Agriculture Reference
In-Depth Information
to investigate methods of promoting zones of denitrification higher in agricultural water-
sheds (e.g., Moorman et al., 2010; Woli et al., 2010). One method introduces a layer of wood
chips (i.e., a source of substrate and habitat) directly surrounding drainage tiles to provide
an opportunity for nitrate removal (i.e., denitrification) prior to entering the engineered
drainage system (Moorman et al., 2010). In other words, this method spatially manipulates
organic amendments into agricultural systems explicitly for environmental protection.
I see several opportunities to spatially manipulate organic amendments and crop residues
to promote various soil microbial processes for agronomic and environmental benefits. As
highlighted, the spatial distribution of N-rich crop residue can alter the rate of N
2
O emissions
and N mineralization; however, these few studies were conducted under simplified condi-
tions (e.g., lab incubations and container experiments). More work is warranted on the spatial
manipulation of organic amendments and crop residues under field conditions. It is likely that
the influence of spatial manipulation on environmental protections (i.e., greenhouse gas emis-
sions) will vary with amendment chemistry, particular size, and edaphic factors. The influence
of such manipulations on crop yields and nutrient use efficiencies has received even less atten-
tion (Loecke and Robertson, 2009a). See
Chapter 6
by Grandy et al. in this volume for a discus-
sion of the interactions between spatial heterogeneity and N use efficiency in agroecosystems.
Conceptual models of plant litter decomposition and soil C sequestration (e.g.,
Moorhead and Sinsabaugh, 2006; Manzoni and Porporato, 2009) often detail the role of
spatial heterogeneity in the form of soil structure or litter particle size and vertical distri-
bution as well as larger landscape heterogeneous factors (e.g., soil texture, topography, and
exposure); however, to date the spatial aggregation of plant litter has not explicitly been
considered in these models. Empirical work from forested systems suggested litter aggre-
gation significantly affects soil micro- and mesofauna activity (Sulkava and Huhta, 1998).
In agricultural systems, field testing of the influence of crop residue spatial manipulations
on soil microbial processes and plant-microbe interactions will inform the necessity of
including litter aggregation into these conceptual models.
Introducing bias into soil microbial process rate estimates due to Jensen's inequal-
ity (i.e., aggregation bias) is unavoidable and unpredictable in some cases and yet sys-
tematic and easily correctable in others (e.g.,
Q
10
interpolations) (Ruel and Ayres, 1999).
Methods for interpolating with known variance are well appreciated in geospatial sta-
tistics (Webster and Oliver, 2007); however, too often interpolation of process rates across
time does not consider aggregation bias. Using correction factors when interpolating pro-
cess rates derived from simple monotonic nonlinear functions (e.g., soil temperature effect
on metabolic rate) should be a standard practice for scaling point measures to longer tem-
poral scales in agroecological research.
References
Aikio, S., and A. L. Ruotsalainen. 2002. The modelled growth of mycorrhizal and non-mycorrhizal
plants under constant versus variable soil nutrient concentration.
Mycorrhiza
12:257-261.
Al-Kaisi, M. M., X. H. Yin, and M. A. Licht. 2005. Soil carbon and nitrogen changes as affected by till-
age system and crop biomass in a corn-soybean rotation.
Appl. Soil Ecol.
30:174-191.
Auerswald, K., F. Mayer, and H. Schnyder. 2010. Coupling of spatial and temporal pattern of cattle
excreta patches on a low intensity pasture.
Nutr. Cycl. Agroecosyst.
88:275-288.
Benedetti-Cecchi, L. 2005a. The importance of the variance around the mean effect size of ecological
processes: reply.
Ecology
86:265-268.
Benedetti-Cecchi, L. 2005b. Unanticipated impacts of spatial variance of biodiversity on plant pro-
ductivity.
Ecol. Lett.
8:791-799.
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