ORIGINAL PAPER

Can ants be used as indicators of environmental impactscaused by arsenic?

Carla R. Ribas • Ricardo R. C. Solar •

Renata B. F. Campos • Fernando A. Schmidt •

Clarisse L. Valentim • Jose H. Schoereder

Received: 10 February 2011 / Accepted: 20 July 2011 / Published online: 4 August 2011

� Springer Science+Business Media B.V. 2011

Abstract We evaluated ants as bioindicators of envi-

ronmental impacts caused by arsenic residuals in the soil.

We tested the hypotheses that the presence of arsenic in the

soil affects: (1) estimates of resources and habitat condition

for arboreal and epigaeic ants; (2) species richness of

arboreal and epigaeic ants and (3) arboreal and epigaeic ant

species composition. Ants were sampled at an inactivated

raticide factory in Nova Lima, Minas Gerais, Brasil, which

used arsenic as one of its main byproducts. The following

environmental variables were measured: bioavailable

arsenic concentration in the soil, the number and density of

tree species, plant cover and leaf litter depth. The species

richness of arboreal ants decreased with increased bio-

available arsenic concentration whilst epigaeic ants

increased with arsenic. Arboreal ants were positively

related to the number of tree species, which in turn were

negatively affected by arsenic. We verified which ants are

good bioindicators of arsenic. Independent verification of

the influence of arsenic on background environmental

variables was fundamental in defining responses of ant

communities, as well as in identifying the most effective

pathways for the recovery of biological communities in

degraded areas.

Keywords Arboreal ants � Brazil � Epigaeic ants � Species

composition � Species richness � Toxic residuals

Introduction

One of the most prevalent negative impacts of human

activities on ecosystems is the release of toxic residuals

(e.g. heavy metals) (Ribeiro-Filho et al. 2001). These

residuals are highly toxic to plants and animals and may

have long-lasting effects on the structure of biological

communities (Hoffmann et al. 2000; Hoffmann and

Andersen 2003). They also are cumulative in plant tissues

that are ingested by animals, which may in turn be used for

human nutrition (Foster 2003).

The use of pesticides and fertilizers in agriculture

together with various aspects of the mining industry (Baird

2002; Smith et al. 1998) can lead to heavy metal release.

The release of arsenic to the environment is one of the

major risk factors facing the future integrity of ecosystems,

in addition to causing severe damage to human health,

including mutagenic and carcinogenic effects, and heart,

vascular and pulmonary diseases (Felipe et al. 2009).

C. R. Ribas � J. H. Schoereder

Departamento de Biologia Geral, Universidade Federal de

Vicosa, Vicosa, MG 36570-000, Brazil

e-mail: jschoere@ufv.br

C. R. Ribas (&)

Setor de Ecologia, Departamento de Biologia, Universidade

Federal de Lavras, Lavras, MG 37200-000, Brazil

e-mail: crribas@gmail.com

R. R. C. Solar � F. A. Schmidt � C. L. Valentim

Departamento de Entomologia—Programa de Pos-Graduacao

em Entomologia, Universidade Federal de Vicosa, Vicosa, MG

36570-000, Brazil

e-mail: rrsolar@gmail.com

F. A. Schmidt

e-mail: schmidt.fa@gmail.com

C. L. Valentim

e-mail: claralapa@gmail.com

R. B. F. Campos

Instituto Superior de Educacao de Divinopolis, Fundacao

Educacional de Divinopolis, Av. Parana, 3001, Jardim

Belvedere, Divinopolis, MG 35501-170, Brazil

e-mail: rbfcampos@gmail.com

123

J Insect Conserv (2012) 16:413–421

DOI 10.1007/s10841-011-9427-2

Environmental monitoring protocols have been devel-

oped to verify the level of toxic residuals in affected

locations (Hilty and Merenlender 2000). The simplest way

to detect the presence of toxic residuals on the environ-

ment is to directly measure their concentration, but this

could be too expensive and the presence of toxins alone

may or may not be indicative of a negative (or positive)

effect on biological communities (Goodsell et al. 2009).

