Greenhouse Gas Exchange Research Articles

High‐resolution peat volume change in a northern peatland: Spatial variability, main drivers, and impact on ecohydrology

AbstractThe depth of the groundwater table below the surface and its spatiotemporal variability are major controls on all major biogeophysical processes in northern peatlands, including ecohydrology, carbon balance, and greenhouse gas exchange. In these ecosystems, water table fluctuations are buffered by compression and expansion of peat. Controls on peat volume change and its spatial variability, however, remain elusive, hampering accurate assessment of climate change impact on functioning of peatlands. We therefore (1) analysed patterning of seasonal surface elevation change at high spatial resolution (0.5 m); (2) assessed its relationship with vegetation, geohydrology, and position within the peatland; and (3) quantified the consequences for peatland surface topography and ecohydrology. Changes in surface elevation were monitored using digital close‐range photogrammetry along a transect in a northern peatland from after snowmelt up to midgrowing season (May–July). Surface elevation change was substantial and varied spatially from −0.062 to +0.012 m over the measurement period. Spatial patterns of peat volume change were correlated up to 40.8 m. Spatial variation of peat volume change was mainly controlled by changes in water table, and to a lesser extent to vegetation, with peat volume change magnitude increasing from lawn < hollow < flark. Our observations suggest that patchiness and vertical variability of peatland surface topography are a function of the groundwater table. In dry conditions, the variability of surface elevation increases and more localized groundwater flows may develop. Consequently, spatially variable peat volume change may enhance peatland water retention and thereby sustain carbon uptake during drought.

Three-Year Variability Of Energy And Carbon Dioxide Fluxes At Clear-Cut Forest Site In The European Southern Taiga

Forest clearing strongly influences the energy, water and greenhouse gas exchange at the land sur face - atmosphere inter face. To estimate effects of clear cutting on sensible (H), latent heat (LE) and CO 2 fluxes the continuous eddy covariance measurements were provided at the recently clear-cut area situated in the western part of Russia from spring 2016 to the end of 2018. The possible effects of surrounding forest on the air flow disturbances and on the spatial pattern of horizontal advection terms within the selected clear-cut area were investigated using a process-based 3D momentum, energy and CO 2 exchange model. The modeling results showed a very low contribution of horizontal advection term into total turbulent momentum fluxes at flux tower location in case of the southern wind direction. The results of field flux measurements indicated a strong inter- and intra-annual variability of energy and CO 2 fluxes. The energy budget is characterized by higher daily and monthly LE fluxes throughout the entire period of measurements excepting the first two months after timber harvest. The mean Bowen ratio ( β =H/LE) was 0.52 in 2016, 0.30 - in 2017 and 0.35 - in 2018. Analysis of CO 2 fluxes during the first year following harvest showed that the monthly CO 2 release at the clear-cut area consistently exceeded the CO 2 uptake rates. The mean net ecosystem exchange (NEE) in the period was 3.3±1.3 gC∙m-2∙d-1. During the second and the third years of the flux measurements the clear-cut was also a prevailed sink of CO 2 for the atmosphere excepting short periods in June and in the first part of July when daily CO 2 uptake was higher than CO 2 release rates. The mean NEE rates averaged for the entire warm period of corresponding years were 1.2±2.3 g С ∙m -2 ∙d -1 in 2017 and 2.8±2.5 gC∙m -2 ∙d -1 in 2018, respectively. The mean ratio between gross primary production (GPP) and ecosystem respiration (TER) was 0.58 in 2016, 0.84 - in 2017 and 0.74 - in 2018.

An incubation study of temperature sensitivity of greenhouse gas fluxes in three land-cover types near Sydney, Australia

