Leaf Allocation Research Articles (Page 1)

Understanding the relationships between species' demography and functional traits is crucial for gaining a mechanistic understanding of community dynamics. While leaf morphology represents a key functional dimension for plants worldwide (i.e., the leaf economics spectrum), its ability to explain variation in trees' life history strategies remains limited. Plant growth is influenced by both leaf morphology and allocation; hence, incorporating both dimensions is essential but rarely done. Additionally, trait–performance relationships have mainly been studied in tropical communities, leaving gaps in our understanding of temperate forests where different seasonality patterns may alter these relationships. We examined whether species' leaf area index (leaf area per crown size, LAI), a measure of leaf allocation, explains the variation of juvenile tree species' potential growth rates in a winter‐deciduous broadleaf forest. LAI has not been characterized as a species‐level trait, but its ability to predict plant productivity at the ecosystem scale highlights its potential for explaining plant growth. We evaluated species' maximum LAI both individually and in conjunction with wood density (WD) and leaf mass per area (LMA). We expected that models would improve when both leaf morphology (LMA) and leaf allocation (LAI) were included and that species with denser crowns would have higher potential growth rates. LAI and LMA were significant predictors of growth but only when both were incorporated, and together explained a high proportion of species' growth variations (R2adj = 0.59). We found evidence of a trade‐off between LAI and LMA, with a negative relationship between them and each having a positive influence on species' growth, suggesting that there are multiple allocation strategies to achieve fast growth. A surprisingly positive LMA–growth relationship contrasts with observations from tropical forests. We did not find significant relationships with WD in this forest. Our results highlight that incorporating leaf allocation improves models of trait–performance relationships. They also suggest, in agreement with the limited literature, that temperate forests may exhibit different trait–performance relationships from those of tropical forests, where LMA is negatively related to growth and WD is often important. Clarifying the details and contexts of trait–performance relationships is crucial for applying the functional trait framework to understanding community structure and dynamics of forests globally.

Abstract Internal nutrient recycling, such as leaf nutrient resorption, serves as an important strategy for plants to optimise their growth and survival on nutrient‐poor soils. Phosphorus resorption efficiency (P RE ) varies widely (20%–90%) among species living on P‐poor soils. However, the key drivers behind this local variation are poorly understood. We hypothesised that two traits would drive variation in P RE among species at a site characterised by chronically low soil P (total soil P of 84 ppm): leaf lifespan (LL) and the proportion of leaf P in ‘labile’ fractions that are easily resorbed. Labile P concentration, P labile , is comprised of inorganic phosphates and soluble phosphorylated metabolites. To test this hypothesis and gain a wider understanding of how leaf nutrient resorption varies locally, we quantified a set of related traits for 14 common woody species in a species‐rich but nutrient‐poor sclerophyll woodland community at Davies Park in the Blue Mountains, NSW, Australia. These traits were LL, P labile , green and senesced leaf N and P concentrations and P resorption efficiency (P RE ). Supporting our hypothesis, LL explained >50% variation in leaf P RE . Similarly, P RE was strongly and positively associated ( R 2 > 60%) with the allocation of green leaf P to P labile . The LL‐P RE relationship was mainly driven by lower senesced leaf P than green leaf P. The local soil P availability explained 60% variation in green leaf P. Overall, this study highlights the combination of traits leading to greater internal recycling of P, including high P RE , long LL and high allocation of leaf P to P labile , in species‐rich, nutrient‐poor ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Research on the factors driving below‐ground traits at broad scales is crucial for understanding plant adaptation to diverse environments and the function of the plant economics spectrum. However, studies on intraspecific trait variation (ITV) remain scarce, and even fewer address the integration of both above‐ and below‐ground traits. By cultivating 74 globally sourced genotypes of Phragmites australis, a cosmopolitan grass species, in a controlled environment, we measured both above‐ and below‐ground traits. Our results revealed significant latitudinal variation, with plant height, shoot diameter and rhizome diameter decreasing, while shoot number, leaf allocation and specific root length (SRL) increased with absolute latitude. Bioclimatic heterogeneity had a stronger influence on ITV than geographical isolation. Above‐ground traits responded primarily to radiation and temperature, while below‐ground traits were more influenced by precipitation. Our results highlighted the presence of two distinct yet interconnected trait modules for above‐ground and below‐ground traits. Synthesis. This coordination enhances resource use efficiency and ecological success across latitudinal gradients, enabling plants to thrive in diverse environments. The study establishes a comprehensive framework for deciphering the intricate interplay of environmental factors that drive plant adaptive strategies. By revealing how ITV responds to bioclimatic heterogeneity, our research offers insights into the resilience of widespread plants under global climate change.

