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Journal of Applied Ecology 2011, 48, 609–618
doi: 10.1111/j.1365-2664.2010.01944.x
The effect of agricultural diversity and crop choice on
functional capacity change in grassland conversions
Brenda B. Lin1,2*‡, Dan F.B. Flynn2‡, Daniel E. Bunker2†, Marı́a Uriarte2
and Shahid Naeem2
1
The Earth Institute, Columbia University, Hogan Hall B-19, 2910 Broadway, MC 3277, New York, NY 10025, USA;
and 2Department of Ecology, Evolution, and Environmental Biology, Columbia University, 1200 Amsterdam Avenue,
10th Floor Schermerhorn Ext., New York, NY 10027, USA
Summary
1. Given that approximately one-quarter of grasslands worldwide have been converted to agriculture, understanding the consequences of agricultural conversion for ecosystem functioning can provide insight into potential changes in the world’s most intensively managed biomes. The Great
Plains of the United States represents a major grassland region that has experienced substantial conversion of prairie grassland ecosystems to agriculture, leading to widespread changes in plant species composition and functional trait diversity. While the converted system dramatically improves
food, fuel and fibre production, changes in plant trait diversity may alter the capacity of these ecosystems to provide sustaining and regulating services to society.
2. Using three key plant functional traits, we illustrate how the trait composition and trait diversity
of the Great Plains plant communities has been dramatically altered when visualized in multidimensional trait space, showing strong displacement and a 10-fold reduction in trait space volumes, as
systems have shifted from grassland to agricultural regimes. However, individual case studies demonstrate large variation in the direction and magnitude of trait diversity change during conversion,
with some case studies exhibiting much larger reductions in trait diversity from the average on
conversion, largely a consequence of the changes in species richness accompanying agricultural
conversion.
3. Synthesis and applications. The conversion of grassland to agriculture does not necessarily lead
to a loss of functional trait diversity, as crop choice and diversity can ameliorate the functional trait
differences between native-dominated and agricultural communities. In this study, regardless of the
sign and magnitude of change in trait space, a shift in trait range was observed, reflecting the dramatically different selection that agricultural plant functional traits experience compared with their
native counterparts. Historical agricultural policy and modern land-use patterns have led to a landscape with decreasing plant diversity and functional capacity. However, initiatives to increase agricultural diversity on-farm and at the landscape level through the implementation of cover crops of
the perennialization of cropping systems may allow ecosystems to recover and maintain greater
functional capacity.
Key-words: agricultural management, convex hull volume, ecosystem services, functional
traits, Great Plains, land use change
Introduction
*Correspondence author. CSIRO, Marine and Atmospheric
Research, 107–121 Station Street, Aspendale, VIC 3195, Australia.
E-mail: [email protected], [email protected]
†Present address: Department of Biological Sciences, New Jersey
Institute of Technology, 433 Colton Hall, University Heights,
Newark, NJ 07102-1982, USA.
‡These authors contributed equally to this work.
The transformation of terrestrial ecosystems to agro-ecosystems involves reductions in biodiversity to improve provisioning ecosystem services of food and fuel, generally at the cost of
other sustaining and regulating services (Altieri 1999). In the
US, conversion of native ecosystems to agriculture has enormously increased the production of goods in the Great Plains,
! 2011 The Authors. Journal of Applied Ecology ! 2011 British Ecological Society
610 B. B. Lin et al.
where corn and cotton production have increased 400% in the
last 50 years, due to increases in cultivated land and production technologies (Parton, Gutmann & Ojima 2007). However,
such conversions may result in long-term, large-scale losses in
sustaining ecosystem services such as soil carbon storage, soil
stabilization and soil production (Manies et al. 2001; Parton
et al. 2005; Montgomery 2007). Given that approximately
one-quarter of temperate and tropical grasslands worldwide
have been converted to agriculture (Mock 2000), understanding the consequences of agricultural conversion in the Great
Plains for ecosystem functioning can provide insight into mitigating potential negative changes in the world’s most heavily
and increasingly intensively managed biomes.
Research into the relationship between biodiversity and ecosystem functioning has identified species traits as the biological
mechanism for how plant diversity influences ecosystem functioning (Lavorel & Garnier 2002). Although changes in plant
biodiversity are known to influence ecosystem functioning, the
way in which changes in plant diversity associated with agricultural conversion have impacted ecosystem functioning remains
understudied (Hooper et al. 2005; Balvanera et al. 2006; Flynn
et al. 2009). Species traits represent the species’ potential contribution to ecosystem functioning; thus, the greater the range
of expression of traits among species in a community, the
greater the potential capacity for the community to provide
ecosystem functioning across a range of environmental conditions (Hillebrand & Matthiessen 2009; Reiss et al. 2009).
