Ecohydrological modelling with EcH2O‐iso to quantify forest and grassland effects on water partitioning and flux ages

We used the new process‐based, tracer‐aided ecohydrological model EcH₂O‐iso to assess the effects of vegetation cover on water balance partitioning and associated flux ages under temperate deciduous beech forest (F) and grassland (G) at an intensively monitored site in Northern Germany. Unique, multicriteria calibration, based on measured components of energy balance, hydrological function and biomass accumulation, resulted in good simulations reproducing measured soil surface temperatures, soil water content, transpiration, and biomass production. Model results showed the forest “used” more water than the grassland; of 620 mm average annual precipitation, losses were higher through interception (29% under F, 16% for G) and combined soil evaporation and transpiration (59% F, 47% G). Consequently, groundwater (GW) recharge was enhanced under grassland at 37% (~225 mm) of precipitation compared with 12% (~73 mm) for forest. The model tracked the ages of water in different storage compartments and associated fluxes. In shallow soil horizons, the average ages of soil water fluxes and evaporation were similar in both plots (~1.5 months), though transpiration and GW recharge were older under forest (~6 months compared with ~3 months for transpiration, and ~12 months compared with ~10 months for GW). Flux tracking using measured chloride data as a conservative tracer provided independent support for the modelling results, though highlighted effects of uncertainties in forest partitioning of evaporation and transpiration. By tracking storage—flux—age interactions under different land covers, EcH₂O‐iso could quantify the effects of vegetation on water partitioning and age distributions. Given the likelihood of drier, warmer summers, such models can help assess the implications of land use for water resource availability to inform debates over building landscape resilience to climate change. Better conceptualization of soil water mixing processes and improved calibration data on leaf area index and root distribution appear obvious respective modelling and data needs for improved simulations.     

Simulated water budget of a small forested watershed in the continental/maritime hydroclimatic region of the United States

Annual streamflows have decreased across mountain watersheds in the Pacific Northwest of the United States over the last ~70 years; however, in some watersheds, observed annual flows have increased. Physically based models are useful tools to reveal the combined effects of climate and vegetation on long‐term water balances by explicitly simulating the internal watershed hydrological fluxes that affect discharge. We used the physically based Simultaneous Heat and Water (SHAW) model to simulate the inter‐annual hydrological dynamics of a 4 km² watershed in northern Idaho. The model simulates seasonal and annual water balance components including evaporation, transpiration, storage changes, deep drainage, and trends in streamflow. Independent measurements were used to parameterize the model, including forest transpiration, stomatal feedback to vapour pressure, forest properties (height, leaf area index, and biomass), soil properties, soil moisture, snow depth, and snow water equivalent. No calibrations were applied to fit the simulated streamflow to observations. The model reasonably simulated the annual runoff variations during the evaluation period from water year 2004 to 2009, which verified the ability of SHAW to simulate the water budget in this small watershed. The simulations indicated that inter‐annual variations in streamflow were driven by variations in precipitation and soil water storage. One key parameterization issue was leaf area index, which strongly influenced interception across the catchment. This approach appears promising to help elucidate the mechanisms responsible for hydrological trends and variations resulting from climate and vegetation changes on small watersheds in the region. Copyright © 2015 John Wiley & Sons, Ltd.     

Lumped parameter sensitivity analysis of a distributed hydrological model within tropical and temperate catchments

Parameter sensitivity of the Distributed Hydrology‐Soil‐Vegetation Model (DHSVM) was studied in two contrasting environments: (1) Pang Khum Experimental Watershed (PKEW) in tropical northern Thailand; and (2) Cedar River basin (CRB) in Washington State of the temperate US Pacific Northwest. The analysis shows that for both basins, the most sensitive soil parameters were porosity, lateral saturated hydraulic conductivity, and the exponential decrease rate of lateral saturated hydraulic conductivity with soil depth. The most sensitive vegetation parameters were leaf area index, vegetation height, vapour pressure deficit, minimum stomatal resistance (for both grassland and forest scenarios), hemisphere fractional coverage, overstory fractional coverage, and trunk space (for the forest scenario only). Parameter sensitivity was basin‐specific, with the humid, temperate CRB being more influenced by vegetation parameters, while tropical PKEW was more influenced by soil properties. Increases and decreases in parameter values resulted in opposite and unequal changes in bias and root mean square error (RMSE), indicating the non‐linearity of physical process represented in the hydrological model. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatial patterns of vegetation and climate in the North China Plain during the Last Glacial Maximum and Holocene climatic optimum

Reconstructing the spatial patterns of regional climate and vegetation during specific intervals in the past is important for assessing the possible responses of the ecological environment under future global warming scenarios. In this study, we reconstructed the history of regional vegetation and climate based on six radiocarbon-dated pollen records from the North China Plain. Combining the results with existing pollen records, we reconstruct the paleoenvironment of the North China Plain during the Last Glacial Maximum(LGM) and the Holocene Climatic Optimum(HCO). The results show that changes in the regional vegetation since the LGM were primarily determined by climatic conditions, the geomorphic landscape and by human activity.During the LGM, the climate was cold and dry; mixed broadleaf-coniferous forest and deciduous-evergreen broadleaf forest developed in the southern mountains, and cold-resistant coniferous forest and mixed broadleaf-coniferous forest were present in the northern mountains. The forest cover was relatively low, with mesophytic and hygrophilous meadow occupying the southern part of the plain, and temperate grassland and desert steppe were distributed in the north; Chenopodiaceae-dominated halophytes grew on the exposed continental shelf of the Bohai Sea and Yellow Sea. During the HCO, the climate was warm and wet;deciduous broadleaf forest and deciduous-evergreen broadleaf forest, with subtropical species, developed in the southern mountains, and deciduous broadleaf forest with thermophilic species was present in northern mountains. Although the degree of forest cover was greater than during the LGM, the vegetation of the plain area was still dominated by herbs, while halophytes had migrated inland due to sea level rise. In addition, the expansion of human activities, especially the intensification of cultivation,had a significant influence on the natural vegetation. Our results provide data and a scientific basis for paleoclimate modelling and regional carbon cycle assessment in north China, with implications for predicting changes in the ecological environment under future global warming scenarios.     

基于简化参数方法的蒙古干旱区土壤湿度被动微波遥感

卫星被动微波遥感土壤湿度,是准确分析大空间尺度上陆表水分变化信息的有效手段.美国航天局(NASA)发布的基于AMSR-E观测亮温资料的全球土壤湿度反演产品,在蒙古干旱区的实际精度并不令人满意.本文基于对地表微波辐射传输中地表粗糙度和植被层影响的简化处理方法,采用AMSR-E的6.9 GHz,10.7 GHz和18.7 GHz之V极化亮温资料,应用多频率反演算法,并以国际能量和水循环协同观测计划(The Coordinated Energy and Water Cycle Observations Project)即CEOP实验在蒙古国东部荒漠地区的地面实验资料作为先验知识,获取被动微波遥感模型的优化参数,以期获得蒙古干旱区精度更高的土壤湿度遥感估算结果.分析表明,本文方法反演的白天和夜间土壤湿度结果与地面验证值之间的均方根误差(RMSE)接近0.030 cm³/cm³, 证明所用方法在不需要其他辅助资料或参数帮助下,可较精确地反演干旱区表层土壤湿度信息,能够全天候、动态监测大空间尺度的土壤湿度变化,可为干旱区气候变化研究及陆面过程模拟和数据同化研究提供高精度的表层土壤湿度初始场资料.     

基于多植物生长模式的SWAT模型的修正与有效性初探

以农林系统的非点源污染模拟为目标,通过研究建立变化密度及多种类混杂的森林生长模型,修正了SWAT模型采用平均森林植被密度和单一植物生长模式估算生物累积量的问题,并建立了与之相适应的森林优势组份丰度遥感反演模型、叶面积指数和消光系数遥感反演模型以获取森林生长模型的相关参数.同时,根据间作套种下的辐射能利用Keating方程,引入间作套种指数变量,修正SWAT原有的单一生物量日积累模型,探讨了作物复种指数、间作套种指数遥感反演方法和以此为基础的作物间作套种生长模型.以亚热带季风湿润区红壤背景下的鄱阳湖流域子流域梅江流域为试验区,以野外实测数据为基础,探讨修正SWAT模型的有效性.结果表明:修正后的SWAT模型与原始SWAT模型相比,在模拟流量和营养盐负荷方面,得到了较好的改善.在模拟流量方面,有效性提高了7.8%,流量峰值的模拟也得到了改善,能更好地反映地表蓄流方面的实际情况;在模拟营养盐负荷方面,有效性提高了6.4%(总磷)和6.1%(总氮).     

