Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protectiv...Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.展开更多
The Andean montane forests provide a wide range of ecosystem services like water supply, carbon sequestration, and biodiversity preservation. Restoration of these forests is critical due to their degraded state and th...The Andean montane forests provide a wide range of ecosystem services like water supply, carbon sequestration, and biodiversity preservation. Restoration of these forests is critical due to their degraded state and the need to recover, maintain and enhance the ecosystem services they provide. However, we lack understanding of aboveground biomass (AGB) accumulation in restored Andean montane forests. AGB is a key indicator of ecosystem productivity and provides essential data on vegetation carbon stocks, permitting the assess successfulness of restoration efforts. In 2010 the initiative Más Bosques para Medellín was formulated in Medellín City, tropical Andes, Colombia, aiming to restore the forests located in the surrounding rural areas of the city, with interest in preserving the ecosystems services like water supply. The project established 548 ha of mixed plantations with native species. After 13 years, our study aims to developed in situ allometric equations and to evaluate AGB accumulation to assess restoration performance. We measured, harvested, and weighted 144 individuals from these arrangements to fit a general equation for the project and six specific equations for each one of the six most frequent species. The AGB had a positive correlation with diameter at breast height (D), total height (H) and specific wood density (WD). The best general equation uses D and WD as predictors (R^(2) = 0.928). The specific species equations certainly responded to the functional traits of each species. Using the latest inventory of permanent plots of the project we estimated a mean AGB accumulation of 41.91 ± 30.34 Mg ha^(–1) and a total accumulation of 22,996.05 Mg of AGB for the 548 ha. We compared these results with studies developed for natural forest in the region and other land covers. We found contrast behaviors in the AGB accumulation across our study zones. The developed equations have broad applicability across the Andes region, offering valuable insights for similar restoration initiatives. Furthermore, will facilitate the assessment of current restoration efforts and inform scientifically based decisions for future mixed plantation practices.展开更多
Most research on carbon storage in forests has focused on qualitative studies of carbon storage and influ-encing factors rather than on quantifying the effect of the spatial distribution of carbon storage and of its i...Most research on carbon storage in forests has focused on qualitative studies of carbon storage and influ-encing factors rather than on quantifying the effect of the spatial distribution of carbon storage and of its influencing factors at different scales.Here we described the spatial dis-tribution of aboveground carbon storage(ACS)in a 20-ha plot in a subtropical evergreen broad-leaved forest to evalu-ate and quantify the relative effects of biotic factors(species diversity and structural diversity)and abiotic factors(soil and topographic factors)on ACS at different scales.Scale effects of the spatial distribution of ACS were significant,with higher variability at smaller scales,but less at larger scales.The distribution was also spatially heterogeneous,with more carbon storage on north-and east-facing slopes than on south-and west-facing slopes.At a smaller scale,species diversity and structural diversity each had a direct positive impact on ACS,but soil factors had no significant direct impact.At increasing scales,topographic and soil fac-tors gradually had a greater direct influence,whereas the influence of species diversity gradually decreased.Structural diversity had the greatest impact,followed by topographic factors and soil factors,while species diversity had a rela-tively smaller impact.These findings suggest studies on ACS in subtropical evergreen broadleaf forests in southern China should consider scale effects,specifically on the heterogene-ity of ACS distribution at small scales.Studies and conser-vation efforts need to focus on smaller habitat types with particular emphasis on habitat factors such as aspect and soil conditions,which have significant influences on community species diversity,structural diversity,and ACS distribution.展开更多
While numerous allometric models exist for estimating biomass in trees with single stems,models for multi-stemmed species are scarce.This study presents models for predicting aboveground biomass(AGB)in European hazel(...While numerous allometric models exist for estimating biomass in trees with single stems,models for multi-stemmed species are scarce.This study presents models for predicting aboveground biomass(AGB)in European hazel(Corylus avellana L.),growing in multi-stemmed shrub form.We measured the size and harvested the biomass of 30 European hazel shrubs,drying and weighing their woody parts and leaves separately.AGB(dry mass)and leaf area models were established using a range of predictors,such as the upper height of the shrub,number of shoots per shrub,canopy projection area,stem base diameter of the thickest stem,and the sum of cross-sectional areas of all stems at the stem base.The latter was the best predictor of AGB,but the most practically useful variables,defined as relatively easy to measure by terrestrial or aerial approaches,were the upper height of the shrub and the canopy projection area.The leaf biomass to AGB ratio decreased with the shrub's height.Specific leaf area of shaded leaves increases with shrub height,but that of leaves at the top of the canopy does not change significantly.Given that the upper shrub height and crown projection of European hazel can be estimated using remote sensing approaches,especially UAV and LIDAR,these two variables appear the most promising for effective measurement of AGB in hazel.展开更多
Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tre...Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tree biomass within a fully censused 20 ha forest plot in a temperate forest of northern Alabama,USA.We evaluated the relationship between biomass and topography using ridge and valley landforms along with digitally derived moisture and solar radiation indices.Every live woody stem over 1 cm diameter at breast height within this plot was mapped,measured,and identified to species in 2019-2022,and diameter data were used along with speciesspecific wood density to map the aboveground biomass at the scale of 20 m×20 m quadrats.The aboveground tree biomass was 211 Mg·ha^(-1).Other than small stream areas that experienced recent natural disturbances,the total stand biomass was not associated with landform or topographic indices.Dominant species,in contrast,had strong associations with topography.American beech(Fagus grandifolia)and yellow-poplar(Liriodendron tulipfera)dominated the valley landform,with 37% and 54% greater biomass in the valley than their plot average,respectively.Three other dominant species,white oak(Quercus alba),southern shagbark hickory(Carya carolinaeseptentrionalis),and white ash(Fraxinus americana),were more abundant on slopes and benches,thus partitioning the site.Of the six dominant species,only sugar maple(Acer saccharum)was not associated with landform.Moreover,both topographic wetness and potential radiation indices were significant predictors of dominant species biomass within each of the landforms.The study highlights the need to consider species when examining forest productivity in a range of site conditions.展开更多
Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe.In addition,according to climate models,decreased growth of many economically and ecologically important native trees w...Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe.In addition,according to climate models,decreased growth of many economically and ecologically important native trees will likely be observed in the future.We aimed to assess the impact of these two neophytes,which differ in the biomass range and nitrogen-fixing abilities observed in Central European conditions,on the relative aboveground biomass increments of native oaks Qucrcus robur and Q.petraea and Scots pine Pinus sylvestris.We aimed to increase our understanding of the relationship between facilitation and competition between woody alien species and overstory native trees.We established 72 circular plots(0.05 ha)in two different forest habitat types and stands varying in age in western Poland.We chose plots with different abundances of the studied neophytes to determine how effects scaled along the quantitative invasion gradient.Furthermore,we collected growth cores of the studied native species,and we calculated aboveground biomass increments at the tree and stand levels.Then,we used generalized linear mixed-effects models to assess the impact of invasive species abundances on relative aboveground biomass increments of native tree species.We did not find a biologically or statistically significant impact of invasive R.pseudoacacia or P.serotina on the relative aboveground,biomass increments of native oaks and pines along the quantitative gradient of invader biomass or on the proportion of total stand biomass accounted for by invaders.The neophytes did not act as native tree growth stimulators but also did not compete with them for resources,which would escalate the negative impact of climate change on pines and oaks.The neophytes should not significantly modify the carbon sequestration capacity of the native species.Our work combines elements of the per capita effect of invasion with research on mixed forest management.展开更多
Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biom...Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.展开更多
There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the...There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the impact of the sampling strategy on model accuracy still need to be resolved.In this study,we first corrected the bias arising from upscaling the LG-AGB map to match the spatial resolution of Landsat observations.Subsequently,the stratified random sampling method was used to select training samples from the corrected LG-AGB map(cLG-AGB)for the Random Forest(RF)regression model.The RF model features were extracted from the Landsat observations and auxiliary data.The impact of strata numbers on model accuracy was explored during the sampling process.Finally,independent validation was conducted using in situ measurements.The results indicated that:(1)about 68% of the biases can be corrected in the up-scale transformation;(2)compared to no stratification,a three-strata model achieved a 6.5% improvement in AGB estimation accuracy while requiring a 37.8% reduction in sample size;(3)the black locust forest had a low saturation point at 60.52±4.46 Mg/ha AGB and 72.4%AGB values were underestimated and the remaining were overestimated.In summary,our study provides a framework to harmonize near-surface LiDAR and satellite data for AGB estimation in plantation forest ecosystems with small patch sizes and fragmented distribution.展开更多
Because of global climate change, it is necessary to add forest biomass estimation to national forest resource monitoring. The biomass equations developed for forest biomass estimation should be compatible with volume...Because of global climate change, it is necessary to add forest biomass estimation to national forest resource monitoring. The biomass equations developed for forest biomass estimation should be compatible with volume equations. Based on the tree volume and aboveground biomass data of Masson pine （Pinus massoniana Lamb.） in southern China, we constructed one-, two- and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations. The prediction precision of aboveground biomass estimates from one variable equa- tion exceeded 95%. The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height, although the contributions to regressions were statistically insignificant. For the biomass conversion function on one variable, the conversion factor decreased with increasing diameter, but for the conversion function on two variables, the conversion factor increased with increasing diameter but decreased with in- creasing tree height.展开更多
Remote sensing is a valuable and effective tool for monitoring and estimating aboveground biomass （AGB） in large areas.The current international research on biomass estimation by remote sensing technique mainly focu...Remote sensing is a valuable and effective tool for monitoring and estimating aboveground biomass （AGB） in large areas.The current international research on biomass estimation by remote sensing technique mainly focused on forests,grasslands and crops,with relatively few applications for desert ecosystems.In this paper,Landsat Thematic Mapper （TM）/Enhanced Thematic Mapper Plus （ETM＋） images from 1988 to 2007 and the data of 283 AGB samples in August 2007 were used to estimate the AGB for Mu Us Sandy Land over the past 30 years.Moreover,temporal and spatial distribution characteristics of AGB and influencing factors of climate and underlying surface were also studied.Results show that：（1） Differences of correlations exist in the fitted equations between AGB and different vegetation indices in desert areas.The modified soil adjusted vegetation index （MSAVI） and soil adjusted vegetation index （SAVI） show relatively higher correlations with AGB,while the correlation between normalized difference vegetation index （NDVI） and AGB is relatively lower.Error testing shows that the AGB-MSAVI model established can be used to accurately estimate AGB of Mu Us Sandy Land in August.（2） AGB in Mu Us Sandy Land shows the fluctuant characteristics over the past 30 years,which decreased from the 1980s to the 1990s,and increased from the 1990s to 2007.AGB in 2007 had the highest value,with a total AGB of 3.352×106 t.Moreover,in the 1990s,AGB had the lowest value with a total AGB of 2.328×106 t.（3） AGB with relatively higher values was mainly located in the middle and southern parts of Mu Us Sandy Land in the 1980s.AGB was low in the whole area in the1990s,and relatively higher AGB values were mainly located in the southern parts of Uxin.In 2007,AGB in the whole area was relatively higher than those of the last twenty years,and higher AGB values were mainly located in the northern,western and middle parts of Mu Us Sandy Land.展开更多
Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive ...Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive to global climate warming.It is of great importance to study the changes in aboveground biomass and species diversity of alpine meadows on the QTP under predicted future climate warming.In this study,we selected an alpine meadow on the QTP as the study object and used infrared radiators as the warming device for a simulation experiment over eight years(2011-2018).We then analyzed the dynamic changes in aboveground biomass and species diversity of the alpine meadow at different time scales,including an early stage of warming(2011-2013)and a late stage of warming(2016-2018),in order to explore the response of alpine meadows to short-term(three years)and long-term warming(eight years).The results showed that the short-term warming increased air temperature by 0.31℃and decreased relative humidity by 2.54%,resulting in the air being warmer and drier.The long-term warming increased air temperature and relative humidity by 0.19℃and 1.47%,respectively,and the air tended to be warmer and wetter.The short-term warming increased soil temperature by 2.44℃and decreased soil moisture by 12.47%,whereas the long-term warming increased soil temperature by 1.76℃and decreased soil moisture by 9.90%.This caused the shallow soil layer to become warmer and drier under both short-term and long-term warming.Furthermore,the degree of soil drought was alleviated with increased warming duration.Under the long-term warming,the importance value and aboveground biomass of plants in different families changed.The importance values of grasses and sedges decreased by 47.56%and 3.67%,respectively,while the importance value of weeds increased by 1.37%.Aboveground biomass of grasses decreased by 36.55%,while those of sedges and weeds increased by 8.09%and 15.24%,respectively.The increase in temperature had a non-significant effect on species diversity.The species diversity indices increased at the early stage of warming and decreased at the late stage of warming,but none of them reached significant levels(P>0.05).Species diversity had no significant correlation with soil temperature and soil moisture under both short-term and long-term warming.Soil temperature and aboveground biomass were positively correlated in the control plots(P=0.014),but negatively correlated under the long-term warming(P=0.013).Therefore,eight years of warming aggravated drought in the shallow soil layer,which is beneficial for the growth of weeds but not for the growth of grasses.Warming changed the structure of alpine meadow communities and had a certain impact on the community species diversity.Our studies have great significance for the protection and effective utilization of alpine vegetation,as well as for the prevention of grassland degradation or desertification in high-altitude regions.展开更多