Leaf phenology, represented at the ecosystem scale by the seasonal dynamics of leaf area index (LAI), is a key control on the exchanges of CO2, energy, and water between the land and atmosphere. Robust simulation of leaf phenology is thus important for both dynamic global vegetation models (DGVMs) and land-surface representations in climate and Earth System models. There is no general agreement on how leaf phenology should be modeled. However, a recent theoretical advance posits a universal relationship between the time course of "steady-state" gross primary production (GPP) and LAI-that is, the mutually consistent LAI and GPP that would pertain if weather conditions were held constant. This theory embodies the concept that leaves should be displayed when their presence is most beneficial to plants, combined with the reciprocal relationship of LAI and GPP via (a) the Beer's law dependence of GPP on LAI, and (b) the requirement for GPP to support the allocation of carbon to leaves. Here we develop a global prognostic LAI model, combining this theoretical approach with a parameter-sparse terrestrial GPP model (the P model) that achieves a good fit to GPP derived from flux towers in all biomes and a scheme based on the P model that predicts seasonal maximum LAI as the lesser of an energy-limited rate (maximizing GPP) and a water-limited rate (maximizing the use of available precipitation). The exponential moving average method is used to represent the time lag between leaf allocation and modeled steady-state LAI. The model captures satellite-derived LAI dynamics across biomes at both site and global levels. Since this model outperforms the 15 DGVMs used in the TRENDY project, it could provide a basis for improved representation of leaf-area dynamics in vegetation and climate models.

Abstract Tropical forests are generally characterized by high species diversity and low soil phosphorus (P) availability. Although tropical plants have evolved adaptations to low soil P availability, we know relatively little about the strategies of different groups of species to efficiently use P, or how these strategies might shape their distributions. We compared the performance of 16 co‐occurring species in tropical forests in South China under two soil P regimes. We divided these species into three groups: exotic species, which are not native to South China; eurytopic native species, which occur in both P‐limited and P‐richer habitats; stenotopic native species, which only occur in low‐P habitats. We assessed their growth rates, foliar functional traits and foliar P fractions under experimentally manipulated soil P availability (Control vs. +P). Exotic species exhibited greater plasticity in allocation of leaf P fractions than native species. Compared with native species, exotic species allocated more P to inorganic‐P than to ester‐P and nucleic‐P in P‐enriched soil, while they allocated less P to inorganic‐P and ester‐P in low‐P soil. Eurytopic native species responded inconsistently to P addition, indicating that eurytopic native species may employ various strategies to cope with low P availability, whereas stenotopic native species showed only minor changes in leaf P allocation with P fertilization. We distinguished two strategies for plant adaptation to low soil P availability: (1) a P‐plastic strategy exhibited by exotic species, in which Pleaf and leaf P‐fraction allocation patterns changed substantially with soil P enrichment; (2) a P‐conservative strategy exhibited by stenotopic native species, in which Pleaf and leaf P‐fraction allocation patterns changed only slightly with soil P enrichment. In conclusion, the distinct strategies exhibited by plants in low‐P habitats may determine their distribution and coexistence in tropical regions. Read the free Plain Language Summary for this article on the Journal blog.

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

Cadmium (Cd) is a heavy metal that is highly toxic to plants and animals and can accumulate in the environment as a result of industrial activities and agricultural application of some types of phosphate fertilizer. This study aimed to assess the role of sodium nitroprusside (SNP), as a source of nitric oxide (NO) in alleviating Cd stress in maize plants. Maize plants were kept in soil saturated with 40%-strength nutrient solution in a greenhouse, and cadmium nitrate, Cd(NO3)2, was applied at different concentrations, (0, 10, and 50µM). Sodium nitroprusside, [Fe(CN)5NO]·2H2O, at concentrations of 0.05, 0.1, and 0.2µM. Growth, leaf gas exchange, and leaf anatomy analyses were performed. The experimental design was completely randomized in a 3 × 3 factorial arrangement with five replicates. The highest concentrations of Cd and SNP reduced the total dry mass and leaf and stem dry mass but increased the allocation of biomass to the roots and stem, but the leaf allocation did not change. The application of Cd and SNP promoted an increase in gas exchange and leaf area, in addition to an increase in leaf tissue thickness and stomatal density. The presence of SNP at low concentrations reduces the toxicity of Cd, but at high concentrations, this compound can generate negative effects and even toxicity in maize plants.

