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1. Direct uptake of organically derived carbon by grass roots and allocation in leaves and phytoliths: 13C labeling evidence

   https://doi.org/10.5194/bg-13-1693-2016  

   Alexandre, Anne ; Balesdent, Jérôme ; Cazevieille, Patrick ; Chevassus-Rosset, Claire ; Signoret, Patrick ; Mazur, Jean-Charles ; Harutyunyan, Araks ; Doelsch, Emmanuel ; Basile-Doelsch, Isabelle ; Miche, Hélène ; et al ( January 2016 , Biogeosciences)

   In the rhizosphere, the uptake of low-molecular-weight carbon (C) and nitrogen (N) by plant roots has been well documented. While organic N uptake relative to total uptake is important, organic C uptake is supposed to be low relative to the plant's C budget. Recently, radiocarbon analyses demonstrated that a fraction of C from the soil was occluded in amorphous silica micrometric particles that precipitate in plant cells (phytoliths). Here, we investigated whether and to what extent organically derived C absorbed by grass roots can feed the C occluded in phytoliths. For this purpose we added ¹³C- and ¹⁵N-labeled amino acids (AAs) to the silicon-rich hydroponic solution of the grass Festuca arundinacea. The experiment was designed to prevent C leakage from the labeled nutritive solution to the chamber atmosphere. After 14 days of growth, the ¹³C and ¹⁵N enrichments (¹³C excess and ¹⁵N excess) in the roots, stems and leaves as well as phytoliths were measured relative to a control experiment in which no labeled AAs were added. Additionally, the ¹³C excess was measured at the molecular level, in AAs extracted from roots and stems and leaves. The net uptake of labeled AA-derived ¹³C reached 4.5 % of the total AA ¹³C supply. The amount of AA-derived ¹³C fixed in the plant was minor but not nil (0.28 and 0.10 % of total C in roots and stems/leaves, respectively). Phenylalanine and methionine that were supplied in high amounts to the nutritive solution were more ¹³C-enriched than other AAs in the plant. This strongly suggested that part of AA-derived ¹³C was absorbed and translocated into the plant in its original AA form. In phytoliths, AA-derived ¹³C was detected. Its concentration was on the same order of magnitude as in bulk stems and leaves (0.15 % of the phytolith C). This finding strengthens the body of evidences showing that part of organic compounds occluded in phytoliths can be fed by C entering the plant through the roots. Although this experiment was done in nutrient solution and its relevance for soil C uptake assessment is therefore limited, we discuss plausible forms of AA-derived ¹³C absorbed and translocated in the plant and eventually fixed in phytoliths, and implications of our results for our understanding of the C cycle at the soil–plant–atmosphere interface 

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2. Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

   https://doi.org/10.5061/dryad.8sf7m0cpx  

   Hussain, Mir Zaman ; Hamilton, Stephen ; Robertson, G. Philip ; Basso, Bruno ( January 2021 , Dryad)

   Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α = 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 

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3. A new North American calibration for predicting canopy structure in deep time using epidermal phytolith morphology

   Canares, Brielle Ann ; Heath, Kit ; Torres, Juan ; Brightly, W H ; Dunn, R E ; Lowe, Alex ; Stiles, E ; Strömberg, C A ( July 2023 , Botany)

   Degree of canopy cover is linked to transpiration, carbon cycling and primary productivity of an ecosystem. In modern ecology, canopy structure is often quantified as Leaf Area Index (LAI), which is the amount of overstory leaf coverage relative to ground area. Although a key aspect of vegetation, the degree of canopy cover has proven difficult to reconstruct in deep time. One method, Reconstructed Leaf Area Index (rLAI), was developed to infer canopy structure using the relationship between non-grass leaf epidermal phytolith (plant biosilica) morphology, and leaf coverage in modern forests. This method leverages the observed correlation between epidermal phytolith size, shape (margin undulation), and light availability. When more light is available in a canopy, epidermal phytoliths tend to be smaller and less undulate, whereas less light availability is linked to larger and more undulate epidermal phytoliths. However, the calibration set used to develop this method was compiled from field sites and samples from localities in Costa Rica and it remains unclear how applicable it is to temperate North American fossil sites due to lack of data from relevant vegetation types and taxonomic differences between plant communities in the Neotropics vs. mid-latitude North America. For example, preliminary results measuring rLAI in phytolith assemblages from the Miocene of the North American Great Plains have yielded surprisingly high degrees of canopy density despite containing high relative abundances of open-habitat grasses. To test whether vegetational and taxonomic differences impact the calibration set, we constructed a new North American calibration using 24 quadrats from six sites, representing reasonable modern analogs for Miocene vegetation in eastern North America. Specifically, we sampled in Bennett Springs State Park in Lebanon, MO; Mark Twain National Forest in Rolla, MO; Tellico in Franklin, NC and Congaree National Park in Hopkins, SC. All sites include a range of canopy covers and vegetation types, from oak savannas and oak woodlands to mixed hardwood forests, pine savannas, and old growth bottomland forests. From each quadrat, we collected a soil sample and took hemispherical photos of the local canopy. From modern soil samples, biosilica was extracted in the lab, yielding phytolith assemblages which were scanned for epidermal phytoliths using a compound microscope. Recovered epidermal phytoliths size and margin undulation were measured and assemblage averages were used to predict measured LAI at each quadrat. Hemispherical photographs were processed using the software Gap Light Analyzer to obtain LAI values. We hypothesize there will be a linear relationship between actual LAI and LAI calculated from epidermal phytolith morphology, but its relationship will differ from that found in South America. Results will be used to reevaluate canopy coverage in sites within the Great Plains Miocene as well as applied to Pacific Northwest Miocene sites, both to understand changes to vegetation during global climatic events in their respective regions. 

