An ecological regionalization system was developed for the arid lands of northwestern China based on ecological and environmental factors, including climate, large-scale terrain features, landform, geology, vegetation, and soils, in combination with characteristics of social and economic development. The region was stratified into discrete geographical units of uniformity at three levels: Level I, the ecodomain, was based on climate and large-scale terrain features with consideration of the role of higher levels of regionalization and industrial development; Level II, the ecoregion, was based primarily on secondary landform, topography and large-scale vegetation types; and, Level III, the ecodistrict, was based on differences in local vegetation due to differences in geology and soils, as well as its eco-productive paradigm and potential future development. Based on this three-class system, we defined three ecodomains, 23 ecoregions and 80 ecodistricts. An ecoregional map of northwestern arid lands of China was drawn at 1∶1 million scale using GIS. The goals of the ecological regionalization classification were not only to develop a unique system of arid land ecological classification, but also to supervise local development and land use management to promote sustainable development of arid lands in northwestern China.

Plant traits link environmental factors, individuals and ecosystem structure and functions as plants respond and adapt to the environment. This review introduces worldwide classification schemes of plant functional traits and summarizes research on the relationships between plant functional traits and environmental factors such as climate (e.g., temperature, precipitation and light), geographical variation (e.g., topography, ecological gradients and altitude), nutrients and disturbance (including fire, grazing, invasion and land use), as well as between plant functional traits and ecosystem functions. We synthesize impacts of global change (e.g., climate change) on plant functional traits of individuals and plant communities. Research on plant functional traits is very fruitful, being applicable to research on global change, paleovegetation and paleoclimate reconstruction, environmental monitoring and assessment and vegetation conservation and restoration. However, further studies at large scale and including multi-environmental factors are needed and methods of measuring traits need to be improved. In the future, study of plant functional traits in China should be accelerated in a clear and systematic way.

Three photosynthetic pathways are used by plants: C₃, which most plants use, C₄ and crassulacean acid metabolism (CAM). C₃ is the ancestral pathway, with C₄ and CAM representing recently diverged forms. We conclude that the variation and evolution of photosynthetic pathway of C₃ and C₄ are adaptations to environmental stresses. First, we discuss the evolutional future of photosynthetic pathways. It has been suggested that low atmosphere CO₂, enhanced temperatures, drought and salinity are external drivers of C₄ photosynthetic evolution. Second, we analyze the possibility of evolution from C₃ to C₄. The polyphyletic evolution of the C₄ pathway suggests that the transition from C₃ to C₄ was relatively simple. This suggestion is supported by the observation that both C₃ and C₄ plants possess inherent plasticity in their photosynthetic characteristics. The stress causing the shift from C₃ to C₄ was involved in the environmental regulation of plants, and the C₄ pathway in C₃ plants evolved as an adaptation. The environmental stresses may have involved plant capacities for survivorship and competition in arid areas. Third, we present a simplistic model of the main phases of C₄ photosynthetic evolution and discuss the variation and evolution of C₃ and C₄ photosynthetic carbon assimilating pathways. Evolution was not directly to C₄ photosynthesis, so each step had to be stable, beginning with numerous preconditions needed for an evolutionary lineage to begin evolving C₄ characteristics. A current complication of C₄ photosynthetic evolution is global climate change and human manipulation of the biosphere. It is possible that C₄ photosynthesis can be used to resist adversity and increase the yield of C₃ crops. In conclusion, study of the evolution of photosynthetic pathway in plants provided insight into the photosynthetic physiology of plants under stress and provided new theory to reconstruct vegetation, enhance crop yield, and explain adaptation of C₃ species in arid areas.

Chlorates are a group of oxidizers with strong toxic effects that can cause significant damage to plants. However, chlorates have been used as a non-selective herbicide, defoliant and desiccant. It was found that potassium chlorate can induce flowering in longan (Dimocarpus longan). It has been widely used in longan orchards in recent years, especially in north Thailand and south China, but research has shown that potassium chlorate is toxic to organisms. It can also contaminate soil and water. The aim of this study was to determine the effects of potassium chlorate stress on the growth and physiological response of peanut (Arachis hypogaea).
The main method used to induce flower initiation in longan for off-season production is the application of potassium chlorate under the tree canopy. Most research efforts have been devoted to determining the optimum time and amount of application. Little is known about the phytotoxic effects of potassium chlorate on peanut plants, which usually is planted within longan orchards. In this paper, the effects of potassium chlorate on the growth of peanut plants were studied. Using the soil culture method, six potassium chlorate treatments were used to assess its effects on seed germination, chlorophyll content, levels of electrolytic leakage (EL), membrane permeability (MP), and activities of nitrate reductase (NR) and catalase (CAT) in peanut seedling leaves, as well as the biomass and number of Rhizobium, and the transpiration and photosynthetic rates in mature peanut plants. The results showed that: when the concentration of potassium chlorate was higher than 50 mg·L^-1, the germination rates of peanut seeds and root lengths were greatly reduced, while the amount of electrolytic leakage and the activity of CAT were increased significantly. When the concentration of potassium chlorate was higher than 50 mg·kg^-1 in soil, its phytotoxic effects resulted in a significant increase in MP in seedling leaves, and a decrease in NR, chlorophyll, biomass and the number of Rhizobium, and a reduction in transpiration and photosynthesis. It can be concluded that soil concentrations of potassium chlorate higher than 50 mg·kg^-1 would have a significantly negative effect on the growth of peanut plants.

