The ecological concept of Plant Functional Types（PFTs）, which refers to the assemblage of plants with certain functional traits, has been introduced for the study of plant responses to the environment change and hum...The ecological concept of Plant Functional Types（PFTs）, which refers to the assemblage of plants with certain functional traits, has been introduced for the study of plant responses to the environment change and human disturbance. Taking the alpine meadow community in the Zoigê Plateau as a study case, this paper classified PFTs in terms of plant nutrition traits. The sequential results are as follows.（1） The main herbages in the Zoigê Plateau included 16 species in 5 families. Among the five families, Cyperaceae vegetation accounted for 81.37%of herbage area in total, while the remaining 4families occupied less than 20%. As for the species,Kobresia setchwanensis Hand.-Maizz. was dominant,accounting for 48.74% of the total area; while the remaining 51.26% was comprised of Polygonum viviparum L., Anaphalis fiavescens Hand.-Mazz.,Stipa aliena Keng and other species.（2） By using the Principal Component Analysis（PCA）, the assessment of herbages nutrition was carried out based on the comprehensive multi-index evaluation model.Polygonum viviparum L. had the highest nutritional value score（1.43）, and Stipa aliena Keng had the lowest（-1.40）. Nutritional value of herbage species had a significantly positive correlation with altitude（P＆lt;0.01） in the Zoigê Plateau.（3） Based on the nutritional values, herbages in the Zoigê Plateau could be grouped into 3 nutrition PFTs（high, medium and low） by using the Natural Breaks（Jenks） method.展开更多
Tree mortality significantly influences forest structure and function,yet our understanding of its dynamic patterns among a range of tree sizes and among different plant functional types(PFTs)remains incomplete.This s...Tree mortality significantly influences forest structure and function,yet our understanding of its dynamic patterns among a range of tree sizes and among different plant functional types(PFTs)remains incomplete.This study analysed size-dependent tree mortality in a temperate forest,encompassing 46 tree species and 32,565 individuals across different PFTs(i.e.,evergreen conifer vs.deciduous broadleaf species,shade-tolerant vs.shade-intolerant species).By employing all-subset regression procedures and logistic generalized linear mixed-effects models,we identified distinct mortality patterns influenced by biotic and abiotic factors.Our results showed a stable mortality patte rn in eve rgreen conifer species,contrasted by a declining pattern in deciduous broadleaf and shadetolerant,as well as shade-intolerant species,across size classes.The contribution to tree mortality of evergreen conifer species shifted from abiotic to biotic factors with increasing size,while the mortality of deciduous broadleaf species was mainly influenced by biotic factors,such as initial diameter at breast height(DBH)and conspecific negative density.For shade-tolerant species,the mortality of small individuals was mainly determined by initial DBH and conspecific negative density dependence,whereas the mortality of large individuals was subjected to the combined effect of biotic(competition from neighbours)and abiotic factors(i.e.,convexity and pH).As for shade-intolerant species,competition from neighbours was found to be the main driver of tree mortality throughout their growth stages.Thus,these insights enhance our understanding of forest dynamics by revealing the size-dependent and PFT-specific tree mortality patterns,which may inform strategies for maintaining forest diversity and resilience in temperate forest ecosystems.展开更多
Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings we...Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types(PFTs)and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.展开更多
Carbon (C) quality of non-leaf litter is closely related to decomposition rate and plays a vital role in terrestrial ecosystem C sequestration.However,to date,the global patterns and influencing factors of non-leaf li...Carbon (C) quality of non-leaf litter is closely related to decomposition rate and plays a vital role in terrestrial ecosystem C sequestration.However,to date,the global patterns and influencing factors of non-leaf litter C quality remain unclear.Here,using meta-analysis method,we quantified the characteristics and driving factors of the initial C quality of non-leaf litter (bark,branch,flower,fruit,root,stem,and wood) with 996 observations collected from 279 independent publications,including the concentrations of total C,lignin,cellulose,and hemicellulose.Results showed that (1) only total C and cellulose concentrations significantly varied among different types of non-leaf litter;(2) C quality is higher (i.e.,lower concentration) in bark,branch,root,stem and wood litter from angiosperms than gymnosperms,from herbaceous than woody plants,from broadleaved than coniferous trees,and from arbuscular mycorrhizal (AM) than ectomycorrhizal (ECM) plants (except for hemicellulose concentration);and (3) the impacts of different geographic features on C quality of non-leaf litter differed among different litter types,while soil properties generally exhibited strong impacts.Overall,our results clearly show the global patterns of C quality and associated influencing factors for different types of non-leaf litter,which would be helpful for a better understanding of role of non-leaf litter in terrestrial ecosystem C cycling and for the improvement of C cycling models.展开更多
