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Table of Content
    Volume 40 Issue 1
    01 January 2016

    Thescenery of vegetation over the Qilian Mountains located within the upper reaches of the Heihe River Basin (Photographed by YAN Min). Yan et al. simulated the gross primary productivity at forest and grass site using the optimized MODIS MOD_17 GPP model and the results were validated against the measurements, then the spatial feature of GPP and its relationships with climatic factors were analyzed (Pages 1–12 of this issue).

      
    Orginal Article
    Remote sensing estimation of gross primary productivity and its response to climate change in the upstream of Heihe River Basin
    YAN Min,LI Zeng-Yuan,TIAN Xin,CHEN Er-Xue,GU Cheng-Yan
    Chin J Plan Ecolo. 2016, 40 (1):  1-12.  doi:10.17521/cjpe.2015.0253
    Abstract ( 687 )   HTML ( 10 )   PDF (5444KB) ( 1522 )   Save
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    AimsQuantifying the gross primary productivity (GPP) of vegetation is of primary interest in studies of global carbon cycle. This study aims to optimize the MODIS GPP model for specific environments of a fragile waterhead ecosystem, by performing simulations of long-term (from 2001 to 2012) GPP with optimized MOD_17 model, and to analyze the response of GPP to the local climatic variations.Methods The original MODIS GPP products that underestimate GPP were validated against two years (2010-2011) of eddy covariance (EC) data at two sites (i.e. an alpine pasture site and a forest site, respectively) in the upstream of Heihe River Basin. Three comparative experiments were then conducted to analyze the effects of input parameters derived from three sources (i.e. meteorological, biome-specific, and fraction of absorbed photosynthetically active radiation (fPAR) parameters) on the model behavior. After refining the model-driven parameters, long-term GPPs of the study area were estimated using the optimized MOD_17 model, and the Least Absolute Deviation method was applied to analyze the partial correlations between interannual GPPs and climatic variables (temperature, precipitation and vapor pressure deficit (VPD)). Important findings The uncertainties in the original MODIS GPP products are attributable to biome-specific parameters, input data (e.g. meteorological and radiometry data) and vegetation maps. At the pasture site, the light use efficiency had the strongest impact on the GPP simulations. The refined fPAR calculated from the leaf area index (LAI) products of Global Land Surface Satellite (GLASS) greatly improved the GPP estimates, especially at the forest site. The GPPs from the optimized MOD_17 model well matched the EC data (R2 = 0.90, root mean squared error (RMSE) = 1.114 g C·m-2·d-1 at the alpine pasture site; R2 = 0.91, RMSE = 0.649 g C·m-2·d-1 at the forest site). The time series of GPPs displayed an up trend at an average rate of 9.58 g C·m-2·a-1 from 2001 to 2012. Examination of the partial correlations between interannual GPPs and climatic variables showed that the annual mean temperature and VPD generally had significant positive impacts on GPP, and the annual precipitation had a negative impact on GPP.
    Vegetation change and its response to climate change in Central Asia from 1982 to 2012
    ZHANG Qi,YUAN Xiu-Liang,CHEN Xi,LUO Ge-Ping,LI Long-Hui
    Chin J Plan Ecolo. 2016, 40 (1):  13-23.  doi:10.17521/cjpe.2015.0236
    Abstract ( 652 )   HTML ( 13 )   PDF (4838KB) ( 1109 )   Save
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    AimsCentral Asia is one of the most vulnerable and sensitive areas to the change in climate. To understand the response of Central Asia ecosystems to climate change, it is important to improve our understanding of vegetation change and its response to climatic variations. Our objective is to explore and analyze the normalized difference vegetation index (NDVI) and its response to climate change in Central Asia during the period 1982-2012.MethodsThe linear regression, the empirical orthogonal function (EOF), the singular value decomposition (SVD) and the partial correlation analysis were used to analyze the NDVI change and its response to climate factors in Central Asia during the period of 1982-2012.Important findings 34% of vegetation in Central Asia showed a pronounced change in NDVI with a significant trend of increase (p < 0.05) and the rate of increase in NDVI exceeded 0.004 per year for mountainous regions. Both air temperature and precipitation showed significant effects on NDVI. Based on partial correlation analysis, 63% of vegetation was found to be significantly affected by precipitation (p < 0.05) while 32% vegetation was affected by air temperature (p < 0.05). The NDVI changes showed increasing trend from 1982 to 1994, fluctuations between 1994 and 2002, and increasing trend again from 2002 to 2012 in mountainous and northeastern areas. While the NDVI changes experienced increasing trend from 1982 to 1994 but decreasing trend from 1994 to 2012 in northwestern areas. Based on the analysis of SVD, the spatial patterns of NDVI variations were consistent with the spatial patterns of precipitation variations. However, the temperature responses of vegetation NDVI differed across the northeast and the mountainous regions in Central Asia.
