Forage or Biofuel: Assessing Native Warm-season Grass
Production among Seed Mixes and Harvest Frequencies
within a Wildlife Conservation Framework
Raymond B. Iglay, Tara J. Conkling, Travis L. DeVault, Jerrold L. Belant, and James A. Martin
Southeastern Naturalist, Volume 18, Issue 1 (2019): 1–18
Full-text pdf (Accessible only to subscribers.To subscribe click here.)
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R.B. Iglay, T.J. Conkling, T.L. DeVault, J.L. Belant, and J.A. Martin
22001199 SOUTHEASTERN NATURALIST Vol1.8 1(81,) :N1–o1. 81
Forage or Biofuel: Assessing Native Warm-season Grass
Production among Seed Mixes and Harvest Frequencies
within a Wildlife Conservation Framework
Raymond B. Iglay1,*, Tara J. Conkling1,2, Travis L. DeVault3, Jerrold L. Belant1,4,
and James A. Martin5
Abstract - Native warm-season grasses (NWSG) are gaining merit as biofuel feedstocks for
ethanol production with potential for concomitant production of cattle forage and wildlife
habitat provision. However, uncertainty continues regarding optimal production approaches
for biofuel yield and forage quality within landscapes of competing wildlife conservation
objectives. We used a randomized complete block design of 4 treatments to compare vegetation
structure, forage and biomass nutrients, and biomass yield between Panicum virgatum
(Switchgrass) monocultures and NWSG polycultures harvested once or multiple times near
West Point, MS, 2011–2013. Despite taller vegetation and greater biomass in Switchgrass
monocultures, NWSG polycultures had greater vegetation structure heterogeneity and plant
diversity that could benefit wildlife. However, nutritional content from harvest timings optimal
for wildlife conservation (i.e., late dormant season-collected biomass and mid-summer
hay samples) demonstrated greater support for biofuel production than quality cattle forage.
Future research should consider testing various seed mixes for maximizing biofuel or forage
production among multiple site conditions with parallel observations of wildlife use.
Introduction
Recent interests in climate change have fostered development of renewable energy
production, including biofuels, as an option to reduce carbon emissions, with
the United States setting an estimated production goal of 16 billion gallons per year
of cellulosic biofuels by 2022 (Perlack et al. 2011). Primary row and small grain
crops used for biofuel production globally include Zea mays L. (Corn), Saccharum
officinarum L. (Sugarcane), and Triticum aestivum L. (Wheat). However, these
traditional monoculture biofuels may negatively impact carbon sequestration, conservation
of biodiversity, and air and water quality. Removal of pre-existing habitat
is also detrimental to wildlife populations and diversity (Fargione et al. 2009, Hartman
et al. 2011, Knight 2010, Parrish and Fike 2005).
1Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Box
9690, Mississippi State, MS 39762. 2Current address - US Geological Survey, Forest and
Rangeland Ecosystem Science Center, Snake River Field Station, Boise, ID 83706. 3United
States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services,
National Wildlife Research Center, 6100 Columbus Avenue, Sandusky, OH 44870.
4Current address - College of Environmental Science and Forestry, State University of New
York, 1 Forestry Drive, Syracuse, NY 13210. 5Warnell School of Forestry and Natural Resources,
Savannah River Ecology Lab, The University of Georgia, Warnell 3 Room 320,
180 East Green Street, Athens, GA 30602. *Corresponding author - ray.iglay@msstate.edu.
Manuscript Editor: Robert Carter
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Row and small grain crops for biofuel production generally occur on arable
land currently used for growing food crops (Campbell et al. 2008). Perennial native
warm-season grass species including Panicum virgatum (Switchgrass), Andropogon
gerardii (Big Bluestem), and Sorghastrum nutans (Indiangrass), however,
can be used to generate lignocellulosic biofuels in marginal landscapes (DeVault
et al. 2012) that are not necessarily suited for traditional agricultural practices
(Gonzalez-Hernandez et al. 2009). Native warm-season grasses (hereafter NWSG)
provide wildlife habitat, reduce erosion, and support ecosystem functions such as
nutrient cycling (Hong et al. 2013, Samson and Omielan 1992). Unlike traditional
agricultural crops, NWSG require minimal supplemental nutrients to establish and
manage (Mulkey et al. 2006, Tilman et al. 2006).
Past research demonstrated that NWSG, especially Switchgrass monocultures,
can provide high biofuel yields across multiple environments and topographic gradients
(David and Ragauskas 2010, Mitchell et al. 2012, Sanderson and Adler 2008,
Sanderson et al. 2004). Switchgrass monocultures are the most-frequently studied
native warm-season grass species considered for biofuel production (Gonzalez-
Hernandez et al. 2009, Vogel et al. 2002, Sarath et al. 2008), but mixed-species
plantings of grasses and forbs may offer advantages over monocultures for biofuel
production (Gonzalez-Hernandez et al. 2009, Tilman et al. 2006). Mixed species
plantings often include perennial plants with diverse adaptations capable of tolerating
biotic and abiotic stressors (Gonzalez-Hernandez et al. 2009) and provide
biomass yields similar to or greater than Switchgrass monocultures (Adler et al.