Climate-induced shifts in the composition and structure of alpine vegetation cover,both expansion and reduction,are altering alpine ecosystem functions.However,accurately quantifying variations over large-scale region...Climate-induced shifts in the composition and structure of alpine vegetation cover,both expansion and reduction,are altering alpine ecosystem functions.However,accurately quantifying variations over large-scale regions requires a detailed characterization of the fine-scale mosaic vegetation covers.In this study,we employed a regression-based unmixing model using synthetic data to develop a multi-temporal machine learning model aimed to esti-mate the fractions of alpine plant functional types(PFTs)from 1984 to 2024 in the Yarlung Zangbo River Basin(YZRB),China.The estimated cover fractions for tree cover,shrub cover and herbac-eous cover had mean absolute errors of 10.36%,14.06%and 13.38%,respectively.The variations in the fractions of each alpine PFT revealed a slight increase in tree cover and shrub cover,along-side a contraction in herbaceous cover.Specifically,tree cover and shrub cover expanded by+1.54%and+1.83%per decade,respec-tively,while herbaceous cover declined at a rate of 1.98%per decade.These variations were predominantly observed at higher elevations(4000-6000 m),on shaded aspects,and on lower slopes.The variations in these fractions are also positively correlated with air temperature and soil moisture in most regions.This study pro-vides new insights into vegetation cover shifts in this ecologically sensitive region.展开更多
We conducted a systematic census of leaf N for 102 plant species at 112 research sites along the North-South Transect of Eastern China （NSTEC） following the same protocol, to explore how plant functional types （PFT...We conducted a systematic census of leaf N for 102 plant species at 112 research sites along the North-South Transect of Eastern China （NSTEC） following the same protocol, to explore how plant functional types （PFTs） and environmental factors affect the spatial pattern of leaf N. The results showed that mean leaf N was 17.7 mg g^-1 for all plant species. The highest and lowest leaf N were found in deciduous-broadleaf and evergreen-conifer species, respectively, and the ranking of leaf N from high to low was： deciduous 〉 evergreen species, broadleaf 〉 coniferous species, shrubs ≈ trees 〉 grasses. For all data pooled, leaf N showed a convex quadratic response to mean annual temperature （MAT）, and a negative linear relationship with mean annual precipitation （MAP）, but a positive linear relationship with soil nitrogen concentration （Nsoil）. These patterns were similar when PFTs were examined individually. Importantly, PFTs, climate and Nsoil, jointly explained 46.1% of the spatial variation in leaf N, of which the independent explanatory powers of PFTs, climate and Nsoil, were 15.6%, 2.3% and 4.7%, respectively. Our findings suggest that leaf N is regulated by climate and Nsoil, mainly via plant species composition. The wide scale empirical relationships developed here are useful for understanding and modeling of the effects of PFTs and environmental factors on leaf N.展开更多
Land use projections are crucial for climate models to forecast the impacts of land use changes on the Earth’s system.However,the spatial resolution of existing global land use projections(e.g.,0.25°×0.25&#...Land use projections are crucial for climate models to forecast the impacts of land use changes on the Earth’s system.However,the spatial resolution of existing global land use projections(e.g.,0.25°×0.25°in the Land-Use Harmonization(LUH2)datasets)is still too coarse to drive regional climate models and assess mitigation effectiveness at regional and local scales.To generate a high-resolution land use product with the newest integrated scenarios of the shared socioeconomic pathways and the representative concentration pathways(SSPs-RCPs)for various regional climate studies in China,here we first conduct land use simulations with a newly developed Future Land Uses Simulation(FLUS)model based on the trajectories of land use demands extracted from the LUH2 datasets.On this basis,a new set of land use projections under the plant functional type(PFT)classification,with a temporal resolution of 5 years and a spatial resolution of 5 km,in eight SSP-RCP scenarios from 2015 to 2100 in China is produced.The results show that differences in land use dynamics under different SSP-RCP scenarios are jointly affected by global assumptions and national policies.Furthermore,with improved spatial resolution,the data produced in this study can sufficiently describe the details of land use distribution and better capture the spatial heterogeneity of different land use types at the regional scale.We highlight that these new land use projections at the PFT level have a strong potential for reducing uncertainty in the simulation of regional climate models with finer spatial resolutions.展开更多
