Impact of growth temperature on scaling relationships linking photosynthetic metabolism to leaf functional traits

Leaf Functional Traits and Their Influencing Factors in Six Typical Vegetation Communities

Leaf functional traits (LFTs) have become a popular topic in ecological research in recent years. Here, we measured eight LFTs, namely leaf area (LA), specific leaf area (SLA), leaf thickness (LT), leaf dry matter content (LDMC), leaf carbon content (LCC), leaf nitrogen content (LNC), leaf phosphorus content (LPC), and leaf potassium content (LKC), in six typical vegetation communities (sclerophyllous evergreen broad-leaved forests, temperate evergreen coniferous forests, cold-temperate evergreen coniferous forests, alpine deciduous broad-leaved shrubs, alpine meadows, and alpine scree sparse vegetation) in the Chayu River Basin, southeastern Qinghai-Tibet Plateau. Our aim was to explore their relationships with evolutionary history and environmental factors by combining the RLQ and the fourth-corner method, and the method of testing phylogenetic signal. The results showed that (i) there were significant differences in the eight LFTs among the six vegetation communities; (ii) the K values of the eight LFTs were less than 1; and (iii) except for LCC, all other LFTs were more sensitive to environmental changes. Among these traits, LA was the most affected by the environmental factors, followed by LNC. It showed that the LFTs in the study were minimally influenced by phylogenetic development but significantly by environmental changes. This study further verified the ecological adaptability of plants to changes in environmental factors and provides a scientific basis for predicting the distribution and diffusion direction of plants under global change conditions.

Testing a generalized leaf mass estimation method for diverse tree species and climates of the continental United States

Estimating tree leaf biomass can be challenging in applications where predictions for multiple tree species is required. This is especially evident where there is limited or no data available for some of the species of interest. Here we use an extensive national database of observations (61 species, 3628 trees) and formulate models of varying complexity, ranging from a simple model with diameter at breast height (DBH) as the only predictor to more complex models with up to 8 predictors (DBH, leaf longevity, live crown ratio, wood specific gravity, shade tolerance, mean annual temperature, and mean annual precipitation), to estimate tree leaf biomass for any species across the continental United States. The most complex with all eight predictors was the best and explained 74%-86% of the variation in leaf mass. Consideration was given to the difficulty of measuring all of these predictor variables for model application, but many are easily obtained or already widely collected. Because most of the model variables are independent of species and key species-level variables are available from published values, our results show that leaf biomass can be estimated for new species not included in the data used to fit the model. The latter assertion was evaluated using a novel "leave-one-species-out" cross-validation approach, which showed that our chosen model performs similarly for species used to calibrate the model, as well as those not used to develop it. The models exhibited a strong bias toward overestimation for a relatively small subset of the trees. Despite these limitations, the models presented here can provide leaf biomass estimates for multiple species over large spatial scales and can be applied to new species or species with limited leaf biomass data available.

Estimation model and its trade-off strategy of Mangifera persiciforma Colletotrichum gloeosporioides degree based on leaf reflection spectrum

Colletotrichum gloeosporioides is one of the most common and serious fungal diseases of the tree Mangifera persiciforma. Yet we lack an effective method to evaluate this ecological interaction accurately. Here, we measured the functional traits and leaf reflectance spectrum of the host plants under different disease degrees. The findings provide a fast and efficient method for large-scale and high-precision monitoring of C. gloeosporioides in M. persiciforma stands. Using the collected leaf reflection data, we set up a prediction model of the optimal disease degree. Firstly, we found that leaf functional traits of M. persiciforma generally consisted of low leaf thickness, low relative chlorophyll content, small specific leaf area, high leaf tissue density, high dry matter content, low stomatal density, and large stomatal area. Secondly, leaf reflectivity increases with damage of C. gloeosporioides, which corresponds to five main reflection peaks and five absorption valleys in the spectral reflectance curve of leaves at the same positions (350-1800 nm). Thirdly, with the increase of infection degree, red edge slope and yellow edge slope decrease, while green peak reflectance, red valley reflectance, and blue edge slope all increase. Blue shift was detected in the red edge, green peak, and red valley, while red shift appeared at the blue edge and yellow edge. Finally, the best predictive model was that based on green peak reflectance (y=3.6396-0.0693x, R²=0.5149, RMSE [root-mean-square error] =0.2735), with an R²=0.92 and RMSE=0.0042 between its predicted vs. observed values. Because of its high inversion accuracy, the model can be used to predict the invasion conditions of M. persiciforma by C. gloeosporioides. Our study demonstrated that when plants are infected by C. gloeosporioides, there was a strong trade-off relationship between leaf functional traits. On the global leaf economics spectrum, the leaves tended toward the "slow investment-return" end when infected by C. gloeosporioides.

