Use of historical isoscapes to develop an estuarine nutrient baseline

Coastal eutrophication is a prevalent threat to the healthy functioning of ecosystems globally. While degraded water quality can be detected by monitoring oxygen, nutrient concentrations, and algal abundance, establishing regulatory guidelines is complicated by a lack of baseline data (e.g., pre-Anthropocene). We use historical carbon and nitrogen isoscapes over ~300 years from sediment cores to reconstruct spatial and temporal changes in nutrient dynamics for a central California estuary, Elkhorn Slough, where development and agriculture dramatically enhanced nutrient inputs over the past century. We found strong contrasts between current sediment stable isotopes and those from the recent past, demonstrating shifts exceeding those in previously studied eutrophic estuaries and substantial increases in nutrient inputs. Comparisons of contemporary with historical isoscapes also revealed that nitrogen sources shifted from a historical marine-terrestrial gradient with higher δ15N near the inlet to amplified denitrification at the head and mouth of the modern estuary driven by increased N inputs. Geospatial analysis of historical data suggests that an increase in fertilizer application – rather than population growth or increases in the extent of cultivated land – is chiefly responsible for increasing nutrient loads during the 20th century. This study demonstrates the ability of isotopic and stoichiometric maps to provide important perspectives on long-term shifts and spatial patterns of nutrients that can be used to improve management of nutrient pollution

Data for: Drainage impacts on the productivity of wetland species Spartina alterniflora and Salicornia pacifica

