Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model

The Lund–Potsdam–Jena Dynamic Global Vegetation Model (LPJ) combines process‐based, large‐scale representations of terrestrial vegetation dynamics and land‐atmosphere carbon and water exchanges in a modular framework. Features include feedback through canopy conductance between photosynthesis and transpiration and interactive coupling between these ‘fast’ processes and other ecosystem processes including resource competition, tissue turnover, population dynamics, soil organic matter and litter dynamics and fire disturbance. Ten plants functional types (PFTs) are differentiated by physiological, morphological, phenological, bioclimatic and fire‐response attributes. Resource competition and differential responses to fire between PFTs influence their relative fractional cover from year to year. Photosynthesis, evapotranspiration and soil water dynamics are modelled on a daily time step, while vegetation structure and PFT population densities are updated annually. Simulations have been made over the industrial period both for specific sites where field measurements were available for model evaluation, and globally on a 0.5°° × 0.5°° grid. Modelled vegetation patterns are consistent with observations, including remotely sensed vegetation structure and phenology. Seasonal cycles of net ecosystem exchange and soil moisture compare well with local measurements. Global carbon exchange fields used as input to an atmospheric tracer transport model (TM2) provided a good fit to observed seasonal cycles of CO₂ concentration at all latitudes. Simulated inter‐annual variability of the global terrestrial carbon balance is in phase with and comparable in amplitude to observed variability in the growth rate of atmospheric CO₂. Global terrestrial carbon and water cycle parameters (pool sizes and fluxes) lie within their accepted ranges. The model is being used to study past, present and future terrestrial ecosystem dynamics, biochemical and biophysical interactions between ecosystems and the atmosphere, and as a component of coupled Earth system models.     

Modelled effects of precipitation on ecosystem carbon and water dynamics in different climatic zones

The ongoing changes in the global climate expose the world's ecosystems not only to increasing CO₂ concentrations and temperatures but also to altered precipitation (P) regimes. Using four well-established process-based ecosystem models (LPJ, DayCent, ORCHIDEE, TECO), we explored effects of potential P changes on water limitation and net primary production (NPP) in seven terrestrial ecosystems with distinctive vegetation types in different hydroclimatic zones. We found that NPP responses to P changes differed not only among sites but also within a year at a given site. The magnitudes of NPP change were basically determined by the degree of ecosystem water limitation, which was quantified here using the ratio between atmospheric transpirational demand and soil water supply. Humid sites and/or periods were least responsive to any change in P as compared with moderately humid or dry sites/periods. We also found that NPP responded more strongly to doubling or halving of P amount and a seasonal shift in P occurrence than that to altered P frequency and intensity at constant annual amounts. The findings were highly robust across the four models especially in terms of the direction of changes and largely consistent with earlier P manipulation experiments and modelling results. Overall, this study underscores the widespread importance of P as a driver of change in ecosystems, although the ultimate response of a particular site will depend on the detailed nature and seasonal timing of P change.     

Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space

• 1 Advances in dynamic ecosystem modelling have made a number of different approaches to vegetation dynamics possible. Here we compare two models representing contrasting degrees of abstraction of the processes governing dynamics in real vegetation.
• 2 Model (a) (GUESS) simulates explicitly growth and competition among individual plants. Differences in crown structure (height, depth, area and LAI) influence relative light uptake by neighbours. Assimilated carbon is allocated individually by each plant to its leaf, fine root and sapwood tissues. Carbon allocation and turnover of sapwood to heartwood in turn govern height and diameter growth.
• 3 Model (b) (LPJ) incorporates a ‘dynamic global vegetation model’ (DGVM) architecture, simulating growth of populations of plant functional types (PFTs) over a grid cell, integrating individual‐level processes over the proportional area (foliar projective cover, FPC) occupied by each PFT. Individual plants are not simulated, but are replaced by explicit parameterizations of their growth and interactions.
• 4 The models are identical in their representation of core physiological and biogeochemical processes. Both also use the same set of PFTs, corresponding to the major woody plant groups in Europe, plus a grass type.
• 5 When applied at a range of locations, broadly spanning climatic variation within Europe, both models successfully predicted PFT composition and succession within modern natural vegetation. However, the individual‐based model performed better in areas where deciduous and evergreen types coincide, and in areas subject to pronounced seasonal water deficits, which would tend to favour grasses over drought‐intolerant trees.
• 6 Differences in model performance could be traced to their treatment of individual‐level processes, in particular light competition and stress‐induced mortality.
• 7 Our results suggest that an explicit individual‐based approach to vegetation dynamics may be an advantage in modelling of ecosystem structure and function at the resolution required for regional‐ to continental‐scale studies.