2006, 2009; Tilman et al. 2006). Additionally, the viability of monocultures such
as Switchgrass for wildlife habitat or other ecosystem services may be limited,
especially during breeding season when diverse polycultures may be more useful
to nesting birds by providing greater availability of potential nest sites as well as
arthropods to feed nestlings (Conkling et al. 2017, Hovick et al. 2014, McCoy and
Kurzejeski 2001, Monroe et al. 2016, Sanderson et al. 2004). Therefore, increasing
structural heterogeneity within plantings could support diverse grassland bird
communities, thereby increasing the appeal of NWSG plantings as alternative land
covers for biomass production (Coppedge et al. 2008, Davis and Brittingham 2004,
Hovick et al. 2014, Valone and Kelt 1999). However, grassland bird conservation
goals could also affect forage and biomass goals by constraining harvest timing
(Ball et al. 2007).
Harvesting biofuel crops multiple times per year may generate additional biomass
for production, but increased harvest frequency has variable effects on the
nutritional quality of the collected forage, thereby affecting its suitability as a
biofuel or forage for livestock (Adler et al. 2006, Fike et al. 2006). For example,
as cellulose characteristics such as cell-wall constituents including cellulose,
hemicellulose, and lignin increase, biofuel production likewise increases but
ruminant digestibility decreases (Ball et al. 2001). Alternatively, forage quality
can increase with high concentrations of crude protein and digestible dry matter.
Considering the differing criteria of biomass for livestock forage and biofuel
production, investigation of alternative planting and harvest regimes could inform
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landowners of approaches to increase profit on marginal lands to enhance biofuel
or forage. Our objectives were to: (1) examine differences in vegetation structure
and species composition between monocultures and mixed species plantings and
(2) determine the effects of harvest frequency and planting regime on biofuel
and forage production. We expected greater quality biomass for biofuel production
within Switchgrass monocultures, as biomass production for biofuels may
be inversely related to the species diversity of a given plot (Johnson et al. 2010,
Tilman et al. 2006). However, we also predicted lower nutritional forage quality
including crude protein in Switchgrass monocultures and grasses harvested multiple
times in a year compared to NWSG plantings harvested just once per year
(Guretzky et al. 2011).
Field-Site Description and Methods
We conducted the study on 16 experimental plots (5.03–8.41 ha) located at B.
Bryan Farm near West Point, MS, within the Blackland Prairie region (33°38'53"N,
88°34'43"W). The study site was primarily composed of pastures, row crop agriculture,
and grasslands managed for conservation on high alkalinity soils classified
as Inceptisols and Vertisols (Barone and Hill 2007). We arranged the study plots
in a randomized complete block design with 8 plots planted with a NWSG mixture
(Table 1) and 8 plots planted to a Switchgrass monoculture during spring 2010.
We conducted no harvests in 2010 or 2011 to allow plants to establish, and did
not fertilize the plots throughout the study. Other common species in the seedbank
were Ambrosia artemisiifolia (Annual Ragweed), Urochloa platyphylla (Broadleaf
Signalgrass), and Sesbania spp. (riverhemp). Plots were harvested once or twice
annually as is done for haying and biomass collection, resulting in 4 treatments:
single harvest NWSG (“NWSG Single”), multiple harvest NWSG (“NWSG Multiple”),
single harvest Switchgrass (“Switchgrass Single”), and multiple harvest
Switchgrass (“Switchgrass Multiple”). The first harvest (dormant harvest) occurred
Table 1. Species planted (kg/ha) in at Bryan Farms in Clay County, MS, (2011–2013), for comparing
native warm-season grass plots to Switchgrass monoculture plots.
Common name Species Planting rate
Big Bluestem Andropogon gerardii Vitman 2.27
Little Bluestem Schizachyrium scoparium (Michx.) Nash 4.50
Indiangrass Sorghastrum nutans (L.) Nash 2.27
Roundhead Lespedeza Lespedeza capitata Michx. 0.28
Grayhead Coneflower Ratibida pinnata (Vent.) Barnhart 0.28
Showy Tick Trefoil Desmodium canadense (L.) DC. 0.28
Tickseed Sunflower1 Bidens aristosa (Michx.) Britton 0.28
Illinois Bundleflower Desmanthus illinoensis (Michx.) MacMill. ex B.L. 0.28
Rob. & Fernald
Wild Blue Lupine Lupinus perennis L. 0.28
Switchgrass – ‘Alamo’2 Panicum virgatum L. 10.10
1Tickseed Sunflower had the greatest establishment of all planted forbs.
2Switchgrass was only planted in Switchgrass monocultures.
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in April 2012 before green-up to simulate a winter harvest and was applied to all
plots after fields were dry enough to access with equipment. The timing of both
harvest treatments helped provide standing cover during grassland bird breeding
and overwintering seasons. We were unable to successfully establish Switchgrass
in 1 Switchgrass Single and 1 Switchgrass Multiple plot, so we removed these plots
from subsequent analyses (n = 14 plots for analysis).
