The Nitrogen Legacy: Understanding Time Lags in Catchment Response as a Function of Hydrologic and Biogeochemical Controls

Global population has seen a more than threefold increase over the last 100 years, accompanied by rapid changes in land use and a dramatic intensification of agriculture. Such changes have been driven by a great acceleration of the global nitrogen (N) cycle, with N fertilizer use now estimated to be 100 Tg/year globally. Excess N commonly finds its way into both groundwater and surface water, leading to long-term problems of hypoxia, aquatic toxicity and drinking water contamination. Despite ongoing efforts to improve water quality in agroecosystems, results have often been disappointing, with significant lag times between adoption of accepted best management practices (BMPs) and measurable improvements in water quality. It has been hypothesized that such time lags are a result of the buildup of legacy N within the landscape over decades of fertilizer application and agricultural intensification. The central theme of my research has been an exploration of this N legacy, including (1) an investigation of the form, locations and magnitudes of legacy N stores within intensively managed catchments; (2) development of a parsimonious, process-based modeling framework for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy); and (3) use of a statistical approach to both quantifying N-related time lags at the watershed scale, and identifying the primary physical and management controls on these lags. As a result of these explorations I am able to provide the first direct, large-scale evidence of N accumulation in the root zones of agricultural soils, accumulation that may account for much of the ‘missing N’ identified in mass balance studies of heavily impacted watersheds. My analysis of long-term soil data (1957-2010) from 206 sites throughout the Mississippi River Basin (MRB) revealed N accumulation in cropland of 25-70 kg ha-1 y-1, a total of 3.8 ± 1.8 Mt y-1 at the watershed scale. A simple modeling framework was then used to show that the observed accumulation of soil organic N (SON) in the MRB over a 30-year period (142 Tg N) would lead to a biogeochemical lag time of 35 years for 99% of legacy SON, even with a complete cessation of fertilizer application. A parsimonious, process-based model, ELEMeNT (Exploration of Long-tErM Nutrient Trajectories), was then developed to quantify catchment-scale time lags based on both soil N accumulation (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model allowed me to predict the time lags observed in a 10 km2 Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. The model results showed that concentration reduction benefits are a function of the spatial pattern of implementation of conservation measures, with preferential conversion of land parcels having the shortest catchment-scale travel times providing greater concentration reductions as well as faster response times. This modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures. To better our understanding of long-term N dynamics, I expanded the ELEMeNT modeling framework described above to accommodate long-term N input trajectories and their impact on N loading at the catchment scale. In this work, I synthesized data from a range of sources to develop a comprehensive, 214-year (1800-2104) trajectory of N inputs to the land surface of the continental United States. The ELEMeNT model was used to reconstruct historic nutrient yields at the outlets of two major U.S. watersheds, the Mississippi River and Susquehanna River Basins, which are the sources of significant nutrient contamination to the Gulf of Mexico and Chesapeake Bay, respectively. My results show significant N loading above baseline levels in both watersheds before the widespread use of commercial N fertilizers, largely due to 19th-century conversion of natural forest and grassland areas to row-crop agriculture. The model results also allowed me to quantify the magnitudes of legacy N in soil and groundwater pools, thus highlighting the dominance of soil N legacies in the MRB and groundwater legacies in the SRB. It was found that approximately 85% of the annual N load in the MRB can be linked to inputs from previous years, while only 47% of SRB N loading is associated with “older” N. In addition, it was found that the dominant sources of current N load in the MRB are fertilizer, atmospheric deposition, and biological N fixation, while manure and atmospheric deposition account for approximately 64% of the current loads in the SRB. Finally, long-term N surplus trajectories were paired with long-term flow-averaged nitrate concentration data to as means of quantifying N-related lag times across an intensively managed watershed in Southern Ontario. In this analysis, we found a significant linear relationship between current flow-averaged concentrations and current N surplus values across the study watersheds. Temporal analysis, however, showed significant nonlinearity between N inputs and outputs, with a strong hysteresis effect indicative of decadal-scale lag times between changes in N surplus values and subsequent changes in flow-averaged nitrate concentrations. Annual lag times across the study watersheds ranged from 15-33 years, with a mean lag of 24.5 years. A seasonal analysis showed a distribution of lag times across the year, with fall lags being the shortest and summer lags the longest, likely due to differences in N delivery pathways. Multiple linear regression analysis of dominant controls showed tile drainage to be a strong determinant of differences in lag times across watersheds in both fall and spring, with a watershed’s fractional area under tile drainage being significantly linked to shorter lag times. In summer, tile drainage was found to be an insignificant factor in driving lag times, while a significant relationship was found between the percent soil organic matter and longer N-related lag times. By moving beyond the traditional focus on nutrient concentrations and fluxes, and instead working towards quantification of the spatio-temporal dynamics of non-point source nutrient legacies and their current and future impacts on water quality, we make a significant contribution to the science of managing human impacted landscapes. Due to the strong impacts of nutrient legacies on the time scales for recovery in at-risk landscapes, my work will enable a more accurate assessment of the outcomes of alternative management approaches in terms of both short- and long-term costs and benefits, and the evaluation of temporal uncertainties associated with different intervention strategies

