Impacts on soil nitrogen availability of converting managed pine plantation into switchgrass monoculture for bioenergy.

Biofuels derived from lignocellulosic materials is one of the options in addressing issues on climate change and energy independence. One of the most promising bioenergy crops is switchgrass (Panicum virgatum L.), particularly in North America. Future advancement in large-scale conversion of lignocellulosic feedstocks and relatively more competitive price for biomass and other economic advantages could lead to landowners opting to venture on switchgrass monoculture (SWITCH) in lieu of loblolly pine monoculture (PINE). Therefore, we investigated the conversion of previously managed loblolly pine stand into SWITCH in eastern North Carolina, U.S.A. on soil N availability. Treatments included PINE, SWTICH, and mature loblolly pine stand (REF). Each treatment was replicated three times on 0.8 ha plots drained by open ditches dug 1.0-1.2 m deep and spaced at 100 m. Rates of net N mineralization (Nm) and nitrification (Nn) at the top 20 cm were measured using sequential in-situ techniques in 2011 and 2012 (the 3rd and 4th years of establishment, respectively) along with a one-time laboratory incubation. On average, PINE, SWITCH, and REF can have field net Nm rates up to 0.40, 0.34 and 0.44 mg N·kg soil-1·d-1, respectively, and net Nn rates up to 0.14, 0.08 and 0.10 mg N·kg soil-1·d-1, respectively. Annually, net Nm rates ranged from 136.98 to 167.21, 62.00 to 142.61, and 63.57 to 127.95 kg N·ha-1, and net Nn rates were 56.31-62.98, 16.45-30.45, 31.99-32.94 kg N·ha-1 in PINE, SWITCH, and REF, respectively. Treatment effect was not significant on field Nm rate (p = 0.091). However, SWITCH significantly reduced nitrate-N production (p < 0.01). Overall, results indicated that establishment of SWITCH on poorly drained lands previously under PINE is less likely to significantly impact total soil N availability and potentially has minimum N leaching losses since soil mineral N under this system will be dominated by ammonium-N.

Temporal variations and controlling factors of nitrogen export from an artificially drained coastal forest.

Nitrogen losses in drainage water from coastal forest plantations can constrain the long term sustainability of the system and could negatively affect adjacent nutrient sensitive coastal waters. Based on long-term (21 years) field measurements of hydrology and water quality, we investigated the temporal variations and controlling factors of nitrate and dissolved organic nitrogen (DON) export from an artificially drained coastal forest over various time scales (interannual, seasonal, and storm events). According to results of stepwise multiple linear regression analyses, the observed large interannual variations of nitrate flux and concentration from the drained forest were significantly (p < 0.004) controlled by annual mean water table depth, and annual drainage or precipitation. Annual precipitation and drainage were found to be dominant factors controlling variations of annual DON fluxes. Temporal trends of annual mean DON concentration could not be explained explicitly by climate or hydrologic factors. No significant difference was observed between nitrogen (both nitrate and DON) export during growing and nongrowing seasons. Nitrate exhibited distinguished export patterns during six selected storm events. Peak nitrate concentrations during storm events were significantly (p < 0.003) related to 30-day antecedent precipitation index and the minimum water table depth during individual events. The temporal variations of DON export within storm events did not follow a clear trend and its peak concentration during the storm events was found to be significantly (p < 0.006) controlled by the short-term drying and rewetting cycles.

DRAINMOD-FOREST: Integrated Modeling of Hydrology, Soil Carbon and Nitrogen Dynamics, and Plant Growth for Drained Forests.

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model, which was adapted mainly from the 3-PG model. The forest growth model estimates net primary production, C allocation, and litterfall using physiology-based methods regulated by air temperature, water deficit, stand age, and soil N conditions. The performance of the newly developed DRAINMOD-FOREST model was evaluated using a long-term (21-yr) data set collected from an artificially drained loblolly pine ( L.) plantation in eastern North Carolina, USA. Results indicated that the DRAINMOD-FOREST accurately predicted annual, monthly, and daily drainage, as indicated by Nash-Sutcliffe coefficients of 0.93, 0.87, and 0.75, respectively. The model also predicted annual net primary productivity and dynamics of leaf area index reasonably well. Predicted temporal changes in the organic matter pool on the forest floor and in forest soil were reasonable compared to published literature. Both predicted annual and monthly nitrate export were in good agreement with field measurements, as indicated by Nash-Sutcliffe coefficients above 0.89 and 0.79 for annual and monthly predictions, respectively. This application of DRAINMOD-FOREST demonstrated its capability for predicting hydrology and C and N dynamics in drained forests under limited silvicultural practices.

Impacts of fertilization on water quality of a drained pine plantation: a worst case scenario.

