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The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (>g50g% of the soil organic carbon stocks are below 30gcm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4ggC warming in the whole-soil profile to 100gcm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30gcm) by 28g% but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources.

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20g g€¯S to 20g g€¯N) the spring onset of elevated CH4 emissions starts 3g€¯d earlier, and the CH4 emission season lasts 4g€¯d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at 10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Increasing global temperatures have the potential to stimulate decomposition and alter the composition of soil organic matter (SOM). However, questions remain about the extent to which SOM quality and quantity along the soil profile may change under future warming. In this study we assessed how +4 °C whole-soil warming affected the quantity and quality of SOM down to 90 cm depth in a mixed-coniferous temperate forest using biomarker analyses. Our findings indicate that 4.5 years of soil warming led to divergent responses in subsoils (>20 cm) as compared to surface soils. Warming enhanced the accumulation of plant-derived n-alkanes over the whole soil profile. In the subsoil, this was at the expense of plant- and microorganism-derived fatty acids, and the relative abundance of SOM molecular components shifted from less microbially transformed to more transformed organic matter. Fine root mass declined by 24.0 ± 7.5% with warming over the whole soil profile, accompanied by reduced plant-derived inputs and accelerated decomposition of aromatic compounds and plant-derived fatty acids in the subsoils. Our study suggests that warming accelerated microbial decomposition of plant-derived inputs, leaving behind more degraded organic matter. The non-uniform, and depth dependent SOM composition and warming response implies that subsoil carbon cycling is as sensitive and complex as in surface soils.

Soil organic carbon management has the potential to aid climate change mitigation through drawdown of atmospheric carbon dioxide. To be effective, such management must account for processes influencing carbon storage and re-emission at different space and time scales. Achieving this requires a conceptual advance in our understanding to link carbon dynamics from the scales at which processes occur to the scales at which decisions are made. Here, we propose that soil carbon persistence can be understood through the lens of decomposers as a result of functional complexity derived from the interplay between spatial and temporal variation of molecular diversity and composition. For example, co-location alone can determine whether a molecule is decomposed, with rapid changes in moisture leading to transport of organic matter and constraining the fitness of the microbial community, while greater molecular diversity may increase the metabolic demand of, and thus potentially limit, decomposition. This conceptual shift accounts for emergent behaviour of the microbial community and would enable soil carbon changes to be predicted without invoking recalcitrant carbon forms that have not been observed experimentally. Functional complexity as a driver of soil carbon persistence suggests soil management should be based on constant care rather than one-time action to lock away carbon in soils.

Developing a more mechanistic understanding of soil respiration is hampered by the difficulty in determining the contribution of different organic substrates to respiration and in disentangling autotrophic-versus-heterotrophic and aerobic-versus-anaerobic processes. Here, we use a relatively novel tool for better understanding soil respiration: The apparent respiration quotient (ARQ). The ARQ is the amount of CO2 produced in the soil divided by the amount of O2 consumed, and it changes according to which organic substrates are being consumed and whether oxygen is being used as an electron acceptor. We investigated how the ARQ of soil gas varied seasonally, by soil depth, and by in situ experimental warming (+4 °C) in a coniferousforest whole-soil-profile warming experiment over 2 years. We then compared the patterns in ARQ to those of soil δ13CO2. Our measurements showed strong seasonal variations in ARQ, from ≈ 0.9 during the late spring and summer to 0:7 during the winter. This pattern likely reflected a shift from respiration being fueled by oxidized substrates like sugars and organic acids derived from root and root respiration during the growing season to more reduced substrates such as lipids and proteins derived from microbial necromass during the winter. This interpretation was supported by δ13CO2 values, which were lower, like lipids, in the winter and higher, like sugars, in the summer. Furthermore, experimental warming significantly changed how both ARQ and δ13CO2 responded to soil temperature. Wintertime ARQ and δ13CO2 values were higher in heated than in control plots, probably due to the warming-driven increase in microbial activity that may have utilized oxidized carbon substrates, while growing-season values were lower in heated plots. Experimental warming and phenology change the sources of soil respiration throughout the soil profile. The sensitivity of ARQ to these changes demonstrates its potential as a tool for disentangling the biological sources contributing to soil respiration.

Despite the fundamental importance of soil temperature for Earth's carbon and energy budgets, ecosystem functioning, and agricultural production, studies of climate change impacts on soil processes have mainly relied on air temperatures, assuming they are accurate proxies for soil temperatures. We evaluated changes in soil temperature, moisture, and air temperature predicted over the 21st century from 14 Earth system models. The model ensemble predicted a global mean soil warming of 2.3 ± 0.7 and 4.5 ± 1.1 °C at 100-cm depth by the end of the 21st century for RCPs 4.5 and 8.5, respectively. Soils at 100 cm warmed at almost exactly the same rate as near-surface (~1 cm) soils. Globally, soil warming was slightly slower than air warming above it, and this difference increased over the 21st century. Regionally, soil warming kept pace with air warming in tropical and arid regions but lagged air warming in colder regions. Thus, air warming is not necessarily a good proxy for soil warming in cold regions where snow and ice impede the direct transfer of sensible heat from the atmosphere to soil. Despite this effect, high-latitude soils were still projected to warm faster than elsewhere, albeit at slower rates than surface air above them. When compared with observations, the models were able to capture soil thermal dynamics in most biomes, but some failed to recreate thermal properties in permafrost regions. Particularly in cold regions, using soil warming rather than air warming projections may improve predictions of temperature-sensitive soil processes.

Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2 + H2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

The Arctic is expected to shift from a sink to a source of atmospheric CO2 this century due to climate-induced increases in soil carbon mineralization1. The magnitude of this effect remains uncertain, largely because temperature sensitivities of organic matter decomposition2,3 and the distribution of these temperature sensitivities across soil carbon pools4 are not well understood. Here, a new analytical method with natural abundance radiocarbon was used to evaluate temperature sensitivities across soil carbon pools. With soils from Utqiaġvik (formerly Barrow), Alaska, an incubation experiment was used to evaluate soil carbon age and decomposability, disentangle the effects of temperature and substrate depletion on carbon mineralization, and compare temperature sensitivities of fast-cycling and slow-cycling carbon. Old, historically stable carbon was shown to be vulnerable to decomposition under warming. Using radiocarbon to differentiate between slow-cycling and fast-cycling carbon, temperature sensitivity was found to be invariant among pools, with a Q10 of ~2 irrespective of native decomposition rate. These findings suggest that mechanisms other than chemical recalcitrance mediate the effect of warming on soil carbon mineralization.

Developing and testing decadal-scale predictions of soil response to climate change is difficult because there are few long-term warming experiments or other direct observations of temperature response. As a result, spatial variation in temperature is often used to characterize the influence of temperature on soil organic carbon (SOC) stocks under current and warmer temperatures. This approach assumes that the decadal-scale response of SOC to warming is similar to the relationship between temperature and SOC stocks across sites that are at quasi steady state; however, this assumption is poorly tested. We developed four variants of a Reaction-network-based model of soil organic matter and microbes using measured SOC stocks from a 4,000-km latitudinal transect. Each variant reflects different assumptions about the temperature sensitivities of microbial activity and mineral sorption. All four model variants predicted the same response of SOC to temperature at steady state, but different projections of transient warming responses. The relative importance of Qmax, mean annual temperature, and net primary production, assessed using a machine-learning algorithm, changed depending on warming duration. When mineral sorption was temperature sensitive, the predicted average change in SOC after 100 years of 5 °C warming was −18% if warming decreased sorption or +9% if warming increased sorption. When microbial activity was temperature sensitive but mineral sorption was not, average site-level SOC loss was 5%. We conclude that spatial climate gradients of SOC stocks are insufficient to constrain the transient response; measurements that distinguish process controls and/or observations from long-term warming experiments, especially mineral fractions, are needed.

Model projections of future CO2 and CH4 exchange in Arctic tundra diverge widely. Here we used ecosys to examine how climate change will affect CO2 and CH4 exchange in troughs, rims, and centers of a coastal polygonal tundra landscape at Barrow, AK. The model was shown to simulate diurnal and seasonal variation in CO2 and CH4 fluxes associated with those in air and soil temperatures (Ta and Ts) and soil water contents (θ) under current climate in 2014 and 2015. During RCP 8.5 climate change from 2015 to 2085, rising Ta, atmospheric CO2 concentrations (Ca), and precipitation (P) increased net primary productivity (NPP) from 50–150 g C m-2 y-1, consistent with current biometric estimates, to 200–250 g C m−2 y−1. Concurrent increases in heterotrophic respiration (Rh) were slightly smaller, so that net CO2 exchange rose from values of −25 (net emission) to +50 (net uptake) g C m−2 y−1 to ones of −10 to +65 g C m−2 y−1. Increases in net CO2 uptake were largely offset by increases in CH4 emissions from 0–6 to 1–20 g C m−2 y−1, reducing gains in net ecosystem productivity. These increases in net CO2 uptake and CH4 emissions were modeled with hydrological boundary conditions that were assumed not to change with climate. Both these increases were smaller if boundary conditions were gradually altered to increase landscape drainage during model runs with climate change.

We describe a new coordination activity and initial results for a global synthesis of eddy covariance CH4 flux measurements.