Greenhouse gas (GHG) fluxes play crucial roles in regulating the Earth surface temperature. However, our understanding of the effect of land-cover and soil depth on the potential GHG fluxes and their temperature sensitivities (Q10) is limited, which consequently increases the uncertainty to predict GHG exchange between soils and the atmosphere. In the present study, we sampled soils with contrasting characteristics from three land-cover types (wetland, grassland, and forest) and soil depths (0–10, 10–20, and 20–30 cm) from the Cumberland Plain near Sydney, Australia, and incubated at optimal (60%) water holding capacity at three temperatures (15, 25, and 35 °C). Overall, GHG fluxes and Q10 values differed significantly among land-cover types and soil depths. CO2 and N2O emissions were highest in wetland followed by grassland and forest soils, and they decreased with soil depth. In contrast, CH4 uptake was highest in grassland followed by forest and wetland soils, and it increased with soil depth. Combining the three major GHGs, the global warming potential in soil from wetland was higher than that from grassland and forest. Moreover, Q10 values of CO2 and N2O emissions were: wetland > grassland > forest, while Q10 value of CH4 uptake showed the opposite pattern. Q10 values of CO2 and N2O emissions and CH4 uptake all increased with soil depth, demonstrating that subsoil has a higher potential for CO2 and N2O emissions and CH4 uptake in a warming climate. While these experiments were conducted under ideally controlled laboratory conditions, results suggest that the large carbon stocks in wetland soils are vulnerable to loss and thus may amplify climate warming; upland soils are crucial CH4 sinks and thus potentially mitigate climate change. In addition, the greater temperature sensitivities of CO2 and N2O emissions and CH4 uptake in subsoil should be accounted for in carbon and nitrogen cycling models.

Impact of Different Nitrogen‐Horizontal Placements on Greenhouse Gas Exchange in an Apple Orchard

Nitrogen (N) placement can impact nitrogen use efficiency, but its effect on greenhouse gas (GHG) emissions remain unclear. The objective of this study is to compare the effects of four different N horizontal placement methods (i.e., annular canal (An), radial canal (Ra), band (Ba), and nest fertilization (Ne)) with urea broadcast (Br) on nitrous oxide (N2O), methane (CH4), and soil heterotrophic respiration carbon dioxide (CO2) emissions from an apple orchard to assess the seasonal and spatial variations in these gas emissions. The total cumulative GHG emissions are determined through spots that are differentiated as fertilized or unfertilized. A field simulation study is conducted in an apple orchard, and all N sources have an application rate of 300 kg N ha−1. In the spots with fertilizer application, the N2O emissions from the Br treatment are significantly lower than those of other treatments, and the emissions from the Ne treatment are 1.7‐fold higher than those of the Br treatment. Surprisingly, the cumulative N2O emissions from the Br treatment are significantly higher than those of the other four treatments. N horizontal placement does not significantly influence the soil CH4 sink. The CO2 emissions in the Br treatment are higher than in other treatments. High N2O emissions in the Br treatment result in a significantly higher GHG exchange than in other treatments, while the Ne treatment significantly reduces the GHG exchange throughout the measurement period. Therefore, optimizing N placement may serve as an effective way to reduce GHG emissions from arable soils.

Evidence of Freezing Pressure in Sea Ice Discrete Brine Inclusions and Its Impact on Aqueous‐Gaseous Equilibrium

AbstractSea ice in part controls surface water properties and the ocean‐atmosphere exchange of greenhouse gases at high latitudes. In sea ice, gas exists dissolved in brine and as air bubbles contained in liquid brine inclusions or as bubbles trapped directly within the ice matrix. Current research on gas dynamics within the ocean‐sea ice‐atmosphere interface has been based on the premise that brine with dissolved air becomes supersaturated with respect to the atmosphere during ice growth. Based on Henry's law, gas bubbles within brine should grow when brine reaches saturation during cooling, given that the total partial pressure of atmospheric gases is above the implicit pressure in brine of 1 atm. Using high‐resolution light microscopy time series imagery of gas bubble evolution inside discrete brine pockets, we observed bubbles shrinking during cooling events in response to the development of freezing pressure above 3 atm. During warming of discrete brine pockets, existing bubbles expand and new bubbles nucleate in response to depressurization. Pressure variation within these inclusions has direct impacts on aqueous‐gaseous equilibrium, indicating that Henry's law at a constant pressure of 1 atm is inadequate to assess the partitioning between dissolved and gaseous fractions of gas in sea ice. This new evidence of pressure build‐up in discrete brine inclusions controlling the solubility of gas and nucleation of bubbles in these inclusions has the potential to affect the transport pathways of air bubbles and dissolved gases within sea ice‐ocean‐atmosphere interface and modifies brine biochemical properties.

