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The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and R S are irreconcilable. When we estimate GPP based on R S measurements and some assumptions about R S :GPP ratios, we found the resulted global GPP values (bootstrap mean [Formula: see text] Pg C yr -1 ) are significantly higher than most GPP estimates reported in the literature ([Formula: see text] Pg C yr -1 ). Similarly, historical GPP estimates imply a soil respiration flux (Rs GPP , bootstrap mean of [Formula: see text] Pg C yr -1 ) statistically inconsistent with most published R S values ([Formula: see text] Pg C yr -1 ), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global R S :GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget., (© 2022. The Author(s).)

Tree stems from wetland, floodplain and upland forests can produce and emit methane (CH 4 ). Tree CH 4 stem emissions have high spatial and temporal variability, but there is no consensus on the biophysical mechanisms that drive stem CH 4 production and emissions. Here, we summarize up to 30 opportunities and challenges for stem CH 4 emissions research, which, when addressed, will improve estimates of the magnitudes, patterns and drivers of CH 4 emissions and trace their potential origin. We identified the need: (1) for both long-term, high-frequency measurements of stem CH 4 emissions to understand the fine-scale processes, alongside rapid large-scale measurements designed to understand the variability across individuals, species and ecosystems; (2) to identify microorganisms and biogeochemical pathways associated with CH 4 production; and (3) to develop a mechanistic model including passive and active transport of CH 4 from the soil-tree-atmosphere continuum. Addressing these challenges will help to constrain the magnitudes and patterns of CH 4 emissions, and allow for the integration of pathways and mechanisms of CH 4 production and emissions into process-based models. These advances will facilitate the upscaling of stem CH 4 emissions to the ecosystem level and quantify the role of stem CH 4 emissions for the local to global CH 4 budget., (© 2018 No claim to original US government works New Phytologist © 2018 New Phytologist Trust.)

Global modeling efforts indicate semiarid regions dominate the increasing trend and interannual variation of net CO2 exchange with the atmosphere, mainly driven by water availability. Many semiarid regions are expected to undergo climatic drying, but the impacts on net CO2 exchange are poorly understood due to limited semiarid flux observations. Here we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (photosynthesis and respiration), precipitation, and evapotranspiration (ET) in 21 semiarid North American ecosystems with an observed range of 100 - 1000 mm in annual precipitation and records of 4-9 years each. In addition to evaluating spatial relationships among CO2 and water fluxes across sites, we separately quantified site-level temporal relationships, representing sensitivity to interannual variation. Across the climatic and ecological gradient, photosynthesis showed a saturating spatial relationship to precipitation, whereas the photosynthesis-ET relationship was linear, suggesting ET was a better proxy for water available to drive CO2 exchanges after hydrologic losses. Both photosynthesis and respiration showed similar site-level sensitivity to interannual changes in ET among the 21 ecosystems. Furthermore, these temporal relationships were not different from the spatial relationships of long-term mean CO2 exchanges with climatic ET. Consequently, a hypothetical 100-mm change in ET, whether short term or long term, was predicted to alter net ecosystem production (NEP) by 64 gCm(-2) yr(-1). Most of the unexplained NEP variability was related to persistent, site-specific function, suggesting prioritization of research on slow-changing controls. Common temporal and spatial sensitivity to water availability increases our confidence that site-level responses to interannual weather can be extrapolated for prediction of CO2 exchanges over decadal and longer timescales relevant to societal response to climate change., (© 2016 John Wiley & Sons Ltd.)

Forest ecosystems can act as sinks of carbon and thus mitigate anthropogenic carbon emissions. When forests are actively managed, treatments can alter forests carbon dynamics, reducing their sink strength and switching them from sinks to sources of carbon. These effects are generally characterized by fast temporal dynamics. Hence this study monitored for over a decade the impacts of management practices commonly used to reduce fire hazards on the carbon dynamics of mixed-conifer forests in the Sierra Nevada, California, USA. Soil CO2 efflux, carbon pools (i.e. soil carbon, litter, fine roots, tree biomass), and radial tree growth were compared among un-manipulated controls, prescribed fire, thinning, thinning followed by fire, and two clear-cut harvested sites. Soil CO2 efflux was reduced by both fire and harvesting (ca. 15%). Soil carbon content (upper 15 cm) was not significantly changed by harvest or fire treatments. Fine root biomass was reduced by clear-cut harvest (60-70%) but not by fire, and the litter layer was reduced 80% by clear-cut harvest and 40% by fire. Thinning effects on tree growth and biomass were concentrated in the first year after treatments, whereas fire effects persisted over the seven-year post-treatment period. Over this period, tree radial growth was increased (25%) by thinning and reduced (12%) by fire. After seven years, tree biomass returned to pre-treatment levels in both fire and thinning treatments; however, biomass and productivity decreased 30%-40% compared to controls when thinning was combined with fire. The clear-cut treatment had the strongest impact, reducing ecosystem carbon stocks and delaying the capacity for carbon uptake. We conclude that post-treatment carbon dynamics and ecosystem recovery time varied with intensity and type of treatments. Consequently, management practices can be selected to minimize ecosystem carbon losses while increasing future carbon uptake, resilience to high severity fire, and climate related stresses.