Radiocarbon measurements of ecosystem respiration and soil pore space CO2 are useful for determining the sources of ecosystem respiration, identifying environmental controls on soil carbon cycling rates, and parameterizing and evaluating models of the carbon cycle. We measured flux rates and radiocarbon content of ecosystem respiration, as well as radiocarbon in soil profile CO2 in UtqiaAïvik (Barrow), Alaska, during the summers of 2012, 2013, and 2014. We found that radiocarbon in ecosystem respiration (Δ;14CReco) ranged from +60.5 to '160 ‰ with a median value of +23.3 ‰. Ecosystem respiration became more depleted in radiocarbon from summer to autumn, indicating increased decomposition of old soil organic carbon and/or decreased CO2 production from fast-cycling carbon pools. Across permafrost features, ecosystem respiration from high-centered polygons was depleted in radiocarbon relative to other polygon types. Radiocarbon content in soil pore-space CO2 varied between '7.1 and '280 ‰, becoming more negative with depth in individual soil profiles. These pore-space radiocarbon values correspond to CO2 mean ages of 410 to 3350 years, based on a steady-state, one-pool model. Together, these data indicate that deep soil respiration was derived primarily from old, slow-cycling carbon, but that total CO2 fluxes depended largely on autotrophic respiration and heterotrophic decomposition of fast-cycling carbon within the shallowest soil layers. The relative contributions of these different CO2 sources were highly variable across microtopographic features and time in the sampling season. The highly negative Δ14C values in soil pore-space CO2 and autumn ecosystem respiration indicate that when it is not frozen, very old soil carbon is vulnerable to decomposition. Radiocarbon data and associated CO2 flux and temperature data are stored in the data repository of the Next Generation Ecosystem Experiments (NGEE-Arctic) at http://dx.doi.org/10.5440/1364062 and https://doi.org/10.5440/1418853.

Atmospheric methane (CH4) mixing ratios exhibited a plateau between 1995 and 2006 and have subsequently been increasing. While there are a number of competing explanations for the temporal evolution of this greenhouse gas, these prominent features in the temporal trajectory of atmospheric CH4 are expected to perturb the surface energy balance through radiative forcing, largely due to the infrared radiative absorption features of CH4. However, to date this has been determined strictly through radiative transfer calculations. Here, we present a quantified observation of the time series of clear-sky radiative forcing by CH4 at the surface from 2002 to 2012 at a single site derived from spectroscopic measurements along with line-by-line calculations using ancillary data. There was no significant trend in CH4 forcing between 2002 and 2006, but since then, the trend in forcing was 0.026 ± 0.006 (99.7% CI) W m2 yr-1. The seasonal-cycle amplitude and secular trends in observed forcing are influenced by a corresponding seasonal cycle and trend in atmospheric CH4. However, we find that we must account for the overlapping absorption effects of atmospheric water vapour (H2O) and CH4 to explain the observations fully. Thus, the determination of CH4 radiative forcing requires accurate observations of both the spatiotemporal distribution of CH4 and the vertically resolved trends in H2O.

Temperature records and model predictions demonstrate that deep soils warm at the same rate as surface soils, contrary to Xiao et al's assertions. In response to Xiao et al's critique of our Q10 analysis, we present the results with all data points included, which show Q10 values of >2 throughout the soil profile, indicating that all soil depths responded to warming.

AmeriFlux scientists were early adopters of a network-enabled approach to ecosystem science that continues to transform the study of land-atmosphere interactions. In the 20 years since its formation, AmeriFlux has grown to include more than 260 flux tower sites in the Americas that support continuous observation of ecosystem carbon, water, and energy fluxes. Many of these sites are co-located within a similar climate regime, and more than 50 have data records that exceed 10 years in length. In this prospective assessment of AmeriFlux’s strengths in a new era of network-enabled ecosystem science, we discuss how the longevity and spatial distribution of AmeriFlux data make them exceptionally well suited for disentangling ecosystem response to slowly evolving changes in climate and land-cover, and to rare events like droughts and biological disturbances. More recently, flux towers have also been integrated into environmental observation networks that have broader scientific goals; in North America these include the National Ecological Observatory Network (NEON), Critical Zone Observatory network (CZO), and Long-Term Ecological Research network (LTER). AmeriFlux stands apart from these other networks in its reliance on voluntary participation of individual sites, which receive funding from diverse sources to pursue a wide, transdisciplinary array of research topics. This diffuse, grassroots approach fosters methodological and theoretical innovation, but also challenges network-level data synthesis and data sharing to the network. While AmeriFlux has had strong ties to other regional flux networks and FLUXNET, better integration with networks like NEON, CZO and LTER provides opportunities for new types of cooperation and synergies that could strengthen the scientific output of all these networks.