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The τ–ω model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types.     

基于无人机和卫星遥感影像的升金湖草滩植被地上生物量反演

湿地植被地上生物量是衡量湿地生态系统健康状况的重要指标,对于珍稀水禽越冬繁殖、全球碳循环、生态净化具有重要意义,是生态学与遥感解译的研究热点之一.针对于地上生物量的测算,卫星遥感数据覆盖范围广但其空间分辨率较低,无人机遥感数据空间分辨率高但采集范围小,同时受湿地面积、观测系统及外界环境等条件的影响,使得遥感影像地上生物量反演更加复杂和困难.本研究基于无人机和高分一号数据对升金湖草滩植被地上生物量反演进行研究,结合升金湖保护区4个样区无人机可见光影像与相应样区实测样本数据,建立地上生物量与可见光波段、多种可见光植被指数的线性、幂函数、多项式、对数回归模型,并通过可决系数（R²）、平均绝对误差（MAE）和均方根误差（RMSE）对模型进行精度评价,选择最优模型对无人机影像进行地上生物量反演;通过可见光波段反演得到的生物量,与高分一号WFV归一化差分植被指数（Normalized Difference Vegetation Index,NDVI）影像相结合进行回归建模,获取整个升金湖草滩植被地上生物量分布.结果表明,利用无人机红光波段建立的多项式方程对地上生物量反演有着最高模拟精度,R²=0.86、预测精度MAE=111.33 g/m²、RMSE=145.42 g/m²,且红光波段生物量反演方法得到的结果与实际生物量分布一致性较高,高分一号WFV NDVI与无人机反演生物量构建的多项式模型为最优模型,R²为0.91.本研究利用无人机和高分一号数据进行生物量反演研究,整合多源遥感数据优点,以获取更加丰富和准确的信息,进而提高地上生物量反演精度,为湿地监测和湿地恢复管理提供数据和技术支撑,具有重要研究意义和应用价值.     

Biotic controls on shallow translational landslides

In undisturbed tropical montane rainforests massive organic layers accommodate the majority of roots and only a small fraction of roots penetrate the mineral soil. We investigated the contribution of vegetation to slope stability in such environments by modifying a standard model for slope stability to include an organic layer with distinct mechanical properties. The importance of individual model parameters was evaluated using detailed measurements of soil and vegetation properties to reproduce the observed depth of 11 shallow landslides in the Andes of southern Ecuador. By distinguishing mineral soil, organic layer and above‐ground biomass, it is shown that in this environment vegetation provides a destabilizing effect mainly due to its contribution to the mass of the organic layer (up to 973 t ha^{? 1} under wet conditions). Sensitivity analysis shows that the destabilizing effect of the mass of soil and vegetation can only be effective on slopes steeper than 37.9°. This situation applies to 36% of the study area. Thus, on the steep slopes of this megadiverse ecosystem, the mass of the growing forest promotes landsliding, which in turn promotes a new cycle of succession. This feedback mechanism is worth consideration in further investigations of the impact of landslides on plant diversity in similar environments. Copyright © 2012 John Wiley & Sons, Ltd.     

Relative influence upon microwave emissivity of fine-scale stratigraphy,internal scattering,and dielectric properties

Summary The microwave emissivity of relatively low-loss media such as snow, ice, frozen ground, and lunar soil is strongly influenced by fine-scale layering and by internal scattering. Radiometric data, however, are commonly interpreted using a model of emission from a homogeneous, dielectric halfspace whose emissivity derives exclusively from dielectric properties. Conclusions based upon these simple interpretations can be erroneous. Examples are presented showing that the emission from fresh or hardpacked snow over either frozen or moist soil is governed dominantly by the size distribution of ice grains in the snowpack. Similarly, the thickness of seasonally frozen soil and the concentration of rock clasts in lunar soil noticeably affect, respectively, the emissivities of northern latitude soils in winter and of the lunar regolith. Petrophysical data accumulated in support of the geophysical interpretation of microwave data must include measurements of not only dielectric properties, but also of geometric factors such as finescale layering and size distributions of grains, inclusions, and voids.     