The identification of easily measured plant functional types (PFTs) that consistently predict grazing response would be a major advance.The responses to grazing of individual traits and PFTs were analyzed along a graz...The identification of easily measured plant functional types (PFTs) that consistently predict grazing response would be a major advance.The responses to grazing of individual traits and PFTs were analyzed along a grazing gradient in an alpine shrub meadow on the Qinghai-Tibet Plateau,China.Three response types were identified;grazing increaser (GI),grazing decreaser (GD),and neutral (NE) for both traits and PFTs.Seven traits were measured:plant height,economic group,cotyledon type,plant inclination,growth form,life cycle,and vegetative structure.The first five were significantly affected by grazing.Ordinal regressions for grazing response of the seven traits showed that the best single predictors of response were growth form (including the attributes "Scattered","Bunched" or "Closely Bunched"),and plant inclination ("Rosette","Prostrate",or "Erect"),followed by economic group ("Shrub","Grass","Sedge","Legume","Forb",or "Harmful") and plant height ("Tall","Medium",or "Small").Within the four optimal traits,the summed dominance ratio (SDR) of small plants,forbs,rosette and bunched plants,invariably increased,while that of tall plants,shrubs,grasses,and erect plants decreased,when grazing pressure was enhanced.Canonical correspondence analysis (CCA) identified eleven explanatory PFTs based on 195 defined PFTs,by combining the different attributes of the four optimal traits.Among explanatory PFTs,the most valuable in predicting the community response to grazing were Tall×Shrub×Erect×Scattered and Small×Forb×Rosette,as these have the closest connections with grazing disturbance and include fewer species.Species richness,diversity,and community evenness,did not differ among grazing treatments because turnover occurred in component species and their relative abundances along the grazing gradient.We have demonstrated that a minimum set of PFTs resulting from optimal individual traits can provide consistent prediction of community responses to grazing in this region.This approach provides a more accurate indicator of change within a changing environment than do univariate measures of species diversity.We hope to provide a link between management practices and vegetation structure,forming a basis for future,large scale,plant trait comparisons.展开更多
基金supported by the sub topics of National Key Technology R&D Program (Grant No. 2015BAC05B05-01)
文摘The ecological concept of Plant Functional Types（PFTs）, which refers to the assemblage of plants with certain functional traits, has been introduced for the study of plant responses to the environment change and human disturbance. Taking the alpine meadow community in the Zoigê Plateau as a study case, this paper classified PFTs in terms of plant nutrition traits. The sequential results are as follows.（1） The main herbages in the Zoigê Plateau included 16 species in 5 families. Among the five families, Cyperaceae vegetation accounted for 81.37%of herbage area in total, while the remaining 4families occupied less than 20%. As for the species,Kobresia setchwanensis Hand.-Maizz. was dominant,accounting for 48.74% of the total area; while the remaining 51.26% was comprised of Polygonum viviparum L., Anaphalis fiavescens Hand.-Mazz.,Stipa aliena Keng and other species.（2） By using the Principal Component Analysis（PCA）, the assessment of herbages nutrition was carried out based on the comprehensive multi-index evaluation model.Polygonum viviparum L. had the highest nutritional value score（1.43）, and Stipa aliena Keng had the lowest（-1.40）. Nutritional value of herbage species had a significantly positive correlation with altitude（P＆lt;0.01） in the Zoigê Plateau.（3） Based on the nutritional values, herbages in the Zoigê Plateau could be grouped into 3 nutrition PFTs（high, medium and low） by using the Natural Breaks（Jenks） method.
基金supported by the China Postdoctoral Science Foundation (No.2023M733712)the National Natural Science Foundation of China (No.31971491)。
文摘Tree mortality significantly influences forest structure and function,yet our understanding of its dynamic patterns among a range of tree sizes and among different plant functional types(PFTs)remains incomplete.This study analysed size-dependent tree mortality in a temperate forest,encompassing 46 tree species and 32,565 individuals across different PFTs(i.e.,evergreen conifer vs.deciduous broadleaf species,shade-tolerant vs.shade-intolerant species).By employing all-subset regression procedures and logistic generalized linear mixed-effects models,we identified distinct mortality patterns influenced by biotic and abiotic factors.Our results showed a stable mortality patte rn in eve rgreen conifer species,contrasted by a declining pattern in deciduous broadleaf and shadetolerant,as well as shade-intolerant species,across size classes.The contribution to tree mortality of evergreen conifer species shifted from abiotic to biotic factors with increasing size,while the mortality of deciduous broadleaf species was mainly influenced by biotic factors,such as initial diameter at breast height(DBH)and conspecific negative density.For shade-tolerant species,the mortality of small individuals was mainly determined by initial DBH and conspecific negative density dependence,whereas the mortality of large individuals was subjected to the combined effect of biotic(competition from neighbours)and abiotic factors(i.e.,convexity and pH).As for shade-intolerant species,competition from neighbours was found to be the main driver of tree mortality throughout their growth stages.Thus,these insights enhance our understanding of forest dynamics by revealing the size-dependent and PFT-specific tree mortality patterns,which may inform strategies for maintaining forest diversity and resilience in temperate forest ecosystems.
