Moisture-driven divergence in mineral-associated soil carbon persistence.

Mineral stabilization of soil organic matter is an important regulator of the global carbon (C) cycle. However, the vulnerability of mineral-stabilized organic matter (OM) to climate change is currently unknown. We examined soil profiles from 34 sites across the conterminous USA to investigate how the abundance and persistence of mineral-associated organic C varied with climate at the continental scale. Using a novel combination of radiocarbon and molecular composition measurements, we show that the relationship between the abundance and persistence of mineral-associated organic matter (MAOM) appears to be driven by moisture availability. In wetter climates where precipitation exceeds evapotranspiration, excess moisture leads to deeper and more prolonged periods of wetness, creating conditions which favor greater root abundance and also allow for greater diffusion and interaction of inputs with MAOM. In these humid soils, mineral-associated soil organic C concentration and persistence are strongly linked, whereas this relationship is absent in drier climates. In arid soils, root abundance is lower, and interaction of inputs with mineral surfaces is limited by shallower and briefer periods of moisture, resulting in a disconnect between concentration and persistence. Data suggest a tipping point in the cycling of mineral-associated C at a climate threshold where precipitation equals evaporation. As climate patterns shift, our findings emphasize that divergence in the mechanisms of OM persistence associated with historical climate legacies need to be considered in process-based models.

Patterns and controls of foliar nutrient stoichiometry and flexibility across United States forests.

Plant element stoichiometry and stoichiometric flexibility strongly regulate ecosystem responses to global change. Here, we tested three potential mechanistic drivers (climate, soil nutrients, and plant taxonomy) of both using paired foliar and soil nutrient data from terrestrial forested National Ecological Observatory Network sites across the USA. We found that broad patterns of foliar nitrogen (N) and foliar phosphorus (P) are explained by different mechanisms. Plant taxonomy was an important control over all foliar nutrient stoichiometries and concentrations, especially foliar N, which was dominantly related to taxonomy and did not vary across climate or soil gradients. Despite a lack of site-level correlations between N and environment variables, foliar N exhibited intraspecific flexibility, with numerous species-specific correlations between foliar N and various environmental factors, demonstrating the variable spatial and temporal scales on which foliar chemistry and stoichiometric flexibility can manifest. In addition to plant taxonomy, foliar P and N:P ratios were also linked to soil nutrient status (extractable P) and climate, especially actual evapotranspiration rates. Our findings highlight the myriad factors that influence foliar chemistry and show that broad patterns cannot be explained by a single consistent mechanism. Furthermore, differing controls over foliar N versus P suggests that each may be sensitive to global change drivers on distinct spatial and temporal scales, potentially resulting in altered ecosystem N:P ratios that have implications for processes ranging from productivity to carbon sequestration.

Pervasive alterations to snow-dominated ecosystem functions under climate change.

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution.

From hillslope to small catchment scales (< 50 km2), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m2) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a - 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry.

We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO2 , warming, and decreased precipitation combined because higher water-use efficiency with elevated CO2 and higher fertility with warming compensate for responses to drought. Response to elevated CO2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C-nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO2 and climate change.

Nitrification and denitrification in the Community Land Model compared with observations at Hubbard Brook Forest.

Models of terrestrial system dynamics often include nitrogen (N) cycles to better represent N limitations on terrestrial carbon (C) uptake, but simulating the fate of N in ecosystems has proven challenging. Here, key soil N fluxes and flux ratios from the Community Land Model version 5.0 (CLM5.0) are compared with an extensive set of observations from the Hubbard Brook Forest Long-Term Ecological Research site in New Hampshire. Simulated fluxes include microbial immobilization and plant uptake, which compete with nitrification and denitrification, respectively, for available soil ammonium (NH4 + ) and nitrate (NO3 - ). In its default configuration, CLM5.0 predicts that both plant uptake and immobilization are strongly dominated by NH4 + over NO3 - , and that the model ratio of nitrification:denitrification is ~1:1. In contrast, Hubbard Brook observations suggest that NO3 - plays a more significant role in plant uptake and that nitrification could exceed denitrification by an order of magnitude. Modifications to the standard CLM5.0 at Hubbard Brook indicate that a simultaneous increase in the competitiveness of nitrifying microbes for NH4 + and reduction in the competitiveness of denitrifying bacteria for NO3 - are needed to bring soil N flux ratios into better agreement with observations. Such adjustments, combined with evaluation against observations, may help to improve confidence in present and future simulations of N limitation on the C cycle, although C fluxes, such as gross primary productivity and net primary productivity, are less sensitive to the model modifications than soil N fluxes.

Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model.

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change, and broadening the impact of ecological research.

Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models.

Microbially explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (RH ), a stringent test for soil biogeochemical models, has never been evaluated. We used statistical global RH products, as well as 7821 daily site-scale RH measurements, to evaluate the spatiotemporal performance of one first-order decay model (CASA-CNP) and two microbially explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different input datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the input data used to drive them. Spatial variability in RH fluxes was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of RH well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise but also needs to be improved for realistic spatiotemporal variability of RH . Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models.

Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2).

Earth system models are intended to make long-term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)-especially in the tropics-and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.

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.

Greater stem growth, woody allocation, and aboveground biomass in Paleotropical forests than in Neotropical forests.

Forest dynamics and tree species composition vary substantially between Paleotropical and Neotropical forests, but these broad biogeographic regions are treated uniformly in many land models. To assess whether these regional differences translate into variation in productivity and carbon (C) storage, we compiled a database of climate, tree stem growth, litterfall, aboveground net primary production (ANPP), and aboveground biomass across tropical rainforest sites spanning 33 countries throughout Central and South America, Asia, and Australasia, but excluding Africa due to a paucity of available data. Though the sum of litterfall and stem growth (ANPP) did not differ between regions, both stem growth and the ratio of stem growth to litterfall were higher in Paleotropical forests compared to Neotropical forests across the full observed range of ANPP. Greater C allocation to woody growth likely explains the much larger aboveground biomass estimates in Paleotropical forests (~29%, or ~80 Mg DW/ha, greater than in the Neotropics). Climate was similar in Paleo- and Neotropical forests, thus the observed differences in C likely reflect differences in the evolutionary history of species and forest structure and function between regions. Our analysis suggests that Paleotropical forests, which can be dominated by tall-statured Dipterocarpaceae species, may be disproportionate hotspots for aboveground C storage. Land models typically treat these distinct tropical forests with differential structures as a single functional unit, but our findings suggest that this may overlook critical biogeographic variation in C storage potential among regions.

Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions.

Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and-the newly developed-5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO2) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models.

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0-100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, temperature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temperature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. By providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about factors regulating the turnover of soil organic matter.

A test of the hierarchical model of litter decomposition.

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO2. Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France-and capturing both within and among site variation in putative controls-we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

Temperature and rainfall interact to control carbon cycling in tropical forests.

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short-term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer-term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate - C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (< 20 °C), high rainfall slowed rates of C cycling, but in warm tropical forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate - C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth.

Applying population and community ecology theory to advance understanding of belowground biogeochemistry.

Approaches to quantifying and predicting soil biogeochemical cycles mostly consider microbial biomass and community composition as products of the abiotic environment. Current numerical approaches then primarily emphasise the importance of microbe-environment interactions and physiology as controls on biogeochemical cycles. Decidedly less attention has been paid to understanding control exerted by community dynamics and biotic interactions. Yet a rich literature of theoretical and empirical contributions highlights the importance of considering how variation in microbial population ecology, especially biotic interactions, is related to variation in key biogeochemical processes like soil carbon formation. We demonstrate how a population and community ecology perspective can be used to (1) understand the impact of microbial communities on biogeochemical cycles and (2) reframe current theory and models to include more detailed microbial ecology. Through a series of simulations we illustrate how density dependence and key biotic interactions, such as competition and predation, can determine the degree to which microbes regulate soil biogeochemical cycles. The ecological perspective and model simulations we present lay the foundation for developing empirical research and complementary models that explore the diversity of ecological mechanisms that operate in microbial communities to regulate biogeochemical processes.

Organic forms dominate hydrologic nitrogen export from a lowland tropical watershed.

