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Are grasslands important habitats for soil microarthropod conservation?

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Biodiversity has been a focal aim of environmental protection since the Rio conference, but only with the beginning of the new millennium did soil biodiversity become an important aspect of international policy. Edaphic fauna play a key role in many soil functions, such as organic matter decomposition, humus formation and nutrient element cycling; moreover, affect the porosity, aeration, infiltration and distribution of organic matter in soil horizons, modifying soil structure and improving its fertility. The ecosystem services provided by soil animals are becoming progressively lost due to agricultural practice intensification, which causes a reduction in both abundance and taxonomic diversity of soil communities. In the present study, a permanent grassland habitat was studied in order to evaluate its potential as a soil biodiversity reservoir in agroecosystems. Grassland samples were compared with samples from a semi-natural woodland area and an arable land site. Microarthropod abundances, Acari/Collembola ratio (A/C), Shannon diversity index (H′) and evenness index (E) were calculated. QBS-ar index was used in order to evaluate soil biological quality. Microarthropod communities of the three land use typologies differed in both the observed groups and their abundance. Steady soil taxa characterized both woodland and grassland soils, whereas their abundances were significantly higher in woodland soil. Taxon diversity and soil biological quality in the grasslands did not differ from the woodland samples. The microarthropod community in the arable land showed a reduction both in taxa numbers and soil biological quality compared with the other sites. Soil biological quality and edaphic community composition highlighted the importance of grassland habitats in the protection of soil biodiversity. KeywordsBiodiversity–Grassland–Microarthropods–QBS-ar–Soil quality–Sustainable agriculture
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ORIGINAL PAPER
Are grasslands important habitats for soil
microarthropod conservation?
Cristina Menta
Alan Leoni
Ciro Gardi
Federica Delia Conti
Received: 12 October 2010 / Accepted: 11 February 2011 / Published online: 24 February 2011
Ó Springer Science+Business Media B.V. 2011
Abstract Biodiversity has been a focal aim of environmental protection since the Rio
conference, but only with the beginning of the new millennium did soil biodiversity
become an important aspect of international policy. Edaphic fauna play a key role in many
soil functions, such as organic matter decomposition, humus formation and nutrient ele-
ment cycling; moreover, affect the porosity, aeration, infiltration and distribution of
organic matter in soil horizons, modifying soil structure and improving its fertility. The
ecosystem services provided by soil animals are becoming progressively lost due to
agricultural practice intensification, which causes a reduction in both abundance and
taxonomic diversity of soil communities. In the present study, a permanent grassland
habitat was studied in order to evaluate its potential as a soil biodiversity reservoir in
agroecosystems. Grassland samples were compared with samples from a semi-natural
woodland area and an arable land site. Microarthropod abundances, Acari/Collembola ratio
(A/C), Shannon diversity index (H
0
) and evenness index (E) were calculated. QBS-ar index
was used in order to evaluate soil biological quality. Microarthropod communities of the
three land use typologies differed in both the observed groups and their abundance. Steady
soil taxa characterized both woodland and grassland soils, whereas their abundances were
significantly higher in woodland soil. Taxon diversity and soil biological quality in the
grasslands did not differ from the woodland samples. The microarthropod community in
the arable land showed a reduction both in taxa numbers and soil biological quality
compared with the other sites. Soil biological quality and edaphic community composition
highlighted the importance of grassland habitats in the protection of soil biodiversity.
Keywords Biodiversity Grassland Microarthropods QBS-ar Soil quality
Sustainable agriculture
C. Menta (&) A. Leoni F. D. Conti
Department of Evolutionary and Functional Biology, Section Natural History Museum, University
of Parma, Via Farini, 90, 43100 Parma, Italy
e-mail: cristina.menta@unipr.it
C. Gardi
Institute for Environment and Sustainability, European Commission Joint Research Centre,
21020 Ispra, Varese, Italy
123
Biodivers Conserv (2011) 20:1073–1087
DOI 10.1007/s10531-011-0017-0
Introduction
Edaphic microarthropod communities are an important reservoir of biodiversity and play
an essential role in several soil ecosystem functions; furthermore, they are often used as
soil quality indicators. Although biodiversity was one of the focal points of the Rio con-
ference, virtually no attention had been paid in the 1990s to conservation activities for soil
communities (Hagvar 1998). On the contrary, with the new millennium, the conservation
of soil biodiversity become an important aim in international environmental policies, as
highlighted in the EU Soil Thematic Strategy (2006), the Biodiversity Action Plan for
Agriculture (EU 2001), the Kiev Resolution on Biodiversity (UE/ECE 2003) and after-
wards in the Message from Malahide (EU 2004), that lay down the goals of the 2010
Countdown.
Soil biota play an essential role in soil function as they are involved in processes
such as organic matter decomposition, humus formation and the nutrient cycling of
many elements (nitrogen, sulphur, carbon). Moreover, edaphic fauna affect the porosity,
aeration, infiltration and distribution of organic matter in soil horizons (Bird et al.