Greater trait diversity increases both the magnitude and stability of ecosystem functioning (Eviner & Chapin 2003; Hooper
et al. 2005), and trait diversity research can provide insights
into ecosystem functioning under different scenarios of biodiversity loss (Bunker et al. 2005; McIntyre et al. 2007).
Although functional trait diversity research thus far has largely
been theoretical in application, the use of functional trait diversity comparisons could be very useful in understanding the
functional differences between ecological communities. The
approach has not been applied widely because of the limited
availability of trait information; however, here we apply this
approach to some well-studied grasslands and agricultural systems to better understand how functional trait diversity has
changed under conversion.
Agricultural plants have long been selected by breeding to
function optimally in their cultivation environment (Altieri
1999). Thus, traits of crops may be similar in mean and range
to those of native plants within a similar environment as crops
must also be physiologically successful in that environment, as
studies of managed landscapes in Europe suggest that land-use
change may select for specific traits through environmental filtering because changes in the landscape will lead to changes in
the environment (Lososova et al. 2006). Other research has
shown that plant traits have the ability to respond to land-use
change (Garnier et al. 2007), signifying that agricultural conversion would lead to a selection of different traits in agricultural species.
In this paper, we present four case studies of functional trait
diversity change with conversion of native-dominated grasslands to agricultural plant communities in four counties within
the US Great Plains. One way to measure trait diversity, and
thus the functional capacity of ecosystems, is the multidimensional volume circumscribed by the trait values present in an
ecosystem (Cornwell, Schwilk & Ackerly 2006). In this study,
we measured the trait volume of native and agricultural communities as a surrogate for functional capacity using leaf mass
per area, leaf nitrogen, and maximum photosynthetic capacity
of each species within each community, and refer to this quantification of functional capacity as the functional trait volume
(FTV) of the community. We use these case studies as examples in how measurement of traits and trait volumes can inform
on the differences in trait diversity between and among specific
communities.
There are four possible outcomes (illustrated in Fig. 1) for
a change in FTV following conversion to agriculture, which
we label contraction, expansion, shifting centroid and displacement. Contraction reflects reduced FTV in the agricultural
community due to trait range contraction. Expansion reflects
increased FTV in the agricultural community because of a
necessity for a broader range of traits for crop production.
Shifting centroid reflects no significant contraction in FTV,
but a shift in FTV centroid between natural and agricultural
ecosystems due to differing selection regimes, with overlap
between the two. Finally, displacement reflects a shift in
centroid with no overlap in FTV reflecting relatively independent ecological and selection processes shaping the two
communities. This general framework for comparative
studies of FTV can be broadly applied to comparative
studies of functional trait diversity, not just grasslands versus
(a)
(b)
(c)
(d)
Fig. 1. Hypothetical outcomes for change in functional trait volume
(FTV) and hull spacing following conversion to agriculture (native
hull – blue; agricultural hull – red): (a) agricultural trait range contraction, (b) agricultural trait range expansion, (c) shifting centroid:
no net loss of FTV with overlap, (d) displacement: no net loss of FTV
without overlap. Note that this figure can be used for comparison
between any two communities.
! 2011 The Authors. Journal of Applied Ecology ! 2011 British Ecological Society, Journal of Applied Ecology, 48, 609–618
Crop choice effects on functional capacity 611
croplands. Figure 1 serves primarily as a heuristic device, as
more than three traits would lead to multidimensional space
and not be easily illustrated.
Within the analysis, we expect to see a large difference in the
FTV of the native versus agricultural ecosystem, as the functional trait diversity of a community will, in general, decrease
with reduced species richness. Although this may be true of the
overall pattern of agricultural conversion, the change in functional diversity in specific smaller-scale landscapes may differ
based on the extent of conversion experienced and the diversity
of agricultural crops maintained in the converted system.
Therefore, the contraction in space and the amount of displacement in space remains unknown and could vary across
the various case studies.
Materials and methods
SITE SELECTION
In order to understand how the functional capacity has changed with
the conversion of native grasslands to agriculture, we compared functional diversity between native and agricultural communities. Data
on the composition and abundance of both native and agricultural
communities were required for the analysis. We chose counties as the
unit of analysis for the case studies because the USDA National Agricultural Statistical Survey collects crop acreage coverages at the
county level. This information gave us both the abundance of each
crop in the county as well as the overall acreage under cultivation
within the county. Within the county selections, we chose locations
where there would be ample information regarding species composition and trait data, and for this reason, we focused on counties where
there are current long-term ecological research (LTER) sites already
collecting these types of data.
