Nitrate Runoff Contributing from the Agriculturally Intensive San Joaquin River Watershed to Bay-Delta in California

Governing Ecological Connectivity in Cross-Scale Dependent Systems

Ecosystem management and governance of cross-scale dependent systems require integrating knowledge about ecological connectivity in its multiple forms and scales. Although scientists, managers, and policymakers are increasingly recognizing the importance of connectivity, governmental organizations may not be currently equipped to manage ecosystems with strong cross-boundary dependencies. Managing the different aspects of connectivity requires building social connectivity to increase the flow of information, as well as the capacity to coordinate planning, funding, and actions among both formal and informal governance bodies. We use estuaries in particular the San Francisco Estuary, in California, in the United States, as examples of cross-scale dependent systems affected by many intertwined aspects of connectivity. We describe the different types of estuarine connectivity observed in both natural and human-affected states and discuss the human dimensions of restoring beneficial physical and ecological processes. Finally, we provide recommendations for policy, practice, and research on how to restore functional connectivity to estuaries.

Restoring wetlands on intensive agricultural lands modifies nitrogen cycling microbial communities and reduces N2O production potential

The concentration of nitrous oxide (N₂O), an ozone-depleting greenhouse gas, is rapidly increasing in the atmosphere. Most atmospheric N₂O originates in terrestrial ecosystems, of which the majority can be attributed to microbial cycling of nitrogen in agricultural soils. Here, we demonstrate how the abundance of nitrogen cycling genes vary across intensively managed agricultural fields and adjacent restored wetlands in the Sacramento-San Joaquin Delta in California, USA. We found that the abundances of nirS and nirK genes were highest at the intensively managed organic-rich cornfield and significantly outnumber any other gene abundances, suggesting very high N₂O production potential. The quantity of nitrogen transforming genes, particularly those responsible for denitrification, nitrification and DNRA, were highest in the agricultural sites, whereas nitrogen fixation and ANAMMOX was strongly associated with the wetland sites. Although the abundance of nosZ genes was also high at the agricultural sites, the ratio of nosZ genes to nir genes was significantly higher in wetland sites indicating that these sites could act as a sink of N₂O. These findings suggest that wetland restoration could be a promising natural climate solution not only for carbon sequestration but also for reduced N₂O emissions.

Crop growth, hydrology, and water quality dynamics in agricultural fields across the Western Lake Erie Basin: Multi-site verification of the Nutrient Tracking Tool (NTT)

Agricultural field- and watershed-scale water quality models are used to assess the potential impact of management practices to reduce nutrient and sediment exports. However, observed data are often not available to calibrate and verify these models. Three years of data from the U.S. Department of Agriculture-Agricultural Research Service's 12 paired edge-of-field sites in northwest Ohio were used to calibrate and validate the Nutrient Tracking Tool. The goal of this study was to identify a single optimal parameter set for the Nutrient Tracking Tool in simulating annual crop yields, water balance, and nutrient loads across the Western Lake Erie Basin. A multi-site and multi-objective auto-calibration subroutine was developed in R to perform model calibration across the edge-of-field sites. The statistical metrics and evaluation criteria used in comparing the simulated results with the observed data were: Cohen's D Effect Size (Cohen's D < 0.20) and Percent bias (PBIAS ± 10% for crop yields, subsurface (tile) discharge, and surface runoff and ± 25% for dissolved reactive phosphorus (DRP) and nitrate‑nitrogen (nitrate-N) in tile discharge, and DRP, particulate phosphorus, and nitrate-N in surface runoff). In both calibration and validation, the Cohen's D and PBIAS for annual crop yields, tile discharge, surface runoff, DRP, particulate P, and nitrate-N showed that the average simulated results were similar to the average observed values for each variable. The calibrated model simulated well the annual averages of crop yields, flows, and nutrient losses across fields. The tile drainage and phosphorus transport subroutines in the Nutrient Tracking Tool should be further improved to better simulate the dynamics of discharge and phosphorus transport through subsurface drainage. Stakeholders can use the verified model to evaluate the effectiveness of conservation practices in improving the water quality across the Western Lake Erie Basin.

Investigation of watershed nutrient export affected by extreme events and the corresponding sampling frequency

Although the real-time monitoring technique has been widely applied due to the improvement of sensors, development of traditional sampling methods is still worth of being discussed due to the economically feasibility. Currently, extreme events (e.g. extreme rainfall caused by climate change) play a relatively important role in nutrient export. However, impacts of extreme events on the optimization of sampling strategy is still not well addressed despite the uncertainty of different frequency sampling programs has been sufficiently discussed in previous studies. Therefore, the corresponding impact of extreme events impact on the optimization of sampling strategy was investigated by examining temporal (i.e., inter-annual and seasonal) variations of available data. Uncertainty of nutrient flux estimates under different sampling frequencies was explored by subsampling daily monitoring data. Results showed that uncertainty in flux estimates differed between nitrogen and phosphorus. The relative error (RE) in annual TN flux estimates ranged from -4.2% to 2.4% (once per three-day) to -21.4-31.1% (monthly sampling), while the RE in annual TP flux estimates varied from -14.1% to 8.2% (once per three-day) to -65.9%-163.4% (monthly sampling). Biweekly and weekly sampling routines are considered the optimal sampling program for total nitrogen (TN) and for total phosphorus (TP) when the extreme events impact were not been considered. The uncertainty of flux estimates with different sampling frequencies increased with the increasing extreme events. High level of uncertainty occurred in years with the most extreme events in 2012 (RE: 21.4-69.0% for TN, 33.3-96.6% for TP), while the lowest can be found in 2011 (RE: 0-20.7% for TN, 0-48.3% for TP) (with the fewest extreme events). In addition, uncertainty in TN and TP flux estimates was generally greater during summer season than during other seasons. These results highlighted the important role of extreme events in nutrient export. Approximately half of the annual TN and TP flux occurred in some extreme days that only accounted for less than 20% in the same year. The onset of these extremes of nutrient export was likely due to the stormflow with addition of external fertilizer and the direct discharge of surface ponding water from paddy fields during special periods of time. These results would be helpful for the optimization of sampling strategy.