Introduction

Forest disruption and resultant erosion of biodiversity is one of the most damaging human-made changes to the planet1,2. From 2000 to 2010, for example, nearly 130 million hectares of forest (representing 3.2% of the total forest area in 2000) were lost worldwide3. In South China alone, an estimated 3.74 × 106 ha that once possessed by native forests is now degraded and without desirable forest tree species and natural succession from degraded shrubland to regional climax forest is slow and may require hundreds of years4. To accelerate this process, researchers have attempted many methods including the use of nurse plants5,6,7,8,9,10.

By definition, nurse plants facilitate the establishment and growth of other plant species (target species) under their canopies by providing a benign microhabitat condition11. Shrubs are found to be ideal nurse plants because they have strong facilitative effects on the survival and initial growth of certain target species6,12. The shade condition under shrub nurse plant may protect target species from high temperature and radiation, as well as improve soil moisture and nutrition (i.e., fertility islands) and target plant water relations7,8,9. Nurse plant coverage may well facilitate tree seedlings in their early growth because most tree species (late successional species) are shade tolerant in juvenile stage but grow in higher light conditions as they mature6,13,14. In contrast, the fast growing pioneer tree species show complex differentiation in response to light environments and the canopy shading gradients may affect the growth of pioneers in different patterns15,16. Therefore, even the ameliorated microenvironmental factors under canopies are important for plant establishment, tree seedlings may not always respond positively to the improved environment in terms of establishment and growth. Our previous studies conducted in subtropical shrubland also showed that all the tree seedlings exhibited improved growth under shrub nurse plant in the first growing season8, but their performances varied largely in the following growing seasons due to changes in environmental factors17. Although soil properties and plant photosynthetic parameters have been measured and used to explain target plant growing performance, the intrinsic mechanisms (e.g. alterations in plant chemical compositions and redistribution of photosynthates) underlying target plant responses are still incompletely understood. As the rhizosphere nutrient accumulation and cycling processes accelerate beneath nurse plant canopy, the carbon status and chemical compositions of the target species can be modified7,8,11,12.

Allocation of assimilated carbon and mineral nutrients has proven to be a key process that regulates biosynthesis and conversion of sugar into different chemical compounds in each organ of the plant18. To understand such carbon investments, researchers assess the biosynthetic pathways leading to the construction of a plant organ and calculate the construction cost (CC), which is defined as the amount of glucose required to produce 1 g of biomass. In previous studies, CC values were obtained from relatively quick measurements, based on strong correlations between the CC values of organic compounds and either carbon concentrations or heat of combustion values19,20. Such analyses, however, do not provide insights into the causes underlying differences in CC values. Better understanding of the variation in CC values of woody species will require the determination of how the chemical composition of leaves is related to the observed variation in CC values18.

Based on their chemical composition and CC values, plant compounds can be classified into eight principal groups18,21,22. Researchers have estimated that plants require 2–3 g of glucose to produce 1 g of the following four groups: lignin, protein, soluble phenolics and lipids23. The production of 1 g of the following three groups requires approximately 1 g of glucose: total structural carbohydrates (TSC), total non-structural carbohydrates (TNC) and organic acids. The eighth group consists of minerals, which are considered to require no glucose except that needed to support the root respiration involved in mineral absorption21. The payback time required for photosynthesis to recover CC values, also an important factor for understanding carbon investments24, is defined as the time that a leaf requires to amortize its cost, i.e. the time that a leaf must photosynthesize to recover the cost invested in its construction25.

Although previous studies have shown that biological and environmental factors (e.g. light environments, species-specific traits and pollutants) can alter the cellular concentrations in leaves of membrane lipids, pigments, proteins, phenolics, mineral nutrients and lignin, as well as CC values22,25,26, the plant nurse effects on CC values and on leaf chemical compounds have not been studied. Despite our improved understandings of target plant physiological performance in response to shrub nurse effects8,9,12, we still know little about the carbon metabolism of target plant tissues.

Here, we describe a field experiment that lasted 3.5 years and that involved different target tree species planted under shrub canopies and in open areas in a subtropical degraded shrubland. Our general goal is to increase our understandings on the mechanisms underlying shrub nurse effects on target species. Specifically, we examine how growth, physiological traits, leaf chemical compositions and CC values of four target plant species responded to a selected nursing shrub plant after 3.5 years. We aim to test our hypotheses in this study: (1) the growth of the fast growing species are suppressed under the canopy of shrub while the more shade tolerant species are facilitated; (2) changes in foliar chemical composition, CC values and payback time may help explore the intrinsic mechanisms in such differences. We also consider the implications of species-specific differences in growth, CC values and payback time for the reforestation of subtropical degraded shrubland in South China.

