Independent and interactive effects of N and P additions on foliar P fractions in evergreen forests of southern China

Qingquan Meng, Zhijuan Shi, Zhengbing Yan, Hans Lambers, Yan Luo, Wenxuan Han. Independent and interactive effects of N and P additions on foliar P fractions in evergreen forests of southern China[J]. Forest Ecosystems, 2025, 12(1): 100265. DOI: 10.1016/j.fecs.2024.100265

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Independent and interactive effects of N and P additions on foliar P fractions in evergreen forests of southern China

a.
Key Laboratory of Plant–Soil Interactions, Ministry of Education, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
b.
Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
c.
School of Biological Sciences, The University of Western Australia, Perth, WA, 6009, Australia
d.
Key Laboratory of Oasis Ecology of Education Ministry, College of Ecology and Environment, Xinjiang University, Urumqi 830017, China

Funds:

the National Natural Science Foundation of China 41473068

China Postdoctoral Science Foundation 2022M722667

More Information

Corresponding author:
Wenxuan Han, E-mail address: hanwenxuan@cau.edu.cn (W. Han)
Received Date: 26 July 2024
Rev Recd Date: 13 October 2024
Accepted Date: 13 October 2024

Graphical Abstract

Abstract

Abstract

Fertilization or atmospheric deposition of nitrogen (N) and phosphorus (P) to terrestrial ecosystems can alter soil N (P) availability and the nature of nutrient limitation for plant growth. Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N (P) availability and nutrient-limiting conditions. However, the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive. We conducted a meta-analysis of data about the concentrations and allocation proportions of leaf P fractions, specifically associated with individual and combined additions of N and P in evergreen forests, the dominant vegetation type in southern China where the primary productivity is usually considered limited by P. This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies. Nitrogen addition (exacerbating P limitation) reduced the concentrations of leaf total P and different leaf P fractions. Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions, while P addition showed opposite trends. The simultaneous additions of N and P showed an antagonistic (mutual suppression) effect on the concentrations of leaf P fractions, but an additive (summary) effect on the allocation proportions of leaf P fractions. These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability. Importantly, our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions, thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.

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1. Introduction

Phosphorus (P) is an essential element for sustaining life on Earth. It plays a crucial role in the synthesis of nucleic acids and membranes, as well as in the regulation of enzyme activities, thereby exerting a significant impact on fundamental biological processes such as photosynthesis and respiration (Lambers, 2022). Meanwhile, P is considered to be a major limiting element for plant activity and primary productivity in forest ecosystems (Elser et al., 2007; Hawkesford et al., 2023; Li et al., 2016). Recent research has emphasized the potential significance of leaf P allocation among various functional components in providing insights into plant adaptation to P limitation (Hidaka and Kitayama, 2011; Lambers, 2022; Veneklaas et al., 2012).

To adapt to low soil P availability, plants must strike a balance in allocating P to different leaf P fractions (Hayes et al., 2022; Wen et al., 2023), involving the prioritization of leaf P fractions that are essential for vital functions such as photosynthesis, while reducing allocation to secondary functions like structural roles. Leaf P can be divided into four fractions using chemical extraction methods, including metabolic P, lipid P, nucleic acid P and residual P. Metabolic P refers to inorganic P (Pi) and small P-containing metabolites (metabolite P); Pi is a soluble fraction located in the cytoplasm where it participates in metabolic activities, whereas excess Pi is stored in vacuoles to buffer the P concentration in the cytoplasm (Veneklaas et al., 2012). Metabolite P mainly comprises intermediates of carbon metabolism such as sugar phosphates, and these compounds play a crucial role in the Calvin cycle and glycolysis (Tsujii et al., 2023; Veneklaas et al., 2012; Wen et al., 2023). Lipid P is composed of phospholipids, which play a crucial role in membranes. Specifically, they are major components of both the plasmalemma and organelle membranes, especially the endoplasmic reticulum (Lambers, 2022). Nucleic acid P comprises biomolecules that are essential for life, including DNA which carries genetic information in living systems, and RNA which regulates protein turnover and synthesis (de Oliveira et al., 2018). Residual P is a fraction difficult to extract by chemical methods, including phosphorylated proteins and possibly some unidentified P-containing compounds (Hidaka and Kitayama, 2011; Mo et al., 2019).