We obtained data on native species composition and abundance
from three LTER sites and a prairie reserve, all of which are characteristic of the original ecosystems that agricultural systems have
replaced. The LTER sites are Konza Prairie (in Riley County,
Kansas, 39"05¢N, 96"35¢W), Shortgrass Steppe (in Weld County,
Colorado, 40"80¢N, 104"80¢W) and Cedar Creek (in Anoka
County, Minnesota, 45"40¢N, 93"20¢W). Within these sites, species
data of unmanipulated native communities without fertilization or
irrigation were chosen to be most representative of the original
habitat (Cleland et al. 2008). In addition to these LTER sites, plant
data from Kalsow prairie in Pocahontas County, Iowa, (42"34¢N,
94"34¢W) were also used (Dornbush 2004). Within each of the four
counties, county-level agricultural species composition and abundance data were collected from the state level reports of the 2002
National Census of Agriculture (USDA 2004). Although proportionally very little native grassland remains in many of these counties, these four sites are representative of the major ecosystems
likely to have been in place and the major kinds of agricultural ecosystems that have replaced them in the Great Plains. It is important
to note, however, that these grasslands have gone through many
changes and the native communities should be considered ‘nativedominated’ versus completely composed of all native species, with
certain exotic species (e.g. Poa pratensis and Echinochloa crusgalli)
appearing in high abundance within the native grassland sites.
These counties reflect a range of environmental conditions in the
Great Plains (Table 1), as well as a range in the history of agricultural extensification.
Table 1. Environmental and soil conditions in the study sites. Mean
annual temperature (MAT) and mean annual precipitation (MAP)
data from 1961–1990 and 1948–1995 averages, respectively, from the
National Climatic Data Center; soil types from the National
Cooperative Soil Characterization Data
Site
Location
MAP
(mm
MAT
year)1) ("C) Soil type
Pocahontas
County,
Iowa
42"34¢N, 94"34¢W
786Æ1
7Æ7
Clay loam to
loam
Weld
County,
Colorado
40"80¢N, 104"80¢W 326Æ8
8Æ7
Fine sandy
loam to
sandy clay
loam
Riley
County,
Kansas
39"05¢N, 96"35¢W
837Æ9
12Æ8
Silt clay to
silt clay
loam
Anoka
County,
Minnesota
45"40¢N, 93"20¢W
784Æ1
6Æ9
Fine sandy
loam to find
sand
DATA COLLECTION
Within the comparative analysis of native and agricultural communities, only species comprising the top 80% of the total abundance of
plants were used in the analyses to focus on the traits of the dominant
species only. This was also a practical measure as trait data for many
species is still quite limited. For agricultural plants, acreage was used
to represent abundance, while for native plants, abundance was represented by frequency of presence in study plots (IA), cover class (CO,
KS) or biomass (MN). Within the native communities, the 80% cutoff resulted in 13 out of 46 total species at Shortgrass Steppe (CO)
with the next species below the cut-off representing only 2Æ6% of the
relative abundance; 14 out of 60 species in Konza Prairie (KS) with
the next species representing less than 1% of relative abundance; 7
out of 35 species at Cedar Creek (MN) with the next species representing 2% of the relative abundance; and 32 out of 87 species in Kalsow
Prairie (IA) with the next species representing less than 1% of the relative abundance. Within the agricultural community, this cut-off
resulted in 5 out of 31 total species in Weld County, Colorado, with
the next species only 4% of the relative abundance; 5 out of 27 species
in Riley County, Kansas, with the next species representing 3Æ7% of
the relative abundance; 5 out of 31 crops in Anoka County, MN with
the sixth species representing 3Æ4% of the relative abundance; and 2
out of 7 total species in Pocahontas County, Iowa, with the third species representing less than 1% of relative abundance (Table 2).
We selected three traits broadly reflective of the life-history strategies of plants and widely recognized to be key measures of plant physiology and ecology. These were leaf mass per area (LMA, g m)2), leaf
nitrogen (N%) and maximum photosynthetic capacity (Amax,
lmol m)2 s)1). These traits form the ‘leaf economic spectrum’,
describing a range from species with fast tissue turnover, rapid
resource acquisition, and little investment in defence against herbivores to the opposite combination of traits (Garnier et al. 2001; Reich
et al. 2003; Dahlgren et al. 2006). Other key traits which have been
identified in the literature as key indicators of plant life-history strategies include seed size, leaf size and height at maturity (Westoby et al.
2002), but fewer data were available across our focal species for these
traits.
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612 B. B. Lin et al.
