ArticlePDF Available

Weed seedbank diversity and sustainability indicators for simple and more diverse cropping systems

Authors:

Abstract

Storkey and Neve (2018) hypothesised that weed seedbank diversity could be used as an indicator of agroecosystem sustainability, with cropping systems associated with higher weed seedbank diversity being more agronomically and environmentally sustainable than those with lower weed diversity. We evaluated their hypothesis using multiple years of empirical data collected from a long‐term field experiment in Iowa, USA, and life cycle assessment models parameterised with data from that experiment. We found that diversifying a 2‐year maize–soyabean rotation with two additional crop phases, oat and lucerne, to form a 4‐year rotation (a) increased Simpson's diversity index for weed species in the soil seedbank, while (b) increasing maize and soyabean productivity, (c) maintaining total crop energy production and profitability, and (d) reducing herbicide‐related aquatic toxicity, fossil energy consumption, greenhouse gas emissions, damage to human health due to fine particulate matter, and discharge of soil sediment, nitrogen, and phosphorus. Increased weed biomass production and greater weed species diversity that occurred within oat and lucerne phases of the 4‐year rotation sequence did not result in a loss of weed control within maize and soyabean phases of the rotation. We suggest that while there was no cause‐and‐effect relationship between greater weed seedbank diversity and improved agroecosystem sustainability in agronomic, economic and environmental dimensions, all of these responses were driven in a parallel manner by cropping system diversification. Consequently, weed seedbank diversity may indeed be a useful agroecosystem sustainability indicator. Further evaluation of this hypothesis in more systems is warranted.
Weed Research. 2021;00:1–14.
|
  1wileyonlinelibrary.com/journal/wre
Received: 23 Septem ber 2020 
|
Accepted: 5 January 2021
DOI : 10.1111/wre.1 246 6
ORIGINAL ARTICLE
Weed seedbank diversity and sustainability indicators for
simple and more diverse cropping systems
Matt Liebman1| Huong T. X. Nguyen1| Matthew M. Woods1| Natalie D. Hunt2|
Jason D. Hill2
This is an op en access article under the ter ms of the Creative Commons Attribution-NonCommercial-NoD erivs License, which permits use and distrib ution in
any medium, provided the original work is properly cited, the use is non-commercial and no modificat ions or adaptations are made.
© 2021 The Authors. Weed Research published by John Wiley & Sons Ltd on behalf of European Weed Research Societ y.
1Depar tment of Agronomy, Iowa State
University, Ames, IA, USA
2Department of Bioproducts and Biosystems
Enginee ring, University of Minnesot a, St.
Paul, MN , USA
Correspondence
Matt Liebman, Depar tment of Agronomy,
Iowa State University, Ames, IA 50 011, USA.
Email: mliebman@iastate.edu
Funding information
This research was suppor ted by grants
from the U. S. Department of Agriculture's
Agriculture and Food Research I nitiative
(2014- 67013-21712) and th e Leo pol d Center
for Sust ainable Agriculture (2014-XP01), and
by U.S. Depart ment of Agriculture Hatch
Project MIN-12-083.
Subjec t Editor : Jonathan Storkey
Abstract
Storkey and Neve (2018) hypothesised that weed seedbank diversity could be used
as an indicator of agroecosystem sustainability, with cropping systems associated
with higher weed seedbank diversity being more agronomically and environmentally
sustainable than those with lower weed diversity. We evaluated their hypothesis
using multiple years of empirical data collected from a long-term field experiment
in Iowa, USA, and life cycle assessment models parameterised with data from that
experiment. We found that diversifying a 2-year maize–soyabean rotation with
two additional crop phases, oat and lucerne, to form a 4-year rotation (a) increased
Simpson's diversity index for weed species in the soil seedbank, while (b) increasing
maize and soyabean productivity, (c) maintaining total crop energy production and
profitability, and (d) reducing herbicide-related aquatic toxicity, fossil energy con-
sumption, greenhouse gas emissions, damage to human health due to fine particulate
matter, and discharge of soil sediment, nitrogen, and phosphorus. Increased weed
biomass production and greater weed species diversity that occurred within oat and
lucerne phases of the 4-year rotation sequence did not result in a loss of weed con-
trol within maize and soyabean phases of the rotation. We suggest that while there
was no cause-and-effect relationship between greater weed seedbank diversity and
improved agroecosystem sustainability in agronomic, economic and environmental
dimensions, all of these responses were driven in a parallel manner by cropping sys-
tem diversification. Consequently, weed seedbank diversity may indeed be a useful
agroecosystem sustainability indicator. Further evaluation of this hypothesis in more
systems is warranted.
KEYWORDS
agroecosystem sustainability indicators, crop rotation systems, weed community diversity,
weed seedbanks
2 
|
   LIEBMAN Et AL.
1 | INTRODUCTION
Reconciling the production of sufficient amounts of food and farm
income with the protec tion of environmental quality is a critical
priorit y for both developed and developing countries (Foley, 2011).
Meeting this goal will require approaching crop production and crop
protect ion within the broa de r context of agro ecosystem sustainabil-
ity. Swanton and Murphy (1996) recommended that weed manage-
ment strategies should be evaluated not only with regard to their
impact s on weed suppression and crop yield, but also their impacts
on soil quality, water quality, biological diversity, fossil energy use
efficiency, and other components of agroecosystem performance.
MacLaren et al., (2020) emphasised that achieving sustainable weed
management requires the integration of systems-level ecological
perspectives into agronomic decision-making.
Cropping system diversification through the use of multi-species
rotations can increase the range of disturbance events and stress and
mortality factors that regulate weed population dynamics, and thus
can be useful for suppressing weed population densities while re-
duc ing the burde n of crop protection pla ced on herbicides and phys-
ical weed control practices (Liebman and Nichols, 2020; Teasdale,
2018; Weisberger et al., 2019). Diversified crop rotation systems can
also decrease selection for herbicide resistance in weed populations
(Beckie and Harker, 2017; Beckie et al., 2014). More broadly, crop-
ping system diversification can play an important role in suppressing
insect pests and diseases, protecting soil quality, and improving crop
productivity (Bennett et al., 2012; Karlen et al., 1994).
Despite the potential advantages of diversified crop rotation
systems, over the past half-century, cropping system diversity has
declined in many agricultural regions worldwide. This trend is espe-
cially striking in the Midwestern USA , where expansion of the area
used for maize (Zea mays L.) an d soya bean (Glycine max (L.) Merr.) has
displaced the production of small-grain cereals (e.g. oat, Avena sativa
L., and wheat, Triticum aestivum L.) and forages (lucerne, Medicago
sativa L., and various grasses) (Broussard et al., 2012; Hatfield et al.,
2009; Sulc and Tracy, 2007). Loss of cropping system diversity in the
Midwestern USA, especially the large reduction in the area used for
small grains and perennial forages, has been linked to a variety of
negative environmental effects. These include greater discharge of
nitrogen and phosphorus to surface waters (Alexander et al., 2008;
Broussard and Turner, 2009; Hatfield et al., 20 09), increased levels
of soil erosion (Heathcote et al., 2012), and loss of soil organic carbon
(Karlen et al., 2006).
Simplification of cropping systems and attendant management
practices has generally been found to lead to simplified weed floras,
including greater dominance by harder-to-control species and in-
creased prevalence of herbicide-resistant weed genotypes (Gaba
et al., 2014; Mohler, 2001). Conversely, Smith et al., (2009) suggested
that increased cropping system diversity could lead to greater weed
diversit y, with concomitant reductions in the competitive effect s of
weeds on crops. In accordance with Smith et al.'s (2009) suggestion,
Murphy et al., (2006) and Leon et al., (2015) did find that increas-
ing cropping system diversity was associated with increased weed
seedbank diversity. Enlarging the scope with which weed communi-
ties are evaluated, Storkey and Neve (2018) hypothesised that weed
seedbank diversity could be used as an indicator of the agronomic
and environmental sustainability of cropping systems, with systems
associated with higher weed diversity being more sustainable than
those associated with lower weed seedbank diversity.
Here, we report the results of a field experiment and associated
modelling analyses that were suitable for testing Storkey and Neve's
(2018) hypothesis. We used multiple years of empirical data to eval-
uate weed abundance and diversity, crop productivity, and cropping
system profitability. We used life cycle assessment (LCA) models to
evaluate the environmental impact s of production systems in a man-
ner that considered raw materials and energy consumed, and the
products and wastes generated (Curran, 2008). Though often used
to evaluate industrial systems, LCA is also used to evaluate farming
systems and practices, such as pesticide use (Berthoud et al., 2011;
Poore and Nemecek, 2018; Rosenbaum et al., 2008). We used these
empirical data and LCA model outputs to test three hypotheses:
(a) increased cropping system diversity would be coincident with
increased weed seedbank diversity; (b) increased cropping system
diversit y would maintain or raise crop produc tivit y and profitability;
and (c) increased cropping system diversit y would be coincident with
lower environmental damage.
2 | MATERIALS AND METHODS
2.1 | Overview
To determine whether greater weed seedbank diversity was coin-
cident with increased agroecosystem sustainability, we compared
two contrasting crop rotation systems present in a long-term field
experiment with regard to patterns of weed infestation and a set
of agronomic, economic, and environmental performance indica-
tors. Weed biomass and seedbank data were collected from experi-
ment plots in 2014–2017. Empirical data collected from the plots in
2008–2016 were used to evaluate crop productivity and profitabil-
ity. Modelling approaches, including LCA tools, were used to evalu-
ate how the contrasting rotation systems performed in 2008–2016
with respect to herbicide-related aquatic toxicity, soil sediment and
nutrient discharge, fossil energy use, greenhouse gas emissions, and
human health damage from emissions of pollutants that increase at-
mospheric fine particulate matter (PM2.5) concentrations.
2.2 | Site characteristics, experimental design, and
management practices
Empirical measurements were made at Iowa State University's
Marsden Farm, which is situated in Boone County, Iowa, USA
(42°01′N, 93°47′W, 333 m above sea level). All soil types at the
experimental site are Mollisols (Lazicki et al., 2016). The site has a
small amount of sub-surface tile drainage but is subject to localised
  
|
 3
LIEBMAN E t AL.
flooding during periods of high precipitation. The site was used for
several decades to produce maize and soyabean prior to the initia-
tion of experimental work.
In 2002, a 9-hectare experiment was established at the site to
compare different crop rotation systems and contrasting weed man-
agement regimes (Davis et al., 2012; Hunt et al., 2017; Liebman et al.,
2008). In the present study, we made use of data from a subset of
the treatments represented in the experiment: a 2-year maize–soy-
abean rotation and a 4-year maize–soyabean–oat plus lucerne–lu-
cerne rotation, both managed with herbicides applied to maize and
soyabean at full labelled rates.
Each of the 24 experimental units used in this study was
9 m × 84 m. Plots were organised in a randomised complete block
design, with every crop phase of both rotation systems present
every year in each of four replicate blocks (Table 1). The six rota-
tion system × crop phase combinations were randomly assigned to
experimental units (i.e. plots) in each replicate block. During the
course of the experiment, the rot ation system used in each plot re-
mained constant, but the crop phases present in each plot changed
yearly to follow the order of crops within the rotation sequences
(Table 1). This type of experimental design has the advantage of
replicating crop and rotation system treatments within years, thus
avoiding the confounding of year and treatment effects (Payne,
2015).