Soils are a globally important reservoir of organic carbon. There is a growing understanding that interactions with soil mineral phases contribute to the accumulation and retention of otherwise degradable organic matter (OM) in soils and sediments. However, the bioavailability of organic compounds in mineral-organic-associations (MOAs), especially under varying environmental conditions is not well known. To assess the impact of mineral association and warming on the decomposition of an easily respirable organic substrate (glucose), we conducted a series of laboratory incubations at different temperatures with field-collected soils from 10 to 20cm, 50-60cm, and 80-90cm depth. We added 13C-labeled glucose either directly to native soil or sorbed to one of two synthetic iron (hydr)oxide phases (goethite and ferrihydrite) that differ in crystallinity and affinity for sorbing glucose. We found that: (1) association with the Fe (hydr)oxide minerals reduced the decomposition rate of glucose by >99.5% relative to rate of decomposition for free glucose in soil; (2) the respiration rate per gram carbon did not differ appreciably with depth, suggesting a similar degree of decomposability for native C across depths and that under the incubation conditions total carbon availability represents the principal limitation on respiration under these conditions as opposed to reduced abundance of decomposers or moisture and oxygen limitations; (3) addition of free glucose enhanced native carbon respiration at all soil depths with the largest effect at 50-60cm; (4) in general respiration of the organo-mineral complex (glucose and iron-(hydr)oxide) was less temperature sensitive than was respiration of native carbon; (5) the addition of organic free mineral decreased the rate of soil respiration in the intermediate 50-60cm depth soil. The results emphasize the key role of MOAs in regulating the fluxes of carbon from soils to the atmosphere and in turn the stocks of soil carbon.

For the 70th Anniversary of the establishment of the British Society of Soil Science, this short paper explores the idea that research on soil organic matter has remained a central theme within soil science over the past 70 years, albeit with changing emphasis and application. The number of publications on soil organic matter has increased greatly in recent decades; for example, there were almost 35 000 journal papers with this theme in the decade 2007–2016. Several topics in research on soil organic matter, such as soil fertility, have endured for a number of decades, with publications found on soil organic matter and fertility in the decade 1947–1956. A search with other keywords occurring with soil, such as climate change, biodiversity, fertility, quality, health and security, showed that several topics did not appear before the 1970s and 1980s, but since then the sub‐topics and applications have diversified. Carbon is a keyword that has become more associated with publications on soil organic matter; carbon is in over half of soil organic matter publications of the last decade. A closer examination of research on agricultural soil carbon sequestration since 1990 reveals that the focus of papers in the literature has changed over this period. A closer examination of papers on modelling shows that the next generation of soil organic matter models is developing from pseudo first‐order decay models using conceptual pools and prescribed controls of turnover time to vertically resolved, microbially explicit models representing mineral surface and plant interactions. Given its higher policy profile during the last 2 years, research on soil organic matter and soil carbon sequestration is predicted to have a bright future. HIGHLIGHTS: The number of publications on soil organic matter has increased greatly in recent decades. Soil fertility research has endured for many decades, whereas other topics have diversified. Soil organic matter has been increasingly associated with carbon, which has changed the focus of papers since 1990. Expanding policy attention to soil organic matter research during the last 2 years suggests a bright future.

Microtopographic variation that develops among features (troughs, rims, and centers) within polygonal landforms of coastal arctic tundra strongly affects movement of surface water and snow and thereby affects soil water contents (θ) and active layer depth (ALD). Spatial variation in ALD among these features may exceed interannual variation in ALD caused by changes in climate and so needs to be represented in projections of changes in arctic ALD. In this study, increases in near-surface θ with decreasing surface elevation among polygon features at the Barrow Experimental Observatory (BEO) were modeled from topographic effects on redistribution of surface water and snow and from lateral water exchange with a subsurface water table during a model run from 1981 to 2015. These increases in θ caused increases in thermal conductivity that in turn caused increases in soil heat fluxes and hence in ALD of up to 15 cm with lower versus higher surface elevation which were consistent with increases measured at BEO. The modeled effects of θ caused interannual variation in maximum ALD that compared well with measurements from 1985 to 2015 at the Barrow Circumpolar Active Layer Monitoring (CALM) site (R2 = 0.61, RMSE = 0.03 m). For higher polygon features, interannual variation in ALD was more closely associated with annual precipitation than mean annual temperature, indicating that soil wetting from increases in precipitation may hasten permafrost degradation beyond that caused by soil warming from increases in air temperature. This degradation may be more rapid if increases in precipitation cause sustained wetting in higher features.

Differences of surface elevation in arctic polygonal landforms cause spatial variation in soil water contents (θ), active layer depths (ALD), and thereby in CO2 and CH4 exchange. Here we test hypotheses in ecosys for topographic controls on CO2 and CH4 exchange in trough, rim, and center features of low- and flat-centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements during 2013 at Barrow, Alaska. Larger CO2 influxes and CH4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in lower features (troughs) than in higher (rims) within LCPs and FCPs. Spatially aggregated CO2 and CH4 fluxes from ecosys were significantly correlated with EC flux measurements. Lower features were modeled as C sinks (52–56 g C m−2 yr−1) and CH4 sources (4–6 g C m−2 yr−1), and higher features as near C neutral (−2–15 g C m−2 yr−1) and CH4 neutral (0.0–0.1 g C m−2 yr−1). Much of the spatial and temporal variations in CO2 and CH4 fluxes were modeled from topographic effects on water and snow movement and thereby on θ, ALD, and soil O2 concentrations. Model results forced with meteorological data from 1981 to 2015 indicated increasing net primary productivity in higher features and CH4 emissions in some lower and higher features since 2008, attributed mostly to recent rises in precipitation. Small-scale variation in surface elevation causes large spatial variation of greenhouse gas (GHG) exchanges and therefore should be considered in estimates of GHG exchange in polygonal landscapes.