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4. High methane concentrations in tidal salt marsh soils: Where does the methane go?

   https://doi.org/10.1111/gcb.17050  

   Capooci, Margaret ; Seyfferth, Angelia L. ; Tobias, Craig ; Wozniak, Andrew S. ; Hedgpeth, Alexandra ; Bowen, Malique ; Biddle, Jennifer F. ; McFarlane, Karis J. ; Vargas, Rodrigo ( November 2023 , Global Change Biology)

   Tidal salt marshes produce and emit CH₄. Therefore, it is critical to understand the biogeochemical controls that regulate CH₄spatial and temporal dynamics in wetlands. The prevailing paradigm assumes that acetoclastic methanogenesis is the dominant pathway for CH₄production, and higher salinity concentrations inhibit CH₄production in salt marshes. Recent evidence shows that CH₄is produced within salt marshes via methylotrophic methanogenesis, a process not inhibited by sulfate reduction. To further explore this conundrum, we performed measurements of soil–atmosphere CH₄and CO₂fluxes coupled with depth profiles of soil CH₄and CO₂pore water gas concentrations, stable and radioisotopes, pore water chemistry, and microbial community composition to assess CH₄production and fate within a temperate tidal salt marsh. We found unexpectedly high CH₄concentrations up to 145,000 μmol mol⁻¹positively correlated with S²⁻(salinity range: 6.6–14.5 ppt). Despite large CH₄production within the soil, soil–atmosphere CH₄fluxes were low but with higher emissions and extreme variability during plant senescence (84.3 ± 684.4 nmol m⁻² s⁻¹). CH₄and CO₂within the soil pore water were produced from young carbon, with most Δ¹⁴C‐CH₄and Δ¹⁴C‐CO₂values at or above modern. We found evidence that CH₄within soils was produced by methylotrophic and hydrogenotrophic methanogenesis. Several pathways exist after CH₄is produced, including diffusion into the atmosphere, CH₄oxidation, and lateral export to adjacent tidal creeks; the latter being the most likely dominant flux. Our findings demonstrate that CH₄production and fluxes are biogeochemically heterogeneous, with multiple processes and pathways that can co‐occur and vary in importance over the year. This study highlights the potential for high CH₄production, the need to understand the underlying biogeochemical controls, and the challenges of evaluating CH₄budgets and blue carbon in salt marshes.

    

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5. Making the case for an International Decade of Radiocarbon

   https://doi.org/10.1098/rsta.2023.0081  

   Eglinton, Timothy I. ; Graven, Heather D. ; Raymond, Peter A. ; Trumbore, Susan E. ; Aluwihare, Lihini ; Bard, Edouard ; Basu, Sourish ; Friedlingstein, Pierre ; Hammer, Samuel ; Lester, Joanna ; et al ( November 2023 , Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences)

   Radiocarbon (¹⁴C) is a critical tool for understanding the global carbon cycle. During the Anthropocene, two new processes influenced¹⁴C in atmospheric, land and ocean carbon reservoirs. First,¹⁴C-free carbon derived from fossil fuel burning has diluted¹⁴C, at rates that have accelerated with time. Second, ‘bomb’¹⁴C produced by atmospheric nuclear weapon tests in the mid-twentieth century provided a global isotope tracer that is used to constrain rates of air–sea gas exchange, carbon turnover, large-scale atmospheric and ocean transport, and other key C cycle processes. As we write, the¹⁴C/¹²C ratio of atmospheric CO₂is dropping below pre-industrial levels, and the rate of decline in the future will depend on global fossil fuel use and net exchange of bomb¹⁴C between the atmosphere, ocean and land. This milestone coincides with a rapid increase in¹⁴C measurement capacity worldwide. Leveraging future¹⁴C measurements to understand processes and test models requires coordinated international effort—a ‘decade of radiocarbon’ with multiple goals: (i) filling observational gaps using archives, (ii) building and sustaining observation networks to increase measurement density across carbon reservoirs, (iii) developing databases, synthesis and modelling tools and (iv) establishing metrics for identifying and verifying changes in carbon sources and sinks.

   This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'.

    

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