Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses

Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C₄ perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C₄ photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C₄ grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC.     

Water and carbon fluxes above European coniferous forests modelled with artificial neural networks

Artificial neural networks are used to select a minimal set of input variables to model water vapour and carbon exchange of coniferous forest ecosystems, independently of tree species and without detailed physiological information. Neural networks are used because of their power to fit highly non-linear relations between input and output-variables. Radiation, temperature, vapour pressure deficit and time of the day showed to be the dynamic input variables that determine ecosystem water fluxes. The same variables, together with projected leaf area index are needed for modelling CO₂-fluxes. The results for the individual sites show that the neural networks found mean water and carbon flux responses to the driving variables valid for all sites. The sensitivity analysis of the derived neural networks shows that the LAI-effect of the CO₂-flux model is overfitted because of the low variability of LAI. However, the predictions of CO₂-fluxes of sites not included in the calibration set indicate that the LAI-response of the network is reliable and that results can be used as a first estimate of the net ecosystem carbon exchange of the forest sites. Independent predictions of forest ecosystem vapour fluxes were equally satisfying as empirical models specifically calibrated for the individual sites. The results indicate that both short term water and carbon fluxes of European coniferous forests can be modelled without using detailed physiological and site specific information.     

3 forest simulation model

The 3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. 3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

Modelling cyanobacteria in shallow coastal seas

There is an increasing need to describe cyanobacteria bloom dynamics using ecosystem models. We consider two fundamentally different ways how cyanobacteria are currently implemented: a simple approach without explicit consideration of the life cycle which assumes that cyanobacteria grow due to nitrogen fixation alone and an advanced approach that computes the succession of four different stages of the cyanobacteria life cycle based on internal quotas of energy and nitrogen. To qualitatively and quantitatively intercompare these different approaches and with observations, we use the Baltic Sea ecosystem model ERGOM coupled to the one-dimensional water column model GOTM. Four experiments are carried out: three, using the simple approach with either (a) a prescribed constant minimum production, (b) no minimum value or (c) a prescribed constant minimum concentration, and one with (d) the full predictive life cycle. The model data of 35 years (1970-2005) are analyzed for the timing of the bloom, the interannual variability, the annual mean nitrogen fixation rates and the effect of cyanobacteria on eukaryotic phytoplankton. The results show significant differences. In the climatological seasonal mean, only the advanced approach which resolves the life cycle produces a realistic bloom onset and duration. The interannual variability of blooms is unrealistically small in the experiments with a prescribed minimum value. Annual mean nitrogen fixation rates diverge by up to 30% between the four model solutions. Finally, the representation of the cyanobacteria also influences the seasonal cycle of eukaryotic phytoplankton, i.e., flagellates. This study demonstrates that the way how cyanobacteria are implemented in coupled biological-physical models strongly determines the fluxes into the system and between the individual compartments.     

A new scheme for initializing process-based ecosystem models by scaling soil carbon pools

Process-based ecosystem models are useful tools, not only for understanding the forest carbon cycle, but also for predicting future change. In order to apply a model to simulate a specific time period, model initialization is required. In this study, we propose a new scheme of initialization for forest ecosystem models, which we term a “slow-relaxation scheme”, that entails scaling of the soil carbon and nitrogen pools slowly during the spin-up period. The proposed slow-relation scheme was tested with the CENTURY version 4 ecosystem model. Three different combinations of scaled soil pools were also tested, and compared to the results from a fast-relaxation regime. The fast-relaxation of soil pools produced unstable, transient model behaviour whereas slow-relaxation overcame this instability. This approach holds promise for initializing ecosystem models, and for starting simulations with more realistic initial conditions.     

Coupling a land use model and an ecosystem model for a crop-pasture zone

This paper describes the development of a land use model coupling ecosystem processes. For a given land use pattern in a region, a built-in regional ecosystem model (TESim) simulates leaf physiology of plants, carbon and nitrogen dynamics, and hydrological processes including runoff generation and run-on re-absorption, as well as runoff-induced soil erosion and carbon and nitrogen loss from ecosystems. The simulation results for a certain period from 1976 to 1999 were then used to support land use decisions and to assess the impacts of land use changes on environment. In the coupling model, the land use type for a land unit was determined by optimization of a weighted suitability derived from expert knowledge about the ecosystem state and site conditions. The model was applied to the temperate crop-pasture band in northern China (CCPB) to analyze the interactions between land use and major ecosystem processes and functions and to indicate the added value of the feedbacks by comparing simulations with and without the coupling and feedbacks between land use module and ecosystem processes. The results indicated that the current land use in CCPB is neither economical nor ecologically judicious. The scenario with feedbacks increased NPP by 46.78 g C m⁻² a⁻¹, or 32.23% of the scenario without feedbacks, also decreased soil erosion by 0.65 kg m⁻² a⁻¹, or 23.13%. Without altering the regional land use structure (proportions of each land use type). The system developed in this study potentially benefits both land managers and researchers.     