Root exudates have specialized roles in nutrient cycling and signal transduction between a root system and soil, as well as in plant response to environmental stresses. They are the key regulators in rhizosphere communication, and can modify the biological and physical interactions between roots and soil organisms. Root exudates play important roles in biogeochemical cycle, regulation of rhizospheric ecological processes, and plant growth and development, and so on. Root exudates also serve roles in the plant-plant, plant-microbe, and microbe-microbe interactions. Plant allelopathy, intercropping system, bioremediation, and biological invasion are all the focal subjects in the field of contemporary agricultural ecology. They all involve the complex biological processes in rhizosphere. There are increasing evidences that various positive and negative plant-plant interactions within or among plant populations, such as allelopathy, consecutive monoculture problem, and interspecific facilitation in intercropping system, are all the results of the integrative effect of plant-microbe interactions mediated by root exudates. Recently, with the development of biotechnology, the methods and technologies relating to soil ecological research have achieved a remarkable progress. In particular, the breakthroughs of meta-omics technologies, including environmental metagenomics, metatranscriptomics, metaproteomics, and metabonomics, have largely enriched our knowledge of the soil biological world and the biodiversity and function diversity belowground. Research on plant-soil-microbe interactions mediated by root exudates has important implications for elucidating the functions of rhizosphere microecology and for providing practical guidelines. The concept and components of root exudates as well as the functions are reviewed in this paper. An overview on the root-bacteria, root-fungi, and root-fauna interactions is presented in detail. Methods to study root exudates and microbial communities are reviewed and the aspects needed to be further studied are also suggested.

Natural systems are essentially complex. In most cases, fully understanding natural systems requires the capacity to examine simultaneous influences and responses among multiple interacting factors. Compared with traditional multivariate methods, structural equation model (SEM) could specify the causal or dependent relationships among variables using the prior knowledge of researchers before conducting relevant experiments, i.e. initial models. SEM could not only identify the individual path coefficient for each relationship, but also estimate the whole model fit to determine whether to revise the initial models. We attempt to introduce SEM from the following aspects: definition and types of variables in SEM, detailed procedures for how to analyze data through SEM, some applications of SEM in ecology and recommended software. We encourage more researchers to apply SEM in ecological data analyses in order to improve understanding of natural systems and advance the field of ecology.

Microbiome is the combination of all microorganisms and their genetic information in a specific environment or ecosystem, which contains abundant microbial resources. A comprehensive and systematic analysis of the structure and function of microbiome will provide new ideas in solving the core issues in the fields of energy, ecological environment, industrial and agricultural production and human health. However, the study of microbiome largely depends on the development of relevant technologies and methods. Before to the advent of high-throughput sequencing technology, microbial research was mainly based on techniques such as isolation, pure-culture and fingerprint. However, due to the technical restrictions, scientists could only get limited knowledge of microorganisms. Since the beginning of 21st century, the revolutionary advances in the technology of high-throughput sequencing and mass spectrometry have greatly improved our understanding on the structure and ecological functions of environmental microbiome. However, the application of microbiomics technology in microbial research still faces many challenges. In addition, the descriptive studies focusing on the structure and diversity of microbiome have already matured, and the study of microbiomics is facing a critical transition period from quantity to quality and from structure to function. Hence, this paper will firstly introduce the basic concepts of microbiomics and a brief development history. Secondly, this paper introduces the related technologies and methods of microbiomics with their development process, and further expounds the applications and main problems of microbiomics technologies and methods in ecological study. Finally, this paper expounds the frontier direction of the development of microbiomics technology and methods from the technical, theoretical and application levels, and proposes the priority development areas of microbiome research in the future.

Aims Net primary productivity (NPP) is a key component of the terrestrial carbon cycle. Model simulation is commonly used to estimate regional and global NPP given difficulties to directly measure NPP at such spatial scales. A number of NPP models have been developed in recent years as research issues related to food security and biotic response to climatic warming have become more compelling. However, large uncertainties still exist because of the complexity of ecosystems and difficulties in determining some key model parameters.
Methods We developed an estimation model of NPP based on geographic information system (GIS) and remote sensing (RS) technology. The vegetation types and their classification accuracy are simultaneously introduced to the computation of some key vegetation parameters, such as the maximum value of normalized difference vegetation index (NDVI) for different vegetation types. This can remove some noise from the remote sensing data and the statistical errors of vegetation classification. It also provides a basis for the sensitivity analysis of NPP on the classification accuracy. The maximum light use efficiency (LUE) for some typical vegetation types in China is simulated using a modified least squares function based on NOAA/AVHRR remote sensing data and field-observed NPP data. The simulated values of LUE are greater than the value used in the CASA model and less than the values simulated with the BIOME-BGC model. The computation of the water restriction factor is driven with ground meteorological data and remote sensing data, and complex soil parameters are avoided. Results are compared with other studies and models.
Important findings The simulated mean NPP in Chinese terrestrial vegetation from 1989-1993 is 3.12 Pg C (1 Pg=10¹⁵ g). The simulated NPP is close to the observed NPP, and the total mean relative error is 4.5% for 690 NPP observation stations distributed in the whole country. This illustrates the utility of the model for the estimation of terrestrial primary production over regional scales.

Metabolomics is an important platform for studying stress in plants. We can qualify and quantify the metabolites of plants with environment stress using modern analytical techniques. The metabolomics data can be further studied by correlating with transcriptomics and genomics data. The combination of ‘omics’ platforms is an essential tool for systems analyses of plants to determine the mechanics of plant response to environment stress. We review recent studies of plant response to abiotic stress using metabolomics method and combination of different ‘omics’ platforms.