Fertilization and atmospheric deposition have significantly increased N and P inputs into terrestrial ecosystems (Elser et al., 2007). Nitrogen inputs are more prevalent in terrestrial ecosystems than P inputs (Peñuelas et al., 2012, 2013); however, in specific regions, excessive application of P fertilization has led to elevated P inputs, which disrupt the equilibrium between N and P inputs (Cech et al., 2008). The imbalance between N and P inputs can result in N limitation, P limitation, or both (Peñuelas et al., 2013). Global N modeling projections indicated that, in the coming decades, southern China will be among the areas most significantly affected by N deposition (Galloway et al., 2008). Evergreen forests are the predominant vegetation type in southern China, and their primary productivity is usually considered limited by P (Shi et al., 2024); moreover, the high N deposition in southern China is assumed to exacerbate this P limitation and potentially alter plant nutrient utilization strategies in these evergreen forest ecosystems (Yuan and Chen, 2015b). Researchers have sought to investigate how plant nutrient use strategies respond to N and P inputs in this area by analyzing leaf P fractions. However, from the limited number of available studies, the concentrations and allocations of leaf P fractions exhibit inconsistent trends - either increasing, decreasing, or showing no marked change with nutrient addition, presenting incongruent models of P fraction allocation (Mo et al., 2019; Yu et al., 2022). So far, the influence of N and P additions on the concentrations and allocation proportions of leaf P fractions remains not fully understood. Therefore, examining the response of evergreen forests to unbalanced N and P inputs in southern China can offer valuable insights into nutrient cycling in P-limited areas and inform strategies for plant nutrient utilization in the context of increasing and imbalanced anthropogenic nutrient inputs.

Nitrogen addition either reduces leaf P fractions concentrations or has no significant effect (Su et al., 2024; Yu et al., 2022). Phosphorus addition and combined N and P additions typically increased leaf P fractions concentrations, though some studies reported no significant effect (Mo et al., 2019; Zhang et al., 2021). Research on leaf P fraction concentrations suggests that as natural soil P availability decreases and P limitation increases, the residual P concentration in plant leaves remains relatively constant; however, metabolic P, lipid P, and nucleic acid P concentrations show a declining trend, which may be related to the release of Pi from vacuoles, lipid remodeling, and reduced protein synthesis (Gao et al., 2022a; Hidaka and Kitayama, 2011; Yan et al., 2019). Therefore, we hypothesized that N addition (exacerbating P limitation) would decrease the leaf total, metabolic, lipid, and nucleic acid P concentrations; conversely, P addition (weakening P limitation) would trend in the opposite direction. Additionally, N and P usually were added at low ratios in actual combined N and P-addition experiments (Crowther et al., 2019; Garbowski et al., 2023; Widdig et al., 2020). Such treatment protocols could enhance the effect of P addition; therefore, we hypothesize that the effect of combined N and P addition is similar to that of P addition alone (Hypothesis 1).

In environments with severe P deficiency, certain plants adopt a strategy to maintain basic leaf physiological functions, including protein synthesis turnover and photosynthesis, by reducing overall metabolic activity; this adaptive approach allows them to reduce their overall demand for leaf P (Han et al., 2022; Hidaka and Kitayama, 2011; Mo et al., 2019; Warren, 2011; Zhang et al., 2021). Several studies have investigated the variation in leaf P fraction concentrations with soil P availability. A consistent trend has emerged: as soil P availability decreases, plants reduce the allocation to metabolic P while increasing the allocation to nucleic acid P and lipid P (Gao et al., 2022a, 2022b; Hidaka and Kitayama, 2011). Nitrogen addition typically does not affect the allocation of leaf P fractions, though some studies have observed an increase in the allocation to nucleic acid P and lipid P (Mo et al., 2019; Yu et al., 2022). In contrast, P addition and co-addition of N and P usually cause an increase in the allocation of metabolic P fractions (Hayes et al., 2022; Yu et al., 2022). Based on these findings, it is hypothesized that N addition (exacerbating P limitation) reduces the allocation to leaf metabolic P while increasing the allocation of P to leaf nucleic acid and lipid P; conversely, leaf P allocation will exhibit the opposite pattern under P addition and combined N and P addition (weakening P limitation) (Hypothesis 2).

