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This study is the first assessment of a fjord Ecological Quality Status (EcoQS) by comparing both the traditional morphology‐based and emerging metabarcoding techniques in benthic foraminifera. For this, we focus on historically polluted Idefjord on the Swedish Norwegian border, which has experienced high effluent load from pulp and paper mill for almost a century. Based on our results, the morphological data was more sensitive to "naturally stressed" conditions, like course sediments and cascading water inflows at fjord sills. Generally, both data sets report congruous responses in the EcoQS and benthic foraminiferal assemblages to environmental stress factors, showing highest diversity at the coastal reference station and the outer fjord, with a diversity decline in proximity of industrial facilities and at the most oxygen depleted sites in the inner fjord. Genetic methods tend to overestimate EcoQS at highly anoxic sites probably due to a presence of dormant propagules or extraorganismal DNA, emphasizing a need for cross‐correlation with morphological methods to validate EcoQS assessment in such conditions. Plain Language Summary: The Ecosystem Quality Status (EcoQS) of fjords can be difficult to assess because of natural variation caused by for example, complex sea floor topography and bottom water oxygen depletion. Fjords have often restricted water exchange, resulting in stagnant bottom waters and pollutant accumulation in basin sediment caused by proximity to industrial facilities. Benthic foraminifera (shell‐bearing protists) can be used to provide information about the health of such ecosystems. Environmental DNA (eDNA) extracted from sediment samples can also be used to identify the foraminifera species present and calculate biological indices. Yet, it is still unclear how well the eDNA technique performs in fjord EcoQS assessment and how it compares to the traditional morphology‐based approach. In Idefjord (Sweden‐Norway), historic dumping of waste from the pulp and paper industry, has led to a build‐up of organic matter, chemical pollutants in the sediment and widespread oxygen depletion. Based on our study, the fjord EcoQS determined by both approaches was fairly similar, showing highest diversity at the coastal reference station and the outer fjord, with a decline in diversity in proximity to industrial facilities and in the inner fjord. The genetic method, however, tended to over‐estimate the EcoQS at the anoxic stations, likely due to left‐over eDNA from transport or resting stages. Key Points: Natural and anthropogenic variability for example, low oxygen, organic matter and pollutant accumulation, deteriorate Ecological Quality StatusMorphology‐based and molecular assessment methods show congruent responses of benthic foraminifera to environmental stressGenetic methods can overestimate Ecological Quality Status in anoxic sites due to dormant propagules or transported DNA presence [ABSTRACT FROM AUTHOR]

The editorial team at JGR: Biogeosciences would like to extend thanks to the 2022 reviewers who offered their time and expertise to help make decisions and improve our papers. Plain Language Summary: The editorial team at JGR: Biogeosciences would like to extend thanks to the 2022 reviewers who offered their time and expertise to help make decisions and improve our papers. Key Points: JGR Biogeosciences relies on hundreds of reviewers with wide ranging expertiseThank you to our 2022 reviewers [ABSTRACT FROM AUTHOR]

Plain Language Summary: The Journal of Geophysical Research‐Biogeosciences focuses on the interactions between biology, hydrology, geology, chemistry, and physics within the Earth system. Here, we are presenting a brief early history of the journal and evolution of the topics and papers published over the past 20 years. We present an updated aims and scope which now explicitly considers method and data articles. Key Points: JGR: Biogeosciences has published 3,000 articles on integrating biological, chemical, and physical properties across ecosystemsNew methodologies, new approaches, big datasets, monitoring, and new ways of thinking are important for the biogeosciencesWe are updating our aims and scope to formalize biogeosciences methods and data articles in the journal [ABSTRACT FROM AUTHOR]

Glaciers in the Svalbard Archipelago are retreating rapidly in response to climate change. This retreat leads to the alteration of the hydrological and thermal regimes of freshwater ecosystems. In this delicate context, existing anadromous Arctic charr (Salvelinus alpinus) populations are at severe risk and might disappear from the archipelago. However, the retreat of glaciers also promotes the formation of new lake systems that might be suitable for colonization by anadromous Arctic charr. These systems may provide a substantial opportunity for the establishment of new populations of anadromous charr, potentially buffering the decline in existing systems. To date, there is a lack of information on the number of recently deglaciated lake systems that have emerged since the end of the Little Ice Age (ca. 1920) that might be suitable for charr colonization. Therefore, the goal of this paper is to provide an initial assessment of the number of these lakes. To this end, and in accordance with previously published research, this study assesses whether a recently deglaciated lake system is potentially open to colonization based on gradient, river length, and lake surface area. Depending on the applied threshold (four in total), up to 24 lake systems are classified as potentially open to colonization by anadromous Arctic charr, with Spitsbergen emerging as a potential hotspot for colonization. The findings of this paper might serve as basis for new studies and for implementing proactive management and conservation strategies to protect anadromous charr populations. Plain Language Summary: The landscape of the Archipelago of Svalbard is rapidly evolving in response to glacier retreat. The retreat of glaciers alters temperature and discharge of river and lake systems. These alterations may lead to the collapse of the highly valuable populations of anadromous Arctic charr (Salvelinus alpinus) in the Svalbard Archipelago. Whilst existing populations are at serious risk, new populations might establish in recently deglaciated lake systems. In order to implement proactive management and conservation strategies, it is of fundamental importance to classify newly formed lakes that might be open to colonization by anadromous charr. To this end, this study provides the first comprehensive identification of these lakes. Depending on the thresholds used to determine whether a lake is open to colonization, up to 24 lake systems are identified in the archipelago, with Spitsbergen emerging as a potential hotspot for colonization. Key Points: The retreat of glaciers since the end of the Little Ice Age has contributed to the formation of 168 lake systems in the Svalbard ArchipelagoUp to 24 lake systems were classified as potentially open to colonization by anadromous Arctic charr (Salvelinus alpinus)Recently deglaciated lake systems might offer new opportunities for the establishment of new anadromous charr populations [ABSTRACT FROM AUTHOR]

This study is part of the requirements consolidation study for the European Copernicus Hyperspectral Imaging Mission for Environment (CHIME). It explores the value added by existing hyperspectral data of similar characteristics to CHIME, namely AVIRIS‐NG and PRecursore IperSpettrale della Missione Applicativa (PRISMA), for detecting topsoil texture properties. The spatial variability is retrieved using the linear spectral mixture analysis, an image‐based algorithm that breaks down the hyperspectral data set into fractional abundance of spectral classes within each pixel. The fractional abundance of image‐based endmembers is broken into categories to find intervals having a spatial relation with texture components in terms of fine (clay and silt) or coarse (sand) abundance. The fraction maps obtained show similar spatial patterns to the USDA soil texture classification, obtained with a geostatistical approach. Specifically, AVIRIS CHIME‐like FAM1 > 0.45 presented an agreement of 86% with clay and/or silt higher than 45% which, according to the United Stated Agriculture Department (USDA) intervals, correspond to loam‐clay loam classes. Similar results are obtained with PRISMA with FAM2 0.20–0.35, overlapping 63% of the kriging‐based USDA clay‐loam class. The fractional abundance categories showing the highest overlap percentages are correlated with the short‐wave infrared spectral range, showing average coefficients of 0.7 where wavelengths are over 1,500 nm. From 1700 nm, CHIME‐like shows values of 0.8. In conclusion, this exploratory research and results leverage the opportunity of extending the processing chain to a larger number of case studies to better understand the physical relation between the spectral reflectance captured by new spaceborne hyperspectral sensors and the spatial patterns of soil texture classes. Plain Language Summary: In the current context led by the constant availability, almost in near‐real time, of remote sensing data with high spatial, spectral and temporal resolutions, the monitoring of soil properties should no longer be solely limited to field data observations. There is a growing need of knowledge for preserving and exploiting soils and the upcoming generation of hyperspectral satellite remote sensing has popped up new opportunities for developing and adapting algorithms that break up the image pixels into several spectral behaviors that correspond to different soil properties. This paper contributes to the application of these image analysis techniques to soil texture classes retrieval considering the United Stated Agriculture Department model. The paper uses the principles of the spectral mixture concept to explore the opportunity of detecting soil textures in two farmland units and provides some highlights on the observational requirements needed to integrate the future satellite missions' architecture within the agriculture and food security application domain. Key Points: Hyperspectral imaging is used to retrieve United Stated Agriculture Department soil texture classification in two farmland units applying linear spectral mixture analysisCopernicus Hyperspectral Imaging Mission for Environment‐like and PRecursore IperSpettrale della Missione Applicativa‐derived fractional abundance intervals are found to spatially overlap the clay‐loam class obtained with field dataFractional abundances categories having the highest overlap percentage are strongly correlated with the Short‐Wave InfraRed > 1,500 nm [ABSTRACT FROM AUTHOR]

The atmospheric deposition of long‐range atmospheric mercury pollution presents forest managers with a "wicked" problem—forestry operations run the risk of mobilizing this pollution legacy. Management of that risk would benefit from a process‐based understanding of how forest management influences the mercury cycle. This commentary highlights the value for building such an understanding of a comprehensive Before‐After‐Control‐Impact study reported by McCarter et al. (2022), https://doi.org/10.1029/2022JG006826 on the Marcel Experimental Forest in the north‐central continental US. That study looked at how different types of forest harvest influenced the movement of mercury through the landscape. The results of this study place it at the minimal end of the range of impacts on Hg mobilization resulting from forest harvest. What makes this paper, together with the companion papers resulting from this study, particularly valuable for improving the understanding of forestry influences on mercury is the number of system boundaries that the study crossed: between land and atmosphere, from a forested hillslope down into a wetland, and finally up into the biota on that wetland. Plain Language Summary: Forest harvest can mobilize toxic mercury from forest soils and move it into living organisms. This mercury originated in air pollution created far away from the forest, but forest managers still need to deal with the risks of this "pollution legacy" to people, fish and wildlife. A recent study in the north‐central US took a detailed look at how two different types of forest harvest mobilized mercury in the soil. This study showed a relatively small impact of the forest harvest on mercury relative to some other studies. Since previous studies have found a wide range of mercury responses to forest harvest, this carefully designed and executed study has value in adding to the evidence base about forest management impacts on mercury in the environment. What is particularly valuable about this study is its comprehensiveness, since it crosses a number of environmental system boundaries: between the forest and the atmosphere, from upslope mineral soils into a downslope peatland, and from the wetland environment into the biota. Key Points: A well‐executed study sheds new light on the "wicked" problem of how forest harvest influences the mobility and bioaccumulation of mercuryThe study is particularly valuable because it extends across several environmental system boundaries: atmosphere‐forest‐peatland‐biotaCrossing downstream boundaries can show how more of the stream network embedded in a landscape reacts to land‐use and climate change [ABSTRACT FROM AUTHOR]