Another, complementary approach is to use bioindicators

which can reveal the impact of toxins on overall envi-

ronmental condition, allowing some insight into the likely

ecological mechanisms that may herald future environ-

mental problems (McGeoch 1998; Niemi and McDonald

2004).

The use of certain species or groups of organisms as

indicators of the effectiveness of environmental manage-

ment practices has been widespread in recent decades

(Gardner 2010; Hilty and Merenlender 2000). The bio-

logical parameters most commonly employed to evaluate

the level of environmental impacts include measurements

of abundance, diversity, evenness and species composition

(Gollan et al. 2011; Graham et al. 2009).

Ants are among the groups of organisms most com-

monly employed as bioindicators (e.g. Andersen and

Majer 2004; Andersen et al. 2004; Majer et al. 2007;

Ottonetti et al. 2006; Philpott et al. 2010). Their use has

been proposed for monitoring recovery from environ-

mental impacts, as indicators of conservation status as

they present a wide distribution, high levels of abundance,

are amenable to sampling, play ecologically significant

roles in the functioning of ecosystems, are sensitive to

environmental changes, and are relatively well known

ecology and taxonomy (Agosti et al. 2000; Underwood

and Fischer 2006).

Some authors report that some ant species can easily

accumulate heavy metals, including arsenic (Eeva et al.

2004; Rabitsch 1997; Sorvari et al. 2006). On the other

hand, Kuehnelt et al. (1997) and Moriarty et al. (2009)

observed that other species did not accumulate arsenic or

stored very low levels of it in their bodies.

The present study is aimed at assessing the potential use

of ant communities as bioindicators of the environmental

impact caused by residuals of arsenic in the soil. We tested

the following hypotheses about the effect of bioavailable

arsenic concentration on ant communities: (1) estimates of

resource availability and habitat condition for ants are

negatively related to bioavailable arsenic concentration and

this response is reflected in changes in ant species richness;

(2) the species richness of arboreal and epigaeic ants

decreases with the increased concentration of bioavailable

arsenic in the soil; and (3) arboreal and epigaeic ant species

composition is modified relative to levels of bioavailable

arsenic concentration in the soil.

Materials and methods

Sampling site

The sampling was performed in March 2007, at a hill know

as Morro do Galo (19859005.400S and 43849033.200W), in

Nova Lima, Metropolitan area of Belo Horizonte, in Minas

Gerais state, southeastern Brazil.

The area of study belongs to the mining company An-

gloGold Ashanti South America, where a rat poison factory

operated for around 35 years. This factory was installed at

the base of the hill and it had a main chimney through

which arsenic trioxide residuals were released, resulting in

a complete clearance of the native vegetation.

In 1975, the factory ceased its activities, after that in the

area began a progressive natural vegetation regeneration

process. However, for about 20 years, the vegetation was

sparse and almost exclusively composed of grasses. Due to

this fact, in 1995 a vegetation recovery program was

implemented with soil tillage, lime and fertilizers appli-

cation and the introduction of 41,124 tree seedlings from

80 native and exotic species, with arboreal and shrubby

characteristics.

Ants

A transect of 270 m was delimited from the location where

the plant chimney was installed. Twenty-seven sampling

points 10 m apart from each another were distributed along

the transect. At each sampling point, we collected ants in

two microhabitats (epigaeic and arboreal) with the use of

pitfall traps. The transect length was limited by a ditch

made by the company to catch the flow of the rainfall

together with arsenic leached from the soil. Most ants have

relatively short foraging distances (Lach et al. 2010), and it

is likely that ants collected in two consecutive pitfall

belong to different colonies.