The Nitrogen Legacy: Understanding Time Lags in Catchment Response as a Function of Hydrologic and Biogeochemical Controls

Global population has seen a more than threefold increase over the last 100 years, accompanied by rapid changes in land use and a dramatic intensification of agriculture. Such changes have been driven by a great acceleration of the global nitrogen (N) cycle, with N fertilizer use now estimated to be 100 Tg/year globally. Excess N commonly finds its way into both groundwater and surface water, leading to long-term problems of hypoxia, aquatic toxicity and drinking water contamination. Despite ongoing efforts to improve water quality in agroecosystems, results have often been disappointing, with significant lag times between adoption of accepted best management practices (BMPs) and measurable improvements in water quality. It has been hypothesized that such time lags are a result of the buildup of legacy N within the landscape over decades of fertilizer application and agricultural intensification. The central theme of my research has been an exploration of this N legacy, including (1) an investigation of the form, locations and magnitudes of legacy N stores within intensively managed catchments; (2) development of a parsimonious, process-based modeling framework for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy); and (3) use of a statistical approach to both quantifying N-related time lags at the watershed scale, and identifying the primary physical and management controls on these lags. As a result of these explorations I am able to provide the first direct, large-scale evidence of N accumulation in the root zones of agricultural soils, accumulation that may account for much of the ‘missing N’ identified in mass balance studies of heavily impacted watersheds. My analysis of long-term soil data (1957-2010) from 206 sites throughout the Mississippi River Basin (MRB) revealed N accumulation in cropland of 25-70 kg ha-1 y-1, a total of 3.8 ± 1.8 Mt y-1 at the watershed scale. A simple modeling framework was then used to show that the observed accumulation of soil organic N (SON) in the MRB over a 30-year period (142 Tg N) would lead to a biogeochemical lag time of 35 years for 99% of legacy SON, even with a complete cessation of fertilizer application. A parsimonious, process-based model, ELEMeNT (Exploration of Long-tErM Nutrient Trajectories), was then developed to quantify catchment-scale time lags based on both soil N accumulation (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model allowed me to predict the time lags observed in a 10 km2 Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. The model results showed that concentration reduction benefits are a function of the spatial pattern of implementation of conservation measures, with preferential conversion of land parcels having the shortest catchment-scale travel times providing greater concentration reductions as well as faster response times. This modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures. To better our understanding of long-term N dynamics, I expanded the ELEMeNT modeling framework described above to accommodate long-term N input trajectories and their impact on N loading at the catchment scale. In this work, I synthesized data from a range of sources to develop a comprehensive, 214-year (1800-2104) trajectory of N inputs to the land surface of the continental United States. The ELEMeNT model was used to reconstruct historic nutrient yields at the outlets of two major U.S. watersheds, the Mississippi River and Susquehanna River Basins, which are the sources of significant nutrient contamination to the Gulf of Mexico and Chesapeake Bay, respectively. My results show significant N loading above baseline levels in both watersheds before the widespread use of commercial N fertilizers, largely due to 19th-century conversion of natural forest and grassland areas to row-crop agriculture. The model results also allowed me to quantify the magnitudes of legacy N in soil and groundwater pools, thus highlighting the dominance of soil N legacies in the MRB and groundwater legacies in the SRB. It was found that approximately 85% of the annual N load in the MRB can be linked to inputs from previous years, while only 47% of SRB N loading is associated with “older” N. In addition, it was found that the dominant sources of current N load in the MRB are fertilizer, atmospheric deposition, and biological N fixation, while manure and atmospheric deposition account for approximately 64% of the current loads in the SRB. Finally, long-term N surplus trajectories were paired with long-term flow-averaged nitrate concentration data to as means of quantifying N-related lag times across an intensively managed watershed in Southern Ontario. In this analysis, we found a significant linear relationship between current flow-averaged concentrations and current N surplus values across the study watersheds. Temporal analysis, however, showed significant nonlinearity between N inputs and outputs, with a strong hysteresis effect indicative of decadal-scale lag times between changes in N surplus values and subsequent changes in flow-averaged nitrate concentrations. Annual lag times across the study watersheds ranged from 15-33 years, with a mean lag of 24.5 years. A seasonal analysis showed a distribution of lag times across the year, with fall lags being the shortest and summer lags the longest, likely due to differences in N delivery pathways. Multiple linear regression analysis of dominant controls showed tile drainage to be a strong determinant of differences in lag times across watersheds in both fall and spring, with a watershed’s fractional area under tile drainage being significantly linked to shorter lag times. In summer, tile drainage was found to be an insignificant factor in driving lag times, while a significant relationship was found between the percent soil organic matter and longer N-related lag times. By moving beyond the traditional focus on nutrient concentrations and fluxes, and instead working towards quantification of the spatio-temporal dynamics of non-point source nutrient legacies and their current and future impacts on water quality, we make a significant contribution to the science of managing human impacted landscapes. Due to the strong impacts of nutrient legacies on the time scales for recovery in at-risk landscapes, my work will enable a more accurate assessment of the outcomes of alternative management approaches in terms of both short- and long-term costs and benefits, and the evaluation of temporal uncertainties associated with different intervention strategies