Coastal wetlands display ecohydrological zonation such that vertical differences of plant zones are driven by varying groundwater levels over tidal cycles. It is unclear how variable levels of tidal drainage directly impact biotic and abiotic factors in coastal wetland ecosystems. To determine the impacts of drainage levels, simulated tides in mesocosms with varying degrees of drainage were created with Spartina alterniflora, the salt marsh coastal ecosystem dominant species on the United States Atlantic Coast, and Salicornia pacifica, the Pacific Coast dominant. We measured biomass production and photosynthesis as indicators of plant health, and we also measured soil and porewater characteristics to help interpret patterns of productivity. These measures included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, net ecosystem exchange, photosynthesis rate, respiration rate, and methane flux. We found the greatest plant production in soils with intermediate drainage levels, with production values that were 13.7% higher for S. alterniflora and 57.7% higher for S. pacifica in the intermediate flooding levels than found in more inundated and more drained conditions. Understanding how drainage impacts plant species is important for predicting wetland resilience to sea level rise, as increasing water levels alter ecohydrological zonation.Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 1946302This experiment was conducted using two ecosystem-dominant salt marsh species Spartina alterniflora and Salicornia pacifica. Mesocosms were used to quantify the effects of the varying drainage treatments on the coastal wetland plant growth and soil conditions. The mesocosm soil was prepared by combining 25% marsh soil that was collected from the Tuckerton Peninsula, New Jersey (39.5388°, -74.3254°), 25% multipurpose sand (Lowes, Philadelphia, PA, USA), and 50% mushroom compost (Primex Garden Center, Glenside, PA, USA). Soils were screened at 2-mm to remove shell hash and coarse organic matter, homogenized with a cement mixer, and added to plant pots. The S. alterniflora plants were contained in pots that were made from cylindrical PVC pipes that were 20-cm long x 10-cm in diameter and were screened at the bottom to allow for water exchange. The S. pacifica plants were contained in 20-cm long square (7.6 x 7.6-cm) treepots, also screened at the bottom. We conducted a 2 x 4 factorial experiment where two types of plants were exposed to four different drainage treatments, with a total of 64 experimental units. Pots were placed in 150 L tidal mesocosms constructed from stock tanks and painted white. Simulated tides were created using tubing to pump water between the experimental tank and a reservoir, using timers to create a once-daily three-hour high tide and a 21-hour low tide. Inside four separate tanks, there were four drainage treatments: where the low tide water level was never drained (0-cm), and where the low tide water levels were drained to 5-cm, 10-cm, and 20-cm below the surface of the plant pot, The plants were propagated outdoors receiving natural precipitation. Plants were propagated in freshwater for one week, transitioned to 10 ppt salinity for one week, and finally changed over to 20 ppt salinity for the remainder of the experiment. Saline conditions were created utilizing Instant Ocean and adjusted weekly. Plants were propagated for 12 weeks from 13 May 2021 to 3 August 2021. To measure the productivity of the wetland species Spartina alterniflora and Salicornia pacifica, the aboveground and belowground biomass of each treatment was measured. Aboveground and belowground biomass was harvested at the end of week 12. Stalks growing from the soil were cut, plants were washed over a 2-mm sieve, dried at 60°C, and weighed. Belowground biomass was separated from the soil by hand, rinsed over a sieve, dried at 60°C, and then weighed. Biomass values were scaled to a square meter through multiplication by a constant. Measurements of the effects of soil drainage on abiotic parameters included porewater salinity, pH, ammonium, and hydrogen sulfide. Porewater was collected with a push pointsampler on 7 August 2021 (PPX36, MHE, East Tawas, MI, USA) at a depth of 20-cm. Samples for ammonium, pH, and salinity were frozen for later analysis. Subsamples (2 mL) were fixed with 0.22% zinc acetate solution, and frozen, for later analysis of hydrogen sulfide. Samples were analyzed for salinity and pH using a calibrated portable pH/Conductivity meter (Star A325 pH/Conductivity Portable Multiparameter Meter, Thermo Scientific Orion). UV-vis spectrophotometry was used for measurements of porewater ammonium using the indophenol blue method. Hydrogen sulfide was measured spectrophotometrically on the zinc acetate-fixed samples following the methylene blue method. All samples below the detection limit (~0.25 µM) were assigned a sulfide concentration of zero for the purposes of data analysis. Redox potential measurements were taken at depths of 5-cm and 15-cm for the Spartina alterniflora soils, and depths of 3-cm and 9-cm for Spartina pacifica soils to reflect the size of the pots using a bench-top redox meter (Bench-Top pH/mV Meter, Sper Scientific). Carbon dioxide and methane fluxes were measured to calculate the photosynthesis, respiration, and net ecosystem exchange (NEE) rates of the plants. The fluxes were measured in the field on 7 August 2021 from 10 a.m. to 4 p.m. (Eastern Standard Time), using an LGR ultra-portable greenhouse gas analyzer via cavity ring-down spectroscopy (ABB-Los Gatos Research, San Jose, CA, USA). Positive fluxes were defined as those in which gas concentrations increased over time within the chamber, and negative fluxes as those in which concentrations decreased (Nakanoa et al., 2004). Photosynthesis rates were obtained by measuring the carbon dioxide concentration as a function of time in the light and dark conditions, and then subtracting the dark measurement from the light measurement. Respiration rates were obtained by measuring the carbon dioxide concentration as a function of time in the dark conditions. All statistical analyses were performed in R 4.2.3 (R Core Team, 2023). Bar graphs and scatter plots were made using the package ggplot2. The responses of the study plants Spartina and Salicornia to drainage were analyzed using permutational multivariate analysis of variance (perMANOVAs; Anderson, 2001), utilizing the R package vegan. The dependent variables included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, NEE, photosynthesis rate, respiration rate, and methane flux. We partitioned the variability and obtained F-statistics on matrices of Euclidean distances calculated from the original raw data. P-values were calculated using 10,000 random permutations of the appropriate exchangeable units. Where values of certain variables were missing, the means of a treatment group factor were added to the matrix to ensure each variable had the same number of values. Redox was rank-transformed prior to analysis to remove negative values. Because the interaction term was significant, we conducted contrast tests using the same function (adonis2), with a Bonferroni correction applied for the number of contrasts (0.05/16 = 0.0031). Because the results of the contrasts did not reveal strong groupings, we conducted follow-up two-way ANOVAs to identify the factors contributing to significant differences between the species and drainage levels. ANOVAs were performed on rank-transformed data to account for the non-normal error structure. ANOVAs were run in base R using the aov command. Follow-up least-square means comparisons tests were completed on main effects and interactions, where appropriate, using package lsmeans using the Tukey or Sidak methods for p-value adjustments as appropriate. A principal component analysis (PCA) was used for dimension reduction of the multivariate measurements to examine variability between treatments and plant species, as well as to determine species and treatment grouping patterns with respect to the dependent variables. The eigenvalues provide a measure of the amount of variance explained by each principal component. The data matrix was constructed using the 11 dependent variables which included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, NEE, photosynthesis rate, respiration rate, and methane flux. The packages used for the PCA include cor, ggcorrplot, factoextra. To perform the PCA, the data was first normalized, and a correlation matrix was computed and visualized. Visualization of the PCA was constructed as a biplot of the first vs. second principal components. A Kaiser-Meyer-Olkin (KMO) test was used to determine how suited the data is for factor analysis, utilizing the EFAtools package. A Bartlett's test of sphericity was used to test for significant correlations among at least some of the variables, utilizing the psych package. As many of the measured variables varied in response to the drainage treatments in a multi-dimensional way, we constructed loess curves (span=0.40) to describe the relationship between treatment and the response variables of above and belowground biomass, porewater salinity, porewater pH, porewater ammonium and sulfide concentration, NEE, and redox potential. A loess curve is a nonparametric method for smoothing a series of data and was used because of the non-linear structure of the relationship between drainage and response variables