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Soil respiration (Rs), the soil‐to‐atmosphere flux of CO2, is a dominant but uncertain part of the carbon cycle, even after decades of study. This review focuses on progress in understanding Rs from laboratory incubations to global estimates. We survey key developments of in situ ecosystem‐scale Rs observations and manipulations, synthesize Rs meta‐analyses and global flux estimates, and discuss the most compelling challenges and opportunities for the future. Increasingly sophisticated lab experiments have yielded insights into the interaction among heterotrophic respiration, substrate supply, and enzymatic kinetics, and extended incubation‐based analyses across space and time. Observational and manipulative field‐based experiments have used improved measurement approaches to deepen our understanding of the integrated effects of environmental change and disturbance on Rs. Freely‐available observational databases have enabled meta‐analyses and studies probing the magnitude of, and constraints on, the global Rs flux. Key challenges for the field include expanding Rs measurements, experiments, and opportunities to under‐represented communities and ecosystems; reconciling independent estimates of global respiration fluxes and trends; testing and leveraging the power of machine learning and process‐based models, both independently and in conjunction with each other; and continuing the field's tradition of using novel experiments to explore diverse mechanisms and ecosystems. Plain Language Summary: "Soil respiration" refers to the flow of carbon dioxide, mostly generated by plant roots and microbes, from the soil to the atmosphere. This flux is large and highly uncertain, and understanding it has significant implications for our ability to predict the effects of land use and climate change. This review summarizes advances, insights, and challenges in soil respiration science. It examines laboratory approaches and findings; documents changes in how researchers measure and understand soil respiration in the natural world; and describes efforts to estimate the global dynamics of soil respiration from openly‐available databases of observations. We conclude by discussing the most compelling challenges and opportunities for the future. Key Points: Recent decades have seen large advances in measurement methods, experimental approaches, and data availability in soil respiration scienceLab and field‐based experiments have improved our understanding of the integrated effect of environmental change on soil respirationKey challenges include broadening access and continuing to explore diverse mechanisms and ecosystems using novel model‐experiment approaches [ABSTRACT FROM AUTHOR]

Tidal channels are biogeochemical hotspots that horizontally exchange carbon (C) with marsh platforms, but the physiochemical drivers controlling these dynamics are poorly understood. We hypothesized that C‐bearing iron (Fe) oxides precipitate and immobilize dissolved organic carbon (DOC) during ebb tide as the soils oxygenate, and dissolve into the porewater during flood tide, promoting transport to the channel. The hydraulic gradient physically controls how these solutes are horizontally exchanged across the marsh platform‐tidal channel interface; we hypothesized that this gradient alters the concentration and source of C being exchanged. We further hypothesized that trace soil gases (i.e., CO2, CH4, dimethyl sulfide) are pushed out of the channel bank as the groundwater rises. To test these hypotheses, we measured porewater, surface water, and soil trace gases over two 24‐hr monitoring campaigns (i.e., summer and spring) in a mesohaline tidal marsh. We found that Fe2+ and DOC were positively related during flood tide but not during ebb tide in spring when soils were more oxidized. This finding shows evidence for the formation and dissolution of C‐bearing Fe oxides across a tidal cycle. In addition, the tidal channel contained significantly (p < 0.05) more terrestrial‐like DOC when the hydraulic gradient was driving flow toward the channel. In comparison, the channel water was saltier and contained significantly (p < 0.05) more marine‐like DOC when the hydraulic gradient reversed direction. Trace gas fluxes increased with rising groundwater levels, particularly dimethyl sulfide. These findings suggest multiple physiochemical mechanisms controlling the horizontal exchange of C at the marsh platform‐tidal channel interface. Plain Language Summary: Tidal salt marshes store large amounts of carbon belowground in soils, but there is also a significant amount of carbon flowing into and out of these ecosystems via tidal channels. We investigated the carbon flowing between the channel bank and surface water in a salt marsh in Delaware. We found that soil minerals (i.e., iron oxides) control the mobility of carbon as iron oxides retain carbon during ebb tides and release carbon during flood tides as the minerals dissolve. The gradient between the groundwater and surface water elevation (i.e., hydraulic gradient) controls the flow direction for dissolved carbon, altering the concentration and source of carbon found in the tidal channel across tidal cycles. In addition, gases trapped in channel banks are pushed out of the soils as the tide rises. These findings will improve our understanding of carbon cycles in these critical carbon sinks. Key Points: Physiochemical mechanisms control horizontal exchange of carbon across marsh‐tidal channel interfaces, affecting lateral carbon fluxDissolution and reprecipitation of carbon‐bearing Fe oxides during flood and ebb tides control the horizontal mobility of carbonHydraulic gradients control the carbon character in the tidal channel, and rising tides push greenhouse gases out of the channel bank [ABSTRACT FROM AUTHOR]

The exchange of multiple greenhouse gases (i.e., CO2 and CH4) between tree stems and the atmosphere represents a knowledge gap in the global carbon cycle. Stem CO2 and CH4 fluxes vary across time and space and are unclear, which are their individual or shared drivers. Here we measured CO2 and CH4 fluxes at different stem heights combining manual (biweekly; n = 678) and automated (hourly; n > 38,000) measurements in a temperate upland forest. All trees showed CO2 and CH4 emissions despite 20% of measurements showing net CH4 uptake. Stem CO2 fluxes presented clear seasonal trends from manual and automated measurements. Only automated measurements captured the high temporal variability of stem CH4 fluxes revealing clear seasonal trends. Despite that temporal integration, the limited number of automated chambers made stand‐level mean CH4 fluxes sensitive to "hot spots," resulting in mean fluxes with high uncertainty. Manual measurements provided better integration of spatial variability, but their lack of temporal variability integration hindered the detection of temporal trends and stand‐level mean fluxes. These results highlight the potential bias of previous studies of stem CH4 fluxes solely based on manual or automated measurements. Stem height, temperature, and soil moisture only explained 7% and 11% of the stem CH4 flux variability compared to 42% and 81% for CO2 (manual and automated measurements, respectively). This large unexplained variability, in combination with high CH4 concentrations in the trees' heartwood, suggests that stem CH4 fluxes might be more influenced by gas transport and diffusivity through the wood than by drivers of respiratory CO2 flux, which has crucial implications for developing process‐based ecosystem models. We postulate that CH4 is likely originated within tree stems because of lack of a consistent vertical pattern in CH4 fluxes, evidence of CH4 production in wood incubations, and low CH4 concentration in the soil profile but high concentrations within the trees' heartwood. [ABSTRACT FROM AUTHOR]

