated water holding capacity is the ratio of the difference between the leaf weight after soaking for 24 to 48 hours and the dry weight to the dry weight. The calculation formula for the standard water holding capacity is: Wherein, WHC standard is the standard water holding capacity, M1 is the weight of the leaf blade after soaking for 1 - 2 hours, and M is the dry weight of the leaf blade; The calculation formula for the saturated water holding capacity is: Wherein, WHC saturated is the saturated water holding capacity, and M2 is the weight of the leaf after soaking for 24 - 48 hours.

8. The method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that, In step 4, the decomposition half-life and decomposition turnover period of the litter leaves are estimated through the decomposition rate. The calculation formula is: t 0.5 = ln(0.5) / (-k) t 0.95 = ln(0.95) / (-k) where t 0.5 is the half-life of litter decomposition, i.e., the time taken for 50% of the litter to decompose, and t 0.95 is the turnover period of litter decomposition, i.e., the time taken for 95% of the litter to decompose, and k is the litter decomposition coefficient.

9. The method for analyzing the correlation between the decomposition rate of forest ecosystem litter and leaf traits according to claim 1, characterized in that In step 5, Pearson correlation analysis is used for the correlation analysis to clarify the influence of different leaf traits on the decomposition rate of the litter leaves. The calculation formula is: Where r is the Pearson correlation coefficient, with a value range of -1 to 1, representing the strength and direction of the linear correlation between two variables, n is the sample size, x i and y i are the i-th observations, corresponding to variables X and Y respectively, and are the sample means of variables X and Y.

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