The light and CO₂ response curve of photosynthesis is an important tool to study plant physiology and plant ecology that can provide a scientific basis for the response of plant photosynthetic properties to environmental factors. This review considered the progress and potential weaknesses of light and CO₂ response models of photosynthesis and discussed research trends. Photosynthesis, which involves energy of light, absorption, energy conversion, electron transfer, ATP synthesis, CO₂ fixation etc., is a complex physical and chemical reaction process. It includes three basic steps: the primary reaction, the assimilatory power forms and the carbon assimilation, and each link may directly influence other processes. Classical models on photosynthetic light response only involve with light energy absorption, and biochemistry models do with the assimilatory power to form as well as carbon assimilation. A future direction of research of the mechanistic model of photosynthetic light response is the primary reaction of photosynthesis, namely participation the energy of light absorption, the transmission and the transformation of the harvesting light pigment member the physical parameter (e.g., the light-harvesting pigment molecules, light energy absorption cross-section of the harvesting pigment, the mean lifetime of the harvesting light pigment) unify in the biochemistry model.

Photosynthate allocation is influenced by both environmental and biological factors. This paper reviews recent advances in the mechanism of photosynthate allocation and its controls at individual and community/ecosystem levels in order to improve understanding of plant responses to global change. At the individual level, more photosynthate will be allocated to roots under conditions of high light, low water and low nutrient availabilities. The effect of increased atmospheric carbon dioxide concentration on photosynthate allocation depends on soil nitrogen availability. The root mass fraction (RMF) will increase under low nitrogen and is unchanged under high nitrogen. At the community/ecosystem levels, photosynthate allocation is insensitive to environmental change. The RMF decreases with increasing stand age. The functional equilibrium hypothesis (optimal partitioning) can explain the regulation of photosynthate allocation in response to environmental change, the source-sink relationship can reflect the effect of ontogeny on photosynthate allocation and the allometric relationship provides an important theoretical baseline prediction to disentangle the effects of plant size and environmental variation on photosynthate allocation. Research is needed on 1) the fraction of photosynthate allocated to respiration at the ecosystem level, 2) accurate estimation of belowground biomass and belowground net primary productivity (BNPP), 3) comparative study of photosynthate allocations between young and mature forests and between field and greenhouse experiments, 4) effects of multiple factors and their interactions on photosynthate allocation at the ecosystem level and 5) cooperative effects of ontogeny and environmental factors on the regulation of photosynthate allocation.

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.

Proteomics is one of the most active research fields in the post-genomic era. The concepts, research methods and major applications of proteomics in plant science are briefly introduced in this paper. The term “proteomics" comes from two words, “protein" and “genome" and refers to the proteins expressed by the whole genome or the presence and action modes of all the proteins in a cell, tissue, organ, and whole organism. It is generally acknowledged that the field of plant proteomics was based much on the development and improvement of techniques and methods, such as two-dimensional electrophoresis (2D-E), mass spectrometry (MS), protein chips, yeast two-hybrid system, and proteomic databases. In population genetics, proteomic techniques are helpful in studies of genetic diversity and mutation. In individual plants, proteomic studies are helpful in understanding the response of plants to biotic and abiotic environmental factors. Proteomic differences among different plant tissues or organs could be used to better understand tissue differentiation and development of the plant embryo. Proteomic differences also exist between organelles in plant cells, and plant proteomic studies could be used to understand mechanisms that control many physiological processes. Different perspectives of proteomics were also discussed in this paper.

Aims Our major objective was to reveal the distribution pattern of plant species diversity in the mountainous region of Ili River Valley, Xinjiang, China and explore how environmental gradients influenced the pattern.

Methods Based on a survey of 94 sample plots in the study area, DCCA was performed to analyze the relationships between diversity indices and environmental gradients and GAM was employed to model the response curve of diversity indices to elevation.

Important findings We recorded 259 plant species, including 235 herbaceous species; the species of woody plants were very limited. Communities with complex vertical structure had higher values of diversity. The distribution pattern of species diversity on the northern slope was affected by elevation, slope aspect, slope gradient, total nitrogen, total potassium, soil water content, organic matter, etc., and that on the southern slope was mainly affected by slope gradient, elevation, available phosphorus, soil water content, etc. On the northern slope, Patrick index and Shannon-Wiener index had a bimodal pattern with elevation and Simpson index and Pielou index showed a partially unimodal pattern. On the southern slope all the distribution pattern of species diversity indices showed two peaks, though that of the Patrick index was not obvious. These patterns were formed by the synthetic action of a variety of environmental factors in which elevation played an important role.

Aims Cropping practices and fertilizer/organic matter application affects the soil microbial growth and activity. In china, only few studies have been conducted on the influence of long-term fertilizer and organic matter with fertilizer application on the soil biological properties. Our objective was to study the changes in soil biological and biochemical characteristics under a long-term (15 years) field experiment involving fertility treatments (inorganic fertilizers and organic matter with fertilizers) and two crop rotation systems.
Methods In 1990, thirteen different treatments were established in the Drab Fluvo-aquic soil in Beijing for the long-term experiment. Six treatments were chosen in this study. Four were in a wheat-maize rotation receiving no fertilizer (CK), mineral fertilizers (NPK), mineral fertilizers plus farmyard manure (NPKM) and mineral fertilizers with maize straw incorporated (NPKS). One was in a wheat-maize/wheat-soybean rotation receiving NPK (NPKF). The other was abandoned arable land (CK0) growing weeds. The amount of chemical fertilizer per year was N 150 kg·hm^-2, P₂O₅ 75 kg·hm^-2, K₂O 45 kg·hm^-2, manure 22.5 Mg·hm^-2 and maize straw 2.25 Mg·hm^-2. Established methods were used to analyze soil enzymes and soil physical and chemical characteristics. Analysis was done using an integrative method combining correlation and component analyses in SPSS.
Important findings The soil organic C (SOC) and total N (STN) content, microbial biomass C (SMB-C) & N (SMB-N), activities of soil invertase, phosphatase and urease, and the ratio of SMB-C/SOC and SMB-N/STN were found higher in long-term (15 years) abandoned arable land than those in cultivated arable land soils. However, the soil metabolic quotient, pH value and bulk density of fallow soil were lower than those in cultivated arable land soils. The soil nutrient concentration, microbial biomass C & N, activities of soil invertase, phosphatase and urease, were higher in treatments with fertilizer application (NPK, NPKM, NPKS and NPKF) compared to no fertilizer application treatment (CK). The above soil parameters were also found higher in wheat-maize/wheat-soybean rotation cropping system compared to continuous wheat-maize cropping system. Among the fertilizer application treatments (NPK, NPKM, NPKS and NPKF), NPKM had relative higher soil nutrient concentration, microbial biomass C & N, and enzyme activities compared to other fertilizer application treatments. However, the soil metabolic quotient, pH value and bulk density of NPKM were lower than them.

The symbiosis between leguminous plants and rhizobia leads to the formation of a novel root organ, the nodule. In mature nodules, rhizobia provide the host plant with ammonium, which is produced through bacterial nitrogen fixation. The symbiotic interactions involve the perception of bacterial signaling factors called Nod factors (NFs) by plant host, the NF signaling pathway, the formation of infection threads and the development of nodule in the cortex. Although this nodule formation is beneficial for host plants to secure a nitrogen resource, overproduction of nodules could deleteriously affect plant growth. Legume plants avoid this by utilizing a negative feedback regulation known as autoregulation of nodulation (AON), in which earlier formed nodules suppress further nodulation through shoot-root communication. We summarize nodule formation and types and highlight recent studies on the molecular basis underlying NF signaling cascade, AON and effects of environmental nitrogen conditions on nodulation. We also discuss current research problems and reflect on the future of this field.

Aims Much research has been carried out on the relationship between forest fire occurrence and weather factors by use of modeling in recent years. However, the data organization used in past research can not satisfy the requirements of models well. Our aims are to determine the regression model that best fits the forest fire data set and provides a new model theory for research on forest fire and its influencing factors in order to forecast lighting fire occurrence.

Methods We used negative binomial (NB) and zero-inflated negative binomial (ZINB) models to describe the relationship between lighting fire occurrence and weather factors in the Daxing’an Mountains for 1980-2005 using SAS 9.1 version and R-Project statistic software and comparing results from these models by use of AIC and Vuong methods.

Important findings Both NB and ZINB models produced results with high significance for each weather factor. Comparison of the two models according to AIC, Vuong and other methods showed that the fitting ability and predictive power of ZINB model are better than those of the NB model. The advantage was also found when we compared the modeling results with Ordinary Least Squares. Then we obtained the best model for the relationship between lighting fire and weather factors.

Seed germination is a key process in the natural regeneration of plant populations and is mainly controlled by favorable temperature, water or light conditions. Light plays a critical role in determining the ability and rate of germination of photoblastic seeds. Furthermore, the regulation of seed germination by light involves not only complicated physiological processes but also rigorous signal transductions and gene expression pathways. We summarized available data on the relationships between seed germination and other factors (i.e., light attributes, coupling of light and water/heat and phytochromes in seeds). To assess the effects of light on seed germination, we also comprehensively summarized the physiological reaction and light signal transduction mechanisms regulated by phytochromes in seed germination.

The aridity Index (AI, here defined as the climatic aridity) is an index that describes the dry and wet conditions of a site. Historically, the AI has been often used in long-term studies of geography and ecology. Recently it has became one of the most frequently used climatic factors in studies of global change, especially in studies of climate change, ariditification and desertification. A total of 22 AIs used worldwide were briefly introduced in this paper, and of these eight of the more commonly used AIs were evaluated. We discussed their principles, calculation methods, their applications in ecological and geographical studies, and the advantages and shortcomings of each indice were analyzed based on their applications and practice in China. Our analyses indicated that three AIs, the modified Selianinov AI, the de Martonne AI and the Holdridge potential evapotranspiration ratio (another AI to some extent) have clear applicability and significance for physics and ecology. These AIs are suitable for characterizing the physical environment of China and can be used in future studies of climate change, aridification and desertification in China.

Vegegraphy, a newly-created term in this paper and a compound word of prefix “vege-” of “vegetation” and suffix of “-graphy”, is a series of monographs that describe detailedly species composition, structures, functions, environmental settings, and distribution of a set of plant communities and/or their combinations for each vegetation type, using community data from vegetation survey. Its compilation is very huge, comprehensive, time-consuming research project, and great importance in the ecological research, vegetation restoration and utilization, biodiversity conservation, and environmental monitoring. This article first documents major community characteristics (i.e., species composition, structures, physiognomy, and dynamics), and historical development and current state of vegetation survey in China and worldwide, then reviews historical studies on vegetation classification systems and their revisions, and finally discusses compilation of vegetation of China and classification of vegetation types used for the compilation. For the revision of vegetation classification systems, we mainly revised high-level units of previous classification systems and the corresponding English terms. Following this revised classification system, the hierarchical level of China’s vegetation classification is expressed as high-level units (Vegetation Formation Group, Vegetation Formation, and Vegetation Subformation), medium-level units (Alliance Group, Alliance, and Suballiance), and lower-level units (Association Group and Association), respectively. In the Vegetation Formation Group unit, nine types were divided as Forest, Shrubland, Herbaceous vegetation, Desert, Swamp & Aquatic Vegetation, Alpine Tundra & Sparse Vegetation, Cultivated Vegetation, Urban Vegetation, and Non-Vegetated Area. For the compilation of vegetation of China and the classification of vegetation types, we used the high-level unit, Vegetation Formation, as the Volume of the vegegraphy, and used a specific term, “Vegetation type”, as the Issue under the Volume. The Vegetation type here is not a real vegetation classification unit but is a combination of a set of vegetation units (i.e., Vegetation Subformation and/or Alliance Group and/or Alliance) in which there exist the same or similar constructive species or the same dominant taxa (species or genus) in the communities. The determination of “Vegetation type” follows the four principles: identity of dominant taxa and life form, relative importance of habitats, difference of vegetation characteristics and application, and practicability of vegegraphy. As a result, the vegetation of China (Vegegraphy of China) completed will be composed of 48 volumes and about 110 issues.