We measured maximum height of visual obstruction (VOR) in addition to
heights of dominant plant species and species composition data among treatments
using Robel-pole and point-intercept methods, respectively (Robel et al. 1970). We
used point-intercept methods to characterize plant communities and Robel-pole
measurements to index habitat heterogeneity (wildlife conservation benefit) and
biomass production (Robel et al. 1970). We employed a geographic information
system (i.e., ArcGIS) to overlay 50 m x 50 m grids on each plot, randomly selected
5 grid squares per plot based on preliminary sample-size analysis, and centered a
50-m line transect per square with a random orientation. We recorded VOR in all
4 cardinal directions every 10 m along each transect per month from June 2011 to
October 2013 (n = 5 subsamples per transect per month; Barone and Hill 2007,
Robel et al. 1970). From June–October 2011 and May–October 2012 and 2013, we
identified the 3 most common plant species (including standing dead vegetation)
and measured heights (cm) at 5-m intervals in addition to bare ground and litter
(10 subsamples per transect per month; Caratti 2007). We did not sample species
composition from November to April because of winter dormancy and our interest
in growing-season biomass production.
Metrics calculated included average height and species frequency of occurrence
for species and growth forms (e.g., bare ground and litter [frequency only]), dead
grass, forbs, grasses, herbaceous vines, legumes, sedges and rushes, semi-woody
vines, woody plants, woody vines] by plot and month for analysis. Frequency of
occurrence was also used to calculate species richness and Shannon–Wiener diversity
index (H') from a species matrix including all identified species. We used
frequency of occurrence by growth form to determine the most common growth
forms detected (i.e., growth forms occurring in at least 25% of samples among all
transects per plot per month).
We measured biofuel production and cattle forage production among treatments
by weighing clipped biomass and hay bales in addition to conducting nutrient
analyses. We collected 6 biomass samples from 1-m2 plots along each transect,
1 sample per 10 m (i.e., 0 m, 10 m, 20 m, 30 m, 40 m, 50 m) from late March to
early April 2014. All vegetation samples were weighed (kg; wet weight) and then
frozen until dried at 60 °C in a forced-air oven for 72 hours, then weighed again
(dry weight). We used samples from the 10-m and 40-m points on each transect to
determine biofuel nutrients and from the 0-m and 50-m points for forage nutrient
analysis. Despite similarities in biofuel and forage nutrients, we present separate
statistics for each because we submitted separate samples to the nutrient analysis
laboratory. Average dry and wet biomass weights (Mg/ha) and average nutrients
per transect from biomass samples were calculated. For hay-bale forage nutrient
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analysis, we collected sample cores from 5 hay bales per plot in late June 2012 and
early July 2013 from June harvests. We weighed (kg) a subsample of hay bales (n =
1–16 bales, mean = 11.6 bales, σ = 4.56) using a truck scale, correcting for truck
and trailer weight, and calculated total biomass weight as the product of the average
hay bale weight and total bales per plot (Mg/ha). We only measured hay weights
from multiple harvested treatments due to limited availablity of a truck scale. All
nutrient analyses followed standard protocols and were conducted by the Mississippi
State Chemical Laboratory using a 0.5-mm sieve.
We used univariate (GLMM) and multivariate (MGLMM) generalized linear
mixed models to investigate vegetation structure and composition directional responses
to treatments (Hadfield 2010). We assessed plant height, visual obstruction,
growth form, and nutrient responses in a Bayesian model-selection framework,
thus avoiding issues associated with multiple hypothesis testing. We used deviance
information criterion (DIC) to select the best random structure of our treatment
model with random effects (e.g., block, plot, year, month) associated with each
observation (idh variance structure) or among all observations (Spiegelhalter et
al. 2002). We ran 3 fixed-effects models (e.g., treatment by growth form, growth
form, and null) with an effective sample size of 5000 from 100,000 iterations after
a 50,000-iteration burn-in and thinning interval of 10. We ran each model 3 times
to visually assess error (Hadfield 2010) and convergence. We selected the model
with the least average DIC value and deemed it to have strong directional response
when ΔDIC > 4.00. We also calculated summary statistics of the top model’s
posterior distribution, including using the time-series standard error because it
better represents the standard error of time-series data and an additional statistic
representing the proportion of posterior distribution values >0 as a metric of the
strength of the directional response when 95% credible intervals overlapped 0. We
developed univariate Bayesian models (GLMM) for species richness, Shannon’s
diversity index, visual obstruction, and nutrient- and biomass-production responses
comparing treatment and null models and an added interaction term (treatment ×
year) for hay-bale nutrient analysis. For total hay weight per plot, we used paired
t-tests to compare total weight between years and treatments with block indicating
each pair. We further investigated vegetation composition responses to treatments
using analysis of similarity (ANOSIM). For ANOSIM, we tested for no difference
in species composition among treatments by year using frequency of occurrence
data, Bray-Curtis distance measure, and 999 permutations.