As two essential mineral nutrients for plants, N and P are functionally coupled in biological systems, from cells to ecosystems (Ågren et al., 2012; Han et al., 2005; Reich and Oleksyn, 2004; Sterner and Elser, 2002). Previous studies have demonstrated that interactions between N and P are widespread in the biosphere. For example, at the molecular level, N-P interactions influence the expression of genes that are responsive to P starvation and nitrate transport (Hu and Chu, 2020). At the cell level, N-P interactions influence the concentrations and allocations of leaf P fractions (Zhang et al., 2021). At the individual level, N-P interactions regulate plant growth rates, stoichiometry, and nutrient uptake (Yan et al., 2015). Finally, at the ecosystem level, N-P interactions affect ecosystem productivity (Elser et al., 2007). To predict plant responses to imbalanced N and P inputs, it is crucial to determine whether plant growth responses to N and P addition are interdependent; if they are, it is important to identify the primary type of interaction. The combined N-P addition may result in additive, antagonistic, or synergistic effects. When N and P are co-added, the positive effects of P additions in P-limited systems may be diminished or entirely negated by N additions, suggesting the potential for either additive or antagonistic effects (Li et al., 2016; Su et al., 2014). In contrast, synergistic effects tend to occur in situations where systems are co-limited by N and P (Harpole et al., 2011). Plant biomass shows significant synergistic responses to N and P additions in terrestrial ecosystems (Elser et al., 2007; Harpole et al., 2011; Jiang et al., 2019); however, for most P-related metrics, the impact tends to be additive; this is observed in metrics such as total leaf P concentration, leaf N-to-P ratio (N: P), concentrations of total soil P, available soil P, and microbial biomass P (Jiang et al., 2019; Yuan and Chen, 2015a; Yue et al., 2018). Currently, there is insufficient research on the interactive effects of N and P additions on the concentrations and allocation proportions of leaf P fractions. We hypothesize that similar to other P-related metrics, the impact of combined N and P addition on the concentrations and allocation proportions of different leaf P fractions is additive (Hypothesis 3).

We carried out a thorough meta-analysis utilizing the data that was accessible from peer-reviewed case studies. The study had three specific objectives: (1) to clarify the effects of N and P additions on the concentrations of leaf P fractions, both individually and combined; (2) to determine the allocation proportions of leaf P fractions impacted by N and P additions individually and combined; and (3) to examine the interactive effects of N and P co-addition on both the concentrations and allocation proportions of different leaf P fractions.

2. Materials and methods

2.1 Data collection

Literature retrieval was conducted using the Web of Science and China National Knowledge Infrastructure until January 2024. The search used the following terms: ("N fertilization", "N addition", "N deposition", "N enrichment", and "N limitation"; "P fertilization", "P addition", "P deposition", "P enrichment", and "P limitation"; "nutrient addition", "nutrient enrichment", and "nutrient limitation") in combination with ("leaves", "leaf") and ("P fraction", "P allocation"). Furthermore, potential data collection was conducted by reviewing the references cited in the retrieved literature.

The criteria for paper selection were as follows:

(1) All studies were based on evergreen forests in southern China;

(2) Leaves must be mature and green, not young or senescent;

(3) Sampling must be based on natural field conditions, not greenhouse or indoor experiments;

(4) Leaves must be freeze-dried before measuring P fractions, not air-dried;

(5) The paper must contain all four required fractions or more, as needed for this study;

(6) The literature should include both controls and nutrient-addition treatments conducted under identical conditions;

(7) Data presented in the literature should consist of mean values and standard deviation (or standard error).

We obtained the required data directly from tables and supplementary files, or indirectly extracted from figures using GetData (version 2.20). Finally, our dataset includes 39 instances of N addition, 21 instances of P addition, and 21 instances of N and P co-addition for 17 woody evergreen species from southern China (Supplementary data). Additionally, data of leaf N: P ratio were also collected, given that this parameter is commonly used to indicate N and P limitation types that affect plant growth. When the leaf N: P ratio is greater than 16, the growth of plants is often limited by P (Han et al., 2013; Koerselman and Meuleman, 1996). According to these criteria of leaf N: P, the growth of 80% woody plant species in the field-experiment studies (the control groups) could be assumed to be limited by P in their natural habitats (Supplementary data, Fig. S1).

2.2 Data processing and analysis

The Shapiro-Wilk test was used for the assessment of the normality of the data before the statistical analyses. To improve data normality, we applied a logarithmic transformation, and then analyzed the correlations between the concentrations and allocation proportions of different leaf P fractions using standardized major axis regression with the 'smart' package in R 4.1.3 (R Development Core Team, 2022).