Soil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The global soil respiration database (SRDB) is a compilation of in situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions has produced better‐constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n = 5173 and v5.0 n = 10,366) to determine how additional data influenced global Rs annual sum, spatial patterns and associated uncertainty (1 km spatial resolution) using a machine learning approach. A quantile regression forest model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C year−1, and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C year−1, whereas parameterization using SRDBv5 yielded 96.5 Pg C year−1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C year−1. Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9–50.2 (mean 50.1) and 53.3–53.5 (mean 53.4) Pg C year−1, respectively. SRDBv5's inclusion of new data from underrepresented regions (e.g., Asia, Africa, South America) resulted in overall higher model uncertainty. The largest differences between models parameterized with different SRDVB versions were in arid/semi‐arid regions. The SRDBv5 is still biased toward northern latitudes and temperate zones, so we tested an optimized global distribution of Rs measurements, which resulted in a global sum of 96.4 ± 21.4 Pg C year−1 with an overall lower model uncertainty. These results support current global estimates of Rs but highlight spatial biases that influence model parameterization and interpretation and provide insights for design of environmental networks to improve global‐scale Rs estimates. [ABSTRACT FROM AUTHOR]

Field-measured soil respiration (RS , the soil-to-atmosphere CO2 flux) observations were compiled into a global soil respiration database (SRDB) a decade ago, a resource that has been widely used by the biogeochemistry community to advance our understanding of RS dynamics. Novel carbon cycle science questions require updated and augmented global information with better interoperability among datasets. Here, we restructured and updated the global RS database to version SRDB-V5. The updated version has all previous fields revised for consistency and simplicity, and it has several new fields to include ancillary information (e.g., RS measurement time, collar insertion depth, collar area). The new SRDB-V5 includes published papers through 2017 (800 independent studies), where total observations increased from 6633 in SRDB-V4 to 10 366 in SRDB-V5. The SRDB-V5 features more RS data published in the Russian and Chinese scientific literature and has an improved global spatio-temporal coverage and improved global climate space representation. We also restructured the database so that it has stronger interoperability with other datasets related to carbon cycle science. For instance, linking SRDB-V5 with an hourly timescale global soil respiration database (HGRsD) and a community database for continuous soil respiration (COSORE) enables researchers to explore new questions. The updated SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field RS measurements, and it provides opportunities for the biogeochemistry community to better understand the spatial and temporal variability in RS , its components, and the overall carbon cycle. The database can be downloaded at https://github.com/bpbond/srdb and will be made available in the Oak Ridge National Laboratory's Distributed Active Archive Center (ORNL DAAC). All data and code to reproduce the results in this study can be found at 10.5281/zenodo.3876443 (Jian and Bond-Lamberty, 2020). [ABSTRACT FROM AUTHOR]

Environmental observatory networks (EONs) provide information to understand and forecast the spatial and temporal dynamics of Earth's biophysical processes. Consequently, representativeness analyses are important to provide insights for improving EONs' management, design, and interpretation of their value‐added products. We assessed the representativeness of registered FLUXNET sites (n = 41, revised on September 2018) across Latin America (LA), a region of great importance for the global carbon and water cycles, which represents 13% of the world's land surface. Nearly 46% of registered FLUXNET sites are located in evergreen broad‐leaf forests followed by sites in woody savannas (∼20%). Representativeness analyses were performed using a 0.05° spatial grid for multiple environmental variables, gross primary productivity (GPP), and evapotranspiration (ET). Our results showed a potential representativeness of 34% of the surface area for climate properties, 36% for terrain parameters, 34% for soil resources, and 45% when all aforementioned environmental variables were summarized into a principal component analysis. Furthermore, there was a 48% potential representativeness for GPP and 34% for ET. Unfortunately, data from these 41 sites are not all readily available for the scientific community, limiting synthesis studies and model benchmarking/parametrization. The implication is that global/regional data‐driven products are forced to use information from FLUXNET sites outside LA to predict patterns in LA. Representativeness could increase to 86% (for GPP) and 80% (for ET) if 200 sites are optimally distributed. We discussed ongoing challenges, the need to enhance interoperability and data sharing, and promote monitoring efforts across LA to increase the accuracy of regional‐to‐global data‐driven products. Plain Language Summary: Environmental observatory networks (EONs) provide information to better understand, model, and forecast the spatial and temporal dynamics of Earth's biophysical processes. Consequently, representativeness analyses of EON's are important to provide insights for improving EONs' management, design, and interpretation of their value‐added products (e.g., datasets, model predictions). We assessed the representativeness of registered FLUXNET sites (n = 41, revised on September 2018) across Latin America (LA), a region of great importance for the global carbon and water cycles, which represents nearly 13% of the world's land surface area. Representativeness analyses were performed using multiple environmental variables, gross primary productivity (GPP), and evapotranspiration (ET) across LA. Our results showed potential spatial representativeness of 34% of the surface area for climate properties, 36% for terrain parameters, 34% for soil resources, and 45% when all aforementioned environmental variables were summarized. Furthermore, there was a 48% potential representativeness for GPP and 34% for ET. Our results represent a best‐case scenario because data from these 41 sites is not all readily available for the scientific community. We discussed the need to enhance collaboration, promote the participation of active/inactive sites to share information with local, regional and international networks, and promote monitoring efforts across this region of the world. Key Points: There is a need to promote data sharing and improve the representativeness of environmental networks across Latin AmericaCurrently, 48% of gross primary productivity and 34% of evapotranspiration patterns are represented by FLUXNET sitesData‐driven products are forced to use information outside Latin America to predict patterns within this region [ABSTRACT FROM AUTHOR]