Data for: Drainage impacts on the productivity of wetland species Spartina alterniflora and Salicornia pacifica

Coastal wetlands display ecohydrological zonation such that vertical differences of plant zones are driven by varying groundwater levels over tidal cycles. It is unclear how variable levels of tidal drainage directly impact biotic and abiotic factors in coastal wetland ecosystems. To determine the impacts of drainage levels, simulated tides in mesocosms with varying degrees of drainage were created with Spartina alterniflora, the salt marsh coastal ecosystem dominant species on the United States Atlantic Coast, and Salicornia pacifica, the Pacific Coast dominant. We measured biomass production and photosynthesis as indicators of plant health, and we also measured soil and porewater characteristics to help interpret patterns of productivity. These measures included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, net ecosystem exchange, photosynthesis rate, respiration rate, and methane flux. We found the greatest plant production in soils with intermediate drainage levels, with production values that were 13.7% higher for S. alterniflora and 57.7% higher for S. pacifica in the intermediate flooding levels than found in more inundated and more drained conditions. Understanding how drainage impacts plant species is important for predicting wetland resilience to sea level rise, as increasing water levels alter ecohydrological zonation.Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 1946302This experiment was conducted using two ecosystem-dominant salt marsh species Spartina alterniflora and Salicornia pacifica. Mesocosms were used to quantify the effects of the varying drainage treatments on the coastal wetland plant growth and soil conditions. The mesocosm soil was prepared by combining 25% marsh soil that was collected from the Tuckerton Peninsula, New Jersey (39.5388°, -74.3254°), 25% multipurpose sand (Lowes, Philadelphia, PA, USA), and 50% mushroom compost (Primex Garden Center, Glenside, PA, USA). Soils were screened at 2-mm to remove shell hash and coarse organic matter, homogenized with a cement mixer, and added to plant pots. The S. alterniflora plants were contained in pots that were made from cylindrical PVC pipes that were 20-cm long x 10-cm in diameter and were screened at the bottom to allow for water exchange. The S. pacifica plants were contained in 20-cm long square (7.6 x 7.6-cm) treepots, also screened at the bottom. We conducted a 2 x 4 factorial experiment where two types of plants were exposed to four different drainage treatments, with a total of 64 experimental units. Pots were placed in 150 L tidal mesocosms constructed from stock tanks and painted white. Simulated tides were created using tubing to pump water between the experimental tank and a reservoir, using timers to create a once-daily three-hour high tide and a 21-hour low tide. Inside four separate tanks, there were four drainage treatments: where the low tide water level was never drained (0-cm), and where the low tide water levels were drained to 5-cm, 10-cm, and 20-cm below the surface of the plant pot, The plants were propagated outdoors receiving natural precipitation. Plants were propagated in freshwater for one week, transitioned to 10 ppt salinity for one week, and finally changed over to 20 ppt salinity for the remainder of the experiment. Saline conditions were created utilizing Instant Ocean and adjusted weekly. Plants were propagated for 12 weeks from 13 May 2021 to 3 August 2021. To measure the productivity of the wetland species Spartina alterniflora and Salicornia pacifica, the aboveground and belowground biomass of each treatment was measured. Aboveground and belowground biomass was harvested at the end of week 12. Stalks growing from the soil were cut, plants were washed over a 2-mm sieve, dried at 60°C, and weighed. Belowground biomass was separated from the soil by hand, rinsed over a sieve, dried at 60°C, and then weighed. Biomass values were scaled to a square meter through multiplication by a constant. Measurements of the effects of soil drainage on abiotic parameters included porewater salinity, pH, ammonium, and hydrogen sulfide. Porewater was collected with a push pointsampler on 7 August 2021 (PPX36, MHE, East Tawas, MI, USA) at a depth of 20-cm. Samples for ammonium, pH, and salinity were frozen for later analysis. Subsamples (2 mL) were fixed with 0.22% zinc acetate solution, and frozen, for later analysis of hydrogen sulfide. Samples were analyzed for salinity and pH using a calibrated portable pH/Conductivity meter (Star A325 pH/Conductivity Portable Multiparameter Meter, Thermo Scientific Orion). UV-vis spectrophotometry was used for measurements of porewater ammonium using the indophenol blue method. Hydrogen sulfide was measured spectrophotometrically on the