2004). The ecosystem services provided by soil fauna are one of the most powerful
arguments for the conservation of edaphic biodiversity (Ridder 2008). Modern agri-
cultural practices like ploughing, chemical fertilization and pesticide use frequently
cause a degradation of soil environmental conditions which leads to a reduction in the
abundance (Cortet et al. 2002) and to a simplification of animal and plant communities,
where species able to bear stress predominate (Solbrig 1991; Gardi and Menta 2004)
and rare taxa decrease in abundance or disappear. The result of this biodiversity
reduction is an artificial ecosystem that requires constant human intervention and extra
running costs, whereas natural ecosystems are regulated by plant and animal commu-
nities through flows of energy and nutrients, a form of control progressively lost with
agricultural intensification (Swift and Anderson 1993). For these reasons the identifi-
cation of agricultural systems which allow the combination of productive goals and
environmentally friendly management practices, protecting both soil and biodiversity, is
essential in order to prevent the decline of soil fauna communities in agricultural
landscapes.
Permanent grasslands show both high soil fertility, through the gradual increase in
humus contents and nutrients adsorbed onto colloids, and rich soil fauna diversity.
Groups like nematodes, microarthropods and annelids are the most abundant in terms of
both number and biomass (Bradgett and Cook 1998). Permanent grass cover protects
soil against water erosion, and roots maintain a good soil structure. Moreover, in
intensively cultivated areas, permanent grasslands play an important function as reser-
voirs for vegetation biodiversity, with highly phyto-geographically valued plants (Gardi
et al. 2002).
For these reasons, we hypothesize that permanent grasslands in intensive agricultural
landscapes could be suitable habitats for soil biodiversity conservation, especially for taxa
typical of steady soils such as Symphyla, Protura and Pauropoda, which are generally
observed in natural areas.
In this study, grassland and arable land soil microarthropod communities were com-
pared in order to evaluate whether grassland habitats support a higher biodiversity and
abundance of microarthropod communities. Moreover, both of these soil communities
were compared with a community sampled in a nearly semi-natural woodland site, iden-
tified as a low anthropic impact habitat.
1074 Biodivers Conserv (2011) 20:1073–1087
123
Materials and methods
Study area
The sampled areas are located in the Po valley (northern Italy) 15 kilometres from Parma
(44°48
0
10
00
N, 10°19
0
30
00
E). A total of 14 sites were sampled which belonged to three land
use typologies: arable land (AR), permanent grassland (G) and woodland (W). Agro-
nomical information such as age of cultivation, irrigation and fertilization typologies were
obtained from historical archives and memories of rural inhabitants.
The arable land sites belong to Spalletti’s farm property, which is located in the
Sant’Ilario municipality (44°45
0
09
00
N, 10°28
0
02
00
E). Four plots were sampled: AR1 in the
second year of maize (Zea mays) cultivation with inorganic fertilization; AR2 in the second
year of maize cultivation with compost fertilization; AR3 in the first year of maize cul-
tivation with inorganic fertilization; AR4 in the first year of maize cultivation with compost
fertilization. All were irrigated by rain and had been ploughed in the previous autumn. The
two latest plots had formerly been alfalfa (Medicago sativa) meadows.
The permanent grassland sites are located in the Taro River Regional Park
(44°44
0
25
00
N, 10°10
0
28
00
E). The park was established in 1988 and is 2500 hectares in size
in a level area along the Taro river (elevation ranging between 130 and 56 m a.s.l.). The
landscape is dominated by arable lands, permanent grassland and alfalfa meadows. The six
permanent grassland (G) plots have the following characteristics: G150 is about 150 years
old, flood irrigated and organically fertilized; G100 is about 100 years old, rain irrigated
and fertilized with mature dung; G50 is over 50 years old, flood irrigated and fertilized
with mature dung; G40 is about 40 years old, rain irrigated and inorganically fertilized;
G20 is about 20 years old, rain irrigated and inorganically fertilized; G5 is only 5 years
old, flood irrigated and fertilized with mature dung.
The four woodland sites are part of Carrega’s Woodland Regional Park (44°43
0
23
00
N,
10°12
0
21
00
E), which was established in 1992 and covers an area of 1270 hectares. Before
the park was established, Carrega’s land had, for centuries, been a hunting area reserved for
the noble families of Parma. This former use brought about important effects on the forest
management, such as the plantation of chestnut trees. The park is located in an area near
the Taro river. Each sampled plot was characterized by different tree species: WQC was
oak forest dominated by Quercus cerris with scarce grass cover (120 m a.s.l.); WPE is oak
forest dominated by Quercus petraea, where the trees are generally spaced out and the
grass cover is not homogenous (210 m a.s.l.); WPU is oak forest dominated by young
Quercus pubescens trees, strongly sloping and exposed to the south, and the grass cover is
scarce (300 m a.s.l.); WCS is dominated by chestnut trees (Castanea sativa) and the grass
cover is scarce (280 m a.s.l.).
Samples
In each site three soil cores, 100 cm
2
and 10 cm deep were picked up in both the spring
and autumn. In the woodland sites the litter layer was removed before sampling and only
soil was taken. Because of logistical reasons the sites were not sampled simultaneously:
arable land samples were collected in April 2006 and October 2006, grassland samples
were collected in October 2003 and June 2004, and the woodland sites were sampled in
June 2004 and November 2004.
