Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4

Several studies have shown that satellite retrievals of solar‐induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux‐tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V_max) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.     

Cross‐biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

We analyzed results from 10‐year long field incubations of foliar and fine root litter from the Long‐term Intersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these models changed over short to long time periods. Six genera of foliar and three genera of root litters were studied with a 10‐fold range in the ratio of acid unhydrolyzable fraction (AUF, or ‘lignin’) to N. Litter was incubated at 27 field sites across numerous terrestrial biomes including arctic and alpine tundra, temperate and tropical forests, grasslands and warm deserts. We used three separate mathematical models of first‐order (exponential) decomposition, emphasizing either the first year or the entire decade. One model included the proportion of relatively stable material as an asymptote. For short‐term (first‐year) decomposition, nonlinear regressions of exponential or power function form were obtained with r² values of 0.82 and 0.64 for foliar and fine‐root litter, respectively, across all biomes included. AUF and AUF : N ratio were the most explanative litter quality variables, while the combined temperature‐moisture terms AET (actual evapotranspiration) and CDI (climatic decomposition index) were best for climatic effects. Regressions contained some systematic bias for grasslands and arctic and boreal sites, but not for humid tropical forests or temperate deciduous and coniferous forests. The ability of the regression approach to fit climate‐driven decomposition models of the 10‐year field results was dramatically reduced from the ability to capture drivers of short‐term decomposition. Future work will require conceptual and methodological improvements to investigate processes controlling decadal‐scale litter decomposition, including the formation of a relatively stable fraction and its subsequent decomposition.     

Simple three‐pool model accurately describes patterns of long‐term litter decomposition in diverse climates

As atmospheric CO₂ increases, ecosystem carbon sequestration will largely depend on how global changes in climate will alter the balance between net primary production and decomposition. The response of primary production to climatic change has been examined using well‐validated mechanistic models, but the same is not true for decomposition, a primary source of atmospheric CO₂. We used the Long‐term Intersite Decomposition Experiment Team (LIDET) dataset and model‐selection techniques to choose and parameterize a model that describes global patterns of litter decomposition. Mass loss was best represented by a three‐pool negative exponential model, with a rapidly decomposing labile pool, an intermediate pool representing cellulose, and a recalcitrant pool. The initial litter lignin/nitrogen ratio defined the size of labile and intermediate pools. Lignin content determined the size of the recalcitrant pool. The decomposition rate of all pools was modified by climate, but the intermediate pool's decomposition rate was also controlled by relative amounts of litter cellulose and lignin (indicative of lignin‐encrusted cellulose). The effect of climate on decomposition was best represented by a composite variable that multiplied a water‐stress function by the Lloyd and Taylor variable Q₁₀ temperature function. Although our model explained nearly 70% of the variation in LIDET data, we observed systematic deviations from model predictions. Below‐ and aboveground material decomposed at notably different rates, depending on the decomposition stage. Decomposition in certain ecosystem‐specific environmental conditions was not well represented by our model; this included roots in very wet and cold soils, and aboveground litter in N‐rich and arid sites. Despite these limitations, our model may still be extremely useful for global modeling efforts, because it accurately (R²=0.6804) described general patterns of long‐term global decomposition for a wide array of litter types, using relatively minimal climatic and litter quality data.     

Long-term dynamics of pine and hardwood litter in contrasting environments: toward a global model of decomposition

