Trade-offs among different plant functional traits reflect the different strategies of plants in resource acquisition and allocation and have been a hot topic in ecological research in recent years. Starting from research scales, leaf traits, organs, and plant groups, this review briefly introduces how the study of trait relationships has gradually expanded and deepened based on the leaf economic spectrum (LES) in recent decades. 1) Relevant studies have been focused on the species living in extremely harsh environments. LES is relatively stable along environmental gradients studied. Both intra- and inter-specific leaf trait relationships are similar. 2) Leaf decomposition rate and flammability are significantly related to the morphological traits and nutrient contents. The relationship between leaf economic traits and hydraulic traits depends on environmental water availability. 3) Leaf mass per area is coupled with wood density and seed size. However, the morphological traits of leaf are not related to relevant traits of root and flower, indicating that these organs may have evolved independently. 4) LES can well explain the growth/survival strategies of some special vascular plants: invasive plants have relatively high resource use efficiencies and fast relative growth rates, locating on the “low investment-quick returns” end in LES. In contrast, the leaves of the carnivorous plants are capable of catching prey, but have relatively low photosynthetic and growth rates, distributing on the other end of LES. Besides, LES pertains to not only the oldest seed plant cycads but also ferns and poikilohydric plants (bryophytes and lichens). This review summarizes the research progress of this topic and presents some suggestions, hoping to provide some new insights for future studies.

Forests are large and persistent carbon (C) sink mainly through the C sequestration of tree growth, which can mitigate the rising rate of CO₂ concentration in the atmosphere. According to C availability in trees, two mechanisms involved in controlling tree growth are attributed to limitations to C input and C utilities. Since many environmental factors influence the activities of C-source and C-sink of trees interdependently, it is difficult to quantify how the sensitivity of C-source or C-sink activity to environmental changes affects tree growth. Therefore, it is of significance to understand physiological mechanisms underlying potential limitations to tree growth in order to predict tree growth and forest C sink under global change scenarios. In this review, the debates on the C-source and C-sink limitations to tree growth were firstly introduced. Second, we discussed responses of tree growth to biotic and abiotic stresses, such as defoliation, drought and low temperature from the perspective of C-source/sink limitations. Finally, we proposed three priorities for future studies in this field: (1) to explore the regulating mechanisms on the allocation of non-structural carbohydrates (NSC) in trees, and to determine what conditions and what extent trees actively allocate the photosynthates to NSC storage at the expense of growth; (2) to strengthen studies on the tree C-sink, and determine the photosynthates allocated to all components of tree C-sink, especially the missing C-sinks such as the activities of roots and related microorganisms; and (3) to implement studies on interactions among C metabolism, mineral nutrition and hydraulics physiology, and fully understand the C-water-nutrient coupling and its effects on tree growth.

Aims The leaf stoichiometry and potential driving factors play a vital role in understanding the distribution patterns of plant community and predicting the plant responses to environmental changes. In this study, we aimed to investigate the spatial distribution patterns and driving factors of leaf carbon (C), nitrogen (N) and phosphorus (P) stoichiometry of coniferous species on the eastern Qinghai-Xizang Plateau, China.
Methods We collected leaf and soil samples from 29 coniferous tree species at 84 sampling sites on the eastern Qinghai-Xizang Plateau. Linear fitting was used to analyze the variation patterns of leaf stoichiometry along geographical and climatic gradients. Partial redundancy analysis was used to characterize the relative contributions of climate and soil factors to leaf stoichiometry variation patterns.
Important findings (1) At the level of family and genus, C and N concentrations as well as C:N of leaves were significantly different across distinct conifer species. The leaf N:P was less than 14, indicating that conifer species in the study region were mainly N-limited. (2) Leaf N and P concentrations showed a consistent distribution pattern along environmental gradients. Specifically, N and P concentrations of leaves were significantly decreased with elevated latitude and altitude, while remarkably increased with the increase of mean annual temperature (MAT) and mean annual precipitation (MAP). In comparison, leaf C concentration had no significant correlation with latitude, altitude, MAT or MAP. (3) The leaf C:N and C:P showed an opposite distribution pattern with leaf N and P concentrations, which significantly increased with elevated latitude and altitude, while markedly declined with the increase of MAT and MAP. Leaf N:P had no significant correlation with altitude, MAT or MAP. (4) The main driving factors of leaf C, N, P concentrations and their stoichiometric characteristics were different. Specifically, soil properties were the main driving factors accounting for the variations of leaf C concentration and N:P. The variations of leaf N and P concentrations as well as ratios of C:N and C:P were primarily explained by climatic factors. Collectively, variations of leaf stoichiometry of coniferous species along environmental gradients in the study region provided a compelling support for the Temperature Biogeochemistry Hypothesis. These findings largely improved the understanding of the distribution patterns and driving mechanism of leaf stoichiometry under changing environments.