The soil samples were sealed in polyethylene bags and transported to the laboratory
within 48 h. A Berlese-Tu
¨
llgren funnel was used for microarthropod extraction and the
Biodivers Conserv (2011) 20:1073–1087 1075
123
specimens were collected in a solution of 75% alcohol and 25% glycerine by volume. The
extracted specimens were observed under a stereomicroscope and identified at different
taxonomical levels: classes for miriapoda (Diplopoda, Chilopoda, Symphyla, Pauropoda)
and order for insects, chelicerata and crustaceans. The organisms belonging to each bio-
logical taxon were counted in order to estimate their density at the sampled depth
(0–10 cm) and relating the number of individuals and the sample area to 1 m
2
of the
surface (ind/m
2
).
Indices
The biodiversity of soil communities was evaluated using the number of observed taxa
(NT), the Shannon-Weiner diversity index (H
0
) and Pielou’s evenness index (E).These
diversity measures were calculated using the number of specimens observed in each
sample identified at the taxonomical level mentioned above.
Soil quality was estimated with the Acari/Collembola ratio (A/C) and the QBS-ar index.
The A/C index is based on the densities of Acari and Collembola communities, where in
natural conditions the ratio of the number of mites to the number of Collembola is larger
than one. On the contrary, in case of soil degradation, the ratio shifts towards Collembola
and its value decreases (Bachelier 1986).
The QBS-ar index (Parisi et al. 2005; Gardi et al. 2008; Tabaglio et al. 2009; Menta et al.
2010) is based on the following concept: the higher the soil quality, the higher the number of
microarthropod groups morphologically well adapted to this soil habitat. Soil organisms are
separated into biological forms according to their morphological adaptation to soil envi-
ronments; each of these forms is associated with a score named the EMI (eco-morphological
index), which ranges from 1 to 20 in proportion to the degree of adaptation. The QBS-ar
index value is obtained from the sum of the EMI of all collected groups. If in a group,
biological forms with different EMI scores are present, the higher value (more adapted to
the soil form) is selected to represent the group in the QBS-ar calculation. The sampling
methodology ensured that three soil cores (with an area of 100 cm
2
and 10 cm deep) were
taken at each sample site and combined into a single sample.
Statistical analysis
The taxa abundances were evaluated using the principal component analysis (PCA) in
order to highlight the microarthropod groups that were related to land use typologies and to
obtain a graphical representation of the relationships between soil samples. The data were
ln(x ? 1) transformed and the taxa which were not observed in at least 10% of the samples
(Palpigrada, Lepidoptera larva, Psocoptera, Dermaptera) were omitted in order to reduce
biases.
Significant differences in taxa abundances and index values (H
0
, E, NT, A/C) between
the land use typologies were tested using the analysis of variance (ANOVA). The main
effects in the ANOVA model were land use typology (fixed factor), site (random factor)
and sample period (random factor) nested within site and land use typology. The taxa
abundance data were ln(x ? 1) transformed before the analysis whereas the H
0
, E, NT and
A/C index values were ln(x) transformed because the values were non-zero numbers. The
QBS-ar index values were used untransformed. In the case of the QBS-ar index, nested
ANOVA was performed again with land use typology (fixed factor) as main effect but only
with sample season (random factor) as a nested factor. In fact, there was only one QBS-ar
value for each site in each sample period because, as mentioned above, the sampling
1076 Biodivers Conserv (2011) 20:1073–1087
123
methodology combined three samples into one. All pairwise comparisons of the analysed
variables among the three land use typologies were performed using the Bonferroni
correction.
Taxa abundances and index values (H
0
, E, NT, A/C) were also tested using nested
ANOVA in order to highlight seasonal differences. Nested ANOVA was performed for
each land use typology using the sample period (fixed factor) and site (random factor) as
main effects nested within the sample period. Also, the QBS-ar index values were analysed
using the Student’s paired-samples t-test to highlight seasonal differences. All statistical
analyses were performed using SPSS 15.0 software.
Results
Abundance and distribution of taxa
A total of 38025 specimens belonging to 21 taxa were observed. Acari and Collembola
were the most abundant group sampled, representing 44.9 and 47.4% of the extracted
microarthropods, respectively. The Hymenoptera group (ants) represented 2.5% of the total
specimens but was only observed in 35.2% of the samples (almost all grassland samples),
whereas coleopteran larvae represented only 1.2% of the total specimens and were present
in 75% of the samples. None of the other 17 groups observed reached an abundance of 1%
of the total number of specimens.
Factor I and II obtained by the principal components analysis accounted for 38.12% of
the variation: 22.99 and 15.13%, respectively. The graphical representation of samples
obtained by plotting factor I on the abscissa and factor II on ordinate (Fig. 1) showed quite
a clear separation of clusters related to land use. The G cluster was the most scattered,
whereas the AR samples were highly grouped. The W cluster showed an outlier sample
(QPUa3) in the higher area of the plot, although performing the PCA with and without
these samples gave similar variation and component values (Table 1). The woodland
Fig. 1 Principal component analysis (PCA) ordination diagram of soil samples. G Grassland, W Woodland,
AR Arable land
Biodivers Conserv (2011) 20:1073–1087 1077
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samples were located on the negative side of the horizontal axis (factor I), whereas
grassland samples were on the positive side. Positively high correlations with this axis
were obtained for Acari, Collembola, Hymentoptera, Tisanoptera and Coleoptera (both
adults and larvae), highlighting the links between these groups and the grassland habitat.
