Leaf Nitrogen Research Articles

Effects of nitrogen addition and leaf age on needle traits and the relationships among traits in Pinus koraiensis

Leaf functional traits are essential for the growth and adaptation of trees to environmental changes. However, how needle traits and trait–trait relationships respond to different nitrogen (N) addition rates and leaf ages remain unclear for evergreen coniferous species. Our study aimed to investigate the effects of N addition and leaf age on needle traits and their bivariate correlations. Understanding resource utilization and distribution strategies during tree growth under the background of increased N deposition is important. We conducted a six-year manipulative field experiment in a Pinus koraiensis plantation in northeastern China with variable N addition levels: control (no N addition, CK); 20 kg N ha−1yr−1 (low-N, LN); 40 kg N ha−1yr−1 (medium-N, MN); and 80 kg N ha−1yr−1 (high-N, HN). The needle trait data were collected in September. The morphological traits, i.e., specific leaf area (SLA) and leaf dry matter content (LDMC); and chemical traits, i.e., leaf nitrogen concentration (LNC), leaf phosphorus concentration (LPC), and leaf nonstructural carbohydrates (NSC) concentrations, were measured to investigate the changes in needle traits and their bivariate correlations. We found that N addition and needle age significantly affected needle traits, and the effect of needle age was much stronger than that of N addition. N addition and needle age had no significant interaction effects on any of the traits except for the LNC. Due to the dispersal trait values of current-year needles, there were almost no significant bivariate correlations between traits under different N addition rates. The SLA–LDMC and LDMC–LNC relationships were found to differ among the various N addition rates, and other traittrait relationships may be relatively stable because of the weak plasticity of older needles. Additionally, needle age significantly affected the slope of the SLA–LDMC relationship and the elevation of the LDMC–LPC and NSC–LNC relationships, indicating differences in the ecological strategies of needles at different ages. In summary, our findings emphasize that trait–trait relationships in current-year and older needles were inconsistent in response to N addition and that the optimal allocation of resources in needles was based on their functional needs during leaf aging.

Leaf ecological stoichiometry and anatomical structural adaptation mechanisms of Quercus sect. Heterobalanus in southeastern Qinghai–Tibet Plateau

BackgroundWith the dramatic uplift of the Qinghai–Tibet Plateau (QTP) and the increase in altitude in the Pliocene, the environment became dry and cold, thermophilous plants that originally inhabited ancient subtropical forest essentially disappeared. However, Quercus sect. Heterobalanus (QSH) have gradually become dominant or constructive species distributed on harsh sites in the Hengduan Mountains range in southeastern QTP, Southwest China. Ecological stoichiometry reveals the survival strategies plants adopt to adapt to changing environment by quantifying the proportions and relationships of elements in plants. Simultaneously, as the most sensitive organs of plants to their environment, the structure of leaves reflects of the long-term adaptability of plants to their surrounding environments. Therefore, ecological adaptation mechanisms related to ecological stoichiometry and leaf anatomical structure of QSH were explored. In this study, stoichiometric characteristics were determined by measuring leaf carbon (C), nitrogen (N), and phosphorus (P) contents, and morphological adaptations were determined by examining leaf anatomical traits with microscopy.ResultsDifferent QSH life forms and species had different nutrient allocation strategies. Leaves of QSH plants had higher C and P and lower N contents and higher N and lower P utilization efficiencies. According to an N: P ratio threshold, the growth of QSH species was limited by N, except that of Q. aquifolioides and Q. longispica, which was limited by both N and P. Although stoichiometric homeostasis of C, N, and P and C: N, C: P, and N: P ratios differed slightly across life forms and species, the overall degree of homeostasis was strong, with strictly homeostatic, homeostatic, and weakly homeostatic regulation. In addition, QSH leaves had compound epidermis, thick cuticle, developed palisade tissue and spongy tissue. However, leaves were relatively thin overall, possibly due to leaf leathering and lignification, which is strategy to resist stress from UV radiation, drought, and frost. Furthermore, contents of C, N, and P and stoichiometric ratios were significantly correlated with leaf anatomical traits.ConclusionsQSH adapt to the plateau environment by adjusting the content and utilization efficiencies of C, N, and P elements. Strong stoichiometric homeostasis of QSH was likely a strategy to mitigate nutrient limitation. The unique leaf structure of the compound epidermis, thick cuticle, well-developed palisade tissue and spongy tissue is another adaptive mechanism for QSH to survive in the plateau environment. The anatomical adaptations and nutrient utilization strategies of QSH may have coevolved during long-term succession over millions of years.