The Changes of Leaf Reflectance Spectrum and Leaf Functional Traits of Osmanthus fragrans Are Related to the Parasitism of Cuscuta japonica

Studies on the influence of parasitism on plants based on hyperspectral analysis have not been reported so far. To fully understand the variation characteristics and laws of leaf reflectance spectrum and functional traits after the urban plant parasitized by Cuscuta japonica Choisy. Osmanthus fragrans (Thunb.) Lour. was taken as the research object to analyze the spectral reflectance and functional traits characteristics at different parasitical stages. Results showed that the spectral reflectance was higher than those being parasitized in the visible and near-infrared range. The spectral reflectance in 750~1400 nm was the sensitive range of spectral response of host plant to parasitic infection, which is universal at different parasitic stages. We established a chlorophyll inversion model (y = −65913.323x + 9.783, R2 = 0.6888) based on the reflectance of red valley, which can be used for chlorophyll content of the parasitic Osmanthus fragrans. There was a significant correlation between spectral parameters and chlorophyll content index. Through the change of spectral parameters, we can predict the chlorophyll content of Osmanthus fragrans under different parasitic degrees. After being parasitized, the leaf functional traits of host plant were generally characterized by large leaf thickness, small leaf area, small specific leaf area, low relative chlorophyll content, high leaf dry matter content and high leaf tissue density. These findings indicate that the host plant have adopted a certain trade-off strategy to maintain their growth in the invasion environment of parasitic plants. Therefore, we suspect that the leaf economics spectrum may also exist in the parasitic environment, and there was a general trend toward the “slow investment-return” type in the global leaf economics spectrum.

Convergence of ecophysiological traits drives floristic composition of early lineage vascular plants in a tropical forest floor

BACKGROUND AND AIMS

Tropical understorey plant communities are highly diverse and characterized by variable resource availability, especially light. Plants in these competitive environments must carefully partition resources to ensure ecological and evolutionary success. One mechanism of effective resource partitioning is the optimization of functional traits to enhance competition in highly heterogeneous habitats. Here, we surveyed the ecophysiology of two early lineage vascular plant groups from a tropical forest understorey: Selaginella (a diverse lineage of lycophytes) and ferns.

METHODS

In a lowland rain forest in Costa Rica, we measured a suite of functional traits from seven species of Selaginella and six fern species. We evaluated species microclimate and habitat; several photosynthetic parameters; carbon, nitrogen and phosphorus content; chlorophyll concentration; leaf mass per area (LMA); and stomatal size and density. We then compare these two plant lineages and search for relationships between key functional parameters that already exist on a global scale for angiosperms.

KEY RESULTS

Convergence of trait function filtered Selaginella species into different habitats, with species in heavily shaded environments having higher chlorophyll concentrations and lower light compensation points compared with open habitats. Alternatively, lower foliar nitrogen and higher stomatal densities were detected in species occupying these open habitats. Selaginella species had denser and smaller stomata, lower LMA and lower foliar nutrient content than ferns, revealing how these plant groups optimize ecophysiological function differently in tropical forest floors.

CONCLUSIONS

Our findings add key pieces of missing evidence to global explorations of trait patterns that define vascular plant form and function, which largely focus on seed plants. Broadly predictable functional trait relationships were detected across both Selaginella and ferns, similar to those of seed plants. However, evolutionary canalization of microphyll leaf development appears to have driven contrasting, yet successful, ecophysiological strategies for two coexisting lineages of extant homosporous vascular plants.

Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix olgensis Henry Trees

Numerical integration of the instantaneous net photosynthetic rate (An) is a common method for calculating the long-term CO2 uptake of trees, and accurate dynamic simulation of the crown An has been receiving substantial attention. Tree characteristics are challenging to assess given their aerodynamically coarse crown properties, spatiotemporal variation in leaf functional traits and microenvironments. Therefore, the variables associated with the dynamic variations in the crown An must be identified. The relationships of leaf temperature (Tleaf), the vapor pressure deficit (VPD), leaf mass per area (LMA) and the relative depth into the crown (RDINC) with the parameters of the photosynthetic light-response (PLR) model of Larix olgensis Henry were analyzed. The LMA, RDINC and VPD were highly correlated with the maximum net photosynthetic rate (Amax). The VPD was the key variable that mainly determined the variation in the apparent quantum yield (AQY). Tleaf exhibited a significant exponential correlation with the dark respiration rate (Rd). According to the above correlations, the crown PLR model of L. olgensis trees was constructed by linking VPD, LMA and RDINC to the original PLR equation. The model performed well, with a high coefficient of determination (R2) value (0.883) and low root mean square error (RMSE) value (1.440 μmol m−2 s−1). The extinction coefficient (k) of different pseudowhorls within a crown was calculated by the Beer–Lambert equation based on the observed photosynthetically active radiation (PAR) distribution. The results showed that k was not a constant value but varied with the RDINC, solar elevation angle (ψ) and cumulative leaf area of the whole crown (CLA). Thus, we constructed a k model by reparameterizing the power function of RDINC with the ψ and CLA, and the PAR distribution within a crown was therefore well estimated (R2 = 0.698 and RMSE = 174.4 μmol m−2 s−1). Dynamic simulation of the crown An for L. olgensis trees was achieved by combining the crown PLR model and dynamic PAR distribution model. Although the models showed some weakened physiological biochemical processes during photosynthesis, they enabled the estimation of long-term CO2 uptake for an L. olgensis plantation, and the results could be easily fitted to gas-exchange measurements.