Table 2. Native and agricultural species lists (comprising 80% cumulative abundance) for the four county case studies. Relative abundance by
percentage cover for native species and by percentage area under cultivation for agricultural species. For native species, availability of all three
focal traits and thus inclusion in the trait volume analysis is indicated overall in parentheses and for each species; trait data were available for all
agricultural species. Nomenclatures: IA: Gleason & Cronquist 1991, CO, KS: Great Plains Flora Association 1986, MN: Ownbey and Morley
1991
Relative
abundance
Complete set
of traits
Agricultural
species
Relative
abundance
0Æ05
0Æ04
0Æ04
0Æ04
x
x
Zea mays
Glycine max
0Æ56
0Æ43
0Æ04
0Æ04
0Æ04
0Æ03
0Æ04
0Æ04
0Æ03
0Æ03
0Æ03
0Æ07
x
x
x
Zea mays
Triticum aestivum
Medicago sativa
Phaseolus spp.
0Æ30
0Æ24
0Æ22
0Æ05
Triticum aestivum
Glycine max
Sorghum spp.
Medicago sativa
Zea mays
0Æ27
0Æ22
0Æ18
0Æ07
0Æ09
County
Native species
Pocahontas County,
Iowa (16 of 30)
Poa pratensis
Andropogon gerardii
Zizia aurea (L.) Koch.
Helianthus grosseserratus
Martens
Solidago canadensis
Aster ericoides L.
Rosa arkansana
Dichanthelium leibergii
Carex sp.
Sporobolus heterolepis
Galium obtusum
Fragaria sp.
Fragaria virginiana
Calystegia sepium (L.) R.
Br.
Phlox pilosa
Aster lanceolatus Willd.
Ratibida pinnata (Vent.)
Barnh
Aster laevis L.
Vicia americana
Panicum virgatum
Solidago rigida L.
Desmodium canadense
Equisetum laevigatum
Equisetum spp.
Helianthus rigidus (Cass.)
Desf.
Achillea millefolium L.
Elymus canadensis
Amorpha canescens
Eleocharis compressa
Euthamia graminifolia (L.)
Nutt. Ex Cass.
0Æ03
0Æ02
0Æ02
0Æ01
0Æ02
0Æ01
0Æ01
0Æ01
x
x
x
Buchloe dactyloides
Bouteloua gracilis
Stipa comata
Gutierrezia sarothrae
Aristida longiseta
Artemisia frigida
Atriplex canescens
Carex eleocharis
Chrysopsis villosa
Agropyron smithii
Ratibida columnifera
Echinochloa crus-galli
Opuntia polyacantha
0Æ16
0Æ15
0Æ07
0Æ06
0Æ06
0Æ05
0Æ04
0Æ05
0Æ03
0Æ04
0Æ03
0Æ03
0Æ03
x
x
x
x
Panicum virgatum
Symphoricarpos orbiculatus
Solidago canadensis
Andropogon gerardii
Schizachyrium scoparium
Ambrosia artemisiifolia
Bouteloua curtipendula
Carex bicknellii
Sorghastrum nutans
0Æ11
0Æ11
0Æ10
0Æ10
0Æ10
0Æ09
0Æ07
0Æ03
0Æ03
Weld County,
Colorado (8 of 13)
Riley County,
Kansas (8 of 14)
0Æ02
0Æ01
0Æ02
0Æ01
0Æ02
0Æ01
0Æ01
0Æ01
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
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Crop choice effects on functional capacity 613
Table 2. (Continued)
County
Anoka County, Minnesota (7 of 7)
Native species
Relative
abundance
Cirsium altissimum
Poa pratensis
Solidago missouriensis
Ambrosia psilostachya
Cassia chamaecrista
0Æ02
0Æ01
0Æ01
0Æ01
0Æ00
Schizachyrium scoparium
Solidago rigida L.
Poa pratensis
Euphorbia corollata
Lathyrus venosus
Aster azureus
Carex sp.
0Æ17
0Æ16
0Æ14
0Æ11
0Æ08
0Æ08
0Æ05
Complete set
of traits
Agricultural
species
Relative
abundance
Glycine max
Medicago sativa
Zea mays
Raphanus sativus
Daucus carota
0Æ30
0Æ22
0Æ19
0Æ06
0Æ03
x
x
x
x
x
x
x
x
We compiled trait data from the scientific literature, including grey
literature reported by state extension agencies. Our search extended
from September 2007 to April 2008 and included direct contact with
extension agents in each of the four counties for agricultural plant
traits as well as an organized search of scientific literature of each trait
for each species. Using full-text (Google Scholar) and key word (ISI
Web of Science) searches for articles with potential data, we used the
following specific search terms for each trait: leaf mass per area:
LMA, SLA, leaf mass per area, and specific leaf area; leaf nitrogen:
leaf nitrogen, leaf N, N content, and % N; maximum photosynthetic
capacity: Amax, Pmax, photosyn* and CO2 assimilation. Data were
extracted from the articles and compiled into a database where trait
data for each trait–species combination were averaged for the FTV
analysis. Each trait–species combination was averaged in order to use
a general representative number for the analysis although there was
variation in the measurements. Of the 58 species across all of the
native sites, data were completely unavailable for 14, while only one
trait was available for eight, and only two traits were available for
seven species. As such, these results represent a highly conservative
assessment of the actual range of trait values in these communities.