Influence of selected growing media on the morphology, yield and nutrient uptake of Strawberry Cv. Winter Dawn

The present investigation was carried out at Horticultural Demonstration Farm, SGT University, Gurugram, during the years 2022-23 to determine the efficacy of growth, yield, quality and nutrient uptake in the Strawberry cultivar Winter Dawn. The research trial was conducted in the RBD with seven different growing media (T1: Perlite + Soil, T2: Cocopeat + Soil, T3: FYM + Soil, T4: Cocopeat + Perlite + Soil, T5: Cocopeat + FYM + Soil, T6: FYM + Perlite and T7: FYM + Cocopeat + Perlite + Soil) and a control (T0). The results showed that the maximum plant height (40.93 cm), no. of leaves (36.73%), no. of crown (13.33%), no. of berry percentage (10.40%), fruit yield/plant (206.95 gm), berry weight (26.36 gm), berry size (35.45 mm), berry volume (30.32 cc), TSS (10.05°Brix), total sugar (6.01%), titratable acidity (0.77%), reducing sugars (5.93%), nonreducing sugars (0.53%) and leaf nutrient uptake, i.e., nitrogen (27.70%), phosphorus (3.56%) and potassium (90.80%), were greatest in the T7 treatment group, followed by the T5 treatment group. T7 application leads to improvements in soil nutrient content and microbial activity, contributing to significant improvements in both the quantity and quality of produce. Therefore, growing media (especially FYM, cocopeat and perlite) should be selected as growing media to cultivate strawberries for quality production.

Rapid estimates of leaf litter chemistry using reflectance spectroscopy

Measuring the chemical traits of leaf litter is important for understanding plants’ influence on nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including both needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R2 = 0.543–0.941; %root mean squared error (RMSE) = 7.49–18.5) and ground-leaf litter spectra (validation R2 = 0.491–0.946; %RMSE = 7.00–19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, intact-leaf spectral models allow non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption.

Alpha and beta diversity of functional traits in subtropical evergreen broad-leaved secondary forest communities.

Intra-speciic variation is the main source of functional trait diversity and has similar ecological effects as inter-speciic variation. We studied 79 species and 3546 individuals from 50 ixed monitoring plots in subtropical evergreen broad - leaved secondary forests in Zhejiang Province, China. Using trait gradient analysis, we examined nine traits (speciic leaf area, leaf dry matter content, wood density, leaf area, chlorophyll content, leaf nitrogen content, leaf phosphorus content, leaf potassium content, and nitrogen-phosphorus ratio) by decomposing species functional traits into alpha (within-community) and beta (among-communities) measure the impact of environmental gradients and the presence of other species on the variation of traits. All nine functional traits showed some degree of differentiation in the forest communities, with a greater range of variation in alpha values than in beta values . Correlations were signiicantly different between the trait differences in the communities. The alpha values of each trait showed a higher correlation with other components than the beta values. The factors affecting intra-speciic trait variation were relatively complex. The alpha component had a more signiicant and stronger effect on intra-speciic trait variation compared to the beta component. Abiotic factors, such as soil nutrient content, soil nitrogen-phosphorus content, directly affected the beta component. In contrast, biotic factors, such as tree height variation, had a direct and stronger effect on the alpha component. Our results demonstrate that alpha and beta components, as independent differentiation axes among coexisting species, have different sensitivities to different environmental factors and traits in different ecological strategies and spatial scales. Trait gradient analysis can more clearly reveal the variation patterns of species traits in communities, which will help to understand the scale effects and potential mechanisms of trait relationships.