Results

Plant growth, photosynthetic and structural parameters

Results showed that relative growth rates of seedling height (RGR-H, P < 0.001) and basal diameter (RGR-B, P = 0.001), maximum photosynthetic rates (Amax, P = 0.023) and specific leaf areas (SLA, P < 0.001) were significantly affected by species and the interaction between species and treatment (P ≤ 0.023 for all) (Table 1). Meanwhile, RGR-B was also significantly affected by treatment factor (P = 0.012). Pinus elliottii showed significantly lowered RGR-H, RGR-B and Amax (P ≤ 0.033 for all) in canopy subplots (CS) than in open subplots (OS) (Fig. 1a–d). Similarly, the RGR-B and Amax of Michelia macclurei were significantly decreased (P < 0.001 and P = 0.012), but SLA was increased (P = 0.012) when grown in CS than in OS. In contrast, Schima superba had much higher RGR-B, RGR-H and Amax (P ≤ 0.015 for all) grown in CS than in OS. These parameters for Castanopsis fissa, however, were not significantly different between shrub nurse treatments and controls.

Table 1 P values from two-way ANOVA statistics for the effects of species (4 levels) and treatment (2 levels) on plant growth parameters, maximum photosynthetic rate, specific leaf area and leaf total carbon, nitrogen and phosphorus concentrations.
Full size table
Figure 1
figure 1

Plant relative seedling height growth rate (a), plant relative basal diameter growth rate (b), maximum photosynthetic rate (c), specific leaf area (d) and leaf total carbon (e), nitrogen (f) and phosphorus (g) concentrations. Values are means + SD (n = 5). Single, double and triple asterisks indicate a significant difference between CS and OS plots at p < 0.05, p < 0.005 and p < 0.001, respectively.

Full size image

Leaf main element concentration

Leaf total carbon (C), nitrogen (N) and phosphorus (P) concentrations were significantly affected by species (P < 0.001 for all), but not affected by treatment (P ≥ 0.223 for all) (Table 1). Meanwhile, leaf N concentration was significantly affected by the interactions between species and treatment (P = 0.003). For P. elliottii, leaf C and N concentrations were significantly lower (P = 0.008 and P = 0.006) when grown in CS than in OS (Fig. 1e–g). In contrast, for S. superba and C. fissa, leaf N concentrations were significantly increased when grown in CS than in OS (P = 0.001 and P = 0.009). Leaf P concentrations were not significantly changed between treatment for any of the four species.

Leaf chemical composition

Leaf minerals, organic acids, protein, lipid, soluble phenolics, lignin, TSC and TNC concentrations were significantly affected by species (P ≤ 0.041 for all), but only leaf organic acids and soluble phenolics concentrations were significantly affected by treatment (P = 0.002 and P = 0.023, respectively) (Table 2). Leaf minerals, organic acids, protein, lipid concentrations were also significantly affected by the interactions between species and treatment (P ≤ 0.019 for all). For P. elliottii seedlings, leaf organic acids was significantly increased (P < 0.001) but leaf protein (P = 0.018) and soluble phenolics (P = 0.039) were significantly decreased when grown in CS than in OS (Fig. 2). The minerals concentration of S. superba was significantly lower (P = 0.046) but protein concentration of this species was significantly higher in CS than in OS (P = 0.025). For C. fissa, minerals, organic acids and protein concentrations were all significantly higher when grown in CS than in OS (P ≤ 0.037 for all). For M. macclurei, only soluble phenolics were significantly lower when grown in CS than in OS (P = 0.016). Lignin, TSC or TNC concentrations were not significantly affected by shrub nurse effect for any of the tested target species.

Table 2 P values from two-way ANOVA statistics for the effects of species (4 levels) and treatment (2 levels) on CC value, payback time and chemical compositions.
Full size table
Figure 2
figure 2

Concentrations of the chemical constituents in leaves of four target plants growing in open subplots (OS) and canopy subplots (CS).

(a) minerals; (b) organic acids; (c) proteins; (d) lipids; (e) soluble phenolics; (f) lignin; (g) total structural carbohydrates; and (h) total non-structural carbohydrates. Values are means + SD (n = 5). Single, double and triple asterisks indicate a significant difference between CS and OS plots at p < 0.05, p < 0.005 and p < 0.001, respectively.