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operated in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. These results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.

Coastal tundra ecosystems are relatively flat, and yet display large spatial variability in ecosystem traits. The microtopographical differences in polygonal geomorphology produce heterogeneity in permafrost depth, soil temperature, soil moisture, soil geochemistry, and plant distribution. Few measurements have been made, however, of how water fluxes vary across polygonal tundra plant types, limiting our ability to understand and model these ecosystems. Our objective was to investigate how plant distribution and geomorphological location affect actual evapotranspiration (ET). These effects are especially critical in light of the rapid change polygonal tundra systems are experiencing with Arctic warming. At a field site near Barrow, Alaska, USA, we investigated the relationships between ET and plant cover in 2014 and 2015. ET was measured at a range of spatial and temporal scales using: (1) An eddy covariance flux tower for continuous landscape-scale monitoring; (2) An automated clear surface chamber over dry vegetation in a fixed location for continuous plot-scale monitoring; and (3) Manual measurements with a clear portable chamber in approximately 60 locations across the landscape. We found that variation in environmental conditions and plant community composition, driven by microtopographical features, has significant influence on ET. Among plant types, ET from moss-covered and inundated areas was more than twice that from other plant types. ET from troughs and low polygonal centers was significantly higher than from high polygonal centers. ET varied seasonally, with peak fluxes of 0.14 mm h−1 in July. Despite 24 hours of daylight in summer, diurnal fluctuations in incoming solar radiation and plant processes produced a diurnal cycle in ET. Combining the patterns we observed with projections for the impact of permafrost degradation on polygonal structure suggests that microtopographic changes associated with permafrost thaw have the potential to alter tundra ecosystem ET.

The seasonal pattern of the carbon isotope content (δ13C) of atmospheric CO2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δsource at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ13C variation of nonlocal sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δsource at the forest sites (0.5‰ variation). We did not find a consistent seasonal relationship between VPD and δsource across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δsource (5‰) dominated by seasonal transitions in C3/C4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ13C of land-atmosphere CO2 exchange (δsource) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C3/C4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate δsource when background atmospheric observations are remote and/or prone to anthropogenic influence.

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35% during the spring growing season. The model accurately simulated the interannual variation in yield at the USARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

The role of organo-mineral interactions, microbial dynamics, and vertical plant input profiles are hypothesized to be important in controlling soil organic matter (SOM) stocks and dynamics. To test this hypothesis, we enhanced and applied a model (Biotic and Abiotic Model of SOM – BAMS1) that represents microbial dynamics and organo-mineral interactions integrated with a multiphase reactive transport solver for variably saturated porous media. The model represents aqueous chemistry, aqueous advection and diffusion, gaseous diffusion, sorption processes, bacterial and fungal activity, and archetypal monomer- and polymer-carbon substrate groups, including dead cell wall material. This model structure is fundamentally different, and produces different SOM dynamics, than the pseudo-first order relationships that are used in most site- and global-scale terrestrial SOM models. We simulated two grasslands, a seven-site chronosequence (∼3.9–240 Ky) in Northern California, and a Russian Chernozem site where soils were sampled 100 years apart. We calibrated the model's vertically-resolved soil bulk specific surface area (SBSSA) using observed bulk SOM content, and then tested the model against observed Δ14C profiles. The modeled microbial processes, organo-mineral interactions, and vertical aqueous transport produced realistic vertically-resolved predictions of bulk SOM content, Δ14C values of SOM, lignin content, and fungi-to-aerobic bacteria biomass ratios. Using sensitivity analyses, we found that vertical carbon input profiles were important controls over the Δ14C depth distribution. Shallower carbon input profiles lead to older carbon at depth. In addition, the SBSSA was the dominant control over the magnitude and vertical distribution of SOM stocks. The findings of this study demonstrate the value of explicitly incorporating microbial activity, sorption, and vertical transport into land models to predict SOM dynamics.

Soil organic carbon harbors three times as much carbon as Earth's atmosphere, and its decomposition is a potentially large climate change feedback and major source of uncertainty in climate projections. The response of whole-soil profiles to warming has not been tested in situ. In a deep warming experiment in mineral soil, we found that CO2 production from all soil depths increased with 4°C warming; annual soil respiration increased by 34 to 37%. All depths responded to warming with similar temperature sensitivities, driven by decomposition of decadal-aged carbon. Whole-soil warming reveals a larger soil respiration response than many in situ experiments (most of which only warm the surface soil) and models.

