Plant functional trait diversity and structural diversity co-underpin ecosystem multifunctionality in subtropical forests

Tree species diversity is assumed to be an important component in managing forest ecosystems because of effects on multiple functions or ecosystem multifunctionality.However,the importance of tree diversity in determining multifunctionality in structurally complex subtropical forests relative to other regulators(e.g.,soil microbial diversity,stand structure,and environmental conditions)remains uncertain.In this study,effects of aboveground(species richness and functional and structural diversity)and belowground(bacterial and fungal diversity)biodiversity,functional composition(community-weighted means of species traits),stand structure(diameter at breast height and stand density),and soil factors(pH and bulk density)on multifunctionality(including biomass production,carbon stock,and nutrient cycling)were examined along a tree diversity gradient in subtropical forests.The community-weighted mean of tree maximum height was the best predictor of ecosystem multifunctionality.Functional diversity explained a higher proportion of the variation in multifunctionality than that of species richness and fungal diversity.Stand structure-played an important role in modulating the effects of tree diversity on multifunctionality.The work highlights that species composition and maximizing forest structural complexity are effective strategies to increase forest multifunctionality while also conserving biodiversity in the management of multifunctional forests under global environmental changes.

Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships

The development of allometric biomass models is important process in biomass estimation because the reliability of forest biomass and carbon estimations largely depends on the accuracy and precision of such models.National Forest Inventories(NFI)are detailed assessments of forest resources at national and regional levels that provide valuable data for forest biomass estimation.However,the lack of biomass allometric equations for each tree species in the NFI currently hampers the estimation of national-scale forest biomass.The main objective of this study was to develop allometric biomass regression equations for each tree species in the NFI of China based on limited biomass observations.These equations optimally grouped NFI and biomass observation species according to their phylogenetic relationships.Significant phylogenetic signals demonstrated phylogenetic conservation of the crown-to-stem biomass ratio.Based on phylogenetic relationships,we grouped and matched NFI and biomass observation species into 22 categories.Allometric biomass regression models were developed for each of these 22 species categories,and the models performed successfully(R^(2)=0.97,root mean square error(RMSE)=12.9​t·ha^(–1),relative RMSE=11.5%).Furthermore,we found that phylogeny-based models performed more effectively than wood density-based models.The results suggest that grouping species based on their phylogenetic relationships is a reliable approach for the development and selection of accurate allometric equations.

Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years

Background: In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage(FCS) should first be clarified as much as possible,especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above-and below-ground biomass(AB biomass), so as to eliminate the significant bias in national scale estimations.Methods: We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density(WD), and converts the AB biomass from stem biomass by using allometric relationships.Results: Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges(relative errors: + 4.46% and-4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010 s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD(0.7 t·m-3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates.Conclusions: Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales.

Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Background:Vegetation phenology research has largely focused on temperate deciduous forests,thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions.Results:Using satellite solar-induced chlorophyll fluorescence(SIF)and MODIS enhanced vegetation index(EVI)data,we applied two methods to evaluate temporal and spatial patterns of the end of the growing season(EGS)in subtropical vegetation in China,and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation.Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods(dynamic threshold method and derivative method)was later than that derived from gross primary productivity(GPP)based on the eddy covariance technique,and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks,respectively.We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation(accounting for more than 73%and 62%of the study areas,respectively),but negatively correlated with preseason maximum temperature(accounting for more than 59%of the study areas).In addition,EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors,and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests,shrub and grassland.Conclusions:Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China.We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region.These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China,and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Management scheme influence and nitrogen addition effects on soil CO_(2),CH_(4),and N_(2)O fluxes in a Moso bamboo plantation

Background:It is still not clear whether the effects of N deposition on soil greenhouse gas(GHG)emissions are influenced by plantation management schemes.A field experiment was conducted to investigate the effects of conventional management(CM)versus intensive management(IM),in combination with simulated N deposition levels of control(ambient N deposition),30 kg N·ha^(−1)·year^(−1)(N30,ambient+30 kg N·ha^(−1)·year^(−1)),60 kg N·ha^(−1)·year^(−1)(N60,ambient+60 kg N·ha^(−1)·year^(−1)),or 90 kg N·ha^(−1)·year^(−1)(N90,ambient+90 kg N·ha^(−1)·year^(−1))on soil CO_(2),CH_(4),and N_(2)O fluxes.For this,24 plots were set up in a Moso bamboo(Phyllostachys edulis)plantation from January 2013 to December 2015.Gas samples were collected monthly from January 2015 to December 2015.Results:Compared with CM,IM significantly increased soil CO_(2) emissions and their temperature sensitivity(Q_(10))but had no significant effects on soil CH_(4) uptake or N_(2)O emissions.In the CM plots,N30 and N60 significantly increased soil CO_(2) emissions,while N60 and N90 significantly increased soil N_(2)O emissions.In the IM plots,N30 and N60 significantly increased soil CO_(2) and N_(2)O emissions,while N60 and N90 significantly decreased soil CH_(4) uptake.Overall,in both CM and IM plots,N30 and N60 significantly increased global warming potentials,whereas N90 did not significantly affect global warming potential.However,N addition significantly decreased the Q_(10) value of soil CO_(2) emissions under IM but not under CM.Soil microbial biomass carbon was significantly and positively correlated with soil CO_(2) and N_(2)O emissions but significantly and negatively correlated with soil CH_(4) uptake.Conclusion:Our results indicate that management scheme effects should be considered when assessing the effect of atmospheric N deposition on GHG emissions in bamboo plantations.

Biochar amendments increase soil organic carbon storage and decrease global warming potentials of soil CH4 and N2O under N addition in a subtropical Moso bamboo plantation

Background: Nitrogen(N) deposition affects soil greenhouse gas(GHG) emissions, while biochar application reduces GHG emissions in agricultural soils. However, it remains unclear whether biochar amendment can alleviate the promoting effects of N input on GHG emissions in forest soils. Here, we quantify the separate and combined effects of biochar amendment(0, 20, and 40 t·ha) and N addition(0, 30, 60, and 90 kg N·ha·yr) on soil GHG fluxes in a long-term field experiment at a Moso bamboo(Phyllostachys edulis) plantation.Results: Low and moderate N inputs(≤60 kg N·ha·yr) significantly increase mean annual soil carbon dioxide(CO) and nitrous oxide(NO) emissions by 17.0%–25.4% and 29.8%–31.2%, respectively, while decreasing methane(CH) uptake by 12.4%–15.9%, leading to increases in the global warming potential(GWP) of soil CHand NO fluxes by 32.4%–44.0%. Moreover, N addition reduces soil organic carbon(C;SOC) storage by 0.2%–6.5%. Compared to the control treatment, biochar amendment increases mean annual soil CO2emissions, CHuptake, and SOC storage by 18.4%–25.4%, 7.6%–15.8%, and 7.1%–13.4%, respectively, while decreasing NO emissions by 17.6%–19.2%, leading to a GWP decrease of 18.4%–21.4%. Biochar amendments significantly enhance the promoting effects of N addition on soil COemissions, while substantially offsetting the promotion of N2O emissions, inhibition of CHuptake, and decreased SOC storage, resulting in a GWP decrease of 9.1%–30.3%.Additionally, soil COand CHfluxes are significantly and positively correlated with soil microbial biomass C(MBC) and pH. Meanwhile, NO emissions have a significant and positive correlation with soil MBC and a negative correlation with pH.Conclusions: Biochar amendment can increase SOC storage and offset the enhanced GWP mediated by elevated N deposition and is, thus, a potential strategy for increasing soil C sinks and decreasing GWPs of soil CHand NO under increasing atmospheric N deposition in Moso bamboo plantations.

Responses of soil CH_(4) fluxes to nitrogen addition in two tropical montane rainforests in southern China

Background:Atmospheric nitrogen(N)deposition is projected to increase in the next few decades,which may have a marked impact on soil-atmosphere CH_(4) fluxes.However,the impacts of increased atmospheric N depositions on soil CH_(4) flux in tropical rainforests are still poorly understood.From January 2015 to December 2018,a field experiment was conducted in a primary tropical montane rainforest(PTMR)and a secondary tropical montane rainforest(STMR)in southern China to quantify the impact of N additions at four levels(N0:0 kg N⋅ha^(-1)⋅year^(-1);N25:25 kg N⋅ha^(-1)⋅year^(-1);N50:50 kg N⋅ha^(-1)⋅year^(-1);N100:100 kg N⋅ha^(-1)⋅year^(-1)on soil CH_(4) flux.Results:Four years of measurements showed clear seasonal variations in CH_(4) flux in all treatment plots for both forest types(PTMR and STMR),with lower rates of soil CH_(4) uptake during the wet season and higher rates of soil CH_(4) uptake during the dry season.Soil CH_(4) uptake rates were significantly and negatively correlated with both soil temperature and soil moisture for both forest types.Annual CH_(4) uptake for the N0 plots from the PTMR and STMR soils were2.20 and1.98 kg N⋅ha^(-1)⋅year^(-1),respectively.At the PTMR site,mean CH_(4) uptake compared with the N0 treatment was reduced by 19%,29%,and 36%for the N25,N50,and N100 treatments,respectively.At the STMR site,mean CH_(4) uptake compared with the N0 treatment was reduced by 15%,18%,and 38%for the N25,N50,and N100 treatments,respectively.High level N addition had a stronger inhibitory impact on soil CH_(4) uptake than did the low level N addition.Conclusion:Our data suggest that soil CH_(4) uptake in tropical rainforests is sensitive to N deposition.If atmospheric N deposition continues to increase in the future,the soil CH_(4) sink strength of tropical rainforests may weaken further.

Nitrous oxide emissions from three temperate forest types in the Qinling Mountains,China

To understand soil N2O fluxes from temperate forests in a climate-sensitive transitional zone,N2O emissions from three temperate forest types(Pinus tabulaeformis,PTT;Pinus armandii,PAT;and Quercus aliena var.acuteserrata,QAT)were monitored using the static closed-chamber method from June 2013 to May 2015 in the Huoditang Forest region of the Qinling Mountains,China.The results showed that these three forest types acted as N2O sources,releasing a mean combined level of 1.35±0.56 kg N2O ha^-1 a^-1,ranging from0.98±0.37 kg N2O ha^-1 a^-1 in PAT to 1.67±0.41 kg N2O ha^-1 a^-1 in QAT.N2O emission fluctuated seasonally,with highest levels during the summer for all three forest types.N2O flux had a significantly positive correlation with soil temperature at a depth of 5 cm or in the water-filled pore space,where the correlation was stronger for temperature than for the water-filled pore space.N2O flux was positively correlated with available soil nitrogen in QAT and PAT.Our results indicate that N2O flux is mainly controlled by soil temperature in the temperate forest in the Qinling Mountains.

Evaluating and quantifying the effect of various spruce budworm intervention strategies on forest carbon dynamics in Atlantic Canada

Spruce budworm (SBW) outbreaks are one of the most devastating natural disturbances in spruce-balsam fir forests of eastern North America. Both early intervention strategy (EIS) and foliage protection strategy (FP) are being tested to limit forest losses, but the quantitative impact on forest carbon (C) dynamics is still unclear. In this study, we designed 19 separate scenarios of no intervention or varying success of EIS, FP, and their combination on SBW caused defoliation and mortality. We then used the TRIPLEX-Insect model to quantify their effects on forest C dynamics in the forests of the four provinces of Atlantic Canada. A scenario applying FP to 10%of the area with the greatest potential C losses of living biomass, protecting foliage in 10%of the forests is more realistic than higher proportion of FP given the high cost and large areas involved, resulted in reducing average cumulative net ecosystem productivity (NEP) from 2020 to 2039 by 56%–127%compared to a no outbreak scenario.Our results showed that FP would have to be applied everywhere to reduce tree mortality and increase NEP more than 8 years of successful EIS applied. However, if EIS can be successfully implemented for 12 years, it will maintain more forest C than FP applied everywhere during a moderate outbreak. We also found that the combination of EIS followed by FP in 10%of the areas disturbed by the SBW could maintain average cumulative NEP at similar levels to no defoliation in every province of Atlantic Canada. Black/red spruce forests younger than 60years old underwent the smallest changes in C dynamics whether using EIS, FP, or both. This highlights the importance of forest species, forest age, and their interactions on the effectiveness of a treatment during SBW outbreak. Overall, 31%–76%of the study area in Atlantic Canada could convert from a C sink to a source by 2039,if no protective measures are used under the worst-case scenarios, thus contributing to future climate warming.

