ArticlePDF Available

A strategy for Mapping and Modeling the Ecological Effects of US Lawns

  • Institute of Public Health & Environment

Abstract and Figures

Lawns are ubiquitous in the American urban landscapes. However, little is known about their impact on the carbon and water cycles at the national level. The limited information on the total extent and spatial distribution of these ecosystems and the variability in management practices are the major factors complicating this assessment. In this study, relating turf grass area to fractional impervious surface area, it was estimated that potentially 163,812 km 2 (± 35,850 km 2) of land are cultivated with some form of lawn in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC ecosystem process model, the growth of turf grasses was modelled for 865 sites across the 48 conterminous states under different management scenarios, including either removal or recycling of the grass clippings, different nitrogen fertilization rates and two alternative water irrigation practices. The results indicate that well watered and fertilized turf grasses act as a carbon sink, even assuming removal and bagging of the grass clippings after mowing. The potential soil carbon accumulation that could derive from the total surface under turf (up to 25.7 Tg of C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per person per day, depending on the modeled water irrigation practices, and a cost in carbon emissions due to fertilization and operation of mowing equipment ranging from 15 to 35% of the sequestration.
Content may be subject to copyright.
C. Milesia,e, C. D. Elvidgeb, J. B. Dietzc, B. T. Tuttled, R. R. Nemania and S. W. Runninge
aNASA Ames Research Center, Moffett Field, CA 94035, USA,,
bNOAA/National Geophysical Data Center, 325 Broadway, Boulder, CO 80303, USA -
cCooperative Institute for Research on the Atmosphere, Colorado State University, Fort Collins, CO 80309, USA -
dUniversity of Colorado, Cooperative Institute for Research in the Environmental Sciences, 216 UCB, Boulder, CO,
80309, USA -
eNumerical Terradynamic Simulation Group, College of Forestry and Conservation, University of Montana Missoula,
MT 59812, USA
KEY WORDS: turf grasses, residential lawns, BIOME-BGC, impervious surface area, carbon sequestration potential, water use
Lawns are ubiquitous in the American urban landscapes. However, little is known about their impact on the carbon and water
cycles at the national level. The limited information on the total extent and spatial distribution of these ecosystems and the
variability in management practices are the major factors complicating this assessment. In this study, relating turf grass area to
fractional impervious surface area, it was estimated that potentially 163,812 km2 (± 35,850 km2) of land are cultivated with some
form of lawn in the continental United States, an area three times larger than that of any irrigated crop. Using the Biome-BGC
ecosystem process model, the growth of turf grasses was modelled for 865 sites across the 48 conterminous states under different
management scenarios, including either removal or recycling of the grass clippings, different nitrogen fertilization rates and two
alternative water irrigation practices. The results indicate that well watered and fertilized turf grasses act as a carbon sink, even
assuming removal and bagging of the grass clippings after mowing. The potential soil carbon accumulation that could derive from
the total surface under turf (up to 25.7 Tg of C/yr with the simulated scenarios) would require up to 695 to 900 liters of water per
person per day, depending on the modeled water irrigation practices, and a cost in carbon emissions due to fertilization and
operation of mowing equipment ranging from 15 to 35% of the sequestration.
Lawns are ubiquitous in the American urban landscapes, as
they can be found on most residential lots, parks, institutional
and commercial landscapes, and golf courses, often as
monocultures of turf grasses, independently of the local climate
(Jenkins 1994). Existing estimates indicate that in the early
1990’s the surface cultivated with turf was up to three times
larger than that of irrigated corn, the largest irrigated crop in
the U.S. (DPRA, Incorporated 1992).
Turf grasses contribute to soil carbon (C) sequestration
(Bandaranayake et al., 2003; Qian and Follett, 2002; Van
Dersal, 1936) and, as a component of urban vegetation, to the
mitigation of the urban heat island effect (Spronken-Smith et
al., 2000) and to enhanced water infiltration compared to bare
soil or impervious surfaces. However, turf has also been linked
with a number of negative environmental impacts. Turf grasses
often pose a neglected environmental hazard through the use of
lawn chemicals and over-fertilization (Robbins and Sharp,
2003; Robbins et al., 2001), and, where used, irrigation of turf
grasses sharply increases the summer water consumption for
residential and commercial use, especially if grown in arid and
semiarid regions, where it can account for 75% of the total
household water consumption (Mayer et al., 1999).
In spite of the pervading presence of turf grass systems in the
urban and suburban landscape and their considerable use of
water resources, there continues to be little knowledge about
the ecological functioning of these systems at the national
level. If turf grasses are to be considered carbon sequestering
components of the urban ecosystems, what is their contribution
to the national carbon sequestration potential? And what is the
estimated water use to sustain this sequestration potential? The
fragmented distribution of residential and commercial lawns
and the large variability in management practices adopted to
grow the different types of turf surfaces certainly challenges
the task of answering these questions.
In this study we present an estimate of the carbon sequestration
potential of U.S. lawns and the implied water use by producing
a spatially explicit estimate of their distribution within the
contiguous 48 states and simulating their growth with an
ecosystem process model.
2.1 Estimation of U.S. turf surface
Due to its high level of fragmentation, direct mapping of the
total surface under turf in the U.S. is impractical. Past efforts
to estimate the continental surface of turf grasses used indirect
approaches that provided measures of the total surface under
lawn on a state-by-state basis, therefore lacking the spatial
detail required to calculate spatially-dependent biogeochemical
cycles. Vinlove and Torla (1995), for example, estimated the
national total home lawn area using methods based on adjusted
Federal Housing Authority (FHA) average and median lot sizes
by state, without accounting for the turf surfaces found in golf
courses, parks, schools, road sides, etc. DPRA, Incorporated
(1992), estimated the total area under turf on the basis of direct
surveys in 12 states, which were extrapolated to the remaining
states in proportion to their population.
In our study we assumed the surface of turf grasses to be
inversely related to the amount of impervious surface
associated with urban development (roads, roofs, parking lots,
sidewalks, etc.). We used the 1-km gridded fractional cover of
Impervious Surface Area (ISA) for the continental U.S. derived
by Elvidge et al. (2004). Ground calibration for the creation of
this dataset was provided by direct measurements of the
proportion of constructed surface (roads, parking lots,
buildings) versus the proportion of vegetated (turf grasses
and/or trees) or other (undeveloped) surface from 80 high-
resolution aerial photographs collected along development
transect distributed across thirteen major urban centres
distributed across the U.S.
The proportions of impervious versus vegetated surfaces
derived from the high-resolution aerial photography tiles were
used to develop a predictive relationship between the fractional
ISA and the combined fraction of turf and tree surface, given
that turf was present under the trees observed in the samples.