     

The use of CO2 flux measurements in models of the global terrestrial carbon budget

CO₂ flux measurements give access to two critical terms of the carbon budget of terrestrial ecosystems, the gross primary productivity (GPP) and the net ecosystem productivity (NEP). CO₂ fluxes measured by micrometeorological methods have spatial and temporal characteristics that make them potentially useful in modelling the global terrestrial carbon budget. The first use is in parameterizing ecosystem physiological processes. We present an example, based on parameterizing the mean light response of GPP. This parameterization can be used in diagnostic, satellite-based GPP models. A global application leads to realistic estimates of global GPP. The second use is in testing the seasonality of fluxes predicted by global models. Our example of this use tests two global GPP models. One is a diagnostic, satellite-based model, and one is a prognostic, process-based model. Despite the limitations of the models, both agree reasonably well with the measurements. The agreements and disagreements are useful in addressing the problems of available input datasets and representation of processes, in global models. Long-term CO₂ flux measurements give access to key variables of terrestrial vegetation models and therefore offer exciting perspectives.     

Large uncertainty in carbon uptake potential of land‐based climate‐change mitigation efforts

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land‐based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land‐based mitigation scenarios from two land‐use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ‐GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land‐use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land‐use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land‐use change. Differences between land‐use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land‐based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy.     

Sensitivity of African biomes to changes in the precipitation regime

Aim Africa is identified by the Inter‐governmental Panel on Climate Change (IPCC) as the least studied continent in terms of ecosystem dynamics and climate variability. The aim of this study was (1) to adapt the Lund‐Postdam‐Jena‐GUESS (LPJ‐GUESS) ecological modelling framework to Africa by providing new parameter values for tropical plant functional types (PFT), and (2) to assess the sensitivity of some African biomes to changes in precipitation regime. Location The study area was a representative transect (0–22° N and 7–18° E) through the transition from equatorial evergreen forests to savannas, steppes and desert northwards. The transect showed large latitudinal variation in precipitation (mean rainfall ranged from 50 to 2300 mm year^?1). Methods New PFT parameters used to calibrate LPJ‐GUESS were based on modern pollen PFTs and remote sensed leaf area index (LAI). The model was validated using independent modern pollen assemblages, LAI and through comparison with White's modern potential vegetation map. Several scenarios were developed by combining changes in total rainfall amount with variation in the length of the dry season in order to test the sensitivity of African biomes. Results Simulated vegetation compared well to observed data at local and regional scales, in terms of ecosystem functioning (LAI), and composition (pollen and White's vegetation map). The assessment of the sensitivity of biomes to changes in precipitation showed that none of the ecosystems would shift towards a new type under the range of precipitation increases suggested by the IPCC (increases from 5 to 20%). However, deciduous and semi‐deciduous forests may be very sensitive to small reductions in both the amount and seasonality of precipitation. Main conclusions This version of LPJ‐GUESS parameterized for Africa simulated correctly the vegetation present over a wide precipitation gradient. The biome sensitivity assessment showed that, compared with savannas and grasslands, closed canopy forests may be more sensitive to change in precipitation regime due to the synergetic effects of changed rainfall amounts and seasonality on vegetation functioning.     

