Nitrogen Concentration in Subtending Cotton Leaves in Relation to Fiber Strength in Different Fruiting Branches

Nitrogen（N） fertilizer experiments were conducted to investigate the optimal subtending leaf N concentration for fiber strength,and its relationship with activities of key enzymes（sucrose synthase and β-1,3-glucanase） and contents of key constituents（sucrose and β-1,3-glucan） involved in fiber strength development in the lower,middle and upper fruiting branches of two cotton cultivars（Kemian 1 and NuCOTN 33B）.For each sampling day,we simulated changes in fiber strength,activity of sucrose synthase and β-1,3-glucanase and levels of sucrose and β-1,3-glucan in response to leaf N concentration using quadratic eqs.;the optimal subtending leaf N concentrations were deduced from the eqs.For the same fruiting branch,changes in the optimal leaf N concentration based on fiber development（DPA） could be simulated by power functions.From these functions,the average optimal subtending leaf N concentrations during fiber development for the cultivar,Kemian 1,were 2.84% in the lower fruiting branches,3.15% in the middle fruiting branches and 3.04% in the upper fruiting branches.For the cultivar,NuCOTN 33B,the optimum concentrations were 3.04,3.28 and 3.18% in the lower,middle and upper fruiting branches,respectively.This quantification may be used as a monitoring index for evaluating fiber strength and its related key enzymes and constituents during fiber formation at the lower,middle and upper fruiting branches.

Leaf Longevity in a Timberline Tree Species Juniperus saltuaria in the Sergymla Mountains,Southeastern Tibet

Leaf longevity is an important adaptive strategy that allows plants to maximize photosynthetic carbon gain.Due to the difficulty of identifying overwintering bud scars and distinguishing the age sequence of twigs,leaf longevity is rarely studied in Cupressaceae species,which further limits our understanding of the leaf economic spectrum (LES) for these populations.Here,we investigated the leaf longevity,as well as mass-based leaf nitrogen concentration (N;),of Juniperus saltuaria at different canopy heights for both subalpine and alpine timberline forests in the Sergymla Mountains,southeastern Tibet.We found that the mean leaf longevity was 4.2±1.2 years,and overall it did not differ significantly between different elevations.Along the vertical profiles of juniper canopies,the leaf longevity did not reflect a linear trend.With increasing leaf longevity,N;showed declining trends.We further analyzed the relationship between leaf longevity and the corresponding length of green twigs,and found that the length of green twigs could only explain 1%-3%of the variation in leaf longevity,indicating that the length of green twigs is a poor predictor for the variation in leaf longevity.In summary,for the J.saltuaria species in timberline or nearby subalpine forests,the effects of elevation and canopy depths on leaf longevity are minor,and the leaf trait analysis is in accordance with the prediction of LES.

Community-level trait responses and intra-specific trait variability play important roles in driving community productivity in an alpine meadow on the Tibetan Plateau

Aims Human activities have dramatically increased nutrient inputs to ecosys-tems,impacting plant community diversity,composition and function-ing.Extensive research has shown that a decrease in species diversity and an increase in productivity are a common phenomenon following fertilization in grasslands ecosystem.The magnitude of the response of species diversity and above-ground net primary productivity(ANPP)to fertilization mainly depends on species traits(mean trait values)and traits variability(plasticity).Our aim of this study was to examine(i)changes of species diversity(species richness and Shannon-Wiener index)and ANPP following fertilization;(ii)which species traits or community-weighted mean(CWM)traits can determine ANPP,as expected from the‘biomass ratio hypothesis’;and(iii)the relative role of intra-specific and inter-specific trait variability in this process following fertilization.Methods We measured ANPP and four key plant functional traits:specific leaf area(SLA),leaf dry matter content(LDMC),mature plant height(MPH)and leaf nitrogen concentration(LNC)for 25 component species along a fertilization gradient in an alpine meadow on the Tibetan Plateau.In addition,trait variation of species was assessed using coefficients of variation(CV),and we calculated the ratio of the CVintra to the CVinter.Important Findings Our results showed that:(i)fertilization significantly reduced species richness and Shannon-Weiner diversity index,but sig-nificantly increased ANPP;(ii)there was a significant positive correlation between ANPP and CWM-SLA and CWM-MPH,yet there was no significant relationship between ANPP and CWM-LNC or CWM-LDMC;(iii)intra-specific variability in SLA and MPH was found to be much greater than inter-specific variability,especially at the higher fertilization levels.We con-cluded that CWM-SLA and CWM-MPH can be used to assess the impacts of species changes on ecosystem functioning,and dominant species can maximize resource use through intra-spe-cific variability in SLA and MPH to compensate for the loss of species following fertilization,therefore maintaining high com-munity productivity.

Predicting community traits along an alpine grassland transect using field imaging spectroscopy

Assessing plant community traits is important for understanding how terrestrial ecosystems respond and adapt to global climate change.Field hyperspectral remote sensing is effective for quantitatively estimating vegetation properties in most terrestrial ecosystems,although it remains to be tested in areas with dwarf and sparse vegetation,such as the Tibetan Plateau.We measured canopy reflectance in the Tibetan Plateau using a handheld imaging spectrometer and conducted plant community investigations along an alpine grassland transect.We estimated community structural and functional traits,as well as community function based on a field survey and laboratory analysis using 14 spectral vegetation indices(VIs)derived from hyperspectral images.We quantified the contributions of environmental drivers,VIs,and community traits to community function by structural equation modelling(SEM).Univariate linear regression analysis showed that plant community traits are best predicted by the normalized difference vegetation index,enhanced vegetation index,and simple ratio.Structural equation modelling showed that VIs and community traits positively affected community function,whereas environmental drivers and specific leaf area had the opposite effect.Additionally,VIs integrated with environmental drivers were indirectly linked to community function by characterizing the variations in community structural and functional traits.This study demonstrates that community-level spectral reflectance will help scale plant trait information measured at the leaf level to larger-scale ecological processes.Field imaging spectroscopy represents a promising tool to predict the responses of alpine grassland communities to climate change.