Our changing climate is having effects on freshwater ecosystems in all seasons, especially winter. High latitude lakes, wetlands, and rivers are experiencing shorter periods of ice cover, and lower latitudes systems that used to freeze are experiencing open water conditions throughout the winter. A 2019 AGU Chapman conference convened aquatic scientists to examine these changes and address the implications of changing winters to aquatic life, chemistry, and physics. Several studies demonstrate decreased ice cover duration than in the past. The removal of an ice "lid" from lakes and rivers impacts the exchange of gases with the atmosphere and the predominant types of metabolism occurring in the waters below, with the potential for more photosynthesis and an increase in oxic versus anoxic metabolism when the lid is removed. Multiple studies indicated an increase in the interannual variability of winters, especially in terms of ice‐cover duration and ice quality. Increased variability may simply be an outcome of a more variable winter climate or small differences in environmental conditions such as temperature that can have strong effects on gas exchange, light transmission, and turbulence when ice forms. A question that merits further consideration is whether and how winters of shorter duration and severity will change the dynamics of freshwater systems. Are there memory or legacy effects that carry over to the next season or year? There is much work to be done to understand how changing winters will impact the biogeochemical behavior of lakes and rivers in the coming decades. Plain Language Summary: Winters at mid‐high latitudes are changing rapidly with important implications for freshwater ecosystems. An AGU Chapman conference, convened in 2019, brought together scientists to outline what we know about the changes that are occurring and what questions need further study. This special issue is a collection of the papers that developed from that workshop. These studies demonstrate that lakes and rivers at mid‐high latitudes are experiencing less ice cover duration and greater variability in year‐to‐year ice cover. Changing ice and snow cover impacts processes occurring under ice in winter by altering the light regime, mixing, biota present, and the availability of oxygen. There are many important research questions regarding winter dynamics that still need to be addressed but one of the most important ones has to do with how changing winters might influence the biota in other seasons. Key Points: Several of the papers point to interannual variability in winter and seasonal ice cover along with decreased ice cover durationAvailable winter datasets have grown supporting conceptual developments, but increased efforts focused on ecological responses are neededFuture research should examine connections between seasons, deploy submersed sensors year‐round, and use remote sensing approaches [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) is an important component of the terrestrial carbon cycle in climate change research. The global GPP product derived using Moderate Resolution Imaging Spectroradiometer (MODIS) data is perhaps the most widely used. Unfortunately, many studies have indicated evident error patterns in the MODIS GPP product. One of the main reasons for this is that the applied big‐leaf (BL) MOD17 model cannot properly handle the variable relative contribution of sunlit and shaded leaves to the total canopy‐level GPP. In this study, we developed a model for correcting the errors in the MODIS GPP product by bridging BL and two‐leaf (TL) light use efficiency (LUE) models (CTL‐MOD17). With the available MODIS GPP product, which considers environmental stress factors, the CTL‐MOD17 model only needs to reuse the two inputs of the leaf area index (LAI) and incoming radiation. The CTL‐MOD17 model was calibrated and validated at 153 global FLUXNET eddy covariance (EC) sites. The results indicate that the modeled GPP obtained with the correction model matches better with the EC GPP than the original MODIS GPP product at different time scales, with an improvement of 0.07 in R2 and a reduction in root‐mean‐square error (RMSE) of 117.08 g C m−2 year−1. The improvements are more significant in the green season when the contribution of shaded leaves is larger. In terms of the global spatial pattern, the obvious underestimation in the regions with high LAI and the overestimation in the low LAI regions of the MODIS GPP product is effectively corrected by the CTL‐MOD17 model. This paper not only bridges the BL and TL LUE models, but also provides a new and simple method to obtain accurate GPP through reusing two inputs used in producing the MODIS GPP product. Plain Language Summary: Gross primary productivity (GPP) is crucial for terrestrial carbon cycle study. The Moderate Resolution Imaging Spectroradiometer (MODIS) GPP data is perhaps the most widely used product, but many studies have indicated evident error patterns in it. These errors can be mainly explained by the applied big‐leaf (BL) MOD17 model cannot properly handle the variable relative contribution of sunlit and shaded leaves to the total canopy‐level GPP. As a result, this paper developed a novel and simple model (CTL‐MOD17) to obtain accurate GPP by reusing two inputs data from the MODIS GPP product, based on a two‐leaf (TL) theory. The CTL‐MOD17 model is evaluated at 153 global FLUXNET eddy covariance (EC) sites, and compared with other TL GPP products and models. The results indicate that CTL‐MOD17 can significantly improve the accuracy of MODIS GPP products at different time scales, to be similar to other TL models but with fewer data inputs. The obvious underestimation/overestimation of MODIS GPP in the high/low leaf area index (LAI) regions are all effectively corrected. This study proves the possibility of bridging the BL and TL models for the first time, which can be migrated to other BL products and models. Key Points: A novel product‐based model (CTL‐MOD17) corrects Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product bias, achieving results similar to two‐leaf models with fewer inputsIt is the first time to prove the possibility of bridging the big‐leaf and two‐leaf models, which can be migrated to other big‐leaf GPP products and modelsThe obvious underestimation/overestimation of MODIS GPP in high/low LAI regions are all effectively corrected by the CTL‐MOD17 model [ABSTRACT FROM AUTHOR]

In this analysis of the spatial resolving power of thermal imagery products we focus on four satellite instruments that are used in research and applications, for example, to monitor land surface temperature and derive evapotranspiration. These are thermal imagers on Landsat 7, Landsat 8, and Landsat 9, as well as the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). We compiled sets of close‐in‐time, day‐time images of bridges surrounded by open water bodies, captured by each of the satellite imagers during cloud‐free moments. Where possible, we also included some images captured by the Compact Thermal Imager (CTI), a technology demonstrator that was co‐located with ECOSTRESS on the International Space Station in 2019. Bridges were found to provide a sufficient thermal contrast with the water surface to quantify the line‐spread function of satellite‐based thermal products. The full‐width‐at‐half‐max of a gaussian beam model fitted to this transect quantifies the on‐orbit spatial resolution of different imagers. The results show some loss of spatial resolving power in the final product delivered to end‐users as compared to the at‐sensor characterization of spatial resolution. For Landsat 7, 8, and 9, the spatial resolution of the thermal bands is 1.5 times the ground sampling distance of 60 and 100 m respectively. For the ECOSTRESS the difference is up to twice the sampling distance of 78 by 69 m2. Since spatial resolution is a main driver for instrument design it is important to understand and communicate this discrepancy between pre‐flight design parameters and the characteristics of the surface imagery delivered to the user community. The goal of this research is to facilitate an improved fusion of current and future satellite observations into harmonized products with superior temporal and spatial characteristics. Plain Language Summary: This manuscript describes a method to verify the spatial resolution of thermal imagers after launch. Spatial resolution is a key driving requirement in thermal imager design and technology development. Many aspects that control spatial resolution are mathematically understood and can be calculated based on the design specifications of spaceborne imagers. However, the actual spatial resolution of the products delivered to users may not meet the design target precisely. In this paper we compiled a set of thermal images of the San Francisco Bay area. In these daytime images the bridges show up as clearly defined linear features contrasted with the relatively homogenous water surrounding them. From these images, we construct sharply defined profiles perpendicular to the bridge orientation. We then use these profiles as analogs of the linear cuts used to determine the line‐spread function in laboratory tests of imagers. What we find is a much lower spatial resolving power in the final product delivered to end‐users as compared to the at‐sensor characterization of spatial resolution. The reduced spatial resolution we found compared to what may be expected from mission specifications points to the need of better communication of how imager specifications are conveyed into mission products. Key Points: Day‐time thermal contrast between a bridge and its surrounding waters is used to quantify the spatial performance of space‐borne imagersSpatial resolution of thermal imagery products can be lower, to a factor of 2, than the nominal values calculated based on system designThe divergence between pre‐flight and on‐orbit metrics should be factored into mission design trade studies [ABSTRACT FROM AUTHOR]

Urban expansion leads to increasing water pollution, impacting both human health and ecosystems. This decline in water quality often stems from insufficient wastewater treatment, along with runoff from both urban and agricultural areas. Water quality degradation challenges our efforts for sustainable water management and hinders progress toward the UN's Sustainable Development Goals (SDGs), particularly SDG6. Within aquatic environments, the hyporheic zone—the subsurface area where surface water and groundwater mix—plays a crucial role in facilitating pollutant turnover and overall aquatic health. Mixing between surface water and groundwater generates diverse microhabitats in the streambed with varying levels of oxygen, temperature, and chemical composition, which in turn allows diverse microbial communities to strive. The complexity of exchange flows within the hyporheic zone and associated turnover processes of pollutants and nutrients can only be assessed with detailed, cross‐disciplinary data sets including data about hydrology, climatology, biogeochemistry, and the subsurface composition. However, integrated data sets of this kind are seldom available. As a result, the drivers behind pollutant dynamics in stream‐aquifer systems are still not fully understood. Addressing this knowledge deficit, we present a comprehensive unique data set from an urban stream‐aquifer system in Switzerland spanning over 6 months. Incorporating hydrometric, tracer, nutrient, microbial and organic micropollutant data, our data set can help to shed light on the intricate mechanisms governing hyporheic exchange flows, as well as nutrient and organic micropollutant cycling in urban environments. Plain Language Summary: Polluted water can have negative impacts on human health and other animals and organisms living in water. One of the main reasons for water pollution in urban areas is that wastewater is not always treated properly, and rain can wash harmful substances from cities and farms into streams and groundwater. However, nature has the capacity to clean up some of the pollution. Below rivers and lakes lies the hyporheic zone—an area where water from surface waters mixes with groundwater. The organisms living in this zone can naturally remove some of the pollution, which can improve the water quality. However, assessing how the self‐cleaning of the hyporheic zone works is difficult because we rarely have all the data necessary to study it in detail. This data paper provides a detailed set of different kinds of data collected from an urbanized area in Switzerland over 6 months. We believe that the comprehensive data set presented here will help other scientists understand how the hyporheic zone works, especially in urban environments. Key Points: We present spatiotemporally‐resolved hydrological and biogeochemical data to study hyporheic exchange flow and water pollution [ABSTRACT FROM AUTHOR]

Imaging spectroscopy is a powerful tool used to support diverse Earth science and applications objectives, ranging from understanding and mitigating widespread impacts of climate change to management of water at farm‐scale. Community studies, such as those deployed by NASA's Surface Biology and Geology and ESA's Copernicus Hyperspectral Imaging Mission for the Environment, have offered new and tangible insights into user needs that are then incorporated into overall mission planning and design. These technologies and tools will be key to develop and consolidate downstream services for users and resource management, given the current pressures on the environment posed by climate change and population growth. This process has highlighted the degree to which planned mission capabilities are responsive to community needs. In this study, we analyze user requirements belonging to the Italian Copernicus User Forum and to the user pool of NASA's Surface Biology and Geology community for the synergic use of hyperspectral imaging technology, providing a reference for the development of earth observation services and the consolidation of existing ones. In addition, potential cross‐mission coordination is analyzed to highlight key benefits—(a) addressing shared community needs around products requiring more frequent temporal revisit and (b) shared resources and community expertise around algorithm development. This paper discusses the critical role of early engagement with users to establish a community of practice ready to work with high spatial resolution imaging spectroscopy data sets. The main outcome is a guide for the synergetic use of hyperspectral mission and data together with the identification of the main gaps between user needs and satellite capabilities influencing the development of key national and trans‐national downstream services. Plain Language Summary: In this research we have analyzed needs of users to understand how to develop and improve earth observation downstream services. Hyperspectral imaging provides information across the electromagnetic spectrum in more detail than multispectral imaging, allowing more specific analysis and accurate identification of materials and substances. The users in this study belong to the Italian Copernicus User Forum and to the NASA Surface Biology and Geology community which provided requirements respectively for ESA's Copernicus Hyperspectral Imaging Mission for the Environment and NASA's Surface Biology and Geology. This work identifies common users and examines the advantages of potential synergy between these hyperspectral satellites for responding to their needs. This analysis shows that the synergy would bring significant advantages in terms of improved revisit time and represents an opportunity to address shared community needs around product and algorithm development. Key Points: Current users' needs for hyperspectral earth observation data suggest future investment in improving spatial and temporal resolutionCoordination between missions can fill this gap especially improving temporal revisitShared community and resources can facilitate the improvement of products from these missions and their use across different sectors [ABSTRACT FROM AUTHOR]

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species‐specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing. Plain Language Summary: Biodiversity monitoring based on field data is almost inconceivable at the scale of the entire Earth. Over the past decades, remote sensing has opened possibilities for Earth observation from air and space, allowing us to monitor ecological change, primarily expressed by changes in vegetation cover, distribution, and functioning, which can be subsequently linked to drivers of change in space and time, from local to global scale. Recently, the spectral species concept—an algorithm that clusterizes pixels from spectral images having a similar spectral signal (referred to as 'spectral species')—has brought attention. The aim of this paper is to review the ecological functioning principles of the spectral species concept and to refine its definition by a better linkage with field observations of plant species distribution data (i.e., presence‐absence data) available from vegetation surveys. Key Points: Remote sensing has opened possibilities for Earth observation from air and space, allowing us to monitor ecological changeBiodiversity monitoring based on field data is almost inconceivable at the scale of the entire EarthThe spectral species concept, relating field to remotely sensed data, can open new ways to measure diversity from space [ABSTRACT FROM AUTHOR]

Elucidating the climate feedback due to forest cover loss is critical for a comprehensive understanding of the role of forests in mitigating climate change. Current research studies predominantly focus on the impacts of permanent forest conversion, often overlooking the effects of recurrent disturbances such as fire and harvest. This study addresses this gap by examining the impact of forest cover loss caused by two distinct drivers in China over the period 2003–2020. Our analysis revealed that fire‐induced forest cover loss accounted for approximately 10% of total forest cover loss in China. The immediate (i.e., 1 year after disturbance) changes in land surface temperature (ΔLST) due to fire were higher (ΔLST = 0.11°C, interquartile range (IQR): [−0.02°C–0.23°C]) compared to those caused by harvest (ΔLST = 0.04°C, IQR: [−0.01°C–0.09°C]). This finding highlights the immediate warming effect of fire‐induced forest cover loss, was about triple as large as that caused by harvest. Our analysis also found that the warming effect post‐fire gradually lessened but still maintained approximately 0.02°C 5 years later. Change in evapotranspiration is a primary factor influencing surface temperature changes following forest disturbances. Our study provides comprehensive insights into the differential and persistent effects of LST responses to fire and harvest, underscoring the importance of understanding the climate feedback from forest dynamics from different drivers. Plain Language Summary: This study quantified the biophysical effects attributable to recurrent forest cover loss caused by fire and harvest using a space‐for‐time approach. Previous reports have primarily explored the temperature impacts of either permanent or gradual disturbances. However, the gaps of biophysical effects from recurrent disturbances should not be overlooked. In this paper, we quantified forest cover loss due to fire and harvest and compared surface temperature following these changes. We then identified the dominant biophysical processes governing the LST response to forest cover loss. What we find is a much more pronounced warming effect and a longer recovery period with increasing proportions of fire‐affected areas than that under harvest, with ET being the primary factor driving these LST changes. Our comparable results from different recurrent disturbances provide valuable insights for future research. Key Points: Surface temperature warming effects resulting from forest cover loss under different recurrent disturbances should be widely acknowledgedTemperature feedbacks caused by fire‐induced forest cover loss was higher than those caused by harvestEvapotranspiration is a primary factor influencing surface temperature changes following forest disturbances in temperate forests in China [ABSTRACT FROM AUTHOR]