    Response of radial growth to climate change for Larix olgensis along an altitudinal gradient on the eastern slope of Changbai Mountain, Northeast China
    YU Jian,XU Qian-Qian,LIU Wen-Hui,LUO Chun-Wang,YANG Jun-Long,LI Jun-Qing,LIU Qi-Jing
    Chin J Plan Ecolo. 2016, 40 (1):  24-35.  doi:10.17521/cjpe.2015.0216
    Abstract ( 594 )   HTML ( 12 )   PDF (955KB) ( 1175 )   Save
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    AimsTo further understand the sensitivity of tree growth to climate change and its variation with altitude, particularly the growth-climate relationship near the timberline, the radial growth of Larix olgensis in an oldgrowth forest along an altitudinal gradient on the eastern slope of Changbai Mountain was investigated. MethodsThe relationships between climate factors and tree-ring index were determined using bootstrapped response functions analysis with the software DENDROCLIM2002. Redundancy analysis, a multivariate “direct” gradient analysis, and its ordination axes were constrained to represent linear combinations with meteorological elements. The analysis was used to clarify the relationship between tree-ring width indexes at different elevations and climate factors during the period 1959-2009.Important findings indicated: (1) Tree ring chronologies from high altitudes were more superior than other samples in terms of growth-climate relationship, revealing that trees at high altitudes are more sensitive to climate variation than at low sites, (2) Tree growth was mainly affected by temperatures of from before and through growing season in previous year, especially in June and August. In comparison, tree growth in the low elevation was regulated by the combination of precipitation of August and Palmer drought severity index (PDSI) of September in current year, (3) Trees growing below timberline appeared to be more sensitive to climate warming; small extents of habitat heterogeneity or disturbance events beyond timberline may have masked the response, hence the optimal sites for examining growth trends as a function of climate variation are considered to be just below timberline, and (4) Redundancy analysis between the three chronologies and climate factors showed the same results as that of the correlation analysis and response function analysis, and this is in support of previous conclusion that redundancy analysis is also effective in quantifying the relationship between tree-ring indexes and climate factors.
    Response and correlation of above- and below-ground functional traits of Leymus chinensis to nitrogen and phosphorus additions
    ZHAN Shu-Xia,ZHENG Shu-Xia,WANG Yang,BAI Yong-Fei
    Chin J Plan Ecolo. 2016, 40 (1):  36-47.  doi:10.17521/cjpe.2015.0164
    Abstract ( 599 )   HTML ( 2 )   PDF (1137KB) ( 1367 )   Save
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    AimsLeymus chinensis is a constructive and dominant species in typical steppe of northern China. The structure and functions of L. chinensis grassland ecosystem has been degenerated seriously due to long-term overgrazing in recent decades. As an effective measure to restore the degraded grasslands, the effects of nutrient addition on plant growth and ecosystem structure and functioning have been paid more attention in manipulation experimental research. The effects of nutrient addition, especially P addition on the above- and below-ground functional traits of L. chinensis have rarely been studied; particularly the underpinning mechanisms remain unclear. Our objective is to examine the responses and adaptive mechanisms of L. chinensis to different levels of N and P additions. MethodsWe conducted a culture experiment in the greenhouse, with three levels of N (50, 100 and 250 mg N·kg-1) and P (5, 10 and 25 mg P·kg-1) addition treatments. The above- and below-ground biomass, leaf traits (e.g., specific leaf area, leaf N and P contents) and root traits (e.g., specific root length, root N and P contents) of L. chinensis were determined in this study.Important findings Our results showed that: 1) the aboveground biomass and total biomass of L. chinensis were mostly affected by N addition, while the belowground biomass was mainly affected by P addition. N addition greatly enhanced the aboveground biomass of L. chinensis, while P addition reduced the belowground biomass at the moderate and high N levels. The root-shoot ratio of L. chinensis was influenced by both N and P additions, and root-shoot ratio decreased with increasing N and P levels. N and P additions promoted more biomass and N and P allocations to aboveground and leaf biomass. 2) Leymus chinensis showed different responses and adaptive mechanisms to P addition at low and high N levels. At low N level, L. chinensis exhibited high photosynthetic rate and specific root length (SRL) to improve photosynthetic capacity and root N acquisition, which promoted aboveground biomass. High root P content was favorable for belowground biomass. At high N level, P addition did not significantly affect plant growth of L. chinensis, even reduced its belowground biomass. Leymus chinensis showed high specific leaf area (SLA) and SRL to improve light interception and N acquisition in order to maintain stable aboveground biomass. 3) P addition greatly impacted below-ground than above-ground functional traits. SLA exhibited a weakly positive correlation with SRL, indicating L. chinensis exhibited relatively independence of resource acquirement and utilization between leaf and root functional traits.