Modelling random uncertainty of eddy covariance flux measurements

The eddy-covariance (EC) technique is considered the most direct and reliable method to calculate flux exchanges of the main greenhouse gases over natural ecosystems and agricultural fields. The resulting measurements are extremely important to characterize ecosystem exchanges of carbon, water, energy and other trace gases, and are widely used to validate or constrain parameter of land surface models via data assimilation techniques. For this purpose, the availability of both complete half-hourly flux time series and its associated uncertainty is mandatory. However, uncertainty estimation for EC data is challenging because the standard procedures based on repeated sampling are not suitable for this kind of measurements, and the presence of missing data makes it difficult to build any sensible time series model with time-varying second-order moments that can provide estimates of total random uncertainty. To overcome such limitations, this paper describes a new method in the context of the strategy based on the model residual approach proposed by Richardson et al. (Agric For Meteorol 148(1): 38–50, 2008). The proposed approach consists in (1) estimating the conditional mean process as representative of the true signal underlying observed data and (2) estimating the conditional variance process as representative of the total random uncertainty affecting EC data. The conditional mean process is estimated through the multiple imputation algorithm recently proposed by Vitale et al. (J Environ Inform https://doi.org/10.3808/jei.201800391 , 2018). The conditional variance process is estimated through the stochastic volatility model introduced by Beltratti and Morana (Econ Notes 30(2): 205–234, 2001). This strategy is applied to ten sites that are part of FLUXNET2015 dataset, selected in such a way to cover various ecosystem types under different climatic regimes around the world. The estimated uncertainty is compared with estimates by other well-established methods, and it is demonstrated that the scaling relationship between uncertainty and flux magnitude is preserved. Additionally, the proposed strategy allows obtaining a complete half-hourly time series of uncertainty estimates, which are expected to be useful for many users of EC flux data.

Topographic Controls on the Extension and Retraction of Flowing Streams

AbstractFlowing stream networks extend and retract as their surrounding landscapes wet up and dry out, both seasonally and during rainstorms, with implications for aquatic ecosystems and greenhouse gas exchange. Some networks are much more dynamic than others, however, and the reasons for this difference are unknown. Here we show that the tendency of stream networks to extend and retract can be predicted from down‐valley changes in topographic attributes (slope, curvature, and contributing drainage area), without measuring subsurface hydrologic properties. Topography determines where water accumulates within valley networks, and we propose that it also modulates flow partitioning between the surface and subsurface. Measurements from 17 mountain stream networks support this hypothesis, showing that undissected valley heads have greater subsurface transport capacities than sharply incised valleys downstream. In catchments where broad valley heads rapidly transition to sharply incised valleys, subsurface transport capacity decreases abruptly, stabilizing stream length through wet and dry periods.

Łódzkie badania klimatu miasta

The work presents a historical outline and main achievements of Lodz researchers in the field of urban climate. Although regular meteorological measurements in Lodz began at the beginning of the 20th century, the development of urban climatology, understood as the city's influence on the field of meteorological elements, dates back to the 1950s. The last decade of the 20th century and the beginning of the present century brought a special intensification of activities in the field of urban climatology in Lodz. Apart from studies on the classic problems of the urban heat island or solar relations, unique measurements of the heat balance, surface exchange of greenhouse gases (CO2 and CH4) or radon concentration in the city were carried out during this period; the innovative measurement methods (scintillometry) were used and original numerical models were developed.

Soil aggregates as biogeochemical reactors and implications for soil-atmosphere exchange of greenhouse gases-A concept.

Soil-atmosphere exchange significantly influences the global atmospheric abundances of carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O). These greenhouse gases (GHGs) have been extensively studied at the soil profile level and extrapolated to coarser scales (regional and global). However, finer scale studies of soil aggregation have not received much attention, even though elucidating the GHG activities at the full spectrum of scales rather than just coarse levels is essential for reducing the large uncertainties in the current atmospheric budgets of these gases. Through synthesizing relevant studies, we propose that aggregates, as relatively separate micro-environments embedded in a complex soil matrix, can be viewed as biogeochemical reactors of GHGs. Aggregate reactivity is determined by both aggregate size (which determines the reactor size) and the bulk soil environment including both biotic and abiotic factors (which further influence the reaction conditions). With a systematic, dynamic view of the soil system, implications of aggregate reactors for soil-atmosphere GHG exchange are determined by both an individual reactor's reactivity and dynamics in aggregate size distributions. Emerging evidence supports the contention that aggregate reactors significantly influence soil-atmosphere GHG exchange and may have global implications for carbon and nitrogen cycling. In the context of increasingly frequent and severe disturbances, we advocate more analyses of GHG activities at the aggregate scale. To complement data on aggregate reactors, we suggest developing bottom-up aggregate-based models (ABMs) that apply a trait-based approach and incorporate soil system heterogeneity.