We analysed data on mass loss after five years of decomposition in the field from both fine root and leaf litters from two highly contrasting trees, Drypetes glauca, a tropical hardwood tree from Puerto Rico, and pine species from North America as part of the Long‐Term Intersite Decomposition Experiment (LIDET). LIDET is a reciprocal litterbag study involving the transplanting of litter from 27 species across 28 sites in North and Central America reflecting a wide variety of natural and managed ecosystems and climates, from Arctic tundra to tropical rainforest. After 5 years, estimated k‐values ranged from 0.032 to 3.734, lengths of Phase I (to 20% mass remaining) from 0.49 to 47.92 years, and fractional mass remaining from 0 to 0.81. Pine litter decomposed more slowly than Drypetes litter, supporting the notion of strong control of substrate quality over decomposition rates. Climate exerted strong and consistent effects on decomposition. Neither mean annual temperature or precipitation alone explained the global pattern of decomposition; variables including both moisture availability and temperature (i.e. actual evapotranspiration and DEFAC from the CENTURY model) were generally more robust than single variables. Across the LIDET range, decomposition of fine roots exhibited a Q₁₀ of 2 and was more predictable than that of leaves, which had a higher Q₁₀ and greater variability. Roots generally decomposed more slowly than leaves, regardless of genus, but the ratio of above‐ to belowground decomposition rates differed sharply across ecosystem types. Finally, Drypetes litter decomposed much more rapidly than pine litter in ‘broadleaved habitats’ than in ‘conifer habitats’, evidence for a ‘home‐field advantage’ for this litter. These results collectively suggest that relatively simple models can predict decomposition based on litter quality and regional climate, but that ecosystem‐specific problems may add complications.     

Controls on long-term root and leaf litter decomposition in neotropical forests

Litter decomposition represents one of the largest annual fluxes of carbon (C) from terrestrial ecosystems, particularly for tropical forests, which are generally characterized by high net primary productivity and litter turnover. We used data from the Long-Term Intersite Decomposition Experiment (LIDET) to (1) determine the relative importance of climate and litter quality as predictors of decomposition rates, (2) compare patterns in root and leaf litter decomposition, (3) identify controls on net nitrogen (N) release during decay, and (4) compare LIDET rates with native species studies across five bioclimatically diverse neotropical forests. Leaf and root litter decomposed fastest in the lower montane rain and moist forests and slowest in the seasonally dry forest. The single best predictor of leaf litter decomposition was the climate decomposition index (CDI), explaining 51% of the variability across all sites. The strongest models for predicting leaf decomposition combined climate and litter chemistry, and included CDI and lignin ( R ²=0.69), or CDI, N and nonpolar extractives ( R ²=0.69). While we found no significant differences in decomposition rates between leaf and root litter, drivers of decomposition differed for the two tissue types. Initial stages of decomposition, determined as the time to 50% mass remaining, were driven primarily by precipitation for leaf litter ( R ²=0.93) and by temperature for root litter ( R ²=0.86). The rate of N release from leaf litter was positively correlated with initial N concentrations; net N immobilization increased with decreasing initial N concentrations. This study demonstrates that decomposition is sensitive to climate within and across tropical forests. Our results suggest that climate change and increasing N deposition in tropical forests are likely to result in significant changes to decomposition rates in this biome.     

Matrix approach to land carbon cycle modeling: A case study with the Community Land Model

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically‐resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial‐temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO₂ fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin‐up, permit thorough parametric sensitivity tests, enable pool‐based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.     

Climatic effects on litter decomposition from arctic tundra to tropical rainforest

Climatic effects on the decomposition rates of various litter types in different environments must be known to predict how climatic changes would affect key functions of terrestrial ecosystems, such as nutrient and carbon cycling and plant growth. We developed regression models of the climatic effects on the first‐year mass loss of Scots pine needle litter in boreal and temperate forests across Europe (34 sites), and tested the applicability of these models for other litter types in different ecosystems from arctic tundra to tropical rainforest in Canada (average three year mass loss of 11 litter types at 18 sites), the USA and Central America (four litter types at 26 sites). A temperature variable (annual mean temperature, effective temperature sum or its logarithm) combined with a summer drought indicator (precipitation minus potential evapotranspiration between May and September) explained the first‐year mass loss of the Scots pine needle litter across Europe with a higher R² value than actual evapotranspiration (0.68–0.74 vs. 0.51) and with less systematic error for any sub‐region. The model with temperature sum and the summer drought indicator appeared best suited to the other litter types and environments. It predicted the climatic effects on the decomposition rates in North and Central America with least systematic error and highest R² values (0.72–0.80). Compared with Europe, the decomposition rate was significantly less sensitive to annual mean temperature in Canada, and to changes in actual evapotranspiration in the USA and Central America. A simple model distinguishing temperature and drought effects was able to explain the majority of climatic effects on the decomposition rates of the various litter types tested in the varying environments over the large geographical areas. Actual evapotranspiration summarizing the temperature and drought effects was not as general climatic predictor of the decomposition rate.     