FUNCTIONAL TRAIT VOLUME CALCULATIONS
Convex hulls of the species’ traits distributions were calculated for
native and agricultural communities to estimate the trait volume of
each set of species. Convex hulls describe the minimum volume
required to contain a set of points in multivariate (3D) space and represent the multivariate range of a set of data (see Fig. 2), which are
essentially the FTVs of the communities. Applying this technique
from computational geometry to species traits allows the calculation
of the ‘volume of trait space occupied by species in a community’
(Cornwell, Schwilk & Ackerly 2006). In this technique, the number of
species (vertices) must exceed the number of traits (axes) in order for
a volume to be calculated; thus, with three traits, a minimum of four
species is required for a volume calculation. In addition, displacement
of the agricultural hull with respect to the native hull was calculated
as the distance between the centroids of the two hulls, and reported as
the percentage of the maximum range in trait space for those two
hulls. Both volume change and displacement values are thus relative
to the convex hull of the native plant species used in each comparison.
Analyses were accomplished using the geometry package in the R statistical software package, based on the Quickhull algorithm. In ecology, this method has been applied to measures of plant trait diversity
in oldfields (Schamp, Chau & Aarssen 2008) and in response to
Fig. 2. Convex hulls of the overall comparison between the native
species (blue) and agricultural species (red) community functional
trait volumes (FTV). There are 43 species included within the native
FTV and eight species included in the agricultural FTV.
disturbance (Pausas & Verdu 2008), and has been found to be a powerful method for analyzing patterns of trait-based community assembly (Mouchet et al. 2010).
Results
The results of the FTV calculations, combining data from the
four counties, show that the conversion of grasslands to agricultural lands in the Great Plains ecosystems, in general, reflect
both a contraction and displacement of FTV three-dimensional
space, representing a change in both the values and range of
traits in those communities. Based on the three traits analysed,
our results show that the current functional trait space of
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614 B. B. Lin et al.
Table 3. Functional trait volume (FTV) calculations for native and agricultural communities combined and county hulls. Proportion of
agriculture to native community FTV and percentage displacement of the centroids of the hull volumes for each county. See text for details on
the calculations
Counties
Native
FTV
Agricultural
FTV
Proportion Ag.
to Native FTV (%)
Percent
displacement (%)
All counties
Pocahontas County, Iowa
Weld County, Colorado
Riley County, Kansas
Anoka County, Minnesota
5Æ29
1Æ05
2Æ76
0Æ20
0Æ24
0Æ42
0Æ00
0Æ01
0Æ18
0Æ13
7Æ9
0Æ0
0Æ3
89Æ5
52Æ9
66Æ2
70Æ1
58Æ2
71Æ4
66Æ8
agricultural communities in the Great Plains has been dramatically reduced and has shifted from that of the native communities it replaced. The agricultural community now displays a
hull volume more than 10 times smaller than the native community (native = 5Æ29, agriculture = 0Æ42), and the agricultural hull has shifted 66Æ2% across the total range of trait space
(Fig. 2, Table 3). In the combined analysis, 43 species were
included within the overall native community, and eight species
were included in the overall agricultural community, explaining the difference in trait diversity only in part. The large displacement in the centroids of the hulls (66Æ2% of the trait space
range) and lack of overlap in FTV space between native and
agricultural communities indicates that the two communities
are not confined to similar trait ranges through environmental
filtering, but rather suggests that they have experienced independent ecological and trait selection processes.
Although we see an extreme reduction of functional trait
space as well as a greatly reduced range in all three traits in the
combined analysis, the results for the individual county studies
are more variable, indicating a range in potential FTV change
that will occur under agricultural conversion. A large displacement and lack of overlap between the native and agricultural
hulls was seen in each of the case studies, signifying difference
in trait selection between the two communities. However, the
individual county-level case studies show that differences in
agricultural management and crop choice may allow for some
agricultural conversions to maintain fairly large FTVs, equivalent to that of the grassland counterparts.
Dramatic reductions and shifts in the agricultural FTVs
were seen in two counties, Pocahontas County, Iowa, (native = 0Æ745, agriculture = N ⁄ A) and Weld County, Colorado, (native = 2Æ756, agriculture = 0Æ007) (Fig. 3a,b).