Full size image

Construction costs and payback time

CC value and payback time were significantly affected by species (P < 0.001 and P = 0.009), but not significantly affected by treatment and the interaction between species and treatment (Table 1). For P. elliottii, CC value was significantly decreased (P = 0.003) but payback time was significantly increased (P = 0.047) when grown in CS than in OS (Fig. 3). Also, CC value of C. fissa and payback time of S. superba were found to be decreased in CS than in OS (P = 0.044 and P = 0.001). CC values and payback time of M. macclurei were not significantly different between treatments.

Figure 3
figure 3

Leaf construction costs (a) and payback times (b) for four target plants growing in open subplots (OS) and canopy subplots (CS). Values are means + SD (n = 5). Single and double asterisks indicate a significant difference between CS and OS plots at p < 0.05 and p < 0.005, respectively.

Full size image

Discussion

Overall, our results supported our hypotheses that 1) the growth of the fast growing species (e.g. P. elliottii and M. macclurei) are suppressed under the canopy of shrub while the more shade tolerant species are facilitated (e.g. S. superba); 2) S. superba outperforms P. elliottii and M. macclurei due to its changed foliar chemical composition, unchanged CC values and shortened payback time when facilitated by the shrub.

As revealed by other studies, nurse plant can simultaneously exert both facilitative and competitive effects on target plants seedlings and the relative dominance of either positive or negative effects largely relies on the traits of tested species6,7,10,14. Our previous studies also showed that the differences in target plant growing performances in canopy subplots were mainly caused by their adaptations to light environment8,17. S. superba is a typical late-successional species that adapted to a wide range of light intensity, i.e. it is shade tolerant in juvenile stage but grow in higher light conditions as they mature13. In contrast, P. elliottii, is a fast growing species and M. macclurei is a light demanding species, thus the canopy shade composed negative growing conditions for their growth during the 3.5-year experiment. Moreover, changes in plant resource use efficiencies may also help explain such differences, i.e. some species outperform others by acquiring limited resources or by using resources more efficiently12,27. For M. macclurei, the lowered photosynthetic rates together with the unchanged leaf C, N, P concentrations under R. tomentosa may have decreased photosynthetic energy, nitrogen or phosphorus -use efficiency when grown in canopy subplots. In contrast, S. superba can highly increase its resource use efficiencies when nursed by shrub R. tomentosa. Thus, we conclude that the shrub nurse plant does not benefit the growth and resource-use efficiency of P. elliottii and M. macclurei during the 3.5 years. It follows that the former two species may not be suitable for long-term shrubland restoration when the shrub R. tomentosa is used as a nurse plant.

Although attempts to understand the mechanisms underlying differences in plant utilization and allocation of assimilated carbon among species have often focused on the role of photosynthesis, process of downstream carboxylation may also provide important information on how carbon assimilation is related to the chemical composition of plant organs18. The metabolism of organic acids is fundamentally important at the cellular level for several biochemical pathways, or at the individual level in modulating plant adaptation to the environment28. Organic acids are also involved in transporting micronutrients in the transpiration stream in the xylem29,30. In our study, the highly increased organic acids in foliar tissues of P. elliottii and C. fissa grown in canopy subplots showed that the nurse shrub coverage may largely improve their cellular metabolism such as participate in the balance of charges formed during the extensive metabolism of anions28,31.

As a component of functional proteins, structural proteins and the photosynthetic machinery, nitrogen is an important plant nutrient32. In this study, higher leaf nitrogen concentrations were associated with elevated leaf protein contents in S. superba and C. fissa growing in canopy subplots. Reduced leaf nitrogen contents in P. elliottii, in contrast, were associated with decreased protein contents in canopy subplots. There may be a trade-off between investing nitrogen in the photosynthetic apparatus such as chlorophyll rather than in structural compounds such as cell wall proteins33,34. The proportions of leaf nitrogen partitioned to different nitrogen pools are affected by irradiance35, nutrition36 and other environmental factors34. In this study, as affected by the microenvironment changed by shrub nurse plant, more nitrogen may have been transformed to protein in leaves of S. superba and C. fissa, while less nitrogen was available for constructing different forms of protein in needles of P. elliottii growing in canopy subplots vs. open subplots.