Litter decomposition in grasslands of Central North America (US Great Plains)

One of the major concerns about global warming is the potential for an increase in decomposition and soil respiration rates, increasing CO₂ emissions and creating a positive feedback between global warming and soil respiration. This is particularly important in ecosystems with large belowground biomass, such as grasslands where over 90% of the carbon is allocated belowground. A better understanding of the relative influence of climate and litter quality on litter decomposition is needed to predict these changes accurately in grasslands. The Long‐Term Intersite Decomposition Experiment Team (LIDET) dataset was used to evaluate the influence of climatic variables (temperature, precipitation, actual evapotranspiration, and climate decomposition index), and litter quality (lignin content, carbon : nitrogen, and lignin : nitrogen ratios) on leaf and root decomposition in the US Great Plains. Wooden dowels were used to provide a homogeneous litter quality to evaluate the relative importance of above and belowground environments on decomposition. Contrary to expectations, temperature did not explain variation in root and leaf decomposition, whereas precipitation partially explained variation in root decomposition. Percent lignin was the best predictor of leaf and root decomposition. It also explained most variation in root decomposition in models which combined litter quality and climatic variables. Despite the lack of relationship between temperature and root decomposition, temperature could indirectly affect root decomposition through decreased litter quality and increased water deficits. These results suggest that carbon flux from root decomposition in grasslands would increase, as result of increasing temperature, only if precipitation is not limiting. However, where precipitation is limiting, increased temperature would decrease root decomposition, thus likely increasing carbon storage in grasslands. Under homogeneous litter quality, belowground decomposition was faster than aboveground and was best predicted by mean annual precipitation, which also suggests that the high moisture in soil accelerates decomposition belowground.     

Microbial dynamics and soil physicochemical properties explain large‐scale variations in soil organic carbon

First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation.     

Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon‐LAnd Model Intercomparison Project (C‐LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie‐Ames‐Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO₂ measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO₂ and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr^?1 for CASA′ vs. 1.2 Pg C yr^?1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C‐LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community‐wide platform for model‐data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C‐LAMP are publicly available on the Earth System Grid.     

Global patterns of nitrogen limitation: confronting two global biogeochemical models with observations

Projections of future changes in land carbon (C) storage using biogeochemical models depend on accurately modeling the interactions between the C and nitrogen (N) cycles. Here, we present a framework for analyzing N limitation in global biogeochemical models to explore how C‐N interactions of current models compare to field observations, identify the processes causing model divergence, and identify future observation and experiment needs. We used a set of N‐fertilization simulations from two global biogeochemical models (CLM‐CN and O‐CN) that use different approaches to modeling C‐N interactions. On the global scale, net primary productivity (NPP) in the CLM‐CN model was substantially more responsive to N fertilization than in the O‐CN model. The most striking difference between the two models occurred for humid tropical forests, where the CLM‐CN simulated a 62% increase in NPP at high N addition levels (30 g N m^?2 yr^?1), while the O‐CN predicted a 2% decrease in NPP due to N fertilization increasing plant respiration more than photosynthesis. Across 35 temperate and boreal forest sites with field N‐fertilization experiments, we show that the CLM‐CN simulated a 46% increase in aboveground NPP in response to N, which exceeded the observed increase of 25%. In contrast, the O‐CN only simulated a 6% increase in aboveground NPP at the N‐fertilization sites. Despite the small response of NPP to N fertilization, the O‐CN model accurately simulated ecosystem retention of N and the fate of added N to vegetation when compared to empirical ¹⁵N tracer application studies. In contrast, the CLM‐CN predicted lower total ecosystem N retention and partitioned more losses to volatilization than estimated from observed N budgets of small catchments. These results point to the need for model improvements in both models in order to enhance the accuracy with which global C‐N cycle feedbacks are simulated.     