For this model, only samples over areas with more than 10%
fractional ISA were used, leaving out the sparsely developed
urban fringes, where the occurrence of very low development
density is often associated with forested and other non-turf
vegetated surfaces. The predictive model showed a moderately
strong (R-square=0.69), highly significant (p-value < .0001,
RMSE = 11.2) relationship between fractional ISA and
fractional turf grass area and was subsequently applied to the
conterminous U.S. to produce a 1-km grid of fractional turf
area (Figure 1). For full details on the estimation of the
continental area under turf refer to Milesi et al. (2005).
2.2 Modelling of turf grasses growth
Management of turf grasses is highly variable, and can range
from high maintenance golf courses and athletic fields, which
require high doses of fertilizer, to some residential lawns that
are not adequately watered and fertilized, spending part of the
growing season in a dormant stage. Many residential lawns, on
the other hand, are managed by homeowners who pay little
attention to the amount of resources invested for lawn
maintenance and often receive excess water and fertilizer.
Variability exists also in the fate of the clippings, which are
either mulched and left decompose on the grass (recycling part
of the nitrogen fertilizer) or removed, and composted or bagged
and sent to the landfill. In this study the simulation of the
impact of different turf grass management practices on the
continental C sequestration potential and water budget was
based on the simplifying assumption that, under a given
scenario, the entire turf surface is managed homogeneously,
such as irrigated with the same criteria, fertilized with the
same amount of N and mowed at the same height, whether it
would be part of a residential lawn or a golf course.
We adapted the Biome-BGC ecosystems process model
(Thornton et al., 2002; White et al., 2000) to predict C and
water fluxes of cool season (C3) and warm season (C4) grasses
turf ecosystems at 865 sites distributed across the U.S.
Mowing activities were simulated as mortality processes that
would remove 20% of the leaf area index (LAI) and of the fine
roots every time the LAI reached a critical value of 1.5.
Removal of the clippings was simulated by removing the
portion of C and N associated with the cut leaves from the
ecosystem process. In the cycling scenario, the C and N
associated with the cut leaves were left on the site to
decompose as litter. To evaluate the effect of clipping cycling
on grasses N availability, N was applied at two different rates
in contrasting simulation runs. Clippings were either removed
or cycled in scenarios simulating an application of 146 kg
N/ha/yr and cycled in scenarios with an application of 73 kg
Irrigation during the growing season was simulated by adding
water to the precipitation field in the 18-year 1-km gridded
climate data obtained from the Daymet dataset (Thornton et
al., 1997). We assumed that the sprinkling season of a certain
location would start when the minimum temperatures remained
above 5 °C for seven consecutive days in the spring, and end
when minimum temperatures decreased below 5 °C for seven
consecutive days in the fall, as plants growth requires
temperatures above freezing to take place. Two watering
management scenarios were simulated. In one type of watering
management we followed the common recommendation that
during the growing season turf grasses require about 2.54 cm
(1 inch) of water per week (Schultz, 1999). In the simulations,
in the case of rainfall, rain made up for part of this amount.
The alternative watering management scenario, rather than
providing a fixed weekly amount of water, modulated the
irrigation based on the potential evapotranspiration (PET) and
precipitation, in this case calculated according to Priestly and
Taylor (1972). In this case, irrigation was simulated to be
triggered when the PET minus precipitation, accumulated since
the last watering event, exceeded 60% of the added water.
Irrigation then replaced 20% of the PET, bringing the water
availability to nearly 80% of PET. The effect of the two
different water management practices on the C and water
balance was evaluated comparing scenarios in which N added
through fertilization was constant and irrigation was either
fixed at 2.54 cm of water/week or modulated according to PET.
The simulation sites were assumed to grow either C3 (cool
season) or C4 (warm season) turf grasses, or an equal mix of
the two in the transitional region, based on adaptation zones
(Beard 1973).
The growth of turf grasses at the 865 sites was simulated for
the following five different scenarios:
Control: turf grasses growth was simulated with no
management (no irrigation and no N fertilization) except for
cycling of the clippings;
Removed-146N: the grass was irrigated during the growing
season so that a total of 2.54 cm of water per week was
provided, fertilized with 146 kg N/ha/yr, and the clippings
were removed from the system after each mowing event;
Cycled-146N: same as Removed-146N, except for the
clippings, which were left on the site after each mowing event;
Cycled-73N: same as Cycled-146N, except for the amount of
fertilizer, which was halved to 73 kg N/ha/yr;
Cycled-73N-PET: same as Cycled-73N, except for the
irrigation management, which was calculated based on
Priestly-Taylor PET.
More details on the simulation methods can be found in Milesi
et al. (2005).
The simulation results were extrapolated to the continental
surface assuming that turf areas in the vicinity of a simulation
site displayed similar C and water fluxes. The continental U.S.
was divided into Thiessen polygons centered on the simulation
sites and the output results at each simulation site were then
multiplied by the total turf area estimated within the respective
3.1 Estimation of turf grass area
The total turf grass area estimated in this analysis summed up
to 163,812 km2 (± 35,850 km2 for the upper and lower 95%
confidence interval bounds). This estimate, intended to include
all residential, commercial, and institutional lawns, parks, golf
courses and athletic fields, accounts for approximately 1.9% of
the total continental U.S. area, which compares with 3.5-4.9%
of the total surface estimated to be devoted to urban
development (Nowak et al., 2001; National Association of
Realtors, 2001). Our estimate is compatible with the results
from other studies, in particular when considering the recent
growth in population and urban areas in the U.S. (Fulton et al.,
2001). DPRA, Incorporated (1992), assuming turf surface to be
directly related to the population, estimated a total surface of
188,180 km2, among which 94,090 km2 of home lawns
(Grounds Maintenance, 1996). A 1987 study by Roberts and
Roberts (1987), estimated a total surface of 100,000-120,000
km2. Another study, focusing only on residential lawns,
analyzing state-based average lot sizes of single family homes,
estimated a total home lawn area ranging between 58,000 km2
and 71,680 km2, considerably downsizing DPRA’s estimate of
home lawns (Vinlove and Torla, 1995). One of the earliest
estimates of total turf surface dates back to the late 1960’s,
when it was reported that 67,000 km2 of lawn existed
nationally (Falk, 1976).
Even when the estimate of total surface is considered to be
closer to the lower bound of the 95% confidence interval
(127,962 km2), it appears that turf grasses would represent the
single largest irrigated “crop” in the U.S., occupying a total
area three times larger than the surface of irrigated corn
(43,000 km2 according to the 1997 Census of Agriculture, out
of 202,000 km2 of total irrigated cropland area).
Figure 1. Distribution of the fractional turf grass area (%) in
the conterminous U.S.
3.2 Water budget
The two alternate irrigation methods produced watering
requirements that varied widely across the climatic regions of
the 48 states. In general, a fixed irrigation management based
on turf requirements of 2.54 cm of water per week, including
rainfall, resulted in a minimum of no irrigation in Lincoln
Park, Michigan (meaning that here rainfall alone is able to
satisfy the watering requirements of the turf throughout the
growing season) to a maximum of 125 cm of water per year to
be added through irrigation in Yuma, Arizona. In contrast, the
irrigation management based on PET tended to decrease the
amount of water supplied through irrigation in wet regions and
increase it in arid and semiarid regions of the U.S., where it
was by far larger than 2.54 cm/week. Modulating irrigation
according to PET required a minimum of 17 cm/yr of water to
be added through irrigation in Pensacola, Florida, to a
maximum of 197 cm/yr in Yuma, Arizona. A Mann-Whitney
U-test for differences indicated that the two irrigation methods
would provide significantly different annual amounts of water
at 77% of the 865 sites, with a larger amount of water
sprinkled in the West and less water in the humid southeastern
Extrapolating the water use for irrigation with the two methods
at each of the 865 sites to the surface of turf grasses contained
in the respective Thiessen polygons yields an average total of
73,560 Mm3 (Mega cubic meters) of water with the constant
2.54 cm/week method and 95,100 Mm3 of water with the PET
method, while rain contribution during the sprinkling season to
the watering of the total estimated turf grass area would
amount to 99,130 Mm3 (Figure 2).
These estimates indicate that, in the scenario that the entire
turf surface in the U.S. was to be irrigated to satisfy the 2.54
cm/week water supply or at 80% of PET, domestic and
commercial consumptive water use would be, respectively, 695
to 900 liters of water per person per day. Noteworthy is that in
spite of the elevated irrigation requirements, there appears to
be a considerable amount of water leaving the soil layer as
outflow (water in excess of field capacity) rather than
evapotranspiration (56,620 to 57,670 Mm3 of water, depending
on the irrigation management scenarios). 90% of the estimated
outflow takes place in the eastern and southern U.S., where it
is related to rainfall rather than sprinkling events. In occasion
of abundant rainfall, precipitation is larger than the soil water
holding capacity and leaves the soil before the grass can use it
for evapotranspiration. In spite of a surplus of available water
during the rainy periods, sprinkling is still required during the
drier periods.
If irrigation could just replace actual evapotranspirational
losses, the water to be added through sprinkling would amount
to 11,070 Mm3 in the case of the 2.54 cm/week method and
33,300 Mm3 with the PET-based method. The increase in the
water requirements with the PET-based method has to be
attributed to the arid western U.S., where grasses can
evaporate much more than 2.54 cm of water per week if more
irrigation is supplied. Still, part of the water reaching the
surface during the growing season, either from precipitation
when abundant rainfall occurs, or from the sprinkler, due to
Priestly-Taylor PET overestimating actual evapotranspiration,
would not be used by the grass and leave the soil layer as
Figure 2. Water budgets of the total U.S. surface for the forus
management scenarios. Error bars indicate budget
values calculated for 95% confidence interval lower
and upper buond estimate of total turf surface.
3.3 Soil carbon sequestration potential
The model simulation results referring to the C accumulating
in soils in the five different management scenarios are reported
in Table 1. The values represent the range in simulated soil C
accumulation over the 18-year period of climate data for the
865 locations.
A comparison of the results under the 5 management scenarios
reflects the notion that N fertilization increases the
accumulation of carbon in the soil. For a certain amount of N
input through fertilization, the C accumulations were larger
when cycling of the grass clippings was simulated, since the
onsite decomposition of the mowed grass clippings returned a
consistent amount of N to the soil. For each scenario,
differences in the maximumminimum range were related
mainly to the growing season length.
The control scenario produced the lowest carbon accumulation
(an average of 88 g C/m2 over 18 years). The low number of
mowing counts produced by the model in this scenario suggests
that in most locations (most of the simulation sites except a
few in the northeastern US) it would be impossible to grow a
lawn as a monoculture of turf grasses with no irrigation and
fertilization. If turf grasses reach an LAI of 1.5 only 6-7 times
in areas where the growing season is as long as 300-360 days,
then it is probable that between subsequent cuts there would
be several opportunities for non-turf species to invade the
surface and prosper over time.
The largest C accumulation was simulated for scenario Cycled-
146N. Abundant fertilization (146 kg N/ha/yr) and the
recycling of the N contained in the clippings left to decompose
on the site produced an average C accumulation potential of
1978 g C/m2 over 18 years.
The second largest soil C accumulations were simulated for
scenarios Cycled-73N and Cycled-73N-PET, with an average
reduction of 43% in C accumulation when compared with that
simulated for Cycled-146N but with 50% less fertilizer. For
Cycled-73N and Cycled-73N-PET the different water
management had no significant effect on the carbon cycle.
In scenario Removed-146N, where the clippings are removed,
the soil C accumulation was 60% less than in scenario Cycled-
146N, although the same amount of external N was applied but
no internal N recycling was allowed to take place because of
the removal of the clippings.
146N Cycled-
146N Cycled-
73N Cycled-
Soil C
(g C m-2 yr-1)
-8 – 7
27 – 60
64 – 149
37 – 67
37 – 67
(g C m2 18-yr-) 88 783 1978 1122 1119
counts 0 – 7
16 – 52
22 – 98
14 – 55
16 – 56
Table 1. Minimum and maximum values of the modelled
annual gross soil C accumulation, 18-year
increment in soil C, and mowing counts.
In the managed scenarios turf grasses present average annual
increments in soil carbon comparable to the rates observed for
crops cultivated with no-till practices (Ismail et al., 1994).
Large differences in total C sequestration can be realized under
the same irrigation management of 2.54 cm of water per week,
all resulting in very large losses of water through outflow
(Figure 2). This result is most probably explained by the fact
that in all the simulated management scenarios water is not
limiting growth, which responds rather to increases in N
availability. The large increase in water application observed
when modulating irrigation according to PET, on the other
hand, results in an insignificant change in C fluxes, indicating
that the water is lost in luxury evapotranspiration.
Extrapolating the simulation results from the 865 sites to the
total surface potentially under turf continental U.S., the total
gross soil carbon sequestration ranged from 10.4 Tg C/yr in the
Removed-146N scenario to 25.7 Tg C/yr in the Cycled-146N
scenario (Figure 3). A modest 1.2 Tg C/yr was obtained from
the unmanaged control scenario, since in most of the country
turf grasses would not be able to survive without irrigation and
fertilization. While the highest availability of N in the Cycled-
146N scenario also produces the highest gross C sequestration
potential, halving the input of external fertilizer to 73 kg
N/ha/yr and recycling the clippings appears to be a more
efficient approach to soil C accumulation than fertilizing with
146 kg N/ha/yr and removing the clippings.
Figure 3. Annual gross soil carbon sequestration and C costs
due to N fertilizer and lawn mower operation
From the perspective of evaluating the ecological effects of
lawns in the U.S., the gross soil C sequestration potential
values estimated from the model runs have to be discounted by
the C emissions involved. At least two sources of emissions
implied in the assumptions of this analysis can be quantified
here. For example, there are emissions associated with N
fertilization. While the input of N increases the soil C
accumulation potential, there is a linear increase in C
emissions attributable to the synthesis, transport and
commercialisation of the fertilizer, which is estimated around
1.4 moles of C per mole of N (Schlesinger, 2000). In scenarios
Removed-146N and Cycled-146N, where 2.4 Tg N/yr would be
distributed over the entire area potentially under turf,
fertilization would contribute to 2.9 Tg C/yr, or 28% to 11% of
the soil C sequestration respectively (Figure 3). In scenarios
Cycled-73N and Cycled-73N-PET, the N fertilizer C “cost”
would amount to 10% of the soil C sequestration potential.
A conservative estimate of the C emissions deriving from the
operation of lawn mowers can be attempted using data from
Christensen at al. (2001), reporting the emissions from a small
engine 4-stroke lawn mower. Considering an emission rate of
250 g C/h and assuming an average mowing speed of 2000
m2/hr, lawn mower emissions for the entire surface potentially
under turf would range from 0.7 to 1.1 Tg C/yr depending on
the management scenario, and only 0.1g TgC/yr in the control
scenario (Figure 3). Adding the lawn mower C emissions to the
N fertilizer related emissions would reduce the total gross C
sequestration potential of lawns by 35% in the Removed-146N
scenario and by about 15% in the other management scenarios.
Further reductions in the C sequestration potential that cannot
be accounted for with the available data are possibly connected
with irrigation practices, especially were pumping is involved,
and with the disposal of lawn clippings in landfills.
In this study we mapped the total surface of turf grasses in the
continental U.S. and simulated its water use and C
sequestration potential under different management practices
for irrigation, fertilization and fate of the clippings. Rather
than trying to accurately quantify the existing fluxes, we
simulated scenarios in which the entire surface was to be
managed like a well-maintained lawn, a thick green carpet of
turf grasses, watered, fertilized and kept regularly mown. The
accuracy of the results is therefore limited by both the
uncertainty in the mapping of the total lawn area and by the
simplifying assumptions made while modeling turf grasses
The analysis indicates that turf grasses, occupying about 2% of
the surface of the continental U.S., would be the single largest
irrigated crop in the country. The scenarios described in this
study also indicate that a well-maintained lawn is a C
sequestering system, although the positive C balance
discounted for the hidden costs associated with N-fertilizer and
the operation of lawn mowers comes at the expense of a very
large use of water, N, and, not quantified in this study,
pesticides. The model simulations have assumed a
conservative amount of fertilization (a maximum of 146 kg
N/ha/yr). In general the rates of N applications are similar to
those used for row crops, and the current high-input choices
made by consumers and professional turf managers for
maintaining monocultures of turf grasses typical of many lawns
and play fields comes at the risk, not analyzed here, of
watershed pollution due to improper fertilization and use of
If the entire turf surface was well watered following commonly
recommended schedules there would also be an enormous
pressure on the U.S. water resources, especially when
considering that drinking water is usually sprinkled. At the
time of this writing, in most regions outdoor water use already
reaches 50-75% of the total residential use. Because of
demographic growth and because more and more people are
moving towards the warmer regions of the country the potential
exists for the amount of water used for turf grasses to increase.
Beneficial effects of turf grasses, such as a carbon
sequestration but also recreation, storm runoff reduction due to
increased soil infiltration in occasion of intense rainfall, and
removal of impurities and chemicals during percolation of the
water through the root zone, could be sought by minimizing the
application of fertilizers and pesticides, introduction of lower
input species mixes such as clover and other so-called weeds
(Bormann, 1993), on site decomposition of the grass clippings
and extending the practice of irrigating with waste water rather
than with drinking water.
This study was supported by the NASA Earth System Science
Fellowship program to the first author and by the NASA Land
Cover Land Use Change research program.
Bandaranayake, W., Y.L. Qian, W.J. Parton, D.S. Ojima, and
R.F. Follett, 2003. Estimation of soil organic carbon changes in
turfgrass systems using the CENTURY model. Agronomy
Journal, (95) pp. 558-563.
Beard, J.B. 1973, Turfgrass: science and culture. Prentice
Hall, Englewood Cliffs, NJ, 658 pp.
Bormann, F. H., D. Balmori, G.T. Geballe, 1993. Redesigning
the American lawn: A search for environmental harmony. Yale
University Press, New Haven and London. 148 pp.
Christensen, A., R. Westerholm, J. Almén, 2001. Measurement
of regulated and unregulated exhaust emissions from a lawn
mower with and without an oxidizing catalyst: a comparison of
two different fuels. Environmental Science and Technology,
(35) pp. 2166-2170.
DPRA, Incorporated, 1992. Benefit analysis of insecticide us
on turf: Preliminary biological and economic profile report.
Unpublished Interim Report, Manhattan, Kansas.
Elvidge C.D., C. Milesi, J.B. Dietz, B.J. Tuttle, P.C. Sutton, R.
Nemani and J.E. Vogelmann, 2004. U.S. Constructed Area
Approaches the Size of Ohio. Eos, Transactions, American
Geophysical Union, (85), pp. 233.
Falk, J.H. 1976, Energetics of a suburban lawn ecosystem.
Ecology, (57), pp. 141-150.
Fulton, W., R. Pendall, M. Nguyen, and A. Harrison, 2001.
Who sprawls the most? How growth patterns differ across the
U.S. The Brookings Institution Survey Series. 24 pp.
Grounds Maintenance, 1996. Turf acreage. Grounds
Maintenance, (31), p. 10.
Ismail, I., R.L. Blevins, and W.W. Frye, 1994. Long-term no-
tillage effects on soil properties and continuous corn yields.
Soil Science Society of America Journal, (58), pp. 193-198.
Jenkins, V.S. 1994. The Lawn: A History of an American
Obsession. Smithsonian Institution Press, Washington, DC,
246 pp.
Mayer, P.W., W.B. DeOreo, E.M. Opitz, J.C. Kiefer, W.Y.
Davis, B. Dziegielewski, and J.O. Nelson, 1999. Residential
End Uses of Water. American Water Works Association. 310
Milesi, C., C.D. Elvidge, J.B. Dietz, B.J. Tuttle, R.R. Nemani,
and S.W. Running, 2005. Mapping and modeling the
biogeochemical cycling of turf grasses in the United States.
Environmental Management, Accepted.
National Association of Realtors, 2001. Land use and land loss
in the United States: the impact of land use trends on real
estate development, The Research Division of the National
Association of Realtors. 9 pp.
Nowak, D.J., M.H. Noble, S.M. Sisinni, and J.F. Dwyer, 2001.
People & trees: Assessing the US urban forest resource.
Journal of Forestry, (99), pp. 37-42.
Priestley, C.H.B., and R.J. Taylor, 1972. On the assessment of
surface heat flux and evaporation using large-scale parameters.
Monthly Weather Review, (100), pp. 81-92.
Qian, Y., and R.F. Follett, 2002. Assessing soil carbon
sequestration in turfgrass systems using long-term soil testing
data. Agronomy Journal, (94), pp. 930-935.
Roberts, E.C. and B.C. Roberts, 1987. Lawn and Sports Turf
Benefits. The Lawn Institute, Pleasant Hill, TN, 31 pp.
Robbins, P., A. Polderman, and T. Birkenholtz, 2001. Lawns
and toxins: an ecology of the city. Cities, (18), pp. 369-380.
Robbins, P. and J. Sharp, 2003. Producing and consuming
chemicals: The moral economy of the American lawn.
Economic Geography, (79), pp. 425-451.
Schlesinger, W.H., 2000. Carbon sequestration in soils: some
cautions amidst optimism. Agriculture, Ecosystems and
Environment, (82), pp. 121-127.
Schultz, W., 1999. A man's turf: the perfect lawn. Clarkson N.
Potter, New York, 180 pp.
Spronken-Smith, R.A., T.R. Oke, and W.P. Lowry, 2000.
Advection and the surface energy balance across an irrigated
urban park. International Journal of Climatology, (20), pp.
Thornton P.E., B.E. Law, H.L. Gholz, K.L. Clark, E. Falge,
D.S. Ellsworth, A.H. Goldstein, R.K. Monson, D. Hollinger,
M. Falk, J. Chen, and J.P. Sparks, 2002. Modeling and
measuring the effects of disturbance history and climate on
carbon and water budgets in evergreen needleleaf forests.
Agricultural and Forest Meteorology, (113), pp. 185-222.
Thornton, P.E., S.W. Running, and M.A. White. 1997.
Generating surfaces of daily meteorological variables over
large regions of complex terrain. Journal of Hydrology
Van Dersal, W. 1936. The ecology of a lawn. Ecology 17:515-
Vinlove, F.K., and R.F. Torla. 1995. Comparative estimations
of U.S. home lawn area. Journal of Turfgrass Management
White, M., P. Thornton, S. Running, and R. Nemani, 2000.
Parameterization and sensitivity analysis of the BIOME-BGC
terrestrial ecosystem model: net primary production controls.
Earth Interactions, (4), pp. 1-85.
... Turf is the predominant vegetation cover in urban landscapes, golf courses, residential lawns, and sports fields. In the United States, it was estimated that the total turf area covers 163,812 km 2 with a lower and upper 95% confidence interval bounds of ±35,850 km 2 [1]. According to the National Golf Foundation, there are over 15,000 golf courses, with an average of 50 to 73 ha per golf course, in the United States [2]. ...
Full-text available
Precision spraying can significantly reduce herbicide input for turf weed management. A major challenge for autonomous precision herbicide spraying is to accurately and reliably detect weeds growing in turf. Deep convolutional neural networks (DCNNs), an important artificial intelligent tool, demonstrated extraordinary capability to learn complex features from images. The feasibility of using DCNNs, including various image classification or object detection neural networks, has been investigated to detect weeds growing in turf. Due to the high level of performance of weed detection, DCNNs are suitable for the ground-based detection and discrimination of weeds growing in turf. However, reliable weed detection may be subject to the influence of weeds (e.g., biotypes, species, densities, and growth stages) and turf factors (e.g., turf quality, mowing height, and dormancy vs. non-dormancy). The present review article summarizes the previous research findings using DCNNs as the machine vision decision system of smart sprayers for precision herbicide spraying, with the aim of providing insights into future research.
... Turf is the predominant vegetation cover in urban landscapes, such as athletic fields, institutional and residential lawns, parks, and golf courses [1]. Weeds can be a significant challenge for turf management. ...
Full-text available
Background Precision spraying of postemergence herbicides according to the herbicide weed control spectrum can substantially reduce herbicide input. The objective of this research was to evaluate the effectiveness of using deep convolutional neural networks (DCNNs) for detecting and discriminating weeds growing in turfgrass based on their susceptibility to ACCase-inhibiting and synthetic auxin herbicides. Results GoogLeNet, MobileNet-v3, ShuffleNet-v2, and VGGNet were trained to discriminate the vegetation into three categories based on the herbicide weed control spectrum: weeds susceptible to ACCase-inhibiting herbicides, weeds susceptible to synthetic auxin herbicides, and turfgrass without weed infestation (no herbicide). ShuffleNet-v2 and VGGNet showed high overall accuracy (≥ 0.999) and F 1 scores (≥ 0.998) in the validation and testing datasets to detect and discriminate weeds susceptible to ACCase-inhibiting and synthetic auxin herbicides. The inference time of ShuffleNet-v2 was similar to MobileNet-v3, but noticeably faster than GoogLeNet and VGGNet. ShuffleNet-v2 was the most efficient and reliable model among the neural networks evaluated. Conclusion These results demonstrated that the DCNNs trained based on the herbicide weed control spectrum could detect and discriminate weeds based on their susceptibility to selective herbicides, allowing the precision spraying of particular herbicides to susceptible weeds and thereby saving more herbicides. The proposed method can be used in a machine vision-based autonomous spot-spraying system of smart sprayers.
... Farm houses also have illegal construction within their premises, there by violating the court orders. The maintenance of lawns and trees in the farmhouses in affluent neighbourhood is very much water intensive, thereby leading to lowering of ground water table in the region (Milesi et al., 2005). Thus individual effort of managing their lawns and stringent government policies associated with water use and rainwater harvesting can deter the negative effects of excessive water use (Runfola et al 2013).The emergence of farmhouse in the peri-urban Delhi has brought deeper changes in the socioeconomic and spatial organization of the traditional agricultural communities living in the vicinity of the farmhouses (Kaushik 2016).Some of the farmhouses used for commercial purpose also pose social threat and disturb the peace and tranquillity of the region, with lots of noise and nuisance during festive seasons. ...
Full-text available
Peri-urban areas are the most ecologically and socially fragile areas of the city undergoing rapid urbanization. Delhi’s peri urban area is experiencing rapid urbanisation in conjunction with booming real estate market, leading to development of the farmhouses often on previously cultivated land. Thus, effect of the advent of farmhouses on green cover needs to be understood. This study, therefore, examines the relation between farm houses and vegetation cover in the world’s second most populated city, Delhi. Satellite images of 1973, 1986, 1996, 2005 and 2017 have been used to map the changes in land use and land cover. Information from Google Earth imagery and field observations were used to delineate spatial boundaries of the farm houses, which were then integrated with the land use land cover map for analysis. Results indicate that the vegetation cover increased in the landscape with the establishment of farm houses. This is probably due to the farm house owner’s affordability, aesthetic choice and effective law enforcement. Maintenance of lush green vegetation and manicured lawns in Delhi’s semi-arid climate requires extensive watering, thereby leading to depletion of water table in the region. This calls for concomitant involvement and action of the government, farmhouse owners and local residents for active land management for ensuring better quality of life of the people and enhanced biodiversity.
... Despite the benefits of native plant gardening, lawns are still popular in U.S. residential areas. American turfgrass lawns take up three times more land than corn, making it the largest irrigated crop in the U.S. (Milesi et al., 2005). When making decisions about yards, people are influenced by social factors ranging from the individual scale (e.g., attitudes, beliefs), to the community (e.g., community associations) and institutional (e.g., rebates for replacing lawns) scale . ...
While studies have examined factors influencing individual pro-environmental behavior, less research has examined the drivers of “diffusion behaviors” that disseminate new information via social networks. We conducted a survey of single-family households (n = 337) using an expanded Integrated Model of Behavioral Prediction to investigate the social-psychological drivers of individual and diffusion behavioral intentions for native plant gardening. We also examined how intentions related to actual behavior and potential moderators of the intention-behavior relationship. We found that while individual behavior-specific knowledge and attitude predict both individual and diffusion intentions, behavior-specific personal norms and self-efficacy predicted diffusion intention, and behavior-specific personal norm influenced individual intention. Contrary to theory, diffusion intentions were influenced by a combination of behavior-specific and non-specific predictors. These results suggest that to motivate diffusion intention, outreach interventions may need to enhance diffusion-specific personal norm and self-efficacy beliefs, rather than just individual behavioral perceptions. Intentions predicted indicators of actual diffusion behavior, as measured through native plant voucher use by individuals and their friends and family. However, these indicators of behavior were not predicted directly by social-psychological variables. Diffusion-specific self-efficacy and subjective knowledge appear to moderate the relationship between diffusion intentions and successful diffusion behavior.
... Turfgrass is an essential component of urban and suburban landscapes (Beard and Green, 1994;Monteiro, 2017). In the United States, turfgrass covers 163,812 km 2 , approximately 1.9% of the total residential and commercial land area (Milesi et al., 2005). Furthermore, these turfgrass lawns are expected to expand in coverage with increased urbanization (Robbins and Birkenholtz, 2003). ...
The occurrence and abundance of predatory fauna in turfgrass systems have been reported; however, the activity of predators has rarely been described. The fall armyworm Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae) is a major pest of turfgrass in the United States for which arthropod predation is not considered a key pest management option, but the role of predation on S. frugiperda has not been assessed in turfgrass systems, which are managed at varying intensities. Thus, the objective of this study was to determine (1) the incidence and (2) the severity of predation in less intensively managed residential lawns and intensively managed sod farms. The percentage of predation on live S. frugiperda sentinel larvae and the percentage of predation and its severity on clay models were significantly greater in the residential lawns than in the sod farms. Among the seven impression types recorded on clay models, paired marks were the most abundant. Four new impression types, deep cut marks, stacked surface marks, scooped marks, and U-shaped marks, were observed on clay models in both turfgrass systems. Formicids were documented at significantly greater densities than were other predatory groups, such as carabids. Thus, the results show the need for enhanced predatory activity in sod farms by developing integrated pest management strategies and adopting measures to conserve natural enemies.
... Turfgrass is a major part of the urban landscape found on lawns, athletic fields, golf courses, cemeteries, parks, exposition and fairgrounds, and many other places (Jenkins, 2015;Milesi et al., 2005;Robbins, 2012). The pervasive feature of the home lawn can be explained by its economic and environmental benefits that few other landscapes can offer. ...
Full-text available
Important financial savings, along with reductions in environmental impact, can be achieved by planting lawns with low-input turfgrass species. Drawing on data from an online survey, this article provides empirical evidence on the factors that influence consumers’ willingness to adopt low-input turfgrasses. We group consumers into two segments: Willing Adopters and Reluctant Homeowners . Regardless of segment, consumers who regard maintenance requirements as more important were more willing to adopt low-input turfgrasses, whereas those who placed a higher value on appearance, were more unlikely to change to a low-input turfgrass, especially for Reluctant Homeowners . We categorized the barriers to adoption as follows: 1) Promotion, 2) Benefits and Accessibility, 3) Peer Effect, 4) Sample, and 5) Information. Our models predict that consumers’ willingness to adopt low-input turfgrass can be significantly increased if the identified barriers are removed. Based on our study, suppliers/retailers should adopt heterogeneous and multiple marketing strategies, such as promoting through multiple channels, informing and advising the public on proper information, providing photos or exhibiting in-store samples, triggering communication between different types of consumers, and providing incentives and improving accessibility, to target different consumer groups.
Nitrous oxide (N2O) is an ozone-depleting gas and important greenhouse gas (GHG) that has been implicated in global climate change. Irrigated and N-fertilized turfgrass systems cover large areas of land and emit N2O. DAYCENT and Denitrification-Decomposition (DNDC) are two widely used process-based models that predict GHG fluxes in agricultural lands. Despite many experiments applying these models to other cropping systems, they have not been applied to warm-season (C4) turfgrass systems. Our objectives were to 1) calibrate DAYCENT and DNDC for N2O emissions from ‘Meyer’ zoysiagrass (Zoysia japonica Steud., referred to as zoysia); 2) validate both models and compare their prediction accuracies; and 3) predict long-term impacts of different N fertilization and irrigation management. A combination of global sensitivity analysis and a Bayesian method was used to calibrate DAYCENT and DNDC, followed by validation, using measurements from zoysia field studies. Validation results indicated DAYCENT (R² = 0.30–0.90; relative RMSE = 30–163%) outperformed DNDC (R² = 0.01–0.38; relative RMSE = 119–183%) in biweekly N2O fluxes. Annual N2O emissions from DAYCENT were validated within − 54 to + 14% of estimates interpolated from measurements of different N fertilization and irrigation management, whereas DNDC simulations generally underestimated emissions by − 24 to − 85%. DAYCENT, but not DNDC, adequately simulated the impacts of irrigation and N-fertilization practices on N2O emissions in zoysia, a C4 turfgrass. DAYCENT predicted that typical N-fertilization and irrigation practices in fairway zoysia turf would reduce net global warming potential (GWP) better than no N fertilization by encouraging soil carbon sequestration in the first 30–45 years of establishment. Instead of fixed-amount or no N inputs, gradually reducing N fertilization to maintain turfgrass growth over decades would mitigate the increases of net GWP and better alleviate climate challenges in this century.
Returning turfgrass clippings to soil (i.e., mulching) has been shown to yield many benefits, such as reducing fertilizer requirements. However, previous reports on the contribution of clippings to turfgrass fertilization varies widely, making it difficult for turfgrass managers to adjust their fertilization practices. Other potential benefits of this practice, such as soil water conservation, still need to be quantified. The objectives of this project were to measure the contribution of Kentucky bluegrass clippings to N, P and K fertilization under four different N levels and to measure the impact of clippings management on turfgrass color (NDVI), soil nutrient and water content as well as thatch accumulation. A field experiment was conducted over three years, with treatments consisting of two clipping management strategies (returned or removed) and four nitrogen levels (0, 48, 96 and 144 kg N ha −1 yr −1). Clippings were collected on every mowing date and were analyzed for N, P and K foliar content. Soil volumetric water content and NDVI were measured weekly, while thatch accumulation and soil chemical content (Mehlich-3) were assessed twice per year. Increasing N fertilization resulted in an increase in both clippings dry matter yield (DMY) and foliar N concentration. Returning grass clippings was equivalent to doubling the amount of N applied through the fertilizer and resulted in an increase in turfgrass color and soil P and K levels. For P and K, clippings contribution was more affected by their DMY than by foliar concentrations. Grass clippings did not contribute to thatch accumulation, but resulted in a consistent increase (3.9% on average) in soil volumetric water content.
This chapter briefly describes agriculture technologies, including a brief historical overview, and explains major drivers that shape modern agriculture. It introduces major crops and domestic animals and explains why and how we domesticate them. Finally, this chapter deals with major ways by which agricultural intensification in plant production and animal husbandry is reached and explores the impact those approaches have on various component of ecosystem including biodiversity, nutrient cycling energy flows soils, water, etc. Special attention is paid to interaction of agriculture and ongoing global change.
Full-text available
ABSTRACT,ational facilities, and other greenbelts. Turfgrass ecosys- tems provide excellent soil erosion control, dust stabili- Soil organic C (SOC) directly affects soil quality by influencing zation, flood control, and urban heat dissipation. These aeration and water retention and serving as a major repository and reserve source of plant nutrients. Limited information is available grasslands may act as C sinks, absorbing more CO2 than concerning the long-term SOC changes in turfgrass systselection, mowing, and irrigation management. 0.83 for putting greens. Our results suggest that the CENTURY model Organic C change in soil is a slow process, and many can be used to simulate SOC changes in turfgrass systems and has the years and decades of measurements,are needed,to assess potential to compare C sequestration under various turf management C changes,as influenced,by,management,practices. conditions. Simulation results also suggest that warming temperatures Therefore, evaluation of different management options have greater degree of influence on SOC in turf systems compared with native grasslands.,relative to C sequestration is difficult to accomplish by sampling,and measuring,SOC content and C fractions over time. Simulation models,offer the opportunity,to predict long-term trends based on mathematical,repre- U nderstanding,long-term,SOC changes,in various sentations of nutrient-cycling processes in the soil–plant ecosystems,is of importance,because SOC directly systems. Predictive modeling,exercises allow significant affects soil quality by influencing the air-filled porosity insight into the ecosystem,dynamics. A number,of com- and water retention and serving as a major,repository puter models are available to evaluate SOC dynamics and reserve source of plant nutrients, especially N, P,
Full-text available
As part of the urbanization process, an increasing percentage of land throughout the USA is being converted into turfgrass. Because of high productivity and lack of soil disturbance, turfgrass may be making substantial contributions to sequester atmospheric C. To determine the rate and capacity of soil C sequestration, we compiled historic soil-testing data from parts of 15 golf courses that were near metropolitan Denver and Fort Collins, CO, and one golf course near Saratoga, WY. In addition, we compiled a total of about 690 data sets on previous land use, soil texture, grass species and type, fertilization rate, irrigation, and other management practices. The oldest golf course was 45 yr old in 2000, and the newest golf course was 1.5 yr old. Nonlinear regression analysis of compiled historic data indicated a strong pattern of soil organic matter (SOM) response to decades of turfgrass culture. Total C sequestration continued for up to about 31 yr in fairways and 45 yr in putting greens. However, the most rapid increase occurred during the first 25 to 30 yr after turfgrass establishment, at average rates approaching 0.9 and 1.0 t ha-1 yr-1 for fairways and putting greens, respectively. Our study also found that past land use imparted a strong control of SOM baseline; fairways converted from agricultural lands exhibited 24% lower SOM than fairways converted from native grasslands. We concluded that C sequestration in turf soils occurs at a significant rate that is comparable to the rate of C sequestration reported for USA land that has been placed in the Conservation Reserve Program.
Full-text available
Ecosystem simulation models use descriptive input parame- ters to establish the physiology, biochemistry, structure, and allocation patterns of vegetation functional types, or biomes. For single-stand simulations it is possible to measure required data, but as spatial resolution increases, so too does data unavailability. Generalized biome parameterizations are then re- quired. Undocumented parameter selection and unknown model sensitivity to parameter variation for larger-resolution simulations are currently the major limitations to global and regional modeling. The authors present documented input parameters for a process-based ecosystem simulation model, BIOME- BGC, for major natural temperate biomes. Parameter groups include the fol- lowing: turnover and mortality; allocation; carbon to nitrogen ratios (C:N); the percent of plant material in labile, cellulose, and lignin pools; leaf mor- phology; leaf conductance rates and limitations; canopy water interception and light extinction; and the percent of leaf nitrogen in Rubisco (ribulose bis- phosphate-1,5-carboxylase/oxygenase) (PLNR). Using climatic and site de-
Full-text available
Urban areas in the conterminous United State doubled in size between 1969 and 1994, and currently cover 3.5 percent of the total land area and contain more than 75 percent of the US population. Urban areas contain approximately 3.8 billion trees with an average tree canopy cover of 27 percent. The extent and variation of urban forests across the 48 states are explored to help build a better understanding of this significant national resource. Urbanization and urban forests are likely to be a significant focus of forestry in the 21st century.
A study of the energetics of a sururban lawn was conducted in 1972-73 in Walnut Creek, California USA. Several major components of the annual primary and secondary production were measured, including man's role as manager and experimenter in the system. The system was extremely productive with net productivity of 1,020 g/m^2 per yr compared to cornfields with productivity of 1,066 g/m^2 per yr and exceeding tall grass prairie values of around 1,000 g/m^2 per yr. Homopterans, with maximal values of 19 mg/m^2 were plentiful; other typical grassland species, like Araneida, were scarce, representing only 1% by weight of the total invertebrate population. Food utilization per unit area by suburban birds considerably exceeded natural grassland bird utilization (46 kcal/m^2 per yr vs. 1.01-2.33 kcal/m^2 per yr); lawns are ideal foraging sites for open area adapted, flock-feeding species. Man was the dominant consumer in the community, accounting for 10% of the herbivory and nearly 100% of the scavenging. Energy inputs (labor, gasoline, fertilizer, etc.) amounted to 578 kcal/m"2 per yr, equalling or exceeding corn production for a comparable net productivity, but not necessarily utilitarian return.
Americans love their lawns with a passion rarely seen in other countries; fifty-eight million Americans enthusiastically plant, weed, water, spray, and mow an estimated twenty million acres of lawn. But is our dedication to these lawns contributing to the serious environmental problems facing the planet? The authors in this book state that the lawn may be an ecological anachronism, and they argue that we must rethink the way we care for our lawns so that these small pieces of the environment will demonstrate our commitment to a more ecologically sound world. The authors outline the origins of ideas about the lawn and the reasons for its enduring popularity. They describe the development of ideas about its form and the making of the lawn into an object of beauty. They explain how the lawn industry has encouraged the spread of the "industrial" lawn to sustain high sales of mowers, seeds, fertilizers, pesticides, and irrigation equipment. However, say the authors, Industrial Lawns can have high environmental costs: for example, power motors contribute to regional air pollution and global warming; excess fertilizers and pesticides wash off our lawns and run into our wells, streams, and lakes; grass clippings that are bagged and hauled away are major contributors to solid waste problems; and the watering of lawns depletes scarce water supplies. How can we create environmentally sound lawns? The authors offer a variety of ideas - such as moderation in our use of lawn supplements, ecological use of grass varieties, the substitution of hand mowers for power motors, and the use of grass clippings to fertilize the lawn. These strategies can help us to care for conventional lawns in ways lessdangerous to the environment. They also propose two more radical alternatives: Freedom Lawns that allow natural and unrestricted growth of grasses, clover, wildflowers, and other broad-leafed herbaceous plants; and total replacement of the lawn with new landscape designs. By choosing
The effects of disturbance history, climate, and changes in atmospheric carbon dioxide (CO2) concentration and nitrogen deposition (Ndep) on carbon and water fluxes in seven North American evergreen forests are assessed using a coupled water–carbon–nitrogen model, canopy-scale flux observations, and descriptions of the vegetation type, management practices, and disturbance histories at each site. The effects of interannual climate variability, disturbance history, and vegetation ecophysiology on carbon and water fluxes and storage are integrated by the ecosystem process model Biome-BGC, with results compared to site biometric analyses and eddy covariance observations aggregated by month and year. Model results suggest that variation between sites in net ecosystem carbon exchange (NEE) is largely a function of disturbance history, with important secondary effects from site climate, vegetation ecophysiology, and changing atmospheric CO2 and Ndep. The timing and magnitude of fluxes following disturbance depend on disturbance type and intensity, and on post-harvest management treatments such as burning, fertilization and replanting. The modeled effects of increasing atmospheric CO2 on NEE are generally limited by N availability, but are greatly increased following disturbance due to increased N mineralization and reduced plant N demand. Modeled rates of carbon sequestration over the past 200 years are driven by the rate of change in CO2 concentration for old sites experiencing low rates of Ndep. The model produced good estimates of between-site variation in leaf area index, with mixed performance for between- and within-site variation in evapotranspiration. There is a model bias toward smaller annual carbon sinks at five sites, with a seasonal model bias toward smaller warm-season sink strength at all sites. Various lines of reasoning are explored to help to explain these differences.
Lack of soil disturbance in no-tillage changes some of the most important basic soil properties. Short-term changes have been well documented by previous research, but little is known about long-term changes. This study was to determine the effects of 20 yr of continuous corn (Zea mays L.) under no-tillage (NT) and conventional moldboard plow tillage (CT) with 0, 84, 168, and 336 kg N ha-1 on soil properties and grain yields and, to the extent possible, compare 20-yr results with previously published 5- and 10-yr results. Soil organic C and N: extractable P: exchangeable Ca, Mg, and K; and pH were significantly higher with NT than CT in the 0- to 5-cm depth. Below the 5-cm depth, Mehlich III P: pH; and exchangeable Ca, Mg, and K were higher with CT than NT. Organic C and N increased with increasing N rates. Conversety, pH and exchangeable Ca and Mg declined with high N rates. Bulk density was not significantly different among NT, CT, and bluegrass sod (Poa pratensis L.), but increased with depth. Comparisons of 1989 results with those obtained in 1975 and 1980 revealed that the soil's organic C was restored to the level of the bluegrass sod following a decline of 19% with CT and 9% with NT between 1970 and 1975. Grain yields, which declined along with organic C, have not recovered. Changes in organic matter content, with their many ramifications, are probably the most important long-term effects of tillage differences on basic soil properties.
Although turfgrass benefit assessment studies require information on the extent of residential turf, no nationwide surveys or other means of systematic data collection have yet been conducted to estimate total U.S. home lawn area. In an attempt to measure this statistic, two methods of estimating home lawn acreage by state have been employed. The first utilizes FHA average lot size data that have been inflated to conform to a national average lawn size derived from recent state turfgrass surveys. The second method is similar but employs FHA median lot size data reduced by an assumed percentage allotted to lawns. An upper limit to the nation's total lawn area based on total housing units and national media lot size is approximately 26 million acres. Through the study's two techniques, this figure has been adjusted downward, with the first method producing an approximate total of 18 million acres and the second 14 million acres of U.S. home lawn turf.