Soluble phenolics are thought to have antioxidant effects in stressed plants37. Researchers have proposed that a high concentration of phenolics may protect leaves against high light conditions and may help avoid photosynthetic down-regulation and photoinhibition38,39. In our study, plants growing in the open rather than canopy subplots may have suffered from excessive radiation. In two of our tested target species, P. elliottii and M. macclurei, phenolic concentrations were substantially higher in open subplots than in canopy subplots. The increased phenolic concentrations may have protected their photosynthetic apparatus against the excessive energy. These results also indicate that P. elliottii and M. macclurei can cope with high light conditions and that their establishments in subtropical degraded shrublands may not require shade condition composed by shrub coverage.

The increase in phenolics is mostly associated with lignification because lignin compounds often create barriers between injured and healthy tissues40. Unlike previous studies, however, our study did not detect significant differences in lignin concentration in open vs. canopy subplots for any of the four target species. Total structural carbohydrate and structural carbon in plants are mostly involved in morphogenesis of the plant cytoskeleton and total structural carbohydrate content is relatively stable within a species41. If the growth of a plant is limited by photosynthesis, total non-structural carbohydrate may be lower in a declining stand than in a healthy stand42. In our study, however, total structural and non-structural carbohydrate concentrations did not differ in open subplots vs. canopy subplots for any of the four species, although there were clear differences in growth and photosynthetic performances in the two subplot types.

Researchers have concluded that there is a compromise in chemical composition between growth and defence within a plant because of limitations in available energy43. According to this theory, a plant must choose to invest energy in growth-related processes or in the accumulation of defence-related compounds44. For example, species with high growth potential invest more energy in primary compounds (proteins) and less in secondary compounds with a possible defence role (such as phenols or lignin); the opposite is true for species with a low growth potential18,45. This theory was partially supported by the relationships between chemical compounds and the growth of target species in canopy subplots in the current study. Because the shrub canopy provides a relatively benign micro-environment for other plants, S. superba and C. fissa seedlings growing in canopy subplots invested more energy in the synthesis of proteins than in the synthesis of defence compounds (e.g. phenolics or lignin). In contrast, P. elliottii had decreased levels of proteins and soluble phenolics in canopy subplots, indicating that this target species did not benefit from R. tomentosa.

The CC value is an important parameter relative to the carbon budget of plants. It is a “black box”, however, because the underlying mechanisms that produce different values across treatments are unclear18. Increasing our understanding of CC values requires additional analyses of the chemical compositions of plants. For example, positive correlations between compounds with high energy costs (e.g. proteins, soluble phenolics and lignin) and low energy costs (e.g. minerals and organic acids) could buffer variations in CC values and help explain the difference in CC values between treatments 22,46,47. In this study, low levels of high-cost compounds (e.g. proteins) accompanied by high levels of low-cost compounds (e.g. organic acids) contributed to significantly lower CC values for P. elliottii growing in canopy subplots than in open subplots. For S. superba, because the increased levels of low-cost minerals could not balance the increased levels of high-cost proteins, CC values did not significantly differ between open and canopy subplots. In contrast, the elevated levels of low-cost minerals together with low-cost organic acids resulted in significantly decreased CC values for C. fissa seedlings growing in canopy subplots. For M. macclurei, except for soluble phenolics, most of the chemical compounds did not significantly differ in canopy vs. open subplots, which resulted in little change in CC values.

Research on leaf CC values and associated traits (e.g. payback time for the carbon investment) has provided insights into carbon acquisition strategies of plants and has therefore helped explain plant growth patterns and population dynamics48. Our study also showed that the measurement of a single chemical component or nutrient element might not be able to reveal much about the mechanisms of the plant nurse effects on target species. CC values together with estimated payback time, however, integrate the changes of plant chemical composition and photosynthesis, which may help explain plant response to nurse plants and may enable us to predict long-term growing performances of target plants. The calculated payback time based on CC values for P. elliottii was significantly elevated, but that for S. superba was decreased when growing in canopy subplots. From the perspective of long-term regional restoration practices (>3.5 years), we believe that P. elliottii will require a longer time to construct enough carbon for growth and metabolism when growing in the canopy than when growing in open subplots, while the opposite would be true for S. superba. Thus, we suggest that P. elliottii should be used solely as a pioneer tree to construct plantations and that S. superba can be more widely used to accelerate the establishment of native plantations using R. tomentosa as a nurse plant in subtropical degraded shrublands. We also determined that shrub nurse plant did not shorten the payback time for carbon construction of C. fissa or M. macclurei seedlings, which means that the two species did not benefit from shrub nurse effect during their establishment on subtropical degraded shrublands.