Simulated watershed responses to land cover changes using the Regional Hydro‐Ecological Simulation System

In this work, we used the Regional Hydro‐Ecological Simulation System (RHESSys) model to examine runoff sensitivity to land cover changes in a mountain environment. Two independent experiments were evaluated where we conducted simulations with multiple vegetation cover changes that include conversion to grass, no vegetation cover and deciduous/coniferous cover scenarios. The model experiments were performed at two hillslopes within the Weber River near Oakley, Utah watershed (USGS gauge # 10128500). Daily precipitation, air temperature and wind speed data as well as spatial data that include a digital elevation model with 30 m grid resolution, soil texture map and vegetation and land use maps were processed to drive RHESSys simulations. Observed runoff data at the watershed outlet were used for calibration and verification. Our runoff sensitivity results suggest that during winter, reduced leaf area index (LAI) decreases canopy interception resulting in increased snow accumulations and hence snow available for runoff during the early spring melt season. Increased LAI during the spring melt season tends to delay the snow melting process. This delay in snow melting process is due to reduced radiation beneath high LAI surfaces relative to low LAI surfaces. The model results suggest that annual runoff yield after removing deciduous vegetation is on average about 7% higher than with deciduous vegetation cover, while annual runoff yield after removing coniferous vegetation is on average as about 2% higher than that produced with coniferous vegetation cover. These simulations thus help quantify the sensitivity of water yield to vegetation change. Copyright © 2013 John Wiley & Sons, Ltd.     

Snowfall interception in a deciduous Nothofagus forest and implications for spatial snowpack distribution

Native Nothofagus forests in the midlatitude region of the Andes Cordillera are notorious biodiversity hot spots, uniquely situated in the Southern Hemisphere such that they develop in snow‐dominated reaches of this mountain range. Spanning a smaller surface area than similar ecosystems, where forests and snow coexist in the Northern Hemisphere, the interaction between vegetation and snow processes in this ecotone has received lesser attention. We present the first systematic study of snow–vegetation interactions in the Nothofagus forests of the Southern Andes, focusing on how the interplay between interception and climate determines patterns of snow water equivalent (SWE) variability. The Valle Hermoso experimental catchment, located in the Nevados de Chillán vicinity, was fitted with eight snow depth sensors that provided continuous measurements at varying elevations, aspect, and forest cover. Also, manual measurements of snow properties were obtained during snow surveys conducted during end of winter and spring seasons for 3 years, between 2015 and 2017. Each year was characterized by distinct climatological conditions, with 2016 representing one of the driest winters on record in this region. Distance to canopy, leaf area index, and total gap area were measured at each observational site. A regression model was built on the basis of statistical analysis of local parameters to model snow interception in this kind of forest. We find that interception implied a 23.2% reduction in snow accumulation in forested sites compared with clearings. The interception in these deciduous trees represents, on average, 23.6% of total annual snowfall, reaching a maximum measured interception value of 13.8‐mm SWE for all snowfall events analysed in this research.     

Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance. Forest aboveground biomass (AGB) is an important component in the land surface carbon cycle. In this study, using forest inventory data and forest distribution data, the AGB was estimated for forest in Daxinganlin in northeastern China by combining charge-coupled device (CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast (HJ-1) and Geoscience Laser Altimeter System (GLAS) waveform data from the Ice, Cloud and land Elevation Satellite (ICESat). The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing (CQ) Forest Center, which was calculated from forest inventory data. The resulted statistical regression models have a R ²=0.68 for conifer and R ²=0.71 for broadleaf forests. These models were used to estimate biomass for all GLAS footprints of forest located in the study area. All GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models (R ²=0.55 and R ²=0.52 for needle and broadleaf respectively). Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 data. Biomass data obtained from forest inventory data of the Zhuanglin (ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data (R ²=0.71). About 80% of biomass samples had an error less than 20 t ha⁻¹, and the mean error of all validation samples is 5.74 t ha⁻¹. The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area. It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estimate forest biomass with good precision, and the biomass data can be used as input data for future carbon budget analysis.