The traps were made of plastic pots (diameter of 8 cm;

height of 12 cm) with two recipients installed in its central

part holding bait (sardines and honey). The area of the trap

surrounding the baits contains 200 ml of a conservative

solution of glycerol (5%) and salt (0.9%), such that the ants

that access the trap are captured without making contact

with the baits. The epigaeic traps are buried with their

opening at the soil level (Bestelmeyer et al. 2000) and the

arboreal traps are fixed at about 1.3 m of height (breast

height) in tree trunks (Ribas et al. 2003).

The traps remained in the field for 48 h after which they

were taken to the Universidade Federal de Viscosa (UFV)

Laboratory of Community Ecology, where the ants were

screened and identified up to the level of genus, with the

use of identification keys provided by Bolton (1994) and

Fernandez (2003). When possible, individuals were

414 J Insect Conserv (2012) 16:413–421

123

identified up to the level of species or to morphospecies by

Rodrigo Feitosa (USP) through the comparison with

specimens in the reference collection of the Sao Paulo

University (USP) Museum of Zoology.

Environmental and arsenic variables

The following environmental variables were measured at

each sampling point: number of tree species, tree density,

plant coverage, depth of litter and bioavailable arsenic

concentration.

To determine the number of tree species and the density

of trees, we delimited a rectangle of 2 9 5 m around each

sampling point. In each one of these areas, we counted the

morphospecies and the number of individuals of trees with

circumference at breast height (CBH) of at least 15 cm.

The sampling was alternately performed on the right and

left sides of the transect to avoid any systematic bias. We

opted to analyze tree density at a very local scale because

this environmental variable is likely to have local effects.

Moreover, as we sampled ants at each 10 m interval an

increase in the sampling area for trees would introduce

interdependency amongst points.

The plant coverage at the level of the trees was mea-

sured using digital images with the use of a camera posi-

tioned at a height of 1.3 m, with a fish-eye lens facing

upwards. The percentage of plant coverage of the photos

was analyzed using the Gap Light Analyzer software sys-

tem—GLA (Frazer et al. 1999). The analysis of the plant

coverage at the soil level was performed similarly to the

procedure described for the plant coverage at tree level, but

photographs were taken with the camera installed at soil

level.

Using a digital caliper rule, we also measured the litter

depth, near to each epigaeic trap, and collected soil sam-

ples for the evaluation of the bioavailable arsenic

concentration.

The bioavailable arsenic concentration was assessed by

chemical analysis, extracting the arsenic from the soil

samples with a Mehlich 3 extractor that consists of a

mixture of acids, salts and chelants able to extract the

bioavailable arsenic (Mehlich 1984). To quantify the bio-

available arsenic, dry soil samples of 5 cm3 (three samples)

were sifted (mesh sieve—2 mm) and mixed with 50 mL of

Mehlich 3 extractor in erlenmeyer flasks. These samples

were homogenized in a shaker for 5 min at 220 rpm and

then kept at rest by 16 h. Next, 10 mL of the supernatant

were pipetted and used to measure the bioavailable arsenic

concentration in a spectrophotometry inductively coupled

plasma emission (Perkin Elmer Optima—3300 DV). To

evaluate the accuracy of the method we used blank samples

as a reference.

Statistical analyses

To assess if the enhancing of bioavailable arsenic con-

centration (explanatory variable) leads to a reduction in the

measured environmental variables we used linear regres-

sions, with a Poisson distribution for count data and

Gaussian for the others. Our approach differs from the

classical ANCOVA approaches, as we opted to use GLMs

to choose the most appropriate distribution of errors for

different response variables. When using frequency data

(e.g. count data - number of ant/trees species), the Pois-

son distribution is more suitable than Gaussian (for more

details see Logan 2010). Therefore, we use chi squared

tests with count data because the analysis of frequency data

involves comparing observed and expected frequency

ratios. Moreover the v2 distribution of probabilities is the

most fitted on Poisson data. On the other hand, when data

were Gaussian, we made the classical F test approach to

reach the probabilities (Crawley 2007).

The analyses were performed with the use of the R

statistical software (R Development Core Team 2009),

followed by the analysis of residuals to verify the distri-

bution of errors and adequacy of the model (Crawley

2002).

