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USGS2022

Atmospheric river storm flooding influences tidal marsh elevation building processes

Disturbances are a key component of ecological processes in coastal ecosystems. Investigating factors that affect tidal marsh accretion and elevation change is important, largely due to accelerating sea-level rise and the ecological and economic value of wetlands. Sediment accumulation rates, elevation change, and flooding were examined at five marshes along a riverine-tidal gradient in the northern San Francisco Bay-Delta, California, USA during an Atmospheric River storm event in 2017 using Surface Elevation Tables (SETs), feldspar marker horizons (MH), and continuous water-level sensors. Our results showed that localized marsh flooding increased during the storm event, but not evenly across sites. Marsh surface elevation increased the most at the tidal freshwater marsh site in response to the storms, with an average surface elevation gain of 45.6 ± 13.1 mm, and the least at a tidal saline marsh with an average surface elevation gain of 4.0 ± 1.2 mm. A marsh located on the large embayment did not exhibit an immediate response to the storm but had a surface elevation gain of 21.5 ± 13.7 mm 6 months after the storm. During the storm period, marsh distance to the bay was the strongest predictor of elevation change, followed by SET-MH elevations. Conversely, during non-storm periods, SET-MH elevation was a relatively strong predictor of elevation change. Atmospheric Rivers appear to be a major factor affecting short-term spatial and temporal variability in flooding and sedimentation rates in tidal marsh systems. Incorporating information about storms into monitoring could increase our understanding of how episodic storms can impact marshes.

Journal of Geophysical Research: Biogeosciences↗

USGS2022

The importance of lake emergent aquatic vegetation for estimating Arctic-boreal methane emissions

Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under-represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ∼1.5 m deep and can be detected with synthetic aperture radar (SAR). To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR data from the NASA Arctic-Boreal Vulnerability Experiment to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ∼16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50–68]%, 22 [20–25]%, 1.0 [0.8–1.2]%, and 7.0 [5.0–12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18–25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.

Journal of Geophysical Research: Biogeosciences↗

USGS2022

A model of the spatiotemporal dynamics of soil carbon following coastal wetland loss applied to a Louisiana salt marsh in the Mississippi River Deltaic Plain

The potential for carbon sequestration in coastal wetlands is high due to protection of carbon (C) in flooded soils. However, excessive flooding can result in the conversion of the vegetated wetland to open water. This transition results in the loss of wetland habitat in addition to the potential loss of soil carbon. Thus, in areas experiencing rapid wetland submergence, such as the Mississippi River Delta, coastal wetlands could become a significant source of carbon emissions if land loss is not mitigated. To accurately assess the capacity of wetlands to store (or emit) carbon in dynamic environments, it is critical to understand the fate of soil carbon following the transition from vegetated wetland to open water. We developed a simple soil carbon model representing soil depths to 1 m using the data collected from a Louisiana coastal salt marsh in the Mississippi River Deltaic Plain to predict soil carbon density and stock following the transition from a vegetated salt marsh to an open water pond. While immediate effects of ponding on the distribution of carbon within the 1-m soil profile were apparent, there were no effects of ponding on the overall, integrated, carbon stocks 14 years, following wetland submergence. Rather, the model predicts that soil carbon losses in the first meter will be realized over long periods of time (∼200 years) due to changes in the source of carbon (biomass vs. mineral sediment) with minimal losses through mineralization.

Louisiana↗

USGS2022

A process-model perspective on recent changes in the carbon cycle of North America

Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year −1 for the period 2000–2019 (0.31 and 0.44 PgC year −1 in each decade); split into 0.18 ± 0.12 PgC year −1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year −1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (−0.02 ± 0.46 PgC year −1 ). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.

Journal of Geophysical Research Biogeosciences↗

USGS2023

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3 to 7 %) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

California↗

USGS2023

Comparing sediment microbial communities of Arctic beaver ponds to tundra lakes and streams