Pocahontas County, Iowa, presented an especially stark example of volume reduction because of the large difference in species diversity between the native (30 species) and agricultural
(two species) communities (Table 2). Because only two species
made up the 80% abundance for the agricultural community
in Pocahontas County, the hull is represented simply as a line
between these two points, and no volume could be calculated.
Weld County, Colorado, had 13 species within the native community versus four species within the agricultural community,
with the agricultural community accounting for only 0Æ3% of
the FTV of the native community, despite only nine fewer species difference in richness.
Riley County, Kansas, (native = 0Æ20, agricultural = 0Æ18)
and Anoka County, MN, (native = 0Æ24, agricultural = 0Æ13) (Fig. 3c,d) experienced smaller changes in FTV
between native and agricultural communities, although there
was still a displacement similar to the overall displacement
(Table 3). In Riley County, 14 species were included in the
native community and five species were included in the agricultural community, yet the FTV difference between the native
and agricultural community is quite small. This result contrasts
with the Weld County example which had a similar number of
species in each community, yet dramatically reduced FTV in
the agricultural community.
Discussion
These results show that the general overall pattern of agricultural conversion from grasslands leads to both a dramatic shift
as well as a reduction in FTV space (Fig. 2), but this pattern
varies in magnitude across the four case studies examined.
Within individual counties, crop choice and plant diversity
management within agricultural lands can lead to a wide range
of FTV differences between native and agricultural communities. In communities where there is a large shift in species diversity, such as Pocahontas County (Fig. 3a), there is a large loss
in FTV. In other counties such as Weld Riley, and Anoka
(Fig. 3c) where species ratios are similar, the change in FTV
can range widely based on original community composition
and the agricultural species that have replaced them. These
results show that agricultural FTVs do not necessarily have to
be dramatically smaller than that of native FTVs and both the
number of crops planted as well as the identity of the crops can
have a large impact on the change in FTV with conversion to
agriculture.
Neither the overall nor the individual county examples
showed an overlap in the FTVs of the native and agricultural
FTVs, indicating that there is a distinct difference in trait range
and selection. Examining the individual traits used within the
analyses provides insight into the trait differences between
native and agricultural communities (Table 4). In general, the
LMA of the agricultural community was less than 50% that of
the native community, % N was 50–75% higher, and Amax
was 10–25% higher in the agricultural community. We interpret the shift in hull volume and location as a result of agricultural management, where resource availability is highly
! 2011 The Authors. Journal of Applied Ecology ! 2011 British Ecological Society, Journal of Applied Ecology, 48, 609–618
Crop choice effects on functional capacity 615
(a)
(b)
(c)
(d)
Fig. 3. Convex hull comparisons for the individual counties: Pocahontas County, Iowa, (a); Weld County, Colorado, (b); Riley County, Kansas,
(c); Anoka County, Minnesota, (d). Note that the agricultural ‘hull’ in Pocahontas County, Iowa is a line with zero volume because two crop species make up over 80% of total crop abundance in the county. Axes as in Fig. 2.
subsidized and resource acquisition is highly monitored, leading to a high level of trait selection within the overall agricultural community. This demonstrates the strong differences
between natural environmental filters and agronomic selection
for species traits, whereby natural systems allow or even
require a wide variety of plant form and function whereas agricultural species have been modified to grow in optimal agronomic conditions.
The lower LMA in the agricultural community probably
reflects the fact that many crops do not require high LMA and
its associated high construction costs, since there is little need
for long-lived, well-defended leaves (Paoletti & Pimentel 1996),
especially with the use of agrochemicals. The higher Amax of
crops shows that they have been engineered to maintain high
photosynthetic capacity while concentrating carbohydrates
toward fruit production to maximize yield. Percentage leaf
nitrogen is higher in the agricultural communities probably
due to nitrogen fertilization as well as the use of nitrogen-fixing
crops such as Medicago sativa.
For all research using functional traits to reflect either community responses to land use change (Garnier et al. 2004,
2007; Flynn et al. 2009; Laliberté et al. 2009) or potential for
communities to effect ecosystem properties (D. Flynn, unpublished data; Griffin et al. 2009), the traits selected and the number of traits used critically influence the outcome of the
analysis. The three traits chosen here, LMA, Amax and leaf
%N, reflect an important range of life-history strategies. In the
case of the native plants, these traits show plant adaptations to
the Great Plains environment, while for agricultural plants,
these traits reflect the signature of agricultural practices. If
other trait data had been available, such as root : shoot ratio,
seed size or height, the results would probably have demonstrated different magnitudes of contraction and displacement,
and would have captured functional capacity in a broader
way. Another consideration particular to the convex hull volume method used here is that when only two species are present, as for the agricultural community of Iowa, no volume can
be calculated. Modifications to the convex hull volume method
to include abundance information and intraspecific variation
(D. Bunker, D. Flynn, S. Naeem, unpublished data) are also
being developed in order to more broadly capture the functional representation of a community. However, given these
! 2011 The Authors. Journal of Applied Ecology ! 2011 British Ecological Society, Journal of Applied Ecology, 48, 609–618
616 B. B. Lin et al.
Table 4. Summary of trait data of the native and agricultural communities of the four counties (LMA, N, Amax)
Trait
County
Community
No.