On the contrary, Chilopoda and Pseudoscorpia showed a negative correlation on horizontal
axis in the direction of the W samples. Despite their dispersion, the G and W samples
showed a tendency towards the positive side of the vertical axis, whereas AR samples were
restricted to the lower side of the plot. Pauropoda, Symphyla, Chilopoda, Diplura and
Protura were the most positively correlated groups with this axis.
Taxa abundance differences according to the land use typologies were also confirmed
by the analysis of variance, which highlighted two principal clusters of microarthropod
groups that showed significant differences in abundance due to their higher densities in a
specific habitat (Tables 2, 3). The first cluster consisted of Acari (F=43.949, p \0.001),
Collembola (F=32.983, p \ 0.001), Hemiptera (F=30.707, p \0.001), Isopoda
(F=6.893, p \0.05), and Tisanoptera (F=4.329, p \ 0.05), all of which displayed their
highest mean abundances in grassland sites, as confirmed by the significant differences
observed in pairwise comparisons. The same taxa did not significantly differ in abundance
between woodland and arable land samples. The second group of taxa consisted of
Pauropoda (F=4.203, p \0.05), Symphyla (F=5.606, p \ 0.05) and Chilopoda
(F=9.473, p \ 0.01), all of which displayed their highest mean abundances woodland
sites. The pairwise comparison did not show a significant difference between G and AR
samples. This latter group of taxa also included the Pseudoscorpia taxon (F=18.616,
p \0.001), whose specimens were only observed in W samples. On the contrary,
coleopteran adult (F=25.264, p \ 0.001) specimens showed the opposite trend compared
to these latter taxa. In fact, their abundance was significantly lower in W sites compared to
Table 1 Component matrix
obtained by principal component
analysis
The four higher variable loadings
of each component are in bold
type
Groups Components
12
Acari 0.864 0.287
Araneida 0.229 0.380
Chilopoda -0.448 0.603
Coleoptera adults 0.671 -0.055
Coleoptera larva 0.446 0.168
Collembola 0.848 0.333
Diplopoda 0.023 0.325
Diplura 0.039 0.571
Diptera larva -0.078 0.305
Hemiptera 0.700 0.166
Hymenoptera adults 0.450 0.103
Isopoda 0.269 0.096
Pauropoda -0.289 0.670
Protura 0.028 0.521
Pseudoscorpia -0.499 0.334
Symphyla -0.322 0.660
Tisanoptera 0.574 -0.039
1078 Biodivers Conserv (2011) 20:1073–1087
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the other land use typologies, whereas pairwise comparisons between G and AR samples
did not highlight a significant difference in abundance. The mean density of dipteran larvae
was lower (F=4.440, p \0.05) in AR sites, but pairwise comparisons highlighted a
significant difference only with the W sites. In fact, the highest mean density of this taxon
in G samples was partially due to outlier values.
Even though Diplopoda and Diplura were only observed in woodland and grassland
samples, significant differences were not found in land use typology comparisons, probably
because their presence within these sites was sporadic and characterized by outlier values.
Table 2 Taxa mean abundances (ind/m
2
) and index mean values ± standard error for each land use
typology in spring and autumn samples
GWAR
Spring Autumn Spring Autumn Spring Autumn
Taxon
Acari 35065 ± 5598 16420 ± 4331 1295 ± 245 2235 ± 453 1062 ± 339 4082 ± 620
Araneida 92 ± 46 80 ± 21 53 ± 32 27 ± 12 0 ± 021± 9
Chilopoda 21 ± 13 32 ± 20 80 ± 16 180 ± 60 0 ± 00± 0
Coleoptera
adults
255 ± 41 123 ± 30 11 ± 75± 527± 10 345 ± 60
Coleoptera
larva
637 ± 153 255 ± 136 117 ± 22 127 ± 26 122 ± 62 621 ± 344
Collembola 29545 ± 6893 13956 ± 2993 1587 ± 617 1826 ± 274 605 ± 127 6056 ± 2214
Dermaptera 0 ± 00± 011± 11 0 ± 00± 00±
0
Diplopoda 64 ± 53 104 ± 99 27 ± 27 43 ± 14 0 ± 00± 0
Diplura 159 ± 106 52 ± 48 48 ± 26 117 ± 83 0 ± 00± 0
Diptera larva 195 ± 132 88 ± 39 159 ± 45 122 ± 23 48 ± 22 80 ± 33
Hemiptera 718 ± 289 454 ± 313 0 ± 00± 00± 011± 7
Hymenoptera
adults
2105 ± 796 780 ± 379 11 ± 727± 12 823 ± 667 0 ± 0
Isopoda 21 ± 12 127 ± 52 0 ± 011± 70± 00± 0
Lepidoptera
larva
0 ± 00± 011± 75± 50± 00± 0
Palpigrada 0 ± 00± 00