In recent decades the habitat of North American beaver ( Castor canadensis ) has expanded from boreal forests into Arctic tundra ecosystems. Beaver ponds in Arctic watersheds are known to alter stream biogeochemistry, which is likely coupled with changes in the activity and composition of microbial communities inhabiting beaver pond sediments. We investigated bacterial, archaeal, and fungal communities in beaver pond sediments along tundra streams in northwestern Alaska (AK), USA and compared them to those of tundra lakes and streams in north-central Alaska that are unimpacted by beavers. β -glucosidase activity assays indicated higher cellulose degradation potential in beaver ponds than in unimpacted streams and lakes within a watershed absent of beavers. Beta diversity analyses showed that dominant lineages of bacteria and archaea in beaver ponds differed from those in tundra lakes and streams, but dominant fungal lineages did not differ between these sample types. Beaver pond sediments displayed lower relative abundances of Crenarchaeota and Euryarchaeota archaea and of bacteria from typically anaerobic taxonomic groups, suggesting differences in rates of fermentative organic matter (OM) breakdown, syntrophy, and methane generation. Beaver ponds also displayed low relative abundances of Chytridiomycota (putative non-symbiotic) fungi and high relative abundances of ectomycorrhizal (plant symbionts) Basidiomycota fungi, suggesting differences in the occurrence of plant and fungi mutualistic interactions. Beaver ponds also featured microbes with taxonomic identities typically associated with the cycling of nitrogen and sulfur compounds in higher relative abundances than tundra lakes and streams. These findings help clarify the microbiological implications of beavers expanding into high latitude regions.

Alaska↗

USGS2023

Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.

Mountain headwater streams actively cycle carbon, receiving it from terrestrial landscapes and exporting it through downstream transport and gas exchange with the atmosphere. Although their importance is now widely recognized, aquatic carbon fluxes in headwater streams remain poorly characterized. In this study, aquatic carbon fluxes were measured in 15 mountain headwater streams and were used in a geostatistical analysis to determine how landscape characteristics influence aquatic carbon fluxes. In-stream sensors were used to measure fluorescent dissolved organic matter (fDOM) (a surrogate for dissolved organic carbon (DOC)) at a subset of sites to characterize dynamic responses to hydroclimatic events. Wetlands have a positive influence on aquatic carbon fluxes, whereas perennial snow/ice has the opposite effect, reflecting differences in soil organic matter content in these landscapes. Mean annual temperature (MAT) has a complex influence on DOC, with peak DOC exports in basins with MAT of 0–2°C. Precipitation has a strong positive influence on aquatic carbon fluxes, and declining snowpacks in the western United States may reduce future aquatic carbon exports. fDOM (and by implication DOC) and

Journal of Geophysical Research: Biogeosciences.↗

USGS2024

Spatial, seasonal, and diel controls of nitrogen-carbon-oxygen cycling during lake-water infiltration to an aquifer

Many freshwater lakes are groundwater flow-through systems. Although lakes commonly are considered to be sinks for nitrogen inputs, relatively little is known about carbon and nitrogen export from lakes to groundwater. The current study focused on lake-bottom biogeochemical processes accompanying the transport of nitrogen, dissolved oxygen (O 2 ), and dissolved organic carbon (DOC) during lake-water recharge from a groundwater flow-through lake. Lake-water and porewater (15–100 cm below lakebed) samples were collected along transects within the lake downwelling zone. Infiltrating porewater O 2 and DOC concentrations decreased with depth while nitrate (NO 3 − ) concentrations increased, indicating nitrification of organic matter within the profiles. The depth of NO 3 − production and transport was seasonally dependent. In winter, NO 3 − and O 2 were exported beyond 100-cm depth; whereas in summer, shallow nitrification zones were underlain by deeper NO 3 − reduction zones, and diel patterns of O 2 and NO 3 − penetration depths were observed. Microbial community compositions and stable isotope profiles (δ 15 N[NO 3 − ], δ 18 O[NO 3 − ], δ 18 O[O 2 ]) were consistent with apparent C–N–O reaction stoichiometries indicating O 2 reduction and nitrification in shallower porewater, followed by varying NO 3 − reduction at depth. Maximum porewater NO 3 − concentrations (∼10–20 μM) were limited by infiltrating O 2 concentrations and C/N ratios of reacting organic matter. Lake-water level variations caused changes in shoreline position and porewater velocities, while variations in lake-water temperature, DOC, and O 2 contributed to changes in reaction rates and depth of O 2 and NO 3 − penetration into the lakebed. The quality of groundwater recharged by lake water reflected temporally and spatially varying physical and biogeochemical processes in the sediment porewater.