The editorial team at JGR: Biogeosciences extends thanks to the 2021 reviewers who offered their time and expertise to help us make decisions and improve papers. [ABSTRACT FROM AUTHOR]

Cyanobacterial biocrusts (CBCs) perform a range of functions including early successional colonization of substrates, modification of soil properties, surface stabilization and carbon sequestration. The response of CBCs to hydration is well‐constrained for cultured or single‐species but less so for in situ communities and there are few studies of CBC response to, and impact on, wind erosion. This paper investigates the in situ response of dryland CBCs to rainfall and wind erosion using biological and physical indicators. Field sites are in central Australia in three geomorphic situations ‐ sand dune, nebkha and claypan. Results indicate higher amounts of rainfall trigger a more intense biological response than lower amounts, but not one of longer duration. The intensity of photosynthetic response to rainfall appears related to air temperature. The relationship between CBC and soil loss by wind erosion is inconclusive, but saltation efficiency (Qs/Q) is highest on the dune and claypan when tested 48 hr after applying 5 mm of rainfall. This is attributed to rainfall detachment of sand particles increasing the availability of loose erodible material on the surface. The results highlight the rapid biological response of CBCs to rainfall events (within hours), and the importance of overall environmental conditions, such as air temperature, but raise questions as to the longevity of the biological impact of such response. Drought‐affected CBCs can protect the surface against wind erosion but dehydration may reduce resilience to disturbance and, under predicted future climate scenarios, the protective role of cyanobacterial crusts may be compromised. Plain Language Summary: Biological crusts comprise one or more of cyanobacteria, fungi, algae, lichen and mosses. They are tolerant to high temperatures and long periods of drought and can bind soil particles together making them less susceptible to erosion. This paper examines how cyanobacteria‐dominated soil crusts respond to rainfall and whether that response affects the likelihood of wind erosion. We used a rainfall simulator and a wind tunnel and conducted experiments on a sand dune, the area between the dune and a floodplain, and the floodplain itself. We examined changes in the biological and physical characteristics of the cyanobacterial crust for no rain, 5 mm rain and 10 mm rain. Higher amounts of rainfall led to more biological change than lower amounts. The wind is most effective following 5 mm rain probably because the rain causes sand particles to come to the surface and when the wind blows these particles they impact other particles causing erosion. Cyanobacterial crusts react quickly to rainfall but the response does not last long (less than a day). Drought affected cyanobacterial crusts can protect the surface against wind erosion but this ability may be reduced if future climate conditions are warmer with longer periods between rain. Key Points: Cyanobacteria have a rapid but short‐lived fluorescence response to rainfallSubstrate characteristics affect cyanobacterial crust response to rainfall and wind erosionCyanobacterial photosynthetic response increases with increasing temperature [ABSTRACT FROM AUTHOR]

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8‐day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission. Plain Language Summary: This paper develops a emulated (or synthetic) global hyperspectral data set, based on existing multispectral satellite products, to support the NASA Surface Biology and Geology (SBG) mission development. The challenge of the task is to find a simple yet robust algorithm to interpolate multispectral observations to (unobserved) hyperspectral bands. Based on theoretic analyses and numerical model simulations, we develop an accurate and efficient algorithm that accomplishes this task by combining information from the optical properties of the surface elements and the structural properties of the landscape and vegetation canopies. The former are obtained from existing spectral libraries and the latter can be estimated from the multispectral satellite products. We apply the algorithm to generate a scientifically coherent and consistent global hyperspectral data set, which are publicly available to serve the needs of the science community of SBG and other global hyperspectral remote sensing satellite missions. Key Points: A simple algorithm is developed to generate a global hyperspectral synthetic data set based on multispectral satellite productsThe algorithm is theoretically robust and verified with Monte Carlo Ray Tracing model experimentsThe generated data set is biogeochemically and biogeophysically coherent and consistent [ABSTRACT FROM AUTHOR]

Improving tropical forest current biomass estimates can help more accurately evaluate ecosystem services in tropical forests. The Global Ecosystem Dynamics Investigation (GEDI) lidar provides detailed 3D forest structure and height data, which can be used to improve above‐ground biomass estimates. However, there is still debate on how best to predict tropical forest biomass using GEDI data. Here we compare stand biomass predicted by GEDI data with the observed data of 2,102 inventory plots in tropical forests and find that adding a remotely sensed (RS) trait map of leaf mass area (LMA) significantly (P < 0.001) improves field biomass predictions, but by only a small amount (r2 = 0.01). However, it may also help reduce the bias of the residuals because there was a negative relationship between both LMA (r2 of 0.34) and percentage of phosphorus (%P, r2 = 0.31) and residuals. Leaf spectral data (400–1,075 nm) from 523 individual trees along a Peruvian tropical forest elevation gradient predicted Diameter at Breast height (DBH) (the critical measurement underlying plot biomass) with an r2 = 0.01 and LMA predicts DBH with an r2 = 0.04. Other data sets may offer further improvements and max temperature (Tmax) predicts Amazonian biomass residuals with an r2 of 0.76 (N = 66). Finally, for a network of net primary production (NPP) and gross primary production (GPP) plots (N = 21), leaf traits predicted with remote sensing are better at predicting fluxes than structure variables. Overall, trait maps, especially future improved ones produced by Surface Biology Geology, may improve biomass and carbon flux predictions by a small but significant amount. Plain Language Summary: Improving predictions of tropical forest biomass can help us to fight climate change. In this paper, we tried to improve tropical forest biomass predictions of satellite lidar (Global Ecosystem Dynamics Investigation) by adding remote sensed estimates of leaf traits. Leaf traits like leaf mass area or phosphorus slightly improved predictions of forest biomass with both a ground data set and a remotely sensed data set. Further, remotely sensed trait data could help explain the differences in the prediction of remotely sensed biomass compared with field derived biomass (residuals). Maximum temperature, but not soil fertility, also improved biomass predictions. Remotely sensed leaf traits were better than structure, like tree height, for predicting net primary production (NPP) and gross primary production (GPP). Future improved hyperspectral satellite data may be used to further improve predictions of biomass, NPP and GPP. Key Points: Both field measured and remotely sensed trait data improved biomass predictions, but only by a small amountIn the Amazon region, maximum temperature, but not soil fertility, improved biomass predictionsTrait data was better than structure data for predicting tropical forest net primary production and gross primary production [ABSTRACT FROM AUTHOR]

Chloromethane (CH3Cl) is the most abundant natural chlorinated organic compound in the atmosphere playing an important role in catalyzing stratospheric ozone loss. Vegetation emits the largest amounts of CH3Cl to the atmosphere but its source strength is highly uncertain leading also to large uncertainties in the global budget of CH3Cl. Triple‐element stable isotope analysis may help to reduce uncertainties because it provides additional process‐level information compared to conventional quantification methods. In this study we performed experiments to obtain a first triple‐elemental isotopic fingerprint (2H, 13C, 37Cl) of CH3Cl emitted by a relevant plant species (royal fern, Osmunda regalis). Isotopic values of all three elements showed considerable differences compared to isotopic values of industrially manufactured CH3Cl which bodes well for future applications to distinguish individual sources. Isotopic analysis of potential precursors (rain, methoxy groups) of CH3Cl in plants revealed no measurable change of hydrogen and chlorine isotopic ratios during formation which may provide a simpler route to estimate the isotopic composition of CH3Cl emissions. Plant degradation experiments of CH3Cl were carried out with club moss (Selaginella kraussiana) revealing significant isotopic fractionation for all three elements. The fractionation pattern characterized by epsilon and lambda is inconsistent with known biotic dechlorination reactions indicating a yet unreported biotic degradation mechanism for CH3Cl. Overall, this study provides first insights into the triple‐elemental isotopic fingerprint of plant emissions and degradation. The results may represent important input data for future isotope‐based models to improve global budget estimates of CH3Cl and to explore the yet unknown degradation pathways. Plain Language Summary: Chloromethane is the most abundant chlorinated organic compound in the atmosphere. It contributes to the destruction of the ozone layer that protects us from skin cancer and genetic damage. Currently, we do not have a good understanding of the sources and removal processes of chloromethane in the atmosphere. In this paper, we use a technique that takes advantage of the different varieties of a chemical element. These so‐called isotopes behave differently during chemical reactions that lead to individual isotopic fingerprints depending on the source or removal process. We used isotopic fingerprints of all three chemical elements in chloromethane and showed that chloromethane produced by a plant (royal fern) differs substantially from chloromethane manufactured by industry. Other plant species such as club moss are able to remove chloromethane from the atmosphere but it is often not clear how this occurs. Isotopic analysis revealed that the studied club moss uses a unique, thus far unknown, way to break down chloromethane. This study demonstrates how information extracted from isotopic fingerprints will help to improve our understanding of sources and removal processes of chloromethane in the atmosphere. It can help to better predict how ozone destruction in the stratosphere affects us in the future. Key Points: First triple‐element isotopic characterization of plant CH3Cl emission and degradationPlant degradation experiments suggest another yet unknown transformation pathwayImportant input data for future isotope based models to improve understanding of global CH3Cl budget [ABSTRACT FROM AUTHOR]

Enigmatic is a word that often comes up in discussions about Proterozoic molar tooth carbonate structures (MTS). But when unusual features such as these are common in rocks of a particular age, there is almost always an important message waiting to be discovered. In this case, the observed temporal patterns for MTS likely track first‐order trends in evolving compositions in the oceans during Earth's middle history when CO2 in the atmosphere and carbonate saturation in the ocean were high but declining and oxygen (O2) in the ocean‐atmosphere system was on the rise. A new paper by Tang et al. (2023, https://doi.org/10.1029/2022JG007077) gives us a new way to think about MTS origins, and nested within their model are wide ranging implicit and explicit linkages to Earth surface evolution as life was becoming more complex in a slow march toward the world we know today. Key Points: Temporal patterns for molar tooth carbonate structures (MTS) likely track first‐order trends in evolving compositions in the oceans and atmosphereEarth's middle chapters, because of prevailing redox and ocean compositions, were an ideal window for MTS formationMTS represent the transition from high to lower atmospheric carbon dioxide and low to higher biospheric oxygen [ABSTRACT FROM AUTHOR]

The long‐term monitoring of gross primary production (GPP) is crucial to the assessment of the carbon cycle of terrestrial ecosystems. In this study, a well‐known machine learning model (random forest, RF) is established to reconstruct the global GPP data set named ECGC_GPP. The model distinguished nine functional plant types, including C3 and C4 crops, using eddy fluxes, meteorological variables, and leaf area index (LAI) as training data of RF model. Based on ERA5_Land and the corrected GEOV2 data, global monthly GPP data set at a 0.05° resolution from 1999 to 2019 was estimated. The results showed that the RF model could explain 74.81% of the monthly variation of GPP in the testing data set, of which the average contribution of LAI reached 41.73%. The average annual and standard deviation of GPP during 1999–2019 were 117.14 ± 1.51 Pg C yr−1, with an upward trend of 0.21 Pg C yr−2 (p < 0.01). By using the plant functional type classification, the underestimation of cropland is improved. Therefore, ECGC_GPP provides reasonable global spatial pattern and long‐term trend of annual GPP. Plain Language Summary: Accurate estimation of gross primary production (GPP) is critical for understanding the terrestrial ecosystem carbon cycle. There are a variety of GPP data sets based on different methods, but huge differences validated by the GPP measured values of flux observation towers still exist. At present, a large amount of GPP measured data provides us with the opportunity to use machine learning models to estimate global GPP. This paper presents a new global GPP data set (ECGC_GPP) with 0.05° and monthly scales from 1999 to 2019. This GPP data set is based on random forest model and driven by remote sensing data from GEOV2 and climate data from ERA5_Land. In ECGC_GPP, site‐level training models are constructed based on plant functional types (especially C3 and C4 crops) to improve accuracy. All these improvements are aimed at improving the lack of interannual fluctuations and the underestimation of cropland in current machine learning data set. Key Points: The accuracy of gross primary production (GPP) estimation can be improved by distinguishing plant functional types, especially for C3 and C4 cropsSignificant increasing trend is found in this random forest‐based data setLeaf area index plays a leading role in both the average state and long‐term trend of GPP [ABSTRACT FROM AUTHOR]