Two centuries of nitrogen dynamics: Legacy sources and sinks in the Mississippi and Susquehanna River Basins

© American Geophysical UnionGlobal flows of reactive nitrogen (N) have increased significantly over the last century in response to agricultural intensification and elevated levels of atmospheric deposition. Despite widespread implementation conservation measures, N concentrations in surface waters are often remaining steady or continuing to increase. Although such lack of response has been attributed to time lags associated with legacy N stores in subsurface reservoirs, it is unclear what the magnitudes of such stores are and how they are partitioned between shallow soil and deeper groundwater reservoirs. Here we have synthesized data to develop a 214year (1800-2014) trajectory of N inputs to the land surface of the continental U.S. We have concurrently developed a parsimonious, process-based model, Exploration of Long-tErM Nutrient Trajectories (ELEMeNT) that pairs this input trajectory with a travel time-based approach to simulate transport and retention along subsurface pathways. Using the model, we have reconstructed historic nitrate yields at the outlets of two major U.S. watersheds, the Mississippi River Basin (MRB) and Susquehanna River Basin (SRB). Our results show significant N loading above baseline levels in both watersheds before the widespread use of commercial N fertilizers, largely due to the conversion of forest and grassland to row crop agriculture. Model results also allow us to quantify the magnitudes of legacy N in soil and groundwater pools and to highlight the dominance of soil legacies in MRB and groundwater legacies in SRB. Approximately 55% and 18% of the current annual N loads in the MRB and SRB were found to be older than 10years of age.NSERC Discovery Grant; Ontario Early Researcher Awar

Legacy Phosphorus Across Canada: Insights from a 60-Year Dataset

Human activities over decades of agriculture and urbanization have altered phosphorus (P) cycling, posing a threat to water quality and ecosystem function. Algal blooms have become a pervasive problem in both small and large waterbodies across Canada. Despite concerted efforts to reduce P loading to surface waters, there has yet to be a noticeable improvement in water quality. This can be attributed to the accumulation of legacy P in the landscape as a result of excessive use of synthetic fertilizers and the production of livestock manure. These legacy P can reach the waterbodies decades after implementing P management practices. Therefore, to better understand long-term P dynamics and their drivers, it is crucial to develop long-term datasets of P inputs and outputs. We developed a 60-year (1961–2021), 250-meter grid resolution data of P components and P surplus across Canada. P surplus is the difference between P inputs (fertilizer inputs, livestock manure, detergent, and human waste) and non-hydrological P output (crop uptake). Our result shows the different drivers of P surplus across Canada. In Ontario and Quebec, the P surplus decreased from nutrient regulation programs in 1981 and subsequently rebounded in 2006 due to an increase in P fertilizer use. In prairie provinces, low P inputs and increasing crop yields have led to the mining of the P stores in the soils. This new, longer dataset will improve our understanding of long-term P dynamics and allow for explicit consideration of the impacts of legacy P on environmental outcomes.This research was undertaken thanks, in part, with support from the Global Water Futures Program funded by the Canada First Research Excellence Fund (CFREF)