NRT1.1B mediates rice plant growth and soil microbial diversity under different nitrogen conditions

Interactions between microorganisms and plants can stimulate plant growth and promote nitrogen cycling. Nitrogen fertilizers are routinely used in agriculture to improve crop growth and yield; however, poor use efficiency impairs the optimal utilization of such fertilizers. Differences in the microbial diversity and plant growth of rice soil under different nitrogen application conditions and the expression of nitrogen-use efficiency-related genes have not been previously investigated. Therefore, this study investigates how nitrogen application and nitrogen-use efficiency-related gene NRT1.1B expression affect the soil microbial diversity and growth indices of two rice varieties, Huaidao 5 and Xinhuai 5. In total, 103,463 and 98,427 operational taxonomic units were detected in the soils of the Huaidao 5 and Xinhuai 5 rice varieties, respectively. The Shannon and Simpson indices initially increased and then decreased, whereas the Chao and abundance-based coverage estimator indices decreased after the application of nitrogen fertilizer. Nitrogen fertilization also reduced soil bacterial diversity and richness, as indicated by the reduced abundances of Azotobacter recorded in the soils of both rice varieties. Nitrogen application initially increased and then decreased the grain number per panicle, yield per plant, root, stem, and leaf nitrogen, total nitrogen content, glutamine synthetase, nitrate reductase, urease, and root activities of both varieties. Plant height showed positive linear trends in response to nitrogen application, whereas thousand-grain weights showed a negative trend. Our findings may be used to optimize nitrogen fertilizer use for rice cultivation and develop crop-variety-specific strategies for nitrogen fertilizer application.

Peri-urban Mediterranean plant communities are shaped by chronic anthropogenic disturbances

Peri-urban plant communities perform key ecological functions. However, the integrity of peri-urban vegetation is threatened by the continuous expansion of built-up areas and anthropogenic activities, which result in low-intensity, but continuous and pervasive chronic anthropogenic disturbances (CADs). Despite the growing attention to the ecological role of peri-urban vegetation patches, the assessment of the relationship between CADs and typical Mediterranean plant communities at the local scale is still lacking. In this work, both the compositional and functional responses to typical CADs of five vegetation types were assessed in 48 plots, located around the city of Genoa (Italy). The main anthropogenic and environmental drivers of species composition were identified through a Non-Metric Multidimensional Scaling, and selected variables were used to fit a partial Redundancy Analysis. Differences in the number of alien species in relation to total CAD intensity were assessed with a Kruskal-Wallis test. Regarding functional composition, the community weighted mean values (CWMs) of five functional traits were computed for each plot. Generalized linear models were then fitted to assess the relationship between the CWMs and CADs intensity. Our results showed that the specific composition of peri-urban plant communities of Genoa is shaped by interacting environmental and anthropogenic factors. Considering composition, CADs promote the increase of alien species’ number. Moreover, the increased intensity of CADs altered the functional composition, with increasing specific leaf area, leaf nitrogen content and seed bank longevity. Overall, the effect of typical Mediterranean CADs is more pronounced on the functional composition than on the taxonomic composition of peri-urban plant communities. This work highlights the relevance at the local scale of the typical CADs of the Mediterranean area in influencing the different vegetation types that characterise a peri-urban zone.

Differences and drivers of leaf stable carbon and nitrogen isotope in herbs under different vegetation types on the eastern Qinghai-Tibet Plateau

The natural abundance of stable carbon and nitrogen isotopes (δ13C and δ15N) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δ13C and δ15N have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δ13C and δ15N of herbs and the driving factors. The results showed that there were significant differences in leaf δ13C and δ15N values of herbs among different vegetation types, with the highest δ13C and δ15N values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δ13C and δ15N of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (Narea), and leaf mass per area were the main drivers of leaf δ13C variations of herbs across different vegetation types, while the relative importance of Narea and MAT for variation in leaf δ15N of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δ13C and δ15N as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δ13C and δ15N variations in herbs across different vegetation types.

