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1. Ribbed mussel Geukensia demissa population response to living shoreline design and ecosystem development

   https://doi.org/10.1002/ecs2.3402  

   Bilkovic, Donna Marie ; Isdell, Robert E. ; Guthrie, Amanda G. ; Mitchell, Molly M. ; Chambers, Randolph M. ( March 2021 , Ecosphere)

   Coastal communities increasingly invest in natural and nature‐based features (e.g., living shorelines) as a strategy to protect shorelines and enhance coastal resilience. Tidal marshes are a common component of these strategies because of their capacity to reduce wave energy and storm surge impacts. Performance metrics of restoration success for living shorelines tend to focus on how the physical structure of the created marsh enhances shoreline protection via proper elevation and marsh plant presence. These metrics do not fully evaluate the level of marsh ecosystem development. In particular, the presence of key marsh bivalve species can indicate the capability of the marsh to provide non‐protective services of value, such as water quality improvement and habitat provision. We observed an unexpected low to no abundance of the filter‐feeding ribbed mussel,Geukensia demissa, in living shoreline marshes throughout Chesapeake Bay. In salt marsh ecosystems along the Atlantic Coast of the United States, ribbed mussels improve water quality, enhance nutrient removal, stabilize the marsh, and facilitate long‐term sustainability of the habitat. Through comparative field surveys and experiments within a chronosequence of 13 living shorelines spanning 2–16 years since construction, we examined three factors we hypothesized may influence recruitment of ribbed mussels to living shoreline marshes: (1) larval access to suitable marsh habitat, (2) sediment quality of low marsh (i.e., potential mussel habitat), and (3) availability of high‐quality refuge habitat. Our findings suggest that at most sites larval mussels are able to access and settle on living shoreline created marshes behind rock sill structures, but that most recruits are likely not surviving. Sediment organic matter (OM) and plant density were correlated with mussel abundance, and sediment OM increased with marsh age, suggesting that living shoreline design (e.g., sand fill, planting grids) and lags in ecosystem development (sediment properties) are reducing the survival of the young recruits. We offer potential modifications to living shoreline design and implementation practices that may facilitate self‐sustaining ribbed mussel populations in these restored habitats.

    

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2. Labile organic matter promotes nitrogen retention in natural and constructed gulf coast marshes

   https://doi.org/10.1007/s10533-024-01128-0  

   Starr, S. F. ; Mortazavi, B. ; Tatariw, C. ; Kuehn, K. A. ; Cherry, J. A. ; Ledford, T. ; Smyth, E. ; Wood, A. Griffin ; Sebren, S. E. ( March 2024 , Biogeochemistry)

   Coastal marshes mitigate allochthonous nitrogen (N) inputs to adjacent marine habitat; however, their extent is declining rapidly. As a result, marsh restoration and construction have become a major foci of wetland management. Constructed marshes can quickly reach similar plant biomass to natural marshes, but biogeochemical functions like N removal and retention can take decades to reach functional equivalency, often due to lags in organic matter (OM) pools development in newly constructed marshes. We compared denitrification and dissimilatory nitrate reduction to ammonium (DNRA) rates in a 32 year-old constructed marsh and adjacent reference marsh in the Northern Gulf of Mexico. Marsh sediments packed into 3 mm “thin discs” were subjected to three OM quality treatments (no OM addition, labile OM, or recalcitrant OM) and two N treatments (ambient nitrate or elevated nitrate) during a 13 day incubation. We found that OM addition, rather than marsh type or nitrate treatment, was the most important driver of nitrate reduction, increasing both denitrification and DNRA and promoting DNRA over denitrification in both marshes. Fungal and bacterial biomass were higher in the natural marsh across treatments, but recalcitrant OM increased fungal biomass in the constructed marsh, suggesting OM-limitation of fungal growth. We found that constructed marshes are capable of similar denitrification and DNRA as natural marshes after 30 years, and that labile OM addition promotes N retention in both natural and constructed marshes.

   Graphical Abstract

   Conceptual figure highlighting the findings of this experiment. Under control treatment with no C addition (bottom panel), constructed and natural marshes have similar rates of both DNRA and denitrification. The natural marsh has higher fungal and bacterial biomass, while fungal biomass is not detectable in the constructed marsh. Under labile OM additions (upper left panel), rates of both DNRA and denitrification are increased and DNRA becomes favored over denitrification in both marshes. Recalcitrant OM additions (upper right) increase denitrification, but do not affect DNRA or % denitrification. The addition of recalcitrant OM also increases the detectability of fungal biomass in the constructed marsh.