    Geostatistical analysis of spatial variations in leaf traits of woody plants in Tiantong, Zhejiang Province
    XU Ming-Shan,ZHAO Yan-Tao,YANG Xiao-Dong,SHI Qing-Ru,ZHOU Liu-Li,ZHANG Qing-Qing,Ali ARSHAD,YAN En-Rong
    Chin J Plan Ecolo. 2016, 40 (1):  48-59.  doi:10.17521/cjpe.2015.0246
    Abstract ( 524 )   HTML ( 8 )   PDF (1141KB) ( 907 )   Save
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    AimsExploring spatial variations in leaf traits and their relationships with environmental properties is crucial for understanding plant adaptation strategies and community assembly. This study aimed to reveal how leaf traits varied spatially and the role of environmental factors.MethodsThe study was conducted in a 5-hm2 forest plot in Tiantong, Zhejiang Province. Three leaf traits, including individual leaf area (ILA), specific leaf area (SLA), and leaf dry matter content (LDMC) were measured for 20253 individual trees with diameter at breast height (DBH) ≥1 cm. Soil properties measured included contents of soil total nitrogen, soil total phosphorus, soil total carbon, soil pH value, soil volumetric water content, bulk density, and humus depth. Topographic variables measured included elevation, slope and convexity. We used geostatistical analysis to reveal spatial variations of the three leaf traits. Relationships between leaf variability and environmental factors were analyzed using principal component analysis (PCA) and Pearson’s correlation.Important findings Spatial variability followed the order of ILA > SLA > LDMC. Spatial autocorrelation of three leaf traits was weak within a distance of 5.16 m. The optimal model of the semi-variogram function was Gaussian model for ILA, and exponential model for SLA and LDMC. ILA showed the largest variability at the direction of northeast-southwest, and smallest variability at the direction of northwest-southeast. In contrast, SLA and LDMC had the highest variability at the direction of northwest-southeast and least variability at the direction of northeast-southwest. There were significantly negative relationships between ILA and topographic factors (r = -0.12, p < 0.0001), and between SLA and soil nutrients (r = -0.16, p < 0.0001). In contrast, LDMC was positively correlated with soil nutrients (r = 0.13, p < 0.0001). Relative to soil nutrients, topographic factors affected much more variations in ILA, SLA and LDMC at the direction of northeast-southwest. Distinctly, at the direction of northwest-southeast, variability of ILA was affected mainly by topographic factors, while soil nutrients resulted in the most variability of SLA and LDMC. In conclusion, leaf traits varied considerably with spatial direction in the studied forest plot. Associations between leaf traits and topographic factors and soil nutrients indirectly indicated effects of environmental filtering on community assembly.
    Effects of elevated CO2 concentration on root and needle anatomy and physiological functions in Pinus koraiensis seedlings
    WANG Na,ZHANG Yun,QIAN Wen-Li,WANG Zheng-Quan,GU Jia-Cun
    Chin J Plan Ecolo. 2016, 40 (1):  60-68.  doi:10.17521/cjpe.2015.0273
    Abstract ( 400 )   HTML ( 4 )   PDF (939KB) ( 1041 )   Save
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    AimsThe impacts of CO2 concentration on the anatomy and physiology of plant roots have rarely been studied. Here we studied the effects of elevated CO2 on anatomical and physiological traits of needles and root tips in Pinus koraiensis seedlings. Our objectives were: 1) to examine how the anatomy of needles and root tips change under doubled CO2 concentration treatment; and 2) to explore physiological responses of needles and root tips to the rising CO2 concentration; and 3) to reveal potential relationships of physiological trait changes between needles and root tips.MethodsThree-year-old seedlings of P. koraiensis were grown in CO2 chambers under doubled and ambient CO2 concentrations (350 and 700 µmol·mol-1). Physiological traits of needles were measured by the LI-6400 portable photosynthesis system during the experiment. After 5 months, needles and root tips were sampled to determine their anatomical characteristics. Theoretical hydraulic conductivity of needles and root tips were calculated based on the Hagen-Poiseuille’s Law.Important findings Elevated CO2 concentration had a significant influence on the anatomical characteristics of needles and root tips in P. koraiensis seedlings. Under doubled CO2 concentration, needles had a lower stomatal desnity, greater areas of leaf mesophyll, phloem and xylem. In comparision, root tips under doubled CO2 concentration had a larger diameter, a greater cortical thickness and a larger number of cortical cell layer. Physiological traits of needles and root tips also changed substantially under the elevated CO2 concentration, such as increases in needle photosynthetic rate and water use efficiency, xylem cavitation resistance of roots, as well as decreases in stomatal conductance, transpiration rate and root hydraulic conductivity. These results suggest that the anatomical structure and physiological function of leaf and root respond simultaneously to elevated CO2 concentration. Future studies should not only focus on the impact of global climate change on aboveground organs and fuctions, but also to the belowground counterparts.