The few prethaw observations of tundra carbon fluxes suggest that there may be large spring releases, but little is known about the scale and underlying mechanisms of this phenomenon. To address these questions, we combined ecosystem eddy flux measurements from two towers near Barrow, Alaska, with mechanistic soil-core thawing experiment. During a 2 week period prior to snowmelt in 2014, large fluxes were measured, reducing net summer uptake of CO2 by 46% and adding 6% to cumulative CH4 emissions. Emission pulses were linked to unique rain-on-snow events enhancing soil cracking. Controlled laboratory experiment revealed that as surface ice thaws, an immediate, large pulse of trapped gases is emitted. These results suggest that the Arctic CO2 and CH4 spring pulse is a delayed release of biogenic gas production from the previous fall and that the pulse can be large enough to offset a significant fraction of the moderate Arctic tundra carbon sink.

Land-atmosphere interactions are important to climate prediction, but the underlying effects of surface forcing of the atmosphere are not well understood. In the U.S. Southern Great Plains, grassland/pasture and winter wheat are the dominant land covers but have distinct growing periods that may differently influence land-atmosphere coupling during spring and summer. Variables that influence surface flux partitioning can change seasonally, depending on the state of local vegetation. Here we use surface observations from multiple sites in the U.S. Department of Energy Atmospheric Radiation Measurement Southern Great Plains Climate Research Facility and statistical modeling at a paired grassland/agricultural site within this facility to quantify land cover influence on surface energy balance and variables controlling evaporative fraction (latent heat flux normalized by the sum of sensible and latent heat fluxes). We demonstrate that the radiative balance and evaporative fraction are closely related to green leaf area at both winter wheat and grassland/pasture sites and that the early summer harvest of winter wheat abruptly shifts the relationship between evaporative fraction and surface state variables. Prior to harvest, evaporative fraction of winter wheat is strongly influenced by leaf area and soil-atmosphere temperature differences. After harvest, variations in soil moisture have a stronger effect on evaporative fraction. This is in contrast with grassland/pasture sites, where variation in green leaf area has a large influence on evaporative fraction throughout spring and summer, and changes in soil-atmosphere temperature difference and soil moisture are of relatively minor importance.

Biases in land-atmosphere coupling in climate models can contribute to climate prediction biases, but land models are rarely evaluated in the context of this coupling. We tested land-atmosphere coupling and explored effects of land surface parameterizations on climate prediction in a single-column version of the National Center for Atmospheric Research Community Earth System Model (CESM1.2.2) and an off-line Community Land Model (CLM4.5). The correlation between leaf area index (LAI) and surface evaporative fraction (ratio of latent to total turbulent heat flux) was substantially underpredicted compared to observations in the U.S. Southern Great Plains, while the correlation between soil moisture and evaporative fraction was overpredicted by CLM4.5. To estimate the impacts of these errors on climate prediction, we modified CLM4.5 by prescribing observed LAI, increasing soil resistance to evaporation, increasing minimum stomatal conductance, and increasing leaf reflectance. The modifications improved the predicted soil moisture-evaporative fraction (EF) and LAI-EF correlations in off-line CLM4.5 and reduced the root-mean-square error in summer 2 m air temperature and precipitation in the coupled model. The modifications had the largest effect on prediction during a drought in summer 2006, when a warm bias in daytime 2 m air temperature was reduced from +6°C to a smaller cold bias of -1.3°C, and a corresponding dry bias in precipitation was reduced from -111 mm to -23 mm. The role of vegetation in droughts and heat waves is underpredicted in CESM1.2.2, and improvements in land surface models can improve prediction of climate extremes.

Gross primary productivity (GPP) has been reported to increase with the fraction of diffuse solar radiation, for a given total irradiance. The correlation between GPP and diffuse radiation suggests effects of diffuse radiation on canopy light-use efficiency, but potentially confounding effects of vegetation phenology have not been fully explored. We applied several approaches to control for phenology, using 8 years of eddy-covariance measurements of winter wheat in the U.S. Southern Great Plains. The apparent enhancement of daily GPP due to diffuse radiation was reduced from 260% to 75%, after subsampling over the peak growing season or by subtracting a 15 day moving average of GPP, suggesting a role of phenology. The diffuse radiation effect was further reduced to 22% after normalizing GPP by a spectral reflectance index to account for phenological variations in leaf area index LAI and canopy photosynthetic capacity. Canopy photosynthetic capacity covaries with diffuse fraction at a given solar irradiance at this site because both factors are dependent on day of year or solar zenith angle. Using a two-leaf Sun-shaded canopy radiative transfer model, we confirmed that the effects of phenological variations in photosynthetic capacity can appear qualitatively similar to the effects of diffuse radiation on GPP and therefore can be difficult to distinguish using observations. The importance of controlling for phenology when inferring diffuse radiation effects on GPP raises new challenges and opportunities for using radiation measurements to improve carbon cycle models.