Evaluating soil nutrients of Dacrydium pectinatum in China using machine learning techniques

Background: The accurate estimation of soil nutrient content is particularly important in view of its impact on plant growth and forest regeneration. In order to investigate soil nutrient content and quality for the natural regeneration of Dacrydium pectinatum communities in China, designing advanced and accurate estimation methods is necessary.Methods: This study uses machine learning techniques created a series of comprehensive and novel models from which to evaluate soil nutrient content. Soil nutrient evaluation methods were built by using six support vector machines and four artificial neural networks.Results: The generalized regression neural network model was the best artificial neural network evaluation model with the smallest root mean square error(5.1), mean error(-0.85), and mean square prediction error(29). The accuracy rate of the combined k-nearest neighbors(k-NN) local support vector machines model(i.e. k-nearest neighbors-support vector machine(KNNSVM)) for soil nutrient evaluation was high, comparing to the other five partial support vector machines models investigated. The area under curve value of generalized regression neural network(0.6572) was the highest, and the cross-validation result showed that the generalized regression neural network reached 92.5%.Conclusions: Both the KNNSVM and generalized regression neural network models can be effectively used to evaluate soil nutrient content and quality grades in conjunction with appropriate model variables. Developing a new feasible evaluation method to assess soil nutrient quality for Dacrydium pectinatum, results from this study can be used as a reference for the adaptive management of rare and endangered tree species. This study, however, found some uncertainties in data acquisition and model simulations, which will be investigated in upcoming studies.

Carbon fluxes and soil carbon dynamics along a gradient of biogeomorphic succession in alpine wetlands of Tibetan Plateau

Hydrological changes under climate warming drive the biogeomorphic succession of wetlands and may trigger substantial carbon loss from the carbon-rich ecosystems.Although many studies have explored the responses of wetland carbon emissions to short-term hydrological change,it remains poorly understood how the carbon cycle evolves with hydrology-driven wetland succession.Here,we used a space-for-time approach across hydrological gradients on the Tibetan Plateau to examine the dynamics of ecosystem carbon fluxes(carbon dioxide(CO_(2))and methane(CH4))and soil organic carbon pools during alpine wetland succession.We found that the succession from mesic meadow to fen changed the seasonality of both CO_(2) and CH4 fluxes,which was related to the shift in plant community composition,enhanced regulation of soil hydrology and increasing contribution of spring-thaw emission.The paludification caused a switch from net uptake of gaseous carbon to net release on an annual timescale but produced a large accumulation of soil organic carbon.We attempted to attribute the paradox between evidence from the carbon fluxes and pools to the lateral carbon input and the systematic changes of historical climate,given that the wetlands are spatially low-lying with strong temporal climate-carbon cycle interactions.These findings demonstrate a systematic change in the carbon cycle with succession and suggest that biogeomorphic succession and lateral carbon flows are both important for understanding the long-term dynamics of wetland carbon footprints.

Soil microbial respiration is regulated by stoichiometric imbalances: Evidence from a humidity gradient case

Humidity not only affects soil microbial respiration(SMR) directly, but, indirectly by regulating the availability of soil water and nutrients. However,the patterns of direct and indirect effects of humidity on SMR over large precipitation gradients remain unclear, limiting our understanding of the effects of precipitation changes on soil C cycle. Here, we investigated the relationships among humidity, soil nutrients, and SMR by identifying stoichiometric imbalances, microbial elemental homeostasis, and microbial C use efficiency along a precipitation gradient at a continental scale. The relationship between SMR and humidity index(HI) corresponded to a Richard’s curve with an inflection point threshold value of approximately 0.7. Soil microbial respiration increased with increasing humidity in drier areas(HI < 0.7), but tended to balance above this threshold. Increasing humidity exacerbated C:P and N:P imbalances across the selected gradient. Severe N and P limitations in soil microbial communities were observed in drier areas, while soil microbes suffered from aggravated P limitation as the humidity increased in wetter areas(HI > 0.7). Soil microbial communities regulated their enzyme production to maintain a strong stoichiometric homeostasis in drier areas;enzyme production, microbial biomass, and threshold elemental ratios were non-homeostatic under P limitation in wetter areas, which further contributed to the increase in SMR. Our results identified a moisture constraint on SMR in drier areas and highlighted the importance of nutrient(especially for P) limitations induced by humidity in regulating SMR in wetter areas. Understanding the modulation of SMR via soil enzyme activity may improve the prediction of soil C budget under future global climate change.