Results
We identified 48 plant species (24 forbs, 11 grasses, 4 legumes, 3 herbaceous
vines, 3 sedges and rushes, and 1 species each of shrubs, semi-woody vines, and
woody vines) among all treatments and years. However, only grasses, forbs, legumes,
Switchgrass, bare ground, dead grass, and litter were included in analysis
(i.e., growth forms occurring in at least 25% of samples among all transects per plot
per month). Indiangrass, Switchgrass, Schizachyrium scoparium (Little Bluestem),
Broadleaf Signalgrass, and Big Bluestem were the most common species occurring
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in at least 20% of transects (Table 2). Desmanthus illinoensis (Illinois Bundleflower),
Annual Ragweed, Conyza canadensis (Horseweed), Ranunculus fascicularis
(Early Buttercup), Bidens polylepis (Tick-seed Sunflower), and Ipomoea pandurata
(Morning Glory) were common species occurring in 10–19% of transects. When
present, Switchgrass and Little Bluestem were the tallest dominant plants on average,
followed by Horseweed, Big Bluestem, and Tick-seed Sunflower among all
treatments and years (Table 2).
Average height by vegetation growth form differed among treatments, but frequency
of occurrence did not (Table 3). Forbs, other grasses, and legumes were
taller in NWSG polycultures than either Switchgrass treatment (Table 4). Switchgrass
was tallest in Switchgrass Single monocultures. Grasses were also tallest in
Switchgrass Single monocultures with similar occurrence among all treatments.
Litter and standing dead grass did not demonstrate strong directional responses to
treatments (i.e., minimal differences among treatments).
Table 2. The tallest plants on average among Switchgrass monocultures and native warm‒season
polycultures (NWSG) harvested once (single) or multiple times from 2011 to 2013 and sampled using
line transects June to October 2011 and May to October 2012 and 2013 near West Point, MS.
Height (cm)
Treatment/species Common name Mean SE Occurrence
Switchgrass Single
Panicum virgatum Switchgrass 113.26 2.90 100%
Urochloa platyphylla (Munro Broadleaf Signalgrass 8.36 0.95 36%
ex C. Wright) R.D. Webster
Ranunculus fascicularis Muhl. Early Buttercup 2.11 0.35 16%
ex Bigelow
Digitaria ciliaris (Retz.) Koeler Southern Crabgrass 1.02 0.41 4%
Ambrosia artemisiifolia L. Annual Ragweed 1.00 0.62 2%
Switchgrass Multiple
Panicum virgatum Switchgrass 81.96 2.54 96%
Urochloa platyphylla Broadleaf Signalgrass 12.16 1.05 53%
Digitaria ciliaris Southern Crabgrass 6.09 1.12 16%
Ranunculus fascicularis Early Buttercup 3.32 0.43 24%
Schizachyrium scoparium Little Bluestem 1.57 0.74 2%
NWSG Single
Sorghastrum nutams Indiangrass 43.19 2.23 70%
Schizachyrium scoparium Little Bluestem 40.94 2.15 59%
Andropogon gerardii Big Bluestem 29.63 2.71 32%
Conyza Canadensis (L.) Cronquist Horseweed 28.90 2.51 39%
Ambrosia artemisiifolia Annual Ragweed 20.02 1.88 35%
NWSG Multiple
Sorghastrum nutams Indiangrass 47.54 1.99 86%
Schizachyrium scoparium Little Bluestem 39.02 1.91 67%
Andropogon gerardii Big Bluestem 37.47 2.68 49%
Bidens polylepis Tick-seed Sunflower 12.33 1.55 20%
Ambrosia artemisiifolia Annual Ragweed 11.02 1.41 24%
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Table 4. Average height of live and dead growth forms occurring in at least 25% of transects among
Switchgrass monocultures and native warm-season grass polycultures (NWSG) harvested once
(Single) or more than once (Multiple) in fields near West Point, MS, during June–October 2011 and
May–October 2012 and 2013. All responses are in comparison to Switchgrass monocultures harvested
multiple times.
Time-series 95% CI
Growth formA Treatment Mean SE Mode Prop > 0 Lower Upper
Dead Grass Switchgrass Single -0.931 0.015 -0.888 0.185 -2.989 1.207
NWSG Multiple 0.361 0.013 0.206 0.653 -1.536 2.136
NWSG Single -1.061 0.014 -1.424 0.133 -3.000 0.783
Forbs Switchgrass Single -1.160 0.074 -0.928 0.409 -11.730 8.883
NWSG Multiple 24.340 0.069 23.510 1.000 14.750 33.800
NWSG Single 41.350 0.067 40.133 1.000 31.720 50.910
GrassB Switchgrass Single -9.275 0.067 -10.540 0.021 -18.740 -0.984
NWSG Multiple 32.480 0.056 31.745 1.000 24.630 41.040
NWSG Single 34.950 0.060 35.425 1.000 26.500 43.020
Legumes Switchgrass Single -0.705 0.077 -2.140 0.452 -11.800 9.826
NWSG Multiple 20.460 0.070 20.921 1.000 10.560 30.300
NWSG Single 12.860 0.072 11.388 0.993 2.832 22.570
Switchgrass Switchgrass Single 31.960 0.038 31.928 1.000 26.870 37.530
NWSG Multiple -79.590 0.034 -78.973 0.000 -84.260 -74.940
NWSG Single -79.500 0.035 -79.782 0.000 -84.140 -74.660
AGrowth forms included bare ground and litter (frequency only), dead grass, forbs, grasses, herbaceous
vines, legumes, sedges and rushes, semi-woody vines, woody plants, and woody vines.