A data-driven method is presented for improving sampling designs from times series (1D approach) or spatial arrays (2D approach) of digital information. We present the autocorrelated conditioned Latin Hypercube Sampling (acLHS). This method combines a conditioned Latin Hypercube (cLHS) to obtain a representative sample of the joint probability distribution function and an autocorrelation model to reproduce the spatial or temporal dependency function (i.e., temporal or spatial variability). The acLHS method was tested with two case studies using data of soil CO 2 efflux (i.e., the CO 2 flux from soils to the atmosphere known as soil respiration) that are useful for carbon cycle science. First, we used data representing a time series (1D approach), and then spatial data (2D approach) across the conterminous United States (CONUS). Results show that acLHS was more efficient than other sampling methods (i.e., fixed sampling, cLHS) as it better reproduced the joint probability distribution and the temporal or spatial variability of the variable of interest. Finally, we use a Bernstein copula-based stochastic co-simulation method (BCSCS) and demonstrated that the acLHS reduces modeling prediction errors compared with other methods. The acLHS is a flexible method that can be applied to any variable of interest as a time series (1D approach) or as a spatial format (2D approach). • A geostatistical sampling method to improve representativeness of samples. • Implementation works for time series (1D) and spatial information (2D). • The method improves accuracy and precision for prediction purposes. [ABSTRACT FROM AUTHOR]

Tropical dry forests (TDF) are one of the most widely distributed tropical land‐cover types in Mexico, but their regional‐to‐global contribution to the carbon and water cycles is still highly uncertain. We measured CO2 and water vapor fluxes between the ecosystem and atmosphere using the eddy covariance technique from 2016 to 2018 in an old‐growth TDF in northwestern Mexico. First, we investigated the magnitude and seasonality of evapotranspiration (ET), net ecosystem production (NEP) and its contributing fluxes, gross ecosystem production (GEP), and ecosystem respiration (Reco). Second, we explored the main environmental factors controlling carbon and water fluxes as well as tested if this ecosystem acted as a net carbon source or sink. During the study period, all precipitation entering the ecosystem went back to the atmosphere through ET (738.9 ±58.26 mm y−1). Ecosystem respiration (2203.16 ±244.2 g C m−2 y−1) was consistently larger than GEP (1975.32 ±295.52 g C m−2 y−1), determining an annual NEP (−227.6 ±59.4 g C m−2 y−1) that resulted in net annual carbon losses. This forest maintained its water use efficiency (WUE; GEP/ET) across years (2.53–3.24), but water availability constrained light use and maximum carbon assimilation rates. Our results render relevance to the feedback between soil water content and net radiation as the main environmental variables controlling ecosystem fluxes in this old‐growth TDF. Resumen: El bosque tropical seco (BTS) es una de las coberturas terrestres más ampliamente distribuidas en México, pero su contribución regional y global a los ciclos del carbono y del agua es aún muy incierta. Medimos los flujos de CO2 y vapor de agua entre el ecosistema y la atmósfera utilizando la técnica de covarianza de vórtices entre 2016 y 2018 en un BTS maduro en el noroeste de México. Primero, investigamos la magnitud y la estacionalidad de la evapotranspiración (ET), la producción neta del ecosistema (NEP) y sus flujos contribuyentes, la producción bruta del ecosistema (GEP) y la respiración del ecosistema (Reco). En segundo lugar, exploramos los principales factores ambientales que controlan los flujos de carbono y de agua, y probamos si este ecosistema actuó como fuente o sumidero neto de carbono. Durante el período de estudio, la precipitación que recibió el ecosistema regresó a la atmósfera a través de ET (738.9 ± 58.26 mm y−1). La respiración del ecosistema (2203.16 ± 244.2 g C m−2 y−1) fue consistentemente mayor que la GEP (1,975.32 ± 295.52 g C m−2 y‐1), determinando una NEP anual (−227.6 ± 59.4 g C m−2 y−1) que resultó en pérdidas netas anuales de carbono. Este bosque mantuvo su eficiencia en el uso del agua (WUE; GEP / ET) a lo largo de los años (2.53–3.24), pero la disponibilidad de agua restringió el uso de la luz y las tasas máximas de asimilación de carbono. Nuestros resultados dan relevancia a la retroalimentación entre el contenido de agua del suelo y la radiación neta como las principales variables ambientales que controlan los flujos del ecosistema en este bosque tropical seco maduro. Plain Language Summary: The contribution of tropical forests to the carbon and water cycles is still uncertain. This is especially true for tropical dry forests with high rainfall seasonality and light availability that may affect their carbon sequestration potential. In this study, we report the results of continuous measurements over a 3 year period of carbon and water fluxes between the atmosphere and a tropical dry forest ecosystem in northwestern Mexico using the eddy covariance technique. We found that the studied old‐growth forest was a net carbon source to the atmosphere across years. This result can be explained by ecosystem respiration (the sum of plant and microbial respiration) since it was constantly larger than the gross ecosystem production (or whole‐ecosystem photosynthesis). The main drivers of carbon and water fluxes were soil water content and net solar radiation, but the relative effect of net solar radiation was strongly dependent on soil moisture. In addition to demonstrating the importance of water and light for controlling whole‐ecosystem processes in seasonally dry tropical forests, our results suggest old‐growth tropical forests with little disturbance can act as carbon sources to the atmosphere. Therefore, further studies should investigate ecosystem fluxes in forests under different disturbance or successional stages. Key Points: An old‐growth tropical dry forest was a net carbon source regardless of precipitation variabilityCarbon and water fluxes were highly seasonal and varied interannuallyMain drivers of carbon and water fluxes were soil water content and net solar radiation [ABSTRACT FROM AUTHOR]

Background: An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (R) data has not kept pace. Scope: We identify three major challenges in interpreting R data, and opportunities to utilize it more extensively and creatively: (1) When R is compared to ecosystem respiration (R) measured from EC towers, it is not uncommon to find R > R. We argue this is most likely due to difficulties in calculating R, which provides an opportunity to utilize R for EC quality control. (2) R integrates belowground heterotrophic and autotrophic activity, but many models include only an explicit heterotrophic output. Opportunities exist to use the total R flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. (3) R is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Downscaling EC fluxes to match the scale of R, and improvement of R upscaling techniques will improve resolution challenges. Conclusions: R data can bring a range of benefits to model development, particularly with larger databases and improved data sharing protocols to make R data more robust and broadly available to the research community. [ABSTRACT FROM AUTHOR]

Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental plots. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step to improve this situation would be the development of 'Decomposition Functional Types' (DFTs). Analogous to plant functional types (PFTs), DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent and independent variables that could be used. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities: collection and synthesis of existing data; more in-depth analyses combining open data with rigorous testing of analytical results; using point measurements and realistic forcing variables to constrain process-based models; and planning by the global modeling community for decoupling decomposition from fixed site data. These are all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR. [ABSTRACT FROM AUTHOR]

Abstract: Solutions to current global environmental problems throughout fundamental ecological understandings are only reached through international programmatic and scientific collaborations. Both scientists and policymakers recognize the importance of the role of carbon cycle science (CCS) in North America, however regional ecological studies in North America often do not include the role of Mexico. Given the sharp ecological, climatic and socioeconomic differences among the three countries conforming North America it is fundamental to incorporate Mexico''s unique contributions toward regional CCS. We provide a synthesis of opportunities and challenges for advancing land and ocean research in Mexico in order to move toward a complete North American continental scale CCS. First, we provide the socio-ecological context of Mexico relevant to CCS. Second, we compare the existing relationships among scientific/governmental entities and funding agencies that contribute to CCS in the United States and Mexico. Third, we discuss Mexico''s state-of-the-art CCS, and synthesize its recent advances with emphasis on land– and ocean–atmosphere interactions. We highlight continental-scale opportunities toward a tri-national carbon research, infrastructure, and education network. [Copyright &y& Elsevier]

Summary [ABSTRACT FROM AUTHOR]

Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water-limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20 mm rain event each month, and (3) ambient rain plus four 5 mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content ( θ), soil respiration ( R), along with leaf-level photosynthesis ( A), predawn leaf water potential (Ψ), and seasonal aboveground net primary productivity (ANPP) of the dominant C grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil θ which corresponded with a significant increase in R and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle. [ABSTRACT FROM AUTHOR]

Soil respiration, the flux of CO from the soil to the atmosphere represents a major flux in the global carbon cycle. Our ability to predict this flux remains limited because of multiple controlling mechanisms that interact over different temporal and spatial scales. However, new advances in measurement and analyses present an opportunity for the scientific community to improve the understanding of the mechanisms that regulate soil respiration. In this paper, we address several recent advancements in soil respiration research from experimental measurements and data analysis to new considerations for model-data integration. We focus on the links between the soil-plant-atmosphere continuum at short (i.e., diel) and medium (i.e., seasonal-years) temporal scales. First, we bring attention to the importance of identifying sources of soil CO production and highlight the application of automated soil respiration measurements and isotope approaches. Second, we discuss the need of quality assurance and quality control for applications in time series analysis. Third, we review perspectives about emergent ideas for modeling development and model-data integration for soil respiration research. Finally, we call for stronger interactions between modelers and experimentalists as a way to improve our understanding of soil respiration and overall terrestrial carbon cycling. [ABSTRACT FROM AUTHOR]

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to evaluate the plausibility of four different conceptual models. Phenological indicators were derived from the eddy covariance time series, and from remote sensing and models. We examine spatial patterns (across sites) and temporal patterns (across years); an important conclusion is that it is likely that neither of these accurately represents how productivity will respond to future phenological shifts resulting from ongoing climate change. In spring and autumn, increased GEP resulting from an 'extra' day tends to be offset by concurrent, but smaller, increases in ecosystem respiration, and thus the effect on NEP is still positive. Spring productivity anomalies appear to have carry-over effects that translate to productivity anomalies in the following autumn, but it is not clear that these result directly from phenological anomalies. Finally, the productivity of evergreen needleleaf forests is less sensitive to phenology than is productivity of deciduous broadleaf forests. This has implications for how climate change may drive shifts in competition within mixed-species stands. [ABSTRACT FROM AUTHOR]

Soils play a critical role in the global carbon cycle, yet the biophysical factors regulating soil CO2 dynamics remain unclear. We combined high-frequency in situ observations of fine roots and ectomycorrhizal (EM) fungi with data from multiple soil sensor arrays to examine the biophysical interactions influencing soil CO2 production for one year in a mixed conifer forest. Using structural equation modeling we constructed a hypothesized model to test for causal interactions among environmental factors, biotic factors, and soil CO2 dynamics throughout the soil profile. According to our model, seasonal variation in CO2 production was significantly influenced by EM rhizomorph production, soil temperature, and soil moisture. Fine root production, on the other hand, did not appear to significantly influence soil CO2 production. The relationship between EM rhizomorph production and soil CO2 production was also supported by a zero temporal lag between these two measurements in a cross-correlation analysis. In contrast, CO2 production increased before fine root production suggesting that these two measurements were decoupled in time. Results from this study highlight the need to better understand differences in carbon allocation between plant roots and EM fungi to improve our predictions of soil carbon dynamics under global climate change. [ABSTRACT FROM AUTHOR]