Recently developed in recent decades, the carbon isotope tracing technology is one of the most reliable methods, which has been widely used in the study of carbon (C) cycling in terrestrial ecosystems due to its high specificity and sensitivity. Here, the principle, analysis method and application process of C isotope tracing technology in C cycling in terrestrial ecosystem have been reviewed. Four different methods are currently being used in laboratory or field conditions, including natural abundance method, Free-Air Concentration Enrichment (FACE) technology coupling with ¹³C dilution method, pulse and continuous labeling with ¹³C enriched CO₂, and labeling with ¹³C enriched substrates. Results of field experiments and lab incubation experiments employing carbon isotope tracing technology were combined in order to quantify the transformation and distribution of photosynthetic C in plant-soil system. Furthermore, these techniques also help to understand the contribution of plant photosynthetic C to soil organic matter, the stabilization of soil organic matter and its microbial mechanism, to illustrate the dynamic changes of soil organic carbon (SOC), evaluate the contribution of new and old organic C to soil C storage, and estimate the micromechanism of SOC input, conversion and the stabilization in terrestrial ecosystems. Carbon cycle is affected by climate, vegetation, human activities and other factors, and therefore it is imperative to further develop a sensitive, accurate, multiscale and multidirectional isotope tracing system by combining carbon isotopes with mass spectrometry, spectroscopy and molecular biological technology. We have summarized the coupled application of carbon isotope tracing technology and the insitu detection involving molecular and biological approaches, and discussed the existing issues of carbon isotope tracing technology.

Above- and below-ground are important components of terrestrial ecosystems. Plants and microorganisms are dependent on each other, and they are important in the linkage between above- and below-ground processes. The relationship between plants and soil microorganisms and the fundamental role played by above- and below-ground feedbacks are important in controlling ecosystem processes and properties. Plant species play a fundamental role in nutrient absorption, nutrient accumulation, nutrient distribution and nutrient return. Soil microorganisms are important in controlling plant nutrient availability and soil quality. Our main objective is to summarize the relationships between plants and microbes, such as facilitation and competition. Plants, as producers, provide nutrients for soil microorganisms via leaf litter and root exudation. Soil microorganisms, as decomposers, break down organic matter and provide nutrients to plants. A wide range of soil microbes form intimate symbiotic associations with plants, and this can stimulate plant productivity by delivering limited nutrients to their host plants. However, both plants and microbes compete for nutrients because plant nutrient uptake and microbial immobilization occur simultaneously. We provide an integrated analysis of effects of plant diversity on soil microbial diversity, as well as direct and indirect effects of soil microbes on plant diversity and productivity. Previously, the mechanisms of plants and microorganisms in regulating ecosystem nutrient cycling have been controversial. Litter chemical composition and diversity should be considered important functional traits that explain the mechanisms. It is clear that interactions between plants and microbes play a fundamental role in maintaining the stability of natural ecosystems. This review elucidates the linkage between aboveground and belowground processes, which have been treated separately in the past.

Leaf morphology is closely related to the specific environment and provides the most useful characteristics to understand plant response and adaptation strategy to environmental change. Leaf morphology plasticity is obviously related to the temporal and spatial variation of environmental variables, which are useful to plants to enhance their ability to survive. Consequently, for many years, studies on plant physiology, plant ecology and physiological ecology focused on leaf morphology. We establish a simple category of leaf morphology classification. Simultaneously, based on the principle of material and energy balances, we systematically review the relationships among environment, leaf morphology and energy balances (or material changes), and emphasize that leaf morphology responded or adapted to lower water availability and higher radiation (or temperature) in arid ecosystems. In conclusion, we submit and discuss existing problems in leaf morphology based on the weaknesses of previous studies.

