Cabra-García et al. - 2012 - Cross-taxon congruence of α and β diversity among five leaf litter...

7/31/2019 Cabra-Garca et al. - 2012 - Cross-taxon congruence of and diversity among five leaf litter arthropod groups i

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O R I G I N A L P A P E R

Cross-taxon congruence ofa and b diversity among five

leaf litter arthropod groups in Colombia

Jimmy Cabra-Garca Christian Bermudez-Rivas Ana Milena Osorio

Patricia Chacon

Received: 13 January 2011 / Accepted: 17 February 2012 Springer Science+Business Media B.V. 2012

Abstract In this study a and b diversity patterns of five leaf litter arthropod groups (ants,

predatory ants, oribatid mites, spiders and other arachnids) were described and compared

in 39 sampling patches of a transformed landscape in southwestern Colombia, that rep-

resented five vegetation types: secondary forest, riparian forest, giant bamboo forest,

pasture and sugarcane crop. It was also assessed whether some taxa could be used as

diversity surrogates. A total of 6,765 individuals grouped in 290 morphospecies were

collected. Species richness in all groups was lower in highly transformed vegetation types(pasture, sugarcane crop) than in native ones (forests). In contrast, there were no clear

tendencies ofb diversity among vegetation types. Considering sampling patches, 0.142%

of the variation in a diversity of one taxonomic group could be explained from the a

diversity of another, and 0.233% of the variation of b diversity of a given taxon was

explained by that in other groups. Contrary to recent findings, we concluded that patterns

ofa diversity are more congruent than patterns ofb diversity. This fact could be attributed

to a sampling effect that promotes congruence in a diversity and to a lack of a clear

regional ecological gradient that could promote congruent patterns ofb diversity. We did

Electronic supplementary material The online version of this article (doi:10.1007/s10531-012-0259-5)contains supplementary material, which is available to authorized users.

J. Cabra-Garca (&) C. Bermudez-Rivas A. M. Osorio P. Chacon

Grupo de investigacion en Biologa, Ecologa y Manejo de Hormigas, Seccion de Entomologa,

Departamento de Biologa, Universidad del Valle, A. A. 25360 Cali, Colombia

e-mail: [email protected]

C. Bermudez-Rivas


A. M. Osorio


P. Chacon


Present Address:

J. Cabra-Garca

Departamento de Zoologia, Instituto de Biociencias, Universidade de Sao Paulo,

Sao Paulo CEP: 05508-090, Brazil

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DOI 10.1007/s10531-012-0259-5
http://dx.doi.org/10.1007/s10531-012-0259-5http://dx.doi.org/10.1007/s10531-012-0259-5


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not find evidence for an ideal diversity surrogate although diversity patterns of predatory

ants had the greatest congruencies. These results support earlier multi-taxon evaluations in

that conservation planning should not be based on only one leaf litter arthropod group.

Keywords Ants

Arachnids

Cross-taxon congruence

Diversity indicatorsMulti-taxa inventories Southwestern Colombia Surrogate taxa Tropical dry forest

Introduction

Shortage of knowledge on biodiversity, especially in tropical environments (Lawton et al.

1998; Wrigth 2005), coupled with rapid rates of species loss induced by human activities,

is a major challenge for conservation biology (Negi and Gadgil 2002; Brooks et al. 2002;

McGeoch 2007). This challenge can be faced effectively only by obtaining as much

information as possible with minimum requirements in time and resources (McGeoch

2007). In this context the assessment of biodiversity indicators on multiple scales has

gained great momentum over the last decade (Caro and Odoherty 1999; Duelli and Obrist

2003; Wolters et al. 2006; McGeoch 2007). In particular, different arthropod groups have

attracted interest as potential indicators of biodiversity because of their significant con-

tribution to global species richness, biomass and a large variety of ecological functions and

lifestyles (Kotze and Samways 1999; Moritz et al. 2001; Sauberer et al. 2004; Schulze

et al. 2004; Lovell et al. 2007; Basset et al. 2008a, b; Kessler et al. 2009; Maleque et al.

2009; Uehara-Prado et al. 2009; Finch and Loffler 2010; Leal et al. 2010; Vasquez-Velez

et al. 2010).The use of biodiversity indicators is based on the premise that across large areas the

number of species in one well-studied taxon correlates well with the number of species in

other lesser known taxa (Schall and Pianka 1978; Prendergast and Eversham 1997). It is

assumed that this taxon will positively reflect the patterns and processes of biological

diversity in the landscape (Kotze and Samways 1999). According to Gaston (1996a, b),

there are four possible explanations for richness correlation between different taxa: (1)

random coincidence, (2) interactions between taxa, (3) similar responses to common

factors and (4) responses to different environmental factors that are spatially covariant.

Ants and arachnids, especially spiders, have been among the most commonly used

groups to evaluate the effect of environmental changes (fragmentation, pollution andhabitat loss) on the diversity of arthropod communities (Marc et al. 1999; Alonso 2000;

Maleque et al. 2009). However, the species richness patterns of these groups have not been

consistent as there have been congruent responses in some scenarios (Weaver 1995;

Niemela et al. 1996; Sauberer et al. 2004; Leal et al. 2010), while in others no statistically

significant correlation has been detected (Oliver and Beattie 1996; Kotze and Samways

1999). Moreover, this trend does not apply only for these taxa; various studies have not

found consistent patterns of variation in diverse plants, vertebrates and invertebrates

(Lawton et al. 1998; Oliver et al. 1998; Kati et al. 2004; Heino et al. 2005; Barlow et al.