Intensive plantation forestry will be increasingly important in the next 50 yr to meet the high demand for domestic wood in the United States. However, forest management practices can substantially influence downstream water quality and ecology. This study analyses, the effect of fertilization on effluent water quality of a low gradient drained coastal pine plantation in Carteret County, North Carolina using a paired watershed approach. The plantation consists of three watersheds, two mature (31-yr) and one young (8-yr) (age at treatment). One of the mature watersheds was commercially thinned in 2002. The mature unthinned watershed was designated as the control. The young and mature-thinned watersheds were fertilized at different rates with Arborite (Encee Chemical Sales, Inc., Bridgeton, NC), and boron. The outflow rates and nutrient concentrations in water drained from each of the watersheds were measured. Nutrient concentrations and loadings were analyzed using general linear models (GLM). Three large storm events occurred within 47 d of fertilization, which provided a worst case scenario for nutrient export from these watersheds to the receiving surface waters. Results showed that average nutrient concentrations soon after fertilization were significantly (alpha = 0.05) higher on both treatment watersheds than during any other period during the study. This increase in nutrient export was short lived and nutrient concentrations and loadings were back to prefertilization levels as soon as 3 mo after fertilization. Additionally, the mature-thinned watershed presented higher average nutrient concentrations and loadings when compared to the young watershed, which received a reduced fertilizer rate than the mature-thinned watershed.

Substrate organic matter to improve nitrate removal in surface-flow constructed wetlands.

A wetland mesocosm experiment was conducted in eastern North Carolina to determine if organic matter (OM) addition to soils used for in-stream constructed wetlands would increase NO3--N treatment. Not all soils are suitable for wetland substrate, so OM addition can provide a carbon and nutrient source to the wetland early in its development to enhance denitrification and biomass growth. Four batch studies, with initial NO3--N concentrations ranging from 30 to 120 mg L-1, were conducted in 2002 in 21 surface-flow wetland mesocosms. The results indicated that increasing the OM content of a Cape Fear loam soil from 50 g kg-1 (5% dry wt.) to 110 g kg-1 (11% dry wt.) enhanced NO3--N wetland treatment efficiency in spring and summer batch studies, but increases to 160 g kg-1 (16% dry wt.) OM did not. Wetlands constructed with dredged material from the USACE Eagle Island Confined Disposal Facility in Wilmington, NC, with initial OM of 120 g kg-1 (12% dry wt.), showed no improvement in NO3--N treatment efficiency when increased to 180 g kg-1 (18% dry wt.), but did show increased NO3--N treatment efficiency in all batch studies when increased to 220 g kg-1 (22% dry wt.). Increased OM addition and biosolids to the Cape Fear loam and dredged material blends significantly increased biomass growth in the second growing season when compared to no OM addition. Results of this research indicate that increased OM in the substrate will reduce the area required for in-stream constructed wetlands to treat drainage water in humid regions. It also serves as a demonstration of how dredged material can be used successfully in constructed wetlands, as an alternative to costly storage by the USACE.

Field evaluation of a model for predicting nitrogen losses from drained lands.

The N simulation model, DRAINMOD-N II, was field-tested using a 6-yr data set from an artificially drained agricultural site located in eastern North Carolina. The test site is on a nearly flat sandy loam soil which is very poorly drained under natural conditions. Four experimental plots, planted to a corn (Zea mays)-wheat (Triticum aestivum L.)-soybean (Glycine max.) rotation and managed using conventional and controlled drainage, were used in model testing. Water table depth, subsurface drainage, and N concentration in drain flow were measured and meteorological data were recorded continuously. DRAINMOD-N II was calibrated using the data from one plot; data sets from the other three plots were used for model validation. Simulation results showed an excellent agreement between observed and predicted nitrate-nitrogen (NO(3)-N) losses in drainage water over the 6-yr period and a reasonable agreement on an annual basis. The agreement on a monthly basis was not as good. The Nash-Sutcliffe modeling efficiency (EF) for monthly predictions was 0.48 for the calibration plot and 0.19, 0.01, and -0.02 for the validation plots. The value of the EF for yearly predictions was 0.92 for the calibration plot and 0.73, 0.62, and -0.10 for the validation plots. Errors in predicting cumulative NO(3)-N losses over the 6-yr period were remarkably small; -1.3% for the calibration plot, -8.1%, -2.8%, and 4.0% for the validation plots. Results of this study showed the potential of DRAINMOD-N II for predicting N losses from drained agricultural lands. Further research is needed to test the model for different management practices and soil and climatological conditions.

Modeling denitrification in terrestrial and aquatic ecosystems at regional scales.

Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source-transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures.