Model Forecasts Long-Term Impacts of Forest Land-Use Decisions

The drive to develop crops for use in biofuels is raising questions about how to use forest land. A new computer model developed at North Carolina State University offers the most detailed insight yet into predicting how these new land uses might impact the environment – and may also help us understand how the forest ecosystem will respond to global climate change.

“We think the model will help policy makers and forest managers make informed decisions to maintain forest productivity while minimizing the environmental impact of managed forest plantations,” says Dr. Shiying Tian, a postdoctoral researcher at NC State, and lead author of a paper on the new model. “It also will help us understand how these forest systems will respond if we see changes in temperature or precipitation related to climate change,” says Dr. Mohamed Youssef, an assistant professor biological and agricultural engineering at NC State, and co-author of the paper.

NC State researchers had previously developed models that accounted for the hydrology, carbon and nitrogen cycles in agricultural land with high water table soils. The new model, called DRAINMOD-FOREST, extends the models’ applicability to forest land by accounting for plant growth in the forest ecosystem. The model addresses how trees and other forest vegetation affect – and are affected by – the water, carbon, and nitrogen cycles. DRAINMOD-FOREST looks specifically at forests in areas with a high water table – such as coastal regions.

The new model is timely, due to a number of emerging land uses for forest land. For example, there is national interest in identifying new means of growing biofuels crops, such as switchgrass. One idea has been to plant switchgrass in the space between trees in commercial forests. DRAINMOD-FOREST will help determine whether such an “inter-crop” method is viable and sustainable. Would it hinder tree growth? What would the environmental consequences be?

But the model has other applications as well. For example, “We could also use the model to determine the viability and environmental impact of introducing new commercial tree species,” Tian says.

“This is a whole-system model,” Youssef says. “We look at the hydrology, or water cycle, of the system. We look at the nitrogen and carbon cycles. And we look at plant growth in the forest system. This is the most thorough model yet for forest ecosystems in the coastal regions of the southern and southeastern United States.”

The paper, “DRAINMOD-FOREST: Integrated Modeling of Hydrology, Soil Carbon and Nitrogen Dynamics, and Plant Growth for Drained Forests,” is published in the May issue of the Journal of Environmental Quality. The paper was co-authored by Tian; Youssef; Dr. Wayne Skaggs, William Neal Reynolds Professor of Biological and Agricultural Engineering at NC State; Dr. Devendra Amatya of the U.S. Department of Agriculture (USDA) Forest Service; and Dr. George Chescheir, associate research professor of biological and agricultural engineering at NC State.

The research was supported by the USDA Forest Service, National Council for Air and Stream Improvement, North Carolina Agricultural Research Service and the Weyerhaeuser Company.

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Note to Editors: The study abstract follows.

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

Authors: Shiying Tian, Mohamed A. Youssef, R. Wayne Skaggs and G.M. Chescheir, North Carolina State University; Devendra M. Amatya, USDA Forest Service

Published: May 2012, Journal of Environmental Quality

Abstract: This paper presented 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 the hydrological model, DRAINMOD, and the soil C and N dynamics model, DRAINMOD-N II, to a forest growth model, which was mainly adapted from 3-PG model. The forest growth model estimates net primary production, carbon allocation, and litterfall using physiology based methods that 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-year) data set collected from an artificially drained loblolly pine (Pinus taeda 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 coefficient of 0.93, 0.87and 0.75, respectively. The model also reasonably predicted annual net primary productivity and dynamics of leaf area index. Predicted temporal changes in the organic matter pool on the forest floor and in forest soil were reasonable compared to published literatures. Both predicted annual and monthly nitrate export were in good agreement with field measurements, as indicated by Nash–Sutcliffe coefficient above 0.89 and 0.79 for annual and monthly predictions, respectively. This application of DRAINMOD-FOREST demonstrated its capability for predicting hydrology, C and N dynamics in drained forests under limited silvicultural practices.