     

Identification of robust hyperspectral indices on forest leaf water content using PROSPECT simulated dataset and field reflectance measurements

In this study, we aim at finding efficient and robust hyperspectral indices for estimating forest leaf water content parameters (equivalent water thickness, EWT and fuel moisture content, FMC), which are useful for the understanding of terrestrial ecosystem functioning and evaluating fire risk. The most efficient hyperspectral indices have been identified (both on the context of index types and wavelength domains) using both a simulated dataset generated from the calibrated leaf reflectance model, PROSPECT, and datasets of field measured reflectance. Results indicate that high precision can be obtained using the type of vegetation index of two wavelength bands based on reflectance derivatives to estimate both parameters, with overall R² and RMSE of 0·60 ～ 0·75 and 0·0009 ～ 0·0012 g cm^?2 for EWT, 0·63 ～ 0·87 and 0·12 ～ 0·20 g g^?1 for FMC, respectively. The best indices identified in this study for vegetation water status in temperate deciduous forests were dSR (1510, 1560) for EWT and dSR (2110, 2260) for FMC, with widths of wavebands (Δλ) be variable up to 50 nm for both dSR indices. Despite the obvious discrepancies found in fit when applying the identified indices to different datasets, the indices identified in this study are applicable to various species (Dataset III), various phenological stages, different sites (Dataset I) and various leaf anatomies (Dataset II), and therefore suitable for an all inclusive wide range of application especially in temperate deciduous forests. Copyright © 2011 John Wiley & Sons, Ltd.     

Derivation of vegetative variables from a landsat tm image for modelling soil erosion

A study was carried out to assess the potential use of satellite thematic mapper (TM) images to produce maps of vegetation-related variables for erosion modelling. In a Mediterranean study area in southern France the (semi-)natural vegetation was described at 33 field plots using four quantitative methods: the Fosberg structural classification system, the cover and management factor of the Universal Soil Loss Equation, the leaf area index and the total percentage cover. After radiometric correction of the image, the spectral TM bands were processed following three different methods. Each method aimed at combining the data of the six spectral TM bands into a single band in such a way that the resulting image displayed optimal information on green vegetation cover. The algorithms used comprise the normalized difference vegetation index, the conventional ‘tasselled cap’ transformation and a locally tuned tasselled cap transformation. Only slight differences were found between the different methods to calculate spectral vegetation indices for this particular case. Furthermore, the correlations between the field variables and image-derived spectral indices are generally small. The largest correlations were found for the normalized vegetation index and the leaf area index (r + 0·71) and for the normalized vegetation index and Fosberg's structural vegetation classes (r + 0·76). However, Fosberg's method results in very general classes, which are of little use for soil erosion models. Furthermore, the spectral indices appeared to be sensitive for the vitality of the vegetation. Consequently, an area covered by a sensed, senescent vegetation will not yield a large value for the spectral index, but its soil is protected against splash erosion. This might lead to a misinterpretation of the soil protective cover when satellite images are used. A final conclusion is that a balance has to be found between the more accurate, but time-consuming field surveys to gather information on erosion-controlling factors and a certain loss of accuracy associated with the use of quick and easy remote sensing methods.     

Terrestrial vegetation carbon sinks in China, 1981―2000

Using China's ground observations, e.g., forest inventory, grassland resource, agricultural statistics, climate, and satellite data, we estimate terrestrial vegetation carbon sinks for China's major biomes between 1981 and 2000. The main results are in the following: (1) Forest area and forest biomass carbon (C) stock increased from 116.5×106 ha and 4.3 Pg C (1 Pg C = 1015 g C) in the early 1980s to 142.8×106 ha and 5.9 Pg C in the early 2000s, respectively. Forest biomass carbon density increased form 36.9 Mg C/ha (1 Mg C = 106 g C) to 41.0 Mg C/ha, with an annual carbon sequestration rate of 0.075 Pg C/a. Grassland, shrub, and crop biomass sequestrate carbon at annual rates of 0.007 Pg C/a, 0.014―0.024 Pg C/a, and 0.0125―0.0143 Pg C/a, respectively. (2) The total terrestrial vegetation C sink in China is in a range of 0.096―0.106 Pg C/a between 1981 and 2000, accounting for 14.6%―16.1% of carbon dioxide (CO2) emitted by China's industry in the same period. In addition, soil carbon sink is estimated at 0.04―0.07 Pg C/a. Accordingly, carbon sequestration by China's terrestrial ecosystems (vegetation and soil) offsets 20.8%―26.8% of its industrial CO2 emission for the study period. (3) Considerable uncertainties exist in the present study, especially in the estimation of soil carbon sinks, and need further intensive investigation in the future.     

