Co-occurrence Patterns of Above-ground and Below-ground Mite Communities in Farmland of Sanjiang Plain, Northeast China

One of the fundamental questions in community ecology is whether communities are random or formed by deterministic mechanisms. Although many efforts have been made to verify non-randomness in community structure, little is known with regard to co-occurrence patterns in above-ground and below-ground communities. In this paper, we used a null model to test non-randomness in the structure of the above-ground and below-ground mite communities in farmland of the Sanjiang Plain, Northeast China. Then, we used four tests for non-randomness to recognize species pairs that would be demonstrated as significantly aggregated or segregated co-occurrences of the above-ground and below-ground mite communities. The pattern of the above-ground mite commu- nity was significantly non-random in October, suggesting species segregation and hence interspecific competition. Additionally, species co-occurrence patterns did not differ from randomness in the above-ground mite community in August or in below-ground mite com- munities in August and October. Only one significant species pair was detected in the above-ground mite community in August, while no significant species pairs were recognized in the above-ground mite community in October or in the below-ground mite communities in August and October. The results indicate that non-randomness and significant species pairs may not be the general rule in the above-ground and below-ground mite communities in farmland of the Sanjiang Plain at the fine scale.

Biomass and dominance of conservative species drive above-ground biomass productivity in a mediterranean-type forest of Chile

Background: Forest productivity has a pivotal role in human well-being. Vegetation quantity, niche complementarity, mass-ratio, and soil resources are alternative/complementary ecological mechanisms driving productivity. One challenge in current forest management depends on identifying and manipulating these mechanisms to enhance productivity. This study assessed the extent to which these mechanisms control aboveground biomass productivity(AGBP) of a Chilean mediterranean-type matorral. AGBP measured as tree aboveground biomass changes over a 7-years period, was estimated for twelve 25 m × 25 m plots across a wide range of matorral compositions and structures. Variables related to canopy structure, species and functional diversity, species and functional dominance, soil texture, soil water and soil nitrogen content were measured as surrogates of the four mechanisms proposed. Linear regression models were used to test the hypotheses. A multimodel inference based on the Akaike’s information criterion was used to select the best models explaining AGBP and for identifying the relative importance of each mechanism.Results: Vegetation quantity(tree density) and mass-ratio(relative biomass of Cryptocarya alba, a conservative species) were the strongest drivers increasing AGBP, while niche complementarity(richness species) and soil resources(sand, %) had a smaller effect either decreasing or increasing AGBP, respectively. This study provides the first assessment of alternative mechanisms driving AGBP in mediterranean forests of Chile. There is strong evidence suggesting that the vegetation quantity and mass-ratio mechanisms are key drivers of AGBP, such as in other tropical and temperate forests. However, in contrast with other studies from mediterranean-type forests, our results show a negative effect of species diversity and a small effect of soil resources on AGBP.Conclusion: AGBP in the Chilean matorral depends mainly on the vegetation quantity and mass-ratio mechanisms.The findings of this study have implications for matorral restoration and management for the production of timber and non-timber products and carbon sequestration.

Global patterns in above-ground net primary production and precipitation-use efficiency in grasslands

The above-ground net primary production(ANPP) and the precipitation-use efficiency(PUE) regulate the carbon and water cycles in grassland ecosystems, but the relationships among the ANPP, PUE and precipitation are still controversial. We selected 717 grassland sites with ANPP and mean annual precipitation(MAP) data from 40 publications to characterize the relationships ANPP–MAP and PUE–MAP across different grassland types. The MAP and ANPP showed large variations across all grassland types, ranging from 69 to 2335 mm and 4.3 to 1706 g m^(-2), respectively. The global maximum PUE ranged from 0.19 to 1.49 g m^(-2) mm^(-1) with a unimodal pattern. Analysis using the sigmoid function explained the ANPP–MAP relationship best at the global scale. The gradient of the ANPP–MAP graph was small for arid and semi-arid sites(MAP <400 mm). This study improves our understanding of the relationship between ANPP and MAP across dry grassland ecosystems. It provides new perspectives on the prediction and modeling of variations in the ANPP for different grassland types along precipitation gradients.

Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests

Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression （PLSR） models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM＋ data. The established models were optimized according to the variable importance for projection （VIP） criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test （p〈0.05）. The simplified models without insignificant variables （VIP 〈1） performed as well as the full model but with less computation time. The relative root mean square error （RMSE%） was 29% for canopy closure density, and 58% for above ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above ground biomass.

Estimating above-ground biomass by fusion of LiDAR and multispectral data in subtropical woody plant communities in topographically complex terrain in North-eastern Australia

We investigated a strategy to improve predicting capacity of plot-scale above-ground biomass （AGB） by fusion of LiDAR and Land- sat5 TM derived biophysical variables for subtropical rainforest and eucalypts dominated forest in topographically complex landscapes in North-eastern Australia. Investigation was carried out in two study areas separately and in combination. From each plot of both study areas, LiDAR derived structural parameters of vegetation and reflectance of all Landsat bands, vegetation indices were employed. The regression analysis was carded out separately for LiDAR and Landsat derived variables indi- vidually and in combination. Strong relationships were found with LiDAR alone for eucalypts dominated forest and combined sites compared to the accuracy of AGB estimates by Landsat data. Fusing LiDAR with Landsat5 TM derived variables increased overall performance for the eucalypt forest and combined sites data by describing extra variation （3% for eucalypt forest and 2% combined sites） of field estimated plot-scale above-ground biomass. In contrast, separate LiDAR and imagery data, andfusion of LiDAR and Landsat data performed poorly across structurally complex closed canopy subtropical minforest. These findings reinforced that obtaining accurate estimates of above ground biomass using remotely sensed data is a function of the complexity of horizontal and vertical structural diversity of vegetation.

Estimation of the Above-ground Biomass of Tamarix Species along a Transect at the Tarim River's Middle Reaches

[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in this area.[Method] By dint of the most common sampling method PCQ,five samples in the middle reaches of Tarim River were collected.The best-fit linear-regression model of Tamarix species of this area was set up,based on the fieldwork and the model of Evangelista and obtained the distribution rules of Tamarix species of Tarim River＇s middle reaches.[Result] The result indicated that this model fitted for the estimation of aboveground biomass of the study area.According to the distribution rules of aboveground biomass,it was clear that underground water was the major element which decided the distribution of aboveground biomass.[Conclusion] The study provided theoretical basis for the calculation of biomass of Tamarix.

Plant cover as an estimator of above-ground biomass in semi-arid woody vegetation in Northeast Patagonia,Argentina

The quantification of carbon storage in vegetation biomass is a crucial factor in the estimation and mitigation of CO2 emissions.Globally,arid and semi-arid regions are considered an important carbon sink.However,they have received limited attention and,therefore,it should be a priority to develop tools to quantify biomass at the local and regional scales.Individual plant variables,such as stem diameter and crown area,were reported to be good predictors of individual plant weight.Stand-level variables,such as plant cover and mean height,are also easy-to-measure estimators of above-ground biomass(AGB)in dry regions.In this study,we estimated the AGB in semi-arid woody vegetation in Northeast Patagonia,Argentina.We evaluated whether the AGB at the stand level can be estimated based on plant cover and to what extent the estimation accuracy can be improved by the inclusion of other field-measured structure variables.We also evaluated whether remote sensing technologies can be used to reliably estimate and map the regional mean biomass.For this purpose,we analyzed the relationships between field-measured woody vegetation structure variables and AGB as well as LANDSAT TM-derived variables.We obtained a model-based ratio estimate of regional mean AGB and its standard error.Total plant cover allowed us to obtain a reliable estimation of local AGB,and no better fit was attained by the inclusion of other structure variables.The stand-level plant cover ranged between 18.7%and 95.2%and AGB between about 2.0 and 70.8 Mg/hm^(2).AGB based on total plant cover was well estimated from LANDSAT TM bands 2 and 3,which facilitated a model-based ratio estimate of the regional mean AGB(approximately 12.0 Mg/hm^(2))and its sampling error(about 30.0%).The mean AGB of woody vegetation can greatly contribute to carbon storage in semi-arid lands.Thus,plant cover estimation by remote sensing images could be used to obtain regional estimates and map biomass,as well as to assess and monitor the impact of land-use change on the carbon balance,for arid and semi-arid regions.

Model-based estimation of above-ground biomass in the miombo ecoregion of Zambia

Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and international levels.In many tropical developing countries,this information may be unreliable or at a scale too coarse for use at local levels.There is a vital need to provide estimates of AGB with quantifiable uncertainty that can facilitate land use management and policy development improvements.Model-based methods provide an efficient framework to estimate AGB.Methods：Using National Forest Inventory（NFI） data for a^1,000,000 ha study area in the miombo ecoregion,Zambia,we estimated AGB using predicted canopy cover,environmental data,disturbance data,and Landsat 8 OLI satellite imagery.We assessed different combinations of these datasets using three models,a semiparametric generalized additive model（GAM） and two nonlinear models（sigmoidal and exponential）,employing a genetic algorithm for variable selection that minimized root mean square prediction error（RMSPE）,calculated through cross-validation.We compared model fit statistics to a null model as a baseline estimation method.Using bootstrap resampling methods,we calculated 95% confidence intervals for each model and compared results to a simple estimate of mean AGB from the NFI ground plot data.Results：Canopy cover,soil moisture,and vegetation indices were consistently selected as predictor variables.The sigmoidal model and the GAM performed similarly;for both models the RMSPE was -36.8 tonnes per hectare（i.e.,57% of the mean）.However,the sigmoidal model was approximately 30% more efficient than the GAM,assessed using bootstrapped variance estimates relative to a null model.After selecting the sigmoidal model,we estimated total AGB for the study area at 64,526,209 tonnes（＋/- 477,730）,with a confidence interval 20 times more precise than a simple designbased estimate.Conclusions：Our findings demonstrate that NFI data may be combined with freely available satellite imagery and soils data to estimate total AGB with quantifiable uncertainty,while also providing spatially explicit AGB maps useful for management,planning,and reporting purposes.

Assessment of tree diversity and above-ground biomass in coffee agroforest dominated tropical landscape of India's Central Western Ghats

The purpose of this study was to quantify the changes in tree diversity and above-ground biomass associated with six land-use types in Kodagu district of India's Western Ghats. We collected data on species richness,composition and above-ground biomass(AGB) of trees,shrubs and herbs from 96 sample plots of 0.1 ha. Totals of83 species from 26 families were recorded across the landuses. Tree species richness, diversity and composition were significantly higher in evergreen forest(EGF) than in other land-uses. Similarly, stem density and basal area were greater in EGF compared to other land-uses. Detrended correspondence analysis(DCA) yielded three distinct groups along the land-use intensities and rainfall gradient on the first and second axes, respectively. The first DCA axis accounted for 45% and second axis for 35% of the total variation in species composition. Together the first two axes accounted for over 2/3 of the variation in species composition across land-use types. Across the land-uses,AGB ranged from 58.6 Mg ha-1 in rubber plantation to327.3 Mg ha-1 in evergreen forest. Our results showed that species diversity and AGB were negatively impacted bythe land-use changes. We found that coffee agroforests resembled natural forest and mixed species plantation in terms of tree diversity and biomass production, suggesting that traditional coffee farms can help to protect tree species, sustain smallholder production and offer opportunities for conservation of biodiversity and climate change mitigation.

Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna- woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species- specific regression models relating biomass with measured tree dimen- sions were highly significant （p 〈 0.001）. The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interac- tions. The best-fit equations for total above-ground biomass and stem biomass bad R2 〉 0.70, except for the Acacia species; for branches including twig biomass, R2-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.