Divergent response of vegetation phenology to extreme temperatures and precipitation of different intensities on the Tibetan Plateau

Quantifying how climate factors affect vegetation phenology is crucial for understanding climate-vegetation interactions and carbon and water cycles under a changing climate.However,the effects of different intensities of extreme climatic events on vegetation phenology remain poorly understood.Using a long-term solar-induced chlorophyll fluorescence dataset,we investigated the response of vegetation phenology to extreme temperatures and precipitation events of different intensities across the Tibetan Plateau(TP)from 2000 to 2018.We found that the effect of maximum temperature exposure days(TxED)and minimum temperature exposure days(TnED)on the start of the growing season(SOS)was initially delayed and shifted to advance along the increasing temperature gradients.However,the response of the end of the growing season(EOS)to TxED and TnED shifted from an advance to a delay with increasing temperature gradients until the temperature thresholds were reached,above which thresholds produced an unfavorable response to vegetation growth and brought the EOS to an early end.The corresponding maximum and minimum temperature thresholds were 10.12 and 2.54℃,respectively.In contrast,cumulative precipitation(CP)was more likely to advance SOS and delay EOS as the precipitation gradient increased,but the advance of SOS is gradually weakening.Four vegetation types(i.e.,forest,shrubland,meadow,and steppe)showed similar trends in response to different climates,but the optimal climatic conditions varied between the vegetation types.Generally,meadow and steppe had lower optimal temperatures and precipitation than forest and shrubland.These findings revealed the divergent responses of vegetation phenology to extreme climate events of different intensities,implying that the SOS will continue to advance with warming,whereas the EOS may undergo a partial transformation from delayed areas to advanced areas with continued warming.

Spatiotemporal analysis of the impact of urban landscape forms on PM_(2.5) in China from 2001 to 2020

Urban landscape forms can be effective in reducing increasing PM_(2.5) concentrations due to urbanization in China,making it crucially important to accurately quantify the spatiotemporal impact of urban landscape forms on PM_(2.5) variations.Three landscape indices and six control variables were selected to assess these impacts in 362 Chinese cities during different time scales from 2001 to 2020,using a spatiotemporal geographically weighted regression model,random forest models and partial dependence plots.The results show that there are spatiotemporal differences in the impacts of landscape indices on PM_(2.5).the proportion of urban green infrastructure(PLAND-UGI)and the fractal dimension of urban green infrastructure(FRACT-UGI)exacerbate PM_(2.5) concentrations in the northwest,the proportion of impervious surfaces(PLAND-Impervious)mitigates air pollution in northwest and southwest China,and shannon’s diversity index(SHDI)has seasonal differences in the northwest.PLAND-UGI is the landscape index with the largest contribution(30%)and interpretable range.The relationship between FRACT and PM_(2.5) was more complex than for other landscape indices.The results of this study contribute to a deeper understanding of the spatial and temporal differences in the impact of urban landscape patterns on PM_(2.5),contributing to clean urban development and sustainable development.

植物功能性状对动态全球植被模型改进研究进展

动态全球植被模型(dynamic global vegetation models,DGVMs)在模拟和预测陆地生态系统对气候变化响应中表现出很大的不确定性,重要原因之一在于动态全球植被模型将定义植物功能型的性状值设置为常数,忽略了植物功能性状对环境变化的响应.动态全球植被模型现有的植物功能型框架已经严重地阻碍了其发展,因此迫切需要一种新的方法来克服这种局限性.植物功能性状不仅可以反映植物对环境连续变化的响应,而且与生态系统的结构和功能密切相关,可提升当前动态全球植被模型对生态系统过程的模拟和功能的预测.本文从动态全球植被模型发展和植物功能型局限性入手,详细介绍了植物功能性状发展现状及其对动态全球植被模型改进的重要价值,归纳总结了植物功能性状对动态全球植被模型改进的主要方法,并指明植物功能性状对动态全球植被模型改进的发展方向.以期通过凝练植物功能性状在构建下一代动态全球植被模型中发挥作用,推动动态全球植被模型在我国的发展和应用.