To verify the effect of the environmental variables on

ant species richness hierarchical partitioning (Chevan and

Sutherland 1991) was used to examine the independent

effects of the five key environmental variables (number and

density of tree species, plant cover at the level of the trees

and at the soil level and depth of litter) and arsenic on the

richness of arboreal and epigaeic ant species. Hierarchical

partitioning is a multiple-regression technique in which all

possible linear models are jointly considered to indentify

the most likely causal factors, providing a measure of the

effect of other variables (Chevan and Sutherland 1991;

Mac Nally 2000). The models included Poisson errors, and

we evaluated competing models based on changes to the

log-likelihood goodness of fit statistic. The significance of

independent effects was obtained by using a randomization

routine with 1,000 iterations (Mac Nally 2002). Hierar-

chical partitioning and associated randomization tests were

implemented using the hier.part package, freely available

in the R statistical software (R Development Core Team

2009).

To test the hypothesis that the arboreal and epigaeic ant

species richness decreases with the increased bioavailable

arsenic concentration in the soil, an analysis of covariance

was carried out, in which the bioavailable arsenic con-

centration in the soil and the microhabitat were the

explanatory variables, with ant species richness (at each

point) as the response variable. The analyses were also

performed using the R statistical software (R Development

Core Team 2009), followed by the analysis of residuals for

J Insect Conserv (2012) 16:413–421 415

123

evaluating the error distribution and adequacy of the model

(Crawley 2002).

To verify if arboreal and epigaeic ant species compo-

sition is modified relative to bioavailable arsenic concen-

tration in the soil we produced a two dimensional

ordination by NMDS (non-metric multidimensional scal-

ing), using the Raup-Crick index of similarity (Hammer

et al. 2001) calculated from matrices of presence/absence

using PAST (Hammer et al. 2001). We plotted the two axes

of NMDS scaling each point in the graph by its bioavail-

able arsenic concentration.

Results

Thirty-six ant species belonging to 16 genera were col-

lected, representing seven out of the 14 subfamilies

described by Bolton (2003) for the Neotropical region

(‘‘Appendix’’). The epigaeic microhabitat presented the

highest number of species, with a total of 32 belonging to

16 genera, while the arboreal microhabitat presented only

17 species, belonging to eight genera.

Myrmicinae was the subfamily with the highest number

of species with 16 species of ants (44%), followed by

Formicinae with ten species (28%), Pseudomyrmecinae

with four species (12%), Ponerinae and Ectatomminae with

two species (6%), Dolichoderinae was represented by only

two species (6%) and Ecitoninae by only one species (3%).

Environmental variables

When the relations between the environmental variables and

arsenic were analyzed, the number of tree species presented a

negative relation with the bioavailable arsenic concentration

(v2 = 4.71; P = 0.03; Fig. 1) while plant cover at the soil

level presented a positive relationship with the bioavailable

arsenic concentration (F = 7.24; P = 0.01; Fig. 2). The

density of trees (v2 = 4.36; P = 0.18); depth of litter

(v2 = 531.6; P = 0.10) and plant cover at the tree level

(F = 1.13; P = 0.30) did not present a significant relation-

ship with arsenic levels.

Ant species richness

In the hierarchical partitioning analyses, only the number

of tree species (NTS) presented a positive and significant

influence on the arboreal ant species richness (Fig. 3a).

None of the other environmental variables (density of

trees = DT, plant cover at the level of the trees = PCTL

and depth of litter = DL) or arsenic (A) presented a sig-

nificant relationship with epigaeic ant species richness,

although the plant cover at the soil level (PCSL) can

explain most of the variation in species richness (Fig. 3b).

The ant species richness varied between the arboreal and

epigaeic microhabitats (v2 = 22.3; P \ 0.0001), with a

significant interaction with bioavailable arsenic concen-

tration (v2 = 4.73; P = 0.03; Fig. 4). In other words, the

relationship with arsenic is distinct depending on the

microhabitat (v2 = 1.66; P = 0.20), being positive for

the epigaeic microhabitat and negative for the arboreal.

