Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

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.     

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.     

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.     

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.     

PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

Optimal resource management control for CO2 emission and reduction of the greenhouse effect

In recent years, the world has witnessed an ever-growing concern towards global warming caused by greenhouse gases, such as carbon dioxide (CO₂). In order to reduce the emissions of CO₂ without limiting economic growth, substantial investments should target the development of clean technology and the expansion of forested areas. Considering the limited availability of resources, investments must be used in the most effective way. The present work proposes a method to efficiently manage these resources by applying the optimal control theory to a new mathematical model that describes the dynamics of the atmospheric CO₂. The contributions of this work are twofold: (1) present a model that describes the dynamic relation of CO₂ emission with investment in reforestation and clean technology and (2) present a method to efficiently manage the available resources by casting an optimal control problem. The mathematical model uses ordinary differential equations to relate the production of CO₂ with forest area and Gross Domestic Product (GDP). The model parameters are adjusted to fit the actual published data. Given an appropriate performance index, the optimal solution is found by numerically solving the Two-Point Boundary Value Problem (TPBVP) that arises from the application of Pontriagyn's Maximum Principle. The sensitivity of the obtained numerical solution is evaluated with respect to the uncertainties in the model parameters. The main objective of this work is to provide a quantitative tool for the efficient allocation of resources to reduce the greenhouse effect caused CO₂ emissions.     

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.     

Reduction of CO2 emission by optimally tracking a pre-defined target

The recent global financial crisis has highlighted the need for balanced and efficient investments in the reduction of the greenhouse effect caused by emissions of CO₂ on a global scale. In a previous paper, the authors proposed a mathematical model describing the dynamic relation of CO₂ emission with investment in reforestation and clean technology. An efficient allocation of resources to reduce the greenhouse effect has also been proposed. Here, this model is used to provide estimates of the investments needed in land reforestation and in the adoption of clean technologies for an optimum emission and abatement of CO₂, for the period of 1996–2014. The required investments are computed to minimize deviations with respect to the emission targets proposed in the Kyoto Protocol for European Countries. The emission target can be achieved by 2014 with investments in reforestation peaking in 2004, and a reduction of the expected GDP of 42%, relative to 2006. Investments in clean technology should increase between 2008 and 2010 with maximum transfer figures around 70 million American dollars. Total (cumulative) costs are, however, relatively high depending on the price of carbon abatement and the rate at which the expected CO₂ concentration in the atmosphere should be reduced. Results highlight the advantages for policy makers to be able to manage investments in climate policy more efficiently, controlling optimum transfers based on a portfolio of actions that tracks a pre-defined CO₂ concentration target.     

Zooplankton population model coupled to a biogeochemical model of the North Western Mediterranean Sea ecosystem

A stage structured population (SSP) model based on Fennel's [Fennel, W., 2001. Modelling copepods with links to circulation models. Journal of Plankton Research, 23, 1217–1232] equations is applied to Centropages typicus (Kröyer), a dominant copepod species of the North Western Mediterranean Sea (NWMS) and a prey of small pelagic fish. The model considers five groups of stages and development rates are represented by a mechanistic formulation depending on individual specific growth in each stage. Individual growth is calculated from the individual energy budget depending on food availability and temperature.     

大气CO2、CH4、CO高精度观测混合标气配制方法

高精度、高准确度的大气CO2、CH4、CO浓度观测需使用以干洁大气为底气的标气.标气中水汽含量及CO2的δ13C对基于光学原理的观测系统有不可忽视的影响.本研究利用自组装的混合标气配制系统,以环境大气为底气,并通过添加高浓度气体或利用吸附剂吸附,调节目标物种浓度.CO2和CO吸附效率分别达99.7%和99.8%,标气水汽含量小于3.7×10-6(物质的量分数,下同),可配制不同浓度范围的CO2、CH4、CO混合标气.在青海瓦里关全球大气本底站配制环境大气浓度范围的标气,CO2、CH4、CO实际配制浓度同目标浓度的偏差小于10×10-6、30×10-9、30×10-9,CO2中δ13C同实际大气接近.本方法配制的标气已应用于我国本底站大气CO2、CH4、CO高精度观测,符合世界气象组织/全球大气观测(WMO/GAW)质量要求.     