Conclusion

Changes in plant chemical composition, construction cost and payback time contribute to the different growing performances of target plants when nursed by shrubs. Among the four tested target species, S. superba is the only one that can effectively utilize the ameliorated microclimate constructed by shrubs, thus can potentially form multi-species communities and accelerate the reforestation of degraded subtropical shrublands. The findings of this study showed that the outcomes of shrub nurse effects are highly species- and time-specific because not all species will benefitted from shrub nurse plants at the same time. This study only demonstrated the possible mechanisms on plant nurse effect at a certain time point (3.5 year after the initiation of experiment). Therefore, it is possible that the nurse benefit may there during the early establishment state and gradually dissipate thereafter. Reforestation on degraded ecosystems is a long-term practice. Thus, it is crucial that careful experimental selection of both nursing and target species is assessed using long-term studies before massive practical restoration and plantation efforts.

Methods

Study site

This study was initiated in 2007 in a subtropical shrubland located at the Heshan National Field Research Station of Forest Ecosystems (112o50’E, 22o34’N, Heshan County, Guangdong Province, China). The regional subtropical evergreen broadleaved forest has degraded into a community dominated by shrubs and grasses. The soil type in this region is a typical laterite soil that has been seriously eroded because of a lack of forest coverage. The subtropical monsoon climate in this region is characterized by cool and dry winters and humid summers. The annual precipitation ranges from 1460 to 1820 mm, which mainly occurs as rain between March and August. At the station, the mean annual air temperature is 21.7 °C and the mean annual solar radiation is 435.75 KJ cm−2.

Plant species

Rhodomyrtus tomentosa (Ait.) Hassk. (Myrtaceae) is an evergreen shrub that grows naturally in infertile and acidic soils in tropical and subtropical Asia49. R. tomentosa, which is an indicator of acidic soil and a pioneer on bare land, has a cushion-shaped canopy and can grow as tall as 2 m. Our previous work showed that mature shrubs significantly reduced sunlight radiation and soil temperature, but significantly elevated soil volumetric water content, soil bulk density, as well as soil capillary moisture in subtropical degraded shrublands. R. tomentosa was therefore selected as a nurse plant for different tree seedlings in this and our previous studies8,9,17.

Four tree species were selected as target species. Schima superba Gardn. et Champ (Theaceae), Castanopsis fissa (Champ. ex Benth.) Rehd. et. Wils and Michelia macclurei Dandy. are broadleaved evergreen native tree species commonly used for reforestation in tropical and subtropical regions of China. Among them, S. superba is a shade tolerant, C. fissa is a moderate mesophytic and M. macclurei is a light demanding species. A fourth target tree species, Pinus elliottii Engelm. is an introduced conifer that can grow as tall as 30 m. It is fast growing and resistant to drought and nutrient-poor soils on degraded hills. This pine species is widely used in reforestation in southern China, because it has ecological values such as water and soil conservation and economic values such as a source of timber, pulp, nuts and rein50. Several researches have documented that pines can be facilitated by shrubs 6,7, however, few previous researches tested the facilitation of native shrub Rhodomyrtus tomentosa on the establishment and growth of pine seedlings on subtropical shrubland51. In this study, four reforestation species, including three broadleaved species and one conifer species, were selected to test whether they can be well facilitated by shrubs in their initial life history, to identify the underlying mechanisms from carbon allocation aspects and to instruct regional reforestation practices.

Experimental design

The detailed information regarding the establishment and design of the experiment were previously reported12,17 and are also briefly described below. In 2007, we divided the 2-ha subtropical shrubland field site into three blocks. Within each block, four plots (5 m × 5 m) were randomly selected and each plot was assigned to one of the four target tree species, giving a total of three plots for each target tree species. Within each plot, one 2 m × 2 m subplot was assigned the “canopy” treatment (CS) and one was assigned the “open” treatment (OS). CS subplots were located under the circular edges of the R. tomentosa canopies, which were 1.0–1.8 m high in 20078. OS subplots were located in areas without woody plant canopies. Seedlings (6 months old) of P. elliottii, S. superba, C. fissa and M. macclurei were transplanted individually in the CS and OS subplots in 2007; a total of 40 seedlings were planted in each subplot. As reported earlier17, two-thirds of the target tree seedlings were harvested for analysis at the end of 2008, leaving 10 to 15 seedlings in each subplot. Although some seedling mortality occurred in 2008, no additional mortality occurred in 2009 or 2010.