Shrublands serve as an important component of terrestrial ecosystems, and play an important role in structure and functions of alpine ecosystem.Accurate estimation of biomass is critical to examination of the producti...Shrublands serve as an important component of terrestrial ecosystems, and play an important role in structure and functions of alpine ecosystem.Accurate estimation of biomass is critical to examination of the productivity of alpine ecosystems, due to shrubification under climate change in past decades.In this study, 14 experimental plots and 42 quadrates of the shrubs Potentilla fruticosa and Caragana jubata were selected along altitudes gradients from 3220 to 3650 m a.s.l.(above sea level) on semi-sunny and semi-shady slope in Hulu watershed of Qilian Mountains, China.The foliage, woody component and total aboveground biomass per quadrate were examined using a selective destructive method, then the biomass were estimated via allometric equations based on measured parameters for two shrub species.The results showed that C.jubata accounted for 1–3 times more biomass(480.98 g/m2) than P.fruticosa(191.21 g/m2).The aboveground biomass of both the shrubs varied significantly with altitudinal gradient(P<0.05).Woody component accounted for the larger proportion than foliage component in the total aboveground biomass.The biomass on semi-sunnyslopes(200.27 g/m2 and 509.07 g/m2) was greater than on semi-shady slopes(182.14 g/m2 and 452.89g/m2) at the same altitude band for P.fruticosa and C.jubata.In contrast, the foliage biomass on semi-shady slopes(30.50 g/m2) was greater than on semi-sunny slopes(27.51 g/m2) for two shrubs.Biomass deceased with increasing altitude for P.fruticosa, whereas C.jubata showed a hump-shaped pattern with altitude.Allometric equations were obtained from the easily descriptive parameters of height(H), basal diameter(D) and crown area(C) for biomass of C.jubata and P.fruticosa.Although the equations type and variables comprising of the best model varied among the species, all equations related to biomass were significant(P < 0.005), with determination coefficients(R2) ranging from 0.81 to 0.96.The allometric equations satisfied the requirements of the model, and can be used to estimate the regional scale biomass of P.fruticosa and C.jubata in alpine ecosystems of the Qilian Mountains.展开更多
Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function...Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change（ABM/LUCC）, an ecosystem process model（PnET-Ⅱ）, and a forest dynamic landscape model（LANDIS-Ⅱ） to simulate the change of forest aboveground biomass（AGB） which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that：（1） land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County.（2） Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7%（RCP2.6 ＋ land use）, 57.2%（RCP4.5 ＋ land use）, and 56.9%（RCP8.5 ＋ land use） by 2050, which is in comparison to the results under separate RCPs without land use disturbance.（3） The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function,and developing measures for sustainable forest management.展开更多
Aboveground biomass in grasslands of the Qinghai-Tibet Plateau has displayed an overall increasing trend during 2003–2016, which is profoundly influenced by climate change. However, the responses of different biomes ...Aboveground biomass in grasslands of the Qinghai-Tibet Plateau has displayed an overall increasing trend during 2003–2016, which is profoundly influenced by climate change. However, the responses of different biomes show large discrepancies, in both size and magnitude. By applying partial least squares regression, we calculated the correlation between peak aboveground biomass and mean monthly temperature and monthly total precipitation in the preceding 12 months for three different grassland types(alpine steppe, alpine meadow, and temperate steppe) on the central and eastern Qinghai-Tibet Plateau. The results showed that mean temperature in most preceding months was positively correlated with peak aboveground biomass of alpine meadow and alpine steppe, while mean temperature in the preceding October and February to June was significantly negatively correlated with peak aboveground biomass of temperate steppe. Precipitation in all months had a promoting effect on biomass of alpine meadow, but its correlations with biomass of alpine steppe and temperate steppe were inconsistent. It is worth noting that, in a warmer, wetter climate, peak aboveground biomass of alpine meadow would increase more than that of alpine steppe, while that of temperate steppe would decrease significantly, providing support for the hypothesis of conservative growth strategies by vegetation in stressed ecosystems.展开更多
Allometric equations are important for quantifying biomass and carbon storage in terrestrial forest ecosystems.However,equations for dry deciduous woodland ecosystems,an important carbon sink in the lowland areas of E...Allometric equations are important for quantifying biomass and carbon storage in terrestrial forest ecosystems.However,equations for dry deciduous woodland ecosystems,an important carbon sink in the lowland areas of Ethiopia have not as yet been developed.This study attempts to develop and evaluate species-specific allometric equations for predicting aboveground biomass(AGB)of dominant woody species based on data from destructive sampling for Combretum collinum,Combretum molle,Combretum harotomannianum,Terminalia laxiflora and mixed-species.Diameter at breast height ranged from 5 to 30 cm.Two empirical equations were developed using DBH(Eq.1)and height(Eq.2).Equation 2 gave better AGB estimations than Eq.1.The inclusion of both DBH and H were the best estimate biometric variables for AGB.Further,the equations were evaluated and compared with common generic allometric equations.The result showed that our allometric equations are appropriate for estimating AGB.The development and application of empirical species-specific allometric equations is crucial to improve biomass and carbon stock estimation for dry woodland ecosystems.展开更多
Intercropping of maize(Zea mays L.) and peanut(Arachis hypogaea L.) often results in greater yields than the respective sole crops. However, there is limited knowledge of aboveground and belowground interspecific inte...Intercropping of maize(Zea mays L.) and peanut(Arachis hypogaea L.) often results in greater yields than the respective sole crops. However, there is limited knowledge of aboveground and belowground interspecific interactions between maize and peanut in field. A two-year field experiment was conducted to investigate the effects of interspecific interactions on plant growth and grain yield for a peanut/maize intercropping system under different nitrogen(N) and phosphorus(P) levels. The method of root separation was employed to differentiate belowground from aboveground interspecific interactions. We observed that the global interspecific interaction effect on the shoot biomass of the intercropping system decreased with the coexistence period, and belowground interaction contributed more than aboveground interaction to advantages of the intercropping in terms of shoot biomass and grain yield. There was a positive effect from aboveground and belowground interspecific interactions on crop plant growth in the intercropping system, except that aboveground interaction had a negative effect on peanut during the late coexistence period. The advantage of intercropping on grain came mainly from increased maize yield(means 95%) due to aboveground interspecific competition for light and belowground interaction(61%–72% vs. 28%–39% in fertilizer treatments). There was a negative effect on grain yield from aboveground interaction for peanut, but belowground interspecific interaction positively affected peanut grain yield.The supply of N, P, or N + P increased grain yield of intercropped maize and the contribution from aboveground interspecific interaction. Our study suggests that the advantages of peanut/maize intercropping for yield mainly comes from aboveground interspecific competition for maize and belowground interspecific facilitation for peanut, and their respective yield can be enhanced by N and P. These findings are important for managing the intercropping system and optimizing the benefits from using this system.展开更多