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Soil moisture plays a key role in the Earth's water and carbon cycles, but acquisition of continuous (i.e., gap-free) soil moisture measurements across large regions is a challenging task due to limitations of currently available point measurements. Satellites offer critical information for soil moisture over large areas on a regular basis (e.g., European Space Agency Climate Change Initiative (ESA CCI), National Aeronautics and Space Administration Soil Moisture Active Passive (NASA SMAP)); however, there are regions where satellite-derived soil moisture cannot be estimated because of certain conditions such as high canopy density, frozen soil, or extremely dry soil. We compared and tested three approaches, ordinary kriging (OK), regression kriging (RK), and generalized linear models (GLMs), to model soil moisture and fill spatial data gaps from the ESA CCI product version 4.5 from January 2000 to September 2012, over a region of 465,777 km2 across the Midwest of the USA. We tested our proposed methods to fill gaps in the original ESA CCI product and two data subsets, removing 25% and 50% of the initially available valid pixels. We found a significant correlation (r = 0.558, RMSE = 0.069 m3m−3) between the original satellite-derived soil moisture product with ground-truth data from the North American Soil Moisture Database (NASMD). Predicted soil moisture using OK also had significant correlation with NASMD data when using 100% (r = 0.579, RMSE = 0.067 m3m−3), 75% (r = 0.575, RMSE = 0.067 m3m−3), and 50% (r = 0.569, RMSE = 0.067 m3m−3) of available valid pixels for each month of the study period. RK showed comparable values to OK when using different percentages of available valid pixels, 100% (r = 0.582, RMSE = 0.067 m3m−3), 75% (r = 0.582, RMSE = 0.067 m3m−3), and 50% (r = 0.571, RMSE = 0.067 m3m−3). GLM had slightly lower correlation with NASMD data (average r = 0.475, RMSE = 0.070 m3m−3) when using the same subsets of available data (i.e., 100%, 75%, 50%). Our results provide support for using geostatistical approaches (OK and RK) as alternative techniques to gap-fill missing spatial values of satellite-derived soil moisture. [ABSTRACT FROM AUTHOR]

Tidal salt marsh ecosystems store copious amounts of carbon (C) within sediments. In order to predict how these C stores may be affected by environmental change, it is critical to assess current CO 2 and CH 4 production and efflux from these ecosystems. Production and efflux of these greenhouse gases (GHGs) are governed by coupled geochemical, hydrological, physical and biological processes in sediments that are sensitive to local conditions, which can result in large spatial and temporal heterogeneity of GHGs dynamics within the ecosystem. To understand how the drivers of GHGs dynamics vary across salt marsh ecosystems, we coupled solid-phase geochemistry to measurements of porewater chemistry (to ∼1 m), CO 2 and CH 4 production in sediments and efflux to the atmosphere in a temperate tidal salt marsh for over one year to capture seasonal patterns within two vegetation zones of the marsh landscape that have distinct biogeochemical and hydrologic conditions: Tall Spartina (TS) and Short Spartina (SS). The SS vegetation zone experienced nearly constant inundation, low redox values (−200 to 200 mV), porewater pH 6–7 that did not vary with depth or time, an enrichment of pyrite and goethite with depth and up to 3 mM porewater sulfide. In contrast, the TS vegetation zone on the natural levee proximal to a tidal channel experienced large water level oscillations due to spring-neap tides that resulted in variable but higher redox values (0–700 mV), porewater pH 6–7 at depth but surface (0–3 cm) as low as 4 in the spring, an enrichment of ferrihydrite and a depletion of pyrite at ∼30 cm, and up to 0.8 mM ferrous Fe in porewater. At 50–56 cm, solid phase analyses (STXM-NEXAFS) revealed differential C speciation between the two vegetation zones, with stronger C-Fe spatial association at TS and stronger C-Ca co-association at SS despite both having similar soil pH of 3–4. These results suggest that soil pH may not be strongly predictive of C-mineral control in flooded marsh sediments. Both vegetation zones showed consistent CO 2 and CH 4 emissions from sediments to the atmosphere throughout the study period with TS having ∼60% higher median CO 2 and SS having ∼55% higher median CH 4 efflux. Using depth profiling, unexpectedly high concentrations of CO 2 (>200 μM) and CH 4 (>200 μM) were observed at depths 50–75 cm at both zones that were higher for SS in these sulfate-rich (up to 17 mM) sediments, which suggests methylotrophic methanogenesis occurs deep within the profile of salt marsh sediments away from the tidal channel. Moreover, if we extrapolate our median depth values of CH 4 and CO 2 to the 5.3 Mha of global salt marshes, this could account for a conservative estimate of ∼70 Gg of unaccounted C stored in gaseous form (i.e., CH 4 and CO 2) in marsh sediments, which should be considered when attempting to understand the current patterns and future responses of carbon dynamics from these ecosystems. [ABSTRACT FROM AUTHOR]

A correction to the article "The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling" that was published in the December 30, 2016 issue is presented.

Quantifying the biophysical impacts of management on river and stream ecosystems is an important issue that requires understanding of ecological, hydrological and geomorphological processes. We conducted a year-long ecogeomorphological experiment to determine sedimentation and carbon cycling differences between run-of-river (ROR) dams in a 200 year old impounded floodplain and a floodplain that was formerly impounded > 65 years ago. Our study shows that ROR dams do not necessarily enhance floodplain sedimentation or carbon storage, but promote brief periods of sediment CH 4 flux (up to 2.91 nmol CH 4 m − 2 s − 1 ) to the atmosphere. Removal of a ROR dam may result in channel widening, and removal by lateral transport (i.e., erosion) of nearly 14 MgC per floodplain. We did not find significant differences in mean sediment CO 2 fluxes or temperature sensitivity (Q 10 = 2.1 ± 0.4) of CO 2 efflux among floodplains. All floodplains were likely an annual net source of sediment CO 2 flux (annual mean of 2.12 ± 0.974 μmol CO 2 m − 2 s − 1 ) to the atmosphere, and a sink for atmospheric CH 4 (annual mean of − 0.221 ± 0.163 nmol CH 4 m − 2 s − 1 ). We provide a conceptual model on the management consequences on ROR dam structures for floodplain sedimentation/erosion, and sediment carbon cycling. [ABSTRACT FROM AUTHOR]