Concentration‐discharge (C‐Q) relationships of total suspended solids (TSS), total dissolved solids (TDS), particulate organic carbon (POC), and dissolved organic carbon (DOC) were investigated in the tributaries and main‐stems of two mountainous river systems with distinct watershed characteristics (Eel and Umpqua rivers) in Northern California and central Oregon (USA). Power‐law (C = a × Qb) fits to the data showed strong transport‐limited behavior (b > 1) by TSS and POC, moderate transport limitation of DOC (b > 0.3) and chemostatic behavior (b < 0) by TDS in most streams. These contrasts led to significant compositional differences at varying discharge levels, with particle‐bound constituents becoming increasingly important (relative abundances of 50% to >90%) at high‐flow conditions. Organic carbon contents of TSS displayed marked decreases with discharge whereas they increased in TDS during high‐flow conditions. Daily and cumulative material fluxes for different coastal streams were calculated using the C‐Q relationships and showed that the delivery of transport‐limited constituents, such as TSS and POC (and DOC to a lesser degree), was closely tied to high‐discharge events and occurred primarily during the winter season. The coherence between winter fluxes and high wave‐southerly wind conditions along the coast highlights how seasonal and inter‐annual differences in fluvial discharge patterns affect the fate of land‐derived materials delivered to coastal regions. Plain Language Summary: Rivers play a key role in transporting materials from land to the ocean. In this study, we investigated several streams of different characteristics from two basins, the Eel River in Northern California and the Umpqua River in central Oregon. We measured how the concentrations of dissolved and particulate materials, including total suspended and dissolved solids and particulate and dissolved organic carbon, varied as a function of river flow. Our results show that different streams export these materials in different ways depending on the level of river flow and certain watershed characteristics. The different trends with river flow exhibited by these constituents impact the total amounts exported by rivers each year as well as the timing of their export. The latter is important because ocean conditions off the Eel and Umpqua rivers exhibit marked contrasts in winds, currents, and waves depending on the season. In the paper, we explore how the combination of the timing of export by the river and the ocean conditions offshore influences the distribution and cycling of particulate and dissolved materials from land in the coastal ocean. Key Points: Concentration‐discharge relationships for different constituents show marked variability among streams from different watershedsTotal suspended solids, particulate organic carbon, and to a lesser degree, dissolved organic carbon exhibit transport limitationThe magnitude and composition of constituent fluxes display variability at distinct time scales that affect their transport to the ocean [ABSTRACT FROM AUTHOR]

The Amundsen Sea Embayment in West Antarctica is experiencing rapid ice mass loss, resulting in biogeochemical changes via altered nutrient and organic matter supply. However, organic carbon released from melting ice has not yet been accurately quantified. In this paper, we have integrated new dissolved organic carbon (DOC) data obtained close to the melting Dotson Ice Shelf (DIS) with published radiocarbon (Δ14C) data on sinking and suspended particulate organic carbon (POC), sedimentary OC, DOC and dissolved inorganic carbon to quantify the effect of ice melt to the carbon cycle. Elevated DOC concentrations in deep water near the DIS indicate the transport of carbon sources from the ice shelf to the water column at a rate of 4.6 ± 2.0 × 1010 g C yr−1. Furthermore, Δ14C‐DOC measurements suggest there is a possible dark chemoautotrophic production under the influence of meltwater input. The vertical profile of Δ14C in the sedimentary OC from the Sea Ice Zone and the edge of the DIS demonstrates the presence of aged organic carbon sources during warm episodes at ∼11.5 and 15.9 ka BP. Our study indicates that deep water is not only affected by OC discharge from meltwater but also by biological processes due to altered nutrient inputs. Limited data hampers a precise assessment of the influence of meltwater on the carbon cycle. Further sampling in front of the DIS will be beneficial to enhance our understanding of the role of Antarctic Ice Sheet melting in the downstream ecosystem. Plain Language Summary: The Amundsen Sea, in West Antarctica, is experiencing rapid ice melting because of a warming climate. As found in previous studies conducted in these seasonally ice‐free areas, nutrients released from melting ice sheets and upwelled by buoyant melt water stimulate surface primary production, which in return increases the surface uptake of CO2 in these regions. However, the direct release of organic carbon from melting ice has not been accurately quantified. To address this issue, we conducted radiocarbon analysis of dissolved organic carbon in water samples collected near the melting ice shelf in the Amundsen Sea. Available radiocarbon results from sedimentary organic carbon and sinking POC demonstrate that a warming climate may trigger the release of aged organic carbon from subglacial sediments. Our finding indicates the deep water in the regions is going through a biological process under the influence of meltwater input. Further sampling will be needed for the investigation of the role of meltwater in downstream ecosystems. Key Points: Elevated dissolved organic carbon (DOC) concentrations in front of the Dotson Ice Shelf (DIS) indicate an influence from the melting ice shelf and subglacial dischargeΔ14C‐DOC results demonstrate that meltwater has the potential to increase carbon uptake in the water column via chemoautotrophic productionExtra aged organic carbon sources for sedimentary OC in the Amundsen Sea Embayment during the warm episodes at ∼11.5 and 15.9 ka BP [ABSTRACT FROM AUTHOR]

For years, carbon cycle scientists have sought to understand how a warming climate will impact the decay of soil carbon. However, there have been relatively few investigations of how soils will warm in comparison to the atmosphere. Three recent papers in American Geophysical Union journals have looked at expected soil warming by synthesizing predictions in the Climate Model Intercomparison Project 5 (CMIP5). Collectively, these papers show that soil warming will keep pace with air warming except where snow and ice occur, and that the magnitude of soil warming in northern latitudes is uncertain due to model variability in snow and ice extent. They also show that a considerable portion of anthropogenic warming is being stored in deep soils, and that in comparison to observations, soil heat storage is underrepresented by land models. These studies highlight how important continued investigations of soil climatology are to understanding carbon cycling and Earth energy balance. Key Points: Three recent papers examined soil warming predictions over the 21st centuryThey show air warming is a good proxy for soil warming, except at high latitudesMore efforts to measure and model soil temperatures will broadly benefit the biogeosciences and climate change science [ABSTRACT FROM AUTHOR]

The editorial team at JGR: Biogeosciences would like to extend thanks to the 2020 reviewers who offered their time and expertize to help us make decisions on and improve papers. Key Point: We thank all 2020 reviewers for their contributions [ABSTRACT FROM AUTHOR]

Breithaupt et al. (2020, https://doi.org/10.1029/2019JG005349) investigated why rates of organic carbon (OC) burial in coastal wetlands appear to increase over the past ∼120 years. After comparing dating methods and applying biogeochemical analyses, we concluded that neither dating method nor carbon degradation contribute to the observed trend. Rather, we concluded that OC burial has increased in the past century. Parkinson's (2021) Comment disagrees with our conclusion, contending that: (1) use of a density correction to account for soil auto‐compaction is a flawed methodology that artificially shortens a core's length, (2) there is limited evidence for an acceleration in the regional sea‐level rise (SLR) rate, and (3) vertical accretion rates in previous papers by Breithaupt et al. (2014, https://doi.org/10.1002/2014JG002715; 2017, https://doi.org/10.1016/j.margeo.2017.07.002) are lower than the regional mean rate of SLR and are not to be believed as these wetlands should have converted to open water by now. We reject these contentions because: (1) no density correction was applied to the cores in this study, (2) local tide gauge records and analyses in the literature support an increase in SLR rates coinciding with the timeframe of our OC burial records, and (3) Parkinson's comparison of the 100‐yr mean rate of SLR neglects temporal variability and uncertainties in the long‐term sea‐level record, as well as biophysical feedbacks between wetland surface elevation and SLR. Here, we provide detailed responses to Parkinson's contentions and establish the importance of differentiating operational definitions of OC burial and accretion to clarify why an auto‐compaction correction is not applicable for OC burial measurements. Key Points: Organic carbon burial rates are not altered by auto‐compaction and do not include a density correctionIncreasing rates of sea‐level rise are supported by regional data and analyses from the literature [ABSTRACT FROM AUTHOR]

The El Niño‐Southern Oscillation (ENSO) in the equatorial Pacific is the dominant mode of global air‐sea carbon dioxide (CO2) flux interannual variability (IAV). Air‐sea CO2 fluxes are driven by the difference between atmospheric and surface ocean pCO2, with variability of the latter driving flux variability. Previous studies found that models in Coupled Model Intercomparison Project Phase 5 (CMIP5) failed to reproduce the observed ENSO‐related pattern of CO2 fluxes and had weak pCO2 IAV, which were explained by both weak upwelling IAV and weak mean vertical dissolved inorganic carbon (DIC) gradients. We assess whether the latest generation of CMIP6 models can reproduce equatorial Pacific pCO2 IAV by validating models against observations‐based data products. We decompose pCO2 IAV into thermally and non‐thermally driven anomalies to examine the balance between these competing anomalies, which explain the total pCO2 IAV. The majority of CMIP6 models underestimate pCO2 IAV, while they overestimate sea surface temperature IAV. Insufficient compensation of non‐thermal pCO2 to thermal pCO2 IAV in models results in weak total pCO2 IAV. We compare the relative strengths of the vertical transport of temperature and DIC and evaluate their contributions to thermal and non‐thermal pCO2 anomalies. Model‐to‐observations‐based product comparisons reveal that modeled mean vertical DIC gradients are biased weak relative to their mean vertical temperature gradients, but upwelling acting on these gradients is insufficient to explain the relative magnitudes of thermal and non‐thermal pCO2 anomalies. Plain Language Summary: To date, the global ocean has been responsible for absorbing over a third of carbon dioxide (CO2) emissions, slowing down the growth of atmospheric CO2 levels which drives global warming. Of interest is the equatorial Pacific Ocean, which is the largest oceanic source of CO2 to the atmosphere with large fluctuations that are apparent in the record of global atmospheric CO2. To study the ocean's ability to absorb future CO2 emissions, we need models of the Earth system that can accurately capture fluctuations in the equatorial Pacific. In this paper, we assess surface ocean CO2 fluctuations in the equatorial Pacific in the latest generation of models and we examine their deviations from observations. Compared to observations, models underestimate surface ocean CO2 fluctuations as a result of excessive cancellation between competing drivers of CO2 change. We find that the vertical gradient of carbon in models is too weak, which through ocean circulation, would contribute to weak surface CO2 fluctuations. However, this does not fully account for underestimations in surface CO2 fluctuations. Other processes have a significant role in excessively canceling surface CO2 concentrations and requires further research. Key Points: The majority of models underestimate pCO2 IAV, while they overestimate sea surface temperature IAVThe ratio of non‐thermal‐to‐thermal pCO2 IAV is systematically underestimated in models, which results in weak total pCO2 IAVVertical dissolved inorganic carbon gradients are biased weak more than temperature gradients, but this alone doesn't explain the relative sizes of pCO2 components [ABSTRACT FROM AUTHOR]

This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 400–2,500 nm and an average spectral resolution less than 12 nm and a spatial resolution of 30 m/pixel. This study focuses on the wildfire temperature estimation over the Bootleg Fire, US 2021. The analysis starts by considering the Hyperspectral Fire Detection Index (HFDI) which is used to analyze the informative content of the images, along with the analysis of some specific visible, near‐infrared and shortwave‐infrared bands. This first analysis is used as input to perform a temperature estimation of the areas with active wildfire. Surface temperature is retrieved using PRISMA radiance and a linear mixing model based on two background components (vegetation and burn scar) and two active fire components. PRISMA temperatures are compared with LST (Land Surface Temperature) products from NASA's ECOSTRESS and Landsat 8 which imaged the Bootleg Fire before and after PRISMA. A critical discussion of the results obtained with PRISMA is presented, followed by the advantages and limitation of the proposed approach. Plain Language Summary: This work explores new opportunities for wildfire mapping and monitoring basing on recent technological achievements in the field of remote sensing and data analysis. The input data of this research study are provided by the new satellite PRISMA (Precursore IperSpettrale della Missione Applicativa, Hyperspectral Precursor of the Application Mission) from ASI (Agenzia Spaziale Italiana, Italian Space Agency). This spacecraft represents an innovative remote sensing mission for the observation of the Earth, as it provides images with a revolutionary quantity of spectral information which go far beyond the visible spectrum. Using PRISMA data, we study the Bootleg Fire during 2021 in the US, providing a descriptive analysis of the wildfire and a quantitative estimation of the temperatures achieved during the event. To confirm the results of our approach, we also compare the outcomes to the data provided by two other satellite missions: ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment) and Landsat 8. Hence, a critical discussion of the results obtained with PRISMA is presented in order to report advantages and limitation of the proposed approach. Key Points: Hyperspectral fire index for PRISMA data has been retrieved to create a wildfire detection map of Bootleg Fire, Oregon 2021Hot temperatures of wildfire has been estimated by applying linear mixture analysis to PRISMA dataMultisensor approach has been used to characterize Bootleg wildfire temperature evolution [ABSTRACT FROM AUTHOR]