A simulation model to evaluate the impacts of invasive earthworms on soil carbon dynamics

Recent studies have reported that earthworm invasions alter native communities and impact nutrient cycling in terrestrial ecosystems. We developed a simulation model to evaluate the potential impacts of earthworm invasions on carbon dynamics, taking into consideration earthworm feeding strategies and priming effects on the microorganisms through their casting activities. Responses of carbon stocks (forest litter, soil organic matter, microbial biomass and earthworm populations) and carbon fluxes (litter decomposition, earthworm consumption, and microbial respiration) were used to evaluate an earthworm invasion of a forest ecosystem. Data from a northern temperate forest (Arnot Forest, New York) were adapted for model calibration and evaluation. Simulation results suggest that the impact and outcome of earthworm invasions are affected by pre-invasion resource availability (litter and soil organic matter), invasive earthworm assemblages (particularly feeding strategy), and invasion history (associated with earthworm population dynamics). The abovementioned factors may also determine invasion progress of earthworm species. The accuracy of the model could be improved by the addition of environmental modules (e.g., soil water regimes), precise parameters accounting for individual species attributes under different environmental conditions (e.g. utilization ability of different types of food resources), as well as earthworm population dynamics (size and structure) and interactions with predators and other invasive/indigenous species during the invasion progress. Such an earthworm invasion model could provide valuable evaluation of the complicated responses of carbon dynamics to earthworm invasions in a range of forest ecosystems, particularly under global change scenarios.     

Modelling carbon and nitrogen dynamics in forest ecosystems of Central Russia under different climate change scenarios and forest management regimes

The individual-based stand-level model EFIMOD was used for large-scale simulations using standard data on forest inventories as model inputs. The model was verified for the case-study of field observations, and possible sources of uncertainties were analysed. The approach developed kept the ability for fine-tuning to account for spatial discontinuity in the simulated area. Several forest management regimes were simulated as well as forest wildfires and climate changes. The greatest carbon and nitrogen accumulations were observed for the regime without cuttings. It was shown that cuttings and wildfires strongly influence the processes of carbon and nitrogen accumulations in both soil and forest vegetation. Modelling also showed that the increase in annual average temperatures resulted in the partial relocation of carbon and nitrogen stocks from soil to plant biomass. However, forest management, particularly harvesting, has a greater effect on the dynamics of forest ecosystems than the prescribed climate change.     

燕山典型流域两种造林树种生态系统碳储量及固碳潜力研究

选择燕山典型流域6个林龄序列的小叶杨（Populus simonii）和5个林龄序列的山杏（Prunus sibirica）主要造林树种为研究对象,利用时间替代空间样地测量法量化退牧还林后生物量碳储量、凋落物碳储量和土壤碳储量及生态系统碳储量的变化规律,同时以各组成碳库-林龄序列中的最大碳储量之和作为生态系统饱和碳储量,以未退牧的天然草地生态系统碳储量作为初始植被类型的碳储量,分析总结了退牧还林对生态系统碳储量和碳循环的影响。结果表明,退牧还林后生态系统的生物量碳储量、凋落物碳储量基本随退牧年限的增加而增加,土壤碳储量随退牧年限的增加呈现先减小后增加的趋势。在没有人为干扰的情况下,9、15、18、22及29 a生小叶杨林的生态系统碳储量分别为7147.45、7461.67、7509.895、8468.375及8247.85 g·m^-2,9、15、18、22及26 a生山杏林的生态系统碳储量分别为6695.44、6700.82、8011.86、8001.92及7981.92 g·m^-2;9、15、18、22、29及36 a生小叶杨林的生态系统固碳潜力分别为757.08、1071.3、1119.53、2078.01、1857.48及1312.21 g·m^-2,9、15、18、22及26 a生山杏林的生态系统固碳潜力分别为310.45、1621.49、1611.55、1591.55及757.08 g·m^-2。长期来看,研究区退牧还林对提高生态系统碳汇能力是可观的、积极的。研究结果对提高造林对碳汇影响的估测能力提供数据支持,也为政府参与国际全球气候变化的谈判提供一个很好的案例研究和科学根据。     