涡度相关技术及其在陆地生态系统通量研究中的应用

通量观测是定量描述土壤-植被-大气间物质循环和能量交换过程的基础。涡度相关技术作为直接测量植被冠层与大气间能量与物质交换通量的技术手段, 已经逐步发展成为国际通用的通量观测标准方法。随着涡度相关技术在全球碳水循环研究中的广泛应用, 长期连续的通量观测正在为准确评价生态系统碳固持能力、水分和能量平衡状况、生态系统对全球气候变化的反馈作用、区域和全球尺度模型的优化与验证、极端事件对生态系统结构与功能影响等方面的研究提供重要数据支撑和机制理解途径。通过站点尺度通量长期动态观测, 明确了不同气候区和植被类型生态系统碳水通量强度基线及其季节与年际变异特征。通过多站点联网观测, 在区域和全球尺度研究生态系统碳通量空间变异特征, 揭示了区域尺度上温度和降水对生态系统碳通量空间格局的生物地理学控制机制。该文概括地介绍了涡度相关技术的基本原理、假设与系统构成, 总结了涡度通量长期联网观测在陆地生态系统碳水通量研究中的主要应用, 并对通量研究发展前景进行了展望。     

ORCHIDEE‐STICS,a process‐based model of sugarcane biomass production: calibration of model parameters governing phenology

Agro‐Land Surface Models (agro‐LSM) combine detailed crop models and large‐scale vegetation models (DGVMs) to model the spatial and temporal distribution of energy, water, and carbon fluxes within the soil–vegetation–atmosphere continuum worldwide. In this study, we identify and optimize parameters controlling leaf area index (LAI) in the agro‐LSM ORCHIDEE‐STICS developed for sugarcane. Using the Morris method to identify the key parameters impacting LAI, at eight different sugarcane field trial sites, in Australia and La Reunion island, we determined that the three most important parameters for simulating LAI are (i) the maximum predefined rate of LAI increase during the early crop development phase, a parameter that defines a plant density threshold below which individual plants do not compete for growing their LAI, and a parameter defining a threshold for nitrogen stress on LAI. A multisite calibration of these three parameters is performed using three different scoring functions. The impact of the choice of a particular scoring function on the optimized parameter values is investigated by testing scoring functions defined from the model‐data RMSE, the figure of merit and a Bayesian quadratic model‐data misfit function. The robustness of the calibration is evaluated for each of the three scoring functions with a systematic cross‐validation method to find the most satisfactory one. Our results show that the figure of merit scoring function is the most robust metric for establishing the best parameter values controlling the LAI. The multisite average figure of merit scoring function is improved from 67% of agreement to 79%. The residual error in LAI simulation after the calibration is discussed.     

Vegetation dynamics--simulating responses to climatic change

A modelling approach to simulating vegetation dynamics is described, incorporating critical processes of carbon sequestration, growth, mortality and distribution. The model has been developed to investigate the responses of vegetation to environmental change, at time scales from days to centuries and from the local to the global scale. The model is outlined and subsequent tests, against independent data sources, are relatively successful, from the small scale to the global scale. Tests against eddy covariance observations of carbon exchange by vegetation indicated significant differences between measured and simulated net ecosystem production (NEP). NEP is the net of large fluxes due to gross primary production and respiration, which are not directly measured and so there is some uncertainty in explaining differences between observations and simulations. In addition it was noted that closer agreement of fluxes was achieved for natural, or long-lived managed vegetation than for recently managed vegetation. The discrepancies appear to be most closely related to respiratory carbon losses from the soil, but this area needs further exploration. The differences do not scale up to the global scale, where simulated and measured global net biome production were similar, indicating that fluxes measured at the managed observed sites are not typical globally. The model (the Sheffield Dynamic Global Vegetation Model, SDGVM) has been applied to contemporary vegetation dynamics and indicates a significant CO2 fertilisation effect on the sequestration of atmospheric CO2. The terrestrial carbon sink for the 20th century is simulated to be widespread between latitudes 40 degrees S and 65 degrees N, but is greatest between 10 degrees S and 6 degrees N, excluding the effects of human deforestation. The mean maximum sink capacity over the 20th century is small, at 25 gC m(-2) year(-1), or approximately 1% of gross primary production. Simulations of vegetation dynamics under a scenario of future global warming indicate a gradual decline in the terrestrial carbon sink, with the capacity to absorb human emissions of CO2 being reduced from 20% in 2000 to approximately 2% between 2075 and 2100. The responses of carbon sequestration and vegetation structure and distribution to stabilisation of climate and CO2 may extend for up to 50 years after stabilisation has occurred.     