A model to consider the spatial variability of rainfall partitioning within deciduous canopy. I. Model description

In this first paper of two, a numerical simulation model capable of simulating the spatial variability of rainfall partitioning within a canopy is presented. The second paper details how the model is parameterized, and some testing of its capabilities. The first stage of the model is to derive the mature canopy structure. This is achieved through simplified individual tree structures and a random placement routine based on a modified Poisson distribution. Following this the spatial discretization for throughfall is attained as a series of layers of triangles with a tree trunk at every apex. The number of layers is derived from the leaf area index through a modified Poisson distribution. Seasonal variation in the deciduous canopy is simulated through a time vector routine. The rainfall partitioning section of the model is based upon the Rutter model which has been modified to each individual triangle layer. The main feature of this model is that it offers a method of simulating rainfall partitioning at a scale that is a function of the size of the elementary physical components (tree and leaf scale). This can be used to investigate soil moisture variations under a canopy, or to study the variations within the forest hydrological processes themselves. © 1997 John Wiley & Sons, Ltd.     

Representation of canopy snow interception,unloading and melt in a parsimonious snowmelt model

Recent improvements in the Utah Energy Balance (UEB) snowmelt model are focused on snow–vegetation–atmosphere interactions to understand how different types of vegetation affect snow processes in the mountains of Western USA. This work presents field work carried out in the Rocky Mountains of Northern Utah to evaluate new UEB model algorithms that represent the processes of canopy snow interception, sublimation, mass unloading and melt. Four years' continuous field observations showed generally smaller accumulations of snow beneath the forest canopies in comparison with open (sage and grass) areas, a difference that is attributed to interception and subsequent sublimation and redistribution of intercepted snow by wind, much of it into surrounding open areas. Accumulations beneath the denser forest (conifer) canopies were found to be less than the accumulation beneath the less dense forest (deciduous) canopies. The model was able to represent the accumulation of snow water equivalent in the open and beneath the deciduous forest quite well but without accounting for redistribution tended to overestimate the snow water equivalent beneath the conifer forest. Evidence of redistribution of the intercepted snow from the dense forest (i.e. conifer forest) to the adjacent area was inferred from observations. Including a simple representation of redistribution in the model gave satisfactory prediction of snow water equivalent beneath the coniferous forest. The simulated values of interception, sublimation and unloading were also compared with previous studies and found in agreement. Copyright © 2013 John Wiley & Sons, Ltd.     

Land use changes and their relations with carbon cycles over the past 300 a in China

Land use and land cover in China have changed greatly during the past 300 a, indicated by the rapid abrupt decrease of forest land area and the rapid increase of cropland area, which can affect terrestrial carbon cycle greatly. The first-hand materials are used to analyze main characteristics for land use and land cover changes in China during the study period. The following conclusions can be drawn from this study. The cropland area in China kept increasing from 60.78×106 hm2 in 1661 to 96.09×106 hm2 in 1998. Correspondingly, the forest land area decreased from 248.13×106 hm2 in 1700 to 109.01×106 hm2 in 1949. Affected by such changes, the terrestrial ecosystem carbon storage decreased in the mean time. Car-bon lost from land use and land cover changes mainly consist of the loss from vegetation biomass and soil. In the past 300 a, about 3.70 PgC was lost from vegetation biomass, and emissions from soil ranged from 0.80 to 5.84 PgC. The moderate evaluation of soil losses was 2.48 PgC. The total loss from vegetation and soil was between 4.50 and 9.54 PgC. The moderate and optimum evaluation was 6.18 PgC. Such carbon losses distribution varied spatially from region to region. Carbon lost more significantly in Northeast China and Southwest China than in other regions, because losses of forest land in these two regions were far greater than in the other regions during the past 300 a. And losses of carbon in the other regions were also definite, such as Inner Mongolia, the western part of South China, the Xinjiang Uygur Autonomous Region, and the Qinghai-Tibet Plateau. But the carbon lost very little from the traditional agricultural regions in China, such as North China and East China. Studies on the relationship between land use and land cover change and carbon cycle in China show that the land use activities, especially those related to agriculture and forest management, began to affect terrestrial carbon storage positively in recent years.