SOMPROF: A vertically explicit soil organic matter model

Most current soil organic matter (SOM) models represent the soil as a bulk without specification of the vertical distribution of SOM in the soil profile. However, the vertical SOM profile may be of great importance for soil carbon cycling, both on short (hours to years) time scale, due to interactions with the soil temperature and moisture profile, as well as on long (years to centuries) time scale because of depth-specific stabilization mechanisms of organic matter. It is likely that a representation of the SOM profile and surface organic layers in SOM models can improve predictions of the response of land surface fluxes to climate and environmental variability. Although models capable of simulating the vertical SOM profile exist, these were generally not developed for large scale predictive simulations and do not adequately represent surface organic horizons. We present SOMPROF, a vertically explicit SOM model, designed for implementation into large scale ecosystem and land surface models. The model dynamically simulates the vertical SOM profile and organic layer stocks based on mechanistic representations of bioturbation, liquid phase transport of organic matter, and vertical distribution of root litter input. We tested the model based on data from an old growth deciduous forest (Hainich) in Germany, and performed a sensitivity analysis of the transport parameters, and the effects of the vertical SOM distribution on temporal variation of heterotrophic respiration. Model results compare well with measured organic carbon profiles and stocks. SOMPROF is able to simulate a wide range of SOM profiles, using parameter values that are realistic compared to those found in previous studies. Results of the sensitivity analysis show that the vertical SOM distribution strongly affects temporal variation of heterotrophic respiration due to interactions with the soil temperature and moisture profile.     

treedyn3 forest simulation model

The treedyn3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the treedyn model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. treedyn3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

Habitat type determines herbivory controls over CO2 fluxes in a warmer Arctic

High-latitude ecosystems store large amounts of carbon (C); however, the C storage of these ecosystems is under threat from both climate warming and increased levels of herbivory. In this study we examined the combined role of herbivores and climate warming as drivers of CO2 fluxes in two typical high-latitude habitats (mesic heath and wet meadow). We hypothesized that both herbivory and climate warming would reduce the C sink strength of Arctic tundra through their combined effects on plant biomass and gross ecosystem photosynthesis and on decomposition rates and the abiotic environment. To test this hypothesis we employed experimental warming (via International Tundra Experiment [ITEX] chambers) and grazing (via captive Barnacle Geese) in a three-year factorial field experiment. Ecosystem CO2 fluxes (net ecosystem exchange of CO2, ecosystem respiration, and gross ecosystem photosynthesis) were measured in all treatments at varying intensity over the three growing seasons to capture the impact of the treatments on a range of temporal scales (diurnal, seasonal, and interannual). Grazing and warming treatments had markedly different effects on CO2 fluxes in the two tundra habitats. Grazing caused a strong reduction in CO2 assimilation in the wet meadow, while warming reduced CO2 efflux from the mesic heath. Treatment effects on net ecosystem exchange largely derived from the modification of gross ecosystem photosynthesis rather than ecosystem respiration. In this study we have demonstrated that on the habitat scale, grazing by geese is a strong driver of net ecosystem exchange of CO2, with the potential to reduce the CO2 sink strength of Arctic ecosystems. Our results highlight that the large reduction in plant biomass due to goose grazing in the Arctic noted in several studies can alter the C balance of wet tundra ecosystems. We conclude that herbivory will modulate direct climate warming responses of Arctic tundra with implications for the ecosystem C balance; however, the magnitude and direction of the response will be habitat-specific.     

我国中亚热带人工林水热通量对干旱差异响应的模拟研究

季节性干旱现象在我国中亚热带地区时有发生,为了研究该区域大气-生态系统之间的相互作用关系及其碳水收支状况,2002年起在江西省千烟洲（26.7°N,115.1°E）人工林生态系统建立了通量观测塔。2003年7月该人工林生态系统遭遇了历史上少有的高温少雨天气,本研究应用基于生理生态学过程的EALCO（Ecological Assimilation of Land and Climate Observation）模型及2003和2004年通量观测数据对该生态系统的水热通量进行了模拟,同时分析了干旱胁迫对它们产生的影响。结果显示,模型能够很好的模拟该生态系统的能量通量的日变化,净辐射、显热和潜热通量模拟值与实测值相关系数的平方（R2）及标准差分别为0.99和8.05 W.m-2;0.81和41.02 W.m-2;0.90和31.49 W.m-2,模型可以解释87%的日蒸散量的变化。从模拟结果看,2003年7月下旬（发生较严重干旱胁迫）较2004年同期（干旱程度轻）相比,冠层及土壤水势下降约2倍,植物蒸腾的日变化形式改变,根系吸水滞后冠层蒸腾的时间缩短约半小时,冠层导度下降40%～60%。模拟与观测结果均表明,2003年7月下旬每天正午的波文比大都介于1～2.2,而2004年同期正午的波文比则介于0.2～0.6。EALCO模型通过Ball模型将植物碳水过程耦合在一起,从而可以很好的模拟植物的气孔行为,进而准确的模拟植物水热过程对干旱的响应。土壤水分匮乏对冠层导度的限制是2003年干旱期间冠层潜热通量模拟值下降的根本原因。     

Modelling of matter cycle in a mesotrophic bog ecosystem II. Dynamic model and ecological succession

Based upon the the results of static environ analysis of the organic matter cycle through the ecosystem, a number of dynamic models are developed, in this second part, for the matter and nitrogen cycles. Probable outcomes of ecological succession are obtained within the framework of the dynamic model without using the ergodic hypothesis that is implicitly adopted in ecological studies. The dynamics of both stocks in the ecosytem components and flows among them can be observed within the model in order to compare some turnover characteristics of the succession series with those of the ecological one.     

