Andrew W. Schroth

Estuarine removal of glacial iron and implications for iron fluxes to the ocean

While recent work demonstrates that glacial meltwater provides a substantial and relatively labile flux of the micronutrient iron to oceans, the role of high-latitude estuary environments as a potential sink of glacial iron is unknown. Here we present the first quantitative description of iron removal in a meltwater-dominated estuary. We find that 85% of “dissolved” Fe is removed in the low-salinity region of the estuary along with 41% of “total dissolvable” iron associated with glacial flour. We couple these findings with hydrologic and geochemical data from Gulf of Alaska (GoA) glacierized catchments to calculate meltwater-derived fluxes of size and species partitioned Fe to the GoA. Iron flux data indicate that labile iron in the glacial flour and associated Fe minerals dominate the meltwater contribution to the Fe budget of the GoA. As such, GoA nutrient cycles and related ecosystems could be strongly influenced by continued ice loss in its watershed.

Characterization of Organic Phosphorus Form and Bioavailability in Lake Sediments using P Nuclear Magnetic Resonance and Enzymatic Hydrolysis.

Lake sediments are known to be a significant source of phosphorus (P) to plankton populations under certain biogeochemical conditions; however, the contribution of sediment organic P (P) to internal P loads remains poorly understood. We investigated P speciation and bioavailability in sediments collected over multiple months from a shallow, eutrophic bay in Lake Champlain (Missisquoi Bay, VT) using solution P nuclear magnetic resonance (NMR) spectroscopy and enzymatic hydrolysis (EH) analysis of sediments collected during years with (2008) and without (2007) algal blooms. Sediments collected during bloom onset (July) and peak bloom (August) months contained the largest proportion of enzyme-labile P, whereas pre- and postbloom sediments were primarily composed of nonlabile P. Monoester P to diester P ratios changed with respect to depth, particularly during bloom periods. Monoester P and DNA accumulation, likely from settling particulate matter, began at the onset of the bloom and continued into October 2008 during the postbloom period. The disappearance of inositol hexakisphosphate stereoisomers and the generation of orthophosphate at lower sediment depths was also evident in August 2008. Principal components analysis of EH and NMR species proportions confirmed differences between sediment cores collected during bloom onset and peak bloom, compared with pre- and postbloom sediments. Large enzyme-labile and P species proportions corresponded to increased sediment P flux and reduced manganese and iron species in porewater. These findings suggest that interseasonal changes in P speciation may influence P mobility in sediments and contribute to important feedback dynamics between biological productivity and sediment water interface geochemistry.

The mobility of phosphorus, iron, and manganese through the sediment–water continuum of a shallow eutrophic freshwater lake under stratified and mixed water-column conditions

The management of external nutrient inputs to eutrophic systems can be confounded due to a persistent pool of phosphorus (P) in lake sediments. The behaviors of P and trace metals depend largely on the reductive dissolution of amorphous iron (Fe) and manganese (Mn) (oxy)hydroxides in sediments; however, a holistic understanding of these dynamics in relation to the broader ecological and hydrodynamic conditions of the system remains elusive. We used a high-frequency monitoring approach to develop a comprehensive conceptual model of P, Mn, and Fe dynamics across the sediment water continuum of a shallow bay in Lake Champlain (Missisquoi Bay, USA). The greatest release of sediment P, Mn, and Fe occurred under stable hydrodynamic conditions, particularly during the onset of the cyanobacterial bloom and was associated with low available P and the accumulation of soluble Mn and Fe above the sediment–water interface (SWI). During the warmest part of the season, bloom severity and sediment P release was partially regulated by hydrodynamic drivers, which changed on hourly time scales to affect redox conditions at the SWI and bottom water concentrations of soluble P, Mn, and Fe. A geochemically distinct increase in soluble P and Fe concentrations, but not Mn, marked the influence of riverine inputs during a late season storm disturbance. Despite continued depletion of the reactive sediment P and metals pool into the bloom period, declining temperatures and a well-mixed water column resulted in bloom senescence and the return of P, Mn, and Fe to surface sediments. The closed cycling of P and metals in Missisquoi Bay poses a significant challenge for the long-term removal of P from this system. Multiple time-scale measures of physical and biogeochemical changes provide a basis for understanding P and trace metals behavior across sediments and the water column, which shape seasonally variable cyanobacterial blooms in shallow eutrophic systems.