Modelling the role of agriculture for the 20th century global terrestrial carbon balance

In order to better assess the role of agriculture within the global climate‐vegetation system, we present a model of the managed planetary land surface, Lund–Potsdam–Jena managed Land (LPJmL), which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs). Based on the LPJ‐Dynamic Global Vegetation Model, LPJmL simulates the transient changes in carbon and water cycles due to land use, the specific phenology and seasonal CO₂ fluxes of agricultural‐dominated areas, and the production of crops and grazing land. It uses 13 CFTs (11 arable crops and two managed grass types), with specific parameterizations of phenology connected to leaf area development. Carbon is allocated daily towards four carbon pools, one being the yield‐bearing storage organs. Management (irrigation, treatment of residues, intercropping) can be considered in order to capture their effect on productivity, on soil organic carbon and on carbon extracted from the ecosystem. For transient simulations for the 20th century, a global historical land use data set was developed, providing the annual cover fraction of the 13 CFTs, rain‐fed and/or irrigated, within 0.5° grid cells for the period 1901–2000, using published data on land use, crop distributions and irrigated areas. Several key results are compared with observations. The simulated spatial distribution of sowing dates for temperate cereals is comparable with the reported crop calendars. The simulated seasonal canopy development agrees better with satellite observations when actual cropland distribution is taken into account. Simulated yields for temperate cereals and maize compare well with FAO statistics. Monthly carbon fluxes measured at three agricultural sites also compare well with simulations. Global simulations indicate a ∼24% (respectively ∼10%) reduction in global vegetation (respectively soil) carbon due to agriculture, and 6–9 Pg C of yearly harvested biomass in the 1990s. In contrast to simulations of the potential natural vegetation showing the land biosphere to be an increasing carbon sink during the 20th century, LPJmL simulates a net carbon source until the 1970s (due to land use), and a small sink (mostly due to changing climate and CO₂) after 1970. This is comparable with earlier LPJ simulations using a more simple land use scheme, and within the uncertainty range of estimates in the 1980s and 1990s. The fluxes attributed to land use change compare well with Houghton's estimates on the land use related fluxes until the 1970s, but then they begin to diverge, probably due to the different rates of deforestation considered. The simulated impacts of agriculture on the global water cycle for the 1990s are∼5% (respectively∼20%) reduction in transpiration (respectively interception), and∼44% increase in evaporation. Global runoff, which includes a simple irrigation scheme, is practically not affected.     

Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 2. Carbon balance

This paper examines carbon stocks and their relative balance in terrestrial ecosystems simulated by Biome‐BGC, LPJ, and CASA in an ensemble model experiment conducted using the Terrestrial Observation and Prediction System. We developed the Hierarchical Framework for Diagnosing Ecosystem Models to separate the simulated biogeochemistry into a cascade of functional tiers and examine their characteristics sequentially. The analyses indicate that the simulated biomass is usually two to three times higher in Biome‐BGC than LPJ or CASA. Such a discrepancy is mainly induced by differences in model parameters and algorithms that regulate the rates of biomass turnover. The mean residence time of biomass in Biome‐BGC is estimated to be 40–80 years in temperate/moist climate regions, while it mostly varies between 5 and 30 years in CASA and LPJ. A large range of values is also found in the simulated soil carbon. The mean residence time of soil carbon in Biome‐BGC and LPJ is ～200 years in cold regions, which decreases rapidly with increases of temperature at a rate of ～10 yr °C^?1. Because long‐term soil carbon pool is not simulated in CASA, its corresponding mean residence time is only about 10–20 years and less sensitive to temperature. Another key factor that influences the carbon balance of the simulated ecosystem is disturbance caused by wildfire, for which the algorithms vary among the models. Because fire emissions are balanced by net ecosystem production (NEP) at steady states, magnitudes, and spatial patterns of NEP vary significantly as well. Slight carbon imbalance may be left by the spin‐up algorithm of the models, which adds uncertainty to the estimated carbon sources or sinks. Although these results are only drawn on the tested model versions, the developed methodology has potential for other model exercises.     