A preliminary model of nutrient cycling in sediments of a Mediterranean lagoon

A model of nitrogen and phosphorus cycles in the sediment of a lagoon has been developed. This model was applied to the Thau lagoon (southern France). Sediment was sliced in three layers to reproduce the oxygen profile, which is simulated within the model. Following an equilibrium hypothesis, the model was calibrated against field data. State variables and fluxes were estimated in the sediment and across the sediment-water interface. A Monte Carlo sensitivity analysis was performed to determine the most sensitive parameters and sediment state variables. A dynamic simulation with varying oxygen concentrations then showed the influence of anoxia on the phosphorus and nitrogen fluxes between water and sediment.     

Biogeochemical model (BGC-ES) and its basin-level application for evaluating ecosystem services under forest management practices

It is important for humans to live in harmony with ecosystems. Evaluation of ecosystem services (ES) may be helpful in achieving this objective. In Japan, forest ecosystems need to be re-evaluated to prevent their degradation due to lack of forest management.In order to evaluate the effects of forest management on forest ES, we developed a process-based biogeochemical model to estimate water, carbon, and nitrogen cycles in forest ecosystems (BGC-ES). This model consists of four submodels: biomass, water cycle, carbon-nitrogen (CN) cycles, and forest management. The biomass submodel can calculate growth of forest biomass under forest managements.Several parameters of the model were calibrated using data from observations of evapotranspiration flux and quality of stream flow in forests. The model results were compared with observations of runoff water from a dam catchment site and with carbon flux observations.Our model was coupled with a basin-level GIS database of forests. Evaluations under various forest management scenarios were carried out for forests in a basin contained in the Ise Bay basin (Chubu region, Japan), where plantations (artificial forests) seemed to have degraded from poor forest management.Comparing our simulation results with those of forests without management in the basin, we found that the amounts of absorbed carbon and runoff were larger in managed forests. In addition, the volume of harvested timber was larger and its quality (diameter) was better in managed forests. Changes of ES within the various scenarios were estimated for their economic value and were compared with the cost of forest management.     

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan,Canada

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.     

Coupling biochemical and biophysical processes at the leaf level: an equilibrium photosynthesis model for leaves of C3 plants

The paper presents a generic computer model for estimating short-term steady-state fluxes of CO₂, water vapor, and heat from broad leaves and needle-leaved coniferous shoots of C₃ plant species. The model explicitly couples all major processes and feedbacks known to impact leaf biochemistry and biophysics including biochemical reactions, stomatal function, and leaf-boundary layer heat- and mass-transport mechanisms. The ability of the model to successfully predict measured photosynthesis and stomatal-conductance data as well as to simulate a variety of observed leaf responses is demonstrated. A model application investigating physiological and environmental regulation of leaf water-use efficiency (WUE) under steady-state conditions is discussed. Simulation results suggest that leaf physiology has a significant control over the environmental sensitivity of leaf WUE. The implementation of a highly efficient solution technique allows the model to be directly incorporated into plant-canopy and terrestrial ecosystem models.     

Modeling the effect of photosynthetic vegetation properties on the NDVI--LAI relationship

Developing a relationship between the normalized difference vegetation index (NDVI) and the leaf area index (LAI) is essential to describe the pattern of spatial or temporal variation in LAI that controls carbon, water, and energy exchange in many ecosystem process models. Photosynthetic vegetation (PV) properties can affect the estimation of LAI, but no models integrate the effects of multiple species. We developed four alternative NDVI-LAI models, three of which integrate PV effects: no PV effects, leaf-level effects, canopy-level effects, and effects at both levels. The models were fit to data across the natural range of variation in NDVI for a widespread High Arctic ecosystem. The weight of evidence supported the canopy-level model (Akaike weight, wr = 0.98), which includes species-specific canopy coefficients that primarily scale fractional PV cover to LAI by accounting for the area of unexposed PV. Modeling the canopy-level effects improved prediction of LAI (R2 = 0.82) over the model with no PV effect (R2 = 0.71) across the natural range of variation in NDVI but did not affect the site-level estimate of LAI. Satellite-based methods to estimate species composition, a variable in the model, will need to be developed. We expect that including the effects of PV properties in NDVI-LAI models will improve prediction of LAI where species composition varies across space or changes over time.