BSwitchgrass was not included in the calculation of “Grass” coverage, only other Poaceae including
other planted NWSG species were.
Table 3. Model results comparing average height and frequency of occurrence of vegetation growth
forms in Switchgrass monocultures and native warm‒season grasses polycultures harvested once or
multiple times near west Point, MS, sampled with point intercepts from June to October 2011 and
May to October 2012 and 2013.
DIC
Variable Model k Average Delta
Average height
Growth Form + Treatment:Growth Form 63 52332.30
Null 36 52337.14 4.84
Growth Form 42 52339.21 6.91
Frequency of occurrence
Null 36 34867.96
Growth Form 42 34868.07 0.11
Growth Form + Treatment:Growth Form 63 34868.70 0.74
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Maximum heights of visual obstruction (VOR) differed among treatments (ΔDIC
= 4.72), with tallest VOR in Switchgrass Single plots followed by Switchgrass Mulitple,
NWSG Single, and NWSG Multiple plots (Table 5). Total wet and dry biomass
did not exhibit an apparent treatment effect, but some differentiation was evident
with single harvest plots having greater biomass than multiple harvest plots (Tables
6, 7). Total weight of hay harvested for both Multiple treatments increased about 40%
from 2012 to 2013 (2.47 Mg/ha in 2012 vs. 3.54 Mg/ha in 2013; t = 3.03, P = 0.023).
Between Multiple treatments across years, Switchgrass monocultures (mean = 4.23
Mg/ha, SE = 0.312) produced over twice the biomass of NWSG plots (mean = 2.08
Mg/ha, SE = 0.154) (t = -6.06, P = 0.002).
Most forage nutrients in monoculture Switchgrass and NWSG polyculture treatments
from biomass samples were similar (Table 6). Dry matter decreased from
Switchgrass Single to Switchgrass Multiple to NWSG Single and NWSG Multiple
treatments (Table 7). Crude protein was greatest in NWSG Multiple polycultures,
least in Switchgrass Single monocultures, and at intermediate levels in Switchgrass
Multiple and NWSG Single treatments. Hay bales from Multiple treatment plots had
greater fat content in monoculture Switchgrass than NWSG polyculture (Table 8).
However, biofuel nutrients did not exhibit any strong directional responses among
treatments (Table 7).
Vegetation community species richness (ΔDIC = 167.68) and Shannon–Wiener
diversity (ΔDIC = 206.58) differed among treatments and were greatest in both
harvest types of NWSG polycultures and least in Switchgrass Single monocultures
(Table 5). Dissimilarity of vegetation communities among treatments was strong
during all 3 years (2011: R = 0.598, P < 0.001; 2012: R = 0.544, P < 0.001; 2013:
R = 0.653, P < 0.001).
Table 5. Average height of maximum visual obstruction, species richness and Shannon-Wiener Diversity
Index of vegetation communities within Switchgrass monocultures (Switch) and native warm‒
season grass polycultures (NWSG) in West Point, MS, during June–October 2011 and May–October
2012 and 2013 either harvested once (Single) or Multiple times. All responses are in comparison to
Switchgrass monocultures harvested multiple times. CI = confidence interval.
Time-series 95% CI
Variable Treatment Mean SE Mode Prop > 0 Lower Upper
Maximum visual Switchgrass Single 36.84 0.04 36.96 1.00 31.84 42.07
Obstruction height (m) NWSG Multiple -19.81 0.03 -19.59 0.00 -24.37 -15.18
NWSG Single -7.51 0.03 -8.33 0.00 -12.01 -2.82
Species richness Switchgrass Single -0.451 0.003 -0.517 0.020 -0.904 -0.029
NWSG Multiple 2.140 0.003 2.169 1.000 1.737 2.524
NWSG Single 2.023 0.003 1.972 1.000 1.615 2.421
Shannon–Wiener Switchgrass Single -0.209 0.001 -0.196 0.001 -0.325 -0.089
diversity index NWSG Multiple 0.616 0.001 0.608 1.000 0.505 0.720
NWSG Single 0.607 0.001 0.584 1.000 0.498 0.714
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Discussion
Planting regimes perpetuated differences in vegetative structure heterogeneity
among treatments and had greater influence on plant species richness and diversity
than harvest frequencies. Switchgrass monocultures always supported the tallest
vegetation, but vertical structure heterogeneity and plant diversity was greater in
NWSG polycultures with multiple grass species, forbs, and legumes contributing
to overall structure. Biomass production followed VOR trends (Robel et al. 1970),
but biomass did not vary significantly among treatments. However, Switchgrass
monocultures produced substantially more harvested hay than NWSG polycultures.
Table 6. Model results from multivariate generalized linear mixed models comparing forage and biofuel
nutrient analysis results from biomass samples and forage nutrient analysis results from hay core
samples in Switchgrass monocultures and native warm-season grass polycultures (NWSG) harvested
once or multiple times near West Point, MS. Two biomass samples per nutrient analysis were collected
during late March and early April 2014. Hay core samples were sampled in late June 2012 and early
July 2013 and only in Switchgrass or NWSG fields harvested multi ple times.
Treatment Null
Group Variable model DIC model DIC ΔDIC1
Biomass forage Dry matter (%) 482.38 498.33 -15.95
nutrients Crude protein (%) 314.75 355.19 -40.44
Neutral detergent fiber (%) 666.90 666.52 0.38
Acid detergent fiber (%) 734.62 733.19 1.44
Crude fiber (%) 742.98 741.50 1.47
Fat (%) 94.42 93.91 0.51
Gross energy (MJ) 1531.64 1535.86 -1.22
Total wet biomass (Mg/ha) -5.22 -8.64 3.42
Total dry biomass (Mg/ha) -1.70 -5.04 3.34
Biomass biofuel Dry matter (%) -5.73 -7.03 1.30
nutrients Moisture (%) -5.93 -6.36 0.43
Crude protein (%) -1.99 -0.99 -1.00
Starch (ppm) 4.96 4.38 0.58
Simple sugars (%) -4.99 -3.25 -1.74
Water Soluble carbohydrates (%) -13.47 -9.62 -3.85
Fructans (%) -4.13 -1.00 -3.14
Non-fiber carbohydrates (%) 20.98 18.75 2.23
Acid-insoluble residue lignin (%) 17.21 16.06 1.15
Neutral detergent fiber (%) 17.45 16.71 0.73
Acid detergent fiber (%) 28.68 29.62 -0.94
Hay forage Dry matter (%) 98.28 98.46 -0.42
nutrients Ash (%) 281.97 280.83 1.14
Crude protein (%) 63.73 64.03 -0.30
Neutral detergent fibers (%) 329.56 327.19 2.37
Acid detergent fiber (%) 309.24 307.24 1.99
Crude fiber (%) 276.48 276.72 -0.24
Fat (%) -12.78 16.26 -29.11
Gross Energy (MJ) 851.76 848.54 3.22
1 Negative ΔDIC indicates better model fit by treatment model than null (ΔDIC = DICTreatment - DICNull).
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Both Switchgrass monocultures and NWSG polycultures harvested once (dormant
season) or multiple (dormant season + growing season; late June/early July) times
per year were better suited for biofuel production than cattle forage when managing
for grassland birds, according to nutrient analysis. Therefore, the primary advantages
of NWSG polycultures over Switchgrass monocultures for biofuel production
may be limited to wildlife conservation.
Previous studies have observed plant communities among harvest frequencies
in conservation grasslands similar to our NWSG plantings (Jungers et al. 2015,
Stahlheber et al. 2016). However, increased cutting frequency can increase light
availability, promoting photophilic plant species otherwise deterred by tall vegetation
and dense grass canopies (Hautier et al. 2009, Wilson and Tilman 1991).
Our study plots were on arable land, previously used for agriculture production.
Table 7. Descriptive statistics of forage and biofuel nutrient analysis results from biomass samples
from dormant Switchgrass monocultures and native warm-season polycultures (NWSG) harvested
once or multiple times near West Point, MS, collected during late March and early April 2014. Total
wet and dry biomass were average weights among samples among plots per treatment.
Switchgrass Switchgrass NWSG NWSG
Multiple Single Multiple Single
Harvest Harvest Harvest Harvest
Material/variable Mean SE Mean SE Mean SE Mean SE
Forage nutrients
Dry matter (%) 91.33 0.34 91.53 0.29 89.66 0.26 90.38 0.29
Ash (%) 4.68 0.39 3.71 0.35 6.52 0.55 5.14 0.30
Crude protein (%) 2.83 0.17 1.77 0.07 3.29 0.20 2.29 0.10
Neutral detergent fiber (%) 83.81 0.66 89.09 0.44 77.68 0.97 82.06 0.51
Acid detergent fiber (%) 49.79 0.54 55.74 0.41 48.69 1.06 53.76 0.83
Crude fiber (%) 40.88 0.63 46.03 0.49 40.38 1.08 45.06 0.84
Fat (%) 0.25 0.06 0.23 0.07 0.71 0.08 0.45 0.06
Gross energy (MJ) 4111.19 25.70 4123.14 16.37 3925.77 27.38 4009.68 17.14
Total wet biomass (Mg/ha) 4.00 0.65 8.40 3.23 7.07 3.13 7.19 2.88
Total dry biomass (Mg/ha) 2.30 0.30 6.23 2.55 4.55 1.98 4.78 2.10
Biofuel nutrients
Moisture (%) 7.70 0.20 7.87 0.13 7.40 0.18 7.33 0.25
Dry matter (%) 92.30 0.20 92.13 0.13 92.60 0.18 92.68 0.25
Crude protein (%) 3.17 0.23 2.23 0.38 2.95 0.16 3.13 0.26
Fructose (ppm) 4404.00 129.00 5940.50 825.50 - - - -
Glucose (ppm) 3715.50 77.50 5134.50 1064.50 - - - -
Starch (ppm) 0.60 0.17 1.07 0.43 1.28 0.43 0.85 0.52
Simple sugars (%) 1.40 0.30 1.93 0.38 1.15 0.05 1.48 0.26
Water-soluble 1.73 0.03 1.70 0.06 1.43 0.20 1.08 0.09
carbohydrates (%)
Fructans (%) 0.33 0.27 - - 0.28 0.23 - -
Non-fiber carbohydrates (%) 4.87 0.61 3.47 0.65 6.25 0.70 4.95 1.56
Acid-insoluble residue 10.79 0.69 11.43 0.85 11.53 1.07 12.32 1.56
lignin (%)
Acid detergent fiber (%) 47.37 0.57 51.30 0.46 51.18 1.06 54.78 3.07
Neutral detergent fiber (%) 75.03 0.57 77.23 0.58 74.15 0.58 75.38 1.43
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2019 Vol. 18, No. 1
Multiple studies have attributed diverging plant communities in biofuel plant trials
to past land use and site conditions (Foster et al. 2003, Grman et al. 2013). However,
by conducting our study on homogeneous study plots (i.e., old row crop fields
under similar past management and soil conditions), plant community divergence
can be attributed more to plant seed mixes and post-planting management (i.e.,
harvest rate) than to expressed seedbanks despite observing some sub-dominant
non-planted species contributing to the study stands.
Predominant seedbank species expressed in plots were more prevalent in
Switchgrass monocultures than NWSG polycultures. For example, Broadleaf Signalgrass
is a prolific seed producer capable of saturating seedbanks and decreasing
the effectiveness of site-preparation techniques. Broadleaf Signalgrass has been a
troublesome weed throughout the southeastern United States, even reducing corn
productivity over 30% (Alford et al. 2005) and was second in dominance and frequency
to Switchgrass in monoculture plots. Multiple-year herbicide applications
are often required to adequately prepare sites for NWSG plantings because new
plantings are susceptible to weed competition (Temu et al. 2016, Washburn and
Barnes 2000). However, a current study demonstrating Switchgrass monocultures
as an alternative land cover for airports from Michigan to Mississippi has observed
similar issues of seedbanks competing directly with planted Switchgrass even after
2 years of intense site preparation (e.g., 2 applications glyphosate and metsulfuron
methyl and 1 application of imazapyr; R.B. Iglay, unpubl. data). Therefore, sitepreparation
techniques should be explored for marginal land opportunities that can
produce grasslands with significant proportions of C4 grasses for effective ethanol
yield (Adler et al. 2009, Stahlheber et al. 2016).
Biomass production in this study was similar to past work with unfertilized
fields (Muir et al. 2001, Vogel et al. 2002), but Switchgrass monocultures exceeded
Table 8. Descriptive statistics of forage nutrient analysis results from hay samples in Switchgrass
monocultures and native warm-season polycultures (NWSG) planted in spring 2010 and harvested
twice in 2012 (dormant harvest in early April and growing season harvest in late June to early July)
and in late June to early July 2013 near West Point, MS. Most Switchgrass plants were in the late-boot
to early-seedhead stage during harvest.
2012 2013
Switchgrass NWSG Switchgrass NWSG
Multiple Multiple Multiple Multiple
Harvest Harvest Harvest Harvest
Variable Mean SE Mean SE Mean SE Mean SE
Dry matter (%) 96.84 0.08 95.69 0.25 96.41 0.21 95.28 0.18
Ash (%) 6.33 0.38 6.67 0.21 6.33 0.38 7.70 0.33
Crude protein (%) 4.10 0.13 3.64 0.06 3.00 0.08 4.25 0.14
Neutral detergent fibers (%) 74.22 0.37 72.09 0.58 79.28 0.76 69.77 1.30
Acid detergent fiber (%) 39.62 0.46 44.06 0.87 45.44 0.75 43.23 0.69
Crude fiber (%) 34.80 0.25 38.19 0.79 39.01 0.59 35.70 0.47
Fat (%) 1.49 0.04 1.20 0.03 1.00 0.04 0.76 0.10
Gross energy (MJ) 4193.49 23.78 4109.13 17.32 4157.89 41.40 4065.52 30.19
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NWSG polycultures in terms of hay production. McIntosh et al. (2015, 2016) investigated
similar treatments with fertilized fields and observed greatest biomass
yields in fields with Switchgrass when harvested in the fall, but their results also
indicated changes in harvest yields between early boot and early seedhead stages.
Adler et al. (2009) had observed decreasing biomass yields with increasing species
richness but had no comparison to a monoculture, only increasing species richness
among Conservation Reserve Program fields. Tilman et al. (2006) compared biofuel
production among NWSG polycultures, corn, and soybeans. Switchgrass has taken
center stage as an optimal alternative biofuel crop to small grains (Parrish and Fike
2005, Sarath et al. 2008, Vogel et al. 2002) in part due to biomass production but
also to the feasibility of biofuel conversion (McLaughlin and Kszos 2005, Mitchell
et al. 2008, Parrish and Fike 2005, Sanderson et al. 2006).
Harvest timing could have greater influence on the quality of biomass or forage
from NWSG polycultures and Switchgrass monocultures than plant diversity (Ball
et al. 2007; McIntosh et al. 2015, 2016). Biomass for biofuel production encourages
fall biomass harvests after the first frost to maximize translocation of plant nutrients
to roots for storage reserves before harvest (McIntosh et al. 2015, 2016; Muir et
al. 2001; Sanderson et al. 1996; Vogel et al. 2002). However, delaying harvest to
early spring can allow for additional nutrient loss while maintaining similar caloric
content for producing quality biomass feedstock (Johnson and Gresham 2014).