Modelling Legacy Nitrogen Dynamics in the Transboundary Lake Erie Watershed

Lake Erie is a source of drinking water, recreation, and commercial opportunity for both the United States and Canada, making the protection of its water quality essential. In the past decades, Lake Erie's ecosystems have been adversely impacted by recurring toxic algal blooms. These algal blooms are attributed to nitrogen (N) and phosphorus pollution from agricultural runoff. Despite recent efforts to reduce N application in the Lake Erie basin, high levels of N concentration persist in surface and groundwater systems. One of the reasons for this apparent stasis in N concentrations is legacy stores of N in landscapes that contribute to lag times in water quality response, even after inputs have ceased. Legacy N is stored in the soil and slow-moving groundwater and makes up a large portion of current N contamination. Here, we aim to quantify N legacies across the entire Lake Erie basin to predict time lags in water quality improvements in surface and groundwater. We use a process-based model, ELEMeNT, to quantify legacy N stores and watershed-scale N dynamics over the past century across the basin. Such models inform nutrient management practices across the Lake Erie basin by explicitly incorporating legacy dynamics. Our study shows that N surplus (the difference between N inputs and non-hydrological N outputs) has been rising across most Lake Erie sub-watersheds since 1950 and has only started to plateau or decrease around 2000. Agricultural inputs from manure, fertilizer, and biological fixation were the lead contributors to N surplus in agricultural sub-watersheds, and domestic N was the lead N contributor in urban sub-watersheds. Since 1950, between 4% and 44% of N has been stored as legacy N (23% median). On average, 92% of this N legacy is retained in the soil and 8% is in the groundwater. Through correlation analysis, we have found that higher fractions of groundwater N and SON legacy accumulation are correlated with slower travel times and lower tile drainage, while wastewater denitrification emerged as the dominant component in urban sub-watersheds. These results provide insight into drivers of legacy N and N release in sub-watersheds, which could aid in targeted nutrient management across the watershed.This research was undertaken thanks, in part, with support from the Global Water Futures Program funded by the Canada First Research Excellence Fund (CFREF

Failure of human rhombic lip differentiation underlies medulloblastoma formation

Medulloblastoma (MB) comprises a group of heterogeneous paediatric embryonal neoplasms of the hindbrain with strong links to early development of the hindbrain 1–4. Mutations that activate Sonic hedgehog signalling lead to Sonic hedgehog MB in the upper rhombic lip (RL) granule cell lineage 5–8. By contrast, mutations that activate WNT signalling lead to WNT MB in the lower RL 9,10. However, little is known about the more commonly occurring group 4 (G4) MB, which is thought to arise in the unipolar brush cell lineage 3,4. Here we demonstrate that somatic mutations that cause G4 MB converge on the core binding factor alpha (CBFA) complex and mutually exclusive alterations that affect CBFA2T2, CBFA2T3, PRDM6, UTX and OTX2. CBFA2T2 is expressed early in the progenitor cells of the cerebellar RL subventricular zone in Homo sapiens, and G4 MB transcriptionally resembles these progenitors but are stalled in developmental time. Knockdown of OTX2 in model systems relieves this differentiation blockade, which allows MB cells to spontaneously proceed along normal developmental differentiation trajectories. The specific nature of the split human RL, which is destined to generate most of the neurons in the human brain, and its high level of susceptible EOMES +KI67 + unipolar brush cell progenitor cells probably predisposes our species to the development of G4 MB

Road Salt Legacies: Quantifying Fluxes of Chloride to Groundwater and Surface Water across the Chicago Metropolitan Statistical Area

Groundwater Chloride Data for the Chicago Metropolitan Statistical Area</p

Data from: Signatures of human impact: size distributions and spatial organization of wetlands in the prairie pothole landscape

More than 50% of global wetland area has been lost over the last 200 years, resulting in losses of habitat and species diversity as well as decreased hydrologic and biogeochemical functionality. Recognition of the magnitude of wetland loss as well as the wide variety of ecosystem services provided by wetlands has in recent decades led to an increased focus on wetland restoration. Restoration activities, however, often proceed in an ad-hoc manner, with a focus on maximizing the total restored area rather than on other spatial attributes of the wetland network, which are less well understood. In this study, we have addressed the question of how human activities have altered the size distribution and spatial organization of wetlands over the Prairie Pothole Region of the Des Moines Lobe using high-resolution LIDAR data. Our results show that as well as the generally accepted 90% loss of depressional wetland area, there has been a disproportionate loss of both smaller and larger wetlands, with a marked alteration of the historical power-law relationship observed between wetland size and frequency and a resulting homogenization of the wetland size distribution. In addition, our results show significant decreases in perimeter-to-area ratios, increased mean distances between wetlands, particularly between smaller wetlands, and a reduced likelihood that current wetlands will be located in upland areas. Such patterns of loss can lead to disproportionate losses of ecosystem services, as smaller wetlands with larger perimeter-to-area ratios have been found to provide higher rates of biogeochemical processing and groundwater recharge, while increased mean distances between wetlands hinder species migration and thus negatively impact biodiversity. These results suggest the need to gear restoration efforts towards understanding and recreating the size distribution and spatial organization of historical wetlands, rather than focusing primarily on an increase in overall area

Catchment legacies and time lags: a parsimonious watershed model to predict the effects of legacy storage on nitrogen export.

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures