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USDA’s Long-Term Agroecosystem Research (LTAR) network is composed of 18 locations distributed across the contiguous United States working together to integrate national and local agricultural priorities and advance the sustainable intensification of US agriculture. We explore here the concept of sustainable intensification as a framework for defining strategies to enhance production, environmental, and rural prosperity outcomes from agricultural systems. We also elucidate the diversity of factors that have shaped the past and present conditions of cropland, rangeland, and pastureland agroecosystems represented by the LTAR network and identify priorities for research in the areas of production, resource conservation and environmental quality, and rural prosperity. Ultimately, integrated long-term research on sustainable intensification at the national scale is critical to developing practices and programs that can anticipate and address challenges before they become crises.
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Agriculture in the United States must respond to escalating
demands for productivity and eciency, as well as pressures to
improve its stewardship of natural resources. Growing global
population and changing diets, combined with a greater societal
awareness of agriculture’s role in delivering ecosystem services
beyond food, feed, ber, and energy production, require a
comprehensive perspective on where and how US agriculture
can be sustainably intensied, that is, made more productive
without exacerbating local and o-site environmental concerns.
The USDA’s Long-Term Agroecosystem Research (LTAR) network
is composed of 18 locations distributed across the contiguous
United States working together to integrate national and local
agricultural priorities and advance the sustainable intensication
of US agriculture. We explore here the concept of sustainable
intensication as a framework for dening strategies to enhance
production, environmental, and rural prosperity outcomes from
agricultural systems. We also elucidate the diversity of factors
that have shaped the past and present conditions of cropland,
rangeland, and pastureland agroecosystems represented by the
LTAR network and identify priorities for research in the areas of
production, resource conservation and environmental quality,
and rural prosperity. Ultimately, integrated long-term research
on sustainable intensication at the national scale is critical to
developing practices and programs that can anticipate and
address challenges before they become crises.
Advancing the Sustainability of US Agriculture through
Long-Term Research
P. J. A. Kleinman,* S. Spiegal, J. R. Rigby, S. C. Goslee, J. M. Baker, B. T. Bestelmeyer, R. K. Boughton, R. B. Bryant,
M. A. Cavigelli, J. D. Derner, E. W. Duncan, D. C. Goodrich, D. R. Huggins, K. W. King, M. A. Liebig, M. A. Locke,
S. B. Mirsky, G. E. Moglen, T. B. Moorman, F. B. Pierson, G. P. Robertson, E. J. Sadler, J. S. Shortle, J. L. Steiner,
T. C. Strickland, H. M. Swain, T. Tsegaye, M. R. Williams, and C. L. Walthall
G  for food, feed, ber, and energy is
increasing rapidly as the world’s population approaches
9 billion people and lifestyles shi with demographic
transitions spurred by economic development (von Braun,
2007). Agricultural producers in the United States now face
unprecedented economic opportunity from new markets,
but this comes amid increasing pressures to conserve natural
resources, support rural economies, and enhance ecosystem ser-
vices whose relationships to agriculture are not yet fully under-
stood (Gold, 1999; Millennium Ecosystem Assessment, 2005;
Woteki, 2012; Robertson et al., 2014). ese opportunities and
pressures must be treated as a single, multifaceted challenge—to
advance agriculture that is economically, socially, and environ-
mentally sustainable.
Sustainable agriculture must balance short-term management
decisions with long-term planning so that production can adapt
to changing pressures and demands and recover from periodic
crises (United Nations, 1987; Ruttan, 1999). When applied to
farming systems, sustainability implies nancial stability, resil-
ience to market and environmental shocks, resource conserva-
tion, family and community sustenance, and consistency with
value systems (National Research Council, 2010). When applied
Abbreviations: LTAR, Long-Term Agroecosystem Research.
P.J.A. Kleinman, S.C. Goslee, R.B. Bryant, USDA–ARS Pasture Systems and Watershed
Management Research Unit, University Park, PA 16802; S. Spiegal and B.T.
Bestelmeyer, USDA–ARS Range Management Research Unit, Las Cruces, NM 88003;
J.R. Rigby and M.A. Locke, USDA–ARS National Sedimentation Lab., Oxford, MS
38655; J.M. Baker, USDA–ARS Soil and Water Management Research Unit, St. Paul,
MN 55108; R.K. Boughton, Univ. of Florida Range Cattle Research and Education
Center, Ona, FL 33865; M.A. Cavigelli and S.B. Mirsky, USDA–ARS Sustainable
Agricultural Systems Lab., Beltsville, MD 20705; J.D. Derner, USDA–ARS Rangeland
Resources and Systems Research Unit, Cheyenne, WY 82009; E.W. Duncan and K.W.
King, USDA–ARS Soil Drainage Research Unit in Columbus, OH 43210; D.C. Goodrich,
USDA–ARS Southwest Watershed Research Center, Tucson, AZ 85719; D.R. Huggins,
USDA–ARS Northwest Sustainable Agroecosystems Research Unit, Pullman, WA
99164; M.A. Liebig, USDA–ARS Northern Great Plains Research Lab., Mandan, ND
58554; G.E. Moglen, USDA–ARS Hydrology and Remote Sensing Lab., Beltsville, MD
20705; T.B. Moorman, USDA–ARS National Lab. for Agriculture and the Environment,
Ames, IA 50011; F.B. Pierson, USDA–ARS Northwest Watershed Research Center,
Boise, ID 83712; G.P. Rober tson, Dep. of Plant, Soil and Microbial Sciences at
Michigan State Univ., Hickory Corners, MI 49060; E.J. Sadler, USDA–ARS Cropping
Systems and Water Quality Research Unit in Columbia, MO 65211; J.S. Shortle, Penn
State Univ., State College, PA 16802; J.L. Steiner, USDA–ARS Grazinglands Research
Lab., El Reno, OK 73036; T.C. Strick land, USDA–ARS Southeast Watershed Research
Lab., Tifton, GA 31793; H.M. Swain, Archbold Biological Station, Venus, FL 33960; T.
Tsegaye and C.L. Walthall (retired), Natural Resources and Sustainable Agricultural
Systems, USDA–ARS, Beltsville, MD 20705; M.R. Williams, USDA–ARS National Soil
Erosion Research Lab., Lafayette, IN, 47907. USDA is an equal opportunity provider
and employer. Assigned to Technical Editor Rodney Venterea.
Copyright © American Society of Agronomy, Crop Science Society of America, and
Soil Science Society of America. 5585 Guilford Rd., Madison, WI 53711 USA.
All rights reserved.
J. Environ. Qual. 47:1412–1425 (2018)
This is an open access article distributed under the terms of the CC BY license
Received 2 May 2018.
Accepted 2 Sept. 2018.
*Corresponding author (
Journal of Environmental Quality ENVIRONMENTAL ISSUES
Core Ideas
• The LTAR network was established to enhance the sustainability
of US agriculture.
• The LTAR “common experiment” compares business as usual
with aspirational management.
• LTAR sites contribute research observations to the network’s
• LTAR network research will support sustainable intensication
Published November 1, 2018
Journal of Environmental Quality 1413
to agroecosystems, sustainability acknowledges management
impacts on biodiversity, biogeochemical processes, and socio-
economic dynamics that frequently manifest at scales beyond
the farm gate (for the purposes of this paper, farm refers to farms
and other agricultural enterprises, including ranches). For agri-
cultural industries, sustainability connotes brand and market
preservation, adaptation to consumer priorities, and regulatory
compliance. As dened by the US National Research Council
(2010), a sustainable US agriculture would
• satisfy human food, feed, and ber needs, and contribute to
biofuel needs,
• enhance environmental quality and the resource base,
• sustain the economic viability of agriculture, and
• enhance the quality of life for farmers, farm workers, and
society as a whole.
Agriculture in the United States is diverse, spanning gradi-
ents in scale, climate, physiography, ecology, economics, and
culture (Zhang et al., 2007). ese many dimensions confound
uniform approaches to achieving sustainable production sys-
tems. Complications extend from local constraints to systemic
factors that will not bend to simple solutions. Well-documented
changes in environmental conditions (e.g., climate change, soil
erosion, nutrient accumulation) present geographically uneven
pressures on agriculture by disrupting historical norms, from
lengthened growing seasons that also expand the ranges of pests
to greater frequency and severity of extreme weather events that
aect eld management in many ways (Walthall et al., 2012). At
the same time, farmers have little control over the price of their
output. Farm gate sales account for only 15% (varying from 8 to
54%, depending on product) of the price of food in the grocery
store (Schnepf, 2013). International markets inuence local pric-
ing: exports consume roughly 20% of US crop production. In
addition, the loss of farmland to other uses, especially peri-urban
development, remains a threat to production in some regions,
with nearly half of the value of national farm output located in
US counties under urban expansion (American Farmland Trust,
1994, 2015).
e combined demands for greater production and less envi-
ronmental impact require scalable strategies that more eciently
invest resources for food, feed, ber, and energy production.
Such strategies must also mitigate trade-os produced when
concurrently pursuing production and environmental objectives.
us, the Long-Term Agroecoystem Research (LTAR) network
was established to conduct systems-level research integrating
production, environmental, and rural prosperity objectives to
provide a vision for ensuring the long-term sustainability of US
agriculture. Here, we
• introduce the concept of sustainable intensication as a
means of dening strategies for enhancing production,
environmental, and rural prosperity outcomes from
agricultural systems;
• describe the LTAR network as a program for developing,
testing, and communicating technologies, practices, and
information facilitating the sustainable intensication of
US agriculture;
• elucidate the diversity of factors that have historically
inuenced the long-term sustainability of cropland,
rangeland, and pastureland agroecosystems in the United
States; and
• identify priorities for research aimed at the sustainable
intensication of US agriculture.
Sustainable Intensication as a Process
for Achieving a Sustainable Agriculture
In light of the increasing demand for protein-rich food and the
need to conserve natural resources for future generations, there
has been a call for sustainable intensication– increasing food
security while shrinking the environmental footprint of agri-
culture, two broad objectives that can oen be at odds (Garnett
et al., 2013). Sustainable intensication has evolved rapidly as
a concept, but, as with any overarching ambition, sustainable
intensication has spent its early existence in a theoretical realm
with limited application to real-world conditions (Petersen and
Snapp, 2015). Sustainable intensication has been applied to
many elements of agricultural production and consumption,
from production in elds and farms to processing, distribution,
markets, and waste recovery (Godfray and Garnett, 2014), and
is a useful concept for linking broad, societal demands to local
agricultural production systems, ideally enabling a diversity of
strategies to ensure that these local systems will be sustainable
over time and across multiple scales.
Early debate over sustainable intensication and a long his-
tory of research on sustainable agriculture highlights the need
for exibility in the application of sustainable intensication
to agricultural development (Godfray and Garnett, 2014). A
variety of tactics have been proposed: halting the expansion
of agriculture into sensitive or marginal ecosystems; closing
yield gaps on underperforming areas of production; increasing
eciencies in nutrient, water, and agrichemical use; reducing
post-harvest losses (Foley et al., 2011); and expanding the con-
sideration of non-commodity ecosystem services in decision
making (Millennium Ecosystem Assessment, 2005). ese
tactics have been tested in various settings, but their success as
part of large national or multinational campaigns to promote
sustainable agricultural systems remains open to assessment.
Not surprisingly, it has been argued that for sustainable inten-
sication strategies to be achievable and equitable, new sources
of revenue are needed beyond traditional income bases (Loos
et al., 2014).
Sustainable intensication clearly shows potential to achieve
national goals for agriculture. When applied to a nation as large
as the United States, sustainable intensication strategies that
simultaneously maximize yield and minimize environmental
impacts will need to vary strongly across the nation’s climatic,
edaphic, political and socioeconomic gradients (Garnett, 2013).
Underlying conditions vary considerably across the range of US
production systems, pointing to the need for regionally dened
objectives that meet local, regional, and national goals. While
these goals may change with time, in the United States they have
consistently fallen under the trifecta of (i) increasing produc-
tion to meet growing national ambitions for food, fuel, feed, and
ber; (ii) conserving the nation’s natural resources and protect-
ing its environment; and (iii) promoting the prosperity of rural
1414 Journal of Environmental Quality
The Long-Term Agroecosystem Research
In pursuit of sustainable US agriculture and in response to
calls by the scientic community for long-term investments in
sustainable agriculture research (Robertson et al., 2008), the
USDA launched the LTAR network (Walbridge and Shafer,
2011). e LTAR network is grounded in empirical experi-
mentation and coordinated observation that seeks to develop
a national roadmap for the sustainable intensication of agri-
cultural production in the face of a diverse range of agricul-
tural stressors and expectations. Starting with research on the
constraints to production, protability, and non-commodity
ecosystem services at eld, operation, and watershed scales, the
LTAR network is working to link locally dened advances in
agricultural production to broader supply chains, impacts, and
contexts. Anticipated products from LTAR include decision
support tools, technologies, and management practices that
can be directed toward the broader sustainable intensication
of US agriculture.
The LTAR network is currently represented by 18 loca-
tions across the contiguous United States (Fig. 1). Historical
experimentation and monitoring at LTAR locations aver-
ages 55 years, spanning 19 to more than 100 years (Table 1).
Network science is grounded in local, empirical research, with
a focus on connecting experimentation and monitoring to an
understanding of the state and potential of US agroecosys-
tems, recognizing that agriculture is also organized and influ-
enced by specific industries, markets, and policies (Spiegal
et al., 2018). The LTAR network’s agroecosystems, which
define the local conditions of inference, include a diversity
of annual row cropping systems and grazing lands, represen-
tative of roughly 49% of cereal production, 30% of forage
production, and 32% of livestock production in the United
States. As the USDA expands its investment in LTAR, new
locations are being established (e.g., a California site, which
is not represented here, was added to the network just prior
to publication) to include broader geographic coverage and
additional production systems. As LTAR network research
evolves, new partnerships are anticipated to ensure LTAR’s
relevance to US agriculture as a whole and agroecosystems in
particular (Walbridge and Shafer, 2011).
Operationally, the LTAR network is focused on topics
of cropland and grazing land sustainability with regional
or national consequence. At the core of LTAR is a common
experiment, which contrasts “business-as-usual” manage-
ment and “aspirational” management strategies that sustain-
ably intensify production (Spiegal et al., 2018). All sites seek
to test strategies that increase productivity and profitability
of agriculture while reducing environmental impacts, with
broader objectives refined locally to meet the realities and
needs of producers, ecosystems, and communities. Common
long-term measurements enable cross-site comparison, as
well as integration of findings at broader spatial and temporal
scales, supported by a suite of long-term databases for internal
and external use (Kaplan et al., 2017). Computational mod-
eling applied consistently to each network site (e.g., Arnold
et al., 1998; Rotz et al., 2015) will serve to extrapolate find-
ings and connect LTAR network hypotheses to sustainability
outcomes for the nation’s food, feed, fiber, and energy supply
chains (Macfadyen et al., 2015). Strong ties to federal and
state research, teaching, and extension programs across the
United States ensure that research data and inferences will be
disseminated and applied.
Fig. 1. The 18 LTAR network sites and the major agricultural commodities associated with their agroecological regions. Representation of agricul-
tural commodities for each region corresponds with Table 1. Gray areas represent estimated regional inference spaces of the LTAR sites.
Journal of Environmental Quality 1415
Factors Aecting the Sustainability of
Cropland Agroecosystems
Historical trends in US cropland agroecosystems highlight
the developments that have propelled US productivity to today’s
record high levels, but they also illustrate the constraints and pos-
sibilities provided by information, culture, policy, and markets.
e United States’ 160 million ha of croplands have long been a
foundation of the US economy, supporting its relationship with
the world through trade and humanitarian support and enabling
the growth of its urban populations. Since World War II, US
croplands have undergone profound change in management
intensity and productivity. Crop yields, a core measurement of
productivity, have increased roughly threefold since World War
II (USDA Economic Research Service, 2016a) (Fig. 2).
Advances in fertilizers, crop breeding, pest control, irrigation,
equipment, and drainage have all contributed to crop produc-
tion increases. Mechanization has enabled economies of scale
not possible under earlier agronomic practices (Tilman et al.,
2002), while simultaneously eliminating the need to devote sub-
stantial land area to the production of feed (e.g., oat, Avena sativa
L.) for dra animals. More recently, the precision farming tools
of the modern information era are extending trends in produc-
tivity displayed in Fig. 2 (Gebbers and Adamchuk, 2010), as well
as improving eciencies in production that allow yield goals to
be achieved with fewer inputs (Balafoutis et al., 2017). Further
growth in productivity requires strategies that seek to optimize
Table 1. General characteristics of LTAR network sites. Agricultural commodities listed for each region correspond with USDA National Agricultural
Statistics Service (2012) data for the counties overlapping ≥50% with each regional footprint (Fig. 1). The products listed reect both the region’s
largest contributions to the national yield and products under study by LTAR.
LTAR network site Year
Focal production
systems Major agricultural commodities† Cereal
crops Forages Cotton Livestock
and poultry
— % of national yield — % of national
Archbold Biol. Station/
University of Florida
1941 Rangeland, pastureland Beef cattle, citrus 0 0.5 0 0.6
Central Mississippi River
1971 Cropland, pastureland Beef cattle, swine, corn, soybeans,
wheat, forages
2.2 0.9 0 0.8
Central Plains
Experimental Range
1939 Cropland, rangeland Beef cattle, corn, wheat, forages 4 2.2 0 6.2
Cook Agronomy Farm 1998 Cropland, rangeland Dairy cattle, small grains (wheat,
barley), pulses, forages, oilseeds
1.7 1.8 0 1
Eastern Corn Belt 1974 Cropland, pastureland Dairy cattle, poultry, swine, corn,
soybeans, wheat, forages
4 0.7 0 1.7
Great Basin 1961 Pastureland, rangeland Beef cattle, dairy cattle, barley,
0.9 5.9 0 2.9
Gulf Atlantic Coastal
1965 Cropland, pastureland Beef cattle, poultry, corn, peanuts,
rye, vegetables, forages, cotton
0.2 0.2 9.2 0.4
Kellogg Biological
1987 Cropland, pastureland Dairy cattle, swine, corn, soybeans,
small grains (wheat, oats, rye),
3.6 1.4 0 1.8
Lower Chesapeake Bay 1910 Cropland, pastureland Dairy cattle, poultry, corn,
soybeans, small grains (wheat,
barley, rye), forages
1.2 1.3 0 2
Lower Mississippi River
1981 Cropland Catsh, poultry, corn, soybeans,
wheat, rice, sugar cane, cotton
3.2 0.7 20.6 0.7
Northern Plains 1912 Cropland, pastureland,
Beef cattle, sheep, corn, soybeans,
small grains (wheat, barley,
oats), forages, oilseeds
3.7 2.5 0 0.8
Platte River/High Plains
1912 Cropland, pastureland Beef cattle, swine, corn, soybeans,
wheat, forages
6.4 1.5 0 4
Southern Plains 1948 Cropland, pastureland Beef cattle, small grains (wheat),
forages, cotton
1.4 1.6 1.4 1.2
Texas Gulf 1937 Cropland, pastureland,
Beef cattle, poultry, corn, cotton,
small grains (wheat, oats),
0.5 1.5 1.1 0.4
Upper Chesapeake Bay 1968 Cropland, pastureland Beef cattle, dairy cattle, poultry,
corn, soybeans, small grains
(wheat, barley, oats, rye), forages
0.7 2.8 0 2.4
Upper Mississippi River
1992 Cropland, pastureland Beef cattle, dairy cattle, swine,
poultry, corn, soybeans, oats,
15.1 3.8 0 6.8
Jornada Experimental
1912 Pastureland, rangeland Beef cattle, forages, cotton 0 0.7 0.9 0.3
Walnut Gulch Watershed 1953
† Research foci in bold type.
‡ The Jornada Experimental Range and Walnut Gulch Experimental Watershed share a region.
1416 Journal of Environmental Quality
the interaction of crop genetics with environmental
limits and management options, making genetics
× environment × management a central organiz-
ing principle of LTAR sustainable intensication
research (Hateld and Walthall, 2015).
e greater productivity of US agriculture has
been a boon to the US consumer, as grocery store
prices for farm commodities have fallen by roughly
two-thirds since World War II. And since 1960,
the fraction of disposable income spent by US con-
sumers on food has fallen from 16 to 10% (USDA
Economic Research Service, 2016b). Many of
the practices and technologies responsible for the
nations yield increases have required greater inputs,
with total farm expenditures for inputs having
increased nearly an order of magnitude since World
War II (USDA Economic Research Ser vice, 2016b).
From the 1940s to the present, net returns to farm
operators declined roughly threefold (Henderson et
al., 2011), pressuring farmers to increase economic
eciencies (e.g., by increasing landholdings). At
the same time, farmers are responding to societal
demand for noneconomic priorities, from natural
resource conservation to food safety to nutrition
(Nowak and Korsching, 1998), as well as chang-
ing demand for alternatively grown foods, such as
organic foods. Government commodity, insurance
and conservation programs have helped to buer
these pressures, with total payments to farmers
increasing nearly 18-fold since 1960 to $16.9 billion
in 2015 (McFadden and Hoppe, 2017). Cropland
research sites in LTARs network are exploring a
range of opportunities to augment farm income
without resorting to fencerow-to-fencerow crop
cultivation, from commercially acceptable strategies
to lower energy, fertilizer, and pesticide purchases
(bioenergy crops [Con et al., 2016], improved
manure nutrient use [Rotz et al., 1999], diverse crop
rotations and pest control alternatives [Teasdale et
al., 2005]) to strategies that augment commodity
quality and value (improving organic production
systems [Cavigelli et al., 2013], new crop rotations
and commodities [Karimi et al., 2017]) to more
ecient use of agricultural landscapes (watershed
strategies to target crop production and conserva-
tion practices [Tomer et al., 2015a,b]).
Over the 20th century, gains in production
intensity have been accompanied by specialization
of cropland farming. is trend has increased cost
eciencies (Winsberg, 1982) while reducing on-
farm crop diversity. From 1900 to 1945, individual
US farms produced four to ve commodities; by
1970, the number of commodities per farm declined
to an average of three, and by 2000 to approximately
two (Dimitri et al., 2005). Across the 18 LTAR loca-
tions, corn (Zea mays L.), soybean [Glycine max (L.)
Merr.], and wheat (Triticum aestivum L.) are most
widely grown (Fig. 3). Even in regions with small farms histori-
cally growing more diverse crop rotations, corn and soybean
comprise substantial amounts of the rotation (Jones and Farley,
2016). Corn and soybean currently account for 58% of the total
cropland area of LTARs agroecosystems. It is now understood
Fig. 2. Historical US corn grain yields. Adapted from Duvick (2005) and USDA National
Agricultural Statistics Service (2012). Courtesy of H. Poenbarger.
Fig. 3. Percentage of land in the conterminous United States dedicated to each crop
in 2012 by county. Adapted from USDA National Agricultural Statistics Service (2012).
Category “Fruits, Nuts, and Vegetables” includes citrus and non-citrus fruit, berries,
vegetables harvested, tree nuts, peanut, sugarbeet, and sugarcane. Gray areas repre-
sent estimated regional inference spaces of the LTAR sites.
Journal of Environmental Quality 1417
that the loss of diversity introduces vulnerabilities to the nation’s
crops from stressors such as pests, weather, markets, and poten-
tially, soil health. is is perhaps best exemplied by the 1970
and 1971 infestation of southern corn leaf blight [caused by
Bipolaris maydis (Y. Nisik. & C. Miyake) Shoemaker], resulting
in an estimated economic loss of $1 billion across the United
States (roughly $6.5 billion in today’s value). e average yield
loss across the United States was 20 to 30%, but losses in parts
of LTAR’s eastern Corn Belt region were as high as 50 to 100%
(Bauer, 1972; Ullstrup, 1972). Today’s dependence on a limited
set of herbicide-resistant corn and soybean hybrids has, in turn,
spurred the evolution of herbicide resistance in weeds, most
notably Palmer amaranth (Amaranthus palmeri S. Watson) and
waterhemp [A. tuberculatus (Moq.) Sauer] (see Case Study 1).
us, LTARs sustainable intensication research emphasizes
strategies to diversify cropping systems (intercropping, cover
crops [Varvel, 2006]), as well as alternative approaches to weed
management (Nord et al., 2012).
Although a majority of US crops are grown in agroecosystems
where both crop and animal production occur, the specialization
of agriculture has increasingly separated their management. As
illustrated by LTAR’s agroecosystems, animal production sys-
tems are oen geographically separated from the major crop-
ping systems that serve as the source of feed. is uncoupling of
systems results in ows of resources, particularly nutrients, that
can accumulate around areas of livestock production and, over
time, contribute to an array of environmental concerns (Sharpley
et al., 2013). Cropping systems, particularly corn- and soybean-
dominated systems, are primarily dependent on synthetic fer-
tilizers for crop nutrition. On average, only 5% of the nation’s
cropland is fertilized with manure (USDA Economic Research
Service, 2009), although local rates of cropland manure applica-
tion can be considerably higher (e.g., approximately 17% of Iowa
cropland receives manure [Iowa State University, 2014]). Yet, a
majority of US soybean and corn is fed to farm animals (Denico
et al., 2014). Since animals metabolize less than one-third of the
nutrients in feed, the majority of nutrients in corn and soybean
they eat neither appears on the plates of US consumers nor is
returned to the cropland where the feed originated (Elser and
Bennett, 2011; Lanyon, 2000). Instead, these nutrients enrich
animal manure, which, in turn, is typically applied, oen in
excess, to farmland near animal production areas where it may
contribute to air and water quality degradation that can take
decades to reverse (Sharpley et al., 2013). To elucidate the impact
and management of manure nutrients in uncoupled cropland
and animal production systems, LTAR network research relies
on system-level analyses at farm, watershed, and regional scales
(Rotz et al., 1999; Liebig et al., 2004; Nearing et al., 2011;
Collick et al., 2016). Indeed, more ecient cycling of manure
nutrients and substitution of manure nutrients for mineral fer-
tilizers in cropping systems is a major focus of sustainability
research in one-third of LTAR’s 18 network sites (Spiegal et al.,
2018), recognizing that such recoupling of production systems
will ultimately require major changes to infrastructure, policy,
and management if it is to be achieved (Liebig et al., 2017).
e modern conservation movement was born, in large part,
out of concerns about cropland farming in the rst half of the
20th century: the Dust Bowl of the Great Plains in the 1930s, the
general loss of productivity from farmland, impacts to water and
air, and impairment of a host of ecosystem services that benet
rural communities in the United States (Bennett and Chapline,
1928; Leopold, 1949). Conservation activities compete with
other priorities on US croplands, principally those derived from
the pursuit of protability but also priorities derived from belief
systems and local cultural practices and made possible by con-
stantly evolving technologies (Ervin and Ervin, 1982; Knowler
and Bradshaw, 2007). All LTAR network locations have wit-
nessed major historical declines in the extent of conservation
set-asides (e.g., buer strips and idle land), the principal policy
tool used to protect soil and water as well as to provide habitat
for pollinators and wildlife (Kremen et al., 2002; Swinton et al.,
2007; Lark et al., 2015). When commodity prices soared aer
Case Study 1
Central Mississippi LTAR Site
Straddling the Mississippi River, LTAR’s Central Mississippi agroecosystem occupies the glacial till plains of northern Missouri and
western Illinois. Average yields doubled with the advent of the Green Revolution, from 2.6 Mg ha−1 in 1950 to 5.2 Mg ha−1 in 1975. Over
the same time, agricultural employment declined from 33% to less than 15% of the labor force in the region, even while cropland
expanded by nearly 10% (USACE, 1975). During the 1970s and early 1980s, mean debt of Missouri farmers nearly tripled (Missouri led
the nation in farm bankruptcies in 1985), prompting many small- to mid-sized farms to abandon integrated crop–livestock produc-
tion for more specialized and protable grain production systems (Demissie, 1986). Since that period, farming systems in the Central
Mississippi region largely retained their separate specialized grain and livestock production systems.
In recent decades, multiple new pests have presented broader challenges to agriculture in the region. Glyphosate-resistant soy-
bean and corn have simplied weed control and have helped to expand no-till cropping systems with associated erosion control ben-
ets. However, weeds such as Palmer amaranth and waterhemp have recently become resistant to glyphosate and are aggressively
invading elds where glyphosate is the principal herbicide (Ward et al., 2013). Growing 2 to 6 cm daily, a single Palmer amaranth plant
produces up to 1 million seeds, spreading quickly and reducing yields by as much as 79% for soybean. Current strategies for eective
control of infested elds involve diversied approaches to herbicide selection and, once the weed is established, deep, inversion till-
age, which is considered anathema to soil conservation objectives.
Sustainable intensication strategies in the Central Mississippi agroecosystem seek to address yield gaps as well as to ensure
greater stability in yields over the long term in the face of climate change. Key opportunities at the farm level include greater adop-
tion of precision management and variable rate application technologies. These technologies are also expected to drive reductions
in both greenhouse gas emissions and nitrate losses to ground and surface waters. The persistence of soil conservation concerns
and the evolving paradigm of soil health highlight opportunities for both improving productivity of farm soils and reducing o-site
impacts through practices such as reduced tillage and use of cover crops.
1418 Journal of Environmental Quality
2008, economic incentives to grow grains, particularly corn,
exceeded the national average rental of $140 ha−1 by USDA’s
Conservation Reserve Program. In 2012, there was a net loss
in nearly every LTAR region of Conservation Reserve Program
contracts, as even marginal land was converted to commodity
production (Fig. 4; Lark et al., 2015). Acknowledging the pri-
macy of economics in determining conservation outcomes, a
major theme of LTAR’s sustainable intensication research is to
dene landscape management strategies that increase the pro-
ductivity of prime cropland while nding economically viable
alternative land uses for marginal lands that also reduce negative
environmental impacts (Spiegal et al., 2018).
Across the United States, cropland agriculture is the single
greatest consumer of fresh water, a pattern that has not changed
since early settlement times. Indeed, in much of the western
United States, settlement and cropland establishment required
irrigation development. Given irrigation’s potential to increase
crop yield and quality, reduce pest pressures, precisely deliver
nutrients, and buer against the uncertainty of weather, irriga-
tion can be found in nearly all LTAR cropland agroecosystems.
Today, irrigation represents about two-thirds of the nation’s
groundwater use, with some of the greatest expansions occur-
ring aer World War II through the early 1980s (Maupin et al.,
2014). Extraction of groundwater in some of the nation’s most
productive agricultural regions exceeds groundwater recharge,
resulting in long-term declines in water levels (Reilly et al., 2008).
Regions represented by LTARs Central Plains, Southern Plains,
and Platte River/High Plains sites, which account for 11% of US
irrigated crop production (Gollehon and Winston, 2013), all
rely on the Ogallala High Plains aquifer, which is declining in
many areas. Even in the humid Lower Mississippi River valley,
rapid increases in demand for irrigation from the Mississippi
River valley alluvial aquifer since the 1980s have resulted in
major groundwater declines in some areas. To address the sus-
tainability of irrigated agriculture, LTAR network sites in arid
and humid regions alike are pursuing new water management
strategies (Baker et al., 2012), from precision sprinkler irrigation
systems to water-conserving cropping systems to large-scale man-
aged aquifer recharge.
e relationship of agriculture to rural communities in the
United States has changed over time, reecting trends in global-
ization, agricultural policy, and major demographic shis. With
increasing mechanization, greater eciencies in production,
and the growth of urban job opportunities, farm populations
decreased from nearly 40% of the United States population in
1900 to approximately 25% of the population in 1940 to only
1% aer 2000 (Dimitri et al., 2005; USDA Economic Research
Service, 2016a). While wages for US farm laborers have grown
more than other farm inputs during that time, strong competi-
tive pressures exist to minimize labor costs to ensure the low cost
of agricultural products. In 2012, hired farm labor wages aver-
aged $10.80 h−1 (USDA National Agricultural Statistics Service,
2012), 40% below the US median wage. As US farmers have
aged (average age is currently 58 years compared with 42 years
for the nation’s workforce as a whole), dependence on contrac-
tual labor has dramatically increased, as has the cultural diver-
sity of rural communities (USDA Economic Research Service,
2016c). Agricultural land ownership has also changed dramati-
cally in the United States (Fig. 5). From 2006 to 2015, cropland
values in the United States increased from $5,400 to $9,900 ha−1,
respectively, serving as a major barrier to recruitment of new
farmers (USDA National Agricultural Statistics Service, 2016).
In LTAR’s eastern Corn Belt region, almost half of cropland is
rented or leased (USDA National Agricultural Statistics Service,
2012; Reimer et al., 2012), and rental agreements requiring the
maintenance of soil fertility levels have interfered with local
Fig. 4. USDA Conservation Reserve Program changes in enrollment by county from 2013 to 2014. Adapted from USDA Farm Service Agency (2017).
Contracts expire on 30 September, and most new contracts begin 1 October. Black polygons represent estimated regional inference spaces of the
LTAR sites.
Journal of Environmental Quality 1419
water quality mitigation eorts (King et al., 2017). Sustainable
intensication strategies must take into account the myriad of
social and economic factors that simultaneously inuence adop-
tion of new practices, alter expectations of rural workforces, shi
market opportunities, and change rural life in other ways.
Factors Aecting the Sustainability of
Grazing Agroecosystems
Grazing agroecosystems include both rangelands and pas-
turelands and constitute the single most extensive land use in
the conterminous United States, accounting for 319 million ha,
approximately 40% of the land area of the 48 contiguous states
(Fig. 6). Grazing lands are typically associated with areas that are
unsuitable or undesirable for crop production (e.g., poor soils
or low rainfall), although prime cropland may also be grazed
protably. Opportunities for sustainable intensication of graz-
ing agroecosystems include strategies aimed at balancing both
animal and forage productivity, strategies that oer access to pre-
mium markets (e.g., organic, grass-fed), and strategies aimed at
ensuring long-term resilience in the face of uncertain climatic,
re, and biotic stressors. Notably, grazing agroecosystems pro-
vide key opportunities to recouple animal, forage, and feed
production systems and therefore must ultimately be linked to
cropland strategies. Sustainable intensication of grazing lands
must look beyond the scale of individual management units
(elds, paddocks) and even individual enterprises to consider the
production potential and non-commodity ecosystem services of
the surrounding landscape, as well as opportunities for optimiz-
ing interacting regional and national animal feed production
systems. Although rangelands and pasturelands dier in core
management approaches and ownership patterns, both provide
a wealth of non-commodity ecosystem services—freshwater
storage, soil carbon storage, habitat for ora and fauna, and aes-
thetics—that should be considered in sustainable management
strategies (Havstad et al., 2007; Sanderson et al., 2012).
Americas rangelands—the uncultivated grasslands, shrub-
lands, and savannas that cover about one-third of the contigu-
ous 48 states—span LTAR’s desert, mountain, Great Plains,
and subtropical coastal ecosystems (Fig. 6) and supply approxi-
mately 10% of the total feed needs for US beef, sheep, and
goat production (Havstad et al., 2007). As rangelands are, by
denition, managed as semi-natural systems (Society for Range
Management, 1998), options to sustainably intensify produc-
tion are constrained relative to pasturelands and croplands.
Ranchers are particularly susceptible to the vagaries of weather
and markets, resulting in economic returns that vary widely with
drought, supplemental feed availability, feedlot grain prices, and
consumer demand (Torell et al., 2010). In addition, depend-
ing on the relative importance of private and public lands in
the regional portfolio, ranchers’ access to a land base sucient
for livestock forage requirements are complicated by rising
private land costs and by diculties retaining leases on public
land as agency mandates change (Tanaka et al., 2005; Brunson
and Huntsinger, 2008). Nonetheless, opportunities exist to
improve rangeland production and protability while sustain-
ing rangeland ecological integrity for long-term production.
e LTAR network rangeland sites are evaluating strategies that
simultaneously increase forage utilization, reduce environmen-
tal impacts, and enhance preparedness for accelerating climate
variability, including collaborative adaptive grazing management
(Derner and Augustine, 2016), breed selection (Anderson et al.,
2015; Neel et al., 2016), grass nishing (Diaz et al., 2015), and
Fig. 5. Percentage of US farmland rented or leased by county, 2012. Adapted from USDA National Agricultural Statistics Service (2012). Black poly-
gons represent estimated regional inference spaces of the LTAR sites. Data were not available for counties colored white. Black polygons represent
estimated regional inference spaces of the LTAR sites.
1420 Journal of Environmental Quality
innovative prescribed burning practices (Derner et
al., 2009; Boughton et al., 2013).
Many of the rangeland regions represented by
LTAR have undergone profound shis in vegeta-
tion during recent centuries, and opportunities for
sustainable intensication are closely tied with
these regional histories. e regional agroecosys-
tems represented by the Great Basin, Jornada, and
Walnut Gulch sites have experienced dramatic plant
invasions, altering biodiversity, forage availability,
soil health, and hydrology (see Case Study 2). A
principal focus at these sites is to evaluate whether
ecological restoration can improve both forage
availability and biodiversity (Bestelmeyer et al.,
2018; Goodrich et al., 2015; Williams et al., 2016).
Elsewhere, LTARs Floridian rangelands have been
profoundly altered by large-scale manipulation of
water and re regimes, changing the extent of grass-
lands, composition of habitat, and accompanying
diversity (Bridges, 2006). ere, LTAR is evaluat-
ing strategies to return subtropical rangelands to
a graminoid and forb-dominated system that is
expected to improve livestock grazing capacity and
protect populations of native species. At LTAR’s
Central Plains site, grasslands can accommodate
heavy stocking of cattle due to co-evolution of
grasses and bison (Milchunas et al., 1988; Porensky
et al., 2016). However, to protect a comprehensive
array of ecosystem services, LTAR is evaluating
adaptive strategies that account for preferences of
grassland birds and other valued taxa (Derner et al.,
2009). e LTAR network’s sustainable intensica-
tion strategies for rangeland emphasize seeking to
reconcile the long-term stability of grazing produc-
tion with the protection of the non-commodity eco-
system services that are desired from these systems.
Pasturelands include both rainfed eastern humid
regions and western arid regions where irrigation of
pastures is common (Fig. 6). From an agronomic
management standpoint, pasture maintenance and
infrastructure are oen neglected compared with more intensive
cropland management, resulting in lost opportunities to pro-
duce forage less expensively than purchased feed (see Case Study
3). As with rangelands, a prime challenge with pasturelands
is matching the availability of high-quality forages to animal
demands as pasture forage availability and quality vary spatially
and temporally (Franzluebbers et al., 2012). e dominance of
cool-season species in pastures of LTAR’s northern agroecologi-
cal regions results in mid-summer lulls in forage yields and qual-
ity that are amplied by drought. In arid regions, irrigation of
pastures is necessary to maintain production. Aggressive harvest-
ing of forages can deplete soil nutrient reserves, damage forage
species, and result in long-term problems such as early decline
of grasses (e.g., orchardgrass [Dactylis glomerata L.] die-o ) or
lower nutritional quality ( Jones and Tracy, 2015). As with range-
lands, LTAR’s pastureland sites are evaluating strategies to extend
grazing periods and to improve forage yield and nutritional
quality during periods of low productivity. Strategies range from
using stockpiled forages in the dormant season (Riesterer et
al., 2000) to interseeding new species into established pastures
(Bartholomew and Williams, 2010).
e management of pastures is complex, with concerns
ranging from the invasion of noxious weeds and outbreaks of
plant pests and pathogens to the diculties matching timing
of peak production of forage grasses with peak needs of live-
stock (Sanderson et al., 2012). In LTAR’s Southern Plains and
Archbold/University of Florida agroecosystems, the emergence
of woody weed species has plagued graziers, while burgeoning
populations of wild mustard (Brassica spp.) and the new invasive
bermudagrass stem maggot (Atherigona reversura) are reducing
forage production in the Gulf Atlantic Coastal Plain. ese
complex problems require multipronged mitigation strategies
that include regular burning, adaptive rotational grazing, weed
scouting, and breeding pest-resistant forage varieties to enable
timely responses. Yet, when properly managed, pastures are
Fig. 6. Rangelands and pasturelands in the conterminous United States as percent-
age of county. Rangelands are dened as “Shrub/Scrub” + “Grassland/Herbaceous”
in the 17 western states and Florida; pasturelands are dened as “Pasture/Hay” in all
states (National Land Cover Database [Homer et al., 2015]). Gray polygons represent
estimated regional inference spaces of the LTAR sites.
Journal of Environmental Quality 1421
oen seen as an important component of landscape strategies
aimed at integrating crop and livestock systems (Liebig et al.,
2017) and improving ecosystem services from pollinator habi-
tat (Sanderson, 2016) to soil health (Hammac et al., 2016) and
water quality enhancement (Endale et al., 2011). Even though
the dominant species in US pastures are not native (Sanderson
et al., 2012), pastures can increase farm and landscape habitat
diversity, especially in areas with extensive row-crop produc-
tion (Egan and Mortensen, 2012; Russo et al., 2013). Pastures
can also be leveraged to add value to livestock products, par-
ticularly in contrast with connement operations (Haa et al.,
Sustainable Intensication of US
Agriculture and the LTAR Network
Research to understand and enable sustainable intensica-
tion of US agriculture must encompass the breadth of demands
placed on the nation’s agroecosystems, considering not only
production factors and environmental impacts but also human
nutrition, economic development, and public policy (Garnett,
2013). For the LTAR network’s 18 agroecosystem regions,
spanning nearly one-third of the land area of the 48 contiguous
states, interdisciplinary research into sustainable intensica-
tion addresses four themes simultaneously at multiple spatial
and temporal scales: (i) increasing production to meet growing
national ambitions for food, feed, ber, and energy; (ii) con-
serving the nation’s natural resources and protecting its envi-
ronment; (iii) promoting the prosperity of rural populations;
and (iv) developing a vision for sustainable intensication of
US agriculture that weighs both national and local opportuni-
ties and costs.
Increasing Production to Meet Growing National
Ambitions for Food, Feed, Fiber, and Energy
To achieve national objectives for greater productivity, LTAR
network research embraces the approach of genetics × environ-
ment × management (Hateld and Walthall, 2015), integrating
science across these three major areas of investigation, develop-
ing and vetting production strategies, and then extrapolating
with models to justify the evolution of agriculture. To ensure
sustainable outcomes, research to advance national agricultural
productivity also considers the ensuing resilience of new systems
to multiple concurrent threats.
Yield increases cannot be expected universally. In some cases,
opportunities to increase commodity yields can close yield gaps
(Godfray et al., 2010). In other cases, the production of a com-
modity may be close to its local ceiling, but productivity and
protability increases within the local agroecosystem may still be
possible. erefore, central to the LTAR network’s extrapolation
of ndings from empirical and modeled research is the determi-
nation of appropriate expectations for increasing productivity
and protability across US agroecosystems. is requires the
evaluation of strategies that extend beyond the eld and farm
gate, including forecasting opportunities to maximize produc-
tivity and other outcomes at regional scales (Con et al., 2018).
Conserving the United States’ Natural Resources
and Protecting Its Environment
For commodity production and farm protability to enhance,
rather than compete with, non-commodity ecosystem services,
a comprehensive understanding of agroecosystem processes is
required. Developing this understanding requires basic science,
oen without an immediate applied outcome. However, there
are a plethora of ecological studies with no tie to the realities
Case Study 2
Jornada Experimental Range and Walnut Gulch LTAR Sites
Raising livestock on expansive rangelands has been central to postcolonial culture in the US Southwest (Morrisey, 1951). The
industry grew with Spanish settlers during the 17th and 18th centuries, briey declined in the mid–19th century, and became impor-
tant again during civil wars in the United States and in Mexico. By 1870, enormous herds of cattle were arriving via newly expanded
railroads, funded by investors in the east (Sayre, 2009). Since then, cattle numbers have peaked several times to over 1 million—in
1890, during World War I, and again in 1920—but the count in Arizona and New Mexico combined fell to 900,000 by 1990 (Fredrickson
et al., 1998).
The arid to semiarid rangelands that supported livestock through these cycles have undergone well-documented changes in
social-ecological characteristics. Over the past century, following early episodes of severe overgrazing coupled with drought, the
perennial grass cover that was once predominant has been replaced by shrubs. Regional beef production has declined overall. The
value of ranches and the incomes of people managing them are increasingly decoupled from livestock production because alterna-
tive uses of rangelands are increasing, particularly exurban development and recreation. Even though stocking rates have declined
dramatically compared with the beginning of the 20th century, grassland recovery has been limited or absent in many areas. Ongoing
shrub encroachment, soil erosion, and biodiversity loss aect a variety of ecosystem services, including forage provision, air quality,
hunting, and other recreational opportunities.
Signicant opportunities exist to increase food production and rural incomes in the rangelands of the desert Southwest. From the
standpoint of controlling and reversing shrub invasion, novel mechanical removal and herbicide treatments show promise, with the
intention of increasing forage availability and quality for cattle while stabilizing soils and maintaining habitat for wildlife. In addition,
recent research on alternative cattle breeds has identied potential advantages with Raramuri Criollo cattle, a biotype with 500 years
of adaptive history in the Chihuahuan Desert (Anderson et al., 2015). Compared with the British crossbred cattle raised in the region,
Criollo cattle typically range more widely across desert pastures, a behavior that may help to overcome some of the economic and
environmental problems associated with localized overgrazing in the desert. With focus on specic breeds and sustainable manage-
ment practices, there are also opportunities to expand grass nishing, sustainability branding, and local direct sales. These practices
can lower input costs and increase commodity value.
1422 Journal of Environmental Quality
of management whose recommendations do little to advance
agriculture (Sharpley et al., 2016). erefore, research must link
commodity and non-commodity ecosystem services to realistic
management options relevant to local contexts. rough sys-
tematic measurement using common protocols, LTAR network
research will enable context-specic processes to be compared
across the national spectrum of LTAR sites.
Over the long term, LTAR is seeking to diversify strategies for
agriculture at eld, landscape, and regional scales, recognizing
that some desired outcomes are easier to achieve than others
and that current paradigms for intensication of commodity
production tend to promote homogenization within industries
and within regions, rather than diversication. As a result, there
is a need to understand the constraints placed by markets and
policies to adapt innovative strategies for the enhancement of
ecosystem services.
Promoting the Prosperity of Rural Populations
rough its place-based representation at multiple sites, the
LTAR network is equally focused on ensuring that the national
pursuit of greater commodity production benets local agricul-
tural communities. Benets will be achieved not only through
greater protability of farming systems and improved environ-
mental quality but also through changes that support vibrant
rural community institutions and economic infrastructures
while ensuring equitable access to natural resources and reducing
health risks to rural residents. At a minimum, research to advance
productivity and protability must understand and seek to over-
come the social and economic barriers to change. To ensure that
change is sustainable, connections must be made to rural work-
forces, rural quality of life, and rural economies (Perdue, 2017).
At the heart of research on the full spectrum of ecosystem
services provided by agriculture is an understanding that there
are net benet inequities between the providers (rural) and
beneciaries (rural and metropolitan) of agricultural ecosystem
services and that trade-os in production and environmental
quality that emerge from management and policy decisions
substantially aect rural health and prosperity. ese trade-os
apply to all forms of agricultural production (Cavigelli et al.,
2013; Swain et al., 2013). Sustainable intensication strategies
must leverage such research outcomes to ensure that trade-os
are fully understood and considered.
Developing a Vision for Sustainable Intensication of
US Agriculture That Weighs Both National and Local
Opportunities and Costs
National calls for greater commodity production must
account for the diversity of US agroecosystems to nd opportu-
nities for intensication strategies that can be sustained over the
long term without collateral deterioration of resources, non-com-
modity ecosystem services, and rural prosperity. At local levels,
ecient implementation of sustainable intensication requires
targeting technological, management, and logistical/infrastruc-
ture changes in areas oering opportunities for greater produc-
tivity, new products and markets, and enhanced non-commodity
ecosystem services. At another level, national strategies for sus-
tainable intensication enable exibility in expectations of dif-
ferent agroecosystems, distinguishing between where and how
productivity gains can be made, and assessing when and where
nondetrimental impacts at some scales may accumulate to result
in a substantial detrimental impact at another scale.
Agriculture today reects the outcome of historical shis in
management in which ambitious goals meet with challenges to
production potential, protability, resource availability, cultural
norms, and other factors beyond the control of a single farmer or
rancher. As policies, markets, and populations change demands on
US agriculture, there is little question that US agriculture can rise
to the challenge, but the application of national expectations must
Case Study 3
Upper Chesapeake Bay LTAR Site
Falling within the ancient Appalachian mountains of the mid-Atlantic, LTAR’s Upper Chesapeake Bay location brushes against the
population corridor of the United States’ eastern seaboard. Pastures are a ubiquitous feature of rural and suburban landscapes alike,
accounting for 14% of the total land area and 73% of agricultural land. While certain farming populations, such as plain sect (Amish
and Mennonite) farmers, rely heavily on pastures, pasturelands are largely relegated to less-productive agricultural soils, and their
management is often neglected. A large amount of pastureland is maintained by small beef and hobby farmers. Small horse farms,
each with a few animals, are so numerous that horses are estimated to generate nearly 10% of the manure dry matter in the 166,000-
km2 Chesapeake Bay watershed (which includes LTAR’s Upper and Lower Chesapeake Bay agroecosystems). Pastures oer opportu-
nity to reduce expenses on forage inputs. Indeed, grazing is a signicant component of nearly all dairy systems found in the Upper
Chesapeake Bay region, including on many large conned operations in which dry cows and heifers are typically grazed.
Substantial opportunities exist to improve use of pasture forages, lessen farm dependence on purchased feeds, and improve
the contribution of pastures to multiple ecosystem services. A signicant niche now exists for pastured dairies, with animal welfare,
health benets, and taste contributing to premiums received by some dairy producers, particularly those participating in direct
marketing. Sustainable management of pasturelands includes the need to adopt practices that mitigate the impact of grazing cattle
on the environment, especially through control of manure storage and distribution (Egan et al., 2015). Traditional practices, such as
allowing direct access to streams, can aect not only water quality but many local ecosystem services and can even adversely inu-
ence animal health (James et al., 2007). Under Chesapeake Bay mitigation activities, streambank fencing and riparian corridor restora-
tion have been priorities, but they can impose signicant costs and management diculties to grazers, including impeding access to
certain areas of the farm, imposing demands for watering infrastructure, and providing opportunities for invasive plants to ourish.
These are largely manageable problems, but they require additional planning and management requirements that are unwanted
by small farmers with limited time and resources. Given the narrow prot margins and limited exibility of small farms in the region,
innovation is needed to devise strategies for graziers that can accommodate both provisioning and non-provisioning ecosystems
services (e.g., Moechnig, 2007).
Journal of Environmental Quality 1423
reect local realities, understanding that dierent approaches will
be required across regions and production systems.
e LTAR network is uniquely poised to support the sus-
tainable intensication of US agriculture, providing the data
(Kaplan et al., 2017), as well as the inferences, needed to inform
producers, the public, and policymakers on options and impli-
cations. e land base provided by the LTAR network can pro-
vide test beds to evaluate new cultivars, breeds, and methods
under actual production conditions with careful monitoring of
not only yields but on- and o-site production eects, as well as
the potential and requirements for new products and markets.
Ultimately, a balance of local and national concerns is expected
to support well-reasoned strategies for sustainable intensica-
tion that reect the broad diversity and national ambitions of
US agriculture.
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... As an example, crop yield might be a linear function of average temperature, fertilizer applied, and normalized difference vegetation index (NDVI), with a spatially correlated random To obtain data for use of these models, there are two experimental modalities considered in this paper. Long-term agricultural research permits the monitoring of soil processes such as soil acidification and crop management impacts such as soil erosion that manifest incrementally over long periods of time [17], while on-farm research enables scientists and engineers to work directly with farmers to gain information from expanded sampling environments that is relevant to real-world farm operations [18,19]. This study combined data from both a long-term research site and a local farm in the Palouse region to develop optimal sampling strategies for the determination of lime requirements in Palouse soils. ...
... To obtain data for use of these models, there are two experimental modalities considered in this paper. Long-term agricultural research permits the monitoring of soil processes such as soil acidification and crop management impacts such as soil erosion that manifest incrementally over long periods of time [17], while on-farm research enables scientists and engineers to work directly with farmers to gain information from expanded sampling environments that is relevant to real-world farm operations [18,19]. This study combined data from both a long-term research site and a local farm in the Palouse region to develop optimal sampling strategies for the determination of lime requirements in Palouse soils. ...
... The drawbacks of the on-farm approach were primarily the constraints imposed by working around the field operations and the limited availability of historical data for the farm. This approach combining long-term and on-farm research demonstrates the power of researcher-stakeholder collaborations and knowledge co-production in agriculture [17]. ...
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Soil acidification is a major problem in the inland Pacific Northwest. A potential solution is the application of lime to neutralize acidity and raise pH. As lime is an expensive input, precision variable rate application is necessary. However, high-resolution mapping of pH and buffer pH for lime prescription requires costly sampling and analysis. To reduce the amount of sampling needed, remote sensing, which correlates with soil pH and buffer pH, can be used to determine optimal sampling locations and allow optimal interpolation. We used soil and crop data from the Washington State University R.J. Cook Agronomy Farm to develop an optimal sampling plan for a farmer’s property, followed that sampling design, and used the measured pH and buffer pH to fit a Bayesian hierarchical model using remote sensing variables specific to that farmer’s land. Following this, a new model was developed for the research farm with similar covariates. Ultimately, on the farmer’s field, we observed a root mean square error (RMSE) of 0.2487 for soil pH at a depth of 0–10 cm and 0.1221 for modified Mehlich buffer at 0–10 cm of depth. For the research farm, where buffer pH was not measured, we saw an RMSE of 0.3272 for soil pH at 0–10 cm of depth and 0.3381 for soil pH at 10–20 cm of depth. The ability make predictions of soil acidity with uncertainty using this technique allows for prescription lime application while optimizing soil sampling and testing. Further, this paper serves as a case study of on-farm research.
... The overarching mission of the LTAR network is to provide sustainable solutions for food and fiber production that are currently facing challenges associated with changing climate and increasing resource demands. The LTAR network has been increasingly turning to technological solutions, including remote sensing, to serve as a large-scale indicator Browning et al., 2021) and solve its pressing questions regarding agricultural sustainability (Kleinman et al., 2018;Boughton et al., 2021;Goodrich et al., 2021). The LTAR network includes a wide range of cropping systems, management practices, and land use histories. ...
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Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) network, can allow for the study of broader trends in crop productivity and sustainability. Methods: In this study, gross primary productivity (GPP) estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) for three LTAR cropland sites were integrated for use in a machine learning modeling effort. They are Kellogg Biological Station (KBS, 2 towers and 20 site-years), Upper Mississippi River Basin (UMRB - Rosemount, 1 tower and 12 site-years), and Platte River High Plains Aquifer (PRHPA, 3 towers and 52 site-years). All sites were planted to maize ( Zea mays L .) and soybean ( Glycine max L .). The MODIS GPP product was initially compared to in-situ measurements from Eddy Covariance (EC) instruments at each site and then to all sites combined. Next, machine learning algorithms were used to create refined GPP estimates using air temperature, precipitation, crop type (maize or soybean), agroecosystem, and the MODIS GPP product as inputs. The AutoML program in the h2o package tested a variety of individual and combined algorithms, including Gradient Boosting Machines (GBM), eXtreme Gradient Boosting Models (XGBoost), and Stacked Ensemble. Results and discussion: The coefficient of determination ( r ² ) of the raw comparison (MODIS GPP to EC GPP) was 0.38, prior to machine learning model incorporation. The optimal model for simulating GPP across all sites was a Stacked Ensemble type with a validated r ² value of 0.87, RMSE of 2.62 units, and MAE of 1.59. The machine learning methodology was able to successfully simulate GPP across three agroecosystems and two crops.
... This study included a native tallgrass prairie (64 ha [70,71]. El Reno, Oklahoma, has a temperate continental climate with summer months generally hot and dry and most rainfall occurring during May-June and September-October. ...
Soils harbor highly diverse microbial communities that are critical to soil health, but agriculture has caused extensive land use conversion resulting in negative effects on critical ecosystem processes. However, the responses and adaptations of microbial communities to land use conversion have not yet been understood. Here, we examined the effects of land conversion for long-term crop use on the network complexity and stability of soil microbial communities over 19 months. Despite reduced microbial biodiversity in comparison with native tallgrass prairie, conventionally tilled (CT) cropland significantly increased network complexity such as connectivity, connectance, average clustering coefficient, relative modularity, and the number of species acting at network hubs and connectors as well as resulted in greater temporal variation of complexity indices. Molecular ecological networks under CT cropland became significantly more robust and less vulnerable, overall increasing network stability. The relationship between network complexity and stability was also substantially strengthened due to land use conversion. Lastly, CT cropland decreased the number of relationships between network structure and environmental properties instead being strongly correlated to management disturbances. These results indicate that agricultural disturbance generally increases the complexity and stability of species "interactions", possibly as a trade-off for biodiversity loss to support ecosystem function when faced with frequent agricultural disturbance. The ISME Journal; https://doi.
... In contrast, US agriculture is spatially varied, which makes a uniform approach to achieving sustainable production systems difficult. These complications refer to many issues, starting from local constraints to system factors (Kleinman et al., 2018). ...
This paper proposes a new method for evaluating green growth in agriculture (GGA) based on a set of key performance indicators and a synthetic index. To this end, we used the zero unitarisation method. The objects of study were seven countries/groups of countries with the largest share in agricultural production in 2020. This paper attempts to answer the following questions: (1) Has there been any progress in fulfilling the assumptions of the green growth concept implemented in the agricultural sector of the examined countries? (2) Which countries do better, and which do worse in that respect? (3) What are the challenges respective countries need to face? In the analysed years, the mean GGA index increased from 0.3287 to 0.3342, which means that the overall level of ‘greening’ in agriculture grew insignificantly. Out of the seven analysed countries/regions, China did the best in handling the challenges of GGA, while India did the worst. The paper discusses the reasons for this state of affairs, simultaneously making recommendations for improving the existing situation.
... The LTAR network was developed in part to provide information about how different cropping systems behave (Kleinman et al., 2018). Within the LTAR network, the croplands common experiment aims to evaluate strategies to sustainably intensify agricultural production by comparing aspirational (ASP) and business-as-usual (BAU) cropping systems. ...
To decrease negative environmental impacts associated with row crop agriculture, the conversion of conventional agricultural lands to no-till with cover crops or to restored prairie in the Midwest U.S. has been proposed and has the potential to alter hydrologic behavior. Our understanding of the impacts of this conversion on water and carbon fluxes from (agro-)ecosystems, however, is limited. We deployed eddy covariance systems in a business-as-usual (BAU) tilled cropping system, an aspirational (ASP) no-till cropping system with cover crops, and a native tallgrass prairie (TP) ecosystem to measure evapotranspiration (ET) and carbon dioxide exchange with the atmosphere. Measurements began in 2015 and we have at least 4 complete years of observations at each site. The average annual ET is higher at the TP site than the BAU site, but not significantly different from the ASP site. The gross primary production and ecosystem respiration are highest at the ASP site. Average annual net ecosystem exchange is negative (carbon uptake) at both agricultural sites (-305 ± 25 and-311 ± 31 gC m − 2 yr − 1 at ASP and BAU, respectively) and neutral in the prairie (-11 ± 10 gC m − 2 yr − 1 at TP). We evaluate the sensitivity of fluxes to environmental conditions including soil water content, vapor pressure deficit, air temperature, and photosynthetic photon flux density and find that the BAU site is the most sensitive to changes in environmental conditions while the TP site is the most resilient to changes. The interannual variability in ET is accentuated by agricultural management and because of the more diverse cropping system, is highest at the ASP site. The interannual variability in carbon fluxes, however, is not increased by agricultural management. Our findings illustrate how conservation practices impact the water budget and highlights the value of these practices in a changing climate.
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Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.
Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the U.S. and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha-1 (range = -32.7 to 340.6 kg P ha-1 ), with an average uncertainty of 13.1 kg P ha-1 (range = 1.0 to 87.1 kg P ha-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61 and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy. This article is protected by copyright. All rights reserved.
Current gaps impeding researchers from developing a soil and watershed health nexus include design of long-term field scale experiments and statistical methodologies that link soil health indicators (SHI) with water quality indicators (WQI). Land cover is often used to predict WQI but may not reflect the effects of previous management such as legacy fertilizer applications, disturbance, and shifts in plant populations) and soil texture. Our research objectives were to: use nonparametric Spearman rank-order correlations to identify SHI and WQI that were related across the Fort Cobb Reservoir Experimental Watershed (FCREW); use the resulting rho (r) and p-values (P) to explore potential drivers of SHI-WQI relationships, specifically land use, management and inherent properties (soil texture, aspect, elevation, slope); and interpret findings to make recommendations regarding assessment of the sustainability of land use and management. The SHI values used in the correlation matrix were weighted by soil texture and land management. The SHI that were significantly correlated with one or more WQI were available water capacity (AWC), Mehlich III soil P, and the sand to clay ratio (S:C). Mehlich III soil P was highly correlated with three WQI: total dissolved solids (TDS) (0.80; P<0.01), electrical conductivity of water (EC-H2 O) (0.79; P<0.01), and water nitrates (NO3 - H2 O) (0.76; P<0.01). The correlations verified that soil texture and management jointly influence WQ but the size of the soils data set prohibited determination of the specific processes. Adoption of conservation tillage and grasslands within the FCREW improved WQ such that water samples met the Environmental Protection Agency (EPA) drinking water standards. Future research should integrate current WQI sampling sites into an edge-of-field design representing all management by soil series combinations within the FCREW. This article is protected by copyright. All rights reserved.
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Transitions from semiarid grassland to shrubland states are among the most widely recognized examples of regime shifts in terrestrial ecosystems. Nonetheless, the processes causing grassland-shrubland transitions and their consequences are incompletely understood. We challenge several misconceptions about these transitions in desert grasslands, including that (a) they are currently controlled by local livestock grazing and drought events, (b) they represent severe land degradation, and (c) restoration of grassland states is impossible. Grassland-shrubland transitions are the products of multiple drivers and feedback systems, both ecological and social, interacting at multiple scales of space and time. Grass recovery within shrubland states-with and without shrub removal-produces novel ecosystems that are dissimilar from historical grasslands but that provide important ecosystem services. Projected increases in climate variability are likely to promote the further displacement of perennial grasses by xerophytic shrubs. This article offers guidelines for managing grassland-shrubland transitions in the face of changing biophysical and socioeconomic circumstances.
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Sustainable intensification is an emerging model for agriculture designed to reconcile accelerating global demand for agricultural products with long-term environmental stewardship. Defined here as increasing agricultural production while maintaining or improving environmental quality, sustainable intensification hinges upon decision-making by agricultural producers, consumers, and policy-makers. The Long-Term Agroecosystem Research (LTAR) network was established to inform these decisions. Here we introduce the LTAR Common Experiment, through which scientists and partnering producers in US croplands, rangelands, and pasturelands are conducting 21 independent but coordinated experiments. Each local effort compares the outcomes of a predominant, conventional production system in the region ('business as usual') with a system hypothesized to advance sustainable intensification ('aspirational'). Following the logic of a conceptual model of interactions between agriculture, economics, society, and the environment, we identified commonalities among the 21 experiments in terms of (a) concerns about business-as-usual production, (b) 'aspirational outcomes' motivating research into alternatives, (c) strategies for achieving the outcomes, (d) practices that support the strategies, and (e) relationships between practice outreach and adoption. Network-wide, concerns about business as usual include the costs of inputs, opportunities lost to uniform management approaches, and vulnerability to accelerating environmental changes. Motivated by environmental, economic, and societal outcomes, scientists and partnering producers are investigating 15 practices in aspirational treatments to sustainably intensify agriculture, from crop diversification to ecological restoration. Collectively, the aspirational treatments reveal four general strategies for sustainable intensification: (1) reducing reliance on inputs through ecological intensification, (2) diversifying management to match land and economic potential, (3) building adaptive capacity to accelerating environmental changes, and (4) managing agricultural landscapes for multiple ecosystem services. Key to understanding the potential of these practices and strategies are informational, economic, and social factors—and trade-offs among them—that limit their adoption. LTAR is evaluating several actions for overcoming these barriers, including finding financial mechanisms to make aspirational production systems more profitable, resolving uncertainties about trade-offs, and building collaborative capacity among agricultural producers, stakeholders, and scientists from a broad range of disciplines.
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Agriculture is one of the economic sectors that affect climate change contributing to greenhouse gas emissions directly and indirectly. There is a trend of agricultural greenhouse gas emissions reduction, but any practice in this direction should not affect negatively farm productivity and economics because this would limit its implementation, due to the high global food and feed demand and the competitive environment in this sector. Precision agriculture practices using hightech equipment has the ability to reduce agricultural inputs by site-specific applications, as it better target inputs to spatial and temporal needs of the fields, which can result in lower greenhouse gas emissions. Precision agriculture can also have a positive impact on farm productivity and economics, as it provides higher or equal yields with lower production cost than conventional practices. In this work, precision agriculture technologies that have the potential to mitigate greenhouse gas emissions are presented providing a short description of the technology and the impacts that have been reported in literature on greenhouse gases reduction and the associated impacts on farm productivity and economics. The technologies presented span all agricultural practices, including variable rate sowing/planting, fertilizing, spraying, weeding and irrigation.
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As the LTAR Network designs and develops its data management systems, an LTAR “Information Ecosystem” (Nardi and O’Day, 1999) is envisioned to enable effective communication and collaboration, data sharing policies, standardization of exchange formats for data and metadata, integration of various types of data, and QAQC. We present how LTAR sites, emerging centers for data management, such as the National Agricultural Library, the Center for Agricultural Resources Research, Sustaining the Earth’s Watersheds, Agricultural Research Data System (STEWARDS), Greenhouse gas Reduction through Agricultural Carbon Enhancement Network (GRACEnet), and the new Wind Erosion Network, are identifying existing capacity that can be expanded to meet data management requirements for LTAR.
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Agriculture in the dryland region of the Inland Pacific Northwest (IPNW, including northern Idaho, eastern Washington and northern Oregon) is typically characterized based on annual rainfall and associated distribution of cropping systems that have evolved in response to biophysical and socio-economic factors. Three agro-ecological classes (AEC) have been proposed for the region: (a) crop/fallow (CF), (b) annual crop/fallow transition (CCF), and (c) continuous cropping (CC). AECs attempt to associate land use into relatively homogeneous areas that result in common production systems. Although there is an interest in sustainable intensification of cropping systems (e.g., reduction of fallow), the question remains whether climate change will preclude intensification or shift the borders of existing AECs toward greater fallow utilization. A simulation study was conducted to address this question, with the aim of classifying 4 × 4 km pixels throughout the region into one of the three AECs for baseline (1979–2010) and future periods (2030s, 2015–2045; 2050s, 2035–2065; 2070s, 2055–2085). Baseline data were derived from traditional rotations and historical climate records. Data for future projections were derived from atmospheric CO2 concentration considering daily weather downloaded from 12 global circulation models and 2 representative concentration pathways (RCP 4.5 and 8.5). Due to the direct effect of atmospheric CO2 on photosynthesis and stomatal conductance, the transpiration use efficiency of crops (TUE; g above-ground biomass kg water−1) showed an increasing trend, with winter wheat TUE changing from 4.76 in the historical period to 6.17 and 7.08 g kg−1 in 2070s, depending on AEC. Compared to the baseline, total grain yield by the 2070s in the region was projected to increase in the range of 18–48% (RCP 4.5) and 30–65% (RCP 8.5), depending on AEC. As a consequence of these changes, compared to the historical baseline period, the future fraction of the area classified as CF decreased from 50% to 39–36%, CC increased from 16% to 24–28%, and CCF decreased slightly (~1%), with the greater change projected for the RCP 8.5 scenario.
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The Western Lake Erie Basin (WLEB) was inundated with precipitation during June and July 2015 (two to three times greater than historical averages), which led to significant nutrient loading and the largest in-lake algal bloom on record. Using discharge and concentration data from three spatial scales (0.18–16,000 km²), we contrast the patterns in nitrate (NO3–N) and dissolved reactive phosphorus (DRP) concentration dynamics and discuss potential management implications. Across all scales, NO3–N concentration steadily declined with each subsequent rainfall event as it was flushed from the system. In contrast, DRP concentration persisted, even on soils at or below agronomic P levels, suggesting that legacy P significantly contributes to nutrient loads in the WLEB. These findings highlight the need to revisit current P fertility recommendations and soil testing procedures to increase P fertilizer use efficiency and to more holistically account for legacy P. Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © 2017. . Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Core Ideas Agricultural lands have varying potential based on climate, topography, and soils. Aligning land use and potential improves sustainable delivery of ecosystem services. Integrated agricultural systems (IAS) are uniquely adapted to variable land types. Socioeconomic barriers to IAS implementation are significant. Considerable research and education is needed to facilitate IAS adoption. Contemporary agricultural land use is dominated by an emphasis on provisioning services by applying energy‐intensive inputs through relatively uniform production systems across variable landscapes. This approach to agricultural land use is not sustainable. Achieving sustainable use of agricultural land should instead focus on the application of innovative management systems that provide multiple ecosystem services on lands with varying inherent qualities. Integrated agricultural systems (IAS) represent an alternative approach to prevailing land use, whereby site‐adapted enterprises are implemented to enhance synergistic resource transfer among enterprises and sustainable delivery of ecosystem services. Sustainable deployment of IAS on agricultural land involves placing the “right enterprise” at the “right intensity” at the “right time” on the “right location,” with the inherent attributes of location providing guidance for management decisions. There is an urgent need to design IAS that enhance delivery of ecosystem services while ensuring land potential thresholds are not exceeded.
Core Ideas Soil quality scores were highest in perennial grass systems, followed by a soybean‐dominated rotation, followed by a corn‐based rotation. No‐till crop production had no higher soil quality score than chisel–disk tillage but the uncultivated perennial grass system scored higher than both. In this crop production‐dominated region, soil quality is driven by biological properties like soil C and β‐glucosidase activity and physical properties like bulk density and macroaggregate stability. Soil quality is a critical link between land management and water quality. We aimed to assess soil quality within the Cedar Creek Watershed, a pothole‐dominated subwatershed within the St. Joseph River watershed that drains into the Western Lake Erie Basin in northeastern Indiana. The Soil Management Assessment Framework (SMAF) with 10 soil quality indicators was used to assess inherent and dynamic soil and environmental characteristics across crop rotations, tillage practices, and landscape positions. Surface physical, chemical, and nutrient component indices were high, averaging 90, 93, and 98% of the optimum, respectively. Surface biology had the lowest component score, averaging 69% of the optimum. Crop rotation, tillage, and landscape position effects were assessed using ANOVA. Crop selection had a greater impact on soil quality than tillage, with perennial grass systems having higher values than corn ( Zea mays L.) or soybean [ Glycine max (L.) Merr.]. Furthermore, soybean rotations often scored higher than corn rotations. Uncultivated perennial grass systems had higher overall soil quality index (SQI) values and physical, chemical, and biological component values than no‐till or chisel–disk systems. Chisel–disk effects on overall and component SQI values were generally not significantly different from no‐till management except for a few physical indicators. Toe‐slopes had higher physical, biological, and overall SQI values than summit positions but toe‐slope values were not significantly different from those of mid‐slope positions. This work highlights the positive effects of perennial grass systems, the negative effects of corn‐based systems, and the neutral effects of tillage on soil quality.