This paper discusses different feature selection methods and CO2 flux data sets with a varying quality‐quantity balance for the application of a Random Forest model to predict daily CO2 fluxes at 250 m spatial resolution for the Rur catchment area in western Germany between 2010 and 2018. Measurements from eddy covariance stations of different ecosystem types, remotely sensed vegetation data from MODIS, and COSMO‐REA6 reanalysis data were used to train the model and predictions were validated by a spatial and temporal validation scheme. Results show the capabilities of a backwards feature elimination to remove irrelevant variables and an importance of high‐quality‐low‐quantity flux data set to improve predictions. However, results also show that spatial prediction is more difficult than temporal prediction by reflecting the mean value accurately though underestimating the variance of CO2 fluxes. Vegetated parts of the catchment acted as a CO2 sink during the investigation period, net capturing about 237 g C m−2 y−1. Croplands, coniferous forests, deciduous forests and grasslands were all sinks on average. The highest uptake was predicted to occur in late spring and early summer, while the catchment was a CO2 source in fall and winter. In conclusion, the Random Forest model predicted a narrower distribution of CO2 fluxes, though our methodological improvements look promising in order to achieve high‐resolution net ecosystem exchange data sets at the regional scale. Plain Language Summary: Whether ecosystems absorb or emit CO2 plays a major role in the global carbon cycle and impacts climate change. This exchange is already measured at scattered stations, but creating spatially resolved data sets remains a challenge. In this paper, we used satellite images of vegetation and meteorological data to predict the CO2 exchange of the Rur catchment area near the German‐Dutch‐Belgian border for every day from 2010 to 2018. In order to assess the prediction quality, we compared actual measurements from several stations within the catchment with the predictions at the locations of these stations. Results show that our method could increase prediction quality compared to previous process‐based models, though the error remains rather high. Vegetated parts of the catchment including coniferous forests, deciduous forests, grasslands, and croplands were all CO2 sinks on average. In late spring and early summer, they were the strongest sink, but in fall and winter a CO2 source. Key Points: CO2 flux upscaling with Random Forest can be improved with a backward feature elimination and strict quality control of flux dataVegetated parts of the Rur catchment were predicted to be a CO2 sink on average, with the highest uptake in late spring and early summerThe Enhanced Vegetation Index and potential evapotranspiration are useful predictors for the regionalization of CO2 flux measurements [ABSTRACT FROM AUTHOR]

Lakes in the Alpine region are recognized as critical methane (CH4) emitters, but a robust characterization of the magnitude and variability of CH4 fluxes is missing. We developed a mobile platform for CH4 eddy covariance (EC) flux measurements to tackle this gap. The mobile system was deployed at nine lakes across a latitudinal transect in the Alps and validated by comparing the measured fluxes with fixed on‐shore EC station and to chamber and boundary layer flux estimates. Our approach was shown to be well suited to capture different CH4 emission pathways and to integrate the within lake variability, therefore, overcoming the limitations of other methods (e.g., boundary layer method). Additionally, this mobile system offers a tool to characterize inter‐lake variability of fluxes with consistent measurements. Methane fluxes were explained by dissolved nitrogen, total phosphorus, dissolved oxygen, seston and lake size. The highest fluxes and most substantial seasonal variability were found in a shallow low‐altitude lake in the Southern Alps. We suggest that characterizing the intra‐lake emission heterogeneity and consistent measurements for a better understanding of inter‐lake emission differences is fundamental for a solid estimate of freshwater CH4 budgets. Plain Language Summary: Our paper focuses on lakes in the Alpine region that release a greenhouse gas called methane (CH4) which is relevant for global warming. Even though we know these lakes emit methane, there is still the need to understand how much is released and how it changes over time. To address this, we built a special mobile tool to measure methane emissions using a method called eddy covariance. Eddy covariance is used to measure the exchange of gases, like methane, between the Earth's surface and the atmosphere by tracking the local changes in wind speed and gas concentration. We tested our mobile tool at nine different lakes across the eastern Alps and compared our measurements with data from common methods like estimating methane from the water close to the lake's surface. We found that the presence of nutrients, the lake's size, and the organic material in the water were associated with how much methane is released. Our mobile tool also helped us describe the variability of methane emissions among different parts of the same lake. This information is crucial because it helps us figure out how much methane these lakes are releasing and better understand the differences between lakes. Key Points: We developed and validated a mobile eddy covariance platform for capturing CH4 fluxes across lakes in the Alpine region for 2 yearsCH4 emissions varied substantially within and among the studied lakes which need consideration for accurate emission assessmentsStatistical models with a few in situ physicochemical and biological variables could describe the observed CH4 fluxes [ABSTRACT FROM AUTHOR]

We explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO2) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO2 and methane (CH4) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide. Plain Language Summary: The breathing of the biosphere can be assessed by measuring the fluxes of carbon dioxide, methane and water vapor. Attribution of the biophysical controls of these fluxes is often complex as these forcings can be non‐linear or conditional. We introduce an alternative statistical method that is better suited to disentangle the complex and non‐linear interaction of biophysical forcings on the trace gas emissions. It is called Alternating Conditional Expectations. In this paper, we demonstrate the efficacy of this method with test cases over a savanna woodland and a tidal wetland ecosystem. The method provides new insights on how these trace gas fluxes are modulated. Key Points: Alternating Conditional Expectations can define the shapes of non‐linear biophysical forcings on trace gas fluxesSimple statistical models can explain over 80%–90% of the variance in fluxesMethod is robust for test cases over ecosystems in dry and wet conditions [ABSTRACT FROM AUTHOR]

The sedimentary records of organic matter in lakes can reflect the response of lakes to global warming. Multiple organic proxies in the sediment core samples collected from Luoma Lake and Hongze Lake in Jiangsu were used to expound the effects of global warming and anthropogenic activities on lacustrine productivity and deposition of polycyclic aromatic hydrocarbons (PAHs). Total organic carbon, algal organic matter proxies (S2 and hydrogen index), and nutrients such as total phosphorus and total nitrogen were measured. The source apportionment modeling and the principal component analysis demonstrated that algal organic matter and bacteria organic matter showed an upcore increasing trend and an obvious enrichment effect on PAHs, which was also related to the increasing temperature and algal productivity in the lakes. Global warming enhanced the lacustrine productivity and the accumulation of PAHs in sediments. Therefore, the organic geochemical indicators in lake sediments can effectively reflect the impact of climate warming on the lacustrine productivity and the accumulation of PAHs, and provide data support for the management of lakes. Plain Language Summary: The impact of global warming on the environment is increasing, and previous research was mainly on the polar region, and there are relatively few studies on the impact on inland lake environments. In this paper, a typical organic pollutant, polycyclic aromatic hydrocarbons (PAHs), is taken as the starting point, and two lakes in eastern China, Luoma Lake, and Hongze Lake, are taken as the research objects. The sedimentary records of diatoms and bacteria were also analyzed to explore the interaction between diatoms and bacteria in the lake and PAHs. The results showed that diatoms had bioaccumulation effects on PAHs, especially HMW‐PAHs, and bacteria were the main contributors to the secondary productivity of the lake. In addition, changes in atmospheric temperature of Xuzhou and Bengbu recorded by weather stations near the lake show that the average annual atmospheric temperature has risen by nearly 2°C over the past 70 years, indicating a warming phenomenon in the region. Next, we analyzed the three factors related to algal growth in lakes, temperature, total nitrogen, and total phosphorus, and correlated them with PAH content and algal and bacterial biomarker content. There were significant positive correlations, especially for HMW‐PAHs, indicating that the increase in plankton productivity caused by climate warming promotes the accumulation of HMW‐PAHs in lake sediments. Key Points: The source apportionment model demonstrated the increasing aquatic productivityGlobal warming enhanced the accumulation of aquatic organic matterThe increasing aquatic productivity was critical to the bioaccumulation of polycyclic aromatic hydrocarbon [ABSTRACT FROM AUTHOR]

The highly interactive and variable nature of scales of space and time featured in components of the Earth system imparts enormous complexity to land‐atmosphere interactions. Here, we introduce an open special collection on Advances in Scaling and Modeling of Land‐Atmosphere Interactions that features articles in JGR: Biogeosciences, JGR: Atmospheres, Journal of Advances in the Modeling of Earth Systems, and Earth & Space Science. Collectively, these articles identify interactions across multiple processes, in field experiments, long‐term observations, and numerical simulations, which are then used to advance theories of scale interaction to improve predictive models. Plain Language Summary: Scale refers to the patterns in space and oscillations in time of features in our universe. The Earth system features a wide range of scales. Understanding the processes that explain the size, shape, regularity, and changes in those scales looms large in our science. Land‐atmosphere interaction refers to the ways that organisms and elements of the land surface influence the structure and evolution of the atmosphere and in turn, how weather and climate processes influence the ground. Numerous studies through coordinated field experiments and computer simulations have helped us advance understanding of how scale influences land‐atmosphere interaction. We introduce a special collection that documents many of those. Key Points: Scaling in space and time is an essential foundation for understanding land‐atmosphere interactionsA series of papers in this collection demonstrate scale‐related advances in a number of areasCoordination of research across disciplines is needed [ABSTRACT FROM AUTHOR]

Measurements of carbonyl sulfide (OCS) enable independent estimates of regional stomatal conductance provided that non‐stomatal OCS fluxes are well constrained. OCS is taken up through plant leaves, following the same pathway as CO2; in contrast to CO2, OCS is irreversibly destroyed in plant leaves and plants do not typically exhibit OCS emissions. Ecosystem uptake of OCS can indicate changes in stomatal opening. Here we present an empirical model to assess the potential impact of soil OCS exchange, the non‐Stomatal OCS exchange Empirical Model (SOCSEM, version 0). We created biome‐specific response curves characterizing soil OCS exchange and restricted the model design to require only knowledge of soil moisture and surface temperature because remote sensing observations are available for these two features. Comparing the model to field‐based chamber observations reveal deviations that can be attributed to missing complexity of the ground surface (having excluded litter and plants without regulated stomata), shortwave radiation, or the soil environment. For agricultural regions with known net emissions, we use remotely‐sensed surface temperature data and demonstrate that data resolution can affect anticipated fluxes. We further investigate the influence of regions with unknown soil OCS responses, for example, Arctic tundra. We compare our model to a process‐based and respiration‐based soil OCS exchange model that has been implemented in a land surface model. Further field study of tropical and arctic ecosystems in conjunction with studies of non‐stomatal surfaces in addition to soil (e.g., bryophytes) will increase confidence in applying OCS as a regional tracer for stomatal conductance. Plain Language Summary: Carbonyl sulfide (OCS) uptake over ecosystems is a good proxy for land carbon uptake via photosynthesis when non‐plant OCS exchange is small or at least knowable. From what we have observed, soil OCS fluxes are typically overwhelmed by plant‐based OCS uptake except in the case of wetland soils or when agricultural fields have become hot and dry. In this paper we constructed a model that estimates where soil OCS "hot spots" occur and how important they are for the global balance of OCS. Although this process is known to be fairly complicated, our model uses only soil moisture and surface temperature because these are the two most impactful parameters that can also be observed from space. We identify several potential causes of model‐observation mismatches. For some regions of the world, like the Arctic tundra, there are no published observations and we hypothesize what the OCS exchange might be based on other ecosystems with similar traits. Overall, we note that soil OCS exchange is still much smaller than other surface sinks despite uncertainties. Key Points: Characterizing non‐stomatal fluxes of carbonyl sulfide (OCS) is necessary to use OCS as a tracer of stomatal conductanceWe construct an empirical model of soil‐OCS fluxes based on long term field flux observations and lab incubation dataThe cause of deviations between model output and observations are explored using field observations from in‐tact surfaces [ABSTRACT FROM AUTHOR]