Abstract Plant biomass production (BP), nitrogen uptake (Nup) and their ratio, and nitrogen use efficiency (NUE) must be quantified to understand how nitrogen (N) cycling constrains terrestrial carbon (C) uptake. But the controls of key plant processes determining Nup and NUE, including BP, C and N allocation, tissue C:N ratios and N resorption efficiency (NRE), remain poorly known. We compiled measurements from 804 forest and grassland sites and derived regression models for each of these processes with growth temperature, vapour pressure deficit, stand age, soil C:N ratio, fAPAR (remotely sensed fraction of photosynthetically active radiation absorbed by green vegetation) and growing‐season average daily incident photosynthetic photon flux density (gPPFD; effectively the seasonal concentration of light availability, which increases polewards) as predictors. An empirical model for leaf N was based on optimal photosynthetic capacity (a function of gPPFD and climate) and observed leaf mass per area. The models were used to produce global maps of Nup and NUE. Global BP was estimated as 72 Pg C/year; Nup as 950 Tg N/year; and NUE as 76 g C/g N. Forest BP was found to increase with growth temperature and fAPAR and to decrease with stand age, soil C:N ratio and gPPFD. Forest NUE is controlled primarily by climate through its effect on C allocation—especially to leaves, being richer in N than other tissues. NUE is greater in colder climates, where N is less readily available, because below‐ground allocation is increased. NUE is also greater in drier climates because leaf allocation is reduced. NRE is enhanced (further promoting NUE) in both cold and dry climates. Synthesis. These findings can provide observationally based benchmarks for model representations of C–N cycle coupling. State‐of‐the‐art vegetation models in the TRENDY ensemble showed variable performance against these benchmarks, and models including coupled C–N cycling produced relatively poor simulations of Nup and NUE.

Background and AimsThe leaf economic spectrum (LES) is related to dry mass and nutrient investments towards photosynthetic processes and leaf structures, and to the duration of returns on those investments (leaf lifespan, LL). Phosphorus (P) is a key limiting nutrient for plant growth, yet it is unclear how the allocation of leaf P among different functions is coordinated with the LES. We addressed this question among 12 evergreen woody species co-occurring on P-impoverished soils in south-eastern Australia.MethodsLeaf ‘economic’ traits, including LL, leaf mass per area (LMA), light-saturated net photosynthetic rate per mass (Amass), dark respiration rate, P concentration ([Ptotal]), nitrogen concentration, and P resorption, were measured for three pioneer and nine non-pioneer species. Leaf P was separated into five functional fractions: orthophosphate P (Pi), metabolite P (PM), nucleic acid P (PN), lipid P (PL), and residual P (PR; phosphorylated proteins and unidentified compounds that contain P).ResultsLL was negatively correlated with Amass and positively correlated with LMA, representing the LES. Pioneers occurred towards the short-LL end of the spectrum and exhibited higher [Ptotal] than non-pioneer species, primarily associated with higher concentrations of Pi, PN and PL. There were no significant correlations between leaf P fractions and LL or LMA, while Amass was positively correlated with the concentration of PR.ConclusionsAllocation of leaf P to different fractions varied substantially among species. This variation was partially associated with the LES, which may provide a mechanism underlying co-occurrence of species with different ecological strategies under P limitation.

Nitrogen availability and light quality affect plant resource allocation, but their interaction is poorly understood. Herein, we analyzed the growth and allocation of dry matter and nitrogen using lettuce (Lactuca sativa L.) as a plant model in a factorial experiment combining three light regimes (100% red light, R; 50% red light + 50% blue light, RB; 100% blue light, B) and two nitrogen rates (low, 0.1 mM N; high, 10 mM N). Red light increased shoot dry weight in relation to both B and RB irrespective of nitrogen supply. Blue light favored root growth under low nitrogen. Allometric analysis showed lower allocation to leaf in response to blue light under low nitrogen and similar leaf allocation under high nitrogen. A difference in allometric slopes between low nitrogen and high nitrogen in treatments with blue light reflected a strong interaction effect on root-to-shoot biomass allocation. Shoot nitrate concentration increased with light exposure up to 14 h in both nitrogen treatments, was higher under blue light with high nitrogen, and varied little with light quality under low nitrogen. Shoot nitrogen concentration, nitrogen nutrition index, and shoot NR activity increased in response to blue light. We conclude that the interaction between blue light and nitrogen supply modulates dry mass and nitrogen allocation between the shoot and root.

Trait-based approaches have been extensively used in community ecology to provide a mechanistic understanding of the drivers of community assembly. However, a foundational assumption of the trait framework, traits relate to performance, has been mainly examined through univariate relationships that simplify the complex phenotypic integration of organisms. We evaluate a conceptual framework in which traits are organized hierarchically combining trait information at the individual- and species-level from biomass allocation and organ-level traits. We focus on photosynthetic traits and predict that the positive effects of increasing plant leaf mass on growth depend on species-level leaf traits. We modeled growth data on more than 1,500 seedlings from 97 seedling species from a tropical forest in China. We found that seedling growth increases with allocation to leaves (high leaf area ratio and leaf mass fraction) and this effect is accentuated for species with high specific leaf area and leaf area. Also, we found that light has a significant effect on growth, and this effect is additive with leaf allocation traits. Our work offers an approach to gain further understanding of the effects of traits on the whole plant-level growth via a hierarchical framework including organ-level and biomass allocation traits at species and individual levels.

The responses of plants to recurrent stress may differ from their responses to a single stress event. In this study, we investigated whether clonal plants can remember past environments. Parental ramets of Glechoma longituba (Nakai) Kuprian were exposed to UV-B stress treatments either once or repeatedly (20 and 40 repetitions). Differences in DNA methylation levels and growth parameters among parents, offspring ramets and genets were analysed. Our results showed that UV-B stress reduced the DNA methylation level of parental ramets, and the reduction was enhanced by increasing the number of UV-B treatments. The epigenetic variation exhibited by recurrently stressed parents was maintained for a long time, but that of singly stressed parents was only short-term. Moreover, clonal plants responded to different UV-B stress treatments with different growth strategies. The one-time stress was a eustress that increased genet biomass by increasing offspring leaf allocation and defensive allocation in comparison to the older offspring. In contrast, recurring stress was a distress that reduced genet biomass, increased the biomass of storage stolons, and allocated more defensive substances to the younger ramets. This study demonstrated that the growth of offspring and genets was clearly affected by parental experience, and parental epigenetic memory and the transgenerational effect may play important roles in this effect.

The trade-off between leaf size and number is the basis for plant growth strategies. It is of great significance to study the underlying mechanism of leaf size and number trade-offs for well understanding plant growth strategies. In this study, leaf size was expressed by the dry mass of single leaf, while leafing intensity was expressed by the number of leaves per unit stem volume. We used standardized major axis regression analysis method to examine the trade-off relationship between leaf size and number in Hulunbuir grassland. There was a significant negative isometric-growth trade-off between leaf size and number in Chenqicuogang (typical steppe) and Chenqibayi (meadow steppe). There was a significant negative allometric-growth trade-off between leaf size and number in Xeltala (meadow steppe). The underlying mechanism of the relationship between leaf size and number depended on the leaf and stem biomass allocation mechanism and the changes of the stem tissue density.

不同密度猪毛菜形态结构性状及生物量分配策略的异速关系

Abstract Individual‐level demographic outcomes should be predictable upon the basis of traits. However, linking traits to tree performance has proven challenging likely due to a failure to consider physiological traits (i.e. hard‐traits) and the failure to integrate organ‐level and whole plant‐level trait information. Here, we modelled the survival rate and relative growth rate of trees while considering crown allocation, hard‐traits and local‐scale biotic interactions, and compared these models to more traditional trait‐based models of tree performance. We found that an integrative trait, total tree‐level photosynthetic mass (estimated by multiplying specific leaf area and crown area) results in superior models of tree survival and growth. These models had a lower AIC than those including the effect of initial tree size or any other combination of the traits considered. Survival rates were positively related to higher values of crown area and photosynthetic mass, while relative growth rates were negatively related to the photosynthetic mass. Relative growth rates were negatively related to a neighbourhood crowding index. Furthermore, none of the hard‐traits used in this study provided an improvement in tree performance models. Synthesis. Overall, our results highlight that models of tree performance can be greatly improved by including crown area information to generate a better understanding of plant responses to their environment. Additionally, the role of the hard‐traits in improving models of tree performance is likely dependent upon the level of stress (e.g. drought stress), micro‐environmental conditions or short‐term climatic variations that a particular forest experiences.

Abstract Plants allocate biomass to different organs in response to resource variation for maximizing performance, yet we lack a framework that adequately integrates plant responses to the simultaneous variation in above‐ and below‐ground resources. Although traditionally, the optimal partition theory (OPT) has explained patterns of biomass allocation in response to a single limiting resource, it is well‐known that in natural communities multiple resources limit growth. We study trade‐offs involved in plant biomass allocation patterns and their effects on plant growth under variable below‐ and above‐ground resources—light, soil N and P—for seedling communities. We collected information on leaf, stem and root mass fractions for more than 1,900 seedlings of 97 species paired with growth data and local‐scale variation in abiotic resources from a tropical forest in China. We identified two trade‐off axes that define the mass allocation strategies for seedlings—allocation to photosynthetic versus non‐photosynthetic tissues and allocation to roots over stems—that responded to the variation in soil P and N and light. Yet, the allocation patterns did not always follow predictions of OPT in which plants should allocate biomass to the organ that acquires the most limiting resource. Limited soil N resulted in high allocation to leaves at the expense of non‐photosynthetic tissues, while the opposite trend was found in response to limited soil P. Also, co‐limitation in above‐ and below‐ground resources (light and soil P) led to mass allocation to stems at the expense of roots. Finally, we found that growth increased under high‐light availability and soil P for seedlings that invested more in photosynthetic over non‐photosynthetic tissues or/and that allocated mass to roots at the expense of stem. Synthesis. Biomass allocation patterns to above‐ and below‐ground tissues are described by two independent trade‐offs that allow plants to have divergent allocation strategies (e.g. high root allocation at the expense of stem or high leaf allocation at the expense of allocation to non‐photosynthetic tissues) and enhance growth under different limiting resources. Identifying the trade‐offs driving biomass allocation is important to disentangle plant responses to the simultaneous variation in resources in diverse forest communities.

Hybrid Napier grass (Pennisetum purpureum Schumach × P. americanum (L.) Leeke cv. Pakchong1) and Giant reed (Arundo donax L.) as candidate species in temperate European paludiculture: Growth and gas exchange responses to suboptimal temperatures

Plant functional traits provide a link in process-based vegetation models between plant-level physiology and ecosystem-level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large-scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re-evaluation of trait-based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type-specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.

Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO2 fertilization and anthropogenic climate change. Here, we develop an optimization-based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta-analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic-carbon coupling explains observed patterns in leaf allocation across large environmental and CO2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree-level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.

Allocation of biomass to different organs is a fundamental aspect of plant responses and adaptations to changing environmental conditions, but how it responds to nitrogen (N) and phosphorus (P) availability remains poorly addressed. Here we conducted greenhouse fertilization experiments using Arabidopsis thaliana, with five levels of N and P additions and eight repeat experiments, to ascertain the effects of N and P availability on biomass allocation patterns. N addition increased leaf and stem allocation, but decreased root and fruit allocation. P addition increased stem and fruit allocation, but decreased root and leaf allocation. Pooled data of the five levels of N addition relative to P addition resulted in lower scaling exponents of stem mass against leaf mass (0.983 vs. 1.226; p = 0.000), fruit mass against vegetative mass (0.875 vs. 1.028; p = 0.000), and shoot mass against root mass (1.069 vs. 1.324; p = 0.001). This suggested that N addition relative to P addition induced slower increase in stem mass with increasing leaf mass, slower increase in reproductive mass with increasing vegetative mass, and slower increase in shoot mass with increasing root mass. Further, the levels of N or P addition did not significantly affect the allometric relationships of stem mass vs. leaf mass, and fruit mass vs. vegetative mass. In contrast, increasing levels of N addition increased the scaling exponent of shoot to root mass, whereas increasing levels of P addition exerted the opposite influence on the scaling exponent. This result suggests that increasing levels of N addition promote allocation to shoot mass, whereas the increasing levels of P addition promote allocation to root mass. Our findings highlight that biomass allocation of A. thaliana exhibits a contrasting response to N and P availability, which has profound implications for forecasting the biomass allocation strategies in plants to human-induced nutrient enrichment.