We provide observational evidence that land-atmosphere coupling is underestimated by a conventional metric defined by the correlation between soil moisture and surface evaporative fraction (latent heat flux normalized by the sum of sensible and latent heat flux). Land-atmosphere coupling is 3 times stronger when using leaf area index as a correlate of evaporative fraction instead of soil moisture, in the Southern Great Plains. The role of vegetation was confirmed using adjacent flux measurement sites having identical atmospheric forcing but different vegetation phenology. Transpiration makes the relationship between evaporative fraction and soil moisture nonlinear and gives the appearance of weak coupling when using linear soil moisture metrics. Regions of substantial coupling extend to semiarid and humid continental climates across the United States, in terms of correlations between vegetation metrics and evaporative fraction. The hydrological cycle is more tightly constrained by the land surface than previously inferred from soil moisture.

Arctic soils contain a large pool of terrestrial C and are of interest due to their potential for releasing significant carbon dioxide (CO2) and methane (CH4) to the atmosphere. Due to substantial landscape heterogeneity, predicting ecosystem-scale CH4 and CO2 production is challenging. This study assessed dissolved inorganic carbon (DIC = Σ (total) dissolved CO2) and CH4 in watershed drainages in Barrow, Alaska as critical convergent zones of regional geochemistry, substrates, and nutrients. In July and September of 2013, surface waters and saturated subsurface pore waters were collected from 17 drainages. Based on simultaneous DIC and CH4 cycling, we synthesized isotopic and geochemical methods to develop a subsurface CH4 and DIC balance by estimating mechanisms of CH4 and DIC production and transport pathways and oxidation of subsurface CH4. We observed a shift from acetoclastic (July) toward hydrogenotropic (September) methanogenesis at sites located toward the end of major freshwater drainages, adjacent to salty estuarine waters, suggesting an interesting landscape-scale effect on CH4 production mechanism. The majority of subsurface CH4 was transported upward by plant-mediated transport and ebullition, predominantly bypassing the potential for CH4 oxidation. Thus, surprisingly, CH4 oxidation only consumed approximately 2.51 ± 0.82% (July) and 0.79 ± 0.79% (September) of CH4 produced at the frost table, contributing to

The climatic impact of CO2 and other greenhouse gases is usually quantified in terms of radiative forcing, calculated as the difference between estimates of the Earth's radiation field from pre-industrial and present-day concentrations of these gases. Radiative transfer models calculate that the increase in CO2 since 1750 corresponds to a global annual-mean radiative forcing at the tropopause of 1.82 ± 0.19 W m(-2) (ref. 2). However, despite widespread scientific discussion and modelling of the climate impacts of well-mixed greenhouse gases, there is little direct observational evidence of the radiative impact of increasing atmospheric CO2. Here we present observationally based evidence of clear-sky CO2 surface radiative forcing that is directly attributable to the increase, between 2000 and 2010, of 22 parts per million atmospheric CO2. The time series of this forcing at the two locations-the Southern Great Plains and the North Slope of Alaska-are derived from Atmospheric Emitted Radiance Interferometer spectra together with ancillary measurements and thoroughly corroborated radiative transfer calculations. The time series both show statistically significant trends of 0.2 W m(-2) per decade (with respective uncertainties of ±0.06 W m(-2) per decade and ±0.07 W m(-2) per decade) and have seasonal ranges of 0.1-0.2 W m(-2). This is approximately ten per cent of the trend in downwelling longwave radiation. These results confirm theoretical predictions of the atmospheric greenhouse effect due to anthropogenic emissions, and provide empirical evidence of how rising CO2 levels, mediated by temporal variations due to photosynthesis and respiration, are affecting the surface energy balance.

U.S. national and regional emissions of HFC-134a are derived for 20082012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximumlikelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr-1 for the contiguous U.S. during 20082012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 20082010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 1020% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 2050%.

The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at the warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections, and the time taken to return to locally optimal climates for GPP following climate extremes increases by more than 25% over many land regions.

Soils are globally significant sources and sinks of atmospheric CO2. Increasing the resolution of soil carbon turnover estimates is important for predicting the response of soil carbon cycling to environmental change. We show that soil carbon turnover times can be more finely resolved using a dual isotope label like the one provided by elevated CO2 experiments that use fossil CO2. We modeled each soil physical fraction as two pools with different turnover times using the atmospheric 14C bomb spike in combination with the label in 14C and 13C provided by an elevated CO2 experiment in a California annual grassland. In sandstone and serpentine soils, the light fraction carbon was 21-54% fast cycling with 2-9 yr turnover, and 36-79% slow cycling with turnover slower than 100 yr. This validates model treatment of the light fraction as active and intermediate cycling carbon. The dense, mineral-associated fraction also had a very dynamic component, consisting of ∼7% fast-cycling carbon and ∼93% very slow cycling carbon. Similarly, half the microbial biomass carbon in the sandstone soil was more than 5 yr old, and 40% of the carbon respired by microbes had been fixed more than 5 yr ago. Resolving each density fraction into two pools revealed that only a small component of total soil carbon is responsible for most CO2 efflux from these soils. In the sandstone soil, 11% of soil carbon contributes more than 90% of the annual CO2 efflux. The fact that soil physical fractions, designed to isolate organic material of roughly homogeneous physico-chemical state, contain material of dramatically different turnover times is consistent with recent observations of rapid isotope incorporation into seemingly stable fractions and with emerging evidence for hot spots or micro-site variation of decomposition within the soil matrix. Predictions of soil carbon storage using a turnover time estimated with the assumption of a single pool per density fraction would greatly overestimate the near-term response to changes in productivity or decomposition rates. Therefore, these results suggest a slower initial change in soil carbon storage due to environmental change than has been assumed by simpler (one-pool) mass balance calculations.©Author(s) 2013. CC Attribution 3.0 License.