Aims New, powerful statistical techniques and GIS tools have resulted in a plethora of methods for modelling species distribution. However, little is known about the relative performance of different models in simulating and projecting species’ distributions under future climate. Our objective is to compare novel ensemble learning models with other conventional models by modelling the potential distribution of Masson pine (Pinus massoniana) and identifying and quantifying differences in model outputs.
Methods We simulated Masson pine potential distribution (baseline 1961-1990) and projected future potential distributions for three time periods (2010-2039, 2040-2069 and 2070-2099) using three global circulation models (GCM) (MIROC32_medres, JP; CCCMA_CGCM3, CA, and BCCR-BCM2.0, NW), one pessimistic SRES emissions scenario (A2), three ensemble learning models (random forest, RF; generalized boosted model, GBM, and NeuralEnsembles) and three conventional models (generalized linear model, GLM; generalized additive models, GAM, and classification and regression model, CART). The environmental envelope method was used to select absence of species. The area under the curve (AUC) values of receiver operator characteristic (ROC) curve, Kappa and true skill statistic (TSS) were used to objectively assess the predictive accuracy of each model. National standards for seed zone of Masson pine (GB 8822.6-1988) was employed to intuitively assess model performance. We developed ClimateChina software to downscale current and future GCM climate data and calculate seasonal and annual climate variables for specific locations based on latitude, longitude and elevation.
Important findings Ensemble learning models (GBM, NeuralEnsembles and RF) achieved a higher predictive success in simulating the distribution of Masson pine compared to other conventional models (CART, GAM and GLM). RF had the highest predictive accuracy, and CART had the lowest. Masson pine shows a globally consistent pattern in response to climate change for the three GCMs and six models, i.e., Masson pine will likely gradually shift northward and expand its distribution under altered future climate, with the magnitude of range changes dependent on model classes and GCMs. RF predicts a greater magnitude of range changes than other models. Projections of Masson pine distribution by NW are more conservative than JP and CA climate scenarios. In the case of Masson pine, range changes are mainly attributed to the colonization of newly available suitable habitat in high-latitudes and unchanging habitat suitability in the south-central part of its baseline range. Differences among 18 projections (6 models × 3 GCMs) increase with increasing time, and the greatest spatial uncertainty in projections is mainly in the north and west borders of the potential distribution range.

Pollen data are the foundation of reconstructing past vegetation patterns and of studying past climate changes and interactions among atmosphere, biosphere and human activities. We searched for pollen-related literature published and reported from the 1960s to 2008 and collected late Quaternary pollen sampling information for China. We focused on the past 20 000 years before present (aBP), especially the Holocene. Information includes site name, detailed location in text and in latitude, longitude and elevation, sample type, sediment depth, number of pollen samples, radiocarbon dating, time period, and reference. There are 2 324 surface pollen samples from soils and lakes and 987 cores/profiles of sediment fossil records. Among them there are 714 fossil pollen sampling sites with high quality data of pollen and radiocarbon dating. Despite research has been performed by domestic and international paleo-scientists in collecting pollen samples and in Quaternary studies in China, geographical gaps exist due to the limitation of financial support and poor topographical conditions. These include the northern and northwestern desert areas, non-settlement area of the Tibetan Plateau, mountainous areas of middle-southern China and highly disturbed areas of eastern China. More pollen sampling records are needed to update and complete the information database. Such information will greatly benefit the Quaternary Chinese Pollen Database. Furthermore, scientific questions can be addressed based on the databases, such as what the geographical patterns of paleovegetation in China were during the late Quaternary, what were the key times of vegetation shifts (abrupt changes), what were the driving factors of vegetation changes, climate change or human disturbances, and how have vegetation changes influenced local and regional climates?

The biological sciences developed very fast during the 20th century and have become increasingly sophisticated and predictive. Along with this trend, areas of research also have become increasingly specialized and fragmented. However, this fragmentation and specialization risks overlooking the most inherent biological characteristics of living organisms. One can ask if the living organisms on the earth have unified and essential characteristics that can connect the disparate disciplines and levels of biological study from molecular structure of genes to ecosystem dynamics. By exploring this question, a new science, ecological stoichiometry, has been developed over the past two decades. Ecological stoichiometry is a study of the mass balance of multiple chemical elements in living systems; it analyzes the constraints and consequences of these mass balances during ecological interactions. All biological entities on the earth have a specific elemental composition and specific elemental requirements, which influence their interactions with other organisms and their abiotic environment in predictable ways. Ecological stoichiometry has been incorporated successfully into many levels of biology from molecular, cellular, organismal and population to ecosystem and globe. At present, the principles of ecological stoichiometry have been broadly applied to research on population dynamics, trophic dynamics, microbial nutrition, host-pathogen interactions, symbiosis, comparative ecosystem analysis, and consumer-driven nutrient cycling. This paper reviews the concepts, research history, principles, and applications of ecological stoichiometry and points out future research hotspots in this dynamic field of study with an aim to promote this discipline of research in China.

Priming effects are defined as “strong short-term changes in the turnover of soil organic matter caused by moderate treatments of the soil”. Rhizosphere is the most important place, where the priming effects take place. Rhizosphere priming effects reflect the turnover rate of soil carbon and nitrogen, and affect the acquisition of competition for nutrients by plants and microorganisms, thus maintaining nutrient balance among the various components of an ecosystem. Although there has been a general understanding on the occurrence of rhizosphere priming effects, the mechanisms underlying their role in soil carbon and nitrogen transformations and their ecological significance are still not fully comprehended. This paper provides a synthesis of the latest advancement in studies of the rhizosphere priming effects. On the basis of reviews of research history and identification of the hotspots, we first put forward a mechanism underlying the occurrence of rhizosphere priming effects, and then examined the biotic and abiotic factors influencing the rhizosphere priming effects. The ecological significance and outlooks of research in the rhizosphere priming effects were discussed and clarified.