± 05± 50± 00± 0
Pauropoda 32 ± 15 60 ± 28 175 ± 34 526 ± 398 0 ± 037± 23
Protura 43 ± 28 48 ± 23 32 ± 32 80 ± 27 11 ± 11 16 ± 11
Pseudoscorpia 0 ± 00± 058± 20 53 ± 19 0 ± 00± 0
Psocoptera 35 ± 21 0 ± 00± 011± 70± 05± 5
Symphyla 110 ± 43 80 ± 60 228 ± 55 292 ± 125 5 ± 511± 7
Tisanoptera 53 ± 23 8 ± 80± 00± 05± 50± 0
Index
H
0
0.94 ± 0.05 0.99 ± 0.07 1.57 ± 0.10 1.43 ± 0.08 0.93 ± 0.08 0.96 ± 0.04
E 0.44 ± 0.02 0.51 ± 0.03 0.76 ± 0.04 0.67 ± 0.03 0.72 ± 0.06 0.61 ± 0.04
NT 8.89 ± 0.42 7.38 ± 0.62 7.92 ± 0.50 8.42 ± 0.38 4.00 ± 0.44 5.08 ± 0.31
A/C 1.85 ± 0.42 1.35 ± 0.20 1.15 ± 0.13 1.17 ± 0.10 1.51 ± 0.26 1.11 ± 0.23
QBS-ar 147 ± 19 140 ± 12 173 ± 15 172 ± 17 62 ± 12 102 ± 7
G grassland, W woodland, AR arable land
Biodivers Conserv (2011) 20:1073–1087 1079
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Indices
Statistical analysis of the indices (H
0
, E, NT, QBS-ar, A/C) used for the land use typologies
showed significant differences for almost all of them, although a common trend was not
identified (Table 3). The diversity index H
0
(F=18.750, p \0.001) showed its highest
mean value in W samples (mean = 1.50, SE = 0.06) and pairwise comparisons high-
lighted significant differences both for G (mean = 0.96, SE = 0.4) and AR (mean = 0.94,
SE = 0.04) samples. These latter two land use typologies were not significantly different
from each other using the diversity index. On the contrary, in the case of NT (F=22.559,
p \0.001), AR (mean = 4.54, SE = 0.30) significantly differed from both the other land
use typologies in the pairwise comparisons, whereas in G (mean = 8.18, SE = 0.38) and
W plots (mean = 8.17, SE = 0.29) higher but not significantly different NT values were
Table 3 ANOVA test for effect of land use typologies on microarthropod abundances and index values
df F G vs. W G vs. AR W vs. AR
Taxon
Acari 2,11 43.949*** *** *** ns
Araneida 2,11 3.202 ns ns ** ns
Chilopoda 2,11 9.473** *** ns ***
Coleoptera adults 2,11 25.264*** *** ns ***
Coleoptera larva 2,11 3.181 ns ns ns ns
Collembola 2,11 32.983*** *** *** ns
Dermaptera 2,11 1.293 ns ns ns ns
Diplopoda 2,11 1.439 ns ns ns ns
Diplura 2,11 3.566 ns ns ns ns
Diptera larva 2,11 4.440* ns ns *
Hemiptera 2,11 30.707*** *** *** ns
Hymenoptera adults 2,11 3.085 ns *** ** ns
Isopoda 2,11 6.893* ** ** ns
Lepidoptera larva 2,11 11.858** ns ns ns
Palpigrada 2,11 1.293 ns ns ns ns
Pauropoda 2,11 4.203* *** ns ***
Protura 2,11 1.640 ns ns ns ns
Pseudoscorpia 2,11 18.616*** *** ns ***
Psocoptera 2,11 1.010 ns ns ns ns
Symphyla 2,11 5.606* *** ns ***
Tisanoptera 2,11 4.329* ** * ns
Index
H
0
2,11 18.750*** *** ns ***
E 2,11 25.808*** *** *** ns
NT 2,11 22.559*** ns *** ***
A/C 2,11 0.394 ns ns ns ns
QBS-ar 2,11 11.265*** ns ** ***
Significant differences in pairwise comparisons
G grassland, W woodland, AR arable land
* p \ 0.05,** p \ 0.01,*** p \ 0.001, ns not significant
1080 Biodivers Conserv (2011) 20:1073–1087
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observed. Pielou’s evenness index (F=25.808, p \ 0.001) showed the lowest mean
values in G (mean = 0.47, SE = 0.02), which significantly differed from both W
(mean = 0.72, SE = 0.03) and AR sites (mean = 0.67, SE = 0.03). These latter two land
use typologies did not differ in E index values. The QBS-ar values (F=11.265,
p \0.001) in the pairwise comparisons showed the same trend as observed for the NT. In
fact, G (mean = 143, SE = 11) and W (mean = 172, SE = 10) did not significantly differ
from each other, but they were significantly higher in comparison to the AR plots
(mean = 82, SE = 10). Statistical differences for the A/C ratios were not found in the land
use comparisons.
Seasonal differences
In G, significant differences in seasonal abundance were observed for Acari (F=5.954,
p \0.05), Tisanoptera (F=5.410, p \0.05) and Coleoptera, for both adult and larval
stages (F=2.679, p \0.05 and F=9.090, p \ 0.05, respectively). The mean densities of
Acari and Tisanoptera were higher in spring with observed values of 35065 and 53 ind/m
2
,
respectively, whereas in autumn these values were 16420 and 8 ind/m
2
, respectively.