Background: Seedling germination and survival is a critical control on forest ecosystem boundaries, such as at the alpine-treeline ecotone. In addition, while it is known that species respond individualistically to the same suite of environmental drivers, the potential additional effect of local adaptation on seedling success has not been evaluated. Aims: To determine whether local adaptation may influence the position and movement of forest ecosystem boundaries, we quantified conifer seedling recruitment in common gardens across a subalpine forest to alpine tundra gradient at Niwot Ridge, Colorado, USA. Methods: We studied Pinus flexilis and Picea engelmannii grown from seed collected locally at High (3400 m a.s.l.) and Low (3060 m a.s.l.) elevations. We monitored emergence and survival of seeds sown directly into plots and survival of seedlings germinated indoors and transplanted after snowmelt. Results: Emergence and survival through the first growing season was greater for P. flexilis than P. engelmannii and for Low compared with High provenances. Yet survival through the second growing season was similar for both species and provenances. Seedling emergence and survival tended to be greatest in the subalpine forest and lowest in the alpine tundra. Survival was greater for transplants than for field-germinated seedlings. Conclusions: These results suggest that survival through the first few weeks is critical to the establishment of natural germinants. In addition, even small distances between seed sources can have a significant effect on early demographic performance - a factor that has rarely been considered in previous studies of tree recruitment and species range shifts. © 2013 The work of C. Castanha, M.S. Torn, and L.M. Kueppers was conducted at Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. The U.S. Government retains, and the publisher, by accepting the article for publication, acknowledges, that the U.S. Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes. The work of M.J. Germino at the U.S. Geological Survey was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. B. Weibel waives her copyright in the work but not her status as co-author of the work.

We investigated the decomposability of soil organic matter (SOM) along a chronosequence of rainforest sites in Hawaii that form a natural fertility gradient and at two long-term fertilization experiments. To estimate turnover times and pool sizes of organic matter, we used two independent methods: (1) long-term incubations and (2) a three-box soil model constrained by radiocarbon measurements. Turnover times of slow-pool SOM (the intermediate pool between active and passive pools) calculated from incubations ranged from 6 to 20 y in the O horizon and were roughly half as fast in the A horizon. The radiocarbon-based model yielded a similar pattern but slower turnover times. The calculation of the 14C turnover times is sensitive to the lag time between photosynthesis and incorporation of organic C into SOM in a given horizon. By either method, turnover times at the different sites varied two- or threefold in soils with the same climate and vegetation community. Turnover times were fastest at the sites of highest soil fertility and were correlated with litter decay rates and primary productivity. However, experimental fertilization at the two least-fertile sites had only a small and inconsistent effect on turnover, with N slowing turnover and P slightly speeding it at one site. These results support studies of litter decomposition in suggesting that while plant productivity can respond rapidly to nutrient additions, decomposition may respond much more slowly to added nutrients. © 2005 Springer Science+Business Media, Inc.

A large source of uncertainty in present understanding of the global carbon cycle is the distribution and dynamics of the soil organic carbon reservoir. Most of the organic carbon in soils is degraded to inorganic forms slowly) on timescales from centuries to millennia. Soil minerals are known to play a stabilizing role, but how spatial and temporal variation in soil mineralogy controls the quantity and turnover of long-residence-time organic carbon is not well known. Here we use radiocarbon analyses to explore interactions between soil mineralogy and sod organic carbon along two natural gradients-of soil-age and of climate-in volcanic soil environments. During the first ~150,000 years of soil development, the volcanic parent material weathered to metastable, non-crystalline minerals. Thereafter, the amount of non-crystalline minerals declined, and more stable crystalline minerals accumulated. Soil organic carbon content followed a similar trend, accumulating to a maximum after 150,000 years, and then decreasing by 50% over the next four million years. A positive relationship between non- crystalline minerals and organic carbon was also observed in soils through the climate gradient, indicating that the accumulation and subsequent loss of organic matter were largely driven by changes in the millennial scale cycling of mineral-stabilized carbon, rather than by changes in the amount of fast- cycling organic matter or in net primary productivity. Soil mineralogy is therefore important in determining the quantity of organic carbon stored in soil, its turnover time, and atmosphere-ecosystem carbon fluxes during long- term soil development; this conclusion should be generalizable at least to other humid environments.