The synergy of intrinsic ecological mechanisms of leaf nutrient resorption in temperate deciduous trees
Data files
Feb 15, 2024 version files 17.04 KB
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Leaf_nutrient_resorption_2022.csv
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README.md
Abstract
Nutrient resorption is a critical process in plant nutrient conservation during leaf senescence. However, the underlying ecological mechanisms on the large variabilities in nitrogen (NRE) and phosphorous (PRE) resorption efficiencies remain poorly understood. We conducted a comprehensive study on NRE and PRE variability using 61 tree individuals of 10 temperate broadleaved tree species. Three potentially interrelated intrinsic ecological mechanisms (i.e., leaf pigments, energy residual and leaf senescence phenology) were verified. We found that delayed leaf senescence date, increased degradation of chlorophyll and carotenoids, biosynthesis of anthocyanins, and reduced nonstructural carbohydrates (particular sugars) coordinately and positively related with NRE and PRE. The intrinsic factors affecting the resorption efficiency were ranked in a decreasing order: leaf pigments > energy residual > senescence phenology. Our findings underscore the synergistic effect of the three ecological mechanisms on leaf nutrient resorption, and hold significant implications for comprehending how nutrient resorption responds to climate change.
README: The synergy of intrinsic ecological mechanisms of leaf nutrient resorption in temperate deciduous trees
https://doi.org/10.5061/dryad.tmpg4f55m
This dataset is supporting for “The synergy of intrinsic ecological mechanisms of leaf nutrient resorption in temperate deciduous trees”. It included 61 tree individuals of 10 species. Three potentially interrelated intrinsic ecological mechanisms (i.e., leaf pigments, energy residual and leaf senescence phenology) were verified. These data are also invaluable in explore the senesced leaf traits.
Description of the data and file structure
The dataset is available as a csv file, including 33 variables. The data for each tree individual is listed. The variable name and unit (in the parentheses) are listed below.
1. Chinese_name, the name of tree species in Chinese from http://www.iplant.cn/.
2. Latin_name, the scientific name of tree species from http://www.iplant.cn/.
3. NRE, nitrogen resorption efficiency (%)
4. PRE, phosphorus resorption efficiency (%)
5. StartDOY, start of leaf coloration (or leaf fall) (DOY)
6. PeakDOY, peak of leaf fall (DOY)
7. EndDOY, end of leaf fall (DOY)
8. TNC_green, total nonstructural carbohydrates in green leaves (mg/g)
9. SSugars_green, soluble sugars in green leaves (mg/g)
10. Starch_green, starch in green leaves (mg/g)
11. Chl_green, chlorophyll in green leaves (mg/g)
12. Chla_green, chlorophyll a in green leaves (mg/g)
13. Chlb_green, chlorophyll b in green leaves (mg/g)
14. Car_green, carotenoids in green leaves (mg/g)
15. N_green, nitrogen in green leaves (mg/g)
16. P_green, phosphorus concentration in green leaves (mg/g)
17. TNC_sen, total nonstructural carbohydrates in senesced leaves (mg/g)
18. SSugars_sen, total nonstructural carbohydrates in senesced leaves (mg/g)
19. Starch_sen, total nonstructural carbohydrates in senesced leaves (mg/g)
20. Chl_sen, chlorophyll in senesced leaves (mg/g)
21. Car_sen, carotenoids in senesced leaves (mg/g)
22. TAC_sen, total anthocyanins in senesced leaves (mg/g)
23. N_sen, nitrogen in senesced leaves (mg/g)
24. P_sen, phosphorus in senesced leaves (mg/g)
25. DeltaChl, degradation of chlorophyll (mg/g)
26. DeltaCar, degradation of carotenoids (mg/g)
27. DeltaChl_per, degradation percentage of chlorophyll (%)
28. DeltaChla_per, degradation percentage of chlorophyll a (%)
29. DeltaChlb_per, degradation percentage of chlorophyll b (%)
30. DeltaCar_per, degradation percentage of carotenoids (%)
31. DeltaTNC, change of total nonstructural carbohydrates (%)
32. DeltaTNC_per, change percentage of total nonstructural carbohydrates (%)
33. CDD_15, cooling degree days (°C·d)
Methods
The datset was conducted at the Maoershan Forest Ecosystem Research Station (45°24′N,127°40′E), Heilongjiang Province, northeastern China. The site has a continental monsoon climate, with a mean annual temperature of 2.1°C and mean precipitation of 726 mm from 2008 to 2019.
From early autumn until leaf-fall in 2022, we randomly marked 61 individuals from 10 tree species, at least 3 healthy and mature individuals were selected from each species (Table S1). The early autumn was carefully determined for sampling time for green mature leaves, by considering: (1) the N, P and chlorophyll concentrations have been not entering the rapid decline phase based on the seasonality of leaf nutrients and chlorophyll. (2) The NSC level has been past its depletion period during rapid summer growth, according to the carbon sink saturation hypothesis on leaf senescence phenology. Furthermore, none of the species has N-fixing symbionts, excluding the contamination of N-fixing status on effects of intrinsic factors on NuRE and anthocyanins. Although we found the NRE was lower in arbuscular mycorrhizal than ectomycorrhiza fungi associated trees (40.2% versus 51.2%, P < 0.01), we did not consider this difference between the two mycorrhizal association types (consistent with the results by Guo et al. 2023) because we sampled five species equally for each mycorrhizal type.