Qinghai-tibetan plateau peatland sustainable utilization under anthropogenic disturbances and climate change

Often referred to as the“Third Pole,”China’s Qinghai-Tibetan Plateau developed large amounts of peatland owing to its unique alpine environment.As a renewable resource,peat helps to regulate the climate as well as performing other important functions.However,in recent years,intensifying climate change and anthropogenic disturbances have resulted in peatland degradation and consequently made sustainable development of peatland more difficult.This review summarizes peatland ecological and economic functions,including carbon sequestration,biodiversity conservation,energy supplies,and ecotourism.It identifies climate change and anthropogenic disturbances as the two key factors attributing to peatland degradation and ecosystem carbon loss.Current problems in environmental degradation and future challenges in peatland management under the effects of global warming are also discussed and highlighted.

Towards a paradigm for open and free sharing of scientific data on global change science in China

Despite great progress in data sharing that has been made in China in recent decades,cultural,policy,and technological challenges have prevented Chinese researchers from maximizing the availability of their data to the global change science community.To achieve full and open exchange and sharing of scientific data,Chinese research funding agencies need to recognize that preserva-tion of,and access to,digital data are central to their mission,and must support these tasks accord-ingly.The Chinese government also needs to develop better mechanisms,incentives,and rewards,while scientists need to change their behavior and culture to recognize the need to maximize the usefulness of their data to society as well as to other researchers.The Chinese research communi-ty and individual researchers should think globally and act personally to promote a paradigm of open,free,and timely data sharing,and to increase the effectiveness of knowledge development.

Integrating global socio-economic influences into a regional land use change model for China

With rapid economic development and urba- nization, land use in China has experienced huge changes in recent years; and this will probably continue in the future. Land use problems in China are urgent and need further study. Rapid land-use change and economic development make China an ideal region for integrated land use change studies, particularly the examination of multiple factors and global-regional interactions in the context of global economic integration. This paper presents an integrated modeling approach to examine the impact of global socio-economic processes on land use changes at a regional scale. We develop an integrated model system by coupling a simple global socio-economic model （GLOBFOOD） and regional spatial allocation model （CLUE）. The model system is illustrated with an application to land use in China. For a given climate change, population growth, and various socio-economic situations, a global socio-economic model simulates the impact of global market and economy on land use, and quantifies changes of different land use types. The land use spatial distribution model decides the type of land use most appropriate in each spatial grid by employing a weighted suitability index, derived from expert knowledge abot^t the ecosystem state and site conditions. A series of model simulations will be conducted and analyzed to demonstrate the ability of the integrated model to link global socio- economic factors with regional land use changes in China. The results allow an exploration of the future dynamics of land use and landscapes in China.

Nitrogen addition mediates the response of foliar stoichiometry to phosphorus addition: a meta-analysis

Background:Changes in foliar nitrogen(N)and phosphorus(P)stoichiometry play important roles in predicting the efects of global change on ecosystem structure and function.However,there is substantial debate on the efects of P addition on foliar N and P stoichiometry,particularly under diferent levels of N addition.Thus,we conducted a global meta-analysis to investigate how N addition alters the efects of P addition on foliar N and P stoichiometry across different rates and durations of P addition and plant growth types based on more than 1150 observations.Results:We found that P addition without N addition increased foliar N concentrations,whereas P addition with N addition had no efect.The positive efects of P addition on foliar P concentrations were greater without N addition than with N addition.Additionally,the efects of P addition on foliar N,P and N:P ratios varied with the rate and duration of P addition.In particular,short-term or low-dose P addition with and without N addition increased foliar N concentration,and the positive efects of short-term or low-dose P addition on foliar P concentrations were greater without N addition than with N addition.The responses of foliar N and P stoichiometry of evergreen plants to P addition were greater without N addition than with N addition.Moreover,regardless of N addition,soil P availability was more efective than P resorption efciency in predicting the changes in foliar N and P stoichiometry in response to P addition.Conclusions:Our results highlight that increasing N deposition might alter the response of foliar N and P stoichiometry to P addition and demonstrate the important efect of the experimental environment on the results.These results advance our understanding of the response of plant nutrient use efciency to P addition with increasing N deposition.

Young asian ecologists to lead the next century of ecology

The Ecological Society of America(ESA),the world’s largest ecological society,has celebrated its centennial anniversary,exhibiting the field’s past achievements and major milestones,and presenting future directions and challenges.As U.S.President Barack Obama said in his video speech to the Ecological Society of America.