zinc acetate-fixed samples following the methylene blue method. All samples below the detection limit (~0.25 µM) were assigned a sulfide concentration of zero for the purposes of data analysis. Redox potential measurements were taken at depths of 5-cm and 15-cm for the Spartina alterniflora soils, and depths of 3-cm and 9-cm for Spartina pacifica soils to reflect the size of the pots using a bench-top redox meter (Bench-Top pH/mV Meter, Sper Scientific). Carbon dioxide and methane fluxes were measured to calculate the photosynthesis, respiration, and net ecosystem exchange (NEE) rates of the plants. The fluxes were measured in the field on 7 August 2021 from 10 a.m. to 4 p.m. (Eastern Standard Time), using an LGR ultra-portable greenhouse gas analyzer via cavity ring-down spectroscopy (ABB-Los Gatos Research, San Jose, CA, USA). Positive fluxes were defined as those in which gas concentrations increased over time within the chamber, and negative fluxes as those in which concentrations decreased (Nakanoa et al., 2004). Photosynthesis rates were obtained by measuring the carbon dioxide concentration as a function of time in the light and dark conditions, and then subtracting the dark measurement from the light measurement. Respiration rates were obtained by measuring the carbon dioxide concentration as a function of time in the dark conditions. All statistical analyses were performed in R 4.2.3 (R Core Team, 2023). Bar graphs and scatter plots were made using the package ggplot2. The responses of the study plants Spartina and Salicornia to drainage were analyzed using permutational multivariate analysis of variance (perMANOVAs; Anderson, 2001), utilizing the R package vegan. The dependent variables included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, NEE, photosynthesis rate, respiration rate, and methane flux. We partitioned the variability and obtained F-statistics on matrices of Euclidean distances calculated from the original raw data. P-values were calculated using 10,000 random permutations of the appropriate exchangeable units. Where values of certain variables were missing, the means of a treatment group factor were added to the matrix to ensure each variable had the same number of values. Redox was rank-transformed prior to analysis to remove negative values. Because the interaction term was significant, we conducted contrast tests using the same function (adonis2), with a Bonferroni correction applied for the number of contrasts (0.05/16 = 0.0031). Because the results of the contrasts did not reveal strong groupings, we conducted follow-up two-way ANOVAs to identify the factors contributing to significant differences between the species and drainage levels. ANOVAs were performed on rank-transformed data to account for the non-normal error structure. ANOVAs were run in base R using the aov command. Follow-up least-square means comparisons tests were completed on main effects and interactions, where appropriate, using package lsmeans using the Tukey or Sidak methods for p-value adjustments as appropriate. A principal component analysis (PCA) was used for dimension reduction of the multivariate measurements to examine variability between treatments and plant species, as well as to determine species and treatment grouping patterns with respect to the dependent variables. The eigenvalues provide a measure of the amount of variance explained by each principal component. The data matrix was constructed using the 11 dependent variables which included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, NEE, photosynthesis rate, respiration rate, and methane flux. The packages used for the PCA include cor, ggcorrplot, factoextra. To perform the PCA, the data was first normalized, and a correlation matrix was computed and visualized. Visualization of the PCA was constructed as a biplot of the first vs. second principal components. A Kaiser-Meyer-Olkin (KMO) test was used to determine how suited the data is for factor analysis, utilizing the EFAtools package. A Bartlett's test of sphericity was used to test for significant correlations among at least some of the variables, utilizing the psych package. As many of the measured variables varied in response to the drainage treatments in a multi-dimensional way, we constructed loess curves (span=0.40) to describe the relationship between treatment and the response variables of above and belowground biomass, porewater salinity, porewater pH, porewater ammonium and sulfide concentration, NEE, and redox potential. A loess curve is a nonparametric method for smoothing a series of data and was used because of the non-linear structure of the relationship between drainage and response variables

Climate Change Scenarios Reduce Water Resources in the Schuylkill River Watershed during the Next Two Decades Based on Hydrologic Modeling in STELLA

The Schuylkill River Watershed in southeastern PA provides essential ecosystem services, including drinking water, power generation, recreation, transportation, irrigation, and habitats for aquatic life. The impact of changing climate and land use on these resources could negatively affect the ability of the watershed to continually provide these services. This study applies a hydrologic model to assess the impact of climate and land use change on water resources in the Schuylkill River Basin. A hydrologic model was created within the Structural Thinking Experiential Learning Laboratory with Animation (STELLA) modeling environment. Downscaled future climate change scenarios were generated using Localized Constructed Analogs (LOCA) from 2020 to 2040 for Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 emission scenarios. Three regional land use change scenarios were developed based on historical land use and land cover change trends. The calibrated model was then run under projected climate and land use scenarios to simulate daily streamflow, reservoir water levels, and investigate the availability of water resources in the basin. Historically, the streamflow objective for the Schuylkill was met 89.8% of the time. However, the model forecasts that this will drop to 67.2–76.9% of the time, depending on the climate models used. Streamflow forecasts varied little with changes in land use. The two greenhouse gas emission scenarios considered (high and medium emissions) also produced similar predictions for the frequency with which the streamflow target is met. Barring substantial changes in global greenhouse gas emissions, the region should prepare for substantially greater frequency of low flow conditions in the Schuylkill River.Validerad;2023;Nivå 2;2023-11-13 (joosat);License fulltext: CC BY</p

Tidal Flushing Rather Than Non-Point Source Nitrogen Pollution Drives Nutrient Dynamics in A Putatively Eutrophic Estuary

The effects of nonpoint source nutrients on estuaries can be difficult to pinpoint, with researchers often using indicator species, monitoring, and models to detect influence and change. Here, we made stable isotope measurements of nitrogen and carbon in sediment, water column particulates, primary producers, and consumers at 35 stations in the reportedly eutrophic Barnegat Bay (New Jersey) to assess N sources and processing pathways. Combined with water quality and hydrological data, our C and N isoscapes revealed four distinct geographic zones with diverging isotopic baselines, indicating variable nutrient sources and processing pathways. Overall, the carbon stable isotopes (δ13C) reflected the terrestrial-marine gradient with the most depleted values in the urban and poorly flushed north of the estuary to the most enriched values in the salt marsh-dominated south. In contrast, the nitrogen stable isotope values (δ15N) were most enriched near the oceanic inlets and were consistent with offshore δ15N values in particulate organic matter. Several biogeochemical processes likely alter δ15N, but the relatively lower δ15N values associated with the most urbanized area indicate that anthropogenic runoff is not a dominant N source to this area. Our findings stand in contrast to previous studies of similar estuaries, as δ15N signatures of biota in this system are inversely correlated to population density and nutrient concentrations. Further, our analyses of archival plant (Spartina sp., Phragmites australis) and shell (Geukensia demissa, Ilyanassa obsoleta) samples collected between 1880 and 2020 indicated that δ15N values have decreased over time, particularly in the consumers. Overall, we find that water quality issues appear to be most acute in the poorly flushed parts of Barnegat Bay and emphasize the important role that oceanic exchange plays in water quality and associated estuarine food webs in the lagoon

Evaluating Thin-Layer Sediment Placement as a Tool for Enhancing Tidal Marsh Resilience: a Coordinated Experiment Across Eight US National Estuarine Research Reserves

Thin-layer sediment placement (TLP) is a promising management tool for enhancing tidal marsh resilience to rising seas. We conducted a 3-year experiment at eight US National Estuarine Research Reserves using a standardized implementation protocol and subsequent monitoring to evaluate effects of sediment placement on vegetation in low and high marsh, and compared this to control and reference plots. Sediments added to experimental plots were sourced from nearby quarries, were sandier than ambient marsh soils, and had more crab burrowing, but proved effective, suggesting that terrestrial sources can be used for tidal marsh restoration. We found strong differences among sites but detected general trends across the eight contrasting systems. Colonization by marsh plants was generally rapid following sediment addition, such that TLP plot cover was similar to control plots. While we found that 14-cm TLP plots were initially colonized more slowly than 7-cm plots, this difference largely disappeared after three years. In the face of accelerated sea-level rise, we thus recommend adding thicker sediment layers. Despite rapid revegetation, TLP plots did not approximate vegetation characteristics of higher elevation reference plots. Thus, while managers can expect fairly fast revegetation at TLP sites, the ultimate goal of achieving reference marsh conditions may be achieved slowly if at all. Vegetation recovered rapidly in both high and low marsh; thus, TLP can serve as a climate adaptation strategy across the marsh landscape. Our study illustrates the value of conducting experiments across disparate geographies and provides restoration practitioners with guidance for conducting future TLP projects