Plots were managed with farm machinery suitable for commer-
cial operations, and crops were dependent on rainfall, with no sup-
plemental irrigation. Maize and soyabean were grown for seed, oat
was grown for seed and straw, and lucerne, which was sown with
oat and which continued to grow after oat harvest, was used for
hay. The 2-year maize–soyabean system currently dominates much
of the Midwestern USA and is used to generate feedstocks for of f-
site livestock and liquid fuel production, whereas the 4-year system
is representative of integrated farms in the region that couple crop
and livestock production.
Soil fertility and tillage practices differed between the rota-
tion systems. Mineral fertilisers were applied to the 2-year system
at rates based on soil tests. Fertility in the 4-year system was pro-
vided by composted cattle manure, which was applied once every
4 years at the termination of the lucerne phase, and lower rates of
mineral fertilisers, which were applied based on soil tests to bring
soil fertility levels in both rotation systems to roughly equal levels.
As reported by Hunt et al., (2019), averaged over all crop phases
during 2008–2016, mineral fertilisers were applied to the 2-year
system at 89 kg N ha-1 yr-1 and 15 kg P ha-1 yr-1; the 4-year rotation
received 8 kg N ha-1 yr-1 and 9 kg P ha-1 yr-1 from mineral fertilisers
and 34 kg N ha-1 yr-1 and 11 kg P ha-1 yr-1 from manure. Similar rates
of fertility amendments were used in 2017. In the 2-year rotation,
maize plots were sur face cultivated in the spring before planting and
chisel ploughed in the fall following harvest; soyabean plots were
surface cultivated before planting. Similar practices were used for
maize and soyabean in the 4-year system, but, additionally, soyabean
residue was disked before planting the oat and lucerne mixture, and
lucerne was mouldboard ploughed in the fall preceding maize pro-
duction. The effects of these fer tility and tillage practices were in-
tertwined with those of the crops in which they were used and were
part of system-level comparisons in which suites of farming prac-
tices varied between the different rotation systems.
Chemical weed management in the present study relied on pre-
and post-emergence herbicides that were broadcast during maize
and soyabean phases of both rotations; no interrow cultivation was
used in either maize or soyabean. Herbicide product selection was
driven by the identity, size, and density of observed weed species,
and thus differed slightly among years. Oat and lucerne received
no herbicide treatments throughout the study, as weeds were
suppressed by mowing stubble and removing hay. Table 2 shows
chemical and mechanical weed management practices used during
2014–2017, when weed measurements were made for the present
study; weed management practices in preceding years were given
by Hunt et al., (2017).
2.3 | Weed data
Above-ground weed biomass from maize and soyabean plots was
determined in September 2014–2017 prior to crop harvest based
on material collected from eight randomly selected 3.05 m × 0.76 m
sampling areas per plot. Weed biomass in oat and lucerne plots was
determined in September or early October 2014–2017 by clipping
plant shoots at ground level in eight 0.25 m2 quadrats per plot.
Sampling areas in all crops were located at least 3 m from plot edges.
TABLE 1 Crop phases of the 2-year and 4-year rotation systems present in each of four replicate blocks during 2008–2017
Rotation s ystem
Year
2008 2009 2010 2011 2012 2013 2014 2015 2016 2 017
2-year MSMSMSMSMS
2-year SMSMSMSMSM
4-year MS O L M S O L M S
4-year S O L M S O L M S O
4-year OL M S O L M S O L
4-year L M S O L M S O L M
Abbreviations: L, Lucerne; M, maize; O, oat intercropped with lucerne; S, soyabean.
4 
|
   LIEBMAN Et AL.
Weed biomass samples were placed in forced air ovens for drying,
then weighed at ~ 0% moisture.
The two most common methods of assessing soil weed seed-
banks are germination of weed seeds from soil placed in trays in a
glasshouse and direct extraction of seeds from soil. We chose to use
a direct extraction approach because it has been found to be more
accurate for quantifying weed seed density, species richness, and
diversit y (Reinhardt and Leon, 2018). We determined densities of
viable weed seeds in the soil to a depth of 20 cm by drawing 35 cores
(in 2014) or 36 cores (in 2015, 2016, and 2017) with a 17.5-mm-di-
ameter probe from each plot after crop harvests were completed in
October or November. Soil samples were composited by plot, and
silt and clay particles were washed away from seeds in an elutria-
tor (Wiles et al., 1996). The material remaining after elutriation was
further processed with a floatation procedure that used 5M calcium
chloride solution to separate sand and gravel fragments from plant
materials. Seeds were then recovered with forceps under a micro-
scope, enumerated by species, and analysed for viability via direct
germination in a growth chamber and crush testing (Borza et al.,
20 07 ). Ungermin at ed seed s that resist ed forceps pr essure were con -
sidered viable and included with germinated seeds in determining
the total densities of viable seeds in each plot. Weed seed densities
were expressed as number per m2 of field surface area to a depth of
20 cm, based on the diameter and number of soil cores drawn from
each plot.
We evaluated weed seedbank diversity, species richness, and
evenness based on the numbers of viable seeds of each species
recovered from each plot each year. We calculated Simpson's
TABLE 2 Chemical and mechanical weed management practices for crops grown in 2-year and 4-year rotation systems in 2014–2017
Rotation(s) Crop Year Practices
2-year and 4-year Maize 2014 Pre-emergence: thiencarbazone methyl (0.037 kg a.i. ha-1 ) plus
isoxaflutole (0.092 kg a.i. ha-1) (Corvus 1.88 and 0.75 SC, Bayer
AG)
2015 Pre-emergence: thienc arbazone methyl (0.037 kg a.i. ha-1) plus
isoxaflutole (0.092 a.i. k g ha-1) (Corvus 1.88 and 0.75 SC, Bayer
AG)
2016 Pre-emergence: thiencarbazone methyl (0.035 a.i. kg ha-1) plus
isoxaflutole (0.089 a.i. kg ha-1 ) (Corvus 1.88 and 0.75 SC, Bayer
AG); post-emergence: nicosulfuron (0.053 kg a.i. ha-1) (Accent Q
54.5 DF, DuPont) plus mesotrione (0.105 kg a.i. ha-1 ) (Callisto 4 SE,
Syngenta AG)
2017 Pre-emergence: thiencarbazone methyl (0.037 kg a.i. ha-1) plus
isoxaflutole (0.093 a.i. k g ha-1) (Corvus 1.88 and 0.75 SC, Bayer
AG)
2-year and 4-year Soyabean 2014 Post-emergence: glyphosate as potassium salt (1.326 k g a.i. ha-1)
(Roundup PowerMax 4.5 SL, Monsanto Co.) plus acifluorfen
(0.297 kg a.i. ha-1 ) (Ultra Blazer 2 SL, United Phosphorus Ltd.)
2015 Post-emergence: glyphosate as potassium salt (1.203 kg a.i. ha-1)
(Roundup WeatherMax 4.5 SL , Monsanto Co.) plus acifluorfen
(0.263 k g a.i. ha-1) (Ultra Blazer 2 SL, United Phosphorus Ltd.)
2016 Post-emergence: glyphosate as potassium salt (1.203 kg a.i. ha-1)
(Roundup WeatherMax 4.5 SL , Monsanto Co.) plus acifluorfen
(0.263 k g a.i. ha-1) (Ultra Blazer 2 SL, United Phosphorus Ltd.)
2017 Pre-emergence: flumioxazin (0.109 kg a.i. ha-1) ( Valor 51 WDG,
Valent U.S.A. LLC); post-emergence: glyphosate as potassium
salt (1.249 kg a.i. ha-1 ) (Roundup PowerMax 4.5 SL , Monsanto
Co.) plus acifluor fen (0.224 kg a.i. ha-1) (Ultra Blazer 2 SL, United
Phosphorus Ltd.)
4-year Oat + lucerne 2014 Stubble mowing (1x), 6 weeks after oat har vest
2015 Stubble mowing (1x), 4 weeks af ter oat harvest
2016 Stubble mowing (1x), 4 weeks after oat harvest
2017 Stubble mowing (2x), 3 weeks and 7 weeks af ter oat harvest
4-year Lucerne 2014 Hay removal (3x)
2015 Hay removal (3x)
2016 Hay removal (4x)
2017 Hay removal (4x)
Abbreviation: a.i., active ingredient.
  
|
 5
LIEBMAN E t AL.
diversity index, 1/D, as the inverse of D = Σpi
2, where pi is the
proportional abundance of the ith species in each plot in each
year. Species richness, S, was calculated as the number of weed
species with viable seeds in each plot in each year. Simpson's
evenness index was calculated by dividing the diversity index,
1/D, by S. We assessed the relative densities of weed species
by dividing the number of viable seeds of each individual spe-
cies by the total number of viable seeds of all weeds found in the
four replicate blocks of each crop × rotation system combination
during 2014–2017.
2.4 | Crop data
Maize and soyabean yields were determined in 2008–2016 from six
rows (383 m2) of each plot using a combine and a weigh wagon, or a
combine equipped with a yield monitor (Hunt et al., 2019). Oat grain
yield was determined in the same ways from entire plots (1,530 m2).
Yields of oat straw and lucerne hay (from multiple har vests) were
determined by weighing bales from entire plots. After determining
crop moisture concentrations, yields for all materials were adjusted
to 0% moisture. Annual energy production by each rotation system
was then calculated as the sum of the higher heating value of each
harvested material (kJ g–1) multiplied by the mass per hectare of
each product, divided by two for the 2-year rotation and four for the
4-year rotation (Hunt et al., 2020).
2.5 | Economic data
Economic returns to land and management for each rotation sys-
tem were assessed using field operations logs for labour demands,
seed and chemical inputs, crop yields, and year- and product-
specific databases for materials cost s, operations costs, and crop
pr ices. In put cost s for see ds, fe r tilis ers , herb ici des , and ot her prod -
ucts were obtained from local retailers and state and regional re-
ports. Labour, fuel, and machinery cost data were derived from
Iowa State University Extension and Outreach publications. We
assumed that manure used in the 4-year rotation was produced
by on-farm or neighbouring-farm animals and that costs were in-
curred for labour and machinery to spread it; no cost was assigned
to the manure itself, which was assumed to be a waste product
from the livestock enterprise. Local market-year crop prices were
obtained from the U.S. Department of Agriculture's National
Agricultural Statistics Service, and gross revenue was calculated
as the product of crop price and yield. Mortgage and lease costs
and revenue from government payments were excluded from the
study. Annual net returns per hectare were calculated as the dif-
ference between gross returns and non-land and non-marketing
costs, averaged over the two crops grown in 2 years in the 2-year
system and the four crops grown in 4 years in the 4-year system.
Information pertaining to the economic assessments is described
in detail in Hunt et al., (2017, 2019).
2.6 | Environmental performance indicators
Herbicide toxicity to aquatic organisms was assessed for each
rotation system using the USEtox 2.0 model (Henderson et al.,
2011; Rosenbaum et al., 2008) and procedures described by Hunt
et al., (2017). Data used to populate the USEtox model were de-
rived from 2008 to 2015 operations logs for the field experiment,
which included the identities, formulations, and rates of the active
ingredients applied. USEtox expresses the potential freshwater
ecotoxicity impacts of herbicide applications in comparative tox-
icity units (CTUe) that are calculated as a function of the mass of
the specific chemicals applied; their environmental fates, including
degradation, persistence, and transport; and their effects on various
freshwater aquatic species.