In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH4) flux. In the first part of the study, we used a CH4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint‐Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m−2 s−1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m−2 s−1. This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy‐covariance towers and creates important insights for the interpretation of hot spots of CH4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH4 flux. Plain Language Summary: Wetlands are capable of sequestering large amounts of carbon in their soils but they also emit about a third of all the methane emissions to the atmosphere. These methane emissions vary significantly in space, with some places becoming hot spots of methane flux that so far remain understudied. In this paper, we present a new method to map the spatial heterogeneity in methane fluxes in wetlands as measured by flux towers called eddy covariance towers. We find that this new technique can be used to map the spatial heterogeneity in fluxes of multiple greenhouse gases, with a special ability to map hot spots of methane flux. The presence and the magnitude of these hot spots are validated using chamber measurements finding satisfactory results. This technique paves the way for future studies whose goal is to understand what are the chemical and microbiological processes in the soils leading to these high methane emissions, and thus create strategies to better model and mitigate the consequent warming of the atmosphere. Key Points: We mapped hot spots of methane flux in wetlands using Footprint‐Weighted Flux Maps and validated them using tracer releases and chambersThe proposed method provides mapping of the spatial heterogeneity in sources/sinks of trace gases around eddy covariance towersThe flux footprint model of Kormann & Meixner (2001) had the best performance based on a methane release experiment [ABSTRACT FROM AUTHOR]

Peatland carbon stores are under widespread anthropogenic pressure, resulting in degradation and carbon loss. This paper presents DO14C (Dissolved Organic Carbon) dates from waters draining two eroded blanket peatland catchments in the UK. Both catchments are characterized by severe gully erosion but one additionally has extensive surface erosion on unvegetated surfaces. DO14C values ranged from 104.3 to 88.6 percent modern (present to 976 Before Present). The oldest DOC dates came from the catchment characterized by both gully and surface erosion and are among the oldest reported from waters draining temperate peatlands. Together with peat age‐depth data from across the peatland landscape, the DO14C ages identify where in the peat profile carbon loss is occurring. Source depths were compared with modeled water table data indicating that in the catchment where gully erosion alone dominated, mean water table was a key control on depth of DOC production. In the system exhibiting both gully erosion and surface erosion, DOC ages were younger than expected from the age of surficial peats and measured water tables. This may indicate either that the old organic matter exposed at the surface by erosion is less labile or that there are modifications of hydrological flow pathways. Our data indicate that eroded peatlands are losing carbon from depth, and that erosion form may be a control on carbon loss. Our approach uses point measurements of DO14C to indicate DOC source depths and has the potential to act as an indicator of peatland function in degraded and restored systems. Plain Language Summary: Peatlands are the largest terrestrial soil carbon store, but are under widespread anthropogenic pressure, resulting in degradation and carbon loss. In this study of UK upland peatlands, we used radiocarbon dating of dissolved organic carbon (DOC) from waters draining eroded peatlands to identify the age of the carbon that has been lost. These dates are among the oldest reported from waters draining temperate peatlands. The dates combined with age‐depth data from across the peatland landscape allowed us to model where in the peat profile the carbon loss was concentrated. We compared these results with water table data and found that in the systems we studied, the type of peatland erosion that the system had experienced was an important factor controlling the age of carbon lost. The close association between radiocarbon age of carbon and water table suggested that radiocarbon dating of DOC might be a useful catchment scale proxy for water table, a direct measurement of the locus of carbon loss from the peat, and an effective measure of the overall "health" of the peatland ecosystem. The approach therefore has potential as a rapid method of assessing stabilization and restoration of intact peatland function. Key Points: We present old 14C dates from waters draining eroded temperate peats, caused by deep C loss and low water tables in gullied peatsNovel approaches to dissolved organic carbon source identification indicate that water table drawdown and the nature of peat erosion influence loss of old carbonOur method has potential as a rapid way to indicate peatland function and assess restoration success [ABSTRACT FROM AUTHOR]

This study documents annual carbon stocks and fluxes from 1986 to 2010 at 30‐m resolution across southeastern U.S. forests, analyzing trends and regional greenhouse gas exchange. We used forest inventory data to guide a carbon cycle model representing postdisturbance carbon dynamics for diverse forest and site conditions. We mapped carbon stocks and fluxes with stand age inferred from spaceborne disturbance monitoring and biomass. We assessed the fate of harvested biomass with a wood products model. We found that pine forests experienced the largest biomass removals, with paper products leading all end‐uses. Averaging across all SE forestlands, mean annual net ecosystem productivity decreased from 116 gC · m−2 · year−1 in 1986 to 71 gC · m−2 · year−1 in 2007, and 85 gC · m−2 · year−1 in 2010, equating to a range of 25 to 41 Tg C/year (mean of 34 Tg C/year). Interannual variability in forest‐atmosphere carbon exchange is dominated by the extent of harvesting, with removals ranging from 23 to 56 Tg C/year. Region‐wide live biomass stocks varied little over time, averaging 5.0 kg C/m2 for aboveground biomass or 1,780 TgC, with average annual biomass growth balanced by harvest removals. However, net biome productivity exhibited large interannual variability, spanning a sink of 16 Tg C/year in 1986 to a source of −30 Tg C/year in the year of peak harvest. Two thirds of harvest removals are emitted within 50 years, 8% as methane, causing the forest sector to act as a large CO2‐equivalent source. Uncertainties are estimated at ± 25%. Key Points: We estimate annual carbon stocks and fluxes in southeastern U.S. forests at 30 m with remote sensing, inventory data and a carbon cycle modelNet ecosystem productivity of 34 ± 9 Tg C/year equals harvest removals, leading to no net change in biomassTwo thirds of harvest removals are emitted within 50 years, 8% as methane, causing the forest sector to act as a large CO2‐equivalent source [ABSTRACT FROM AUTHOR]

The Surface Biology and Geology (SBG) concept is the first National Aeronautics and Space Administration (NASA) Earth mission to develop and implement systematic integration of science application needs at the architecture study stage. Prior NASA mission concept and planning activities presumed that science measurement needs would encompasss application measurement needs and so did not explicitly evaluate and include applications at this stage. However, the effort presented here identified, documented and integrated application needs that would not have been included by considering research science needs only. First, a low latency of no greater than 24 hr was identified as the optimal target to enable the maximum number of applications and was then carried through into all SBG candidate architectures. Second, many applications expressed needs around improved spatial and temporal resolution. While increased spatial resolution would not be possible under current cost and technology considerations, the need for improved resolution for temporal sampling helped drive and bolster discussions with international partners such as the European Space Agency, Italian Space Agency, and Centre National D'Etudes Spatiales. Lastly, we found that the applications and science were synergistic with one another; for example, mission concept decisions to consider additional measurement features were driven by both high relevance application and science priorities, and in particular, evapotranspiration for agriculture and high temperature features for fires and geologic hazards. This paper discusses the process and key contributions originating from the SBG Applications Working Group and how they shaped SBG at the architecture study stage. This stage in the mission planning considers the trade space of spacecraft instruments and architectures, and evaluates which formulations are suitable candidates for SBG. The approach described here may be utilized as a framework for applications and science to inform future NASA satellite mission studies. Plain Language Summary: This is the first instance of integration from the perspective of science applications into mission design, and at the architecture study phase. Mission architectures have traditionally been underpinned by science needs only. This effort demonstrates that not only does the applications community confer unique technical and measurement needs that are feasible to integrate into architecture considerations, but also that the overall process for defining mission requirements is enhanced through science and applications synergy and cohesion. Furthermore, applications feed into other aspects of the mission design process at early stages, such as bolstering discussions with international partners and reinforcing the benefits and need of harmonized data products and mission coordination. Key Points: The Surface Biology and Geology study has shown that science and applications can be considered synergistically, at the start of the satellite mission life cycleApplications and science integration produced a more representative and tailored set of measurement needs driving mission architectureApplications conferred unique technical needs, particularly around latency, that were carried through the architecture study [ABSTRACT FROM AUTHOR]

Sulfate is a potential pollutant and important nutrient linked with the nitrogen, carbon, and phosphorus cycles. The importance of different anthropogenic sulfate sources in suburban streams (septic systems, fertilizer, road salt, and infrastructure) is uncertain, and the temporal dynamics of stream export sparsely documented. We study sources and export dynamics of sulfate in suburban and forested headwater catchments. Stream baseflow discharge and sulfate concentrations were strongly positively correlated in both watersheds with the highest values in spring. Suburban concentrations and fluxes (2.48–7.5 mg/L or 25.8–78.1 μM, 16.6 kg/ha/yr) were consistently higher than forested (0.56–2.78 mg/L or 5.8–28.9 μM, 5 kg/ha/yr). Following precipitation, sulfate concentrations in both forested and suburban streams increased to concentrations above pre‐storm values and remained high after peak discharge. These dynamics suggest that both catchments have a large pool of sulfate that can be mobilized under wet conditions. Ridge‐top forest soil samples contained 210 kg/ha stored, extractable sulfate. Current atmospheric sulfate deposition rates (5–7 kg/ha/yr) are approximately in balance with sulfate export in the forested stream. In the suburban watershed, we estimated septic fields contribute up to 11 kg/ha/yr (about half from surfactants) and lawn care up to 4.3 kg/ha/yr and are the most likely sources of elevated stream sulfate. Sulfate sulfur (4.9–5.8‰ forested; 6.1–7.0‰ suburban) and oxygen isotope values (0.7–2.0‰ forested; −0.1–4.1‰ suburban) are consistent with this interpretation, but do not provide strong corroboration due to large variation and overlap in estimated source values. Plain Language Summary: Sulfate can be a nutrient or pollutant that alters stream biogeochemistry depending on dissolved concentrations. For decades, atmospheric sulfur deposition was elevated due to regional anthropogenic emissions. Regulation in the 1990s resulted in decreasing deposition and increasing importance of other sulfur sources, for example, associated with land use. We studied suburban sulfate sources, including infrastructure and activities not widely recognized as sources of stream sulfate. We measured dissolved sulfate concentrations and sulfate tracer isotopes in neighboring forested and suburban watersheds. Sulfate inputs and exports are compared with budgets of possible sulfate contributions to the stream from septic systems, lawn care, road salt, building materials, and historic agriculture. The suburban stream exports about 3x more sulfate a year from the watershed than the forested stream. Extra suburban stream sulfate appears to be largely caused by human waste and cleaning products flowing to septic fields and lawn care. More sulfate is transported to the stream during the wetter spring and after rain. This elevated transport may be because the groundwater table moves upwards during wetter times and transports sulfate that was stored in soil to the stream. Identifying suburban sources of sulfate pollution is important to protecting stream health. Key Points: The suburban stream has elevated sulfate concentrations and fluxes, likely due to contributions from septic systems and lawn careSulfate mobilized in seasonal‐ and event‐scale wet conditions in both forested and suburban streamsSulfate in the suburban stream is associated with soil storage mobilized in wet conditions, not runoff from impervious surfaces [ABSTRACT FROM AUTHOR]

Nitrogen (N) deposition effects on the stoichiometric balance and photosynthetic and hydraulic couplings in subtropical forests has drawn wide attentions. The previously adopted understory application of N fertilization is criticized because it might ignore foliar N retention for different species. This paper reports a fertilizing application from the canopy (CAN) and under the canopy (UAN) in a phosphorus (P) limited ecosystem. Foliage stoichiometric, photosynthetic, and hydraulic traits of six dominant species were measured and analyzed. Both treatments equally enhanced foliage N and N/P, but not foliage P, who was highly species‐specific depending on tree height, which implied enhanced P limitation. Decreased isotope abundance of 15N (δ15N) that approaching to the level in the urea fertilizer under CAN suggested the existence of canopy retention of N. Besides, N response sensitivity of N, P and δ15N that positively related to tree height (H) under CAN indicated different exposure to the added N, which promoted stoichiometric imbalance among species. The photosynthetic traits represented by net photosynthesis (An) increased under both treatments. A divergent foliar photosynthetic and hydraulic traits variation was identified by significant decreased stomatal conductance (gs) and An/gs for CAN treatments, which induced the elevated isotope abundance of 13C (δ13C). Correspondingly, foliage hydraulic traits that shifted to water use efficiency axis were identified only under CAN in principal component analysis. Overall, our results proved that the canopy absorption and species heterogeneity should be considered regarding foliar safety versus efficiency trade‐off in response to nitrogen additions in the future. Plain Language Summary: The nitrogen components released to the atmosphere due to human activities during the past centuries have been mostly transported to the forests via precipitation, which is officially called "wet nitrogen deposition." Just like chemical fertilization in the agriculture, these nitrogen components will not only influence the growth of these "giant crops," but also alter their resistance capacity to harsh environment, such as drought, heat wave and so on. In this study, we simulated a "leaf fertilizer" experiments in a natural forest via many 30 m‐height towers. We checked the leaf performance via some scientific instruments and laboratory tests. We found that the fertilization will lead the plant nutritional imbalance and vulnerability increase, and the taller species will snatch much more resources to suppress shorter one. Besides, we also compared the leaf fertilization with the traditional soil fertilization, who was widely used to study the fertilization effects on these "giant crops." We found that the later did not bring about the plant performances above. Thus, scientists should be more cautious in the future, if they want to know what will happen to the forest under persistent wet nitrogen deposition. Key Points: Although stoichiometric balance was indeed shifted in the subtropical forest, the decoupling of plant photosynthesis and the hydraulic traits was not disturbedThe upper canopy species experience stronger nutrient stoichiometric shifts than the lower‐canopy speciesThe under the canopy application failed to detect the resources redistribution among different species and the strengthened decoupling relation between photosynthesis and hydraulic traits [ABSTRACT FROM AUTHOR]