Plant growth, photosynthetic and structural parameters

Relative growth rates of seedling height (RGR-H) and basal diameter (RGR-B) of that target species were based on the height and basal diameter measured in October 2010 and the mean values measured in April 2007 and the RGRs were calculated as final minus initial logarithmic values divided by the time between measurements16. Leaf photosynthetic rates (A) of each target species were measured using an LI-6400 portable photosynthesis analyser (LI-COR, Lincoln, NE, USA) on clear days in October 2010; in each subplot, four to five replicate leaves (each from one plant) of each species were used. Maximum photosynthetic rates (Amax) were obtained at 1500 μmol m−2 s−1 light intensity with ambient CO2 concentration and air humidity. The obtained values for Amax (μmol CO2 m−2 s−1) were transformed to Amass (nmol CO2 g−1 s−1) based on specific leaf area (SLA). SLA was calculated as the ratio of leaf area/leaf mass after leaves had been oven dried at 60 °C for 72 h12.

Leaf chemical compositions

After photosynthetic rates were measured, leaves on the same branches of each tree were collected and oven-dried at 60 °C for 72 h. The dried leaves were then ground, passed through a 0.08 mm sieve and dried again in the oven. Total carbon (C) and nitrogen (N) concentrations in the leaf samples were determined spectrophotometrically with the potassium dichromate oxidation spectrophotometric method and the Kjeldahl method. Phosphorus concentration (P) was determined colorimetrically after HClO4-H2SO4 digestion52. Nitrate-N contents of leaf samples were measured colorimetrically with salicylic acid53. Ash content was determined by combusting 1 g of plant material in a muffle furnace at 550 °C for 6 h and then weighing the residue. Ash alkalinity was determined acidimetrically by titration54.

Another set of oven-dried leaf samples (1g) was extracted with a solution of water, methanol and chloroform in a volumetric ratio of 1:2:255. The extracts in the chloroform phase were dried with a rotary evaporator and the residue (total lipids) was weighed. Soluble carbohydrates were measured in the methanol-water phase using anthrone reagent56. The soluble phenol contents were also determined colorimetrically in the methanol-water phase with Folin-Ciocalteus reagent57. After extraction with the water, methanol and chloroform mixture, the residues of the leaf samples were boiled in 3% HCl (v/v) for 3 h. Insoluble sugars were subsequently analysed in the supernatants56. The final residues after boiling with HCl were used for another round of determination of carbon and nitrogen concentration using the potassium dichromate oxidation spectrophotometric method and the Kjeldahl method, respectively52.

Chemical calculations

Total mineral, protein and organic acid concentrations in target plant leaf samples were estimated using the following equations58:

The final residue after extraction was considered to be a mixture of lignin and TSC. Lignin concentration was calculated with the carbon and nitrogen concentration and assuming that the carbon concentration in the (hemi)cellulose complex was 444 mg g−1 and that the carbon concentration in lignin was 640 mg g−1 21. CC values of target plant leaf samples were calculated with the following formula59:

where CC is the construction cost (g glucose g−1), Com is the organic carbon concentration (g g−1), M is the total mineral content (g g−1) and Norg is the organic nitrogen concentration (g g−1). Because the quantity of ammonium and nitrate taken up by the different tree species was unknown, these CC values should be considered as maximum values.

Payback time was estimated as CC/Amass by transforming the unit of CC from g glucose g−1 to nmol C g−1 and by transforming the unit of Amass from nmol CO2 g−1 s−1 to nmol C g−1 h−1. Payback time was calculated per hour rather than per day, because the diurnal radiation period changes during the growing season. As a consequence, the estimated payback time is considered to be the theoretically minimum amortization period52,60.

Statistical analyses

We used IBM SPSS Statistics 19.0 for statistical analyses. Results are presented as means + standard deviation (SD). For each target species, differences between OS and CS subplots in plant growth and photosynthetic parameters, CC value, chemical composition and payback time were analysed with one-way ANOVAs. Two-way ANOVA was applied to determine the effect of species (4 levels) and treatments (2 levels) on plant growth and photosynthetic parameters, CC value, chemical composition and payback time.

Additional Information

How to cite this article: Liu, N. et al. Schima superba outperforms other tree species by changing foliar chemical composition and shortening construction payback time when facilitated by shrubs. Sci. Rep. 6, 19855; doi: 10.1038/srep19855 (2016).