Standardisation of chamber technique for CO2, N2O and CH4 fluxes measurements from terrestrial ecosystems

Abstract Chamber measurements of trace gas fluxes between the land surface and the atmosphere have been conducted for almost a century. Different chamber techniques, including static and dynamic, have been used with varying degrees of success in estimating greenhouse gases (CO2, CH4, N2O) fluxes. However, all of these have certain disadvantages which have either prevented them from providing an adequate estimate of greenhouse gas exchange or restricted them to be used under limited conditions. Generally, chamber methods are relatively low in cost and simple to operate. In combination with the appropriate sample allocations, chamber methods are adaptable for a wide variety of studies from local to global spatial scales, and they are particularly well suited for in situ and laboratory-based studies. Consequently, chamber measurements will play an important role in the portfolio of the Pan-European long-term research infrastructure Integrated Carbon Observation System. The respective working group of the Integrated Carbon Observation System Ecosystem Monitoring Station Assembly has decided to ascertain standards and quality checks for automated and manual chamber systems instead of defining one or several standard systems provided by commercial manufacturers in order to define minimum requirements for chamber measurements. The defined requirements and recommendations related to chamber measurements are described here.

Ancillary vegetation measurements at ICOS ecosystem stations

Abstract The Integrated Carbon Observation System is a Pan-European distributed research infrastructure that has as its main goal to monitor the greenhouse gas balance of Europe. The ecosystem component of Integrated Carbon Observation System consists of a multitude of stations where the net greenhouse gas exchange is monitored continuously by eddy covariance measurements while, in addition many other measurements are carried out that are a key to an understanding of the greenhouse gas balance. Amongst them are the continuous meteorological measurements and a set of non-continuous measurements related to vegetation. The latter include Green Area Index, aboveground biomass and litter biomass. The standardized methodology that is used at the Integrated Carbon Observation System ecosystem stations to monitor these vegetation related variables differs between the ecosystem types that are represented within the network, whereby in this paper we focus on forests, grasslands, croplands and mires. For each of the variables and ecosystems a spatial and temporal sampling design was developed so that the variables can be monitored in a consistent way within the ICOS network. The standardisation of the methodology to collect Green Area Index, above ground biomass and litter biomass and the methods to evaluate the quality of the collected data ensures that all stations within the ICOS ecosystem network produce data sets with small and similar errors, which allows for inter-comparison comparisons across the Integrated Carbon Observation System ecosystem network.

Long-term effect of fertilization on the greenhouse gas exchange of low-productive peatland forests

Drainage of peatlands for forestry often leads to carbon dioxide (CO2) net emission from soil due to loss of peat. This emission can be compensated for by the increased tree growth. Hovewer, many drained peatlands have low tree growth due to nutrient limitations. Tree growth at these peatlands can be effectively increased by fertilization, but fertilization has been also found to increase decomposition rates.We studied the long-term effect of fertilization of low-productive forestry-drained peatlands on the complete ecosystem greenhouse gas exchange, including both soil and tree component, and accounting for CO2, methane and nitrous oxide. Five N-rich study sites (flark fens and a rich fen) and one N-poor ombrotrophic site were established. Fertilization had started at the study sites 16–67 years before our measurements.Fertilization considerably increased tree stand CO2 sink (+248–1013 g CO2 m−2 year−1). Decomposition increased on average by 45% (+431 g CO2 m−2 year−1) and litter production by 38% (+360 g CO2 m−2 year−1). Thus, on average 84% of the increased decomposition could be attributed to increased litter production and 16% to increased soil CO2 net emission due to increased loss of peat. Soil CO2 net emission correlated positively with water table depth and top soil N concentration.Fertilization increased soil CO2 net emission at the drained flark fens on average by 187 g CO2 m−2 year−1. At the rich fen, net emission decreased. The N-poor bog exhibited soil CO2 sink both with and without fertilization. Effects on methane and nitrous oxide emissions were small at most sites.The increase in tree stand CO2 sink was higher than the increase in soil CO2 net emission, indicating that fertilization has a climate cooling effect in the decadal time scale. Yet, as the fertilized plots at N-rich sites exhibited soil CO2 source or zero balance, continuation of fertilization-based forestry over several rotations would lead to progressive loss of ecosystem C. At the N-poor bog, fertilization-based forestry may have a climate-cooling effect also in the centennial time scale.