Species composition

The variation in the arboreal and epigaeic ant species

composition among the 27 sampling points seems not to be

explained by changes in arsenic levels, as the scaling of

points according to the bioavailable arsenic concentration

did not produce a consistent trend in the species compo-

sition (Fig. 5).

Bioavailable arsenic concentration (ppm)0 200 400 600 800

Num

ber

of tr

ee s

peci

es

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Fig. 1 Relationship between number of tree species and bioavailable

arsenic concentrations in the soil (v2 = 4.71; P = 0.03)

Bioavailable arsenic concentration (ppm)0 200 400 600 800 1000 1200 1400 1600

Pla

nt c

over

at s

oil l

evel

0

20

40

60

80

Fig. 2 Relationship between plant cover at soil level and bioavailable

arsenic concentration in the soil (F = 7.24; P = 0.01)

416 J Insect Conserv (2012) 16:413–421

123

Discussion

Differences in arboreal and epigaeic ant species richness

were related to increases in bioavailable arsenic concen-

tration in the soil, but in opposite ways. Increases in bio-

available arsenic concentration leads to lower numbers of

arboreal ant species, whilst the number of epigaeic ant

species increased. These results may be explained by a

direct effect of arsenic on ant communities or by an indi-

rect effect of arsenic on the resources and conditions that

affect the ant species richness.

Some studies report that ants can easily accumulate

heavy metals, such as arsenic (Eeva et al. 2004; Rabitsch

1997; Sorvari et al. 2006). However, Kuehnelt et al. (1997)

and Moriarty et al. (2009) observed that ants do not

accumulate arsenic or store it at very low levels in their

bodies, with higher metal accumulation found only in the

jaws of the ants. Nummelin et al. (2006) argue that among

several groups of invertebrates, ants are the less sensitive to

detect differences in the pollution caused by heavy metals.

According to results found by Grze‘s (2009), ant species

richness increases as pollution by metals increases, sug-

gesting that it can be explained by changes in the inter-

actions among species, rather than any changes in abiotic

conditions.

In the present study it is possible to infer that arsenic

does not affect ants directly (Fig. 3). The number of tree

species was the environmental variable that appears to

make an important contribution to the species richness of

arboreal ants, while the plant cover at soil level was the

variable that contributed most (although it was not signif-

icant) for the determination of the epigaeic ant species

richness. Thus, a possible explanation is that arsenic levels

affect changes in key environmental variables, which, in

turn, affect ant species richness. The structure of the veg-

etation, such as the number of tree species, affects ant

communities (Lassau and Hochuli 2004; Vasconcelos et al.

2008, 2010), and a reduction in the availability of resources

and/or the quality of the resource is related to a decrease in

the ant species richness (Ribas et al. 2003).

The same rationale may be used to explain the increased

epigaeic ant species richness with the bioavailable arsenic

concentration. The positive relationship between the plant

cover at soil level and arsenic may be caused by the

decreased number of tree species, probably caused by the

increased spaces in the canopy, which favors the success of

(a) Arboreal ant species richness

Environmental variables

PCTL DT NTS A

% In

depe

nden

t effe

ct

0

20

40

60

80

+

Environmental variablesDL A PCSL

% In

depe

nden

t effe

ct

0

10

20

30

40

50

60 (b) Epigaiec ant species richness

Fig. 3 Distribution of percentage of independent effects of measured

environmental variables on (a) arboreal ant species richness and

(b) epigaeic ant species richness, as determined by hierarchical

partitioning. Black bars represent significant effects (P \ 0.05), as

determined by randomization tests. Positive relationships are shown

by ? symbol. Environmental variables include plant cover at the level

of trees (PCTL), depth of litter (DL), density of trees (DT), number of

tree species (NTS), bioavailable arsenic concentration (A) and plant

cover at soil level (PCSL)