Water is a crucial factor controlling the fate and processing of soil organics. Water commonly flows through the vadose zone via preferential flow pathways, resulting in nonuniform and rapid infiltration. Hence, a large portion of the soil matrix is bypassed. Preferential flow paths, often associated with well-connected macropore networks (>300 μm Ø), offer a unique balance between water availability, nutrient delivery, and re-oxygenation upon drainage. The heightened concentrations of moisture, nutrients, and oxygen make these locations optimal for high rates of microbial activity. Flow paths often display temporal stability. This stability results in repeated wetting and biogeochemical reactivation through time creating a lasting impact on micro-environmental conditions relevant to microbial functioning and carbon cycling in soil. Despite decades of research on preferential flow, there is still a need to link flow paths and the resultant heterogeneous moisture distributions to soil function. In this review, we discuss how preferential flow can serve as a framework of reference for the spatially and temporally heterogeneous biogeochemical cycling of soil carbon. We highlight the importance of combining current knowledge of pore-scale carbon dynamics with an appreciation of connected networks of hydraulically active pores/paths within the soil profile. Such combination opens new possibilities for upscaling pore-scale processes with the inclusion of resource heterogeneity at the macroscale. Working within this hydraulically connected framework can provide insight for the mechanistic representation of hot moments, which are temporally isolated large pulses of CO 2 after rewetting or thawing events. We conclude with suggestions on knowledge gaps and stress the critical need of linking soil physics with biology to mechanistically understand soil functions. • Preferential flow paths play a key role in soil carbon dynamics. • Pore-scale carbon dynamics could be upscaled using hydraulic connectivity. • A conceptual model is presented that considers how soil pores function from hydrological and microbial perspective. [ABSTRACT FROM AUTHOR]

• Visible wavelength indices from phenocam best captured overall season length. • Indices containing infrared bands consistently overestimated onset of dormancy. • Visible wavelength indices and NDVI from phenocam best tracked daily NEP. • Proximal reflectance provides an ecologically meaningful link to carbon dynamics. Salt marshes constitute an important terrestrial-aquatic interface that remains underrepresented in Earth System Models due to constraining biophysical controls and spatially limited land cover. One promising approach to improve representativeness is the application of proximal remote sensing to generate phenological information, yet we lack detailed knowledge on how proximal sensors and indices perform within these ecosystems. We use measurements of net ecosystem productivity (NEP) from eddy covariance (EC) and derive ecologically-relevant phenology parameters (i.e., phenoperiods) to use as carbon phenology benchmarks. These benchmarks are compared against vegetation indices and spectral bands derived from spaceborne (i.e., MODIS) or common proximal sensors (i.e., phenocam and spectral reflectance sensors; SRS). Phenocam derived indices, which exclude infrared wavelengths (i.e., vegetation contrast index; VCI and greenness chromatic coordinate; GCC), aligned closely with NEP benchmarks and provided best predictions of carbon sink season length (within 1–6 days of benchmark). Although isolating infrared from vegetation (NIRv) offered improvements, other indices utilizing infrared bands (i.e., normalized difference vegetation index; NDVI and enhanced vegetation index; EVI) primarily underestimated season start dates (5–30 days prior to benchmark) while overestimating season end dates (7–47 days after benchmark). These discrepancies are greatest for indices derived from MODIS and SRS sensors, which have narrower full width half maximum spectral bandwidths and sharper orientation angles. The phenocam (VCI and GCC) provides the most accurate phenology parameters while offering near-infrared (NIR) response which can generate additional information on seasonal changes in canopy structure and function. The distinctive characteristics of the salt marsh environment and vegetation properties including standing dead biomass can introduce interpretation challenges for commonly used vegetation indices (NDVI, EVI). Incorporating information from proximal sensors utilizing only visible wavelengths (VCI, GCC) or isolating the near-infrared reflectance of vegetation (NIRv) offers improvements for studying carbon phenology within salt marshes. [ABSTRACT FROM AUTHOR]

Storm surges can substantially alter the water level and salinity in tidal salt marshes. Little is known about how changes experienced during storm surges affect greenhouse gas emissions (GHG; CO 2 , CH 4 , N 2 O) from tidal salt marsh soils. Understanding how storm surges influence ecosystem processes is critical for evaluating the ecosystem's sensitivity to sea level rise. To explore how hurricane-induced changes in salinity affect GHG emissions, we exposed intact soil mesocosms (0–9 cm depth) from a Mid-Atlantic temperate salt marsh to pulse changes in salinity experienced at the site before, during, and after Hurricane Joaquin in 2015. Soil temperature, oxygen, and water level were kept constant to avoid confounding effects throughout the experiment. Automated measurements (hourly resolution) of soil GHG emissions were recorded in control (i.e., no salinity changes) and treatment mesocosms, and combined with soil pore water chemistry (i.e., SO 4 2−, S2−, Fe2+, TN b , redox potential, pH) to characterize the biogeochemical responses. Using mixed effects models, we found that the role of different biogeochemical processes, such as sulfur cycling, changed throughout the experiment, underscoring the complex nature of GHG emissions in tidal salt marsh soils. Overall, soils subjected to a salinity decrease had greater GHG emissions than control soils, which were maintained at 17 ppt. The treatment soils had a 24% and 23% increase in global warming potential (20- and 100-year scenarios, respectively) indicating that storm surges can produce pulses of GHG emissions. However, both CH 4 and N 2 O emissions returned to baseline values (following hysteresis responses) when initial conditions were reestablished. The results support the fact that tidal salt marshes are resilient ecosystems, as soil GHG emissions recovered relatively quickly from the pulse event. Unlabelled Image • Studied the influence a pulse-change in salinity on salt marsh GHG biogeochemistry • Coupled automated GHG measurements with pore water chemistry • CO 2 decreased with decreased salinity; CH 4 , and N 2 O fluxes increased. • Salt marsh soils recovered from salinity changes relatively quickly. [ABSTRACT FROM AUTHOR]