High-frequency dissolved organic carbon and nitrate measurements reveal differences in storm hysteresis and loading in relation to land cover and seasonality

Storm events dominate riverine loads of dissolved organic carbon (DOC) and nitrate, and are expected to increase in frequency and intensity in many regions due to climate change. We deployed three high-frequency (15-minute) in-situ absorbance spectrophotometers to monitor DOC and nitrate concentration for 126 storms in three watersheds with agricultural, urban, and forested land use/land cover. We examined intrastorm hysteresis and the influences of seasonality, antecedent conditions, storm size, and dominant land use/land cover on storm DOC and nitrate loads. DOC hysteresis was generally anti-clockwise at all sites, indicating distal and plentiful sources for all three streams despite varied DOC character and sources. Nitrate hysteresis was generally clockwise for urban and forested sites, but anti-clockwise for the agricultural site, indicating an exhaustible, proximal source of nitrate in the urban and forested sites, and more distal and plentiful sources of nitrate in the agricultural site. The agricultural site had significantly higher storm nitrate yield per water yield and higher storm DOC yield per water yield than the urban or forested sites. Seasonal effects were important for storm nitrate yield in all three watersheds and farm management practices likely caused complex interactions with seasonality at the agricultural site. Hysteresis indices did not improve predictions of storm nitrate yields at any site. We discuss key lessons from using high-frequency in-situ optical sensors.

Coupled impacts of climate and land use change across a river–lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000–2040

Global climate change (GCC) is projected to bring higher-intensity precipitation and highervariability temperature regimes to theNortheasternUnited States. The interactive effects of GCCwith anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrientfluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated bywarmerwater temperatures due toGCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCCon the hydrological regime, water temperature, water quality, bloomduration and severity through 2040 in transnational Lake Champlain’sMissisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-basedmodel was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrologicalmodel to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulatedwith a 3Dhydrodynamic-biogeochemicalmodel.We find acceleratedGCC could drastically limit landmanagement options tomaintainwater quality, but the nature and severity of this impact varies dramatically byGCMandGCC scenario.

Coupling of reactive riverine phosphorus and iron species during hot transport moments: impacts of land cover and seasonality

Spring runoff often comprises the majority of annual discharge and riverine phosphorus (P) export due to sustained high flow, and the magnitude of spring runoff can be a strong predictor of receiving water summer harmful algal bloom severity. Yet the loading of reactive forms of P during this time period remains poorly-characterized in time, space and geochemical partitioning. Here, we explore the hypothesis that riverine dissolved and suspended sediment P loads during spring runoff have a particularly high proportion of potentially reactive species due to unique hydrologic pathways and P association with iron (Fe).The concentration, distribution and temporal dynamics of dissolved P (DP), dissolved and colloidal Fe, and redox sensitive suspended sediment P (RSP) and Fe during spring runoff and summer storms were compared in forested and agricultural catchments of the same watershed. The dominant carrier of RSP was Fe (oxy)hydroxides across land cover and season, but Fe (oxy)hydroxide particles and colloids in agricultural catchments were strongly enriched in RSP and DP during spring runoff and summer storms, particularly at the onset of snowmelt. In 2014, 83% of DP and 74% of RSP were delivered to Missisquoi Bay during spring runoff. Suspended sediment was significantly more redox sensitive than typically input to limnological models, suggesting that the reactivity of this load may be systematically underestimated. Changes in the timing, provenance and severity of spring runoff associated with climate or land cover change will have dramatic impacts on total riverine P loads and their potential reactivity in receiving water ecosystems.

Evaluating Spatial Variability in Sediment and Phosphorus Concentration‐Discharge Relationships Using Bayesian Inference and Self‐Organizing Maps

Given the variable biogeochemical, physical, and hydrological processes driving fluvial sediment and nutrient export, the water science and management communities need data-driven methods to identify regions prone to production and transport under variable hydrometeorological conditions. We use Bayesian analysis to segment concentration-discharge linear regression models for total suspended solids (TSS) and particulate and dissolved phosphorus (PP, DP) using 22 years of monitoring data from 18 Lake Champlain watersheds. Bayesian inference was leveraged to estimate segmented regression model parameters and identify threshold position. The identified threshold positions demonstrated a considerable range below and above the median discharge—which has been used previously as the default breakpoint in segmented regression models to discern differences between pre and post-threshold export regimes. We then applied a Self-Organizing Map (SOM), which partitioned the watersheds into clusters of TSS, PP, and DP export regimes using watershed characteristics, as well as Bayesian regression intercepts and slopes. A SOM defined two clusters of high-flux basins, one where PP flux was predominantly episodic and hydrologically driven; and another in which the sediment and nutrient sourcing and mobilization were more bimodal, resulting from both hydrologic processes at post-threshold discharges and reactive processes (e.g., nutrient cycling or lateral/vertical exchanges of fine sediment) at prethreshold discharges. A separate DP SOM defined two high-flux clusters exhibiting a bimodal concentration-discharge response, but driven by differing land use. Our novel framework shows promise as a tool with broad management application that provides insights into landscape drivers of riverine solute and sediment export.