    Eco-physiological responses of linseed (Linum usitatissimum) to salt and alkali stresses
    GUO Rui,LI Feng,ZHOU Ji,LI Hao-Ru,XIA Xu,LIU Qi
    Chin J Plan Ecolo. 2016, 40 (1):  69-79.  doi:10.17521/cjpe.2015.0240
    Abstract ( 445 )   HTML ( 4 )   PDF (500KB) ( 1110 )   Save
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    AimsEffects of salt and alkali stresses (NaCl-Na2SO4 and NaHCO3-Na2CO3) were compared on growth, photosynthesis characters, ionic balance and osmotic adjustment of linseed (Linum usitatissimum), to elucidate the mechanisms of salt and alkali stress (high pH value) damage to plants, and their physiological adaptive mechanisms to the stresses. MethodsThe experiment was carried out in an artificial greenhouse. Plants grew at approximately 700 mmol·m-2·s-1 photosynthetic photon flux density (PPFD) in greenhouse under photoperiod of 15 h in light and 9 h in dark. In each plastic pot (17 cm diameter) which contained 2.5 kg of washed sand, 20 linseed seeds were sown. The seedlings were exposed to stresses lasting 14 days after 2 months.Important findingsThe inhibitory effects of alkali stress on linseed growth were more remarkable than those of salt stress, indicating that alkali and salt represent two distinct forms of stress. The alkali stress increased the Na+ content in shoots, damaged the photosynthetic system, and highly reduced the net photosynthetic rate and C assimilation capacity. Under salinity stress, the Na+ content increased, the K+ content decreased with increasing stress. Greater changes were observed under alkali than under salt stress. Alkali stress caused the massive influx of Na+, which probably explained that the harmful of alkali stress on plants was stronger than that of salt stress. Under alkali stress, Ca2+ and Mg2+ decreased in roots, showing that high pH value around roots hindered the absorption of them. Fe2+ and Zn2+ had little effects on the osmotic adjustment, mainly because of they had a low ion content. Under salt stress, anion increased in order to balance the sharp increase of Na+. However, alkali stress made severe deficit of negative charge, broke the intracellular ionic balance and pH homeostasis, and caused a series of strain response. Our results showed that linseed enhanced the synthesis of soluble sugars to balance massive influx of Na+ under salt stress, but linseed enhanced the synthesis of organic acids to compensate for the shortage of inorganic anions, which might be a key pathway for the pH adjustment. In conclusion, the alkali stress (high pH value) clearly inhibited the growth, element absorption, ion homeostasis reconstruction of plants. Organic acid concentration is possibly a key adaptive factor for linseed to maintain intracellular ion balance and regulate high pH value under alkali stress.
    A review of plant spectral reflectance response to water physiological changes
    LIU Chang,SUN Peng-Sen,LIU Shi-Rong
    Chin J Plan Ecolo. 2016, 40 (1):  80-91.  doi:10.17521/cjpe.2015.0267
    Abstract ( 804 )   HTML ( 15 )   PDF (949KB) ( 1240 )   Save
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    Spectral reflectance is a new, real time and non-destructive hyperspectral remote sensing application to monitor plant water status and physiological changes. The spectral reflectance responses induced by water stress reflect the interaction and coupling of carbon, nitrogen and water cycles. A majority of previous studies focused on a specific structural or physiological effect on spectral reflectance with little attention on their interactions. This paper reviewed and synthesized the direct and indirect spectral responses caused by changes in plant water content, pigments, nutrient status, photosynthesis and chlorophyll fluorescence indices and their internal association. This paper also discussed the common approaches and the new techniques in applying spectral reflectance for detecting water status and physiological activities in plants. This paper concluded that analysis of the spectral reflectance at multiple temporal or spatial scales might have a potential application in projecting vegetation productivities, particularly in the context of climate change.


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