Background:Aboveground biomass(AGB)is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of target...Background:Aboveground biomass(AGB)is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of targeted forest management plans.Methods:Here,we proposed a random forest/co-kriging framework that integrates the strengths of machine learning and geostatistical approaches to improve the mapping accuracies of AGB in northern Guangdong Province of China.We used Landsat time-series observations,Advanced Land Observing Satellite(ALOS)Phased Array L-band Synthetic Aperture Radar(PALSAR)data,and National Forest Inventory(NFI)plot measurements,to generate the forest AGB maps at three time points(1992,2002 and 2010)showing the spatio-temporal dynamics of AGB in the subtropical forests in Guangdong,China.Results:The proposed model was capable of mapping forest AGB using spectral,textural,topographical variables and the radar backscatter coefficients in an effective and reliable manner.The root mean square error of the plotlevel AGB validation was between 15.62 and 53.78 t∙ha^(−1),the mean absolute error ranged from 6.54 to 32.32 t∙ha^(−1),the bias ranged from−2.14 to 1.07 t∙ha^(−1),and the relative improvement over the random forest algorithm was between 3.8%and 17.7%.The largest coefficient of determination(0.81)and the smallest mean absolute error(6.54 t∙ha^(−1)were observed in the 1992 AGB map.The spectral saturation effect was minimized by adding the PALSAR data to the modeling variable set in 2010.By adding elevation as a covariable,the co-kriging outperformed the ordinary kriging method for the prediction of the AGB residuals,because co-kriging resulted in better interpolation results in the valleys and plains of the study area.Conclusions:Validation of the three AGB maps with an independent dataset indicated that the random forest/cokriging performed best for AGB prediction,followed by random forest coupled with ordinary kriging(random forest/ordinary kriging),and the random forest model.The proposed random forest/co-kriging framework provides an accurate and reliable method for AGB mapping in subtropical forest regions with complex topography.The resulting AGB maps are suitable for the targeted development of forest management actions to promote carbon sequestration and sustainable forest management in the context of climate change.展开更多
Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carb...Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB).Different levels of detail are needed to estimate FAGB at local,regional and national scales.Multi-scale remote sensing analysis from high,medium and coarse spatial resolution data,along with field sampling,is one approach often used.However,the methods developed are still time consuming,expensive,and inconvenient for systematic monitoring,especially for developing countries,as they require vast numbers of field samples for upscaling.Here,we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites.The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m),Landsat(30 m)and Google Earth very high resolution(GEVHR)Quickbird(0.65 m)images.For the local scale(Kayerkhola watershed),tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images.An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot.A TCC vs.FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots.A coefficient of determination(R2)of 0.76 was obtained in the modelling,and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district,open source GEVHR images were used as virtual field plots.We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model.Using the multivariate adaptive regression splines machine learning algorithm,we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices.The model was then used to extrapolate FAGB to the entire district.This approach considerably reduced the need for field data and commercial very high resolution imagery while achieving two-scale forest information and FAGB estimates at high resolution(30 m)and accuracy(R2=0.76 and 0.7)with minimal error(RMSE=64 and 38 tons ha-1)at local and regional scales.This methodology is a promising technique for cost-effective FAGB and carbon estimations and can be replicated with limited resources and time.The method is especially applicable for developing countries that have low budgets for carbon estimations,and it is also applicable to the Reducing Emissions from Deforestation and Forest Degradation(REDD?)monitoring reporting and verification processes.展开更多
Soil respiration from decomposing aboveground litter is a major component of the terrestrial carbon cycle. However, variations in the contribution of aboveground litter to the total soil respiration for stands of vary...Soil respiration from decomposing aboveground litter is a major component of the terrestrial carbon cycle. However, variations in the contribution of aboveground litter to the total soil respiration for stands of varying ages are poorly understood. To assess soil respiration induced by aboveground litter, treatments of litter and no litter were applied to 5-, l0-, and 20-year-old stands of Populus davidiana Dode in the sandstorm source area of Beijing-Tianjin, equations were applied to China. Optimal nonlinear model the combined effects of soil temperature and soil water content on soil respiration. Results showed that the monthly average contribution of aboveground litter to total soil respiration were 18.46% ± 4.63%, 16.64% ± 9.31%, and 22.37% ± 8.17% for 5-, 10-, and ao-year-old stands, respectively. The relatively high contribution in 5- and 20-year-old stands could be attributed to easily decomposition products and high accumulated litter, resoectivelv. Also. it fluctuated monthly for all stand ages due to substrate availability caused by phenology and environmental factors. Litter removal significantly decreased soil respiration and soil water content for all stand ages （P 〈 0.05） but not soil temperature （P 〉 0.05）. Variations of soil respiration could be explained by soil temperature at 5-cm depth using an exponential equation and by soil water content at lo-cm depth using a quadratic equation, whereas soil respiration was better modeled using the combined parameters of soil temperature and soil water content than with either soil temperature or soil water content alone. Temperature sensitivity （Q10） increased with stand age in both the litter and the no litter treatments. Considering the effects of aboveground litter, this study provides insights for predicting future soil carbon fluxes and for accurately assessing soil carbon budgets.展开更多
Background: The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-b...Background: The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging(LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference.Results: Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km2 large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m×18 m map units was found to range between 9 and 447 Mg·ha^-1. The corresponding root mean square errors ranged between 10 and 162 Mg·ha^-1. For the entire study region, the mean aboveground biomass was 55 Mg·ha^-1 and the corresponding relative root mean square error 8%. At this level 75%of the mean square error was due to the uncertainty associated with tree-level models.Conclusions: Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF1300203)the National Natural Science Foundation of China(Grant No.42371329s).
文摘Natural forests are the primary carbon sinks within terrestrial ecosystems,playing a crucial role in mitigating global climate change.China has successfully restored its natural forest area through extensive protective measures.However,the aboveground carbon(AGC)stock potential of China's natural forests remains considerably uncertain in spatial and temporal dynamics.In this study,we provide a spatially detailed estimation of the maximum AGC stock potential for China's natural forests by integrating high-resolution multi-source remote sensing and field survey data.The analysis reveals that China's natural forests could sequester up to 9.880.10 Pg C by 2030,potentially increasing to 10.460.11 Pg C by 2060.Despite this,the AGC sequestration rate would decline from 0.190.001 to 0.080.001 Pg C·yr^(-1)over the period.Spatially,the future AGC accumulation rates exhibit marked heterogeneity.The warm temperate deciduous broadleaf forest region with predominantly young natural forests,is expected to exhibit the most significant increase of 26.36%by 2060,while the Qinghai-Tibet Plateau Alpine region comprising mainly mature natural forests would exhibit only a 0.74%increase.To sustain the high carbon sequestration capacity of China's natural forests,it is essential to prioritize protecting mature forests alongside preserving and restoring young natural forest areas.