Observations of high dissolved inorganic nitrogen (DIN) concentrations in stream water have reinforced the notion that primary tropical rain forests cycle nitrogen (N) in relative excess compared to phosphorus. Here we test this notion by evaluating hydrologic N export from a small watershed on the Osa Peninsula, Costa Rica, where prior research has shown multiple indicators of conservative N cycling throughout the ecosystem. We repeatedly measured a host of factors known to influence N export for one year, including stream water chemistry and upslope litterfall, soil N availability and net N processing rates, and soil solution chemistry at the surface, 15- and 50-cm depths. Contrary to prevailing assumptions about the lowland N cycle, we find that dissolved organic nitrogen (DON) averaged 85% of dissolved N export for 48 of 52 consecutive weeks. For most of the year stream water nitrate (NO3-) export was very low, which reflected minimal net N processing and DIN leaching from upslope soils. Yet, for one month in the dry season, NO3- was the major component of N export due to a combination of low flows and upslope nitrification that concentrated NO3- in stream water. Particulate organic N (PON) export was much larger than dissolved forms at 14.6 kg N x ha(-1) x yr(-1), driven by soil erosion during storms. At this rate, PON export was slightly greater than estimated inputs from free-living N fixation and atmospheric N deposition, which suggests that erosion-driven PON export could constrain ecosystem level N stocks over longer timescales. This phenomenon is complimentary to the "DON leak" hypothesis, which postulates that the long-term accumulation of ecosystem N in unpolluted ecosystems is constrained by the export of organic N independently of biological N demand. Using an established global sediment generation model, we illustrate that PON erosion may be an important vector for N loss in tropical landscapes that are geomorphically active. This study supports an emerging view that landscape geomorphology influences nutrient biogeochemistry and limitation, though more research is needed to understand the mechanisms and spatial significance of erosional N loss from terrestrial ecosystems.

Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4).

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. We tested the litter decomposition parameterization of the community land model version 4 (CLM4), the terrestrial component of the community earth system model, with data from the long-term intersite decomposition experiment team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We performed 10-year litter decomposition simulations comparable with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. We performed additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results show large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, and nitrogen immobilization is biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that soil mineral nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, independent of nitrogen limitation. CLM4 has low soil carbon in global earth system simulations. These results suggest that this bias arises, in part, from too rapid litter decomposition. More broadly, the terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models.

Experimental litterfall manipulation drives large and rapid changes in soil carbon cycling in a wet tropical forest.

Global changes such as variations in plant net primary production are likely to drive shifts in leaf litterfall inputs to forest soils, but the effects of such changes on soil carbon (C) cycling and storage remain largely unknown, especially in C-rich tropical forest ecosystems. We initiated a leaf litterfall manipulation experiment in a tropical rain forest in Costa Rica to test the sensitivity of surface soil C pools and fluxes to different litter inputs. After only 2 years of treatment, doubling litterfall inputs increased surface soil C concentrations by 31%, removing litter from the forest floor drove a 26% reduction over the same time period, and these changes in soil C concentrations were associated with variations in dissolved organic matter fluxes, fine root biomass, microbial biomass, soil moisture, and nutrient fluxes. However, the litter manipulations had only small effects on soil organic C (SOC) chemistry, suggesting that changes in C cycling, nutrient cycling, and microbial processes in response to litter manipulation reflect shifts in the quantity rather than quality of SOC. The manipulation also affected soil CO 2 fluxes; the relative decline in CO 2 production was greater in the litter removal plots (-22%) than the increase in the litter addition plots (+15%). Our analysis showed that variations in CO 2 fluxes were strongly correlated with microbial biomass pools, soil C and nitrogen (N) pools, soil inorganic P fluxes, dissolved organic C fluxes, and fine root biomass. Together, our data suggest that shifts in leaf litter inputs in response to localized human disturbances and global environmental change could have rapid and important consequences for belowground C storage and fluxes in tropical rain forests, and highlight differences between tropical and temperate ecosystems, where belowground C cycling responses to changes in litterfall are generally slower and more subtle.

Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis.

Tropical rain forests play a dominant role in global biosphere-atmosphere CO(2) exchange. Although climate and nutrient availability regulate net primary production (NPP) and decomposition in all terrestrial ecosystems, the nature and extent of such controls in tropical forests remain poorly resolved. We conducted a meta-analysis of carbon-nutrient-climate relationships in 113 sites across the tropical forest biome. Our analyses showed that mean annual temperature was the strongest predictor of aboveground NPP (ANPP) across all tropical forests, but this relationship was driven by distinct temperature differences between upland and lowland forests. Within lowland forests (< 1000 m), a regression tree analysis revealed that foliar and soil-based measurements of phosphorus (P) were the only variables that explained a significant proportion of the variation in ANPP, although the relationships were weak. However, foliar P, foliar nitrogen (N), litter decomposition rate (k), soil N and soil respiration were all directly related with total surface (0-10 cm) soil P concentrations. Our analysis provides some evidence that P availability regulates NPP and other ecosystem processes in lowland tropical forests, but more importantly, underscores the need for a series of large-scale nutrient manipulations - especially in lowland forests - to elucidate the most important nutrient interactions and controls.