Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

Modification of an ecosystem model for filling medium-sized gaps in tower-based estimates of net ecosystem productivity

Gap filling of flux data is necessary to assist with periodic interruptions in the measurement data stream. The gap-filling model (GFM), first described in Xing et al. [Xing, Z., Bourque, C.P.-A., Meng, F.-R., Zha, T.-S., Cox, R.M., Swift, E., 2007. A simple net ecosystem productivity model for gap filling of tower-based fluxes: an extension of Landsberg's equation with modifications to the light interception term. Ecol. Model. 206, 250–262], was modified to account for the day-to-day control of net ecosystem productivity (NEP) by incorporating air and soil temperature as new controlling variables in the calculation of NEP. To account for the multiple-phase influences of air and soil temperature on plant growth we model ecosystem respiration as a function of soil and canopy respiration. The paper presents model development in an incremental fashion in order to quantify the contribution of individual model enhancements to the prediction of NEP during periods when air and soil temperature variations are important.     

Acknowledging the spatial heterogeneity in modelling/reconstructing carbon dioxide exchange in a northern aapa mire

Chamber method is commonly used to measure the CO₂ exchange from plant communities. Due to low time resolution, actual measurements reflect only momentary CO₂ exchange rates. Therefore, a common way to derive seasonal or annual estimates is to establish models describing the response of CO₂ exchange to environmental variables, and then to reconstruct the CO₂ exchange over the desired time period. There are several alternative ways to obtain the CO₂ balance for the entire mire: models can be parameterized by individual sample plots, plant communities or the entire site. Similarly, the CO₂ balance can be reconstructed by plots, plant communities or the entire site. We tested how the choice of the modelling and reconstruction approach influences the CO₂ exchange estimates for the entire mire and for individual sample plots and plant communities. We measured the CO₂ exchange in a spatially heterogeneous sedge-dominated northern aapa mire for two growing seasons. We observed high spatial variation in CO₂ balance between the plant communities. We noticed that when the CO₂ balances of individual sample plots or plant communities are of interest, using a model appropriate for the entire site may result in biased estimates. In worst case the different modelling approaches may turn the CO₂ balance of an individual sample plot from positive to negative. Further, while using the whole ecosystem approach in modelling, the superior ability of chamber method in acknowledging spatial variation is lost. While the modelled growing season CO₂ balance of the mire ranged from 232 to 625 g CO₂ m⁻² depending on the chosen modelling and reconstruction approach, the average estimates still remained within the uncertainty range of one another. Acknowledgement of the spatial variation in plant community level makes the areal estimate more robust to varying weather conditions. Further, the reliability of estimates is improved by explicit formulation of the choices behind the modelling and reconstruction units reflecting the study objectives.     

基于CPNtools的环评工程分析信息化技术的研究

以东北制药总厂现状环境评价为例,首先抽象出其采用的代数系统,然后构建了与其同构的着色PetriNet模型,并运用CPNtools完成了环境评价学的各种分析和论证,从而为构建C4ISRE奠定了基础。     

Refining the ecological footprint

Ecological footprint measures how much of the biosphere’s annual regenerative capacity is required to renew the natural resources used by a defined population in a given year. Ecological footprint analysis (EFA) compares the footprint with biocapacity. When a population’s footprint is greater than biocapacity it is reported to be engaging in ecological overshoot. Recent estimates show that humanity’s footprint exceeds Earth’s biocapacity by 23%. Despite increasing popularity of EFA, definitional, theoretical, and methodological issues hinder more widespread scientific acceptance and use in policy settings. Of particular concern is how EFA is defined and what it actually measures, exclusion of open oceans and less productive lands from biocapacity accounts, failure to allocate space for other species, use of agricultural productivity potential as the basis for equivalence factors (EQF), how the global carbon budget is allocated, and failure to capture unsustainable use of aquatic or terrestrial ecosystems. This article clarifies the definition of EFA and proposes several methodological and theoretical refinements. Our new approach includes the entire surface of the Earth in biocapacity, allocates space for other species, changes the basis of EQF to net primary productivity (NPP), reallocates the carbon budget, and reports carbon sequestration biocapacity. We apply the new approach to footprint accounts for 138 countries and compare our results with output from the standard model. We find humanity’s global footprint and ecological overshoot to be substantially greater, and suggest the new approach is an important step toward making EFA a more accurate and meaningful sustainability assessment tool.

网格监测统计积分模式的推导与应用

把大气污染物的空间分布看成是连续变化的超曲面,采用积分法推导网格监测点位均值的积分模式,并由此推导监测范围内污染物总量模式。利用丹东市环境空气SO2被动扩散网格监测数据,采用此模式计算其趋势值和均值。     

Changes in Land Cover and Subsequent Effects on Lower Fraser Basin Ecosystems from 1827 to 1990

/ European settlement began in the Lower Fraser Basin (LFB) inwestern British Columbia in 1827 and has impacted the basin ecosystem in anumber of ways, especially affecting the vegetation. Using previouslypublished data, air photos, and other historical material for the area,estimates of land cover were made for the years prior to 1827 and for 1930and 1990. The area of coniferous forest changed from 71% prior to 1827to 50% in 1930 to 54% in 1990. However, prior to 1827, only27% of the forest would have been immature (<120 years old), while40% would have been immature in 1930 and 73% of the forest wasimmature in 1990. The amount of wetland area decreased from 10% to1% of the study area while urban and agricultural area increased to26% of the study area by 1990. The changes in land cover have hadadverse effects on soil, water, and air quality; aquatic life; and plant andanimal populations. Estimates of changes in net primary production andorganic soil carbon suggest a decline over the past 170 years, although thelatter rate of decrease has slowed since 1930. As human populations in theLower Fraser Basin continue to increase, the quality of air, water, and soilwill continue to decline unless measures are taken.KEY WORDS: Human impact; Land cover; Net primary productivity; Organiccarbon in soil     

Observation and simulation of net primary productivity in Qilian Mountain, western China

We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.