Fig. 4 Relationship between ant species richness in arboreal and

epigaeic microhabitats (v2 = 22.3; P \ 0.0001), and the bioavailable

arsenic concentration in the soil (v2 = 1.66; P = 0.20). Distinct

response of arboreal and epigaeic ants to bioavailable arsenic

concentration (interaction: v2 = 4.73; P = 0.03)

J Insect Conserv (2012) 16:413–421 417

123

grasses and low shrubs resistant to arsenic. Larger plant

cover at the soil positively affects the ant species richness,

with increased structural heterogeneity of the environment,

or increased protection against water loss.

According to Hoffmann (2009), the structure of ant

communities is primarily and directly influenced by

parameters related to the vegetation and soil over distur-

bance events. Our results corroborate these insights, since

the concentration of arsenic (disturbance) does not appear

to be the main explanatory variable for the variation in the

ant species richness (Fig. 3). The causality of the relation is

only noticed by the relation between the number of tree

species (main explanatory variable of the arboreal ant

species richness) with the bioavailable arsenic concentra-

tion and with the arboreal ant species richness.

Although several studies have used ants as bioindicators

in Brazil (e.g. Coelho et al. 2009; Costa et al. 2010;

Delabie et al. 2006; Pereira et al. 2007; Santana-Reis and

Santos 2001; Schmidt and Diehl 2008; Vasconcelos 1999;

Vasconcelos et al. 2000), most authors analyzed the

response of the ant species richness and/or the species or

guild composition, and achieved contrasting results. Some

studies found significant responses of ant species richness

to different environmental impacts (Costa et al. 2010;

Delabie et al. 2006; Pereira et al. 2007; Silva and Brandao

1999), while others concluded that changes in species

composition is a more adequate parameter for bioindication

(Coelho et al. 2009; Schmidt and Diehl 2008; Vasconcelos

et al. 2000), especially in dynamic environments (Gollan

et al. 2011).

Contrary to the work cited above, in our study there was

no variation in the species composition in any of the two

microhabitats sampled, though species richness did vary.

This could mean that there is homogeneity among the

sampling units which host a generalist ant fauna and that

each species has the same chance to access every habitat

within the area. However, the variability in environmental

variables determines which species from the generalist ant

pool should occur in each sampling unit, resulting in a

variation of species richness among them.

One of the possible explanations for the relationships

with species richness is that richness is more responsive to

disturbance in more homogeneous systems, or those with

higher gradients of disturbance, while in more complex and

dynamic systems, such as those found by Coelho et al.

(2009), Schmidt and Diehl (2008) and Vasconcelos et al.

(2000), the turnover of specialist and generalist among

habitats results in comparable levels of richness yet clear

differences in species composition. Thus, species richness

could be a better parameter for bioindication of disturbance

in homogeneous areas (as in this study) than in heteroge-

neous and dynamic areas (where species composition may

be more appropriate).

Conclusions

Most studies on bioindicators focus only on the direct

response pattern of the ant community to environmental

impact, rather than seeking to identify indirect effects from

changes in environmental parameters.

Ant communities belonging to different microhabitats

may present different responses to environmental impacts

(Underwood and Fischer 2006) because they are exposed to

different situations of habitat condition and resource

availability. Therefore, it is important to analyze changes to

ant communities in different microhabitats as demonstrated

in this study, where different ant-disturbance relations were

observed between the arboreal and epigaeic microhabitats.