species
Mean
SD
Range
LMA (g m)2)
Pocahontas County, Iowa
Native
Agricultural
Native
Agricultural
Native
Agricultural
Native
Agricultural
30
2
13
4
14
5
7
5
77Æ85
43Æ08
137Æ07
32Æ73
85Æ26
39Æ17
94Æ11
41Æ43
24Æ91
19Æ58
104Æ84
6Æ88
22Æ47
11Æ38
25Æ12
17Æ08
26Æ9–126Æ4
30Æ1–56Æ9
45Æ3–295Æ1
28Æ6–43
57Æ1–132Æ1
29Æ2–56Æ9
68Æ7–144
27Æ9–63
Native
Agricultural
Native
Agricultural
Native
Agricultural
Native
30
2
13
4
14
5
7
2Æ41
3Æ25
1Æ71
2Æ60
1Æ89
2Æ93
2Æ25
0Æ76
1Æ72
0Æ77
0Æ78
0Æ73
1Æ07
1Æ20
1Æ3–4Æ2
2Æ0–4Æ5
0Æ7–3Æ4
1Æ8–3Æ4
0Æ9–2Æ9
1Æ8–4Æ5
1Æ2–4Æ1
Agricultural
Native
Agricultural
Native
Agricultural
Native
Agricultural
Native
Agricultural
5
30
2
13
4
14
5
7
5
3Æ42
15Æ88
21Æ41
18Æ40
21Æ47
20Æ50
23Æ97
16Æ89
21Æ06
1Æ03
5Æ46
2Æ15
11Æ18
2Æ15
6Æ00
6Æ79
5Æ04
5Æ74
2–4Æ5
7Æ9–27Æ6
18Æ4–23Æ4
1Æ4–35Æ6
18Æ7–23Æ4
7Æ7–27Æ6
18Æ7–35Æ5
11Æ4–24Æ5
12Æ2–27Æ5
Weld County, Colorado
Riley County, Kansas
Anoka County, Minnesota
Leaf N (%)
Pocahontas County, Iowa
Weld County, Colorado
Riley County, Kansas
Anoka County, Minnesota
Amax (lmol CO2 m)2 s)1)
Pocahontas County, Iowa
Weld County, Colorado
Riley County, Kansas
Anoka County, Minnesota
caveats and understanding that future improvements will
strengthen the analysis, this study serves to demonstrate that
with three key traits, a striking contraction and displacement
in functional diversity can be observed with the conversion to
agriculture in the Great Plains, as well as the variation in functional change at the county level.
The variation in the degree of FTV change among
counties may be attributed in-part to environmental conditions and historical county-specific conversion patterns.
Historically, agricultural conversion in combination with
the domestication of crop species, have significantly
reduced native plant and crop genetic diversity in the
landscape (Samson & Knopf 1994; Hyten et al. 2006), but
the patterns differ depending on native grassland composition and the levels of agricultural conversion. For example, the favourable soil and climate conditions in
Pocahontas County, Iowa, (Table 1) resulted in a long
history of annual crop production. By 1850, this county
was already under extensive wheat, corn and potato agriculture. This was followed by a dramatic shift toward
large-scale agricultural production with currently 83% of
the county covered by primarily two species, soybean Glycine max and corn Zea mays. Conversely, Anoka County
in Minnesota represents a region that did not experience
agricultural conversion until the early 1900s (Knops &
Tilman 2000). Currently, only 7% of land in Anoka
County, Minnesota, is under agriculture, as the sandy
soils and the environmental conditions (Table 1) limit the
large-scale development of agriculture, potentially also
leading to a smaller difference in FTV change between
native and agricultural communities. Thus, to some extent
the degree of change in functional diversity with agricultural conversion may be predictable from environmental
conditions. For example, areas only suitable for perennial
pasture would be expected to demonstrate less contraction
or displacement in FTV compared with areas suitable for
annual row crops.
It should be noted that the current analysis calculates the
FTVs assuming that all the species within the native and agricultural communities are present within the systems concurrently to form the full volume of the hull. However, in
agricultural systems, there are often large temporal shifts in
community composition due to crop rotations where one species may be present for part of the year and then replaced by
another species in a different season. Therefore, two or three
species may be rotated within a system throughout the year
and not represented in the landscape at the same time. This
lack of concurrent species representation within the agricultural systems may lower the true FTV for agricultural systems
since the species are not present temporally at the same time,
representing a less diverse species community than the ones
considered in this analysis.
Regional and national agricultural policy, in addition to
county-specific history, plays a large role in the observed shifts
in FTVs between native and agricultural communities. Since
the 1870s, farm policy has played a large role in the extensification and intensification of Great Plains agriculture (Samson &
Knopf 1994). Data from the National Census of Agriculture
(USDA 2004) show that agricultural development from the
late 1800s until the 1960s was marked by a high number of
! 2011 The Authors. Journal of Applied Ecology ! 2011 British Ecological Society, Journal of Applied Ecology, 48, 609–618
Crop choice effects on functional capacity 617
crops planted, particularly following the Dust Bowl in the
1930s. But in all four focal counties, crop diversity has
decreased steadily since the 1960s, due to governmental support for agricultural intensification (Samson & Knopf 1994),
leading to increasing acreage of fewer crops, as well as the possibility of reduced agricultural diversity for functional trait
diversity.
Such changes in functional capacity may have negative
effects on the long-term sustainability of Great Plains agricultural systems. The combined and often synergistic effects of species loss can make a system more vulnerable to environmental
change (Folke et al. 2004). Studies have linked greater hay production biodiversity to more resilient agroecosystems that are
able to provide vital services, such as fodder production, when
challenged by severe weather (Schläpfer, Tucker & Seidl 2002).
When comparing low versus high diversity grassland plots,
year-to-year biomass measures were less variable in species-rich
plots, especially in regards to drought conditions (Tilman,
Reich & Knops 2006), showing greater stability in production
yield. In agricultural studies of hay production, high diversity
grasslands communities were found to be more economically
feasible than intensified, low diversity communities because of
the ability to maintain and attain target yields (Schläpfer,
Tucker & Seidl 2002). Such studies show that functional diversity influences production and a reduction in FTV may lead to
a decline in the stability of production, potentially because the
functional traits have been selected outside of the environmental filters in exchange for high agricultural management.
It is important to note, however, that there are few incentives
toward increasing crop diversification, therefore maintaining a
large difference in plant diversity and functional capacity
between native grasslands and agricultural communities. Five
main commodities (corn, soybean, wheat, cotton and rice)
receive about 90% of the subsidized farm supports in the USA
(Boody et al. 2005), incentivising farmers to specialize production to these one or few crops in order to obtain consistent and
guaranteed prices per bushel. Furthermore, the introduction of
agricultural inputs encourages the progression toward crop
specialization because the inputs provide and replace some of
the lost functionality within the functionally reduced agricultural systems, allowing them to maintain productivity and buffering them from lost ecosystem services (e.g. soil carbon and
soil production). Irrigation additionally allows for the replacement of soil water holding capacity and water use efficiency by
providing systems with water at will. In this sense, agricultural
management has effectively allowed agricultural species to be
decoupled from the environmental filters which would have
selected for traits similar to native species (Robertson & Swinton 2005) to adapt to natural conditions.
Increasingly intensive land use will continue to shift the
functional diversity of plant communities, potentially yielding
a landscape with reduced functional capacity. However, the
results of this paper suggest that the degree of change in functional capacity can vary, as crop choice and planting combinations can exhibit equivalent FTVs to native grasslands,
although all exhibit dramatic shifts in the location in trait
space. Maintaining greater species diversity within agricultural
lands may be one way to reduce the amount of functional
change between native and agricultural systems and preserve
high levels of functional capacity within agricultural systems.
The management of increased on-farm agricultural diversity,
both spatially and temporally, and the use of ecological practices can develop greater functional capacity within agricultural systems (Altieri 1999; Robertson & Swinton 2005).
Initiatives to increase on-farm species diversity, such as the
increased implementation of cover crops or the perennialization of cropping systems, may increase both sustaining and
regulating functions while maintaining provisioning functions.
Such changes in land management would allow ecosystems to
recover and maintain some of the functional capacity that may
have been lost in the Great Plains and elsewhere in ecosystems
that have undergone similar changes.
Acknowledgements
We thank the many extension agents and researchers who assisted with data
compilation, especially J. Blair, M. Dornbush, R. Elmore, S. Gleeson,
D.C. Hart, T. Maxwell, C. McAllister, M. McGinty, D. Mengel, J. Morgan,
J. Nippert, P. Olmstead, M. Palmer, P. Pederson, D.H. Rogers, K. Roozeboom, A. Wiedman and B. Wilsey. We also thank R. Russell for access to the
compiled Census of Agriculture data and the comments of two anonymous
reviewers in improving the manuscript.
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Received 8 July 2010; accepted 16 December 2010
Handling Editor: Brian Wilsey
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