基金supported by resources of the Secretary of Environment of the Medellín district,through the agreement N°001-2023 between this entity,the Faculty of Agricultural Sciences of National University of Colombia at Medellín
文摘The Andean montane forests provide a wide range of ecosystem services like water supply, carbon sequestration, and biodiversity preservation. Restoration of these forests is critical due to their degraded state and the need to recover, maintain and enhance the ecosystem services they provide. However, we lack understanding of aboveground biomass (AGB) accumulation in restored Andean montane forests. AGB is a key indicator of ecosystem productivity and provides essential data on vegetation carbon stocks, permitting the assess successfulness of restoration efforts. In 2010 the initiative Más Bosques para Medellín was formulated in Medellín City, tropical Andes, Colombia, aiming to restore the forests located in the surrounding rural areas of the city, with interest in preserving the ecosystems services like water supply. The project established 548 ha of mixed plantations with native species. After 13 years, our study aims to developed in situ allometric equations and to evaluate AGB accumulation to assess restoration performance. We measured, harvested, and weighted 144 individuals from these arrangements to fit a general equation for the project and six specific equations for each one of the six most frequent species. The AGB had a positive correlation with diameter at breast height (D), total height (H) and specific wood density (WD). The best general equation uses D and WD as predictors (R^(2) = 0.928). The specific species equations certainly responded to the functional traits of each species. Using the latest inventory of permanent plots of the project we estimated a mean AGB accumulation of 41.91 ± 30.34 Mg ha^(–1) and a total accumulation of 22,996.05 Mg of AGB for the 548 ha. We compared these results with studies developed for natural forest in the region and other land covers. We found contrast behaviors in the AGB accumulation across our study zones. The developed equations have broad applicability across the Andes region, offering valuable insights for similar restoration initiatives. Furthermore, will facilitate the assessment of current restoration efforts and inform scientifically based decisions for future mixed plantation practices.
基金supported by the Guangxi Natural Science Foundation Program(2022GXNSFAA035583,2021GXNSFBA196052)the National Natural Science Foundation of China(32060305,32460270).
文摘Most research on carbon storage in forests has focused on qualitative studies of carbon storage and influ-encing factors rather than on quantifying the effect of the spatial distribution of carbon storage and of its influencing factors at different scales.Here we described the spatial dis-tribution of aboveground carbon storage(ACS)in a 20-ha plot in a subtropical evergreen broad-leaved forest to evalu-ate and quantify the relative effects of biotic factors(species diversity and structural diversity)and abiotic factors(soil and topographic factors)on ACS at different scales.Scale effects of the spatial distribution of ACS were significant,with higher variability at smaller scales,but less at larger scales.The distribution was also spatially heterogeneous,with more carbon storage on north-and east-facing slopes than on south-and west-facing slopes.At a smaller scale,species diversity and structural diversity each had a direct positive impact on ACS,but soil factors had no significant direct impact.At increasing scales,topographic and soil fac-tors gradually had a greater direct influence,whereas the influence of species diversity gradually decreased.Structural diversity had the greatest impact,followed by topographic factors and soil factors,while species diversity had a rela-tively smaller impact.These findings suggest studies on ACS in subtropical evergreen broadleaf forests in southern China should consider scale effects,specifically on the heterogene-ity of ACS distribution at small scales.Studies and conser-vation efforts need to focus on smaller habitat types with particular emphasis on habitat factors such as aspect and soil conditions,which have significant influences on community species diversity,structural diversity,and ACS distribution.
基金funded by grants EVA4.0 No.Z.02.1.01/0.0/0.0/16_019/0000803 and ITMS2014+313011W580s provided by EU OP RDEin CZ and SKprojects APVV-18-0086,APVV-19-0387,APVV-20-0168,APVV-20-0215 and APVV-22-0056 from the Slovak Research and Development Agencysupport from the European Research Executive Agency for ReForest,Grant Agreement Nr:101060635
文摘While numerous allometric models exist for estimating biomass in trees with single stems,models for multi-stemmed species are scarce.This study presents models for predicting aboveground biomass(AGB)in European hazel(Corylus avellana L.),growing in multi-stemmed shrub form.We measured the size and harvested the biomass of 30 European hazel shrubs,drying and weighing their woody parts and leaves separately.AGB(dry mass)and leaf area models were established using a range of predictors,such as the upper height of the shrub,number of shoots per shrub,canopy projection area,stem base diameter of the thickest stem,and the sum of cross-sectional areas of all stems at the stem base.The latter was the best predictor of AGB,but the most practically useful variables,defined as relatively easy to measure by terrestrial or aerial approaches,were the upper height of the shrub and the canopy projection area.The leaf biomass to AGB ratio decreased with the shrub's height.Specific leaf area of shaded leaves increases with shrub height,but that of leaves at the top of the canopy does not change significantly.Given that the upper shrub height and crown projection of European hazel can be estimated using remote sensing approaches,especially UAV and LIDAR,these two variables appear the most promising for effective measurement of AGB in hazel.
基金supported in part by the intramural research program of the US Department of Agriculture,National Institute of Food and Agriculture,Evans-Allen#1024525,and Capacity Building Grant#006531supported in part by the US National Science Foundation RII Track 2 FEC:Leveraging Intelligent Informatics and Smart Data for Improved Understanding of Northern Forest Ecosystem Resiliency(INSPIRES)#1920908by The Lyndhurst Foundation.
文摘Understanding local variation in forest biomass allows for a better evaluation of broad-scale patterns and interpretation of forest ecosystems’role in carbon dynamics.This study focuses on patterns of aboveground tree biomass within a fully censused 20 ha forest plot in a temperate forest of northern Alabama,USA.We evaluated the relationship between biomass and topography using ridge and valley landforms along with digitally derived moisture and solar radiation indices.Every live woody stem over 1 cm diameter at breast height within this plot was mapped,measured,and identified to species in 2019-2022,and diameter data were used along with speciesspecific wood density to map the aboveground biomass at the scale of 20 m×20 m quadrats.The aboveground tree biomass was 211 Mg·ha^(-1).Other than small stream areas that experienced recent natural disturbances,the total stand biomass was not associated with landform or topographic indices.Dominant species,in contrast,had strong associations with topography.American beech(Fagus grandifolia)and yellow-poplar(Liriodendron tulipfera)dominated the valley landform,with 37% and 54% greater biomass in the valley than their plot average,respectively.Three other dominant species,white oak(Quercus alba),southern shagbark hickory(Carya carolinaeseptentrionalis),and white ash(Fraxinus americana),were more abundant on slopes and benches,thus partitioning the site.Of the six dominant species,only sugar maple(Acer saccharum)was not associated with landform.Moreover,both topographic wetness and potential radiation indices were significant predictors of dominant species biomass within each of the landforms.The study highlights the need to consider species when examining forest productivity in a range of site conditions.
基金financed by the National Science Centre,Poland,under project No.2019/35/B/NZ8/01381 entitled"Impact of invasive tree species on ecosystem services:plant biodiversity,carbon and nitrogen cycling and climate regulation"by the Institute of Dendrology,Polish Academy of Sciences。
文摘Prunus serotina and Robinia pseudoacacia are the most widespread invasive trees in Central Europe.In addition,according to climate models,decreased growth of many economically and ecologically important native trees will likely be observed in the future.We aimed to assess the impact of these two neophytes,which differ in the biomass range and nitrogen-fixing abilities observed in Central European conditions,on the relative aboveground biomass increments of native oaks Qucrcus robur and Q.petraea and Scots pine Pinus sylvestris.We aimed to increase our understanding of the relationship between facilitation and competition between woody alien species and overstory native trees.We established 72 circular plots(0.05 ha)in two different forest habitat types and stands varying in age in western Poland.We chose plots with different abundances of the studied neophytes to determine how effects scaled along the quantitative invasion gradient.Furthermore,we collected growth cores of the studied native species,and we calculated aboveground biomass increments at the tree and stand levels.Then,we used generalized linear mixed-effects models to assess the impact of invasive species abundances on relative aboveground biomass increments of native tree species.We did not find a biologically or statistically significant impact of invasive R.pseudoacacia or P.serotina on the relative aboveground,biomass increments of native oaks and pines along the quantitative gradient of invader biomass or on the proportion of total stand biomass accounted for by invaders.The neophytes did not act as native tree growth stimulators but also did not compete with them for resources,which would escalate the negative impact of climate change on pines and oaks.The neophytes should not significantly modify the carbon sequestration capacity of the native species.Our work combines elements of the per capita effect of invasion with research on mixed forest management.
基金supported by the Guangxi Key R&D Program (project No. AB16380254)a research project of Guangxi Forestry Department (Guilinkezi [2015] No.5)supported a grant for Bagui Senior Fellow (C33600992001)。
文摘Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.
基金supported by the National Natural Science Foundation of China[grant numbers 41471419 and 31971579].
文摘There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the impact of the sampling strategy on model accuracy still need to be resolved.In this study,we first corrected the bias arising from upscaling the LG-AGB map to match the spatial resolution of Landsat observations.Subsequently,the stratified random sampling method was used to select training samples from the corrected LG-AGB map(cLG-AGB)for the Random Forest(RF)regression model.The RF model features were extracted from the Landsat observations and auxiliary data.The impact of strata numbers on model accuracy was explored during the sampling process.Finally,independent validation was conducted using in situ measurements.The results indicated that:(1)about 68% of the biases can be corrected in the up-scale transformation;(2)compared to no stratification,a three-strata model achieved a 6.5% improvement in AGB estimation accuracy while requiring a 37.8% reduction in sample size;(3)the black locust forest had a low saturation point at 60.52±4.46 Mg/ha AGB and 72.4%AGB values were underestimated and the remaining were overestimated.In summary,our study provides a framework to harmonize near-surface LiDAR and satellite data for AGB estimation in plantation forest ecosystems with small patch sizes and fragmented distribution.
基金the National Biomass Modeling Program for Continuous Forest Inventory(NBMP-CFI) funded by the State Forestry Administration of China
文摘Because of global climate change, it is necessary to add forest biomass estimation to national forest resource monitoring. The biomass equations developed for forest biomass estimation should be compatible with volume equations. Based on the tree volume and aboveground biomass data of Masson pine （Pinus massoniana Lamb.） in southern China, we constructed one-, two- and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations. The prediction precision of aboveground biomass estimates from one variable equa- tion exceeded 95%. The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height, although the contributions to regressions were statistically insignificant. For the biomass conversion function on one variable, the conversion factor decreased with increasing diameter, but for the conversion function on two variables, the conversion factor increased with increasing diameter but decreased with in- creasing tree height.
基金funded by the National Nonprofit Institute Research Grant of Chinese Academy of Forestry(CAFYBB2011003,CAFYBB2011002)the Key Laboratory of Agrometeorological Support and Applied Technique of China Meteorological Administration(AMF201107,AMF201204)the National Natural Science Foundation of China(40801173)
文摘Remote sensing is a valuable and effective tool for monitoring and estimating aboveground biomass （AGB） in large areas.The current international research on biomass estimation by remote sensing technique mainly focused on forests,grasslands and crops,with relatively few applications for desert ecosystems.In this paper,Landsat Thematic Mapper （TM）/Enhanced Thematic Mapper Plus （ETM＋） images from 1988 to 2007 and the data of 283 AGB samples in August 2007 were used to estimate the AGB for Mu Us Sandy Land over the past 30 years.Moreover,temporal and spatial distribution characteristics of AGB and influencing factors of climate and underlying surface were also studied.Results show that：（1） Differences of correlations exist in the fitted equations between AGB and different vegetation indices in desert areas.The modified soil adjusted vegetation index （MSAVI） and soil adjusted vegetation index （SAVI） show relatively higher correlations with AGB,while the correlation between normalized difference vegetation index （NDVI） and AGB is relatively lower.Error testing shows that the AGB-MSAVI model established can be used to accurately estimate AGB of Mu Us Sandy Land in August.（2） AGB in Mu Us Sandy Land shows the fluctuant characteristics over the past 30 years,which decreased from the 1980s to the 1990s,and increased from the 1990s to 2007.AGB in 2007 had the highest value,with a total AGB of 3.352×106 t.Moreover,in the 1990s,AGB had the lowest value with a total AGB of 2.328×106 t.（3） AGB with relatively higher values was mainly located in the middle and southern parts of Mu Us Sandy Land in the 1980s.AGB was low in the whole area in the1990s,and relatively higher AGB values were mainly located in the southern parts of Uxin.In 2007,AGB in the whole area was relatively higher than those of the last twenty years,and higher AGB values were mainly located in the northern,western and middle parts of Mu Us Sandy Land.
基金This study was financially supported by the National Natural Science Foundation of China(41501219)the Applied Basic Research Project of Shanxi Province(2016021136)+2 种基金the National College Students'Innovative Entrepreneurial Training Plan Program of China(201910119007)the Research Project of Philosophy and Social Sciences in Colleges and Universities of Shanxi Province(2019W134)the Soft Science Research Project of Shanxi Province(2018041072-1).
文摘Ecosystems in high-altitude regions are more sensitive and respond more rapidly than other ecosystems to global climate warming.The Qinghai-Tibet Plateau(QTP)of China is an ecologically fragile zone that is sensitive to global climate warming.It is of great importance to study the changes in aboveground biomass and species diversity of alpine meadows on the QTP under predicted future climate warming.In this study,we selected an alpine meadow on the QTP as the study object and used infrared radiators as the warming device for a simulation experiment over eight years(2011-2018).We then analyzed the dynamic changes in aboveground biomass and species diversity of the alpine meadow at different time scales,including an early stage of warming(2011-2013)and a late stage of warming(2016-2018),in order to explore the response of alpine meadows to short-term(three years)and long-term warming(eight years).The results showed that the short-term warming increased air temperature by 0.31℃and decreased relative humidity by 2.54%,resulting in the air being warmer and drier.The long-term warming increased air temperature and relative humidity by 0.19℃and 1.47%,respectively,and the air tended to be warmer and wetter.The short-term warming increased soil temperature by 2.44℃and decreased soil moisture by 12.47%,whereas the long-term warming increased soil temperature by 1.76℃and decreased soil moisture by 9.90%.This caused the shallow soil layer to become warmer and drier under both short-term and long-term warming.Furthermore,the degree of soil drought was alleviated with increased warming duration.Under the long-term warming,the importance value and aboveground biomass of plants in different families changed.The importance values of grasses and sedges decreased by 47.56%and 3.67%,respectively,while the importance value of weeds increased by 1.37%.Aboveground biomass of grasses decreased by 36.55%,while those of sedges and weeds increased by 8.09%and 15.24%,respectively.The increase in temperature had a non-significant effect on species diversity.The species diversity indices increased at the early stage of warming and decreased at the late stage of warming,but none of them reached significant levels(P>0.05).Species diversity had no significant correlation with soil temperature and soil moisture under both short-term and long-term warming.Soil temperature and aboveground biomass were positively correlated in the control plots(P=0.014),but negatively correlated under the long-term warming(P=0.013).Therefore,eight years of warming aggravated drought in the shallow soil layer,which is beneficial for the growth of weeds but not for the growth of grasses.Warming changed the structure of alpine meadow communities and had a certain impact on the community species diversity.Our studies have great significance for the protection and effective utilization of alpine vegetation,as well as for the prevention of grassland degradation or desertification in high-altitude regions.