Highlights • The exotic/invasive buffelgrass has been introduced in drylands to increase productivity and grazing capacity of shrublands. • Adjacent shrubland and a buffelgrass savanna sites showed seasonal differences in CO 2 and water fluxes in the Sonoran Desert. • Seasonal differences in carbon fluxes between sites were related to differences in water use and water use efficiency. • Seasonal differences compensated over time, both sites being comparable carbon sinks over the 3 year study period. • Mechanisms causing similar carbon sink capacity in vegetation change from woody- to grass-dominated ecosystems are discussed. Abstract Land cover and land-use change (LCLUC) between woody- and grass-dominated ecosystems in drylands comprise one of the largest uncertainties in the land CO 2 sink. This is especially true for the widespread transition from shrublands to grasslands/savannas caused by the establishment of exotic C 4 grass species for grazing or through biological invasion of these species, where information about its impacts on ecosystem CO 2 fluxes is limited. For studying this, we used three years of eddy covariance measurements of net ecosystem production (NEP), gross primary production (GPP), ecosystem respiration (R eco) and evapotranspiration (ET) over a Sonoran Desert shrubland and an adjacent grazing savanna of buffelgrass (Cenchrus ciliaris L.), established 35 years ago. At monthly, seasonal and annual time scales, we assessed whether between-site differences in CO 2 fluxes were related to differences in ecosystem water use, measured as the fraction ET to precipitation, water use efficiency (WUE, i.e. the ratio between GPP and ET) and/or to the relation between R eco and GPP. Although the savanna had higher WUE than the shrubland, its summer NEP was limited by water use, due to limitations in leaf area index and likely rooting patterns. Conversely, the savanna had higher NEP than the shrubland during fall to spring due to increased WUE; possibly due to activity of buffelgrass and remaining woody species using (summer) water from deeper soil layers. However, differences across these seasons compensated each other at the inter-annual scale, and both sites had comparable net carbon sinks over the three-year study period. Further studies are needed to understand and reduce the uncertainty associated with carbon and water fluxes associated with LCLUC in dryland ecosystems. [ABSTRACT FROM AUTHOR]

Dryland ecosystems largely control the inter-annual variability of the global carbon cycle. Unfortunately, there is a paucity of data on key biochemical parameters, such as maximum carboxylation velocity (V cmax25 ) and electron transport rate (J max25 ), from species in these ecosystems which limits our capacity to model photosynthesis across ecological scales. We studied six dominant C 3 shrub and tree species from the Sonoran Desert with different leaf traits and phenological strategies. We characterized V cmax25 and J max25 for each species and assessed which traits or trait combinations were the best predictors of these parameters for biochemical models of photosynthesis. All species had high values of V cmax25 and J max25 , mostly explained by high leaf nitrogen content (N area ) and high nitrogen allocation to photosynthetic enzymes comparable to those reported for herbs and crop species but higher than those of shrubs and other functional types in world databases. We found that the high values of V cmax25 and J max25 , by increasing rates of photosynthetic reactions, enhance photosynthetic water and nitrogen-use efficiencies and may favor carbon gain under typical conditions in drylands. Our findings improve the parameterization of photosynthesis models, and provide novel implications to common findings of high N area in dryland species. [ABSTRACT FROM AUTHOR]

Mangrove wetlands play an essential role as blue carbon ecosystems. However, worldwide they also face imminent threats caused by anthropogenic activities and climate change. Mangroves in the semiarid region of the Gulf of California are highly vulnerable to both threats. In this study, we present eddy covariance measurements of net ecosystem exchange of CO 2 (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco) at a preserved mangrove (Estero El Sargento) and a site influenced by anthropogenic activities (Bahia del Tobari) located in northwest Mexico. Both sites were net annual carbon sinks but had different dynamics. The net annual carbon gain for Estero El Sargento was −717 g C m−2 y−1 while for Bahia deTobari was −247 g C m−2 y−1. Over the studied year, Estero El Sargento had lower R eco (329 g C m−2) during the winter-spring months and an overall lower annual R eco /GPP (0.42) than Bahia de Tobari. The R eco was notably high during the winter-spring period at Bahia de Tobari when agriculture drainage from the intensive food production activities at the Yaqui Valley reaches the bay. The contrasting NEE patterns and magnitude between both mangrove sites suggest that anthropogenic activities influencing coastal ecosystems exert an important control on the CO 2 sink potential. • Mangrove forests function as net C sink in regions with less than 200 mm of annual precipitation. • Winter precipitation is important for Gross Primary Productivity in semiarid mangroves. • Ecosystem respiration is high in mangroves influenced by agriculture drainage. [ABSTRACT FROM AUTHOR]

Quantifying and identifying measurement error is an ongoing challenge for carbon cycle science to constrain measurable uncertainty related to the sources and sinks of CO 2 . One source of uncertainty in measurements is derived from random errors ( ε ); thus, it is important to quantify their magnitude and their relationship to environmental variability in order to constrain local-to-global carbon budgets. We applied a paired-observation method to determine ε associated with marine x CO 2 in a coastal upwelling zone of an eastern boundary current. Continuous data (3-h resolution) from a mooring platform during upwelling and non-upwelling seasons was analyzed off of northern Baja California in the California Current. To test the rigor of the algorithm to calculate ε we propose a method for determining daily mean time series values that may be affected by ε . To do this we used either two or three variables in the function, but no significant differences for ε mean values were found due to the large variability in ε (−0.088 ± 27 ppm for two variables and −0.057 ± 28 ppm for three variables). Mean ε values were centered on zero, with low values of ε more frequent than greater values, and follow a double exponential distribution. Random error variability increased with higher magnitudes of x CO 2 , and in general, ε variability increased in relation to upwelling conditions (up to ∼9% of measurements). Increased ε during upwelling suggests the importance of meso-scale processes on ε variability and could have a large influence seasonal to annual CO 2 estimates. This approach could be extended and modified to other marine carbonate system variables as part of data quality assurance/quality control and to quantify uncertainty (due to ε ) from a wide variety of continuous oceanographic monitoring platforms. [ABSTRACT FROM AUTHOR]