Land use and above-ground biomass changes in a mountain ecosystem,northern Thailand

The conversion of forests into agricultural lands is a major cause of deforestation,particularly in the mountain ecosystems of northern Thailand.It results in a rapid loss of biological diversity of both flora and fauna.In addition,the above-ground biomass(AGB),which can be a major source of carbon storage,is also decreased.This study aimed to predict the AGB in Doi Suthep-Pui National Park,Chiang Mai province,based on land-use/land cover(LULC)changes from 2000 to 2030.Landsat-5 TM(2000)and Landsat-8 TM(2015)satellite images were analyzed to predict LULC changes to 2030.Temporary plots(30 m 930 m)were established in each LULC type for AGB analysis;trees with diameters at breast height≥4.5 cm were identified and measured.AGB of all LULC types were analyzed based on specific allometric equations of each type.The results show that area of forest and nonforested areas fluctuated during the study period.Through the first 15 years(2000–2015),5%(2.9 km^2)of forest changed to either agriculture or urban lands,especially mixed deciduous forest and lower montane forest.There was a similar trend in the 2030 prediction,showing the effect of forest fragmentation and the resultant high number of patches.Total AGB tended to decrease over the 30-year period from 12.5 to 10.6 t ha^-1 in the first and second periods,respectively.Deforestation was the main factor influencing the loss of AGB(30.6 t ha^-1)related to LULC changes.Furthermore,habitat loss would be expected to result in decreased biological diversity.Consequently,a management plan should be developed to avoid unsustainable land use changes,which may adversely affect human well-being.

Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Tree Allometry in Tropical Forest of Congo for Carbon Stocks Estimation in Above-Ground Biomass

The research was aimed to estimate the carbon stocks of above-ground biomass (AGB) in Lesiolouna forest in Republic of Congo. The methodology of Allometric equations was used to measure the carbon stock of Lesio-louna tropical rainforest. The research was done with six circular plots each 40 m of diameter, with a distance of 100 m between each plot, depending on the topography of the site of the installation of these plots. The six studied plots are divided in two sites, which are: Iboubikro and Ngambali. Thus, in the six plots, there are three plots in Iboubikro site and three plots in Ngambali site. The results of this study show that the average carbon stock of aboveground biomass (AGB) in six plots was 170.673 t C ha-1. So, the average of carbon stock of aboveground biomass (ABG) in Iboubikro site was 204.693 t C ha-1 and in the Ngambali site was 136.652 t C ha-1. In this forest ecosystem, the high stock of carbon was obtained in Plot 3, which was in Iboubikro site. Plot 3 contains 20 trees and an average DBH of 24.56 cm. However, the lowest carbon stock was obtained in Plot 4, which was in Ngambali site. Also, Plot 4 contains 11 trees and an average DBH of 31.86 cm. The results of this research indicate that, the forests in the study area are an important carbon reservoir, and they can also play a key role in mitigation of climate change.

Remote sensing based shrub above-ground biomass and carbon storage mapping in Mu Us desert,China

The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ecosystems.HJ-1A/B satellite data combined with field measurement data was used for the estimation of shrub AGB and carbon storage in the Mu Us desert,China.The correlations of shrub AGB and spectral reflectance of four bands as well as their combined vegetation indexes were respectively analyzed and stepwise regression analysis was employed to establish AGB prediction equation.The prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than others.Shrub AGB and carbon storage were mapped using the RVI based prediction model in final.The statistics showed the western Mu Us desert has relatively high AGB and carbon storage,and that the gross shrub carton storage in Mu Us desert reaches 16 799 200 t,which has greatly contributed to the carbon fixation in northern China.

Plant above-ground biomass and litter quality drive soil microbial metabolic limitations during vegetation restoration of subtropical forests

Changes in litter quality(carbon:nitrogen,C:N)and above-ground biomass(AGB)following vegetation restoration significantly impact soil physicochemical properties,yet their effects on soil microbial metabolic limitations remain unclear.We measured litter quality,AGB,soil physicochemical properties,and extracellular enzyme activity(EEA)along a vegetation restoration gradient(7,14,49,70 years,and nearly climax evergreen broadleaved forests)in southern China.We also evaluated soil microbial metabolic limitations by a vector analysis of the EEA.Results revealed the soil microbial metabolisms were co-limited by C and phosphorus(P).The microbial C limitation initially decreased(before 14 years)and then increased,while the microbial P limitation initially increased(before 49 years)and then decreased.Partial least squares path modeling(PLS-PM)showed that the microbial C limitation was mainly attributed to microbial C use efficiency induced by litter quality,suggesting that microorganisms may transfer cellular energy between microbial growth and Cacquiring enzyme production.The microbial P limitation was primarily correlated with AGB-driven change in soil elements and their stoichiometry,highlighting the importance of nutrient stoichiometry and balance in microbial metabolism.The shifts between microbial C and P limitations and the strong connections of plant–soil-microbe processes during vegetation restoration revealed here will provide us with helpful information for optimal management to achieve forest restoration success.

Differential roles of seed and sprout regeneration in forest diversity and productivity after disturbance

Natural regeneration after disturbances is a key phase of forest development,which determines the trajectory of successional changes in tree species composition and diversity.Regenerating trees can originate from either seeds or sprouts produced by disturbed trees with sprouting ability.Although both regeneration strategies often develop and co-occur after a disturbance,they tend to affect forest development differently due to significant functional differences.However,the origin of tree regeneration is rarely distinguished in post-disturbance forest surveys and ecological studies,and the differential roles of seed and sprout regeneration in forest productivity and diversity remain poorly understood.To address these research gaps,we explored the role of sprout and seed regeneration in the formation of woody species diversity and above-ground biomass(AGB)productivity in early-stage forest development.Data were collected in two experimental forest stands in the Czech Republic,where trees were cut with varying intensities with the density of residual(uncut)trees ranging from 0 to 275 trees per hectare.All trees were mapped and their sizes were measured before cutting and then,either as a stump with sprouts or a residual tree,remeasured 11 years later.In addition,all tree saplings were mapped and measured 11 years after logging,and their origin(sprout or seed)was identified.To assess abundances and productivity,we estimated AGB of all2,685 sprouting stumps of 19 woody species and 504 generative(i.e.,seed origin)individuals of 16 woody species,using allometric equations.Mixed-effects models were used to analyze the effects of each regeneration strategy on woody species diversity and the total AGB under varying densities of residual trees.Nonmetric multidimensional scaling was used to evaluate the effect of regeneration strategies on species composition.AGB and diversity of sprouts were significantly higher than those of seed regeneration.Sprouts formed on average97.1%of the total regeneration AGB in H ady and 98.6%in Sobe s ice.The average species richness of sprouts was4.7 in H ady and 2.2 in Sob e sice,while the species richness of seed regeneration averaged 2.1 and 1.1 in H ady and Sob e sice,respectively.Increasing density of residual trees reduced AGB and diversity of both sprouts and seed regeneration,but seed regeneration was affected to a greater extent.Residual trees had an especially strong inhibitory effect on the establishment of seed regeneration.Consequently,seed-originated saplings were nearly absent in plots with high residual tree density,and abundant sprouts accounted for most of the AGB and diversity.However,unlike sprouts whose species composition resembled that of the original stand,seed regeneration brought in new species,enriching the stand?s overall species pool and beta diversity.Our results demonstrated differential roles of sprout and seed regeneration in the early stage of forest succession.Sprout regeneration was the main source of woody AGB productivity as well as species diversity,and its importance increased with the increasing density of standing mature trees.The results indicate the crucial yet previously underestimated role of sprout regeneration in post-disturbance forest dynamics.They suggest that the presence of residual mature trees,whether retained after partial cutting or undisturbed,can substantially suppress seed regeneration while the role of sprout regeneration in early succession becomes more distinctly evident.

Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

Wheat biomass can be estimated using appropriate spectral vegetation indices.However,the accuracy of estimation should be further improved for on-farm crop management.Previous studies focused on developing vegetation indices,however limited research exists on modeling algorithms.The emerging Random Forest(RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling.The objectives of this study were to(1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass,(2) test the performance of the RF regression model,and(3) compare the performance of the RF algorithm with support vector regression(SVR) and artificial neural network(ANN) machine-learning algorithms for wheat biomass estimation.Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing,booting,and anthesis stages of growth.Fifteen vegetation indices were calculated based on these images.In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition.The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage,and its robustness is as good as SVR but better than ANN.The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.

Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China

Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites （including temperate meadow steppe, temperate steppe, temperate desert steppe and alpine meadow） were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity （ANPP） and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation （MAP） was the main factor determining spatial distribution of grassland ANPP （r^2 = 0.61, P 〈 0.01）; while temporally, no significant relationship was found between the variance of AN PP and inter-annual precipitation for the four types of grassland. However, after dividing annual preeipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow steppe, the key variable determining inter-annual change of ANPP was last August-May precipitation （r^2 = 0.47, P = 0.01）; for the temperate steppe, the key variable was July precipitation （r^2 = 0.36, P = 0.02）; for the temperate desert steppe, the key variable was April-June precipitation （r^2 = 0.51, P 〈 0.01）; for the alpine meadow, the key variable was last September-May precipitation （r^2 = 0.29, P 〈 0.05）. In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.

Biomass Components and Environmental Controls in Ningxia Grasslands

Grassland plays an important role in the global carbon cycle and climate regulation. However, there are still large uncertainties in grassland carbon pool and also its role in global carbon cycle due to the lack of measured grassland biomass at regional scale or global scale with a unified survey method, particular for below-ground biomass. The present study, based on a total of 44 grassland sampling plots with 220 quadrats across Ningxia, investigated the characteristics of above-ground biomass （AGB）, below-ground biomass （BGB）, litter biomass （LB）, total biomass （TB） and root：shoot ratios （R：S） for six predominantly grassland types, and their relationships with climatic factors. AGB, BGB, LB and TB varied markedly across different grassland types, the median value ranging from 28.2-692.6 g m-2 for AGB, 130.4-2 036.6 g m-： for BGB, 9.2-82.3 g m2 for LB, and 168.0-2 681.3 g m-： for TB. R：S showed less variation with median values from 3.2 to 5.3 （excluding marshy meadow）. The different grassland types showed similar patterns of biomass allocation, with more than 70% BGB for all types. There is evidence of strong positive effects associated with mean annual precipitation （MAP） and negative effects associated with mean annual temperature （MAT） on AGB, BGB, and LB, although both factors have the opposite effect on R：S.

Ecological biomass allocation strategies in plant species with different life forms in a cold desert, China

Biomass allocation patterns among plant species are related to their adaptive ecological strategies. Ephemeral, ephemeroid and annual plant life forms represent three typical growth strategies of plants that grow in autumn and early spring in the cold deserts of China. These plants play an important role in reducing wind velocity in the desert areas. However, despite numerous studies, the strategies of biomass allocation among plant species with these three life forms remain contentious. In this study, we conducted a preliminary quadrat study during 2014–2016 in the southern part of the Gurbantunggut Desert, China, to investigate the allocation patterns of above-ground biomass(AGB) and below-ground biomass(BGB) at the individual level in 17 ephemeral, 3 ephemeroid and 4 annual plant species. Since ephemeral plants can germinate in autumn, we also compared biomass allocation patterns between plants that germinated in autumn 2015 and spring 2016 for 4 common ephemeral species. The healthy mature individual plants of each species were sampled and the AGB, BGB, total biomass(TB), leaf mass ratio(LMR) and root/shoot ratio(R/S) were calculated for 201 sample quadrats in the study area. We also studied the relationships between AGB and BGB of plants with the three different life forms(ephemeral, ephemeroid and annual). The mean AGB values of ephemeral, ephemeroid and annual plants were 0.806, 3.759 and 1.546 g/plant, respectively, and the mean BGB values were 0.106, 4.996 and 0.166 g/plant, respectively. The mean R/S value was significantly higher in ephemeroid plants(1.675) than in ephemeral(0.154) and annual(0.147) plants. The mean LMR was the highest in annual plants, followed by ephemeroid plants and ephemeral plants, reflecting the fact that annual plants allocate more biomass to leaves, associated with their longer life span. Biomass of ephemeral plants that germinated in autumn was significantly higher than those of corresponding plants that germinated in spring in terms of AGB, BGB and TB. However, the R/S value was similar in plants that germinated in autumn and spring. The slope of regression relationship between AGB and BGB differed significantly among the three plant life forms. These results support different biomass allocation hypotheses. Specifically, at the individual level, the AGB and BGB partitioning supports the allometric hypothesis for ephemeroid and annual plants and the isometric hypothesis for ephemeral plants.