Deep soil nitrogen storage slows nitrate leaching through the vadose zone.

Nitrogen (N) fertilizer applications are important for agricultural yield, yet not all the applied N is taken up by crops, leading to surplus N storage in soil or leaching to groundwater and surface water. Leaching loss of fertilizer N represents a cost for farmers and has consequences for human health and the environment, especially in the southern Willamette Valley, Oregon, USA, where groundwater nitrate contamination is prevalent. While improved nutrient management and conservation practices have been implemented to minimize leaching, nitrate levels in groundwater continue to increase in many long-term monitoring wells. To elucidate controls on leaching rates and N dynamics in agricultural soils across soil depths, and in response to seasonal and annual variation in management (e.g., fertilizer input amount and summer irrigation), we intensively monitored the transport of water and nitrate every two weeks for four years through the vadose zone at three depths (0.8, 1.5, and 3.0 m) in a sweet corn (maize) field. Though nitrate leaching was highly variable among lysimeters at the same depth and across years, a strong pattern emerged: annual nitrate leaching significantly decreased with depth across the study, averaging ~104 kg N ha-1 yr-1 near the surface (0.8 m) versus ~56 kg N ha-1 yr-1 in the deep soil (3.0 m), a 54% reduction in leaching between the soil layers. Even though crops were irrigated in summer, most leaching (~72% below 3.0 m) occurred during the wet fall and winter. Based on steady state assumptions, a net equivalent of ~29% of surface N inputs leached below 3.0 m into the deeper soil and groundwater, while ~44% was removed in crop harvest, indicating considerable N retention in the soil (~27% of inputs or approximately 58 kg N ha-1 yr-1). The accumulation and long-term dynamics of deep soil N is a legacy of agricultural management that should be further studied to better manage and reduce nitrate loss to groundwater.

Validation of rapid assessment methods to determine streamflow duration classes in the Pacific Northwest, USA.

United States Supreme Court rulings have created uncertainty regarding U.S. Clean Water Act (CWA) authority over certain waters, and established new data and analytical requirements for determining CWA jurisdiction. Thus, rapid assessment methods are needed that can differentiate between ephemeral, intermittent, and perennial streams. We report on the validation of several methods. The first (Interim Method) was developed through best professional judgment (BPJ); an alternative (Revised Method) resulted from statistical analysis. We tested the Interim Method on 178 study reaches in Oregon, and constructed the Revised Method based on statistical analysis of the Oregon data. Next, we evaluated the regional applicability of the methods on 86 study reaches across a variety of hydrologic landscapes in Washington and Idaho. During the second phase, we also compared the Revised Method with a similar approach (Combined Method) based on combined field data from Oregon, Washington, and Idaho. We further compared field-based methods with a GIS-based approach (GIS Method) that used the National Hydrography Dataset and a synthetic stream network. Evaluations of all methods compared results with actual streamflow duration classes. The Revised Method correctly determined known streamflow duration 83.9% of the time, versus 62.3% accuracy of the Interim Method and 43.6% accuracy for the GIS-based approach. The Combined Method did not significantly outperform the Revised Method. Analysis showed biological indicators most accurately discriminate streamflow duration classes. While BPJ established a testable hypothesis, this study illustrates the importance of quantitative field testing of rapid assessment methods. Results support a consistent method applicable across the Pacific Northwest.

Foliage physiology and biochemistry in response to light gradients in conifers with varying shade tolerance.

To examine the predictability of leaf physiology and biochemistry from light gradients within canopies, we measured photosynthetic light-response curves, leaf mass per area (LMA) and concentrations of nitrogen, phosphorus and chlorophyll at 15-20 positions within canopies of three conifer species with increasing shade tolerance, ponderosa pine [Pinus ponderosa (Laws.)], Douglas fir [Pseudotsuga menziesii (Mirb.) Franco], and western hemlock [Tsuga heterophylla (Raf.) Sarg.]. Adjacent to each sampling position, we continuously monitored photosynthetically active photon flux density (PPFD) over a 5-week period using quantum sensors. From these measurements we calculated FPAR: integrated PPFD at each sampling point as a fraction of full sun. From the shadiest to the brightest canopy positions, LMA increased by about 50% in ponderosa pine and 100% in western hemlock; Douglas fir was intermediate. Canopy-average LMA increased with decreasing shade tolerance. Most foliage properties showed more variability within and between canopies when expressed on a leaf area basis than on a leaf mass basis, although the reverse was true for chlorophyll. Where foliage biochemistry or physiology was correlated with FPAR, the relationships were non-linear, tending to reach a plateau at about 50% of full sunlight. Slopes of response functions relating physiology and biochemistry to ln(FPAR) were not significantly different among species except for the light compensation point, which did not vary in response to light in ponderosa pine, but did in the other two species. We used the physiological measurements for Douglas fir in a model to simulate canopy photosynthetic potential (daily net carbon gain limited only by PPFD) and tested the hypothesis that allocation of carbon and nitrogen is optimized relative to PPFD gradients. Simulated photosynthetic potential for the whole canopy was slightly higher (<10%) using the measured allocation of C and N within the canopy compared with no stratification (i.e., all foliage identical). However, there was no evidence that the actual allocation pattern was optimized on the basis of PPFD gradients alone; simulated net carbon assimilation increased still further when even more N and C were allocated to high-light environments at the canopy top.