基金funded by the National Natural Science Foundation of China(Grant Nos.91025011,91125013,41222001)the Project for Incubation of Specialists in Glaciology and Geocryology of National Natural Science Foundation of China(J1210003/J0109)
文摘Shrublands serve as an important component of terrestrial ecosystems, and play an important role in structure and functions of alpine ecosystem.Accurate estimation of biomass is critical to examination of the productivity of alpine ecosystems, due to shrubification under climate change in past decades.In this study, 14 experimental plots and 42 quadrates of the shrubs Potentilla fruticosa and Caragana jubata were selected along altitudes gradients from 3220 to 3650 m a.s.l.(above sea level) on semi-sunny and semi-shady slope in Hulu watershed of Qilian Mountains, China.The foliage, woody component and total aboveground biomass per quadrate were examined using a selective destructive method, then the biomass were estimated via allometric equations based on measured parameters for two shrub species.The results showed that C.jubata accounted for 1–3 times more biomass(480.98 g/m2) than P.fruticosa(191.21 g/m2).The aboveground biomass of both the shrubs varied significantly with altitudinal gradient(P<0.05).Woody component accounted for the larger proportion than foliage component in the total aboveground biomass.The biomass on semi-sunnyslopes(200.27 g/m2 and 509.07 g/m2) was greater than on semi-shady slopes(182.14 g/m2 and 452.89g/m2) at the same altitude band for P.fruticosa and C.jubata.In contrast, the foliage biomass on semi-shady slopes(30.50 g/m2) was greater than on semi-sunny slopes(27.51 g/m2) for two shrubs.Biomass deceased with increasing altitude for P.fruticosa, whereas C.jubata showed a hump-shaped pattern with altitude.Allometric equations were obtained from the easily descriptive parameters of height(H), basal diameter(D) and crown area(C) for biomass of C.jubata and P.fruticosa.Although the equations type and variables comprising of the best model varied among the species, all equations related to biomass were significant(P < 0.005), with determination coefficients(R2) ranging from 0.81 to 0.96.The allometric equations satisfied the requirements of the model, and can be used to estimate the regional scale biomass of P.fruticosa and C.jubata in alpine ecosystems of the Qilian Mountains.
基金National Basic Research Program of China（973 Program）,No.2015CB452702 National Natural Science Foundation of China,No.41571098,No.41371196,No.41530749 National Key Technology R＆D Program,No.2013BAC03B04
文摘Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change（ABM/LUCC）, an ecosystem process model（PnET-Ⅱ）, and a forest dynamic landscape model（LANDIS-Ⅱ） to simulate the change of forest aboveground biomass（AGB） which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that：（1） land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County.（2） Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7%（RCP2.6 ＋ land use）, 57.2%（RCP4.5 ＋ land use）, and 56.9%（RCP8.5 ＋ land use） by 2050, which is in comparison to the results under separate RCPs without land use disturbance.（3） The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function,and developing measures for sustainable forest management.
基金National Key R&D Program of China,No.2018YFA0606102National Natural Science Foundation of China,No.41771056National Key Technology Support Program,No.2012BAH31B02
文摘Aboveground biomass in grasslands of the Qinghai-Tibet Plateau has displayed an overall increasing trend during 2003–2016, which is profoundly influenced by climate change. However, the responses of different biomes show large discrepancies, in both size and magnitude. By applying partial least squares regression, we calculated the correlation between peak aboveground biomass and mean monthly temperature and monthly total precipitation in the preceding 12 months for three different grassland types(alpine steppe, alpine meadow, and temperate steppe) on the central and eastern Qinghai-Tibet Plateau. The results showed that mean temperature in most preceding months was positively correlated with peak aboveground biomass of alpine meadow and alpine steppe, while mean temperature in the preceding October and February to June was significantly negatively correlated with peak aboveground biomass of temperate steppe. Precipitation in all months had a promoting effect on biomass of alpine meadow, but its correlations with biomass of alpine steppe and temperate steppe were inconsistent. It is worth noting that, in a warmer, wetter climate, peak aboveground biomass of alpine meadow would increase more than that of alpine steppe, while that of temperate steppe would decrease significantly, providing support for the hypothesis of conservative growth strategies by vegetation in stressed ecosystems.
文摘Allometric equations are important for quantifying biomass and carbon storage in terrestrial forest ecosystems.However,equations for dry deciduous woodland ecosystems,an important carbon sink in the lowland areas of Ethiopia have not as yet been developed.This study attempts to develop and evaluate species-specific allometric equations for predicting aboveground biomass(AGB)of dominant woody species based on data from destructive sampling for Combretum collinum,Combretum molle,Combretum harotomannianum,Terminalia laxiflora and mixed-species.Diameter at breast height ranged from 5 to 30 cm.Two empirical equations were developed using DBH(Eq.1)and height(Eq.2).Equation 2 gave better AGB estimations than Eq.1.The inclusion of both DBH and H were the best estimate biometric variables for AGB.Further,the equations were evaluated and compared with common generic allometric equations.The result showed that our allometric equations are appropriate for estimating AGB.The development and application of empirical species-specific allometric equations is crucial to improve biomass and carbon stock estimation for dry woodland ecosystems.
基金supported by the National Key Research and Development Program of China(2017YFD0200202)the National Natural Science Foundation of China(U1404315)+1 种基金the China Scholarship Council(201608410278)the Natural Science Foundation of Henan Province(182300410014)。
文摘Intercropping of maize(Zea mays L.) and peanut(Arachis hypogaea L.) often results in greater yields than the respective sole crops. However, there is limited knowledge of aboveground and belowground interspecific interactions between maize and peanut in field. A two-year field experiment was conducted to investigate the effects of interspecific interactions on plant growth and grain yield for a peanut/maize intercropping system under different nitrogen(N) and phosphorus(P) levels. The method of root separation was employed to differentiate belowground from aboveground interspecific interactions. We observed that the global interspecific interaction effect on the shoot biomass of the intercropping system decreased with the coexistence period, and belowground interaction contributed more than aboveground interaction to advantages of the intercropping in terms of shoot biomass and grain yield. There was a positive effect from aboveground and belowground interspecific interactions on crop plant growth in the intercropping system, except that aboveground interaction had a negative effect on peanut during the late coexistence period. The advantage of intercropping on grain came mainly from increased maize yield(means 95%) due to aboveground interspecific competition for light and belowground interaction(61%–72% vs. 28%–39% in fertilizer treatments). There was a negative effect on grain yield from aboveground interaction for peanut, but belowground interspecific interaction positively affected peanut grain yield.The supply of N, P, or N + P increased grain yield of intercropped maize and the contribution from aboveground interspecific interaction. Our study suggests that the advantages of peanut/maize intercropping for yield mainly comes from aboveground interspecific competition for maize and belowground interspecific facilitation for peanut, and their respective yield can be enhanced by N and P. These findings are important for managing the intercropping system and optimizing the benefits from using this system.
基金the Natural Science Foundation of China(Nos.31670552,31971577)China Postdoctoral Science Foundation(No.2019 M651842)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Background:Aboveground biomass(AGB)is a fundamental indicator of forest ecosystem productivity and health and hence plays an essential role in evaluating forest carbon reserves and supporting the development of targeted forest management plans.Methods:Here,we proposed a random forest/co-kriging framework that integrates the strengths of machine learning and geostatistical approaches to improve the mapping accuracies of AGB in northern Guangdong Province of China.We used Landsat time-series observations,Advanced Land Observing Satellite(ALOS)Phased Array L-band Synthetic Aperture Radar(PALSAR)data,and National Forest Inventory(NFI)plot measurements,to generate the forest AGB maps at three time points(1992,2002 and 2010)showing the spatio-temporal dynamics of AGB in the subtropical forests in Guangdong,China.Results:The proposed model was capable of mapping forest AGB using spectral,textural,topographical variables and the radar backscatter coefficients in an effective and reliable manner.The root mean square error of the plotlevel AGB validation was between 15.62 and 53.78 t∙ha^(−1),the mean absolute error ranged from 6.54 to 32.32 t∙ha^(−1),the bias ranged from−2.14 to 1.07 t∙ha^(−1),and the relative improvement over the random forest algorithm was between 3.8%and 17.7%.The largest coefficient of determination(0.81)and the smallest mean absolute error(6.54 t∙ha^(−1)were observed in the 1992 AGB map.The spectral saturation effect was minimized by adding the PALSAR data to the modeling variable set in 2010.By adding elevation as a covariable,the co-kriging outperformed the ordinary kriging method for the prediction of the AGB residuals,because co-kriging resulted in better interpolation results in the valleys and plains of the study area.Conclusions:Validation of the three AGB maps with an independent dataset indicated that the random forest/cokriging performed best for AGB prediction,followed by random forest coupled with ordinary kriging(random forest/ordinary kriging),and the random forest model.The proposed random forest/co-kriging framework provides an accurate and reliable method for AGB mapping in subtropical forest regions with complex topography.The resulting AGB maps are suitable for the targeted development of forest management actions to promote carbon sequestration and sustainable forest management in the context of climate change.
基金supported by the CAS Strategic Priority Research Program(No.XDA19030402)the National Key Research and Development Program of China(No.2016YFD0300101)+2 种基金the Natural Science Foundation of China(Nos.31571565,31671585)the Key Basic Research Project of the Shandong Natural Science Foundation of China(No.ZR2017ZB0422)Research Funding of Qingdao University(No.41117010153)
文摘Forests account for 80%of the total carbon exchange between the atmosphere and terrestrial ecosystems.Thus,to better manage our responses to global warming,it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB).Different levels of detail are needed to estimate FAGB at local,regional and national scales.Multi-scale remote sensing analysis from high,medium and coarse spatial resolution data,along with field sampling,is one approach often used.However,the methods developed are still time consuming,expensive,and inconvenient for systematic monitoring,especially for developing countries,as they require vast numbers of field samples for upscaling.Here,we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites.The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m),Landsat(30 m)and Google Earth very high resolution(GEVHR)Quickbird(0.65 m)images.For the local scale(Kayerkhola watershed),tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images.An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot.A TCC vs.FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots.A coefficient of determination(R2)of 0.76 was obtained in the modelling,and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district,open source GEVHR images were used as virtual field plots.We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model.Using the multivariate adaptive regression splines machine learning algorithm,we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices.The model was then used to extrapolate FAGB to the entire district.This approach considerably reduced the need for field data and commercial very high resolution imagery while achieving two-scale forest information and FAGB estimates at high resolution(30 m)and accuracy(R2=0.76 and 0.7)with minimal error(RMSE=64 and 38 tons ha-1)at local and regional scales.This methodology is a promising technique for cost-effective FAGB and carbon estimations and can be replicated with limited resources and time.The method is especially applicable for developing countries that have low budgets for carbon estimations,and it is also applicable to the Reducing Emissions from Deforestation and Forest Degradation(REDD?)monitoring reporting and verification processes.
基金funded by the National Natural Science Foundation of China (Grant No.31170414)the 100 Talents Program of Chinese Academy of Sciences,and the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No.XDA05060600)
文摘Soil respiration from decomposing aboveground litter is a major component of the terrestrial carbon cycle. However, variations in the contribution of aboveground litter to the total soil respiration for stands of varying ages are poorly understood. To assess soil respiration induced by aboveground litter, treatments of litter and no litter were applied to 5-, l0-, and 20-year-old stands of Populus davidiana Dode in the sandstorm source area of Beijing-Tianjin, equations were applied to China. Optimal nonlinear model the combined effects of soil temperature and soil water content on soil respiration. Results showed that the monthly average contribution of aboveground litter to total soil respiration were 18.46% ± 4.63%, 16.64% ± 9.31%, and 22.37% ± 8.17% for 5-, 10-, and ao-year-old stands, respectively. The relatively high contribution in 5- and 20-year-old stands could be attributed to easily decomposition products and high accumulated litter, resoectivelv. Also. it fluctuated monthly for all stand ages due to substrate availability caused by phenology and environmental factors. Litter removal significantly decreased soil respiration and soil water content for all stand ages （P 〈 0.05） but not soil temperature （P 〉 0.05）. Variations of soil respiration could be explained by soil temperature at 5-cm depth using an exponential equation and by soil water content at lo-cm depth using a quadratic equation, whereas soil respiration was better modeled using the combined parameters of soil temperature and soil water content than with either soil temperature or soil water content alone. Temperature sensitivity （Q10） increased with stand age in both the litter and the no litter treatments. Considering the effects of aboveground litter, this study provides insights for predicting future soil carbon fluxes and for accurately assessing soil carbon budgets.
基金Funding was provided by the Swedish NFI Development Foundationthe Swedish Kempe Foundation (SMK-1847)。
文摘Background: The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging(LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference.Results: Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km2 large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m×18 m map units was found to range between 9 and 447 Mg·ha^-1. The corresponding root mean square errors ranged between 10 and 162 Mg·ha^-1. For the entire study region, the mean aboveground biomass was 55 Mg·ha^-1 and the corresponding relative root mean square error 8%. At this level 75%of the mean square error was due to the uncertainty associated with tree-level models.Conclusions: Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study.