Integrative trophic network assessments of a lentic ecosystem by key ecological approaches of water chemistry, trophic guilds, and ecosystem health assessments along with an ECOPATH model

The objective of this study was to describe the trophic structure and energy flow in a lentic ecosystem in South Korea. Physicochemical water conditions were evaluated along with the reservoir ecosystem health using a multimetric IBI model. Nutrient analyses of the reservoir showed a nutrient rich and hypereutrophic system. Guild analysis revealed that tolerant and omnivorous species dominated the ecosystem. Tolerant fish, as a proportion of the number of individuals, were associated (R² > 0.90, p < 0.01) with TN and TP, the key indicators of trophic state in lentic ecosystems. The mean Reservoir Ecosystem Health Assessment (REHA) score was 19.3 during the study, which was judged as in ‘fair to poor’ condition. A trophic analysis of the reservoir estimated by the ECOPATH model shows that most activity in terms of energy flow occurred in the lower part of the trophic web, where there was intensive use of primary producers as a food source. Consequently, of the 10 consumer groups, nine fell within trophic levels <2.8. Trophic levels (TL) estimated from the weighted average of prey trophic levels varied from 1.0 for phytoplankton, macrophytes, and detritus to 3.25 for the top predator, Pseudobagrus fulvidraco. Our integrated approach to trophic network analysis may provide a key tool for determining the effects of nutrient influx on energy flow pathways in lentic ecosystems.     

Using equation discovery to revise an Earth ecosystem model of the carbon net production

Equation discovery approaches to automated modeling from observed data usually derive equation-based models from scratch rather than from an initial model already established in the domain of use. In this paper, we present an approach that uses new or recent observational data to improve an existing equation-based model. The approach is used to reduce the error of the Earth ecosystem model of the net production of carbon in the atmosphere. We revise the initial ecosystem model in two directions. First, we calibrate the values of the constant parameters in the model on new observational data. Second, we allow the use of alternative equation structures for some of the sub-models of the initial model and use our approach to choose among them. Experiments show that both revision of values of the constant parameters and revision of the structures of sub-models can considerably reduce the error of the initial model.     

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.     

Qualitative modeling and monitoring of selected ecosystem functions

This paper proposes three qualitative models that were applied for modeling of Small Water Cycle violation in ecosystem of Trebon region, South Bohemia. SWC refers to the behavior of the local ecosystem (e.g., the Trebon region), in which the volume of water that comes into the ecosystem is evaporated and falls back into this system. SWC is characterized by early morning dues and frequent small rain precipitation. In the Trebon Biosphere Reserve characterized by wetlands, forests and agriculture land, the evaporated water rises quickly inside the zone and does not have time to recondense before it is transported outside the ecosystem to the distant mountains, where it condenses spontaneously in the rising air streams.The essential pre-model for developing our qualitative models is the database model implemented in the MS SQL environment. The data in this model were collected for last five years and contain information about SWC violation and about the landscape stability development. The database system is used for standard reports, for correlating digital and graphic runs from associated meteorological stations, and for computing the evapotranspiration at the points where the stations are located and also at approximate inter-points.In parallel, and in addition to this standard use of the database model, the data was applied in the development of qualitative models (state model, model for the detection of unexpected situations and matroid model). This transformation and compression of the data was done with help of experienced experts and with the help of special mathematical operations. Qualitative models introduced in this paper overcome experience with quantitative models namely in these items: (1) They provide compression of information contained in large volumes of numerical data. (2) On the contrary of individual quantitative modeling qualitative models enable to describe the function and properties of the whole ecosystem. (3) Conclusions from qualitative models are in many cases better than are the generalizations of results from quantitative models.The first goal of the paper is to model situations associated with violations of the Small Water Cycle (SWC) in this ecosystem, and to contribute to acceptable solutions. The second goal of the paper is to investigate temporary models for the stability of the landscape development and to propose qualitative models for software support for integrated environmental modeling.     

On the risk of extinction of a wild plant species through spillover of a biological control agent: Analysis of an ecosystem compartment model

Invasive plant species can be controlled by introducing natural enemies (insect herbivores) from their native range. However, such introduction entails the risk that the introduced herbivores attack indigenous plant species in the area of introduction. Here, we study the effect of spillover of a herbivore from a managed ecosystem compartment (agriculture) to a natural compartment (non-managed) and vice versa. In the natural compartment, an indigenous plant species is attacked by the introduced herbivores, whereas another indigenous plant species, which competes with the first, is not attacked. The combination of competition and herbivory may result in extinction of the attacked wild plant species. Using a modelling approach, we determine model parameters that characterize the risk of extinction for a wild plant species. Risk factors include: (1) a high attack rate of the herbivores on the wild non-target species, (2) niche overlap expressed as strong competition between the attacked non-target species and its competitor(s), and (3) factors favouring large spillover from the managed ecosystem compartment to the natural compartment; these include (3a) a high dispersal ability, and (3b) a moderate attack rate of the introduced herbivore on the target species, enabling large resident populations of the insect herbivore in the managed compartment. The analysis thus indicates that a high attack rate on the target species, which is a selection criterion for biocontrol agents with respect to their effectiveness, also mitigates risks resulting from spillover and non-target effects. While total eradication of an invasive plant species is not possible in the one-compartment-one-plant-one-herbivore system, natural enemy spillover from a natural to a managed compartment can make the invasive weed go extinct.     

Evaluating CO2 reduction strategies in the US

We constructed a model to simulate emissions of CO₂ from electricity generation in the US and, using the model, we developed 20-year projections of emissions under various regulatory scenarios.     

Effects of boreal forest management practices on the climate impact of CO2 emissions from bioenergy

In Life Cycle Assessment (LCA), carbon dioxide (CO₂) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is CO₂ flux neutral, i.e. the quantity of CO₂ released approximately equals the amount of CO₂ sequestered in biomass. This convention is a plausible assumption for fast growing biomass species, but is inappropriate for slower growing biomass, like forests. In this case, the climate impact from biomass combustion can be potentially underestimated if CO₂ emissions are ignored, or overestimated, if biogenic CO₂ is considered equal to anthropogenic CO₂. The estimation of the effective climate impact should take into account how the CO₂ fluxes are distributed over time: the emission of CO₂ from bioenergy approximately occurs at a single point in time, while the absorption by the new trees is spread over several decades. Our research target is to include this dynamic time dimension in unit-based impact analysis, using a boreal forest stand as case study. The boreal forest growth is modelled with an appropriate function, and is investigated under different forestry regimes (affecting the growth rate and the year of harvest). Specific atmospheric decay functions for biomass-derived CO₂ are then elaborated for selected combinations of forest management options. The contribution to global warming is finally quantified using the GWP_bio index as climate metric. Results estimates the effects of these practices on the characterization factor used for the global warming potential of CO₂ from bioenergy, and point out the key role played by the selected time horizon.     

g-C3N4 nanosheets coupled with CoSe2 as co-catalyst for efficient photooxidation of xylose to xylonic acid

Photocatalysis has emerged as an effective approach to sustainably convert biomass into value-added products. CoSe₂ is a promising nonprecious, efficient cocatalyst for photooxidation, which can facilitate the separation of photogenerated electron–holes, increase the reaction rates,and enhance photocatalytic efficiency. In this work, we synthesized a stable and efficient photocatalysis system of CoSe₂/g-C₃N₄ through attaching CoSe₂ on g-C₃N₄ sheets, with a yield of 50.12% for the selective photooxidation of xylose to xylonic acid. Under light illumination,the photogenerated electrons were prone to migrating from g-C₃N₄ to CoSe₂ due to the higher work function of CoSe₂, resulting in the accelerated separation of photogenerated electron–holes and the promoted photooxidation. Herein, this study reveals the unique function of CoSe₂, which can significantly promote oxygen adsorption, work as an electron sink and accelerate the generation of ·O₂^-, thereby improving the selectivity toward xylonic acid over other by-products. This work provides useful insights into the design of selective photocatalysts by engineering g-C₃N₄ for biomass high-value utilization.