Coleopteran adult abundances were 255 ind/m
2
in spring and 123 ind/m
2
in autumn. The
same trend was also observed for coleopteran larval densities, whose mean values were
637 ind/m
2
in spring and 255 ind/m
2
in autumn. In W, no taxa showed significant dif-
ferences in seasonal abundance. In AR samples, the mean abundance values of 4081 and
6055 ind/m
2
were recorded for Acari and Collembola in autumn, respectively. These
values were significantly different (F=7.044, p \ 0.05 for Acari and F=16.100,
p \0.01 for Collembola) from spring samples, when the observed mean values were only
1062 and 605 ind/m
2
respectively. A significantly higher abundance of coleopteran adults
(F=8.402, p \0.001) was also observed in autumn, with a mean density of 345 ind/m
2
,
whereas in spring it was only 27 ind/m
2
.
No land significant seasonal differences of the H
0
, E, NT or A/C indices were observed
for any of the land use typologies (Table 4). On the contrary, a significant seasonal dif-
ference of QBS-ar values was observed in AR samples (t =-5.665, p \0.05), with mean
values of 62 and 102 in spring and autumn respectively.
Discussion
Microarthropod communities in the three land use typologies differed both for the taxa
observed and their abundance, as highlighted by the PCA graphical representation. The
higher grassland and woodland sample scatterings are likely to be a consequence of the
aggregated distribution rather than the constant presence of rare taxa, especially in the case
of the vertical axis. Both ANOVA and PCA showed a significantly higher abundance of
Acari and Collembola in G soil communities, illustrating the suitable conditions of this
habitat for these taxa. Previous research has also highlighted grasslands and perennial
crops as having the highest microarthropod densities and biomass compared with arable
lands (Lagerlof and Andre
´
n 1991). Collembola are particularly known as one of the most
abundant microarthropod groups in grasslands (Bardgett and Cook 1998) and for the
positive correlation between their numbers and the productivity of this land use typology
(Bardgett et al. 1993). The present data agree with the higher soil fertility usually observed
in grasslands, since soil microarthropod communities are predominantly regulated by
bottom-up forces. In fact, the high amount of energy transferred via plants to the soil in this
Biodivers Conserv (2011) 20:1073–1087 1081
123
habitat stimulates microbial growth, which results in an increased food resource for
edaphic fauna (Cole et al. 2005). The higher abundance of microarthropods allows the soil
to perform key functions such as decomposition and nutrient cycling. In fact, most of the
effects of edaphic fauna in fundamental processes for agricultural management are driven
mainly by abundance and biomass rather than by species composition (Cole et al. 2004;
Chauvat et al. 2007). On the contrary, the reduction in Acari and Collembola populations
in AR plots confirms the adverse effects of tillage and intensive agricultural practices on
Table 4 ANOVA (F) and t-test (t) for season effect on microarthropod abundances and index values in
each land use typology
GWAR
df F df F df F
Taxon
Acari 1,10 5.954* 1,6 2.646 ns 1,6 7.044*
Araneida 1,10 0.411 ns 1,6 0.101 ns 1,6 6.000 ns
Chilopoda 1,10 0.512 ns 1,6 0.397 ns 1,6 nt
Coleoptera adults 1,10 5.212* 1,6 0.429 ns 1,6 42.926**
Coleoptera larva 1,10 9.090* 1,6 0.022 ns 1,6 1.158 ns
Collembola 1,10 2.462 ns 1,6 1.286 ns 1,6 16.100**
Dermaptera 1,10 nt 1,6 1.000 ns 1,6 nt
Diplopoda 1,10 0.034 ns 1,6 1.242 ns 1,6 nt
Diplura 1,10 1.593 ns 1,6 0.245 ns 1,6 nt
Diptera larva 1,10 0.384 ns 1,6 0.152 ns 1,6 0.416 ns
Hemiptera 1,10 2.429 ns 1,6 nt 1,6 3.000 ns
Hymenoptera adults 1,10 1.045 ns 1,6 0.780 ns 1,6 2.038 ns
Isopoda 1,10 4.148 ns 1,6 1.000 ns 1,6 nt
Lepidoptera larva 1,10 nt 1,6 0.429 ns 1,6 nt
Palpigrada 1,10 nt 1,6 1.000 ns 1,6 nt
Pauropoda 1,10 0.810 ns 1,6 0.685 ns 1,6 2.983 ns
Protura 1,10 0.330 ns 1,6 1.848 ns 1,6 0.201 ns
Pseudoscorpia 1,10 nt 1,6 0.016 ns 1,6 nt
Psocoptera 1,10 4.213 ns 1,6 3.000 ns 1,6 1.000 ns
Symphyla 1,10 1.000 ns 1,6 0.007 ns 1,6 0.429 ns
Tisanoptera 1,10 5.410* 1,6 nt 1,6 1.000 ns
Index
H
0
1,10 0.037 ns 1,6 0.523 ns 1,6 0.678 ns
E 1,10 2.999 ns 1,6 1.414 ns 1,6 5.487 ns
NT 1,10 4.592 ns 1,6 0.580 ns 1,6 2.930 ns
A/C 1,10 0.475 ns 1,6 0.208 ns 1,6 0.184 ns
GWAR
df t df t df t
QBS-ar 5 0.504 ns 3 0.430 ns 3 -5.665*
G grassland, W woodland, AR arable land, nt no specimen of this taxon was observed
* p \ 0.05,** p \ 0.01,*** p \ 0.001, ns not significant
1082 Biodivers Conserv (2011) 20:1073–1087
123
soil fauna (Wallwork 1976; Hulsmann and Wolters 1998; Kladivko 2001), and conse-
quently on soil functions. These negative effects were also highlighted by the significant
reduction of the QBS-ar index and the restriction to the lower side of the PCA graphical
representation of arable land samples, since typical steady soil taxa were positively cor-
related with the vertical axis. In the case of soft bodied organisms, such as Symphyla and
Pauropoda, ploughing is known as the main factor determining the reduction in their
populations because these arthropods are easily crushed if located near the soil surface
during tilling; moreover, ploughing destroys the channels they use to move around in
(Peachey et al. 2002). The ANOVA test showed a significantly higher abundance of
Pauropoda, Symphyla and Chilopoda only in woodland samples, whereas no differences
were found in G versus AR comparisons. This discordance of indications between PCA
and ANOVA highlighted the fact that the abovementioned taxa were observed in G
samples with a lower frequency and abundance in comparison with the W plots, but they
represent a part of the grassland microarthropod community that generally lacks in arable
land soil fauna. Although these groups were fewer in number, although diversified in taxa,
they might play an important role in organic matter and energy conversion processes (Tang
et al. 2006).