Sunlight can oxidize dissolved organic carbon (DOC) to dissolved inorganic carbon (DIC) in freshwaters. The importance of complete photooxidation, or photomineralization, as a sink for DOC remains unclear in temperate rivers, as most estimates are restricted to lakes, high latitude rivers, and coastal river plumes. In this study, we construct a model representing over 75,000 river reaches in the Connecticut River Watershed (CRW), USA, to calculate spectrally resolved photomineralization. We test the hypothesis that photomineralization is a negligible DOC sink across all reaches and flow conditions relative to DOC fluxes. Our model quantifies reaction rates and transport drivers within the river reaches for the ranges of flow conditions, incoming solar irradiance, and canopy cover shading observed throughout the year. Our model predicts average daily areal photomineralization rates ranging from 1.16 mg‐C m−2 day−1 in low flow river reaches in the winter, to 18.33 mg‐C m−2 day−1 in high flow river reaches during the summer. Even for high photomineralization fluxes, corresponding photomineralization uptake velocities are typically at least an order of magnitude smaller than those reported for other instream processes. We calculate DOC elimination by photomineralization relative to DOC fluxes through individual stream reaches as well as the entire riverine portion of the CRW. We find that relative photomineralization fluxes are highest in summer drought conditions in low order streams. In median flows and mean light intensities, for an average watershed travel distance, 3%–5% of the DOC fluxes are eliminated, indicating that photomineralization is a minor DOC sink in temperate rivers. Plain Language Summary: Rivers are an important part of the carbon cycle, moving carbon compounds from land to the ocean. Within rivers, dissolved organic carbon molecules can be broken down into inorganic carbon molecules, including the greenhouse gas carbon dioxide. Sunlight shining into rivers can cause these organic molecules to break down in a process called photomineralization, but it is not clear if this process is important compared to the total amount of organic carbon that travels through rivers every day. In this paper, we build a model for the river sections of temperate Connecticut River Watershed, which calculates photomineralization for possible river flow conditions, dissolved organic carbon concentrations, and seasons, and compares the size of the sunlight‐driven breakdown of dissolved organic carbon to the amount of dissolved organic carbon in the river. This is the first model that puts photomineralization rates in the context of a flowing temperate river network. We show that compared with the dissolved organic carbon amounts present in the river at any time of the year or any flow conditions, photomineralization is essentially an unimportant process, removing on average 3%–5% of the dissolved organic carbon through an average watershed river route. Key Points: We build a model calculating reaction and transport drivers for photomineralization in 75,000 temperate river reachesPhotomineralization is a negligible dissolved organic carbon (DOC) sink relative to DOC fluxesDOC elimination by photomineralization in temperate rivers is limited by short water residence times and canopy cover [ABSTRACT FROM AUTHOR]

The ice‐cover period in lakes is increasingly recognized for its distinct combination of physical and biological phenomena and ecological relevance. Knowledge gaps exist where research areas of hydrodynamics, biogeochemistry and biology intersect. For example, density‐driven circulation under ice coincides with an expansion of the anoxic zone, but abiotic and biotic controls on oxygen depletion have not been disentangled, and while heterotrophic microorganisms and migrating phytoplankton often thrive at the oxycline, the extent to which physical processes induce fluxes of heat and substrates that support under‐ice food webs is uncertain. Similarly, increased irradiance in spring can promote growth of motile phytoplankton or, if radiatively driven convection occurs, more nutritious diatoms, but links between functional trait selection, trophic transfer to zooplankton and fish, and the prevalence of microbial versus classical food webs in seasonally ice‐covered lakes remain unclear. Under‐ice processes cascade into and from the ice‐free season, and are relevant to annual cycling of energy and carbon through aquatic food webs. Understanding the coupling between state transitions and the reorganization of trophic hierarchies is essential for predicting complex ecosystem responses to climate change. In this interdisciplinary review we describe existing knowledge of physical processes in lakes in winter and the parallel developments in under‐ice biogeochemistry and ecology. We then illustrate interactions between these processes, identify extant knowledge gaps and present (novel) methods to address outstanding questions. Plain Language Summary: Winter is an important but poorly understood period for lake ecosystems at high latitudes. Incoming solar radiation is diminished by ice and (often) snow, flows of oxygen and substrates such as organic matter or nutrients from outside the lake are limited, and wind no longer causes turbulent mixing of the water column. The sediments become a source of heat as well as of solutes which drive denser water toward the bottom. The resulting density stratification creates a template for the development of winter ecosystems. Distinct oxygenated and oxygen‐depleted zones will affect microbial community structure and the habitat and behavior of zooplankton and fish. Conditions can rapidly change in spring with increased irradiance and incoming snowmelt. This paper reviews how physical, biogeochemical and biological processes act together to shape aquatic ecosystems in winter and in spring. In addition, we present an overview of the unknowns regarding the interactions between the different processes, which can now be posed due to improved understanding of under‐ice hydrodynamics and the nature of lake ice, of biogeochemistry, and of ecology. However, work to date has largely been conducted within distinct disciplines. We therefore outline interdisciplinary approaches that can bridge current knowledge gaps in winter limnology. Key Points: Ecosystems of seasonally ice‐covered lakes are governed by poorly understood interactions between abiotic and biotic processesDensity‐driven currents enable gradients in redox potential, create niche habitats and redistribute substrates and organisms under iceWinter limnology has tended to progress within disciplines; an interdisciplinary approach is necessary to resolve extant knowledge gaps [ABSTRACT FROM AUTHOR]

Clear trends of warming and wetting have occurred in Central Asia during the last 30 years, but how tree growth in low‐elevation mountainous areas has responded to climate warming remains unclear. In this paper, we investigated the relationships between Zeravschan juniper (Juniperus seravschanica) growth and climate factors based on 16 tree‐ring chronologies from low‐elevation mountainous areas across Central Asia and then used the resulting model to predict changes in Zeravschan juniper growth during the 21st century. Zeravschan juniper growth in our study region is mainly controlled by precipitation, which is predominantly influenced by tropical sea surface temperatures. The combination of increased precipitation and warm temperatures promoted the growth of Zeravschan juniper during the recent warm period. Our simulations suggest that Zeravschan juniper growth will still increase slightly under the RCP4.5 and RCP8.5 scenarios in the next 30 years, possibly due to increased precipitation caused by climate warming; however, climate warming will initially show negative effects and is expected to have greater effects after the 2050s. Better knowledge regarding regional climate mechanisms and their likely influences on tree growth is useful for improving forest planning and management in Central Asia. Key Points: Warm‐wet conditions have caused an increase in Zeravschan juniper growth since the 1980sZeravschan juniper growth was controlled by tropical SST‐induced precipitationHigh greenhouse gas emissions have a negative effect on juniper tree growth in Central Asian low‐elevation areas [ABSTRACT FROM AUTHOR]

Accurate characterization of gross primary productivity (GPP) is critically important in assessing mangrove carbon budgets, but the current knowledge of the temporal variations of GPP in evergreen mangroves is very limited. Remote sensing of sun‐induced chlorophyll fluorescence (SIF) has emerged as a promising approach to approximating GPP across ecosystems, but its capability for tracking GPP in evergreen mangroves has not been assessed. The SIF‐GPP link at a subtropical mangrove and its environmental controls are explored using 1‐year time‐series measurements from tower‐based hyperspectral and eddy covariance systems. Both the relationship between SIF and GPP as well as that between SIFy (SIF yield: the ratio of SIF over absorbed photosynthetically active radiation [APAR]) and LUE (light use efficiency: the ratio of GPP over APAR) at diurnal and seasonal time scales are analyzed. The temporal variations of SIF and GPP shared overall similar changing patterns, but their functional relationship tended to be time scale‐dependent. Midday depressions in SIF were observed when environmental stresses occurred around noon (including excess light and high VPD), and the strength of the SIF‐GPP link was affected by changing environmental conditions. The SIFy‐LUE relationship was temporally more dynamic, tending to match during midday hours but diverge from each other during morning and afternoon hours. These findings confirm SIF can serve as a potential remotely sensed indicator of mangrove canopy photosynthesis. This paper provides the first, high temporal‐resolution, continuous SIF measurements in mangroves, and highlights the importance of the impacts of environmental conditions on the SIF‐GPP relationship. Key Points: First continuous coordinated measurements of sun‐induced chlorophyll fluorescence (SIF) and eddy covariance in mangrove is presentedSIF serve as a potential remotely sensed indicator of tracking diurnal/seasonal variation in mangrove gross primary productivity (GPP)Environmental stresses tend to weaken mangrove SIF‐GPP correlation [ABSTRACT FROM AUTHOR]

Dryland ecosystems cover approximately 40% of terrestrial land surfaces and form a major component of global biogeochemical cycles, which are sensitive and vulnerable to climate change. Rapid climate change observably threatens vegetation growth and profoundly affects the global carbon cycle. However, interannual variations in vegetation growth, and changes in coupling between vegetation growth and precipitation in response to drought are not fully understood in the dryland ecosystems of the Silk Road Economic Belt (SREB). By combining remote sensing normalized vegetation indexes from GIMMS (GIMMS NDVI), simulated net primary productivity levels from TRENDYv2 (TRENDY NPP), terrestrial water storage change data (△TWS) derived from GRACE, and climate grid datasets, we investigated climate change, vegetation growth and nonlinear changes in coupling between vegetation growth and precipitation in the pregrowing and current seasons during 1982–2015. The results show intensified drought and extensive vegetation browning in all seasons, especially the summer, across the drylands of the SREB from 1993 to 2015. Precipitation in the pregrowing season significantly contributed to vegetation growth in the subsequent spring and summer, showing that the effects of precipitation in the pregrowing season on subsequent vegetation growth lags by almost two seasons. We also found that intensified drought significantly strengthened the coupling between vegetation growth and precipitation in the pregrowing and current seasons. These results highlight the nonlinear response of vegetation growth to intensified drought, and can be referenced to improve the coupling of land‐atmospheric models for drylands. Plain Language Summary: Latest studies have reported a substantial terrestrial drying trend for the 21st century. And the relationship of intensified drought and vegetation growth has been widely studied. A well‐known conclusion is that on the spatial gradient, as the drought intensifies, the vegetation is more dependent on precipitation. However, on the temporal scale, as the drought intensifies, the nonlinear changes in the relationship between vegetation growth and precipitation are rarely studied, especially in arid regions. In this paper we investigated climate change, vegetation growth and nonlinear changes in coupling between vegetation growth and precipitation in pre‐growing and current seasons over drylands of the Silk Road Economic Belt (SREB) during 1982–2015. Our results demonstrate that intensified drought and extensive vegetation browning across drylands of the SREB from 1993 to 2015, and precipitation in the pre‐growing season significant contributed to vegetation growth in the subsequent spring and summer, showing that the effects last by almost 2 seasons. We also find a significant strengthening of coupling between vegetation growth and precipitation in pre‐growing and current seasons due to intensified drought. These results highlight the nonlinear response of vegetation growth to intensified drought and can be referenced to improve the coupling of land‐atmospheric models for drylands. Key Points: Intensified drought resulted in vegetation browning in the drylands of the Silk Road Economic Belt during 1993–2015Precipitation in the pregrowing season had a significant effect on subsequent vegetation growth, and lasting for nearly two seasonsIntensified drought enhanced the coupling of vegetation growth and precipitation in the pregrowing and current seasons [ABSTRACT FROM AUTHOR]