Trans-species predictors of tree leaf mass

Tree leaf mass is a small, highly variable, but critical, component of forest ecosystems. Estimating leaf mass on standing trees with models is challenging because leaf mass varies both within and between tree species and at different locations and points in time. Typically, models for estimating tree leaf mass are species specific, empirical models that predict intraspecific variation from stem diameter at breast height (dbh). Such models are highly limited in their application because there are many other factors beyond tree girth and species that cause leaf mass to vary and because such models provide no way to predict leaf mass for species for which data are not available. We conducted destructive sampling of 17 different species in Michigan, covering multiple life history traits and sizes, to investigate the potential for using a single, "trans-species" model for predicting leaf mass for all the trees in our study. Our results show the most important predictors of tree leaf mass are dbh, five-year basal area increment, crown class, and competition index, none of which are species specific. Species-specific variation could be captured by leaf longevity and shade tolerance. Wood specific gravity was a statistically significant, but marginally important predictor. Together, these variables describing tree size, life-history traits, and competitive environment allowed us to develop a generalized leaf mass model applicable to a diverse set of species, without having to develop species-specific equations.

Biological limits on nitrogen use for plant photosynthesis: a quantitative revision comparing cultivated and wild species

The relationship between leaf photosynthesis and nitrogen is a critical production function for ecosystem functioning. Cultivated species have been studied in terms of this relationship, focusing on improving nitrogen (N) use, while wild species have been studied to evaluate leaf evolutionary patterns. A comprehensive comparison of cultivated vs wild species for this relevant function is currently lacking. We hypothesize that cultivated species show increased carbon assimilation per unit leaf N area compared with wild species as associated with artificial selection for resource-acquisition traits. We compiled published data on light-saturated photosynthesis (A_max ) and leaf nitrogen (LN_area ) for cultivated and wild species. The relationship between A_max and LN_area was evaluated using a frontier analysis (90^th percentile) to benchmark the biological limit of nitrogen use for photosynthesis. Carbon assimilation in relation to leaf N was not consistently higher in cultivated species; out of 14 cultivated species, only wheat, rice, maize and sorghum showed higher ability to use N for photosynthesis compared with wild species. Results indicate that cultivated species have not surpassed the biological limit on nitrogen use observed for wild species. Future increases in photosynthesis based on natural variation need to be assisted by bioengineering of key enzymes to increase crop productivity.

Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasting adaptive strategies

How genetic factors control plant performance under stressful environmental conditions is a central question in ecology and for crop breeding. A multivariate framework was developed to examine the genetic architecture of performance-related traits in response to interacting environmental stresses. Ecophysiological and life history traits were quantified in the Arabidopsis thaliana Ler × Cvi mapping population exposed to constant soil water deficit and high air temperature. The plasticity of the genetic variance-covariance matrix (G-matrix) was examined using mixed-effects models after regression into principal components. Quantitative trait locus (QTL) analysis was performed on the predictors of genotype effects and genotype by environment interactions (G × E). Three QTLs previously identified for flowering time had antagonistic G × E effects on carbon acquisition and the other traits (phenology, growth, leaf morphology, and transpiration). This resulted in a size-dependent response of water use efficiency (WUE) to high temperature but not soil water deficit, indicating that most of the plasticity of carbon acquisition and WUE to temperature is controlled by the loci that control variation of development, size, growth, and transpiration. A fourth QTL, MSAT2.22, controlled the response of carbon acquisition to specific combinations of watering and temperature irrespective of plant size and development, growth, and transpiration rate, which resulted in size-independent plasticity of WUE. These findings highlight how the strategies to optimize plant performance may differ in response to water deficit and high temperature (or their combination), and how different G × E effects could be targeted to improve plant tolerance to these stresses.

Temperature responses of developmental processes have not been affected by breeding in different ecological areas for 17 crop species

• Rates of tissue expansion, cell division and progression in the plant cycle are driven by temperature, following common Arrhenius-type response curves. • We analysed the genetic variability of this response in the range 6-37°C in seven to nine lines of maize (Zea mays), rice (Oryza spp.) and wheat (Triticum aestivum) and in 18 species (17 crop species, different genotypes) via the meta-analysis of 72 literature references. • Lines with tropical or north-temperate origins had common response curves over the whole range of temperature. Conversely, appreciable differences in response curves, including optimum temperatures, were observed between species growing in temperate and tropical areas. • Therefore, centuries of crop breeding have not impacted on the response of development to short-term changes in temperature, whereas evolution over millions of years has. This slow evolution may be a result of the need for a synchronous shift in the temperature response of all developmental processes, otherwise plants will not be viable. Other possibilities are discussed. This result has important consequences for the breeding and modelling of temperature effects associated with global changes.