In this research only microarthropods inhabiting soil were studied; litter layer organisms
were not sampled. The use of soil only could explain the higher abundances of Acari and
Collembola observed in G samples in comparison with W sites. In fact, in woodland
habitats these taxa have higher abundances in the litter layer than in soil because of the
greater availability of food resources in litter (Sadaka and Ponge 2003). On the contrary,
the higher abundance of typical steady soil taxa such as Pauropoda and Symphyla in both
W versus G and W versus AR comparisons highlights the suitable environmental condi-
tions for soil fauna of the W habitat (Bedano et al. 2006a). In fact, the tree canopy cover
and litter layer lessen temperature and moisture variations, whereas in agricultural lands
the soil is more exposed to climatic stresses such as rain and heat (Bird et al. 2004; Eaton
et al. 2004). Moreover, the major abundances of large sized predators such as Chilopoda
and Pseudoscorpia in the W sites emphasizes the higher complexity of soil microarthropod
communities in this type of habitat.
The constancy of the woodland soil environment was also demonstrated by the absence
of significant seasonal differences both in taxa abundances and index values. On the
contrary, in the two agricultural habitats, Acari and coleopteran adults highlighted con-
trasting seasonal population dynamics. Both these taxa reached their highest abundances in
the spring and autumn samples in G and AR, respectively. These trends highlighted dif-
ferences in the soil habitats which could be related to food availability and organic matter
dynamics. In fact, the difference in the agricultural management of G and AR plots causes
great differences in time and quantity of organic matter input during the growing season;
for instance, the production of roots and root exudates, or manure or chemical fertilization
in different seasons, and the presence of vegetal residuals after the harvest. In the AR
samples Collembola showed the same trend as observed for the mites, suggesting that soil
under this type of cultivation attains better trophic and environmental conditions at the end
of the growth season. Moreover, the increases in abundance of both of these taxa in the AR
samples showed that they are able to rapidly recover from the detrimental effects of tilling
activities (Neave and Fox 1998; Ferraro and Ghersa 2007). Differences in the type of food
supplies in G and AR were highlighted by the higher abundance, almost exclusive in G, of
groups rich in phytophagous species, such as Hemiptera and Tisanoptera.
The number of observed taxa (NT) seems to confirm the hypothesis that grasslands are a
reservoir of biodiversity. In fact, higher NT values with no significant differences in
Biodivers Conserv (2011) 20:1073–1087 1083
123
W plots were observed in comparison to AR plots. Moreover, the taxa generally present in
G, but extremely rare (Pauropoda, Symphyla) or completely lacking (Chilopoda, Diplo-
poda, Diplura) in AR samples, are known for their sensitivity to environmental stresses
(Wallwork 1970; Menta et al. 2008), agreeing with the significantly higher QBS-ar scores
obtained in W and G in comparison with AR. This confirmed the positive correlation
between taxa biodiversity and soil quality. On the contrary, using the H
0
index in order to
measure biodiversity in G showed the lowest mean value because of the dominance of
Acari and Collembola in this site, which were collected in numbers ten times greater than
the other two habitats. Even though both H
0
and NT could be used as measures of bio-
diversity, H
0
takes into account not only the number of taxa but also their evenness, which
resulted in the difference observed in the trend of these indices. This was confirmed by the
E index which displayed its lowest values in G sites, highlighting the numerical dominance
by only a few taxa.
The QBS-ar index values in G were significantly higher in comparison with the AR
values and quite similar to those observed in the W natural areas, illustrating the higher soil
quality supported by this type of low-management cultivation.
Conclusion
The abundance of microarthropods in grassland soils demonstrates that this type of soil has
suitable trophic conditions to support microarthropod communities. This is because the
main animal food source in the soil, i.e. microflora, is stimulated by continuous inputs of
organic matter from the litter and roots during the year (Vreeken-Buijs et al. 1998).