2.3 Meta-analysis

2.3.1 Calculation of the effect sizes of N-P individual and combined addition

Initially, missing standard deviations in the data were calculated using the Bracken (1992) method. The 'metagear' package in R was then used to complete the missing data. The meta-analysis used the natural logarithm of the response ratio (RR) (Hedges et al., 1999) to evaluate the impacts of N addition, P addition, and combined N and P addition on total leaf P concentration, different P fraction concentrations, and the allocation proportions of different P fractions. The calculation formula was as follows:

$\mathrm{RR}=\ln \left(\frac{X_{\mathrm{e}}}{X_{\mathrm{CK}}}\right)=\ln \left(X_{\mathrm{e}}\right)-\ln \left(X_{\mathrm{CK}}\right)$

(1)

The RR is an indicator of the impact of the experimental treatment on the target variable and is the ratio of the mean of the selected variable in the treatment group (X_e) to that in the control group (X_CK).

The detailed calculation of the variance (v_i) and weight (w_i) of each RR, and the overall effect size (RR) were described in the Supplementary Information (Text S1).

Our study's robustness to publication bias was assessed using Egger's test (Egger et al., 1997) and Rosenberg's fail-safe factor (Rosenberg, 2005). All calculations performed in R used the 'metafor' package. The results indicated that most variables did not exhibit publication bias (Table S1); moreover, for certain variables where potential publication bias was observed, it is unlikely to have impacted the outcomes, as Rosenberg's fail-safe factor considerably exceeded 5N+10 (N, the number of observations) (Table S2).

2.3.2 Calculation of the interactive effects of N-P co-addition

We employed Hedges' d to compute the main effects and interactive effects between N and P addition on the concentrations and allocation proportions of leaf P fractions (Gurevitch and Hedges, 2001). The main effects were determined by comparing the net effects of a single addition in the presence and absence of the second addition; this resembles testing for main effects in the analysis of variance, emphasizing one factor's unique influence at different levels of another factor (Crain et al., 2008). For each observed value, the formulas for calculating the effects of the two driving factors, N addition (d_+N) and P addition (d_+P), and their interactive effect (d_+NP), were as follows:

$d_{+\mathrm{N} i}=\frac{\left(X_{+\mathrm{N}}-X_{\mathrm{CK}}\right)+\left(X_{+\mathrm{NP}}-X_{\mathrm{CK}}\right)-\left(X_{+\mathrm{P}}-X_{\mathrm{CK}}\right)}{2 s} \times J$

(2)

$d_{+\mathrm{P} i}=\frac{\left(X_{+\mathrm{P}}-X_{\mathrm{CK}}\right)+\left(X_{+\mathrm{NP}}-X_{\mathrm{CK}}\right)-\left(X_{+\mathrm{N}}-X_{\mathrm{CK}}\right)}{2 s} \times J$

(3)

$d_{+\mathrm{NP} i}=\frac{\left(X_{+\mathrm{NP}}-X_{\mathrm{CK}}\right)-\left(X_{+\mathrm{N}}-X_{\mathrm{CK}}\right)-\left(X_{+\mathrm{P}}-X_{\mathrm{CK}}\right)}{s} \times J$

(4)

where X_CK, X₊_N, X₊_P, and X₊_NP represent the mean values of the control, N addition, P addition, and their combination for observation i, while s denotes the pooled standard deviation, and J is a correction term. The detailed calculation of i, s, J, and the overall weighted mean of Hedges' d were described in the Supplementary Information (Text S2).

The calculation for the 95% confidence interval (CI) was determined using the standard normal distribution's two-tailed critical value (C_α/2) and the standard error of d_t (s_t) (Zhou et al., 2016). Based on the 95% CI of the interactive effect, the types of interaction were classified as additive (if the 95% CI of d₊_NP overlapped with 0), synergistic (if the sign of d₊_NP matched the sum of d₊_N and d₊_P), or antagonistic (if the sign of d₊_NP opposed the sum of d₊_N and d₊_P) (Fig. S2) (Crain et al., 2008; Jiang et al., 2021; Zhou et al., 2016).

3. Results

3.1 Effects of N and P additions on the concentrations of leaf P fractions

Nitrogen addition significantly decreased the concentration of leaf total P and all P fractions (P < 0.05); in contrast, P addition significantly increased the concentration of leaf total P and all P fractions, except residual P (P < 0.05). The results of combined N and P additions were consistent with P addition (Fig. 1a–c). Analysis of the different P fraction concentrations in the leaves also revealed a positive correlation among them (Fig. 2a–f).

Figure 1. The effect size of N addition (+N), P addition (+P), and combined N and P addition (+NP) on leaf P fraction concentrations. n represents the number of observations of each response variable.