    

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3. Influence of the Keystone Grazer, Sesarma reticulatum, on the Hydrology and Organic Matter Cycling in Salt Marshes of the Southeastern USA

   https://doi.org/10.1007/s12237-024-01336-9  

   Morrison, Elise S. ; Bianchi, Thomas S. ; Kenney, William F. ; Brenner, Mark ; Prince, Kimberly ; Williams, Sydney ; Ortals, Collin ; Cordero, Orlando ; Crotty, Sinéad M. ; Angelini, Christine ( March 2024 , Estuaries and Coasts)

   In salt marshes of the Southeastern USA, purple marsh crabs (Sesarma reticulatum), hereafterSesarma, aggregate in grazing and burrowing fronts at the heads of tidal creeks, accelerating creek incision into marsh platforms. We explored the effects of this keystone grazer and sediment engineer on salt marsh sediment accumulation, hydrology, and carbon (C) and nitrogen (N) turnover using radionuclides (²¹⁰Pb and⁷Be), total hydrolyzable amino acids (THAA), and C and N stable isotopes (δ¹³C and δ¹⁵N) in sediment from pairedSesarma-grazed and un-grazed creeks.Sesarma-grazed-creek sediments exhibited greater bioturbation and tidal inundation compared to sediments in un-grazed creeks, as indicated by larger²¹⁰Pb and⁷Be inventories. Total organic carbon (TOC) to total nitrogen (TN) weight ratios (C:N) were higher and δ¹⁵N values were lower in grazed-creek sediments than in un-grazed-creek sediments, suggestingSesarmaremove and assimilate N in their tissues, and excrete N with lower δ¹⁵N values into sediments. In support of this inference, the percent total carbon (TC) and percent TOC declined by nearly half, percent TN decreased by ~ 80%, and the C:N ratio exhibited a ~ threefold increase betweenSesarmafore-gut and hind-gut contents. An estimated 91% ofSesarma’s diet was derived fromSpartina alterniflora,the region’s dominant salt marsh plant. We found that, asSesarmagrazing fronts progress across marsh landscapes, they enhance the decay ofSpartina-derived organic matter and prolong marsh tidal inundation. These findings highlight the need to better account for the effects of keystone grazers and sediment engineers, likeSesarma, in estimates of the stability and size of blue C stores in coastal wetlands.

    

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4. 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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5. Metabolism of a subtidal rocky mussel reef in a high-temperate setting: pathways of organic C flow

   https://doi.org/10.3354/meps13372  

   Attard, KM ; Rodil, IF ; Berg, P ; Mogg, AOM ; Westerbom, M ; Norkko, A ; Glud, RN ( July 2020 , Marine Ecology Progress Series)

   null (Ed.)

   Mytilid mussels form abundant, species-rich reefs on rocky substrates, but the role of this key habitat in carbon (C) cycling remains poorly understood. We performed a seasonal study on a 5 m deep photic Mytilus trossulus reef in the Central Baltic Sea to investigate pathways and rates of organic C flow. Reef gross primary production (GPP) and respiration ( R ) were estimated seasonally using underwater O 2 eddy covariance on hourly and daily timescales. Photogrammetry and biotic sampling were used to quantify reef rugosity and mussel coverage, and to derive mussel filtration and biodeposition. Mussels were highly abundant, reaching ~50000 ind. m -2 , and the reef structure increased the seabed surface area by 44%. GPP hourly was up to 20 mmol O 2 m -2 h -1 and GPP daily was up to 107 mmol O 2 m -2 d -1 , comparable to a nearby seagrass canopy. Hourly eddy fluxes responded linearly to light intensity and flow velocity, with higher velocities enhancing reef O 2 uptake at night. Reef R daily exceeded GPP daily on 12 of 13 measurement days, and R annual (29 mol O 2 m -2 yr -1 ) was 3-fold larger than GPP annual . The reef sustained a productive community of microbes and fauna whose activities accounted for ~50% of R annual . Horizontal water advection promoted food supply to the reef and likely facilitated substantial lateral C export of mussel biodeposits. Our analyses suggest that a reduction in mussel reef extent due to ongoing environmental change will have major implications for the transport and transformation of C and nutrients within the coastal Baltic Sea. 

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