Seasonal carbon dynamics and water fluxes in an Amazon rainforest

Satellite‐based observations indicate that seasonal patterns in canopy greenness and productivity in the Amazon are negatively correlated with precipitation, with increased greenness occurring during the dry months. Flux tower measurements indicate that the canopy greening that occurs during the dry season is associated with increases in net ecosystem productivity (NEP) and evapotranspiration (ET). Land surface and terrestrial biosphere model simulations for the region have predicted the opposite of these observed patterns, with significant declines in greenness, NEP, and ET during the dry season. In this study, we address this issue mainly by developing an empirically constrained, light‐controlled phenology submodel within the Ecosystem Demography model version 2 (ED2). The constrained ED2 model with a suite of field observations shows markedly improved predictions of seasonal ecosystem dynamics, more accurately capturing the observed patterns of seasonality in water, carbon, and litter fluxes seen at the Tapajos National Forest, Brazil (2.86°S, 54.96°W). Long‐term simulations indicate that this light‐controlled phenology increases the resilience of Amazon forest NEP to interannual variability in climate forcing.     

Microbial community dynamics alleviate stoichiometric constraints during litter decay

Under the current paradigm, organic matter decomposition and nutrient cycling rates are a function of the imbalance between substrate and microbial biomass stoichiometry. Challenging this view, we demonstrate that in an individual‐based model, microbial community dynamics alter relative C and N limitation during litter decomposition, leading to a system behaviour not predictable from stoichiometric theory alone. Rather, the dynamics of interacting functional groups lead to an adaptation at the community level, which accelerates nitrogen recycling in litter with high initial C : N ratios and thus alleviates microbial N limitation. This mechanism allows microbial decomposers to overcome large imbalances between resource and biomass stoichiometry without the need to decrease carbon use efficiency (CUE), which is in contrast to predictions of traditional stoichiometric mass balance equations. We conclude that identifying and implementing microbial community‐driven mechanisms in biogeochemical models are necessary for accurately predicting terrestrial C fluxes in response to changing environmental conditions.     

Biotic degradation at night,abiotic degradation at day: positive feedbacks on litter decomposition in drylands

The arid and semi‐arid drylands of the world are increasingly recognized for their role in the terrestrial net carbon dioxide (CO₂) uptake, which depends largely on plant litter decomposition and the subsequent release of CO₂ back to the atmosphere. Observed decomposition rates in drylands are higher than predictions by biogeochemical models, which are traditionally based on microbial (biotic) degradation enabled by precipitation as the main mechanism of litter decomposition. Consequently, recent research in drylands has focused on abiotic mechanisms, mainly photochemical and thermal degradation, but they only partly explain litter decomposition under dry conditions, suggesting the operation of an additional mechanism. Here we show that in the absence of precipitation, absorption of dew and water vapor by litter in the field enables microbial degradation at night. By experimentally manipulating solar irradiance and nighttime air humidity, we estimated that most of the litter CO₂ efflux and decay occurring in the dry season was due to nighttime microbial degradation, with considerable additional contributions from photochemical and thermal degradation during the daytime. In a complementary study, at three sites across the Mediterranean Basin, litter CO₂ efflux was largely explained by litter moisture driving microbial degradation and ultraviolet radiation driving photodegradation. We further observed mutual enhancement of microbial activity and photodegradation at a daily scale. Identifying the interplay of decay mechanisms enhances our understanding of carbon turnover in drylands, which should improve the predictions of the long‐term trend of global carbon sequestration.     