The percentage of leaves on the canopy that are colored and remaining is usually recorded by a visual estimation every two days, 50% of the leaves on the crown changed color (or 10% of the leaves fallen for green autumn leafed species) as the start of leaf coloration, 50% of the leaves remaining as the peak of leaf-fall, and 90% of the leaves fallen as the end of leaf-fall. We recorded the day of year (DOY) for start of leaf coloration, peak of leaf-fall, and end of leaf-fall changes for each individual. The air temperature measured with HMP45C (Vaisala, Finland) at the 16 m height on the flux tower was used to calculate thermal time for interpreting leaf senescence phenology.
In early September (September 4-7, 2022), just before leaf senescence, we manually climbed each tree to cut a small branch from the mid-to-upper canopy to obtain green leaves to represent the whole crown. Then newly fallen leaves were collected at the ground as the senesced leaf sample, which fairly well represented the whole crown because the fallen leaves were well mixed among vertical canopy layers. All samples were brought back to the laboratory and transferred to a refrigerator as soon as possible. The samples of green leaves and senesced leaves were then measured for (1) leaf mass per area (LMA), (2) leaf pigments concentrations, and (3) NSC and nutrient concentrations.
Leaf mass per area
Leaf mass per area was obtained for green and senescent leaves by measuring the fresh leaf area with 300-DPI scanned pictures and weighing the dry mass at 70°C for 48 hours.
Leaf pigment concentration
One hundred mg of fresh leaves was weighed and moved into centrifuge tubes with steel beads for chlorophyll and carotenoids, and 200 mg of fresh leaves frozen in liquid nitrogen was crushed in centrifuge tubes with glass beads for anthocyanins, before measurement. Chlorophyll and carotenoids were extracted using acetone- absolute alcohol- deionized water in a 4.5:4.5:1 ratio ultrasonic extraction in darkness, while Anthocyanins were extracted by hydrochloric acid methanol-solution in a 2:98 ratio ultrasonic extraction in the dark, and the extracted solutions were balanced with corresponding pH buffers for measurement. Chlorophyll, carotenoids, and anthocyanins in the extracted solutions were measured using a spectrophotometer at different wavelengths (Eqs. 1-8). Leaf water content relative to fresh mass was also measured for converting fresh-mass-based pigments concentrations to dry-mass-based concentrations (%DM). Chlorophyll and carotenoids concentrations were calculated as follows:
Chla (mg/g)=12.55A663.2-2.79A646.8 (1)
Chlb (mg/g)=21.50A646.8-5.10A663.2 (2)
Total chl (mg/g)=7.15A663.2+18.71A646.8 (3)
Carotenoids (mg/g)=1000A470-1.82Chla+85.02Chlb/198 (4)
where Chla is the concentration of chlorophyll a; Chlb is the concentration of chlorophyll b; total Chl is the total chlorophyll concentration; A663.2 is the absorbance value of the sample at 663 nm; A646.8 is the absorbance value of the sample at 647 nm; A470 is the absorbance value of the sample at 470 nm.
The anthocyanins concentration (only for senescent leaves) was measured with a pH differential method:
Cac (mg/mL)=δA×Mw/(s×L) (5)
where C is the total anthocyanins concentration; ΔA is the difference of absorptance at two pH values (Eq. 6); DF is dilution factor established in D; s indicates that the molar absorptivity of the final mixture is ; Mw is the standard molecular weight of the final mixture of ; and L indicates the optical range of the cuvette (1 cm).
δA=[A510nm(pH1.0)-A700nm(pH1.0)] - [A510nm(pH4.5)-A700nm(pH4.5)] (6)
Then, we corrected the volumetric concentration (Cac) with a standard curve using cyanidin-3-glucoside as the equivalent:
C0=1.1974×Cac-0.0004 (7)
Volume concentrations were converted to anthocyanins concentration based on fresh mass:
TAC=C0×V1×V2×DF/m (8)
DF is the equilibrium dilution factor, V1 and V2 are the volume of the extractant and equilibrium constant volume. The water content of senesced leaves was used to convert the anthocyanins concentration based on fresh mass to that based on dry mass.
Leaf nonstructural carbohydrate concentration
The NSC was determined by an improved phenol-sulfuric acid method, which used enzymatic degradation of starch and thus avoided the overestimation of starch concentration caused by hydrolyzed hemicellulose and cellulose components by sulfuric acid. The NSC was defined as soluble sugars and starch, and the sum of the two referred to as total NSC (TNC), expressed as a percentage of dry mass (%DM). The concentrations of soluble sugar and starch were determined based on the sucrose standard curve.
Leaf nutrient concentration
N and P for green and senescent leaves were digested with concentrated sulfuric acid and hydrogen peroxide, and then measured using a continuous flow analyzer (AA3, Bran+luebbe, Germany).