No abstract

River export of nitrogen (N) is influenced strongly by spatial variation in anthropogenic N inputs and climatic variation. We developed a model of riverine N export for 18 Lake Michigan Basin watersheds based on N budgets at 5-year intervals from 1974 to 1992. N inputs explained a high proportion of the spatial variation in river export but virtually none of the temporal variation, whereas between year N export was related to variation in discharge for over one-half of the rivers. A regression model of riverine N exports as an exponential function of N inputs and a powerfunction of annual water discharge accounted for 87% of the variation in annual total nitrogen fluxes over space and time. Application of this model to three scenarios of future land use, including business as usual, greater reliance on organic farming methods, and expanded corn-based ethanol production, and two climate scenarios, including increases in water discharge by 5% and 10%, suggests that riverine N export is likely to increase by as much as 24% in response to heavierfertilizer use for expanded corn production and a 10% increase in annual discharge. However, N export by rivers could decrease below present-day export through reduced reliance on commercial fertilizer use.

The t-distributed stochastic neighbor embedding t-SNE is a new dimension reduction and visualization technique for high-dimensional data. t-SNE is rarely applied to human genetic data, even though it is commonly used in other data-intensive biological fields, such as single-cell genomics. We explore the applicability of t-SNE to human genetic data and make these observations: (i) similar to previously used dimension reduction techniques such as principal component analysis (PCA), t-SNE is able to separate samples from different continents; (ii) unlike PCA, t-SNE is more robust with respect to the presence of outliers; (iii) t-SNE is able to display both continental and sub-continental patterns in a single plot. We conclude that the ability for t-SNE to reveal population stratification at different scales could be useful for human genetic association studies.

We estimated net anthropogenic phosphorus inputs (NAPI) to 18 Lake Michigan (LM) and 6 Lake Erie (LE) watersheds for 1974, 1978, 1982, 1987, and 1992. NAPI quantifies all anthropogenic inputs of P (fertilizer use, atmospheric deposition, and detergents) as well as trade of P in food and feed, which can be a net input or output. Fertilizer was the dominant input overall, varying by three orders of magnitude among the 24 watersheds, but detergent was the largest input in the most urbanized watershed. NAPI increased in relation to area of disturbed land (R 2 = 0.90) and decreased with forested and wetland area (R 2 = 0.90). Export of P by rivers varied with NAPI, especially for the 18 watersheds of LM (R 2 = 0.93), whereas the relationship was more variable among the six LE watersheds (R 2 = 0.59). On average, rivers of the LE watersheds exported about 10% of NAPI, whereas LM watersheds exported 5% of estimated NAPI. A comparison of our results with others as well as nitrogen (N) budgets suggests that fractional export of P may vary regionally, as has been reported for N, and the proportion of P inputs exported by rivers appears lower than comparable findings with N.Keywords Phosphorus Á NAPI Á P export Á River Á Watershed Á Nutrient budget Á Nutrient loading Á Lake Michigan Á Lake Erie Abbreviations LELake Erie LM Lake Michigan NANI Net anthropogenic nitrogen input NAPI Net anthropogenic phosphorus input NLCD National Land Cover Database RMSE Root mean squared error

Catchment nitrogen (N) budgets are a valuable tool to assess relative magnitude of N inputs and predict losses via riverine export. However, a range of computational approaches may be chosen, potentially affecting the modeled relationship between inputs and exports. To determine the influence of various assumptions and computational details on the effectiveness of N input estimates in predicting riverine N export, we compared eight separate net anthropogenic N input budgets and one soils compartment budget for each of 18 Lake Michigan catchments. N input estimation methods that took into account seasonal fluctuations in livestock numbers and estimated crop N-fixation by legume yield rather than area harvested best predicted river N export. The average annual river export of N from the 18 catchments ranged from less than 300 kg N km -2 year -1 in forested areas to more than 800 kg-N km -2 year -1 in agricultural catchments and 1,580 kg-N km -2 year -1 in small urban catchments. Using the most effective model (R 2 = 0.95, median prediction error = 1.8%) riverine N exports were found to account for 21% of N inputs. Other methods predicted riverine N exports less well (R 2 = 0.61-0.73), bias was greater, and the fractional export of N inputs by rivers decreased to *13%. The soil N budget also was a less effective predictor of river export. This comparison demonstrates that N budgeting that incorporates more detailed description of agricultural N sources can substantially improve prediction of riverine N exports from catchments with a wide range of landscape characteristics.