Discharge of soil sediment, nitrogen and phosphorus in overland
flow ('run-off'), and nitrate-N in leachate water were estimated for
each rotation in 2008-2016 using the ArcSWAT interface (Winchell
et al., 2013) of the SWAT hydrologic process model (Gassman et al.,
2007) and procedures described by Hunt et al., (2019). SWAT uses
site-specific parameter values for climate, soil characteristics, ele-
vation, topography, land cover, and farming practices to calculate
hydrologic fluxes and soil and nutrient discharges. The quantities of
nitrogen and phosphorus in run-off water estimated by the model
comp ri sed the sums of or ganic N, disso lved nitr ate-N , org an ic P, sed -
iment P, and dissolved mineral P.
Fossil energy use, emissions of greenhouse gases (carbon diox-
ide, methane, and nitrous oxide), and human health damages from
pollutants that increase concentrations of atmospheric fine par-
ticulate matter (PM2.5) (primary PM2.5, ammonia, nitrogen oxides,
sulphur oxides, and volatile organic compounds) were estimated
on a ha-1 yr-1 basis for each crop phase of each rotation system and
then averaged over the two phases of the 2-year system and the
four phases of the 4-year system. Our analyses covered the man-
ufacture, packaging, distribution, and application of fertilisers and
herbicides; manure generation, storage, and application; farm ma-
chinery operations; and grain drying. We used the life cycle assess-
ment model GREET 2017 (Argonne National Laborator y, 2017) to
estimate fossil energ y consumption, greenhouse gas emissions, and
non-ammonia PM2.5-linked pollutant emissions. Multiple informa-
tion sources were used to estimate ammonia emission quantities and
locations: the Carnegie Mellon University ammonia emissions model
(Goebbes et al., 2003); Ohio State University's manure management
guide (James et al., 2006); the University of Nebraska's manure
source ammonia emissions calculator (Stowell and Koelsch, 2009);
and the U.S. Environmental Protection Agency's national emissions
inventory (USEPA, 2017). A location-specific approach for predict-
ing PM2.5 generation, movement, and damage to human health was
employed using methods described by Goodkind et al., (2019) and
Hill et al., (2019). Human healt h da ma ge resulting from chronic expo-
sure to PM2.5 was monetised using the United States Environmental
Protection Agency's (2010) mortality risk valuation procedures,
which estimate willingness to pay for reductions in mortality risks.
Our analyses of fossil energy use, greenhouse gas emissions, and
6 
|
   LIEBMAN Et AL.
air quality-related human health damage were parameterised with
data from the field experiment during 2008–2016. Details of these
analyses are provided by Hunt et al., (2020).
2.7 | Statistical analyses
The restricted maximum likelihood (REML) method for linear mixed-
effect models was used to evaluate the effects of the rotation
systems on weeds and multiple agronomic, economic, and environ-
mental performance metrics (Payne, 2015). For response variables
that included variation across blocks and years (weed biomass, weed
seedbank density, weed seedbank diversity, crop yields, crop energy
production, and returns to land and labour), the statistical models
included main and interaction effects for block, year, and rotation
system or crop phase within rotation system, with block and year
treated as random factors and rotation or crop phase within rota-
tion system treated as fixed factors. For response variables with no
variation across blocks (fossil energy use, herbicide aquatic toxic-
ity, soil sediment loss, N and P discharge, greenhouse gas emissions,
and human health damage from PM2.5), models were constructed
with main and interaction ef fects for year and rotation system or
crop phase within rotation system, with year treated as a random
factor and rotation or crop phase within rotation system treated as
fixed factors. Data for weed biomass and weed seedbank density
were ln-transformed to meet criteria for normality and homogeneit y
of variance. Possible differences in weed responses between crop
phases of the two rotation systems were assessed with single de-
gree of freedom contrasts. Significance for statistical tests was set
at α = 0.05.
3 | RESULTS
3.1 | Weed biomass, seedbank density, and
seedbank diversity
Weed biomass differed significantly among crop phases of the two
rotation systems (Figure 1a, Table 3). Weed biomass was greater in
the oat stubble and lucerne phases of the 4-year rotation than in
the maize and soyabean phases of both the 4-year and 2-year ro-
tations (p < 0.0001), but it did not differ between oat and lucerne
(p = 0.20). Weed biomass in maize and soyabean was not affected
by rotation system ( p = 0.74) or by crop identity (p = 0.36). Mean
values of weed biomass in maize and soyabean were < 60 kg ha-1
(Figure 1a). In contrast, mean values for weed biomass in oat and
lucerne were 624 kg ha-1 and 156 kg ha-1 respec tively (Figure 1a). As
a consequence of greater weed biomass in oat and lucerne phases
of the 4-year rotation, average weed biomass across all crop phases
of the 4-year rotation was greater than the average for the 2-year
rotation (p = 0.003).
Total density of viable weed seeds also differed significantly
among crop phases of the two rotation systems (Table 3), with mean
values ranging from 9,360 seeds m-2 in the oat phase of the 4-year
rotation to 2,770 seeds m-2 in the maize phase of the 2-year rotation
(Figure 1b). Weed seedbank densit y was greater in the oat and lu-
cerne phases of the 4-year rotation than in the maize and soyabean
phases of both the 4-year and 2-year rotations (p = 0.015), but it did
not differ between oat and lucerne (p = 0.79). Weed seedbank den-
sity in maize and soyabean did not differ between rotation systems
(p = 0.99), nor did it differ between maize and soyabean (p = 0.56).
Though weed seed density was greatest in the oat and lucerne
FIGURE 1 Weed biomass (a) and viable weed seed density (b) in different crops in 2014–2017 within 2-year and 4-year rotations. Means
and their standard errors are shown; n = 16. Statistical analyses were conducted on ln-transformed data. M, S, O, and L refer to maize,
soyabean, oat intercropped with lucerne, and lucerne respectively; 2 and 4 refer to the 2-year and 4-year rotations
a b
  
|
 7
LIEBMAN E t AL.
phases of the 4-year rotation, no dif ference was detected between
rotation systems when weed seed densities were averaged over all
crop phases (p = 0.19).
Viable weed seeds recovered from the 3,432 soil cores taken
in 2014–2017 were placed in 16 species groups (Table 4). Fourteen
taxa were identified to species rank. For the purposes of analys-
ing weed seedbank diversity, species richness, and evenness, two
Setaria spe cie s wer e comb ine d int o a sing le taxon o mic unit an d the
0.46% of seeds that remained unidentified were considered one
unit. The dominant weed taxa present in the soil were the annual
broad-leaved species Amaranthus tuberculatus (Moq.) J.D. Sauer,
Chenopodium album L., and Solanum ptychanthum Dunal, and the
annual grass species Setaria pumila (Poir.) Roem. and Schult. and
S. faberi Herrm. (which were not differentiated), Digitaria sanguina-
lis (L.) Scop., and Echinochloa crus-galli (L.) P. Beauv. (Table 4). The
relative density of Chenopodium album seeds was greater in the
maize and soyabean phases of both rotations than in the oat and
lucerne phases of the 4-year rotation (Table 4). Conversely, the
relative densities of S. faberi, S. pumila, D. sanguinalis, and E. crus-
galli were higher in oat and lucerne than in maize and soyabean
(Table 4).
Averaged over all crop phases within the rotations, the mean
Simpson's diversity index value for seedbanks of the 4-year rotation
(2.31) was 29% greater (p = 0.010) than that of the 2-year rotation
(1.79) (Figure 2a). As shown in Table 3, weed seedbank diversity was
greater in the oat and lucerne phases of the 4-year rotation than in
the maize and soyabean phases of the 4-year and 2-year rotations
(p = 0.006), but seedbank diversity did not differ between oat and
lucerne (p = 0.30). Weed seedbank diversity in maize and soyabean
did not dif fer betwee n th e 2-year an d 4-year rot at io ns (p = 0.14), no r
did it differ between maize and soyabean (p = 0. 29).
Differences among crop phases and rotations in weed seedbank
diversit y were driven by differences in weed seedbank species rich-
ness (Figure 2b, Table 3). Averaged over crop phases within the two
rotations, species richness for the 4-year rotation (3.53) was 38%
greater (p = 0.010) than for the 2-year rotation (2.56). Species rich-
ness was greater in the oat and lucerne phases of the 4-year rota-
tion than in the maize and soyabean phases of the 4-year and 2-year
rotations (p = 0.002) but did not differ between oat and lucerne
(p = 0.73). Species richness in maize and soyabean did not differ
between the 2-year and 4-year rotations (p = 0.24), nor between
maize and soyabean (p = 0.47). Simpson's evenness index for weed
seedbanks (Figure 2c) did not differ among treatments (Table 3).
Averaged over all phases within the rotations, mean evenness of the
2-yea r rotat ion (0.74) did not dif fer (p = 0. 25) fro m that of the 4-year
rotation (0.69).
3.2 | Maize and soyabean seed yields and total crop
energy production
During 2008–2016, maize seed yield was 4% greater in the 4-year
rotation than in the 2-year rotation (p = 0.04) on those hectares
sown with maize (Table 5). Soyabean seed yield was 18% greater in
the 4-year rotation than in the 2-year system (p = 0.0 007) (Table 5).
For a given unit of land cropped with all phases of the whole rotation
systems, total production of maize and soyabean would be lower in
the 4-year rotation than the 2-year rotation, since those crops would
occupy only half the land area in the former system relative to the
latter. However, it is also possible to compare the two rotation sys-
tems with regard to energy content of the full set of crop products
generated by each. To perform those calculations, it was assumed
TABLE 3 Crop and rotation system effects on above-ground weed biomass, total viable weed seed density in soil, and Simpson's
diversit y, species richness, and Simpson's evenness of weed seeds in soil, 2014–2017
ln (weed biomass)
ln (weed seed
density) Simpson's diversity Species richness
Simpson's
evenness
Model R20.72 0.71 0.35 0 .62 0.50
Crop and rotation s ystem
effect
F5,15 p F5,15 p F5,15 p F5,15 p F5,15 P
12.16 <0.0001 1.60 0.22 3.06 0.042 3. 26 0.035 0.81 0.56
Contrasts F1,15 p F1,15 p F1,15 p F1,15 p F1 ,15 P
(M2 & S2) versus (M4,
S4, O4 & L4)
12.32 0.003 1.84 0.19 8.64 0.010 8.59 0.010 1.43 0.25
(O4 & L4) versus (M2,
M4, S2 & S4)
57. 95 <0.0001 7. 55 0.015 10.30 0.006 13.95 0.0 02 2.68 0.12
O4 versus L4 1.78 0.20 0.08 0.79 1 .17 0.30 0.1 2 0.73 0.08 0.78
(M2 & S2) versus (M4
& S4)
0.18 0.74 0.0004 0.99 2.38 0.14 1 .51 0.24 0.19 0. 67
(M2 & M4) versus (S2
& S4)
0.88 0.36 0.36 0.56 1.26 0.29 0.54 0.47 0.0001 0.99
(M2 & S4) versus (M4
& S2)
0.08 0.78 0.04 0.85 0.23 0.64 0.17 0.69 1 .11 0.31
Note: M, S, O, and L refer to maize, soyabean, oat intercropped with lucerne, and lucerne respectively; 2 and 4 refer to the 2-year and 4-year
rotations.
8 
|
   LIEBMAN Et AL.
that if 1.0 ha were used for the 4-year rotation, four parcels, each
0.25 ha in size, would be used for maize, soyabean, oat, and lucerne,
respectively, whereas for the 2-year rotation, there would be two
parcels, each 0.5 ha in size, with one used for maize and the other for
soyabean. As shown in Table 5, energy output of the two rotation
systems per unit of land area was equal (p = 1.00).
3.3 | Net returns to land and management
Net annual returns per unit of land area, calculated by subtract-
ing non-land and non-marketing production costs from the gross
revenue generated by sale of all crop products, were equivalent for
the two rot ation systems (p = 0.58) (Table 5). These calculations
assumed the same proportional distribution of land as previously
described for the calculation of energy output. More detailed infor-
mation concerning economic cost s and returns can be obtained from
Hunt et al., (2019, 2020).
3.4 | Environmental impacts
Impacts of the two rotation systems on aquatic biota and soil, water,
air, and human health were evaluated using the same proportional
Weed species
Relative density (%)
M2 S2 M4 S4 O4 L4
Dicotyledons
Abutilon theophrasti
Medik.
0.00 0. 51 0. 28 0.00 0.00 0.00
Achillea millefolium
L.
0.00 0.00 0.00 0.00 2.55 0.00
Amaranthus
tuberculatus (Moq.)
J. D. Sauer
61.4 9 62.37 5 4.98 58.24 49.71 38.22
Chenopodium album
L.
30.97 3 4.90 30.75 33.09 19.87 37.75
Datura stramonium
L.
0.00 0.00 0.66 0.00 0.00 0.00
Morus alba L. 0.00 0.00 0.00 0.71 0.00 0.00
Persicaria
pensylvanica (L.) M.
Gomez
0.31 0.00 0.00 0.00 0.00 0.39
Solanum
ptychanthum
Dunal
0.98 0.49 2.35 1.18 1.31 1.72
Sonchus arvensis L. 0.00 0.25 0.00 0.00 0.00 0.76
Sonchus asper (L.)
Hill
0.00 0.00 0.00 0.00 0.0 0 0.95
Taraxacum officinale
F. H. Wigg.
0.30 0.00 0.57 0.24 0.00 0.13
Monocotyledons
Digitaria sanguinalis
(L.) Scop.
0.00 0.00 0.64 0.00 2 .76 5.09
Echinochloa crus-
galli (L.) P. Beauv.
0.00 0.00 0.00 0.00 2.38 0.38
Setaria faberi Herrm.
and S. pumila (Poir.)
Roem. & Schult.
4.36 1.48 8.85 6.28 20.78 14.12
Panicum capillare L. 0.00 0.00 0.00 0.00 0.46 0.00
Undetermined 1.60 0.00 0.91 0.25 0.19 0 . 51
Note: Species densities were calculated as a percentage of the total viable weed seeds recovered
from each crop x rotation combination.
M, S, O, and L refer to maize, soyabean, oat intercropped with lucerne, and lucerne respectively; 2
and 4 refer to the 2-year and 4-year rotations.
TABLE 4 Relative density of weed
species in seedbanks of crops grown in
the 2-year and 4-year rotation systems
during 2014–2017
  
|
 9
LIEBMAN E t AL.
distribution of land among different crop phases used for the analy-
ses of total energy output and net economic returns. With the ex-
ception of nitrate-N leaching, all of the environmental impacts of the
4-year rotation that were investigated were lower than those of the
2-year rotation ( Table 5).
The presence of two crop phases within the 4-year rotation that
were not sprayed with herbicides (i.e. oat and lucerne) reduced her-
bicide-related toxicity to aquatic organisms 50% (p = 0.003) relative
to the 2-year rotation. Loss of soil sediment in the 4-year rotation
was 62% lower than in the 2-year system (p = 0.007). Nitrogen and
phosphorus in run-off were 38% lower (p = 0.03) and 31% lower
(p = 0.0 4), respectively, in the 4-year than in the 2-year rotation.
Nitrate-N in leachate water was not significantly affected by rota-
tion system (p = 0.33), though the numerical trend mirrored that
for N in surface run-off. Use of the more diverse rotation rather
than the shorter rotation reduced fossil energy consumption 64%
(p < 0.00 01), greenhouse gas emissions 64% (p < 0.00 01), and dam-
age to human health due to fine particulate matter emissions 57%
(p < 0.0001).
4 | DISCUSSION
Storkey and Neve (2018) hypothesised that greater weed seedbank
diversity accompanies greater agroecosystem sustainability. They
emphasised that to capture the full range of effects on weeds that
are specific to individual crops and their associated management
practices, it is necessary to assess weed communities over all com-
ponent phases of whole cropping systems. Results of the present
study, in which we sampled weed seedbanks for 4 years in all crop
phases of two rotation systems and measured other performance
indicators for 9 years, support Storkey and Neve's hypothesis. We
found that when considering whole rotation systems, diversifying
a 2-year maize–soyabean rotation with two additional crop phases,
oat and lucerne, to form a 4-year rotation increased Simpson's
diversit y index for weed species in the soil seedbank (Figure 2a),
while increasing maize and soyabean productivity, maintaining total
crop energy production and profitability, and reducing damage to
the environment and human health (Table 5). We emphasise that we
considered full set s of crops to assess overall rotation system perfor-
mance; consideration of weed seedbanks and agronomic, economic,
and environmental performance indices in only one crop phase of
each rotation would have provided an incomplete picture.
The composition of weed communities above- and below-ground
is driven, in large part, by crop-specific traits and agronomic man-
agement practices that act as filters regulating the abundance and
distribution of different species (Booth and Swanton, 2002). In an ex-
periment conducted in Michigan, Smith and Gross (2006) observed
that weed seedbanks of rotations containing maize, soyabean, and
winter wheat changed rapidly in composition and abundance and
wer e strongly influenced by the most recent crop within the crop se-
quences. In a survey of weeds growing in arable fields in France, Fried
et al., (2008) foun d that weed co mmunity comp osition reflected cur-
rent and preceding crop types identified according to sowing season.
In a second study of weeds in French crop fields, Meiss et al., (2010)
reported that weed communities associated with the perennial crop
lucerne were distinctly different from those associated with six an-
nual crops: winter wheat, oilseed rape (Brassica napus L.), pea (Pisum
sativum L.), sunflower (Helianthus annuus L.), maize, and sorghum
(Sorghum bicolor (L.) Moench). Meiss et al., (2010) also noted that dif-
ferences between autumn- and spring/summer-sown annual crops
were evident. Weed communities on commercial farms in western
France differed among four types of fields: winter wheat following
various annual crops, 1-year-old lucerne following annual crops, 2- to
6-year-old lucerne, and wheat following pluriannual lucerne (Meiss
et al., 2010). In the latter study, lucerne shifted weed communities
away from annual broad-leaved species, whereas wheat reduced
the abundance of perennial species, rosette-forming annuals, and
certain grasses. In a long-term Canadian study examining different
cropping systems composed of maize, soyabean, and either oat or
FIGURE 2 Simpson's diversity index (a), species richness (b), and Simpson's evenness index (c) for weed species in soil seedbanks of
the 2-year and 4-year rotations sampled in 2014–2017. Means and their standard errors are shown; n = 16. M, S, O, and L refer to maize,
soyabean, oat intercropped with lucerne, and lucerne respectively; 2 and 4 refer to the 2-year and 4-year rotations
ab c
10 
|
   LIEBMAN Et AL.
wheat, Doucet et al., (1999) reported that within each crop, reduc-
tions in the intensity of herbicide use increased weed plant density,
species richness, and diversity. Murphy et al., (2006) investigated
weed dynamics on commercial farms in C anada producing maize,
soyabean, and wheat and found that reductions in tillage intensity
increased the diversity of weeds growing in fields and recovered
from seedbanks. Cardina et al., (1991) also reported that reductions
in tilla ge intensit y and soil dis turba nce led to in creas es in wee d seed-
bank diversity.
Because varied crops and their associated management prac-
tices can have crop-specific effects on the survival and reproduction
of different weed species, diverse rotations could, when analysed
across all of their component crop phase s, ex hibit greater weed spe-
cies diversity than simpler rotation sequences, as a consequence
of each crop phase selecting for or against a par ticular set of weed
species. Murphy et al., (2006) did indeed find that increasing crop
diversit y within rotation sequences was associated with increased
weed seedbank diversity. Similarly, Leon et al., (2015) reported that
the rotation-wide weed seedbank diversity, species richness, and
evenness of a cotton (Gossypium hirsutum L.)-peanut (Arachis hypo-
gaea L.)-bahiagrass (Paspalum notatum Flüggé) rotation were greater
than for a simpler cotton–peanut rotation. However, as noted by
Smith and Gross (2006), weed seedbanks assessed for the same crop
grown in contrasting rotation systems might not show differences in
Performance indicator
4-year
rotation
2-year
rotation F p
Data
source
Maize grain yield (dr y), Mg
ha-1 yr-1
10.6 (0.19) 10.2 (0.19) 6.14 0.04 Hunt
et al.,
(2019)
Soyabean seed yield (dry),
Mg ha-1 yr-1
3.4 (0.08) 2.8 (0.09) 28.28 0.0007 Hunt
et al.,
(2019)
Energy content of all
harvested product s, GJ
ha-1 yr-1
120 (4.5) 120 (3.0) 0.00 1.00 Hunt
et al.,
(2020)
Net returns to land and
management, $ ha-1 yr-1
872 (60.3) 833 (71.6) 0.33 0.58 Hunt
et al.,
(2019)
Herbicide aquatic toxicity,
CTUe ha-1 yr-1
2,363 (532) 4,727 (1,064) 18.49 0.003 Hunt
et al.,
(2017 )
Soil sediment loss, Mg
ha-1 yr-1
1.0 (0.16) 2.6 (0.4 8) 3.65 0.007 Hunt
et al.,
(2019)
Tot a l N discharge in run-
off, kg ha-1 yr-1
6.2 (0.89) 10.0 (1.80) 6.63 0.03 Hunt
et al.,
(2019)
Tot a l P discharge in run-
off, kg ha-1 yr-1
1.6 (0.23) 2.3 (0.45) 5.68 0.04 Hunt
et al.,
(2019)
Nitrate-N discharge in
leachate, kg ha-1 yr-1
15.4 (4.51) 19.8 (6.95) 1.06 0.33 Hunt
et al.,
(2019)
Fossil energy use, GJ
ha-1 yr-1
3.4 (0.14) 9.5 (0.35) 119. 23 <0.0001 Hunt
et al.,
(2020)
GHG emissions, kg CO2e
ha-1 yr-1
281 (15.2) 783 (31.3) 96.56 <0.0001 Hunt
et al.,
(2020)
PM2.5-related human
health damage, $ ha-1 yr-1
298 (11.6) 688 (22.4) 62.65 <0.0001 Hunt
et al.,
(2020)
Note: Means and their standard errors are shown.
Data and analyses are for the years 20 08–2016 for all variables except herbicide aquatic toxicity,
for which data and analyses covered the years 2008–2015. Degrees of freedom of the F value for
herbicide aquatic toxicity were 1 and 7; for other response variables, degrees of freedom for F
values were 1 and 8.
TABLE 5 Crop yields, economic
performance, and selected environmental
and human health impacts of 2-year and
4-year rotation systems
  
|
 11
LIEBMAN E t AL.
abundance or composition, since seedbank responses can be rapid
and crop-specific, and seeds of many weed species are short-lived
and non-persistent, thus minimising legacy effects of previous crop
phases.
