Aims Although shrubs are an important component of forests,their role has not yet been considered in forest biodiversity experiments.In the biodiversity-ecosystem functioning(BEF)experiment with subtropical tree speci...Aims Although shrubs are an important component of forests,their role has not yet been considered in forest biodiversity experiments.In the biodiversity-ecosystem functioning(BEF)experiment with subtropical tree species in south-east China(BEF-China),we factorially combined tree with shrub species-diversity treatments.Here,we tested the hypotheses that shrub survival differs between the 10 planted shrub species,with lower survival rates of late-than early-successional species and is affected by environmental conditions,such as topography and top soil characteristics,as well as by biotic factors,represented by tree,shrub and herb layer characteristics.Methods We analyzed the survival of 42000 shrub individuals in 105 plots varying in tree and shrub species richness of the BEF-China project four years after planting.Shrub survival was analyzed with generalized linear mixed effects models at the level of individuals and with variance partitioning at the plot level.Random intercept and random slope models of different explanatory variables were compared with respect to the Bayesian Information Criterion(BIC).Important Findings Survival rates differed largely between the 10 shrub species,ranging from 26%to 91%for Ardisia crenata and Distylium buxifolium,respectively.Irrespective of species identity,single abiotic factors explained up to 5%of species survival,with a negative effect of altitude and slope inclination and a positive effect of the topsoil carbon to nitrogen ratio,which pointed to drought as the major cause of shrub mortality.In contrast,neither tree nor shrub richness affected shrub survival at this early stage of the experiment.Among the biotic predictors,only herb layer species richness and cover of the dominant fern species(Dicranopteris pedata)affected shrub survival.Overall,our models that included all variables could explain about 65%in shrub survival,with environmental variables being most influential,followed by shrub species identity,while tree species diversity(species richness and identity)and herb layer characteristics contributed much less.Thus,in this early stage of the experiment the biotic interactions among shrubs and between shrubs and trees have not yet overruled the impact of abiotic environmental factors.展开更多
Background:National forest inventories(NFI)have a long history providing data to obtain nationally representative and accurate estimates of growing stock.Today,in most NFIs additional data are collected to provide inf...Background:National forest inventories(NFI)have a long history providing data to obtain nationally representative and accurate estimates of growing stock.Today,in most NFIs additional data are collected to provide information on a range of forest ecosystem functions such as biodiversity,habitat,nutrient and carbon dynamics.An important driver of nutrient and C cycling is decomposing biomass produced by forest vegetation.Several studies have demonstrated that understory vegetation,particularly annual plant litter of the herb layer can contribute significantly to nutrient and C cycling in forests.A methodology to obtain comprehensive,consistent and nationally representative estimates of herb layer biomass on NFI plots could provide added value to NFIs by complementing the existing strong basis of biomass estimates of the tree and tall shrub layer.The study was based on data from the Swiss NFI since it covers a large environmental gradient,which extends its applicability to other NFIs.Results:Based on data from 405 measurements in nine forest strata,a parsimonious model formulation was identified to predict total and non-ligneous herb layer biomass.Besides herb layer cover,elevation was the main statistically significant explanatory variable for biomass.The regression models accurately predicted biomass based on absolute percentage cover(for total biomass:R2=0.65,p=0;for non-ligneous biomass:R2=0.76;p=0)as well as on cover classes(R2=0.83;p=0;and R2=0.79,p=0),which are typically used in NFIs.The good performance was supported by the verification with data from repeated samples.For the 2 nd,3 rd,and 4 th Swiss NFI estimates of non-ligneous above-ground herb layer biomass 586.6±7.7,575.2±7.6,and 586.7±7.9 kg·ha-1,respectively.Conclusions:The study presents a methodology to obtain herb layer biomass estimates based on a harmonized and standardized attribute available in many NFIs.The result of this study was a parsimonious model requiring only elevation data of sample plots in addition to NFI cover estimates to provide unbiased estimates at the national scale.These qualities are particularly important as they ensure accurate,consistent,and comparable results.展开更多
A study was conducted in the forest area of Chittagong （South） Forest Division, Chittagong, Bangladesh for developing al- lometric models to estimate biomass organic carbon stock in the forest vegetation. Allometric...A study was conducted in the forest area of Chittagong （South） Forest Division, Chittagong, Bangladesh for developing al- lometric models to estimate biomass organic carbon stock in the forest vegetation. Allometric models were tested separately for trees （divided into two DBH classes）, shrubs, herbs and grasses. Model using basal area alone was found to be the best predictor of biomass organic carbon stock in trees because of high coefficient of determination （r^2 is 0.73697 and 0.87703 for 〉 5 cm to ≤ 15 cm and 〉 15 cm DBH （diameter at breast height） rang, respectively） and significance of regression （P is 0.000 for each DBH range） coefficients for both DBH range. The other models using height alone; DBH alone; height and DBH together; height, DBH and wood density; with liner and logarithmic relations produced relatively poor coefficient of determination. The allometric models for dominant 20 tree species were also developed separately and equation using basal area produced higher value of determination of coefficient. Allometric model using total biomass alone for shrubs, herbs and grasses produced higher value of determination of coefficient and significance of regression coefficient （r^2 is 0.87948 and 0.87325 for shrubs, herbs and grasses, respectively and P is 0.000 for each）. The estimation of biomass organic carbon is a complicated and time consuming research. The allometric models developed in the present study can be utilized for future estimation of organic carbon stock in forest vegetation in Bangladesh as well as other tropical countries of the world.展开更多
基金financed by the German Research Foundation(DFG FOR 891/1,2,3)in a grant to H.B.(Br1698/10-3)the Sino-German Centre for Research Promotion in Beijing for travel grants and the participation in a summer school on scientific writing(GZ 785)support through the cooperation group“Linkages between plant diversity,microbial diversity and ecosystem functioning in subtropical forest”(GZ 986).