Similarly, leached nutrients such as N, K, and S can remain in the system rather
than be removed from fall Switchgrass harvests (Gamble et al. 2015, Johnson and
Gresham 2014). Concomitantly, delaying harvest to minimize interference with
nesting birds would favor biomass production over forage because of increased
yield and decreased nutrients (McIntosh et al. 2015, 2016).
Despite having single- and multiple-harvest treatments, we sampled all plots at
the same time, at the end of March and early April 2014, for biomass clippings and
compared hay harvests from approximately the same midsummer time period between
years for multiple-harvest treatments. During summer, many NWSG species
experience nutrient lows, especially crude protein. Guretzky et al. (2011) observed
poor forage quality for mid-summer Switchgrass harvests in Oklahoma. Crude
protein can decrease over 50% in NWSG species such as Little and Big Bluestem
from May through late summer and early fall (July–September; Sedivec and Barker
1997). Big Bluestem can maintain 16–18% crude protein through August but drop
as low as 6% come September (United States Department of Agrictulture Natural
Resources Conservation Service 2018).
Late spring harvests of NWSG polycultures and Switchgrass monocultures,
between dormant and June harvests of this study, could produce viable biomass
feedstocks though the low lignin and acid detergent and neutral detergent fibers
make such harvest less than ideal for ruminant intake and digestibility (Ball et
al. 2001). Reduced mineral nutrient concentrations benefit ethanol production
unless excess lignin inhibits availability of cellulose and hemicellulose during
thermochemical conversion (Adler et al. 2006, Chen and Dixon 2007, Sanderson
et al. 2007, Sarath et al. 2008). We observed slightly greater (14% increase)
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2019 Vol. 18, No. 1
acid-insoluble residue lignin in NWSG polyculture biomass samples compared to
Switchgrass monocultures (average values below 12.5%) among treatments. Past
studies have observed Switchgrass acid-insoluble lignin levels of 17.8%, with
other biofuel crops varying from 6.1% to 29.1% (Mood et al. 2013). However,
late spring harvests could be detrimental to nesting birds, thereby decreasing the
potential concomitant benefits of biomass production and wildlife conservation
(Roth et al. 2005, Perlut et al. 2006).
Greater crude protein in multiple-harvest treatments mimics existing Switchgrass
research observing greater nutritional quality of grasses harvested multiple
times compared to those harvested just once per year (Guretzky et al. 2011). However,
the predominant trend in our forage nutrient analysis was no difference in
nutrient load among treatments. Biomass samples among treatments yielded crude
protein levels that were lower than poor grass hay requirements for cattle forage,
and only average crude protein of NWSG Multiple polycultures met minimum
quality standards for silage (Burns et al. 1984, National Research Council 2000).
Acid (ADF) and neutral detergent fibers (NDF) were 65–88% greater than primary
forage quality standards which recommend below 31% for ADF and below 40% for
NDF (Ball et al. 2001, National Research Council 2000). Thus, the only prime forage
quality aspect of late dormant season harvested biomass was percent dry matter
(National Research Council 2000). Mid-summer hay samples did not provide any
additional benefits for cattle forage.
Summer (late June to early July) harvests of unfertilized Switchgrass monocultures
and NWSG polycultures were better suited for biofuel production than cattle
forage in east-central Mississippi. While Switchgrass monocultures were better
suited for maximizing biomass production, NWSG polycultures could provide concomitant
benefits of wildlife habitat and biomass for biofuel production, thereby
increasing the appeal of converting marginal land for biomass production. Adjusting
harvest timing could generate greater nutritional content for cattle (Hedtcke
et al. 2014, McIntosh et al. 2016, Sanderson et al. 1999, Trócsányi et al. 2009)
while providing additional feedstock supplies for refineries (Anteau et al. 2011,
McIntosh et al. 2015, Richard 2010, Sanderson et al. 1999), but more research is
needed across ecoregions including an examination of potential detrimental effects
on wildlife communities (e.g., harvest practices destroying breeding grassland
bird nests; Roth et al. 2005 Perlut et al. 2006). Seed mixes can drive future plant
communities if seedbank competition is minimal and could be tailored to meet
landowner interests regarding biofuel and forage production.
Acknowledgments
We thank W. Batton, K. Schwartz, K. Drey, G. Holmes, L. Latino, M. McConnell, A.
Monroe, F. Owen, T. Pickering, T. Pope, M. Thornton, and others for field assistance. We
thank L.W. Burger Jr. and B. Bryan Farms for plot access. This work was supported by the
Federal Aviation Administration (FAA) and the USDA-APHIS National Wildlife Research
Center (1374390735CA). USDA NRCS, USFWS Partners for Fish and Wildlife Program,
the Mississippi Agricultural and Forestry Experiment Station (MAFES), the Forest and
Southeastern Naturalist
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2019 Vol. 18, No. 1
14
Wildlife Research Center, and the College of Forest Resources at Mississippi State University
provided additional support. Opinions expressed in this study do not necessarily reflect
current FAA policy decisions regarding the control of wildlife on or near airports.
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