The present study demonstrated that ants could be used

as bioindicators of the presence of arsenic (and probably

Axis 2-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4

Axi

s 1

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3(a) Arboreal ant species composition

Axis 2-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3

Axi

s 1

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3 (b) Epigaiec ant species composition

Fig. 5 Non-metric multidimensional scaling of a arboreal ant species

composition and b epigaeic ant species composition with individual

points scaled by changes in bioavailable arsenic concentration. Larger

points represent higher levels of bioavailable arsenic concentration

418 J Insect Conserv (2012) 16:413–421

123

other heavy metals) in the soil. The ant faunas of the two

microhabitas had contrasting relationships with bioavail-

able arsenic concentrations. The fact that the two strata

exhibited contrasting responses to arsenic through their ant

fauna is easily explained. We observed that the ant com-

munities were responsive to changes in arsenic effects via

changes in the habitat condition and availability of envi-

ronmental resources. Ants may also provide good indica-

tors of biodiversity, since they indicated variations in the

ecological structure of the environment (number of tree

species, in this study), an important variable for several

other groups of organisms (e.g. Felton et al. 2010; Paillet

et al. 2010; Tilman and Pacala 1993).

We concluded that our proposal to verify the influence

of different environmental variables, besides the direct

effect of the pollutant itself, is fundamental to evaluating

the responses of biological communities to environmental

impacts caused by the application of pollutant. Moreover,

the analyses of different community strata allowed us to

observe that different microhabitats can respond differently

to the same pollutant. These results have practical impli-

cations as the use of biologically meaningful environ-

mental variables to describe habitat condition is important

for guiding future restoration work in degraded areas.

Acknowledgments This study is resulted from the research project:

CRA—270/07—‘‘Utilizacao de formigas como bioindicadoras de

impacto ambiental e de sua recuperacao em Cerrado e em Mata

Atlantica’’. We are grateful to AngloGold Ashanti South America for

allowing the collections, to Julio N.C. Louzada for his assistance with

some statistical analyses, to Toby A. Gardner for his valuable sug-

gestions in the English expression and to anonymous referees for its

critical reading. We are also grateful for Rodrigo M. Feitosa, who

checked identification of ant species. The authors received grants and

funding from FAPEMIG, CAPES and CNPq.

Appendix

See Table 1.

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Andersen AN, Majer JD (2004) Ants show the way down under:

invertebrate as bioindicators in land management. Front Ecol

Environ 2:291–298

Andersen AN, Fisher A, Hoffmann BD, Read JL, Richards R (2004)

Use of terrestrial invertebrates for biodiversity monitoring in

Australians rangelands, with particular reference to ants. Austral

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Table 1 Frequency of occurrence of ant species captured in two

microhabitats (epigaeic and arboreal) along twenty-seven sampling

points at Nova Lima—MG

Epigaeic Arboreal

Dolichoderinae

Linepithema sp. 1 4

Tapinoma sp. 1 3

Ecitoninae

Neivamyrmex sp. 1

Ectatomminae

Ectatomma brunneum 7 2

Ectatomma edentatum 9

Table 1 continued

Epigaeic Arboreal

Formicinae

Brachymyrmex nr. patagonicus 11

Brachymyrmex sp. 1 3

Camponotus atriceps 6

Camponotus crassus 3 3

Camponotus fastigatus 1

Camponotus rufipes 9 4

Camponotus sp. 1 1 6

Camponotus sp. 2 3 1

Camponotus sp. 3 1

Paratrechina sp. 1 13

Myrmicinae

Atta sexdens 11

Cephalotes pusillus 3

Crematogaster cisplatinalis 1

Crematogaster curvispinosa 1 2

Crematogaster torosa 1

Nesomyrmex sp. 1 1 1

Pheidole sp. 1 14 2

Pheidole sp. 2 5 4

Pheidole sp. 3 1

Pheidole sp. 4 4

Pheidole sp. 5 1

Pheidole sp. 6 1

Pheidole sp. 7 23 1

Pogonomyrmex naegelii 1

Solenopsis invicta 1 1

Solenopsis sp. 1 1

Solenopsis sp. 2 1

Ponerinae

Hypoponera sp. 1 1

Odontomachus haematodus 1

Pseudomyrmecinae

Pseudomyrmex termitarius 6

Pseudomyrmex sp. 1 1

Pseudomyrmex sp1 3 2

Total 32 17

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