Litter decay controlled by temperature,not soil properties,affecting future soil carbon

Widespread global changes, including rising atmospheric CO₂ concentrations, climate warming and loss of biodiversity, are predicted for this century; all of these will affect terrestrial ecosystem processes like plant litter decomposition. Conversely, increased plant litter decomposition can have potential carbon‐cycle feedbacks on atmospheric CO₂ levels, climate warming and biodiversity. But predicting litter decomposition is difficult because of many interacting factors related to the chemical, physical and biological properties of soil, as well as to climate and agricultural management practices. We applied ¹³C‐labelled plant litter to soil at ten sites spanning a 3500‐km transect across the agricultural regions of Canada and measured its decomposition over five years. Despite large differences in soil type and climatic conditions, we found that the kinetics of litter decomposition were similar once the effect of temperature had been removed, indicating no measurable effect of soil properties. A two‐pool exponential decay model expressing undecomposed carbon simply as a function of thermal time accurately described kinetics of decomposition. (R² = 0.94; RMSE = 0.0508). Soil properties such as texture, cation exchange capacity, pH and moisture, although very different among sites, had minimal discernible influence on decomposition kinetics. Using this kinetic model under different climate change scenarios, we projected that the time required to decompose 50% of the litter (i.e. the labile fractions) would be reduced by 1–4 months, whereas time required to decompose 90% of the litter (including recalcitrant fractions) would be reduced by 1 year in cooler sites to as much as 2 years in warmer sites. These findings confirm quantitatively the sensitivity of litter decomposition to temperature increases and demonstrate how climate change may constrain future soil carbon storage, an effect apparently not influenced by soil properties.     

Near‐future forest vulnerability to drought and fire varies across the western United States

Recent prolonged droughts and catastrophic wildfires in the western United States have raised concerns about the potential for forest mortality to impact forest structure, forest ecosystem services, and the economic vitality of communities in the coming decades. We used the Community Land Model (CLM) to determine forest vulnerability to mortality from drought and fire by the year 2049. We modified CLM to represent 13 major forest types in the western United States and ran simulations at a 4‐km grid resolution, driven with climate projections from two general circulation models under one emissions scenario (RCP 8.5). We developed metrics of vulnerability to short‐term extreme and prolonged drought based on annual allocation to stem growth and net primary productivity. We calculated fire vulnerability based on changes in simulated future area burned relative to historical area burned. Simulated historical drought vulnerability was medium to high in areas with observations of recent drought‐related mortality. Comparisons of observed and simulated historical area burned indicate simulated future fire vulnerability could be underestimated by 3% in the Sierra Nevada and overestimated by 3% in the Rocky Mountains. Projections show that water‐limited forests in the Rocky Mountains, Southwest, and Great Basin regions will be the most vulnerable to future drought‐related mortality, and vulnerability to future fire will be highest in the Sierra Nevada and portions of the Rocky Mountains. High carbon‐density forests in the Pacific coast and western Cascades regions are projected to be the least vulnerable to either drought or fire. Importantly, differences in climate projections lead to only 1% of the domain with conflicting low and high vulnerability to fire and no area with conflicting drought vulnerability. Our drought vulnerability metrics could be incorporated as probabilistic mortality rates in earth system models, enabling more robust estimates of the feedbacks between the land and atmosphere over the 21st century.     

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.     

Design and test of a generic cohort model of soil organic matter decomposition: the SOMKO model