Variations in disturbance timing, as reflected in crop sowing and
harvest dates, and in functional attributes of crops, such as height
and competitive ability for light, are important determinants of crop-
ping system effects on weeds, and may have stronger effects than
crop species richness per se. Mahaut et al., (2019) examined data
from 473 fields in France collected over five consecutive seasons
and found that when evaluated over multiple phases of the rota-
tions, weed species richness increased with increasing diversity in
crop height and sowing date, whereas weed abundance decreased
with the diversity of crop sowing dates. In a meta-analysis of 54
crop rotation experiments conducted in a wide range of habitats
worldwide, Weisberger et al., (2019) reported that increasing crop
diversit y reduced weed density by an average of 49%, but that crop-
ping systems that increased the variance around planting dates were
substantially more weed-suppressive than those that increased crop
species richness alone. In the present study, we observed greater
rotation-wide weed seedbank diversity in the 4-year rotation, which
comprised four crops, than in the 2-year rotation, which comprised
two crops (Figure 2a, Table 3). This was the result of greater weed
seedbank species richness in oat and lucerne than in maize and soy-
abean (Figure 2b, Table 3). Increased weed species richness and
diversity in the seedbanks associated with oat and lucerne might re-
flect those crops not being treated with herbicides while maize and
soyabean were, or it might reflect differences in other management
practices, as well as differences in crop phenology and resource use.
Within our experiment, oat was planted earlier and more densely
than maize and soyabean, and was harvested in mid-July, rather
than in late September or October as for the latter two crops. Unlike
maize, soyabean, and oat, lucerne is a deep-rooted perennial forage
species that, when harvested regularly, competes well with the an-
nual weeds.
The mean values for weed species richness (Figure 2b) that we
observed for the seedbanks of particular crop phases and rotation
systems (2. 5–4.0) were small relative to the 16 weed taxa we identi-
fied from the full set of samples we assessed (Table 4). Similarly, Leon
and Wright (2018) reported mean species richness values for weed
seedbanks sampled in different crop phases of a rotation sequence
ranged from 4.1 to 7.5, while the total number of weed species de-
tected was 20. These differences in species richness values based
on individual experimental unit s versus all experimental units reflect
a species–area relationship for weed seedbanks similar to relation-
ships noted by ecologists for many other types of communities; that
is, searching a larger area reveals more species (Gross, 1990). Despite
the low number of weed species we detected in the sets of soil cores
we drew from individual plots, differences among crop phases and
rotation systems were highly significant (Figure 2b, Table 3).
The variation among crop phases in weed seedbank density
(Figure 1b) and species richness (Figure 2b) and diversity (Figure 2a)
might be viewed as a recurrent pattern of release and contraction,
whereby oat and lucerne phases of the 4-year rotation permitted
greater weed growth (Figure 1a, Table 3), seed production, and di-
versity, and then, subsequent maize and soyabean phases reduced
weed growth, fecundity, and diversity. Similar cyclical patterns of
release and contraction were repor ted by Meiss et al., (2010) for
rotations containing wheat and lucerne, and by Leon and Wright
(2018) for cotton–peanut–bahiagrass rotations. In both of the latter
two studies, the forage phases (i.e. lucerne or bahiagrass) served to
release and expand the weed communities within the rotation se-
quences. A key point to emerge from the present study as well as
those by Meiss et al., (2010) and Leon and Wright (2018) is that re-
lease and expansion of weed communities within particular phases
of the respective rotations did not result in a loss of weed control in
the other crops. Thus, rotation-wide increases in weed diversity can
be consistent with adequate long-term weed suppression.
In the present study, increasing cropping system diversity not
only affected weeds, but also affected an important plant patho-
gen. Over a 6-year period, Leandro et al., (2018) observed that the
incidence and severity of soyabean sudden death syndrome (SDS),
a disease caused by the soil-borne pathogen Fusarium virguliforme
O' Do nne ll and T. Aoki , were subs t an tiall y re duced in the 4-yea r rota-
tion relative to the 2-year rotation. Reductions in SDS incidence and
severity were correlated with large increases in soyabean seed yield
(Table 5, Leandro et al., 2018) (Table 5). The mechanisms responsible
for differences in SDS between rotation systems have not yet been
ascertained.
In addition to being associated with greater weed community
diversit y, cropping system diversity can play an important role
with regard to the environmental impacts of agricultural produc-
tion. Deytieux et al., (2012) used empirical data and life cycle as-
sessment model s to compare five cropping syste ms in east-central
France and found that, on a land area basis, increased rotation
diversity coupled with decreased herbicide use lowered energy
demand, global warming potential, ozone formation, eutrophica-
tion, acidification, and aquatic, terrestrial, and human toxicities.
In a survey of 48 farm sites in two regions of France, Lechenet
et al., (2014) found that increased crop rotation diversit y was as-
sociated with reduction in use and environmental impac t of pesti-
cides, use of mineral N fertilisers, and fossil energy consumption.
In the present study, adding oat and lucerne to a maize–soyabean
rotation reduced herbicide use and aquatic toxicity (Table 5; Hunt
et al., 2017), lowered use of mineral N fer tiliser (Hunt et al., 2019),
decreased fossil energy consumption, greenhouse gas emissions,
and fin e par t ic ulate matt er da mage to huma n hea lth (Tabl e 5; Hu nt
et al., 2020), cut soil erosion and nutrient run-off (Table 5; Hunt
et al., 2019), and increased the activity–density and diversity of
ground beetles (Carabidae), which are key predators of insect
pests and weed seeds (O'Rourke et al., 2008). As noted previ-
ously, these environmental effects of the 4-year rotation system
accompanied high crop productivit y and a level of overall system
profitability that was equivalent to that of the simpler 2-year ro-
tation (Table 5). Charging for the cost of manure it self, rather than
for just the labour and machinery associated with its application,
12 
|
   LIEBMAN Et AL.
wou ld reduce profita bi lity of the 4-yea r rotation system below the
level we calculated, but this reduction would be about 5% of net
returns; thus, the economic performance of the 4-year and 2-year
rotations would remain similar (Poffenbarger et al., 2017).
We measured low levels of weed biomass in our experiment
plots (Figure 1a), and thus, weed growth and resource use proba-
bl y ha d littl e im pac t on the fun c t ion i ng of the two rotat i on syst e ms
we compared. While there is no reason to assume that there was
a cause-and-effect relationship between greater weed seedbank
diversit y in the 4-year rotation system (Figure 2a) and improved
agroecosystem sustainability in agronomic, economic, and envi-
ronmental dimensions (Table 5), all of these responses may have
been driven in a parallel manner by the cropping system diversi-
fication practices we employed, which provided not only greater
crop species richness, but also a range of disturbance regimes and
stress and mortality factors affecting weeds. Consequently, as
suggested by Storkey and Neve (2018), weed seedbank diversity
may indeed be a useful agroecosystem sustainability indicator.
Further evaluation of this hypothesis in more systems would be
useful.
Acknowledgements
We express our sincere thanks to Sumil K. Thakrar, Ann Johanns,
Riddh im an Bhatt achar ya , an d th e un de rg ra du ate stud ents and inter-
national visitors who provided assistance with plot maintenance and
data collection and analysis. We were saddened by the death of our
colleague, David N. Sundberg, during the course of this project and
respectfully acknowledge his farming and data management skills.
Our research was supported by grants from the U.S. Department of
Agriculture's Agriculture and Food Research Initiative (2014-67013-
21712) and the Leopold Center for Sustainable Agriculture (2014-
XP01), and by the U.S. Department of Agriculture's Hatch Project
MIN-12-083.
CONFLICT OF INTEREST
The authors declare no conflicts of interest .
REFERENCES
Alexander, R.B., Smith, R .A ., Schwarz, G.E., Boyer, E.W., Nolan, J.V.
and Brakehill, J.W. (2008) Differences in phosphorus and nitrogen
deliver y to the Gulf of Mexico from the Mississippi River Basin.
Environmental Science and Technology, 42, 822–830. https://doi.
org/10.1021/es071 6103
Argonne National Laboratory (2017) GREET 2017: The greenhouse gases,
regulated e missions, and en ergy use in transp ortation model. Lemont, IL:
Argonne National Laboratory, U.S. Department of Energy. Available
at: https://www.osti.gov/doeco de/bibli o/40773. [Accessed 13
Januar y 2021].
Beckie, H.J. and Harker, K.N. (2017) Our top 10 herbicide-resistant weed
management practices. Pest Management Science, 73, 1045–1052.
https://doi.org/10.10 02 /ps.4543
Beckie, H.J., Johnson, E.N., Leeson, J.Y., Shirriff, S.W. and Kapiniak, A.
(2014) Selection and evolution of acetyl-CoA carbox ylase (ACC)-
inhibitor resist ance in wild oat (Avena fatua L.) in a long-term alter-
native cropping systems study. Canadian Journal of Plant Science, 94,
727–731. https://doi.org/10.4141/CJPS2 013-361
Bennet t, A.J., Bending, G.D., Chandler, D., Hilton, S. and Mills, P. (2012)
Meeting the demand for crop production: The challenge of yield de-
cline in crops grown in short rot ations. Biological Reviews, 87, 52–71.
https ://doi.or g/10.1111/ j.14 69-185X. 2011.00184 .x
Berthoud, A.P., Maupu, P., Huet, C. and Poupart, A. (2011) Assessing
freshwater ecotoxicit y of agricultural products in life cycle as-
sessment (LCA): A case study of wheat using French agricultural
practices databases and USEtox model. International Journal of Life
Cycle Assessment, 16, 841–847. ht tps://doi.org/10.1007/s1136
7-0 11- 0 32 1-7
Booth, B.D. and Swanton, C.J. (20 02) Assembly theory applied to weed
communities. Weed Scinece, 50, 2–13.
Borza, J.K., Westerman, P.R. and Liebman, M. (2007) Comparing esti-
mates of seed viability in three foxtail (Setaria) species using the im-
bibed seed crush test with and without additional tetrazolium testing.
Weed Technology, 21, 518–522. https://doi.org/10.1614/WT-06-110
Broussard, W.P. and Turner, R .E. (2009) A century of changing
land-use and water-quality relationships in the continent al U.S.
Frontiers in Ecology and the Enviro nment, 7, 302–307. https://doi.
org/10.1890/080085
Broussard, W.P., Turner, R.E. and Westra, J.V. (2012) Do federal farm
policies influence surface water qualit y? Agriculture, Ecosystems
and Environment, 158, 103–109. https://doi.org /10.1016/j.
agee.2012.05.022
Cardina, J., Regnier, E. and Harrison, K. (1991) Long-term tillage effects
on seed banks in three Ohio soils. Weed Science, 39, 18 6–194. ht t ps ://
doi.or g/10 .1017/S0 043 17450 0 071459
Curran, M. A. (2008) Life-cycle assessment. In: Jorgensen, S.E. and Fath,
B.D. (Eds.) Encyclopedia of ecology. Oxford, U.K: Elsevier Science, pp.
2168–2174.