Model-data synthesis of diurnal and seasonal CO2 fluxes at Niwot Ridge, Colorado

Eddy covariance records hold great promise for understanding the processes controlling the net ecosystem exchange of CO₂ (NEE). However, NEE is the small difference between two large fluxes: photosynthesis and ecosystem respiration. Consequently, separating NEE into its component fluxes, and determining the process‐level controls over these fluxes, is a difficult problem. In this study, we used a model‐data synthesis approach with the Simplified PnET (SIPNET) flux model to extract process‐level information from 5 years of eddy covariance data at an evergreen forest in the Colorado Rocky Mountains. SIPNET runs at a twice‐daily time step, and has two vegetation carbon pools, a single aggregated soil carbon pool, and a soil moisture submodel that models both evaporation and transpiration. By optimizing the model parameters before evaluating model‐data mismatches, we were able to probe the model structure independent of any arbitrary parameter set. In doing so, we were able to learn about the primary controls over NEE in this ecosystem, and in particular the respiration component of NEE. We also used this parameter optimization, coupled with a formal model selection criterion, to investigate the effects of making hypothesis‐driven changes to the model structure. These experiments lent support to the hypotheses that (1) photosynthesis, and possibly foliar respiration, are down‐regulated when the soil is frozen and (2) the metabolic processes of soil microbes vary in the summer and winter, possibly because of the existence of distinct microbial communities at these two times. Finally, we found that including water vapor fluxes, in addition to carbon fluxes, in the parameter optimization did not yield significantly more information about the partitioning of NEE into gross photosynthesis and ecosystem respiration.     

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis‐driven GPP bias was significantly positive with respect to the observed meteorology‐driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m^?2 yr^?1 across sites (ca. 15% of site level GPP). At the northern mid‐/high‐latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20–30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short‐wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site‐level reanalysis‐driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., 2013 ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate‐driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.     

Simulating Regional Vegetation‐climate Dynamics for Middle America: Tropical Versus Temperate Applications

Regional vegetation‐climate modelling studies have typically focused on boreal or temperate ecosystems in North America and Europe, almost completely overlooking tropical ecosystems. We present the first results of simulated regional vegetation‐climate dynamics in Middle America as simulated by the model, LPJ‐GUESS. The Kappa statistic indicated poor agreement, with a Kappa value of 0.301. When we modified the Kappa statistic by aggregating cell sizes and using generalized biomes, the Kappa value increased to 0.543, indicating a fair agreement. Total LAI simulated from LPJ‐GUESS was strongly correlated to remotely sensed LAI values (r = 0.75). Our simulations indicate that fire frequency was overestimated in tropical moist forests and underestimated in savannas. This underestimation of fire resulted in an over‐simulation of dry tropical forest at the expense of savanna. We highlight additional reasons for the initially poor representation of vegetation in Middle America, including factors such as non‐parameterized plant functional types (desert shrub, cacti, and other succulents), rugged topography, and an insufficient representation of soil.     