• 1 SOMKO is a new simulation model of soil organic matter (SOM) dynamics aimed at predicting long‐term and short‐term SOM dynamics based on a mechanistic approach focusing on microbes as the key agents of decomposition.
• 2 SOM is partitioned into cohorts and chemical quality pools (classified by age and chemical composition), the microbial community processes are explicitly represented, and the C : N stoichiometric constraints are accounted for through a new mechanism of offer and demand.
• 3 The analysis of model equations shows that: (1) SOM C : N cannot decrease below microbial C : N; and (2) the nitrogen limitation of decomposition depends on SOM C : N, microbial biomass and soil mineral nitrogen. First tests of the model show good qualitative behaviour for simulating the dynamics of short‐term litter‐bag type decomposition, long‐term SOM increase, pulsed mineral nitrogen production, the priming effect due to easily decomposable carbon addition, and the effects of vegetation clearance and climate change on SOM. Simulations are in good agreement with long‐term experimental data.
• 4 SOMKO is an integrated component of the coupled soil–vegetation models within the ETEMA (European Terrestrial Ecosystem Modelling Activity) framework. Future extensions of this work include: (1) estimating microbial parameters from specific experiments; (2) spatial distribution of SOMKO in multistrata models; and (3) implementing nitrification/denitrification processes, phosphorus limitation and microfaunal activity.

     

Disentangling direct and indirect effects of water table drawdown on above‐ and belowground plant litter decomposition: consequences for accumulation of organic matter in boreal peatlands

Pristine peatlands are carbon (C)‐accumulating wetland ecosystems sustained by a high water table (WT) and consequent anoxia that slows down decomposition. Persistent WT drawdown as a response to climate and/or land‐use change affects decomposition either directly through environmental factors such as increased oxygenation, or indirectly through changes in plant community composition. This study attempts to disentangle the direct and indirect effects of WT drawdown by measuring the relative importance of environmental parameters (WT depth, temperature, soil chemistry) and litter type and/or litter chemical quality on the 2‐year decomposition rates of above‐ and belowground litter (altogether 39 litter types). Consequences for organic matter accumulation were estimated based on the annual litter production. The study sites were chosen to form a three‐stage chronosequence from pristine (undrained) to short‐term (years) and long‐term (decades) WT drawdown conditions at three nutrient regimes. The direct effects of WT drawdown were overruled by the indirect effects through changes in litter type composition and production. Short‐term responses to WT drawdown were small. In long‐term, dramatically increased litter inputs resulted in large accumulation of organic matter in spite of increased decomposition rates. Furthermore, the quality of the accumulated matter greatly changed from that accumulated in pristine conditions. Our results show that the shift in vegetation composition as a response to climate and/or land‐use change is the main factor affecting peatland ecosystem C cycle, and thus dynamic vegetation is a necessity in any model applied for estimating responses of C fluxes to changing environment. We provide possible grouping of litter types into plant functional types that the models could utilize. Furthermore, our results clearly show a drop in soil summer temperature as a response to WT drawdown when an initially open peatland converts into a forest ecosystem, which has not yet been considered in the existing models.     

Simulating greenhouse gas mitigation potentials for Chinese Croplands using the DAYCENT ecosystem model

Understanding the potential for greenhouse gas (GHG) mitigation in agricultural lands is a critical challenge for climate change policy. This study uses the DAYCENT ecosystem model to predict GHG mitigation potentials associated with soil management in Chinese cropland systems. Application of ecosystem models, such as DAYCENT, requires the evaluation of model performance with data sets from experiments relevant to the climate and management of the study region. DAYCENT was evaluated with data from 350 cropland experiments in China, including measurements of nitrous oxide emissions (N₂O), methane emissions (CH₄), and soil organic carbon (SOC) stock changes. In general, the model was reasonably accurate with R² values for model predictions vs. measurements ranging from 0.71 to 0.85. Modeling efficiency varied from 0.65 for SOC stock changes to 0.83 for crop yields. Mitigation potentials were estimated on a yield basis (Mg CO₂‐equivalent Mg^?1Yield). The results demonstrate that the largest decrease in GHG emissions in rainfed systems are associated with combined effect of reducing mineral N fertilization, organic matter amendments and reduced‐till coupled with straw return, estimated at 0.31 to 0.83 Mg CO₂‐equivalent Mg^?1Yield. A mitigation potential of 0.08 to 0.36 Mg CO₂‐equivalent Mg^?1Yield is possible by reducing N chemical fertilizer rates, along with intermittent flooding in paddy rice cropping systems.