基金Funding for this study was provided by the U.S. National Science Foundation Hydrological Science grant 1521238the U.S. Department of Energy's Office of Science Office of Biological and Environmental Research,Terrestrial Ecosystem Sciences Program Award No. DE-SC0007041Ameriflux Management Project Core Site Agreement No. 7096915
文摘Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types(PFTs)and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.
基金supported by the National Natural Science Foundation of China (32201342)the State Key Laboratory of Subtropical Silviculture (SKLSS-KF2024-02)the Natural Science Foundation of Fujian Province (2022J01642)。
文摘Carbon (C) quality of non-leaf litter is closely related to decomposition rate and plays a vital role in terrestrial ecosystem C sequestration.However,to date,the global patterns and influencing factors of non-leaf litter C quality remain unclear.Here,using meta-analysis method,we quantified the characteristics and driving factors of the initial C quality of non-leaf litter (bark,branch,flower,fruit,root,stem,and wood) with 996 observations collected from 279 independent publications,including the concentrations of total C,lignin,cellulose,and hemicellulose.Results showed that (1) only total C and cellulose concentrations significantly varied among different types of non-leaf litter;(2) C quality is higher (i.e.,lower concentration) in bark,branch,root,stem and wood litter from angiosperms than gymnosperms,from herbaceous than woody plants,from broadleaved than coniferous trees,and from arbuscular mycorrhizal (AM) than ectomycorrhizal (ECM) plants (except for hemicellulose concentration);and (3) the impacts of different geographic features on C quality of non-leaf litter differed among different litter types,while soil properties generally exhibited strong impacts.Overall,our results clearly show the global patterns of C quality and associated influencing factors for different types of non-leaf litter,which would be helpful for a better understanding of role of non-leaf litter in terrestrial ecosystem C cycling and for the improvement of C cycling models.
基金supported by the National Natural Science Foundation of China(U22A20567)CAS-ANSO Sustainable Development Research Project(CAS-ANSO-SDRP-2024-04 and CAS-ANSO-SDRP-2024-08)+2 种基金the Sino-Africa Joint Research Center,CAS,China(SAJC202403)the International Science and Technology Cooperation Project of Hubei Province,China(2024EHA035)the Youth Project of Natural Science Foundation of Hubei Province,China(2025AFB393).
文摘Climate-induced shifts in the composition and structure of alpine vegetation cover,both expansion and reduction,are altering alpine ecosystem functions.However,accurately quantifying variations over large-scale regions requires a detailed characterization of the fine-scale mosaic vegetation covers.In this study,we employed a regression-based unmixing model using synthetic data to develop a multi-temporal machine learning model aimed to esti-mate the fractions of alpine plant functional types(PFTs)from 1984 to 2024 in the Yarlung Zangbo River Basin(YZRB),China.The estimated cover fractions for tree cover,shrub cover and herbac-eous cover had mean absolute errors of 10.36%,14.06%and 13.38%,respectively.The variations in the fractions of each alpine PFT revealed a slight increase in tree cover and shrub cover,along-side a contraction in herbaceous cover.Specifically,tree cover and shrub cover expanded by+1.54%and+1.83%per decade,respec-tively,while herbaceous cover declined at a rate of 1.98%per decade.These variations were predominantly observed at higher elevations(4000-6000 m),on shaded aspects,and on lower slopes.The variations in these fractions are also positively correlated with air temperature and soil moisture in most regions.This study pro-vides new insights into vegetation cover shifts in this ecologically sensitive region.