Effect of urbanization on soil methane and nitrous oxide fluxes in subtropical Australia

Increasing population densities and urban sprawl are causing rapid land use change from natural and agricultural ecosystems into smaller, urban residential properties. However, there is still great uncertainty about the effect that urbanization will have on biogeochemical C and N cycles and associated greenhouse gas (GHG) budgets. We aimed to evaluate how typical urbanization related land use change in subtropical Australia affects soil GHG exchange (N2 O and CH4 ) and the associated global warming potential (GWP). Fluxes were measured from three land uses: native forest, a long-term pasture, and a turf grass lawn continuously over two years using a high-resolution automated chamber system. The fertilized turf grass had the highest N2 O emissions, dominated by high fluxes >100gN2 O-Nday-1 immediately following establishment though decreased to just 0.6kgN2 O-Nha-1 in the second year. Only minor fluxes occurred in the forest and pasture, with the high aeration of the sandy topsoil limiting N2 O emissions while promoting substantial CH4 uptake. Native forest was consistently the strongest CH4 sink (-2.9kgCH4 -Cha-1 year-1 ), while the pasture became a short-term CH4 source after heavy rainfall when the soil reached saturation. On a two-year average, land use change from native forest to turf grass increased the non-CO2 GWP from a net annual GHG sink of -83CO2 -e ha-1 year-1 to a source of 245kgCO2 -eha-1 year-1 . This study highlights that urbanization can substantially alter soil GHG exchange by altering plant soil water use and by increasing bulk density and inorganic N availability. However, on well-drained subtropical soils, the impact of urbanization on inter-annual non-CO2 GWP of turf grass was low compared to urbanized ecosystems in temperate climates.

High-frequency greenhouse gas flux measurement system detects winter storm surge effects on salt marsh.

The physical controlling factors on coastal plant communities are among the most dynamic of known ecosystems, but climate change alters coastal surface and subsurface hydrologic regimes, which makes rapid measurement of greenhouse gas fluxes critical. Greenhouse gas exchange rates in these terrestrial-aquatic ecosystems are highly variable worldwide with climate, soil type, plant community, and weather. Therefore, increasing data collection and availability should be a priority. Here, we demonstrate and validate physical and analytical modifications to automated soil-flux chamber measurement methods for unattended use in tidally driven wetlands, allowing the high-frequency capture of storm surge and day/night dynamics. Winter CO2 flux from Sarcocornia perennis marsh to the atmosphere was significantly greater during the day (2.8mmolm-2 hr-1 ) than the night (2.2mmolm-2 hr-1 ; p<0.001), while CH4 was significantly greater during the night (0.16μmolm-2 hr-1 ) than the day (-0.13μmolm-2 hr-1 ; p=0.04). The magnitude of CO2 flux during the day and the frequency of CH4 flux were reduced during a surge (p<0.001). Surge did not significantly affect N2 O flux, which without non-detects was normally distributed around -24.2nmolm-2 hr-1 . Analysis with sustained-flux global potentials and increased storm surge frequency scenarios, 2020 to 2100, suggested that the marsh in winter remains an atmospheric CO2 source. The modeled results showed an increased flux of CO2 to the atmosphere, while in soil, the uptake of CH4 increased and N2 O uptake decreased. We present analytical routines to correctly capture gas flux curves in dynamic overland flooding conditions and to flag data that are below detection limits or from unobserved chamber-malfunction situations. Storm surge is an important phenomenon globally, but event-driven, episodic factors can be poorly estimated by infrequent sampling. Wider deployment of this system would permit inclusion of surge events in greenhouse gas estimates.

Determining Subarctic Peatland Vegetation Using an Unmanned Aerial System (UAS)

Rising global temperatures tied to increases in greenhouse gas emissions are impacting high latitude regions, leading to changes in vegetation composition and feedbacks to climate through increased methane (CH4) emissions. In subarctic peatlands, permafrost collapse has led to shifts in vegetation species on landscape scales with high spatial heterogeneity. Our goal was to provide a baseline for vegetation distribution related to permafrost collapse and changes in biogeochemical processes. We collected unmanned aerial system (UAS) imagery at Stordalen Mire, Abisko, Sweden to classify vegetation cover types. A series of digital image processing routines were used to generate texture attributes within the image for the purpose of characterizing vegetative cover types. An artificial neural network (ANN) was developed to classify the image. The ANN used all texture variables and color bands (three spectral bands and six metrics) to generate a probability map for each of the eight cover classes. We used the highest probability for a class at each pixel to designate the cover type in the final map. Our overall misclassification rate was 32%, while omission and commission error by class ranged from 0% to 50%. We found that within our area of interest, cover classes most indicative of underlying permafrost (hummock and tall shrub) comprised 43.9% percent of the landscape. Our effort showed the capability of an ANN applied to UAS high-resolution imagery to develop a classification that focuses on vegetation types associated with permafrost status and therefore potentially changes in greenhouse gas exchange. We also used a method to examine the multiple probabilities representing cover class prediction at the pixel level to examine model confusion. UAS image collection can be inexpensive and a repeatable avenue to determine vegetation change at high latitudes, which can further be used to estimate and scale corresponding changes in CH4 emissions.

Dissolved organic carbon in streams within a subarctic catchment analysed using a GIS/remote sensing approach.

Climate change projections show that temperature and precipitation increases can alter the exchange of greenhouse gases between the atmosphere and high latitude landscapes, including their freshwaters. Dissolved organic carbon (DOC) plays an important role in greenhouse gas emissions, but the impact of catchment productivity on DOC release to subarctic waters remains poorly known, especially at regional scales. We test the hypothesis that increased terrestrial productivity, as indicated by the normalized difference vegetation index (NDVI), generates higher stream DOC concentrations in the Stordalen catchment in subarctic Sweden. Furthermore, we aimed to determine the degree to which other generic catchment properties (elevation, slope) explain DOC concentration, and whether or not land cover variables representing the local vegetation type (e.g., mire, forest) need to be included to obtain adequate predictive models for DOC delivered into rivers. We show that the land cover type, especially the proportion of mire, played a dominant role in the catchment’s release of DOC, while NDVI, slope, and elevation were supporting predictor variables. The NDVI as a single predictor showed weak and inconsistent relationships to DOC concentrations in recipient waters, yet NDVI was a significant positive regulator of DOC in multiple regression models that included land cover variables. Our study illustrates that vegetation type exerts primary control in DOC regulation in Stordalen, while productivity (NDVI) is of secondary importance. Thus, predictive multiple linear regression models for DOC can be utilized combining these different types of explanatory variables.

Perennial forb invasions alter greenhouse gas balance between ecosystem and atmosphere in an annual grassland in China

Grassland ecosystems are sensitive to invasions by plants from other functional groups which can alter soil greenhouse gas (GHG) fluxes. However, the effects of plant invasion on net GHG exchanges between soils and the atmosphere, plant production, and global warming potential (GWP) of annual grasslands is poorly understood. To evaluate the impacts of perennial forb invasions on GHG budgets of an annual grassland in China, we measured soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes over two years in replicated invaded (dominated by Alternanthera philoxeroides or Solidago canadensis) and non-invaded (dominated by the annual grass Eragrostis pilosa or the annual forb Sesbania cannabina) field sites. On average, soil CO2 and N2O emissions from invaded sites were 30% and 76% higher, respectively, relative to sites dominated by native species. Emissions of N2O and CO2 were especially high in Solidago and Alternanthera dominated sites, respectively. Soil CH4 emissions did not vary with plant species. On average, total biomass C of invaded sites was higher than that of the native dominated sites but this reflected the high C in Solidago dominated sites. Global warming potential (GWP) was increased by Alternanthera invasions and decreased by Solidago invasions. Plant invasions affected GWP of these annual grasslands through higher emissions of some GHGs but also sometimes higher biomass C. Together, this suggests that perennial forb invasions could change the net source or sink role of annual grasslands for GHG budgets, but the effects on GWP vary among species depending on GHG responses and C storage.

Role of Soil Erosion in Biogeochemical Cycling of Essential Elements: Carbon, Nitrogen, and Phosphorus

Most of Earth's terrestrial surface is made up of sloping landscapes. The lateral distribution of topsoil by erosion controls the availability, stock, and persistence of essential elements in the terrestrial ecosystem. Over the last two decades, the role of soil erosion in biogeochemical cycling of essential elements has gained considerable interest from the climate, global change, and biogeochemistry communities after soil erosion and terrestrial sedimentation were found to induce a previously unaccounted terrestrial sink for atmospheric carbon dioxide. More recent studies have highlighted the role of erosion in the persistence of organic matter in soil and in the biogeochemical cycling of elements beyond carbon . Here we synthesize available knowledge and data on how erosion serves as a major driver of biogeochemical cycling of essential elements. We address implications of erosion-driven changes in biogeochemical cycles on the availability of essential elements for primary production, on the magnitude of elemental exports downstream, and on the exchange of greenhouse gases from the terrestrial ecosystem to the atmosphere. Furthermore, we explore fates of eroded material and how terrestrial mass movement events play major roles in modifying Earth's climate.

Climatic role of terrestrial ecosystem under elevated CO2 : a bottom-up greenhouse gases budget.

The net balance of greenhouse gas (GHG) exchanges between terrestrial ecosystems and the atmosphere under elevated atmospheric carbon dioxide (CO2 ) remains poorly understood. Here, we synthesise 1655 measurements from 169 published studies to assess GHGs budget of terrestrial ecosystems under elevated CO2 . We show that elevated CO2 significantly stimulates plant C pool (NPP) by 20%, soil CO2 fluxes by 24%, and methane (CH4 ) fluxes by 34% from rice paddies and by 12% from natural wetlands, while it slightly decreases CH4 uptake of upland soils by 3.8%. Elevated CO2 causes insignificant increases in soil nitrous oxide (N2 O) fluxes (4.6%), soil organic C (4.3%) and N (3.6%) pools. The elevated CO2 -induced increase in GHG emissions may decline with CO2 enrichment levels. An elevated CO2 -induced rise in soil CH4 and N2 O emissions (2.76 Pg CO2 -equivalent year-1 ) could negate soil C enrichment (2.42 Pg CO2 year-1 ) or reduce mitigation potential of terrestrial net ecosystem production by as much as 69% (NEP, 3.99 Pg CO2 year-1 ) under elevated CO2 . Our analysis highlights that the capacity of terrestrial ecosystems to act as a sink to slow climate warming under elevated CO2 might have been largely offset by its induced increases in soil GHGs source strength.

ForC: a global database of forest carbon stocks and fluxes.

Forests play an influential role in the global carbon (C) cycle, storing roughly half of terrestrial C and annually exchanging with the atmosphere more than five times the carbon dioxide (CO2 ) emitted by anthropogenic activities. Yet, scaling up from field-based measurements of forest C stocks and fluxes to understand global scale C cycling and its climate sensitivity remains an important challenge. Tens of thousands of forest C measurements have been made, but these data have yet to be integrated into a single database that makes them accessible for integrated analyses. Here we present an open-access global Forest Carbon database (ForC) containing previously published records of field-based measurements of ecosystem-level C stocks and annual fluxes, along with disturbance history and methodological information. ForC expands upon the previously published tropical portion of this database, TropForC (https://doi.org/10.5061/dryad.t516f), now including 17,367 records (previously 3,568) representing 2,731 plots (previously 845) in 826 geographically distinct areas. The database covers all forested biogeographic and climate zones, represents forest stands of all ages, and currently includes data collected between 1934 and 2015. We expect that ForC will prove useful for macroecological analyses of forest C cycling, for evaluation of model predictions or remote sensing products, for quantifying the contribution of forests to the global C cycle, and for supporting international efforts to inventory forest carbon and greenhouse gas exchange. A dynamic version of ForC is maintained at on GitHub (https://GitHub.com/forc-db), and we encourage the research community to collaborate in updating, correcting, expanding, and utilizing this database. ForC is an open access database, and we encourage use of the data for scientific research and education purposes. Data may not be used for commercial purposes without written permission of the database PI. Any publications using ForC data should cite this publication and Anderson-Teixeira etal. (2016a) (see Metadata S1). No other copyright or cost restrictions are associated with the use of this data set.