Estimating carbon storage in terrestrial ecosystems has been a central focus of research over the past two decades because of its importance to terrestrial carbon cycles and ecosystem processes. As one of the most widespread ecosystem types, China’s grasslands play an important role in global change research. The grasslands in China, which are distributed primarily throughout the temperate regions and on the Tibetan Plateau, were classified into 17 community types. In the present study, a statistical model was established to estimate grassland biomass and its geographical distribution in China based on a grassland inventory data set and remote sensing data (Normalized Difference Vegetation Index) using GIS and RS techniques. We found that there was a significant correlation between aboveground biomass density and the maximum annual NDVI when expressed as a power function (R2=0.71, p<0.001). The aboveground biomass was estimated to be 146.16 TgC (1Tg=1012 g) and belowground biomass was estimated as 898.60 TgC (6.15 times of the above biomass) for a total biomass of 1 044.76 TgC. This value accounts for about 2.1%-3.7% of the world’s grassland biomass. The grassland biomass is distributed primarily in the arid and semiarid regions of Northern China and the Qinghai-Xizang Plateau. The average biomass density of China’s grasslands was 315.24 gC·m-2, smaller than the world average. The aboveground biomass density decreases from southeastern China toward the northwest corresponding with changes in precipitation and temperature. Furthermore, aboveground biomass density reached the lowest levels at 1 350 m elevation and peak levels at 3 750 m above sea level which most likely is related to China’s three-step topographical background. The ratio of total biomass of grassland to forest biomass in China is 1/4, much higher than that of the world, suggesting a greater contribution of grasslands to China’s carbon pool.

Allometric scaling relations are characteristic of all organisms. A challenging task is how the typical allometric scaling relationship—Kleiber’s Law, which depicts the proportionality between the metabolic rate of an animal and its body mass raised to the 3/4 power and is well established and supported by data—can be predicted from a purely theoretical standpoint. Scientists have proposed diverse models to do this, but almost all of the models are criticized for theoretical or methodological difficulties. However, ecologists and physicists recently proposed new models. Here we highlight the Fractal-Like Distribution Network Models and other models, such as Multi-Causes Model, Minimal Overall Entropy Production Model, Constructal Theory, Cell Model and Energy Consumption Model.

Chlorophylls function in harvesting light energy, funneling the excitation to reaction center and converting sunlight into chemical energy, and carotenoids are responsible for light harvesting and photoprotection. Both are vital for photosynthesis. We summarized the distribution and function of the main photosynthetic pigments and variation of pigment composition and content in sun and shade plants. Sun plants possess larger xanthophyll cycle pool size (violaxanthin + antheraxanthin + zeaxanthin), but de-epoxidation level is lower than that of shade plants. The ratio of lutein to xanthophyll cycle pool size is positively correlated to plant shade tolerance. Light intensity and spectral quality vary between different shade sources. Generally for plant growth, building shade is better than vegetation shade, and deciduous shade exceeds coniferous shade. Variation in light intensity may activate two cycles in plants, xanthophyll cycle and lutein epoxide cycle, for light harvesting or energy dissipation. Some species may alter chlorophyll content and Chl a/b ratio to acclimate to different light intensity, but this character is not related to their shade tolerance. Temporary shade is not necessarily detrimental. Xanthophyll cycle pool size is not only determined by daily photon receipt, but also by the way photon flux is distributed over the daylight hours, because light and temperature are both essential for optimal photosynthetic metabolism. The best photosynthetic performances of plants were obtained with the reinforcement of blue, red and far red wavelengths and with a red: far red ratio closer to that observed in nature. We reviewed internal and external factors affecting photosynthetic pigment content and composition, and determined that during the acclimation to different light environments, plants altered pigment composition and content mainly through adjusting the ratio of reaction center to light harvesting complex and PSI/PSII. We also discussed current research problems and provided insight into future relevant research.

The concept of ecological thresholds was raised in the 1970s. However, it was subsequently given different definitions and interpretations depending on research fields or disciplines. For most scientists, ecological thresholds refer to the points or zones that link abrupt changes between alternative stable states of an ecosystem. The measurement and quantification of ecological thresholds have great theoretical and practical significance in ecological research for clarifying the structure and function of ecosystems, for planning sustainable development modes, and for delimiting ecological red lines in managing the ecosystems of a region. By reviewing the existing concepts and classifications of ecological thresholds, we propose a new concept and definition at two different levels: the ecological threshold points, i.e. the turning points of quantitative changes to qualitative changes, which can be considered as ecological red lines; the ecological threshold zones, i.e. the regime shifts of the quantitative changes among different stable states, which can be considered as the yellow and/or orange warning boundaries of the gradual ecological changes. The yellow thresholds mean that an ecosystem can return to a stable state by its self-adjustment, the orange thresholds indicate that the ecosystem will stay in the equilibrium state after interference factors being removed, whereas the red thresholds, as the critical threshold points, indicate that the ecosystem will undergo irreversible degradation or even collapse beyond those points. We also summarizes two types of popular Methods in determining ecological thresholds: statistical analysis and modeling based on data of field observations. The applications of ecological thresholds in ecosystem service, biodiversity conservation and ecosystem management research are also reviewed. Future research on ecological thresholds should focus on the following aspects: (1) methodological development for measurement and quantification of ecological thresholds; (2) emphasizing the scaling effect of ecological thresholds and establishment of national-scale observation system and network; and (3) implementation of ecological thresholds as early warning tools in ecosystem management and delimiting ecological red lines.

Aims A light response curve can reflect a plant’s ability to utilize light, which is also a key tool in determining the relationship between photosynthetic capacity and environmental factors; however the model accuracies concerning the light response curve remain elusive. The objectives of this study were to compare and assess the model accuracies related to a light response curve and the effects of drought. Methods A field rain shelter was used to control the soil water conditions. To obtain photosynthesis parameters from the light response curve and the drought effects, the relevant models (including the rectangular model, non-rectangular hyperbolic model, modified rectangular hyperbolic model, exponential model, quadratic function model, and a newly modified model) were applied to fit the light response curves. The validity of each model was tested by analyzing the differences between the fitted values obtained by the models and the measured values. Important findings The newly modified model has been proved to performing relatively better in accurately describing the light response curve patterns, and credibly obtaining the crucial photosynthetic parameters such as the maximum net photosynthetic rate, light saturation point, light compensation point, and dark respiration rate, especially under high radiation conditions.