Transparent exopolymer particles (TEP) are essential for the ocean carbon cycle. However, their relationships with physical and biogeochemical processes remain inadequately understood in the coastal ocean. Here, we focus on TEP dynamics across a temperature front in the coastal waters of the Northern South China Sea (NSCS). Our results suggested that TEP concentration was relatively high across the frontal system with 35.0–160.5 μg Xeq L−1 (μg Gum Xanthan equivalent per liter) in the surface waters, 70.0–197.2 μg Xeq L−1 in the bottom waters, and 12.1–16.3 mg Xeq g−1 in the surficial sediment. In the surface layer of the front, TEP distributions appeared to be driven by cross‐front physical and biogeochemical variations, as it showed significant correlations with both temperature and nutrients, as well as chlorophyll‐a along with its size‐fractionated components. TEP dominated on the shore side of the front with high phytoplankton biomass and intense TEP production in the surface layer. In contrast, there were much lower TEP concentrations and higher TEP production efficiencies on the seaside driven by nutrient limitation. In the bottom layer of the frontal zone, sediment resuspension associated with the front's secondary circulation was found to play a crucial role in enhancing the levels of TEP‐rich aggregates with prominent distribution patterns characterized by the localized accumulation in the bottom waters at the frontal zone. Our results provide valuable insights about the controlling factors that modulate TEP dynamics in a coastal frontal system and highlighted their potential role in the carbon cycling of the NSCS shelf‐sea. Plain Language Summary: Transparent exopolymer particles (TEP) have gained increasing attention due to their important roles in the biogeochemical cycles of the coastal ocean. Intense phytoplankton booms driven by increasing eutrophication has led to a very high level of TEP in the Pearl River Estuary (PRE). Meanwhile, TEP dynamics in the coastal waters of the Northern South China Sea (NSCS) outside the PRE, particularly in the nearshore frontal zone over the inner shelf, remained mostly unknown. Physical dynamics of the frontal system may be an important driver for TEP distribution and the related biogeochemical processes such as particulate organic carbon export in the coastal ocean, as particles including TEP can be accumulated there due to frontal physics. In this paper, we focused on TEP concentrations in water‐columns and sediments as well as related environmental factors across a nearshore temperature front to explore the physical and biogeochemical mechanisms regulating TEP dynamics in the coastal regions of the NSCS shelf‐sea. Key Points: Phytoplankton is an important source of surface transparent exopolymer particles (TEP) across the frontal systemHigher surface TEP production efficiencies on the seaside of the front driven by nutrient limitationSediment resuspension associated with the front's secondary circulation causes an enhanced TEP concentration in the bottom layers of the frontal zone [ABSTRACT FROM AUTHOR]

The understanding and modeling of photosynthetic dynamics affected by climate variability can be highly uncertain. In this paper, we examined a well‐characterized eddy covariance site in a drought‐prone temperate deciduous broadleaf forest combining tower measurements and satellite observations. We find that an increase in spring temperature usually leads to enhanced spring gross primary production (GPP), but a GPP reduction in late growing season due to water limitation. We evaluated how well a coupled fluorescence‐photosynthesis model (SCOPE) and satellite data sets track the interannual and seasonal variations of tower GPP from 2007 to 2016. In SCOPE, a simple stress factor scaling of Vcmax as a linear function of observed predawn leaf water potential (ψpd) shows a good agreement between modeled and measured interannual variations in both GPP and solar‐induced chlorophyll fluorescence (SIF) from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The modeled and satellite‐observed changes in SIFyield are ~30% smaller than corresponding changes in light use efficiency (LUE) under severe stress, for which a common linear SIF to GPP scaling would underestimate the stress reduction in GPP. Overall, GOME‐2 SIF tracks interannual tower GPP variations better than satellite vegetations indices (VIs) representing canopy "greenness." However, it is still challenging to attribute observed SIF variations unequivocally to greenness or physiological changes due to large GOME‐2 footprint. Higher‐resolution SIF data sets (e.g., TROPOMI) already show the potential to well capture the downregulation of late‐season GPP and could pave the way to better disentangle canopy structural and physiological changes in the future. Key Points: Warm springs usually enhance springtime forest GPP and evapotranspiration but result in water limitation that reduces late‐season fluxesA photosynthesis model with plant stress parameterized by measured leaf water potential can track interannual GPP and SIF variations wellSIFyield shows dampened variations compared to LUE, which explains the smaller observed reduction in SIF than GPP during drought period [ABSTRACT FROM AUTHOR]

Estimates of oceanic emissions of nitrous oxide (N2O) are surrounded by a considerable degree of uncertainty, particularly regarding the contribution of productive shelf regions, where assessments are based on limited observations. In this paper, we have applied a coupled hydrodynamic‐biogeochemical model resolving N2O dynamics to estimate N2O emissions within the northwest European continental shelf. Based on 10‐year average distributions (2006–2015), dominant seasonal patterns of N2O air‐sea exchange were identified. Within the southwest region of the shelf and deep parts of the North Sea, emissions are highest during winter. Peak emissions during late autumn are typical for the northwest part of the shelf and central North Sea, while in the western English Channel, Irish Sea and western North Sea peak outflux shifts toward early autumn. Within these regions, most N2O production occurs below the seasonal pycnocline, and duration and intensity of stratification defines the timing and rate of its subsequent release to the atmosphere. In contrast, within the southeast North Sea and most of the coastal areas, lack of stratification allows the excess N2O to outgas as soon as it is produced, driven by ammonium availability, resulting in peak emissions in summer. We estimate that N2O emissions from the northwest European shelf contribute 0.02224 Tg N to the atmosphere annually, that is, between 3.3–6.8% of total emissions from European shelves and estuaries. Key Points: Model reveals spatial variability in seasonality of nitrous oxide emissions driven by differences in stratification intensity and durationThe northwest European shelf contributes between 3.3% and 6.8% to total nitrous oxide emissions from European shelves and estuariesTotal amount of nitrous oxide is controlled by ammonium availability; changes in nutrient input can alter regional emissions [ABSTRACT FROM AUTHOR]

Complicated biogeochemical cycling and differential organic matter reactivity make quantifying the relative contribution of a given source of organic carbon to the standing stock within an estuary difficult. Here, a new model of tidal marsh‐estuary organic carbon cycling is presented for the Rhode River, MD, a well‐studied tributary of the Chesapeake Bay, USA. A dissolved organic carbon (DOC) budget was estimated by summing the source and sink terms and the advection of water within the tributary. 13.1% and 15.3% of the total DOC input to the Rhode River entered from the marsh and the watershed, respectively, and 52.6% was derived from phytoplankton production. Extrapolating to the entire year, 35.5 Mg of DOC is exported to the main stem of Chesapeake Bay annually, which accounts for 12.3% of the total allochthonous and autochthonous inputs to the estuary. Removing the modeled marsh at the head of the Rhode River decreased export of DOC to the main stem by 39.2%, and up to 56% of the estuarine DOC standing stock can be attributed to the marsh. The model described here can be used across temperate estuarine systems and provides a new methodology for quantifying the amount of DOC that can be attributed to or lost by specific source and sink pathways. Plain Language Summary: Tidal wetlands are potentially significant in global carbon cycling, taking large quantities of carbon dioxide out of the atmosphere and fixing it as plant and root biomass. Some of this fixed carbon is buried on long time scales, but a large portion is also transported out of wetlands into estuaries. Understanding where the carbon goes and how long it takes to get there is important for carbon cycling and potentially feedbacks related to climate change. The role tidal wetlands play in estuary carbon cycling and biogeochemistry is complex, and this paper uses a computer model to give insight into how these two important systems are linked. We found that a tidal wetland in a tributary of Chesapeake Bay contributes a large portion (39%) to the total organic carbon export from the tributary. This implies that relative to their inputs, tidal wetlands potentially contribute a greater portion to the total export from estuaries. Wetlands are thus potentially more important in carbon budgets than their inputs to estuaries would suggest. Key Points: A biogeochemical model was enhanced to include six pools of dissolved organic matter and fully spectral UV‐visible light attenuationPhytoplankton production was the largest contributor to the estuarine dissolved organic carbon budget at 52.6%A tidal marsh contributed 39.2% to the export of dissolved organic carbon from a tributary of Chesapeake Bay [ABSTRACT FROM AUTHOR]

Atmospheric nitrogen (N) deposition alters the cycling of nutrients in terrestrial ecosystems. However, there is limited knowledge regarding how N addition affects foliar nutrients beyond N and phosphorus (P) and their stoichiometry. We conducted a meta‐analysis, including 2,004 observations from 134 fertilization studies, to synthesize the effects of N addition on multiple foliar nutrients and stoichiometry in terrestrial ecosystems and to examine their potential controls. Overall, we found that N addition significantly decreased foliar P, potassium (K), calcium (Ca), magnesium (Mg), and calcium:aluminium (Ca:Al) by 3.22%, 7.58%, 9.55%, 5.65%, and 15.17%, respectively, but significantly increased foliar N, Al, N:K, N:Ca, and N:Mg by 19.02%, 6.99%, 21.06%, 27.65%, and 11.33%, respectively. Among the forest ecosystems, foliar N and P exhibited greater changes in temperate or boreal forests, and foliar K, Mg, and Mn showed greater decreases or increases in tropical forests after N addition. Nitrogen addition significantly affected foliar K (−7.55%), Mg (−6.46%), and Al (+6.81%) in forests but not in grasslands. Similarly, foliar K, Mg, and Al showed significant changes in woody plants but not in herbaceous plants. In addition, we found that environmental factors (e.g., ambient N deposition, mean annual precipitation, and soil pH) affected foliar nutrient responses of N, K, and Mg to N addition. In summary, our findings indicate that N addition affects foliar nutrient contents, with the extent of these effects differing among ecosystem type. This is important for understanding and predicting plant growth and nutrient dynamics under N deposition scenarios. Plain Language Summary: Foliar nutrients, such as nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), aluminum (Al), manganese (Mn), and iron (Fe), play an important role in plant health and ecosystem function, and an imbalance in these elements affects plant growth. Although atmospheric N deposition has been known to affect foliar N and P contents, much uncertainty exists on how N deposition affects other foliar nutrients and stoichiometry. We conducted a meta‐analysis to synthesize the effects of N addition on eight foliar nutrient concentrations (e.g., N, P, K, Ca, Mg, Al, Mn, and Fe) and the stoichiometric ratios of N and these elements in terrestrial natural ecosystems. We found that N addition significantly decreased K, Ca, Mg, and P but increased N, Al, and N:K, N:Ca, and N:Mg across the tested biomes, and these N‐induced effects on foliar nutrients varied depending on the ecosystem type. In addition, we found that environmental factors (e.g., soil pH, ambient N deposition, and mean annual precipitation) regulated foliar nutrient responses of N, K, and Mg to N addition. Our findings provide direct evidence that high N deposition affects the nutrient status of plants in terrestrial natural ecosystems, particularly in tropical/subtropical forests. Key Points: A meta‐analysis was conducted with data from 134 papers to reveal the responses of multiple foliar elements and stoichiometry to N additionResponses of foliar N, P, K, Mg, and Mn to N addition varied depending on the ecosystem typeIncreases in background N deposition and mean annual precipitation decreased the responses of foliar N, K, and Mg to N addition [ABSTRACT FROM AUTHOR]

Accurate remotely sensed land surface temperature (LST) is a promising tool for predicting surface evapotranspiration (ET). The spatial resolution of commonly existing daily satellite products (i.e., Moderate Resolution Imaging Spectroradiometer [MODIS] LST) is ~1 km, which remains relatively low for used in estimating ET. This paper developed a model that disaggregates ~1‐km spatial resolution MODIS‐derived LST data to fine spatial resolutions of 250 m. The proposed model was achieved by using a spatial and temporal nonlinear strategy that contains the predictor variables of the Bowen ratio, the photochemical reflectance index, and the normalized difference vegetation index. The proposed disaggregation model was assessed mainly at two agriculture sites, including the Heihe River Basin in China and the Walnut Creek Watershed in the United States, during the growing seasons. The assessment procedure was conducted at both the field scale and the image scale in terms of disaggregated LST and ET. The statistical results demonstrated that the proposed model produced 250‐m LST and ET that matched better with the observed values and achieved more accurate LST and ET relative to other reference ones. Our study shows that surface moisture status and vegetation physiological dynamic are important factors in improving the LST disaggregation over the agriculture region. The results of this study have the potential to improve water resource management and sustainable water use. Key Points: A model that disaggregates ~1‐km spatial resolution MODIS‐derived LST data to fine spatial resolutions of 250 m was developedThe assessment procedure was conducted at both the field scale and the image scale in terms of disaggregated LST and ETThis study supports water resource management and sustainable water use [ABSTRACT FROM AUTHOR]