In Situ Nondestructive Detection of Nitrogen Content in Soybean Leaves Based on Hyperspectral Imaging Technology

In this paper, hyperspectral imaging technology, combined with chemometrics methods, was used to detect the nitrogen content of soybean leaves, and to achieve the rapid, non-destructive and in situ detection of the nitrogen content in soybean leaves. Soybean leaves under different fertilization treatments were used as the research object, and the hyperspectral imaging data and the corresponding nitrogen content data of soybean leaves at different growth stages were obtained. Seven spectral preprocessing methods, such as Savitzky–Golay smoothing (SG), first derivative (1-Der), and direct orthogonal signal correction (DOSC), were used to establish the quantitative prediction models for soybean leaf nitrogen content, and the quantitative prediction models of different spectral preprocessing methods for soybean leaf nitrogen content were analyzed and compared. On this basis, successive projections algorithm (SPA), genetic algorithm (GA) and random frog (RF) were employed to select the characteristic wavelengths and compress the spectral data. The results showed the following: (1) The full-spectrum prediction model of soybean leaf nitrogen content based on DOSC pretreatment was the best. (2) The PLS model of soybean leaf nitrogen content based on the five characteristic wavelengths had the best prediction performance. (3) The spatial distribution map of soybean leaf nitrogen content was generated in a pixel manner using the extracted five characteristic wavelengths and the DOSC-RF-PLS model. The nitrogen content level of soybean leaves can be quantified in a simple way; this provides a foundation for rapid in situ non-destructive detection and the spatial distribution difference detection of soybean leaf nitrogen. (4) The overall results illustrated that hyperspectral imaging technology was a powerful tool for the spatial prediction of the nitrogen content in soybean leaves, which provided a new method for the spatial distribution of the soybean nutrient status and the dynamic monitoring of the growth status.

Improving Tuber Yield of Tiger Nut (Cyperus esculentus L.) through Nitrogen Fertilization in Sandy Farmland.

The cultivation of tiger nut (Cyperus esculentus L.) on marginal lands is a feasible and effective way to increase food production in Northern China. However, the specific influence of nitrogen fertilizer application on the growth dynamics, tuber expansion, overall yield, and nitrogen use efficiency (NUE) of tiger nuts cultivated on these sandy lands is yet to be fully elucidated. From 2021 to 2022, we conducted a study to determine the effect of N fertilizers on the leaf function morphology, canopy apparent photosynthesis (CAP), tuber yield, and NUE of tiger nut. The results indicate that the tuber yield and NUE are closely related to the specific leaf area (SLA), leaf area index (LAI), leaf nitrogen concentration per area (NA), CAP, and tuber expansion characteristics. Notably, significant enhancements in the SLA, LAI, NA, and CAP during the tuber expansion phase ranging from the 15th to the 45th day under the 300 kg N ha-1 treatment were observed, subsequently leading to increases in both the tuber yield and NUE. Moreover, a maximum average tuber filling rate was obtained under the N300 treatment. These improvements led to substantial increases in the tuber yield (32.1-35.5%), nitrogen agronomic efficiency (NAE, 2.1-5.3%), nitrogen partial factor productivity (NPP, 4.8-8.1%), and nitrogen recovery efficiency (NRE, 3.4-5.7%). Consequently, 300 kg N ha-1 of N fertilizers is the most effective dose for optimizing both the yield of tiger nut tubers and the NUE of tiger nut plants in marginal soils. Structural equation modeling reveals that N application affects the yield and NUE through its effects on leaf functional traits, the CAP, and the tuber filling characteristics. Modeling indicates that tuber expansion characteristics primarily impact the yield, while CAP predominantly governs the NUE. Above all, this study highlights the crucial role of N fertilizer in maximizing the tiger nut tuber yield potential on marginal lands, providing valuable insights into sustainable farming in dry areas.