Moreover, grassland sites show complex edaphic communities both taxonomically and
functionally, with predator and phytophagous groups in addition to fungi and debris
feeders. The higher abundances of Acari and Collembola in G sites resulted in low values
of H
0
and E indices, but they enable soil fauna to perform a larger amount of ecosystem
services. Although the influence of agricultural management on soil ecosystems has not
been precisely predicted, the reported changes in microarthropod abundance has affected
the soil processes in which soil fauna were involved (Bedano et al. 2006b). For this reason,
the observed reduction in the abundance and diversity of soil communities of AR (high
input management) plots may affect organic matter decomposition and nutrient avail-
ability. Even though the functional importance of soil biodiversity is not completely
understood, its conservation is an essential insurance against expected and unpredictable
environmental changes, and the precautionary principle suggests that soil biodiversity
protection should be considered in land use planning (Decaens et al. 2006).
Even though the G sites showed taxa diversity (NT) values similar to W areas, habitat
groups such as Pseudoscorpia, Symphyla and Pauropoda were observed exclusively or in
significantly higher numbers in W sites. These data demonstrate the importance of
woodlands for preserving microarthropod taxa, confirming the higher protective value of
the coexistence of different habitats in order to improve biodiversity (Romero-Alcaraz and
Avila 2000), and also highlighting the need to prevent landscape simplification.
Differences among the studied habitats were not only observed in taxon abundance and
diversity but also in seasonal population dynamics, another factor of diversity in soil
communities.
In agreement with our hypothesis, permanent grasslands are characterized by high
taxonomical diversity and suitable conditions for soil fauna, making them important res-
ervoirs for soil biodiversity in agricultural lands, as was also observed in previous studies
1084 Biodivers Conserv (2011) 20:1073–1087
123
on vegetation (Gardi et al. 2002). Moreover, this type of cultivation represents a good
example of agreement between ecology and economic aims, being it the basis of the high
quality cheese productions typical of this area (Parmesan cheese). The integrated man-
agement of soil fauna and agricultural practices is a holistic process that combines locally
available resources, the climate, socio-economical conditions and management practices
(Brussard et al. 2007). Permanent grasslands produce resources for human needs and also
maintain soil quality, one of the main issues in the definition of sustainable agriculture
(CGIAR 1988; Soil Science Society of America 1997). All of the activities aimed at the
definition of High Nature Value Farmlands (Paracchini et al. 2008), or at the reshaping of
the Common Agricultural Policy expenditure in view of biodiversity conservation (EEA
2009) outline the general recognition of the potential role of sustainable agriculture in
nature conservation.
Despite its utility as an indicator of environmentally friendly cultivation, soil quality
monitoring is often inaccessible to land managers because the measurement systems are
too complex, too expensive or both (Herrick 2000). This contributed to the development of
indicators and indices of quality based on soil organisms (Bongers 1990, 1999; Cortet et al.
2000; van Straalen 1998, 2004) such as the QBS-ar, which enable cheaper and easier
evaluations of soil quality. Differences in the QBS-ar values both between seasons and
between the land use typologies observed in this study highlighted the sensitivity of this
index and its correlation with ecological factors such as taxonomic diversity and soil
stability.
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... Studying the indirect short-and long-term effects of above-ground invertebrate and vertebrate herbivores on soil microarthropod communities, in subalpine grasslands in Switzerland, Vandegehuchte et al., in 2015 [60], highlighted that Prostigmata was one of the most abundant soil groups (from 7 identified soil invertebrate groups), followed by Collembola and Oribatida. In grasslands from Italy, 17 soil taxa were identified, dominant being Acari, Coleoptera and insect larvae [61]. Recent studies revealed that in temperate grasslands the most numerically abundant were Lumbricidae, Acari, Collembola, Enchytraeidae and macrofauna [62]. ...
... Our research teams up with similar studies, confirming that the soil fauna groups of Enchyraeidae, Lumbricidae, Collembola, Mesostigmata, Acaridae, Oribatida and insect larva are bioindicators for different types of grasslands from Europe, being used in monitoring programs [1,6,10,11,21,56,[60][61][62]. We also identified these seven edaphic communities in all five investigated experimental plots (control plot, organically and chemical fertilised grasslands) in the Bucegi Mountains, Romania. ...
... A higher resistance at soil penetration means a lower porosity and the lower capacity of invertebrates to migrate in soil, this phenomenon being an efficient method of edaphic fauna to adapt to rough environmental conditions (as dryness). The porosity of the soil is one of the most important factors which determined the vertical distributions of soil organisms, migrating on both a daily and a seasonal basis [2,57,61,66]. Soil pH is another important edaphic factor that influenced the invertebrate communities. A drastic reduction of the soil pH will decrease the abundance of the soil fauna. ...
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... Protura, Diplura, and Pauropoda, even if they affect soil processes less compared to soil-dwelling organisms [27], are highly sensitive to soil-stress conditions, and can be relevant for biomonitoring purposes [29,63]. Taxa richness and other ecological indicators, such as the Shannon and Simpson's diversity indexes, confirmed the evidence showed by the BSQ ar index, where the grassland is the habitat with the highest biodiversity [64]. According to Gope and Ray [65], the dynamics of microarthropods were probably dependent on the combined effect of vegetation cover and soil characteristics. ...
... Nevertheless, the application of a mulch layer significantly increased the abundance of different arthropod predators [66], especially predator mites. Overall, a more diverse and abundant soil microarthropod community seems to provide better soil functions by reflecting the resource availability in the soil ecosystem [64]. ...
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