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E
Examples of Watershed-Scale or Landscape-Scale Research
That Provide the Foundation for a Landscape Vision of
Production of Biofuel Feedstock
Recent field-scale precision-management studies (Kitchen et al., 2005; Lerch et
al., 2005) provide a practical foundation for the panel’s landscape vision of production of
biofuel feedstock. In 1991, authors of those studies implemented a corn–soybean rotation
in a 14.5-acre field, using mulch tillage to maintain about 30 percent residue cover.
Before initiating the study, they characterized the field on the basis of georeferencing and
developed an order 1 soil survey,1 a digital elevation model, electromagnetic induction,
and soil-fertility maps. They proceeded by mapping crop yield and producing
profitability maps in 1993. The studies showed that the greatest yield-limiting factors
were soil texture, topsoil depth, and topography (Lerch et al., 2005). All three of those
factors influence soil-water holding capacity and within-field water distribution.
Diminished topsoil thickness had an adverse effect on profitability (Kitchen et al., 2005)
and was directly related to soil loss via erosion. Reduced soil quality is a result of poor
physical and chemical characteristics of an underlying argillic claypan horizon that is not
well suited for crop-root growth (Lerch et al., 2005). In a market-driven landscape vision
of lignocellulosic feedstock production proposed by this panel, the precision-agriculture
system devised by Kitchen et al. (2005) serves as a model because their recommendations
to improve sustainability were to add more crop types and crop rotations and to use no-
tillage practices tailored to specific management areas in the field based on their long-
term, georeferenced database.
In another study, Williams et al. (2008) constructed a method based on the
geographic information system (GIS) to delineate agroecozones and agroecoregions that
were suitable for various crops. Their procedure relied completely on digital databases
and was considered more objective than methods that relied at least in part on expert
opinion. The resolution of their procedure, however, was 1 km, and that leaves a spatial-
resolution gap between their procedure and the approach used by Kitchen et al. (2005) for
an individual field. Yan et al. (2007) described a GIS database-driven method similar to
that of Williams et al. Their study, however, was conducted on a single-field scale to
delineate zones requiring different management practices for a single crop.
1
Order 1 soil surveys are soil inventories produced for very intensive land uses that require detailed
information about soils (USDA-NRCS, 2007).
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To implement a landscape vision of bioenergy feedstock production, current land
tenure and community access, drainage patterns, soil-quality status, crop rotation and
distribution patterns, economic conditions, conservation practices, wildlife and human
restrictions and concerns, and other pertinent information should be gathered on scales of
at least 1 mile. A potential biofuel-production scheme that increases ecosystem services
might include establishing woody species (for example, Populus) near streams as buffers
and long-term biomass sources. Next, Miscanthus (Miscanthus x giganteus), reed
canarygrass (Phalaris arundinacea), eastern gammagrass (Tripsacum dactyloides), or
diverse mixtures of these and similar species, could be used at slightly higher landscape
positions to benefit from and reduce leaching of nitrate nitrogen and to sequester carbon
as soil organic matter. Slightly higher on the landscape, diverse mixtures of warm-season
grasses and cool-season legumes could produce biomass and store organic carbon in
soils. In fall, the perennials would be a source of biomass and thus address at least three
of the landscape problems—biomass production, carbon sequestration, and water quality.
Moving up the landscape, a diversified rotation of annual and perennial crops would be
used to meet food, feed, and fiber needs. Erosion could be partially mitigated by using
cover crops or living mulches. Intensive row-crop production areas could be established
by using best management practices with the awareness that if fertilizer recovery was less
than desired, there would be a substantial buffer (lignocellulosic) production area lower
on the landscape to capture residual nutrients and sediment. A step-by-step outline of that
process is presented below:
1. Identify landscape characteristics by using georeferenced technologies and
methods.
2. Identify the landscape’s most important production and conservation issues.
3. Delineate critical areas that require different crops and management practices.
4. Identify suites of suitable crops, crop rotations, and conservation practices for
each management area.
5. Develop a landscape-scale precision-agriculture system.
6. Apply policies, education, and programs that address social and economic
concerns related to the adoption and implementation of the landscape-scale precision-
agriculture systems.
7. Monitor and document the new system’s performance toward production and
conservation goals.
8. Re-evaluate the system and make adaptive changes to improve its performance.
In summary, the important message from the above examples and guidelines is
that the technology needed to implement a sustainable landscape vision of biofuel
production exists and that the practices can already be implemented efficiently and
economically.
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REFERENCES
Kitchen, N.R., K.A. Sudduth, D.B. Myers, R.E. Massey, E.J. Sadler, and R.N. Lerch.
2005. Development of a conservation-oriented precision agriculture system: crop
production assessment and plan implementation. Journal of Soil and Water
Conservation 60:421-430.
Lerch, R.N., N.R. Kitchen, R.J. Kremer, W.W. Donald, E.E. Alberts, E.J. Sadler, K.A.
Sudduth, D.B. Myers, and F. Ghidey. 2005. Development of a conservation-
oriented precision agriculture system: Water and soil quality assessment. Journal
of Soil and Water Conservation 60:411-421.
USDA-NRCS, U.S. Department of Agriculture Natural Resources Conservation Service.
2007. National Soil Survey Handbook, title 430-VI. Washington, D.C.: U.S.
Department of Agriculture Natural Resources Conservation Service.
Williams, C.L., W.W. Hargrove, M. Liebman, and D.E. James. 2008. Agro-
ecoregionalization of Iowa using multivariate geographical clustering.
Agriculture, Ecosystem and Environment 123:161-174.
Yan, L., S. Zhou, L. Feng, and L. Hong-Yi. 2007. Delineation of site-specific
management zones using fuzzy clustering analysis in a coastal saline soil.
Computers and Electronics Agriculture 56:174-186.
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