Diversity Levels under Different Grazing Intensities in Semi-Wet Grasslands

The biodiversity of grasslands has been shaped by long-time interaction between natural processes and human activities, such as grazing. Traditional grazing management by animals contributes to the maintenance of high biodiversity in grasslands. However, changes in land use in recent years such as the abandonment of animal husbandry or intensification of grazing, pose a threat to grasslands biodiversity. The aim of the present study was to investigate the compositional and functional diversity in semi-humid grasslands of northern Greece under different grazing intensities. Three sites with similar vegetation and composition but different grazing intensities were selected in Taxiarchis University Forest of Mountain Holomontas. The three grazing intensities were (1) ungrazed, for more than 40 years, (2) moderate grazed, and (3) highly grazed. The ungrazed area showed an increase in vegetation cover and a decrease in bare ground. In comparison to grazed areas, the ungrazed one showed lower levels of grasses and legumes but higher abundances of woody and broad-leaved species. The highest values of all the studied diversity indices (Shannon–Wiener (H), Simpson Diversity Index, Jaccard, and species abundance) were recorded at moderate grazing intensity. Differences were recorded between the grazed and ungrazed areas in all of the quantitative traits (specific leaf area, leaf dry matter content, stem dry matter content, vegetative and reproductive plant height, leaf nitrogen, and phosphorus concentration). Protecting sensitive mountainous grasslands from both overgrazing and abandonment requires a balanced and sustainable management approach.

Shade tree trait diversity and functions in agroforestry systems: A review of which traits matter

Abstract Shade trees in agroforestry systems confer ecosystem services, such as enhanced soil fertility from diverse litter inputs, microclimate regulation via shade, and disease mitigation through trophic and abiotic interactions. With this thriving role of agroforestry in sustainable agriculture, particularly for tree crops, systematic and reliable methods to select shade trees for specific agroecosystem outcomes are crucial. Plant functional traits offer a framework to describe, select and manage shade trees. Over the last decade, shade tree leaf functional traits and whole plant traits have been assessed in agroforestry systems. Yet, we lack amalgamated information on (i) what we know about shade tree trait relationships with functions to achieve desired agroecosystem outcomes, (ii) how decades of shade tree selection by farmers impacts agroforests inter‐ and intraspecific trait diversity, and (iii) which shade tree traits should be considered for achieving farmer priorities. We consolidate literature on Coffea arabica (coffee) and Theobroma cacao (cocoa) agroforestry systems to summarize the role of shade tree functional traits in three key ecosystem functions: soil fertility, microclimate modification and crop productivity. We compile global and regional datasets on tree functional trait diversity to show the functional space of agroforestry tree species compared with the overall functional space observed in plants. Despite, or maybe because of, high shade tree diversity, shade tree trait characterization remains coarse and commonly measured at the community scale in the literature. Based on published trait data, we show that farmers adjust the functional composition of shade trees to increase the recycling of soil nutrients (high leaf nitrogen), the production of wood (skewing towards lower wood densities) and the production of fruits (tendency towards high seed size). Common shade trees in coffee and cocoa systems fall in the mid‐range of leaf acquisitive to conservative strategies, providing evidence that expanding shade tree portfolios can improve, or even accelerate, functions. Synthesis and applications: Based on the agroforestry literature and on trait‐environment relationships, we propose a matrix of shade tree traits that influence desirable agroecosystem outcomes for farmers, which can guide fine‐scale coordination of trait expression and agroforestry functions.

Tree diversity reduces variability in sapling survival under drought

Abstract Enhancing tree diversity may be important to fostering resilience to drought‐related climate extremes. So far, little attention has been given to whether tree diversity can increase the survival of trees and reduce its variability in young forest plantations. We conducted an analysis of seedling and sapling survival from 34 globally distributed tree diversity experiments (363,167 trees, 168 species, 3744 plots, 7 biomes) to answer two questions: (1) Do drought and tree diversity alter the mean and variability in plot‐level tree survival, with higher and less variable survival as diversity increases? and (2) Do species that survive poorly in monocultures survive better in mixtures and do specific functional traits explain monoculture survival? Tree species richness reduced variability in plot‐level survival, while functional diversity (Rao's Q entropy) increased survival and also reduced its variability. Importantly, the reduction in survival variability became stronger as drought severity increased. We found that species with low survival in monocultures survived comparatively better in mixtures when under drought. Species survival in monoculture was positively associated with drought resistance (indicated by hydraulic traits such as turgor loss point), plant height and conservative resource‐acquisition traits (e.g. low leaf nitrogen concentration and small leaf size). Synthesis. The findings highlight: (1) The effectiveness of tree diversity for decreasing the variability in seedling and sapling survival under drought; and (2) the importance of drought resistance and associated traits to explain altered tree species survival in response to tree diversity and drought. From an ecological perspective, we recommend mixing be considered to stabilize tree survival, particularly when functionally diverse forests with drought‐resistant species also promote high survival of drought‐sensitive species.

Integrating UAV hyperspectral data and radiative transfer model simulation to quantitatively estimate maize leaf and canopy nitrogen content

Crop nitrogen (N) content reflects crop nutrient status and plays an important role in precision nutrient management. Accurate crop N content estimation from remote sensing has been well documented. However, the robustness (i.e., the ability of a model to perform consistently across various conditions) of these methods under varied soil conditions or different growth stages has rarely been considered. We proposed a hybrid method that integrates in-situ measurements and the data simulated by a mechanistic model to improve the estimation of maize N content. In-situ data included hyperspectral images collected by Unmanned Aerial Vehicle (UAV), and leaf and canopy N content (LNC and CNC). A mechanistic radiative transfer model (PROSAIL-PRO) was used to generate simulated data, i.e., canopy reflectance paired with target crop traits (i.e., LNC, CNC). We compared the performance from the hybrid method with a machine learning method (Gaussian Process Regression) and six different vegetation indices (VIs) on four in-situ datasets collected at three study sites from 2021 to 2022. Results show that the hybrid method consistently performed the best for LNC estimation across four testing datasets (RRMSE ranging from 10.08% to 10.84%). For CNC estimation, the hybrid method had the best estimation results on two out of the four testing datasets and performed comparably to the best method on the other two datasets (RRMSE ranging from 13.89% to 25.21%). Next, we assessed the estimation robustness of the hybrid method, the machine learning, and the best-VI by comparing the mean (µ) and standard deviation (σ) of RRMSE across diverse water and N treatments (condition #1) and different growth stages (condition #2). Among 16 total cases (two crop traits by four study sites by two conditions), the hybrid method had 11 cases of smallest µ and seven cases of smallest σ, outperforming the machine learning (0/16 for µ, 4/16 for σ) and the best-VI (5/16 for µ, 5/16 for σ). These results underscore the greater robustness of the hybrid method. This study highlights the potential of integrating in-situ measurements and simulated data to improve estimation accuracy and robustness for maize LNC and CNC. The promising performance of the hybrid method suggests its applicability to a broader range of crops and various crop traits.

Using the response–effect trait framework to disentangle the effects of environmental change on the ecosystem services

Abstract Functional traits play a vital role in mediating the responses of ecosystem services to environmental changes and in predicting the functioning of the ecosystem. However, the connection between functional traits and ecosystem services has become increasingly intricate due to climate change and human activities for degraded ecosystems. To investigate this relationship, we selected 27 sampling sites in the Yanhe River Basin of the Chinese Loess Plateau, each containing two types of vegetation ecosystems: natural vegetation and artificial vegetation ecosystems. At each sampling site, we measured ecosystem services and calculated the composition index of community traits. We established a response–effect trait framework that included environmental factors such as climate, elevation and human activities. Our results showed that leaf tissue density (LTD) was the overlapping response and effect trait when responding to climate change. LTD is positively correlated with mean annual temperature and negatively correlated with supporting services. Under the influence of human activities, leaf nitrogen content and leaf dry matter content were carriers of environmental change. Comparing the two vegetation ecosystems, the relationship between functional traits and ecosystem services showed divergent patterns, indicating that human activities increased the uncertainty of the relationship between functional traits and ecosystem services. Trait-based ecology holds promise for enhancing predictions of ecosystem services responses to environmental changes. However, the predictive ability is influenced by the complexity of environmental changes. In conclusion, our study highlights the importance of understanding the complex connection between functional traits and ecosystem services in response to climate changes and human activities.

Effects of plant leaf traits, abundance and phylogeny on differentiation of herbivorous insect assemblages in Mediterranean mixed forest

AbstractHerbivorous insect assemblages are functionally diverse, with each species exploiting plant tissues in different ways. Availability and palatability of plant tissues influence the diversity and composition of herbivorous insect assemblages. However, few studies have compared herbivorous insect assemblages and their ecological correlates across multiple plant species within the same plant community. Here, we sampled insect assemblages from the canopies of 1060 plants belonging to 36 woody species in two mixed Mediterranean forest stands. 401 insect species were classified as herbivores and grouped into sucker or chewer guilds. We explored differences in the diversity and composition of each insect guild across plant species, and tested their relationships with plant leaf traits, abundance or phylogeny, and explored whether the structures of plant-herbivorous insect networks depended on any of the studied plant traits. Plant identity accounted for the highest proportion of variation in the composition of each insect guild. Plant species abundance showed a positive effect on both insect guilds’ diversity. Suckers’ diversity was higher in plant species with deciduous leaves and low SLA, while the composition was more similar between phylogenetically closer plant species. Chewers diversity increased with the leaf area, while plants with similar LA, leaf nitrogen, SLA and distinct leaf habit showed more similar assemblages. Similarly, closely related angiosperms showed similar chewer assemblages. Plant–insect interaction networks present a modular structure, in which plants belonging to the same module tend to be related and share more sucker species. We add to the evidence supporting the role of plant species features as filters for structuring their associated herbivore insect assemblages.

Decoupling of nitrogen allocation and energy partitioning in rice after flowering.

Estimation of energy partitioning at leaf scale, such as fluorescence yield (ΦF) and photochemical yield (ΦP), is crucial to tracking vegetation gross primary productivity (GPP) at global scale. Nitrogen is an important participant in the process of light capture, electron transfer, and carboxylation in vegetation photosynthesis. However, the quantitative relationship between leaf nitrogen allocation and leaf energy partitioning remains unexplored. Here, a field experiment was established to explore growth stage variations in energy partitioning and nitrogen allocation at leaf scale using active fluorescence detection and photosynthetic gas exchange method in rice in the subtropical region of China. We observed a strongly positive correlation between the investment proportion of leaf nitrogen in photosynthetic system and ΦF during the vegetative growth stage. There were significant differences in leaf energy partitioning, leaf nitrogen allocation, and the relationship between ΦF and ΦP before and after flowering. Furthermore, flowering weakened the correlation between the investment proportion of leaf nitrogen in photosynthetic system and ΦF. These findings highlight the crucial role of phenological factors in exploring seasonal photosynthetic dynamics and carbon fixation of ecosystems.

Sex-specific scaling of leaf phosphorus vs. nitrogen under unequal reproductive requirements in Eurya japonica, a dioecious plant.