基金supported by the National Key Research and Development Program (2010CB833504)the CAS Strategic Priority Research Program (XDA05050602)
文摘We conducted a systematic census of leaf N for 102 plant species at 112 research sites along the North-South Transect of Eastern China （NSTEC） following the same protocol, to explore how plant functional types （PFTs） and environmental factors affect the spatial pattern of leaf N. The results showed that mean leaf N was 17.7 mg g^-1 for all plant species. The highest and lowest leaf N were found in deciduous-broadleaf and evergreen-conifer species, respectively, and the ranking of leaf N from high to low was： deciduous 〉 evergreen species, broadleaf 〉 coniferous species, shrubs ≈ trees 〉 grasses. For all data pooled, leaf N showed a convex quadratic response to mean annual temperature （MAT）, and a negative linear relationship with mean annual precipitation （MAP）, but a positive linear relationship with soil nitrogen concentration （Nsoil）. These patterns were similar when PFTs were examined individually. Importantly, PFTs, climate and Nsoil, jointly explained 46.1% of the spatial variation in leaf N, of which the independent explanatory powers of PFTs, climate and Nsoil, were 15.6%, 2.3% and 4.7%, respectively. Our findings suggest that leaf N is regulated by climate and Nsoil, mainly via plant species composition. The wide scale empirical relationships developed here are useful for understanding and modeling of the effects of PFTs and environmental factors on leaf N.
基金the National Key Research&Development Program of China(2019YFA0607203,2017YFA0604404)the National Natural Science Foundation of China(41901327,41671398,41871318)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(2019A1515010823)the Fundamental Research Funds for the Central Universities(19lgpy41)Natural Resources of the People’s Republic of China(GS(2020)2879)。
文摘Land use projections are crucial for climate models to forecast the impacts of land use changes on the Earth’s system.However,the spatial resolution of existing global land use projections(e.g.,0.25°×0.25°in the Land-Use Harmonization(LUH2)datasets)is still too coarse to drive regional climate models and assess mitigation effectiveness at regional and local scales.To generate a high-resolution land use product with the newest integrated scenarios of the shared socioeconomic pathways and the representative concentration pathways(SSPs-RCPs)for various regional climate studies in China,here we first conduct land use simulations with a newly developed Future Land Uses Simulation(FLUS)model based on the trajectories of land use demands extracted from the LUH2 datasets.On this basis,a new set of land use projections under the plant functional type(PFT)classification,with a temporal resolution of 5 years and a spatial resolution of 5 km,in eight SSP-RCP scenarios from 2015 to 2100 in China is produced.The results show that differences in land use dynamics under different SSP-RCP scenarios are jointly affected by global assumptions and national policies.Furthermore,with improved spatial resolution,the data produced in this study can sufficiently describe the details of land use distribution and better capture the spatial heterogeneity of different land use types at the regional scale.We highlight that these new land use projections at the PFT level have a strong potential for reducing uncertainty in the simulation of regional climate models with finer spatial resolutions.
基金supported by National Natural Science Foundation of China (Grant Nos. 30671490, and 31070382)
文摘The identification of easily measured plant functional types (PFTs) that consistently predict grazing response would be a major advance.The responses to grazing of individual traits and PFTs were analyzed along a grazing gradient in an alpine shrub meadow on the Qinghai-Tibet Plateau,China.Three response types were identified;grazing increaser (GI),grazing decreaser (GD),and neutral (NE) for both traits and PFTs.Seven traits were measured:plant height,economic group,cotyledon type,plant inclination,growth form,life cycle,and vegetative structure.The first five were significantly affected by grazing.Ordinal regressions for grazing response of the seven traits showed that the best single predictors of response were growth form (including the attributes "Scattered","Bunched" or "Closely Bunched"),and plant inclination ("Rosette","Prostrate",or "Erect"),followed by economic group ("Shrub","Grass","Sedge","Legume","Forb",or "Harmful") and plant height ("Tall","Medium",or "Small").Within the four optimal traits,the summed dominance ratio (SDR) of small plants,forbs,rosette and bunched plants,invariably increased,while that of tall plants,shrubs,grasses,and erect plants decreased,when grazing pressure was enhanced.Canonical correspondence analysis (CCA) identified eleven explanatory PFTs based on 195 defined PFTs,by combining the different attributes of the four optimal traits.Among explanatory PFTs,the most valuable in predicting the community response to grazing were Tall×Shrub×Erect×Scattered and Small×Forb×Rosette,as these have the closest connections with grazing disturbance and include fewer species.Species richness,diversity,and community evenness,did not differ among grazing treatments because turnover occurred in component species and their relative abundances along the grazing gradient.We have demonstrated that a minimum set of PFTs resulting from optimal individual traits can provide consistent prediction of community responses to grazing in this region.This approach provides a more accurate indicator of change within a changing environment than do univariate measures of species diversity.We hope to provide a link between management practices and vegetation structure,forming a basis for future,large scale,plant trait comparisons.