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.

Aims Our objectives were to consider a new scheme for vegetation regionalization of Northeast China, especially for vegetation in the Songliao Plain, and to illustrate the distribution pattern of vegetation as determined by altitude.
Methods We clustered the sites from Inner Mongolia steppe, east forest and central Songliao Plain with temperature, precipitation, soil types and underground water depth using principle component analysis (PCA). We also analyzed the physiognomy, topography of Northeastern China using GIS, vegetation types and soil types of Songnen Plain.
Important findings The dominant vegetation of Songliao Plain is meadow, an unzonal vegetation type. The Stipa communities, an indicator of the zonal vegetation type, mainly distributed on the second mesa in Songnen Plain, are a sandland vegetation type that is distributed discontinuously among meadow vegetation. Therefore, the vegetation of Songliao Plain should be regionalized as an area of temperate broad-leaved deciduous forest, and the east boundary of temperate steppe region should be moved toward to the west of the Da Hinggan Mountains. The vegetation distribution of Northeast China shows a vertical zonation determined by altitude.

Leaf mass per area (LMA) is a composite structural parameter as well as a basic leaf functional trait in the leaf economics spectrum (LES). It is not only closely related to many physiological responses of plants, but also can measure the investment of dry mass per unit of light-intercepting leaf area. LMA is considered an important indicator of plant ecological strategies and has been studied widely in plant ecology, agronomy, forestry, and plant physiology. This paper elucidates the structural analysis and computational methods of LMA at the organizational scales of whole leaf, tissues and cells, examines the influence of LMA on photosynthesis, and discusses the inherent differences in LMA and the responses of LMA to environmental stresses (temperature, water and light), aiming for clarifying research frameworks and methods in studies of LMA and providing guidance on future research.

Aims The shape plasticity of plant leaves is an important survival strategy to high temperature and drought in arid region, yet reliable evidences are insufficient to validate the fundamental concepts. Our objective was to demonstrate the specific effects of leaf morphology on leaf surface temperature.

Methods Infrared thermal images were processed to determine the leaf temperature and shape parameters of simulated and actual leaf shape. Microclimatic conditions were recorded using a automatic weather station near the sampling plot, including wind speed, radiation and air temperature.

Important findings Under the drought and high temperature, the plasticity of leaf shape appeared an important measure to regulate leaf temperature, except leaf transpiration. The exchange rates of matter and energy between leaves and the environment were enhanced by smaller leaves that effectively decreased leaf temperature. With low wind speed and high temperature, leaf surface temperature decreased 2.1 °C per 1 cm reduction in leaf width. However, leaf surface temperature of a simulated leaf decreased 0.60-0.86 °C per 1 cm reduction in leaf width. Results from this study will help us to understand plant adaptability and survival strategy in arid region.

Aims Beta diversity is the variation in species composition among sites in a geographic region. Beta diversity is a key concept for understanding the functioning of ecosystems, for the conservation of biodiversity, and for ecosystem management. This paper describes how to analyze it from community composition and associated environmental and spatial data tables.

Methods Beta diversity can be studied by computing diversity indices for each site and testing hypotheses about the factors that may explain the variation among sites. Or, one can carry out a direct analysis of the community composition data table over the study sites, as a function of sets of environmental and spatial variables. These analyses are carried out by the statistical method of partitioning the variation of the diversity indices or the community composition data table with respect to environmental and spatial variables. Variation partitioning is briefly described in this paper.

Important findings Variation partitioning is a method of choice for the interpretation of beta diversity using tables of environmental and spatial variables. Beta diversity is an interesting “currency" for ecologists to compare either different sampling areas, or different ecological communities co-occurring in an area. Partitioning must be based upon unbiased estimates of the variation of the community composition data table that is explained by the various tables of explanatory variables. The adjusted coefficient of determination provides such an unbiased estimate in both multiple regression and canonical redundancy analysis. After partitioning, one can test the significance of the fractions of interest and plot maps of the fitted values corresponding to these fractions.

Aims The community assembly has been a prominent issue in community ecology. This work was intended to explore the mechanisms of the species coexistence and biodiversity in communities. Our objective was to explore the mechanisms of community assembly in subalpine meadow plant communities along slope gradients in Gannan Tibetan Autonomous Prefecture, Gansu Province, Northwest China.
Methods We selected five slope-oriented plots to construct a super-tree representing the species pool. We surveyed the leaf functional traits and soil environmental factors in different slopes. Then we tested the phylogenetic signal of leaf dry matter content (LDMC), specific leaf area (SLA), leaf nitrogen content (LNC) and leaf phosphorus content (LPC).
Important findings The changes of slope aspect had significant influence on soil water content (SWC) and soil nutrient content. Most of the plants leaf functional traits had significant difference along different slope aspects. The LDMC was higher in south and southwest slope than north slope, while SLA, LNC and LPC were relatively high in north and northwest slope. The LPC showed feeble phylogenetic signal, while LDMC, SLA, LNC did not have a significant phylogenetic signal. With changes in the slope aspect from south to north, community phylogenetic structure shifted from over-dispersion to clustered dispersion. In south and southwest slope, habitat filtering was the driving force for community assembly. Interspecific competition was the main driving factor for community assembly in north and northwest slope aspects. But in west slope, two indices showed contrary consequence. This means the process of community assembly in west slope was more complicated and its phylogenetic index may be the result of several mechanisms working together.