Previous work searching for sexual dimorphism has largely relied on the comparison of trait mean vectors between sexes in dioecious plants. Whether trait scaling (i.e., the ratio of proportional changes in covarying traits) differs between sexes, along with its functional significance, remains unclear. We measured 10 vegetative traits pertaining to carbon, water, and nutrient economics across 337 individuals (157 males and 180 females) of the diocious species Eurya japonica during the fruiting season in eastern China. Piecewise structural equation modeling was employed to reveal the scaling relationships of multiple interacting traits, and multivariate analysis of (co)variance was conducted to test for intersexual differences. There was no sexual dimorphism in terms of trait mean vectors across the 10 vegetative traits in E. japonica. Moreover, most relationships for covarying trait pairs (17 out of 19) exhibited common scaling slopes between sexes. However, the scaling slopes for leaf phosphorus (P) vs. nitrogen (N) differed between sexes, with 5.6- and 3.0-fold increases of P coinciding with a 10-fold increase of N in male and female plants, respectively. The lower ratio of proportional changes in P vs. N for females likely reflects stronger P limitation for their vegetative growth, as they require greater P investments in fruiting. Therefore, P vs. N scaling can be a key avenue allowing for sex-specific strategic optimization under unequal reproductive requirements. This study uncovers a hidden aspect of secondary sex character in dioecious plants, and highlights the use of trait scaling to understand sex-defined economic strategies.

Heterotic growth of hybrids of Arabidopsis thaliana is enhanced by elevated atmospheric CO2.

With the global atmospheric CO2 concentration on the rise, developing crops that can thrive in elevated CO2 has become paramount. We investigated the potential of hybridization as a strategy for creating crops with improved growth in predicted elevated atmospheric CO2. We grew parent accessions and their F1 hybrids of Arabidopsis thaliana in ambient and elevated atmospheric CO2 and analyzed numerous growth traits to assess their productivity and underlying mechanisms. The heterotic increase in total dry mass, relative growth rate and leaf net assimilation rate was significantly greater in elevated CO2 than in ambient CO2. The CO2 response of net assimilation rate was positively correlated with the CO2 response of leaf nitrogen productivity and with that of leaf traits such as leaf size and thickness, suggesting that hybridization-induced changes in leaf traits greatly affected the improved performance in elevated CO2. Vegetative growth of hybrids seems to be enhanced in elevated CO2 due to improved photosynthetic nitrogen-use efficiency compared with parents. The results suggest that hybrid crops should be well-suited for future conditions, but hybrid weeds may also be more competitive.

Precipitation change, functional traits and stand structure jointly control the spatiotemporal variability of radial growth in alpine treeline ecotones across northern China

Tree growth and survival at alpine (arctic) treelines are generally limited by temperature, but it is increasingly observed that hotter drought is threatening tree growth at treelines. How treeline growth variability in response to climate change varies at broad scale, and how it is jointly modulated by functional traits, stand structure and climate factors remains unclear. We sampled tree-ring cores from 11 treeline sites along longitude (precipitation) gradients across northern China, and examined two new aspects of radial growth response to climate change: temporal growth variability and spatial growth synchrony. We explored how climate conditions, climate trends and temporal variability, functional traits [specific leaf area (SLA), leaf nitrogen concentration (LN)], and stand factors affect growth variability and synchrony, and assessed the major drivers with mixed-effects models. 1) Contrary to our expectation, growth variability decreased from humid to arid regions. This pattern was partly because water availability increased in the west (arid) while decreased in the east (humid) regions since 1950. 2) Hotter drought and higher climate variability led to higher growth variability and synchrony. 3) Species with fast-growing strategies (higher SLA and LN) showed higher growth variability and synchrony due to experiencing drastic hotter drought and having lower drought tolerance. 4) Taller and denser stands revealed higher growth variability and synchrony due to stronger hydraulic limitation and competition, respectively. 5) Functional traits and stand factors are indispensable modulators of growth spatiotemporal variability even at broad scales, because their variable importance was often higher than climate factors. These results caution against predicting forest vulnerability solely from climate factors. We conclude that forests at many treeline sites were threatened by hotter drought, especially in humid regions of northern China. But the importance of stand factors and functional traits found also suggests forest management as an effective way to alleviate climate change vulnerability.