Measuring and modelling seasonal variation of carbon dioxide and water vapour exchange of a Pinus ponderosa forest subject to soil water deficit

We conducted ecosystem carbon and water vapour exchange studies in an old‐growth Pinus ponderosa forest in the Pacific North‐west region of the United States. The canopy is heterogeneous, with tall multiaged trees and an open, clumped canopy with low leaf area. Carbon assimilation can occur throughout relatively mild winters, although night frosts can temporarily halt the process and physiological factors limit its efficiency. In contrast, carbon assimilation is often limited in the ‘growing season’ by stomatal closure associated with high evaporative demand (D) and soil water deficits. All of these factors present a challenge to effectively modelling ecosystem processes. Our objective was to generate an understanding of the controls on ecosystem processes across seasonal and annual cycles from a combination of fine‐scale process modelling, ecophysiological measurements, and carbon and water vapour fluxes measured by the eddy covariance method. Flux measurements showed that 50% and 70% of the annual carbon uptake occurred outside the ‘growing season’ (defined as bud break to senescence, ～ days 125–275) in 1996 and 1997. On a daily basis in summer, net ecosystem productivity (NEP) was low when D and soil water deficits were large. Whole ecosystem water vapour fluxes (LE) increased from spring to summer (1.0–1.9 mm d?1) as conducting leaf area increased by 30% and as evaporative demand increased, while evaporation from the soil surface became a smaller portion of total LE as soil water deficits increased. The models underestimated soil evaporation, particularly following rain. In the SPA model, varying the temperature optimum for photosynthesis seasonally resulted in overestimation of carbon uptake in winter and spring, showing that in coniferous forests, assumptions about temperature optima are clearly important. Daily estimates of soil surface CO₂ flux from measurements and site meteorological data demonstrated that modelling of soil CO₂ flux based on an Arrhenius‐type equation in CANPOND overestimated CO₂ respired from the soil during drought and when temperatures were low.     

Measurements of gross and net ecosystem productivity and water vapour exchange of a Pinus ponderosa ecosystem,and an evaluation of two generalized models

Net ecosystem productivity (NEP), net primary productivity (NPP), and water vapour exchange of a mature Pinus ponderosa forest (44°30′ N, 121°37′ W) growing in a region subject to summer drought were investigated along with canopy assimilation and respiratory fluxes. This paper describes seasonal and annual variation in these factors, and the evaluation of two generalized models of carbon and water balance (PnET‐II and 3‐PG) with a combination of traditional measurements of NPP, respiration and water stress, and eddy covariance measurements of above‐and below‐canopy CO₂ and water vapour exchange. The objective was to evaluate the models using two years of traditional and eddy covariance measurements, and to use the models to help interpret the relative importance of processes controlling carbon and water vapour exchange in a water‐limited pine ecosystem throughout the year. PnET‐II is a monthly time‐step model that is driven by nitrogen availability through foliar N concentration, and 3‐PG is a monthly time‐step quantum‐efficiency model constrained by extreme temperatures, drought, and vapour pressure deficits. Both models require few parameters and have the potential to be applied at the watershed to regional scale. There was 2/3 less rainfall in 1997 than in 1996, providing a challenge to modelling the water balance, and consequently the carbon balance, when driving the models with the two years of climate data, sequentially. Soil fertility was not a key factor in modelling processes at this site because other environmental factors limited photosynthesis and restricted projected leaf area index to ～1.6. Seasonally, GEP and LE were overestimated in early summer and underestimated through the rest of the year. The model predictions of annual GEP, NEP and water vapour exchange were within 1–39% of flux measurements, with greater disparity in 1997 because soil water never fully recharged. The results suggest that generalized models can provide insights to constraints on productivity on an annual basis, using a minimum of site data.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

A biogeochemistry‐based dynamic vegetation model and its application along a moisture gradient in the continental United States

Abstract. We develop and evaluate a large‐scale dynamic vegetation model, TEM‐LPJ, which considers interactions among water, light and nitrogen in simulating ecosystem function and structure. We parameterized the model for three plant functional types (PFTs): a temperate deciduous forest, a temperate coniferous forest, and a temperate C₃ grassland. Model parameters were determined using data from forest stands at the Harvard Forest in Massachusetts. Applications of the model reasonably simulated stand development over 120 yr for Populus tremuloides in Wisconsin and for Pinus elliottii in Florida. Our evaluation of tree‐grass interactions simulated by the model indicated that competition for light led to dominance by the deciduous forest PFT in moist regions of eastern United States and that water competition led to dominance by the grass PFT in dry regions of the central United States. Along a moisture transect at 41.5° N in the eastern United States, simulations by TEM‐LPJ reproduced the composition of potential temperate deciduous forest, temperate savanna, and C3 grassland located along the transect.     

遥感GPP模型在中亚干旱区4个典型生态系统的适用性评价

总初级生产力(GPP)是全球生态系统碳循环的重要组成部分,对全球气候变化有重要影响。目前有多种遥感模型可以模拟总初级生产力,比较不同遥感模型在中亚干旱区上的适用性对推进全球干旱区碳收支估算具有重要意义。基于涡度协相关技术观测的四个地面站数据验证MOD17、VODCA2、VPM、TG、SANIRv五种模型的模拟精度。结果表明：(1)基于光能利用率理论的MOD17、VPM模型模拟咸海荒漠植被和阜康荒漠植被GPP的精度最高(R²分别为0.52和0.80),但在模拟草地、农田生态系统生产力时存在较明显的低估(RE>20%);基于植被指数的遥感模型TG模型、SANIRv模型模拟巴尔喀什湖草地生态系统和乌兰乌苏农田生态系统GPP的精度最高(R²分别为0.91和0.81),同时模拟值与实测值的相对误差也较低;基于微波的VODCA2模型模拟各生态系统生产力的效果最差。(2)水分亏缺是限制植被GPP的主要因素,因此是否合理考虑水分胁迫是影响GPP模型在中亚干旱区适用性的重要因素。研究揭示了遥感GPP模型在中亚干旱区的应用潜力,为推进全球植被碳通量的准确估...     

Strategies for measuring and modelling carbon dioxide and water vapour fluxes over terrestrial ecosystems

Continuous and direct measurements of ecosystem carbon dioxide and water vapour fluxes can improve our ability to close regional and global carbon and hydrological budgets. On this behalf, an international and multidisciplinary group of scientists (micrometeorologists, ecophysiologists and biogeochemists) assembled at La Thuile, Italy to convene a workshop on ‘Strategies for Monitoring and Modelling CO₂ and Water Vapour Fluxes over Terrestrial Ecosystems’. Over the course of the week talks and discussions focused on: (i) the results from recent field studies on the annual cycle of carbon dioxide and water vapour fluxes over terrestrial ecosystems; (ii) the problems and pitfalls associated with making long-term flux measurements; (iii) alternative methods for assessing ecosystem carbon dioxide and water vapour fluxes; (iv) how direct and continuous carbon dioxide and water vapour flux measurements could be used by the ecological and biogeochemical modelling communities; and (v) if, how and where to proceed with establishing a network of long-term flux measurement sites. This report discusses the purpose of the meeting and summarizes the conclusions drawn from the discussions by the attending scientists. There was a consensus that recent advances in instrumentation and software make possible long-term measurements of carbon dioxide and water vapour fluxes over terrestrial ecosystems. At this writing, eight research teams have conducted long-term carbon dioxide and water vapour flux experiments and more long-term studies are anticipated. The participants advocated an experimental design that would make long-term flux measurement valuable to a wider community of modelers, biogeochemists and ecologists. A network of carbon dioxide and water vapour flux measurement stations should include ancillary measurements of meteorological, ecological and biological variables. To assess spatial representativeness of the long term and tower-based flux measurements, periodic aircraft-based flux experiments and satellite-based assessments of land cover were recommended. Occasional cuvette-based measurements of leaf-level carbon dioxide and water vapour fluxes were endorsed to provide information on the biological control of surface fluxes. They can also provide data to parameterize ecophysiological models. Flask sampling of stable carbon isotopes was advocated to extend the flux measurements to the global scale.