Journal of Geophysical Research: Biogeosciences↗

USGS2024

Controls on stable methane isotope signatures in northern peatlands and potential shifts in signatures under permafrost thaw scenarios

Northern peatlands are a globally significant source of methane (CH 4 ), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH 4 production in these systems will be key to predicting annual emissions changes, with stable carbon isotopes (δ 13 C-CH 4 ) being a powerful tool for characterizing these drivers. Given that δ 13 C signatures of CH 4 are used in top-down atmospheric inversion models to partition sources, our ability to model CH 4 production pathways and associated δ 13 C-CH 4 signatures in peatland types impacted by a changing climate is critical. We sought to characterize the role of environmental conditions, including both hydrologic and vegetation patterns associated with permafrost thaw, on δ 13 C-CH 4 signatures from a diverse set of high-latitude peatlands. We measured porewater and emitted CH 4 stable isotopes, pH, and vegetation composition from five boreal-Arctic peatlands. Porewater δ 13 C-CH 4 was strongly associated with peatland type, with δ 13 C enriched values obtained from more minerotrophic fens (-61.2 ± 9.1‰) compared to permafrost-free bogs (-74.1 ± 9.4‰) and raised permafrost bogs (-81.6 ± 11.5‰). Variation in porewater δ 13 C-CH 4 was best explained by sedge cover, CH 4 concentration, and the interactive effect of peatland type and pH ( r 2 = 0.50, p < 0.001). Emitted δ 13 C-CH 4 varied greatly but was positively correlated with porewater δ 13 C-CH 4 , suggesting that porewater data can be used to predict changing emissions signatures from these systems. We calculated a weighted mean mixed atmospheric CH 4 signature for northern peatlands of -65.3 ± 7‰ and show that this signature is more sensitive to landscape drying (4 to 10 % depletion in δ 13 C) than wetting (1.5 to 5% enrichment in δ 13 C) under permafrost thaw scenarios. Our results suggest northern peatland δ 13 C-CH 4 signatures are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Journal of Geophysical Research: Biogeosciences↗

USGS2025

Quantifying the effect of petrogenic carbon on SOC turnover for two Rocky Mountain soils: When are petrogenic carbon corrections required?

Petrogenic organic carbon (OC petro ), derived from sedimentary rocks, is an often overlooked and poorly quantified source of soil organic carbon (SOC), which may influence measured or modeled SOC composition, age, and stability. In this study, we exploited differences in thermochemical stability between OC petro and biogenic SOC (OC bio ) using stepped elemental analysis to quantify the fractional contribution of OC petro to total SOC (f petro ), and we conducted a sensitivity analysis to estimate the effects of OC petro on modeled SOC transit times and system ages. Specifically, we compared the effects of accounting for OC petro inputs in SOC turnover modeling (using SoilR) for two montane meadow soils that are underlain by Cretaceous Mancos Shale. At these sites, we estimate that OC petro comprises 7%–9% of the total SOC stock (f petro = 0.07–0.09). However, accounting for OC petro as a mixture of inert and passive C or as completely inert C had negligible effects on SOC transit times and system ages, suggesting that there is a threshold of OC petro content under which there is minimal effect on calculated SOC turnover. Based on our sensitivity analysis, we estimate this threshold to be f petro = 0.125, further supporting that the accurate calculation of OC petro remains an important factor in estimating SOC turnover.

Colorado↗

USGS2024

Responses of marginal and intrinsic water-use efficiency to changing aridity using FLUXNET observations

According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water-use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non-linear mWUE-VPD relationship at a sub-daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid-range of VPD. Despite the highly non-linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem-level inherent water-use efficiency (IWUE) and mWUE using the slope, m *. We further identify site-specific m * and its variability with changing site-level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

Journal of Geophysical Research Biogeosciences↗

USGS2024

A semi-mechanistic model for partitioning evapotranspiration reveals transpiration dominates the water flux in drylands

Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well-suited to dryland ecosystems, such as high sensitivity of plant water-use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine-scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi-mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process-based models, and loosely constrains time-varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross-wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub-yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem-scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

New Mexico↗

USGS2024

Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

Biological soil crusts (biocrusts) are widespread soil photosynthetic communities covering about 12% of Earth's land surface and play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable quantifications of biocrusts and their biogeochemical contributions are notably lacking. While remote sensing has enormous potential to assess, scale, and contextualize biocrusts and their functions, the applicability of hyperspectral data in predicting C- and N-related biocrust traits remains largely unexplored. We address this issue by evaluating the potential of in situ hyperspectral data to predict C and N across a range of biocrust species and different environmental conditions. We found that in situ hyperspectral reflectance measurements can be used to predict biocrust tissue C/N ratios and N concentrations with relatively high accuracy but to a lesser extent for potential biocrust N2 fixation rates. Critical wavelength domains included the visible region of the spectrum from roughly 490–600 nm, which most effectively captured variations in biocrust tissue C, and the shortwave infrared region from 1,150 to 1,350 nm and 1,550–1,650 nm, which most effectively captured biocrust tissue N and N2 fixation potential. Finally, we provide evidence that multi- and hyperspectral missions with targeted band placement, such as the proposed 26-band Landsat Next, could be effective in predicting biocrust traits. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts.