Davis, A .S., Hill, J.D., Chase, C.A ., Johanns, A.M. and Liebman, M. (2012)
Increasing cropping system diversity balances productivity, profit-
ability and environmental health. PLoS One, 7(10), e47149. https://
doi.org/10.1371/journ al.pone.0047149
Deytieux, V., Nemecek, T., Freiermuth Knuchel, R., Gaillard, G. and
Munier-Jolain, N.M. (2012) Is integrated weed management efficient
for reducing environmental impacts of cropping systems? A case
study based on life cycle assessment. Europ ean Jour nal of Agronomy,
36, 55–65. https://doi.org/10.1016/j.eja.2011.08.0 04
Doucet, C., Weaver, S.E., Hamill, A.S. and Zhang, J. (1999) Separating the
effects of crop rotation from weed management on weed density
and diver sity. Weed Science, 47, 729–735. https://doi.org/10.1017/
S0043 17450 0091402
Foley, J. (2011) Can we feed the world and save the planet? Scientific
American, 305(5), 60–65. https://doi.org/10.1038/scien tific ameri
can11 11-6 0
Fried, G., Nor ton, L. R. and Reboud, X. (2008) Environmental and man-
agement factors determining weed species composition and diver-
sity in France. Agriculture, Ecosystems and Environment, 128, 68–76.
https://doi.org/10.1016/j.agee.2008.05.003
Gaba, S., Fried, G., Kazakou, E., Chauvel, B. and Navas, M.L. (2014)
Agroecologic al weed control using a functional approach: A review
of cropping systems diversity. Agronomy for Sustainable Development,
34, 103–119. https://doi.org/10.1007/s1359 3- 013-0166-5
Gassman, P.W., Reyes, M.R ., Green, C.H. and Arnold, J.G. (2007) The soil
and water assessment tool: Historical development, applications,
and future research directions. Transactio ns of the American So ciety
of Agricultural an d Biological Engin eers, 50, 1211–1250. https://doi.
org/10.13031/ 2013.236 37
Goebes, M.D., Strader, R. and Davidson, C. (20 03) An ammonia emission
inventory for fer tilizer application in the United States. Atmospheric
Environment, 37, 2539–2550. https://doi.org/10.1016/S1352
- 2 3 1 0 ( 0 3 ) 0 0 1 2 9 - 8
Goodkind, A.L., Tessum, C.W., Coggins, J.S., Hill, J.D. and Marshall, J.D.
(2019) Fine-scale damage estimates of particulate matter air pollution
  
|
 13
LIEBMAN E t AL.
reveal opportunities for location-specific mitigation of emissions.
Proceedi ngs of the National Academy of Sciences, 116, 8775–8780.
https://doi.org/10.1073/pnas.18161 02116
Gross, K.L. (1990) A comparison of methods for estimating seed numbers
in the soil. Journal of Ecology, 78, 1079–1093. https://www.jstor.org/
stabl e/2260953
Hatfield, J.L., McMullen, L.D. and Jones, C.S. (2009) Nitrate-nitrogen
patterns in the Raccoon River Basin related to agricultural prac-
tices. Journal of Soi l and Water Conservation, 64, 190–199. https://doi.
org/10.2489/jswc.64.3.190
Heathcote, A.J., Filstrup, C.T. and Downing, J.A . (2013) Watershed sed-
iment losses to lakes accelerating despite agricultural soil conserva-
tion efforts. PLoS One, 8(1), e53554.
Henderson, A.D., Hauschild, M.Z., van de Meent, D., Huijbreg ts, M.A.J.,
Larsen, H.F., Margni, M. et al. (2011) USEtox fate and ecotoxicit y
factors for comparative assessment of toxic emissions in life cycle
analysis: Sensitivity to key chemical properties. International Journal
of Life Cycle Assessment, 16, 701–709. https://doi.org/10.1007/s1136
7-011-0294-6
Hill, J., Goodkind, A., Tessum, C., Thakur, S., Tilman, D., Polasky, S. e t al. (2019)
Air-quality-related health damages of maize. Nature Sustainability, 2,
397–403. https://doi.org/10.1038/s4189 3-019-0261-y
Hunt, N.D., Hill, J.D. and Liebman, M. (2017) Reducing freshwater toxic-
ity while maintaining weed control, profits, and productivity: Effects
of increased crop rotation diversity and reduced herbicide usage.
Environmental Science and Technology, 51, 1707–1717. htt ps://doi.
org/10.1021/acs.est.6b04086
Hunt, N.D., Hill, J.D. and Liebman, M. (2019) Cropping system diver-
sity effects on nutrient discharge, soil erosion, and agronomic per-
formance. Environmental Science and Technology, 53, 134 4–1352.
https://doi.org/10.1021/acs.est.8b02193
Hunt, N.D., Liebman, M., Thakur, S.K. and Hill, J.D. (2020) Fossil energy
use, climate change impacts, and air quality-related human health
damages of conventional and diversified cropping systems in Iowa,
USA. Environmental Science and Technology, 54(18), 11002–11014.
James, R., Smith, J.M., Eastridge, M.L., Tuovinen, O., Brown, L.C.,
Watson, M.E. et al. (2006) Ohio Livestock Manure Management Guide.
Columbus, OH, USA: Ohio State University Extension. Available at:
https://ocamm.osu.edu/sites/ ocamm/ files/ imce/Manur e/MM-Resou
rces/604_Manur eMgmt Guide_ 2006.pdf [Accessed 13 April 2020].
Karlen, D.L., Hurley, E.G., Andrews, S.S., Cambardella, C.A ., Meek, D.W.,
Duff y, M.D. et al. (2006) Crop rotation effects on soil quality at three
northern Corn/Soybean Belt locations. Agronomy Journal, 98, 484–
495. https://doi.org/10.2134/agron j2005.0098
Karlen, D.L ., Varvel, G.E., Bullock, D.G. and Cruse, R.M. (1994) Crop ro-
tations for the 21st centur y. Advances in Agronomy, 53, 1–45. ht tps://
doi.org/10.1016/S0065 -2113(08)60611 -2
Lazicki, P.A ., Liebman, M. and Wander, M.M. (2016) Root parame-
ters show how management alters resource distribution and soil
quality in conventional and low-input cropping systems in central
Iowa. PLoS One, 11(10), e0164209. https://doi.org/10.1371/journ
al.pone.0164209
Leandro, L., Eggenberger, S., Chen, C., Williams, J., Beattie, G.A. and
Liebman, M. (2018) Cropping system diversification reduces sever-
ity and incidence of soybean sudden death syndrome caused by
Fusarium virguliforme. Plant Disease, 102, 1748–1758. https://doi.
org/10.1094/PDIS-11-16-1660-RE
Lechenet, M., Bret agnolle, V., Bockstalller, C ., Boissinot, F., Petit, M.S.,
Petit, S. et al. (2014) Reconciling pesticide reduction with economic
and environmental sustainability in arable farming. PLoS One, 9(6),
e97922. https://doi.org/10.1371/journ al.pone.0097922
Leon, R.G. and Wright, D.L. (2018) Recurrent changes of weed seed
bank densit y and diversit y in crop-livestock systems. Agronomy
Journal, 110, 1068–1078. https://doi.org/10.2134/agron
j2017.11.0662
Leon, R.G., Wright, D.L. and Marois, J.J. (2015) Weed seed bank s are
more dynamic in a sod-based rotation, than in a conventional,
peanut-cotton rotation. Weed Science, 63, 877–887. https://doi.
org/10.1614/WS-D-15-00003.1
Liebman, M., Gibson, L.R ., Sundberg, D.N., Heggenstaller, A.H.,
Westerman, P.R., Chase, C.A. et al. (2008) Agronomic and economic
performance characteristics of conventional and low-external-input
cropping systems in the central Corn Belt. Agronomy Journal, 100,
600–610. https://doi.org/10.2134/agron j2007.0222
Liebman, M. and Nichols, V.A. (2020) Cropping system redesign for im-
proved weed management: A modeling approach illustrated with
giant ragweed (Ambrosia trifida). Agronomy, 10, 262. https://doi.
org/10.3390/agron omy10 020262
Maclaren, C ., Storkey, J., Menegat, A., Metcalfe, H. and Dehnen-
Schmut z, K. (2020) An ecologic al future for weed science to sus-
tain crop produc tion an d the environment. A review. A gronomy for
Sustainable Development, 40 , 24. https://doi.o rg/10.1007/s1359
3-020-00631 -6
Mahaut, M., Gaba, S. and Fried, G . (2019) A functional diversity
approach of crop sequences reveals that weed diversity and
abundance show different responses to environmental vari-
ability. Journal of Applied Ecology, 56, 1400–1409. https://doi.
org /10.1111/1365-26 64 .13389
Meiss, H., Médiène, S., Waldhardt, R., Caneill, J., Bretagnolle, V., Reboud,
X. et al. (2010) Perennial lucerne affects weed community trajecto-
ries in grain crop rotations. Weed Research, 50, 331–340. https://doi.
org/10.1111/j.1365-3180.2010.00784.x
Meiss, H., Médiène, S., Waldhardt, R., Caneill, J. and Munier-Jolain, N.
(2010) Contrasting weed species composition in perennial alfalfas
and six annual crops: Implications for integrated weed management.
Agronomy for Sustainable Development, 30, 657–666. https://doi.
org/10.1051/ag ro/2009043
Mohler, C.L . (2001) Weed evolution and community structure. In:
Liebman, M., Mohler, C.L. and Staver, C.P.(Eds.) Ecological manage-
ment of agricultural weeds. Cambridge, U.K: Cambridge Universit y
Press, pp. 444–493.
Murphy, S.D., Clements, D.R., Belaoussoff, S., Kevan, P.G. and Swanton,
C.J. (2006) Promotion of weed species diversity and reduc tion of
weed seedbanks with conservation tillage and crop rotation. Weed
Science, 54, 69–77. https://doi.org/10.1614/WS-04-125R1.1
O'Rourke, M.E., Liebman, M . and Rice, M.E. (2008) Ground beetle
(Coleoptera: Carabidae) assemblages in conventional and diversified
crop rotation sys tems. Environmental Entomology, 37, 121–130.
Payne, R.W.(2015) The design and analysis of long-term rotation exper-
iments. Agronomy Journal, 107, 772–785. https://doi.org/10.2134/
agron j2012.0411
Poffenbarger, H., Art z, G., Dahlke, G ., Edwards, W., Hanna, M., Russell,
J. et al. (2017) An economic analysis of integrated crop-livestock
systems in Iowa, U.S. A. Agricultural Sys tems, 157, 51–69. https://doi.
org/10.1016/j.agsy.2017.07.001
Poore, J. and Nemecek, T. (2018) Reducing food’s environmental impact s
through producers and consumers. Science, 360, 987–992. https://
doi.org/10.1126/scien ce.aaq0216
Reinhardt, T. and Leon, R.G. (2018) Extractable and germinable seedbank
methods provide different quantifications of weed communities.
Weed Science, 66, 715–720. https://doi.org/10.1017/wsc.2018.56
Rosenbaum, R.K., Bachmann, T.M., Gold, L.S., Huijbregts, M.A.J.,
Jolliet, O., Juraske, R. et al. (2008) USEtox–the UNEP-SETAC toxic-
ity model: Recommended characterization factors for human tox-
icity and freshwater ecotoxicity in life cycle impac t assessment .
International Journal of Life Cycle Assessment, 13, 532–546. https://
doi.org/10.1007/s1136 7-008-0038-4
Smith, R.G. and Gross, K.L. (2006) Rapid change in the germinable frac-
tion of the weed seed bank in crop rotations. Weed Science, 54,
1094–1110. ht tp s://doi.o rg /10. 23 07/4539511
14 
|
   LIEBMAN Et AL.
Smith, R.G., Mortensen, D.A. and Ryan, M.R. (2009) A new hypothesis
for the functional role of diversity in mediating resource pools and
weed–crop competition in agroecosystems. Weed Research, 50, 37–
48. https://doi.org/10.1111/j.1365-3180.2009.00745.x
Storkey, J. and Neve, P. (2018) What good is weed diversity? Weed
Research, 58, 239–243. https://doi.org/10.1111/wre.12310
Stowell, R. and Koelsch, R. (20 09) Ammonia emissions estimator. Lincoln,
NE, USA: University of Nebraska. Available at: https://water.unl.
edu/docum ents/Ammon ia%20Emi ssion s%20Est imato r%20-%20Dai
ly%20Ver sionV 03.pdf [Accessed 13 April 2020].
Sulc, R.M. and Tracy, B.F. (2007) Integrated crop–livestock systems in
the U.S. Corn Belt. Agronomy Journal, 99, 335–345. https://doi.
org/10.2134/agron j2006.0086
Swanton, C .J. and Murphy, S.D. (1996) Weed science beyond the weeds:
The role of integrated weed management (IWM) in agroecosystem
health. Weed Science, 44, 437–445. https://doi.org/10.1017/S004 3
17450 0 094145
Teasda le, J.R. (2018) The use of rotations and cover crops to manage weeds.
In: Zimdahl, R.L. (Ed.) Integrated weed management for sustainable agricul-
ture. Cambridge, U.K: Burleigh Dodds Science Publishing, pp. 227–260.
United States Environmental Protection Agency (2010) Valuing mortality
risk reduc tions for environmental policy: a white paper. Paper number
EE-0563. Washington, DC: U.S.E.P.A. Available at: https://www.epa.
gov/envir onmen tal-econo mics/valui ng-morta lity-risk-reduc tions
-envir onmen tal-polic y-white -paper -2010 [Accessed 1 April 2020].
United States Environmental Protection Agency (2017) National emis-
sions inventor y. Washington, DC: U.S.E.P.A . Available at: https://
www.epa.gov/air-emiss ions-inven torie s/natio nal-emiss ions-inven
tory-nei [Accessed 13 April 2020].
Weisberger, D.A ., Nichols, V.A . and Liebman, M . (2019) Does diversify-
ing crop rotations suppress weeds? A meta-analysis. PLoS On e, 14(7),
e0219847. https://doi.org/10.1371/journ al.pone.0219847
Wiles, L. J., Barlin, D.H., Schweitzer, E.E., Duke, H.R. and Whitt, D.E.
(1996) A new soil sampler and elutriator for collecting and extr act-
ing weed seeds from soil. Weed Technology, 10, 35–41. https://doi.
org/10.1017/S0890 037X0 004567X
Winchell, M., Srinivasan, R., LDi Luzio, M. and Arnold, J.G. (2013)
ArcSWAT User's Guide for SWAT2012. Temple, TX, USA: Blackland
Research Center, AgriLife Research.
How to cite this article: Liebman M, Nguyen HTX,
Woods MM, Hunt ND, Hill JD. Weed seedbank diversity and
sustainability indicators for simple and more diverse cropping
systems. Weed Res. 2021;00:1–14. https://doi.or g/10.1111/
wre.12466
... This is achieved by rotating crops within a field over time . There is evidence that increasing weed diversity, e.g., through diverse cropping (Hofmeijer et al. 2021), reduces yield losses (Adeux et al. 2019;Liebman et al. 2021), enhances fungal diversity (Triolet et al. 2022), and potentially enhances weed seed predation by insects. ...
Article
Full-text available
To attain food security, we must minimize crop losses caused by weed growth, animal herbivores, and pathogens (or “pests”). Today, crop production depends heavily on the use of chemical pesticides (or “pesticides”) to protect the crops. However, pesticides are phased out as they lose efficiency due to pest resistance, and few new pesticides are appearing on the market. In addition, policies and national action programs are implemented with the aim of reducing pesticide risks. We must redesign our cropping systems to successfully protect our crops against pests using fewer or no pesticides. In this review, I focus on the principles for redesigning the crop ecosystem. Ecological redesign aims to enhance ecological functions in order to regulate pest populations and diminish crop losses. Exploring ecology and ecosystems plays an important role in this transition. Guiding principles for redesigning the cropping system can be drawn from understanding its ecology. Ecosystem and community ecologists have identified four principal ecological characteristics that enhance the biotic regulation of ecological processes across ecosystems: (i) advanced ecosystem succession through introducing and conserving perennial crops and landscape habitats; (ii) reduced disturbance frequency and intensity; (iii) an increase in both managed and wild functional biological diversity, above and below ground; and (iv) matched spatial extent of land use (e.g., crop field size) with that of ecological processes (e.g., dispersal capacity of predators). I review the practices that link these ecosystem characteristics to crop protection in grain commodity cropping in both the crop field and the agricultural landscape. The review brings forth how basic understandings drawn from ecosystem and community ecology can guide agricultural research in the redesign of cropping systems, ensuring that technologies, breeding, innovation, and policy are adapted to and support the reshaped crop ecosystem.
... In a long-term rotation study in Iowa, net returns were used to assess economic performance at the rotation level by calculating gross returns and determining production costs. [19][20][21] Since each metric provides only a partial assessment of a given system, 18 different metrics reveal different trade-offs across cropping systems. For example, Snapp et al. 22 showed that more diverse rotations reduced grain yields but increased grain quality. ...
... Teff is also cheaper and less laborious to establish in the field than installing, removing, and storing landscape fabric (Nelson et al. 2023). When compared with the bare ground treatment, mowed teff yield more marketable 'Athena' muskmelon (Table 8) and likely contributed to the suppression of the weed seed bank (Liebman et al. 2021;Nichols et al. 2020). Despite the potential advantages of teff for weed control, it requires consistent moisture for germination and emergence (Mphande, unpublished data), which may pose a challenge during dryer postseeding periods for growers lacking irrigation equipment. ...
Article
Full-text available
Bacterial wilt of cucurbits, caused by Erwinia tracheiphila, is spread by spotted ( Diabrotica undeimpunctata howardi ) and striped ( Acalymma vittatum ) cucumber beetles and results in major losses for US cucurbit (Cucurbitaceae spp.) growers. Organic growers of muskmelon ( Cucumis melo ) lack reliable control measures against bacterial wilt. During previous field trials in Iowa, USA, a system called mesotunnels, which are 3.5-ft-tall barriers covered with a nylon mesh insect netting, resulted in a higher marketable yield of organic ‘Athena’ muskmelon than low tunnels or noncovered plots. However, satisfactory pollination and weed control are challenging in mesotunnels because the netting covers the crop for most or all of the growing season, and economic feasibility of these systems has not been determined. Consequently, two field trials conducted in Iowa from 2020 to 2022 evaluated strategies to ensure pollination under mesotunnels in commercial-scale plots, assess effectiveness of teff ( Eragrostis tef ) as a living mulch for weed control in mesotunnel systems, and compare the profitability of the treatment options for organic ‘Athena’ muskmelon. The treatments used during the pollination trial were as follows: full season, in which mesotunnels remained sealed all season and bumble bees ( Bombus impatiens ) were added at the start of bloom for pollination; open ends, wherein both ends of the tunnels were opened at the start of bloom then reclosed 2 weeks later; and on-off-on, in which nets were removed at the start of bloom and then reinstalled 2 weeks later. The full-season treatment had significantly higher marketable yield than the other treatments in two of three trial years. Plants with the full season and open ends treatments had a bacterial wilt incidence <2.5% across all three years and similar numbers of cucumber beetles, whereas plants with the on-off-on treatment had an average bacterial wilt incidence of 11.0% and significantly more cucumber beetles. The open ends treatment had fewer bee visits to ‘Athena’ muskmelon flowers than the other treatments. In the 2-year (2021–22) weed management trial, treatments applied to the furrow between plastic-mulched rows were as follows: landscape fabric; teff seeded at 4 lb/acre and mowed 3 weeks after seeding; teff seeded at 4 lb/acre and not mowed; a control with bare ground where weeds were mowed 3 weeks after transplanting; and a bare ground control with no mowing. The landscape fabric and mowed teff treatments had statistically similar marketable yield, and mowing appeared to minimize yield losses compared with nonmowed treatments. The landscape fabric had no weeds, followed by mowed teff, mowed bare ground, and nonmowed teff. Nonmowed bare ground had the highest weed biomass. The partial budget and cost-efficiency ratio analysis indicated that the full-season treatment was the most cost-efficient pollination option for mesotunnel systems. An economic analysis of the weed management strategies showed that using teff as a living mulch in the furrows between organic ‘Athena’ muskmelon rows, coupled with timely mowing to suppress its growth, can generate revenue comparable to that of landscape fabric. Our findings suggest that organic ‘Athena’ muskmelon growers in Iowa may gain the greatest yield and soil quality benefits when mesotunnels are kept closed for the entire season, bumble bees are used for pollination, and teff (mowed 3 weeks after seeding) is used to control weeds in the furrows. Further trials integrating these pollination and weed management strategies would help validate a comprehensive approach to organic ‘Athena’ muskmelon production under mesotunnels.
... intensification process already started), then we should address for a reinforced and enlarged ecologically based weed management (EbWM) definition, backed up by complementary major related disciplines. It must be pointed out that ecology provides the theoretical basis for weed science, much as physics provides a theoretical basis for engineering and biology the theoretical basis for medicine (Liebman et al. 2001). Although much research has been focused on the ecological relationships of weeds within agroecosystems in recent years, substantial gaps in knowledge relevant to weed management still exist, since weed management strategies must include multiple points of intervention in their life cycles (Liebman and Gallandt 1997). ...
Chapter
Managing food production systems on a sustainable basis is one of the most critical challenges for the future of humanity. There is urgent need to create and use ecological knowledge translated into practical strategies of weed management. We then address for a reinforced and enlarged ecologically based weed management (EbWM) backed up by related disciplines and approaches: (i) systems approach; (ii) increased biodiversity in the system; (iii) inclusion of the spatial scale: from the field to the landscape; (iv) significant improvement in the objectives of crop breeding programs; (v) use of herbicides only based on dose-response technology; (vi) calculation of pesticide load in each field.
... Lastly, Storkey and Neve (2018) suggest that an assortment of seeds in the weed seed bank is pointing to the overarching sustainability of the cropping system. Liebman et al. (2021) tested this hypothesis and concluded that weed seed bank variety may undoubtedly be a worthwhile agro-ecosystem sustainability yardstick. However, weed seedbank density will affect crop yields and should be taken into consideration. ...
... Lastly, Storkey and Neve (2018) suggest that an assortment of seeds in the weed seed bank is pointing to the overarching sustainability of the cropping system. Liebman et al. (2021) tested this hypothesis and concluded that weed seed bank variety may undoubtedly be a worthwhile agro-ecosystem sustainability yardstick. However, weed seedbank density will affect crop yields and should be taken into consideration. ...
Article
Full-text available
Faced with the biodiversity extinction crisis and climate change, alternative approaches to food production are urgently needed. Decades of chemical-based weed control have resulted in a dramatic decline in weed diversity, with negative repercussions for agroecosystem biodiversity. The simplification of cropping systems and the evolution of herbicide resistance have led to the dominance of a small number of competitive weed species, calling for a more sustainable approach that considers not only weed abundance but also community diversity and composition. Agroecological weed management involves harnessing ecological processes to minimize the negative impacts of weeds on productivity and maximize biodiversity. However, the current research effort on agroecological weed management is largely rooted in agronomy and field-scale farming practices. In contrast, the contributions of landscape-scale interventions on agroecological weed management are largely unexplored (e.g., interventions to promote pollinators and natural enemies or carbon sequestration). Here, we review current knowledge of landscape effects on weed community properties (abundance, diversity, and composition) and seed predation (a key factor in agroecological weed management). Furthermore, we discuss the ecological processes underlying landscape effects, their interaction with in-field approaches, and the implications of landscape-scale change for agroecological weed management. Notably, we found that (1) landscape context rarely affects total weed abundance; (2) configurational more than compositional heterogeneity of landscapes is associated with higher alpha, beta, and gamma weed diversity; (3) evidence for landscape effects on weed seed predation is currently limited; and (4) plant spillover from neighboring habitats is the most common interpretation of landscape effects on weed community properties, whereas many other ecological processes are overlooked. Strikingly, the drivers of weed community properties and biological regulation at the landscape scale remain poorly understood. We recommend addressing these issues to better integrate agroecological weed management into landscape-scale management, which could inform the movement towards managing farms at wider spatiotemporal scales than single fields in a single season.
Article
Full-text available
No-till planting organic soybean [ Glycine max (L.) Merr.] into rolled-crimped cereal rye ( Secale cereale L.) can have several advantages over traditional tillage-based organic production. However, suboptimal cereal rye growth in fields with large populations of weeds may result in reduced weed suppression, weed-crop competition, and soybean yield loss. Ecological weed management theory suggests that integrating multiple management practices that may be weakly effective on their own can collectively provide high levels of weed suppression. In 2021 and 2022, a field experiment was conducted in central New York to evaluate the performance of three weed management tactics implemented alone and in combination in organic no-till soybean planted into both cereal rye mulch and no mulch: 1) increasing crop seeding rate, 2) inter-row mowing, and 3) weed electrocution. A nontreated control treatment that did not receive any weed management and a weed free control treatment were also included. Cereal rye was absent from two of the five fields where the experiment was repeated; however, the presence of cereal rye did not differentially affect results and thus data were pooled across fields. All treatments that included inter-row mowing reduced weed biomass by at least 60% and increased soybean yield by 14% compared to the nontreated control. The use of a high seeding rate or weed electrocution, alone or in combination, did not improve weed suppression or soybean yield relative to the nontreated control. Soybean yield across all treatments was at least 22% lower than the weed free control plot. Future research should explore the effects of the tactics tested on weed population and community dynamics over an extended period. Indirect effects from inter-row mowing and weed electrocution should also be studied, such as the potential for improved harvestability, decreased weed seed production and viability, and the impacts on soil organisms and agroecosystem biodiversity.
Article
Full-text available
Sustainable strategies for managing weeds are critical to meeting agriculture’s potential to feed the world’s population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weeds at the agroecosystem level that, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management.
Article
Full-text available
Weeds present important challenges to both conventional farmers who rely on herbicides and organic farmers who rely on cultivation. Data from field experiments indicate that diversifying crop sequences with additional species can improve weed suppression when either herbicides or cultivation serve as primary control tactics. Here, we report the results of modeling analyses that investigated how cropping system diversification would affect the population dynamics of giant ragweed (Ambrosia trifida L.), an annual dicotyledonous species that is problematic in the central U.S. for both conventional and organic farmers. We found that to prevent an increase in giant ragweed density, the minimum control efficacy needed from herbicides or cultivation used in corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) would be 99.0% in a 2-year corn–soybean system, but 91.4% in a 5-year corn–soybean–rye (Secale cereale L.)–alfalfa (Medicago sativa L.) system. Thus, the diversified rotation would be better buffered against less-than-perfect weed control during corn and soybean phases. Further modeling analyses indicated that the weed suppression effect associated with greater rotation length was attributable not only to increased crop species richness but also to greater temporal variation in planting dates. A planting interval variation index (PIVI), calculated as the coefficient of variation in months between planting activities, was strongly associated with the weed suppressive ability of the rotations we modeled and may be a useful metric for designing other cropping systems. Overall, our results indicate that diversified rotation systems that include both annual and perennial crops are likely to be valuable for managing problematic weed species.
Article
Full-text available
Over the past half-century, crop rotations have become increasingly simplified, with whole regions producing only one or two crops in succession. Simplification is problematic from a weed management perspective, because it results in weeds’ repeated exposure to the same set of ecological and agronomic conditions. This can exacerbate weed infestations and promote the evolution of herbicide resistance. Diversifying crop rotations through addition of crop species and their associated managements may suppress weeds and reduce selection pressure for herbicide resistance by altering stress and mortality factors affecting weed dynamics. Here we report the results of a meta-analysis using 298 paired observations from 54 studies across six continents to compare weed responses due to simple and more diverse crop rotations. We found diversifying from simple rotations reduced weed density (49%), but did not have a significant effect on weed biomass. We investigated the effect of management practices, environmental factors, and rotation design on this effect. Diversification that increased the variance around crop planting dates was more effective in suppressing weeds than increasing crop species richness alone. Increasing rotational diversity reduced weed density more under zero-tillage conditions (65%) than tilled conditions (41%), and did so regardless of environmental context and auxiliary herbicide use. Our findings highlight the value of diversifying crop rotations to control weed populations, and support its efficacy under varied environmental conditions and management scenarios.
Article
Full-text available
Fine particulate matter (PM 2.5 ) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM 2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM 2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM 2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.
Article
Full-text available
Agriculture is essential for feeding the large and growing world population, but it can also generate pollution that harms ecosystems and human health. Here, we explore the human health effects of air pollution caused by the production of maize—a key agricultural crop that is used for animal feed, ethanol biofuel and human consumption. We use county-level data on agricultural practices and productivity to develop a spatially explicit life-cycle-emissions inventory for maize. From this inventory, we estimate health damages, accounting for atmospheric pollution transport and chemistry, and human exposure to pollution at high spatial resolution. We show that reduced air quality resulting from maize production is associated with 4,300 premature deaths annually in the United States, with estimated damages in monetary terms of US39billion(range:US39 billion (range: US14–64 billion). Increased concentrations of fine particulate matter (PM2.5) are driven by emissions of ammonia—a PM2.5 precursor—that result from nitrogen fertilizer use. Average health damages from reduced air quality are equivalent to US121t1ofharvestedmaizegrain,whichis62121 t⁻¹ of harvested maize grain, which is 62% of the US195 t⁻¹ decadal average maize grain market price. We also estimate life-cycle greenhouse gas emissions of maize production, finding total climate change damages of US4.9billion(range:US4.9 billion (range: US1.5–7.5 billion), or US$15 t⁻¹ of maize. Our results suggest potential benefits from strategic interventions in maize production, including changing the fertilizer type and application method, improving nitrogen use efficiency, switching to crops requiring less fertilizer, and geographically reallocating production.
Article
Full-text available
Combining several crop species and associated agricultural practices in a crop sequence has the potential to control weed abundance while promoting weed diversity in arable fields. However, how the variability in environmental conditions that arise from crop sequences affects weed diversity and abundance remains poorly understood, with most studies to‐date simply opposing weed communities in monoculture and in crop rotation. Here, we describe crop sequences along gradients of disturbance and resource variability using a crop functional trait and associated agricultural practices. We tested the hypothesis that in disturbances reduces weed abundance, whereas variability in resources promotes weed diversity. We used functional Hill's numbers to compute crop sequence functional diversity based on sowing date, herbicide spectrum and crop height—these are the respective proxies of disturbance timings, disturbance types and light availability. Using a large‐scale weed monitoring database, we assessed crop sequence diversity for 1,045 crop sequences of five consecutive cropping seasons. We computed weed richness and abundance at pluri‐annual (pool of weeds observed across five cropping seasons) and annual (pool of weeds observed during a winter cereal cropping season preceded by five cropping seasons) scales. We also accounted for herbicide and tillage intensities to test whether management intensity affects the response of weed diversity and abundance to crop sequence diversity. At the pluri‐annual scale, weed richness increased with the diversity of crop height and sowing date, whereas weed abundance decreased with sowing date diversity. Annual weed richness decreased with sowing date diversity, whereas annual weed abundance poorly relied on crop sequence diversity. Synthesis and applications. This study establishes a scientific basis for designing crop sequences according to specific weed management goals. We show that farmers may enhance arable weed diversity on a pluri‐annual scale by sequentially sowing crop species that differ in their competitive ability and sowing date. They may also achieve a better control of weed abundance by increasing the diversity of crop sowing dates across the crop sequence.
Chapter
Insect pests are the major biotic fauna that reduces the production of different crops. On average, pests account for 20-40% of yield losses worldwide. Farmers rely heavily on chemical control, generally practiced for higher gains and management of insect-pests, but improperly by its injudicious application. The sole reliance on chemical pesticides has led to the problem of 3 R’s viz., Resistance, Resurgence and Residues. Even with chemical methods, the pest could not be managed, and now the cost of input exceeds the yield. When the idea of the "green revolution" emerged, the assured irrigation regions were discovered and solutions were found to boost productivity there. Water plays an important role to reduce or increase the pest population. Heavy rainfall with high intensity wash out the pest population from crop during rainy season. For some pests, water stress play important role for the management of the insect pest. Therefore, the paper is aimed to combine all available techniques, whether they were for a specific pest or all pests of a crop.
Chapter
Concerns over environmental and human health impacts of conventional weed management practices, herbicide resistance in weeds, and rising costs of crop production and protection have led agricultural producers and scientists in many countries to seek strategies that take greater advantage of ecological processes and thereby allow a reduction in herbicide use. This book provides principles and practices for ecologically based weed management in a wide range of temperate and tropical farming systems. After examining weed life histories and processes determining the assembly of weed communities, the authors describe how tillage and cultivation practices, manipulations of soil conditions, competitive cultivars, crop diversification, grazing livestock, arthropod and microbial biocontrol agents, and other factors can be used to reduce weed germination, growth, competitive ability, reproduction and dispersal. Special attention is given to the evolutionary challenges that weeds pose and the roles that farmers can play in the development of new weed-management strategies.
Article
Cropping system diversification can reduce the negative environmental impacts of agricultural production, including soil erosion and nutrient discharge. Less is known about how diversification affects energy use, climate change, and air quality, when considering farm operations and supply-chain activities. We conducted a life cycle study using measurements from a nine-year Iowa field experiment to estimate fossil energy use, greenhouse gas (GHG) emissions, PM2.5-related emissions, human health impacts, and other agronomic and economic metrics of contrasting crop rotation systems and herbicide regimes. Rotation systems comprised a 2-year corn-soybean system, a 3-year corn-soybean-oat/clover system, and a 4-year corn-soybean-oat/alfalfa-alfalfa system. Each was managed with conventional and low-herbicide treatments. GHG and PM2.5-related emissions damages were 42%–57% lower in the 3-year and 4-year rotations than the 2-year rotation. Diversification reduced GHG emissions by 56%–65% and lowered fossil energy consumption by 58%–65%. Herbicide treatment had no significant impact on environmental outcomes, while corn and soybean yields and whole-rotation economic returns improved significantly under diversification. Results suggest that diversification via shifting from conventional corn-soybean rotations to longer rotations with small grain and forage crops substantially reduced fossil energy use, and GHG emissions, and air quality damages, but did not compromise economic or agronomic performance.
Article
Nutrient, herbicide, and sediment loading from agricultural fields cause environmental and economic damage. Nutrient leaching and runoff pollution can lead to eutrophication and impaired drinking water resources, while soil erosion reduces water quality and agronomic productivity. Increased cropping system diversification has been proposed to address these problems. We used the ArcSWAT model and long-term Iowa field experimental measurements to estimate eutrophication and erosion impacts of three crop rotation systems under two weed management regimes. Rotations were comprised of 2-year corn-soybean, 3-year corn-soybean-oat/clover, and 4-year corn-soybean-oat/alfalfa-alfalfa systems. All were managed with conventional or low herbicide applications. Total N and P runoff losses were up to 39% and 30% lower, respectively, in the more diverse systems than the 2-year corn-soybean system, but NO3--N leaching losses were unaffected by cropping system. Diversification reduced erosion losses up to 60%. The 3- and 4-year systems maintained or increased crop yields and net returns relative to the 2-year conventional system. Reductions in herbicide use intensity generally did not affect nutrient and sediment losses, nor crop yields and profitability. These results indicate that diversifying the corn-soybean rotation that dominates the central U.S. could reduce water nutrient contamination and soil erosion, while maintaining farm productivity and profitability.