Atmospheric deposition of glacial iron in the Gulf of Alaska impacted by the position of the Aleutian Low

Our understanding of glacial flour dust storm delivery of iron to the Gulf of Alaska (GoA) is limited. Here we interpret concurrent time-series satellite, meteorological, and aerosol geochemical data from the GoA to examine how inter-annual variability in regional weather patterns impacts offshore aerosol glacial Fe deposition. In 2011, when a northerly Aleutian Low (AL) was persistent during fall, dust emission was suppressed and highly intermittent due to prevalent wet conditions, low winds and a deep early season snowpack. Conversely, in 2012, frequent and prolonged fall dust storms and high offshore glacial Fe transport were driven by dry conditions and strong offshore winds generated by persistent strong high pressure over the Alaskan interior and Bering Sea and a southerly AL. Twenty five-fold inter-annual variability in regional offshore glacial aerosol Fe deposition indicates that glacial dusts impact on GoA nutrient budgets is highly dynamic and particularly sensitive to regional climate forcing.Our understanding of glacial flour dust storm delivery of iron to the Gulf of Alaska (GoA) is limited. Here we interpret concurrent time series satellite, meteorological, and aerosol geochemical data from the GoA to examine how interannual variability in regional weather patterns impacts offshore aerosol glacial Fe deposition. In 2011, when a northerly Aleutian Low (AL) was persistent during fall, dust emission was suppressed and highly intermittent due to prevalent wet conditions, low winds, and a deep early season snowpack. Conversely, in 2012, frequent and prolonged fall dust storms and high offshore glacial Fe transport were driven by dry conditions and strong offshore winds generated by persistent strong high pressure over the Alaskan interior and Bering Sea and a southerly AL. Twenty-five-fold interannual variability in regional offshore glacial aerosol Fe deposition indicates that glacial dusts impact on GoA nutrient budgets is highly dynamic and particularly sensitive to regional climate forcing.

Stream response to an extreme drought-induced defoliation event

We assessed stream ecosystem-level response to a drought-induced defoliation event by gypsy moth caterpillars (Lymantria dispar) with high-frequency water quality sensors. The defoliation event was compared to the prior year of data. Based on long-term records of precipitation and drought indices, the drought of 2015–2016 in Rhode Island, USA was an extreme climatic event that preceded and likely precipitated the defoliation from insect infestation. Canopy cover in the riparian area was reduced by over 50% increasing light availability which warmed the stream and stimulated autotrophic activity. Frass and leaf detritus contributed particulate carbon and organic nutrients to the stream. Based on locally calibrated s::can spectro::lyser data, nitrate concentration and flux did not significantly increase during defoliation while orthophosphate concentration and flux did significantly increase during part of the defoliation period. Lower mean daily dissolved oxygen (DO) levels and wider diel cycles of DO indicated higher biological activity during the defoliation event. Stream metabolism metrics were also significantly higher during defoliation and pointed to heterotrophic activity dominating in the stream. The increases in stream metabolism were low compared to other studies; in streams with higher nutrient levels (e.g., in agricultural or urban watersheds) the increase in light and temperature could have a stronger influence on stream metabolism. The in-stream metabolic processes and nutrient fluxes observed in response to the drought-driven defoliation event resulted from the long-term deployment of high-frequency water sensors. The proliferation of these water sensors now enable studies that assess ecosystem responses to stochastic, unusual disturbances.

Modeling the drivers of interannual variability in cyanobacterial bloom severity using self-organizing maps and high-frequency data

Abstract It is well established that cyanobacteria populations in shallow lakes exhibit dramatic fluctuations on both interannual and intraannual timescales; however, despite extensive research, disentangling the drivers of interannual variability in bloom severity has proved challenging. Critical thresholds of abiotic drivers such as wind, irradiance, air temperature, and tributary inputs may control the development and collapse of blooms, but these thresholds are difficult to identify in large and complex datasets. In this study, we compared high-frequency estimates of oxygen metabolism in a shallow bay of Lake Champlain to concurrent measurements of physical and chemical parameters over 3 years with very different bloom dynamics. We clustered the data using supervised and unsupervised self-organizing maps to identify the environmental drivers associated with key stages of bloom development. We then used threshold analysis to identify subtle yet important thresholds of thermal stratification that drive transitions between bloom growth and decline. We found that extended periods with near-surface temperature differentials above 0.20 °C were associated with the initial development of bloom conditions, and subsequent frequency and timing of wind mixing events had a strong influence on interannual variability in bloom severity. The methods developed here can be widely applied to other high frequency lake monitoring datasets to identify critical thresholds controlling bloom development.