Utah↗

USGS2024

Climate, hydrology, and nutrients control the seasonality of Si concentrations in rivers

The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termed DSi regime , mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large-scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi.

Journal of Geophysical Research Biogeosciences↗

USGS2024

Longitudinal and seasonal changes of organic matter sources through a semi-arid river-reservoir system

The quality and quantity of organic matter (OM) in a river system directly affects ecosystem health; thus, managers benefit from an in-depth understanding of the drivers and sources of OM. In the Snake River, a highly altered river-reservoir system in the semi-arid western United States, OM production and loading are key drivers of reservoir anoxia, which leads to several deleterious processes such as mercury methylation. However, sources and quantities of OM to the Snake River, and the effects of impoundment on OM moving through the river-reservoir system, are not well understood. Particulate organic carbon (POC), dissolved organic carbon (DOC), particulate nitrogen (PN), chlorophyll a (chl- a ), and δ 15 N–PN and δ 13 C–POC isotopic ratios were measured bi-weekly for over 2 years at four locations through the Snake River Hells Canyon Reservoir Complex to determine spatial and temporal patterns of OM quantities and sources. POC concentrations increased through the riverine zone upstream of the reservoirs, likely due to in situ primary production and/or inputs from tributaries and agricultural drains; then decreased through the most upstream reservoir likely due to particle settling. Isotopic ratios and other OM source indicators (δ 15 N–PN, δ 13 C–POC, POC:PN, chl- a :POC) show that the dominant source of particulate OM was phytoplankton with seasonal terrestrial/macrophytic inputs. Results highlight the effects of major tributary and agricultural drain inputs, primary production, and impoundment on OM composition and concentration through a large river-reservoir system and may inform water quality management efforts in this and similar systems.

Idaho, Oregon↗

USGS2014

An empirical approach to modeling methylmercury concentrations in an Adirondack stream watershed

Inverse empirical models can inform and improve more complex process-based models by quantifying the principal factors that control water quality variation. Here we developed a multiple regression model that explains 81% of the variation in filtered methylmercury (FMeHg) concentrations in Fishing Brook, a fourth-order stream in the Adirondack Mountains, New York, a known “hot spot” of Hg bioaccumulation. This model builds on previous observations that wetland-dominated riparian areas are the principal source of MeHg to this stream and were based on 43 samples collected during a 33 month period in 2007–2009. Explanatory variables include those that represent the effects of water temperature, streamflow, and modeled riparian water table depth on seasonal and annual patterns of FMeHg concentrations. An additional variable represents the effects of an upstream pond on decreasing FMeHg concentrations. Model results suggest that temperature-driven effects on net Hg methylation rates are the principal control on annual FMeHg concentration patterns. Additionally, streamflow dilutes FMeHg concentrations during the cold dormant season. The model further indicates that depth and persistence of the riparian water table as simulated by TOPMODEL are dominant controls on FMeHg concentration patterns during the warm growing season, especially evident when concentrations during the dry summer of 2007 were less than half of those in the wetter summers of 2008 and 2009. This modeling approach may help identify the principal factors that control variation in surface water FMeHg concentrations in other settings, which can guide the appropriate application of process-based models.

New York↗

USGS2014

Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models

Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long-term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one- and two-horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO 2 efflux from trenched plots in a Dahurian larch ( Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO 2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long-term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short-term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long-term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long-term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.

Journal of Geophysical Research G: Biogeosciences↗

USGS2015

Source limitation of carbon gas emissions in high-elevation mountain streams and lakes

Inland waters are an important component of the global carbon cycle through transport, storage, and direct emissions of CO 2 and CH 4 to the atmosphere. Despite predictions of high physical gas exchange rates due to turbulent flows and ubiquitous supersaturation of CO 2 —and perhaps also CH 4 —patterns of gas emissions are essentially undocumented for high mountain ecosystems. Much like other headwater networks around the globe, we found that high-elevation streams in Rocky Mountain National Park, USA, were supersaturated with CO 2 during the growing season and were net sources to the atmosphere. CO 2 concentrations in lakes, on the other hand, tended to be less than atmospheric equilibrium during the open water season. CO 2 and CH 4 emissions from the aquatic conduit were relatively small compared to many parts of the globe. Irrespective of the physical template for high gas exchange (high k ), we found evidence of CO 2 source limitation to mountain streams during the growing season, which limits overall CO 2 emissions. Our results suggest a reduced importance of aquatic ecosystems for carbon cycling in high-elevation landscapes having limited soil development and high CO 2 consumption via mineral weathering.

Journal of Geophysical Research G: Biogeosciences↗