文摘Aims Although shrubs are an important component of forests,their role has not yet been considered in forest biodiversity experiments.In the biodiversity-ecosystem functioning(BEF)experiment with subtropical tree species in south-east China(BEF-China),we factorially combined tree with shrub species-diversity treatments.Here,we tested the hypotheses that shrub survival differs between the 10 planted shrub species,with lower survival rates of late-than early-successional species and is affected by environmental conditions,such as topography and top soil characteristics,as well as by biotic factors,represented by tree,shrub and herb layer characteristics.Methods We analyzed the survival of 42000 shrub individuals in 105 plots varying in tree and shrub species richness of the BEF-China project four years after planting.Shrub survival was analyzed with generalized linear mixed effects models at the level of individuals and with variance partitioning at the plot level.Random intercept and random slope models of different explanatory variables were compared with respect to the Bayesian Information Criterion(BIC).Important Findings Survival rates differed largely between the 10 shrub species,ranging from 26%to 91%for Ardisia crenata and Distylium buxifolium,respectively.Irrespective of species identity,single abiotic factors explained up to 5%of species survival,with a negative effect of altitude and slope inclination and a positive effect of the topsoil carbon to nitrogen ratio,which pointed to drought as the major cause of shrub mortality.In contrast,neither tree nor shrub richness affected shrub survival at this early stage of the experiment.Among the biotic predictors,only herb layer species richness and cover of the dominant fern species(Dicranopteris pedata)affected shrub survival.Overall,our models that included all variables could explain about 65%in shrub survival,with environmental variables being most influential,followed by shrub species identity,while tree species diversity(species richness and identity)and herb layer characteristics contributed much less.Thus,in this early stage of the experiment the biotic interactions among shrubs and between shrubs and trees have not yet overruled the impact of abiotic environmental factors.
基金supported financially by the Swiss Federal Office for the Environment(FOEN)(project monitoring by N.Rogiers,contract no.:06.0091.PZ/P043-0606)financial support from FOEN。
文摘Background:National forest inventories(NFI)have a long history providing data to obtain nationally representative and accurate estimates of growing stock.Today,in most NFIs additional data are collected to provide information on a range of forest ecosystem functions such as biodiversity,habitat,nutrient and carbon dynamics.An important driver of nutrient and C cycling is decomposing biomass produced by forest vegetation.Several studies have demonstrated that understory vegetation,particularly annual plant litter of the herb layer can contribute significantly to nutrient and C cycling in forests.A methodology to obtain comprehensive,consistent and nationally representative estimates of herb layer biomass on NFI plots could provide added value to NFIs by complementing the existing strong basis of biomass estimates of the tree and tall shrub layer.The study was based on data from the Swiss NFI since it covers a large environmental gradient,which extends its applicability to other NFIs.Results:Based on data from 405 measurements in nine forest strata,a parsimonious model formulation was identified to predict total and non-ligneous herb layer biomass.Besides herb layer cover,elevation was the main statistically significant explanatory variable for biomass.The regression models accurately predicted biomass based on absolute percentage cover(for total biomass:R2=0.65,p=0;for non-ligneous biomass:R2=0.76;p=0)as well as on cover classes(R2=0.83;p=0;and R2=0.79,p=0),which are typically used in NFIs.The good performance was supported by the verification with data from repeated samples.For the 2 nd,3 rd,and 4 th Swiss NFI estimates of non-ligneous above-ground herb layer biomass 586.6±7.7,575.2±7.6,and 586.7±7.9 kg·ha-1,respectively.Conclusions:The study presents a methodology to obtain herb layer biomass estimates based on a harmonized and standardized attribute available in many NFIs.The result of this study was a parsimonious model requiring only elevation data of sample plots in addition to NFI cover estimates to provide unbiased estimates at the national scale.These qualities are particularly important as they ensure accurate,consistent,and comparable results.
文摘A study was conducted in the forest area of Chittagong （South） Forest Division, Chittagong, Bangladesh for developing al- lometric models to estimate biomass organic carbon stock in the forest vegetation. Allometric models were tested separately for trees （divided into two DBH classes）, shrubs, herbs and grasses. Model using basal area alone was found to be the best predictor of biomass organic carbon stock in trees because of high coefficient of determination （r^2 is 0.73697 and 0.87703 for 〉 5 cm to ≤ 15 cm and 〉 15 cm DBH （diameter at breast height） rang, respectively） and significance of regression （P is 0.000 for each DBH range） coefficients for both DBH range. The other models using height alone; DBH alone; height and DBH together; height, DBH and wood density; with liner and logarithmic relations produced relatively poor coefficient of determination. The allometric models for dominant 20 tree species were also developed separately and equation using basal area produced higher value of determination of coefficient. Allometric model using total biomass alone for shrubs, herbs and grasses produced higher value of determination of coefficient and significance of regression coefficient （r^2 is 0.87948 and 0.87325 for shrubs, herbs and grasses, respectively and P is 0.000 for each）. The estimation of biomass organic carbon is a complicated and time consuming research. The allometric models developed in the present study can be utilized for future estimation of organic carbon stock in forest vegetation in Bangladesh as well as other tropical countries of the world.