Aims We aim to compare the climatic representativeness of blue intensity (BI) and ring width index (RWI) in Picea jezoensis, and to provide guidance for the further application of BI parameters in dendrochronology.
Methods A total of 120 tree-ring cores were extracted from P. jezoensis trees in the Laobai Mountain of Jilin Province. Using the methods of the growth-climate response function analysis and moving correlation analysis, the differences in the responses of BI and RWI to climate change in P. jezoensis along an elevational gradient (namely 900, 1 200 and 1 500 m) were investigated.
Important findings The BI (or RWI) in P. jezoensis trees at the three elevations had similar responses to climate. BI was predominantly and positively correlated with temperature, while RWI was predominantly and negatively correlated with temperature. BI was positively correlated with the maximum temperature in summer and growing season. RWI at the low or medium elevations was significantly and negatively correlated with the annual minimum and mean temperatures and the minimum temperature in growing season. BI was negatively correlated with the SPEI in summer, while RWI was weakly or positively correlated with SPEI in summer. This almost inverse growth-climate relationships by BI and RWI may reflect the trade-off between earlywood and latewood. BI and RWI in P. jezoensis in the study area may infer different climate signals. On the spatial scale, the responses of BI to summer precipitation, maximum temperature and SPEI were better than the traditional RWI. The temporal stability of the correlation of BI with main climatic factors was better than that of RWI. Therefore, BI has some potential application in studies of dendroclimatology.

Aims Orchid plants generally grow better when they are mycorrhizal since mycorrhizal fungi are likely to assist in orchid seeds’ germination. However, there is little quantitative work on it. Thus we hope to better understand this mechanism to benefit the orchid plants protection.
Methods We studied nine small population species of orchids grown in Liaoning Province, China. We analyzed the composition of orchid mycorrhizal fungi (OMF) and fungal communities in the roots, in the rhizosphere soil as well as bulk soil, by taking advantage of the next generation sequencing technology.
Important findings Our study showed that there was a significant difference in fungal communities among in the roots, the rhizosphere soil and the bulk soil, especially in the total operational taxonomic unit (OTU) number. Although the OTU number was far smaller in the roots than in the rhizosphere soil and bulk soil, the species and abundances of OMF were less relative to each other. FunGuild, an indicator to predict the functional fungi, indicated that Arbuscular Mycorrhizal fungi were abundence in the rhizosphere while were rare in the roots of orchids. In general, the fungal communities in the roots were not tightly correlated with that in the root-associated soil.

Aims Our objectives were to investigate the soil phosphorus (P) stocks and distribution patterns in forests of Qinghai Province, and to determine the relationships between soil phosphorus stocks and environmental factors.
Methods Phosphorus stocks in forest soils of Qinghai Province were estimated from measurement data of 240 standard sampling plots in combination with the forest type information in the Qinghai Forest Resources Inventory data. The distribution patterns were examined by spatial analysis.
Important findings Forest soil P stocks in Qinghai Province is estimated at 1.74 Tg. The average soil P density to 1 m depth is about 4.65 Mg·hm ^-2, displaying of pattern of zonal distribution. Soil P density significantly decreases first and then increases with altitude, and is largest in Cinnamon forest soils and less in brown forest soils and dark cinnamon forest soils. Soil P content decreases significantly with altitude. The P content was highest in brown forest soils and lowest in dark cinnamon soils. Total P in the soil profile exhibited characteristics of surface accumulation. The structure equation model (SEM) shows that soil type, altitude, temperature, and soil moisture content have direct impacts on soil P content, with temperature and altitude being among the key factors. Soil P content, altitude, soil moisture content, soil depth, and soil bulk density all have significant effects on soil P density, with soil bulk density being the most prominent factor.