2007; Kessler et al. 2009; Heino et al. 2009; Heino 2010). Nevertheless, the search for

indicator groups and their assessment across different environments and spatial scales

remains an important issue because of the potential for simplifying data requirements for

conservation planning (Larsen et al. 2009; Caro 2010; Lewandowski et al. 2010; Toranza

and Arim 2010).

In the Tropics, assessments of congruency across invertebrate taxa to identify potential

surrogates have focused mainly on humid tropical forests (Lawton et al. 1998; Barlow et al.

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2007; Basset et al. 2008a; Uehara-Prado et al. 2009; Leal et al. 2010). In contrast,

investigations in dry ecosystems are scarce. The tropical dry forest is one of the most

endangered ecosystems in the Neotropics (Janzen 1988). Given the fertility of its soils, it

has undergone intense transformation for benefiting urban populations in the form of

agriculture and livestock (Alvarez et al. 1998). Recent fragmentation studies in the upperCauca River basin (southwestern Colombia), showed that forests (10,716 ha) represent

only 1.76% of the landscape, and other native elements such as giant bamboo forests

account for barely 1%; whereas crops (52%) and pastures (36%) dominate (Arcila 2007).

Because of the current context, the upper Cauca River basin provides a framework suitable

for assessing potential biodiversity indicators.

According to Kotze and Samways (1999), epigeic invertebrates are appropriate in multi-

taxa conservation-oriented research because they (1) include two of the most studied

terrestrial taxa (Carabidae and Formicidae); (2) are associated with one of the most

complex habitat systems, i.e. the soil; and (3) are easily captured using standard techniques

such as pitfall trapping. In this paper we describe and compare a and b diversity of five leaf

litter arthropod groups (ants, predatory ants, oribatid mites, spiders and other arachnids) in

39 sampling patches of the upper basin of the Cauca River valley. In addition, we assess

the congruence of a and b diversities among groups, explore the effect of sampling

completeness in congruence analyses, and evaluate whether some taxa can be used as

diversity surrogates.

Materials and methods

Study area

The study was carried out in the upper basin of the Cauca River Valley, which comprises

three provinces in southwestern Colombia (from the northern Cauca Province to central

Risaralda Province) (Fig. 1a). This valley is 220 km long and 1020 km wide with a total

area of 420,000 ha. According to Holdridges life zone classification system, this region

belongs to the tropical dry forest life zone. It is located at altitudes from 900 to 1,100 masl,

the average annual temperature is above 24C, and the average annual rainfall ranges from

1,000 to 2,000 mm (CVC 1990). Ten sites with one tropical dry forest fragment were

selected across the basin (Fig. 1a). These forests are secondary (originated from clear-cutharvesting followed by a natural tree regeneration) with relatively well-structured canopies

approximately 25 m in height, dominated by tree species such as Anacardium excelsum,

Xilopia ligustrifolia, Laetia americana, Ficus spp., Cecropia sp. and Ceiba petandra (CVC

1990; Armbrecht and Ulloa-Chacon 2003). At each site sampling patches were identified

within a radius of 1,500 m from the centroid of the dry forest fragment (Fig. 1b). These

patches were grouped into the following vegetation types: sugarcane crop, grassland, giant

bamboo forest and riparian forest, comprising a total of 39 sampling patches (Supple-

mentary material 1).

Sampling methods

Fieldwork was conducted between October and December 2005 and FebruaryMay 2006,

covering rainy and dry seasons. We applied the sampling protocol used to characterize the

diversity of ants and staphylinids in rural landscapes of the Andean region (Jime nez et al.

2008; Abada et al. 2010; Vasquez-Velez et al. 2010) and the Cauca River geographic

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Fig. 1 Study area. a Geographic site of the upper Cauca River basin, southwestern Colombia. b An

example of a sampling site: A fragment of tropical dry forest and surrounding sampling patches located

within a radius of 1,500 m from the centroid of the forest fragment

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b Diversity

Similarities in the species composition of sampling patches pairs (all possible combina-

tions of the 39 sampling patches) were quantified with the quantitative Srensen similarity

index (also known as BrayCurtis index) (bobs) according to Kessler et al. (2009). Tocorrect for incomplete sampling, the similarity index of Chao et al. (2005) was used, which

is based on the foregoing index but includes an estimate of incompleteness (best). Raw

abundance values were transformed to the fourth root in order to standardize abundance

between taxa (Su et al. 2004); in the case of ants these values correspond to presence/

absence data as stated above. Similarities in the species composition among vegetation

types were also evaluated.

Correlation analyses

In our analyses a diversity correspond to the diversity within sampling patches and b

diversity corresponds to the diversity among sampling patches. We used the Spearman

rank correlation (due to the absence of normality or homoscedasticity in some variables) to

test for cross-taxon a diversity correlations (aobs, aest) and the Mantel test for cross-taxon b

diversity correlations (bobs, best) and for cross-taxon Da diversity correlations (Daobs,

Daest). Because of a possible spatial effect on the correlation coefficient values (distance

between sampling patches), we tested spatial autocorrelation using the Mantel test to

correlate a matrix of geographical distance between sampling patches and matrices of

differences in a diversity (Da) and b diversity. This multivariate measure evaluates the null

hypothesis of no relationship between two similarity or dissimilarity matrices (Su et al.2004; Kessler et al. 2009). Probabilities are assigned by repeatedly randomizing the

arrangement of similarity matrices, recalculating correlation coefficients each time and

comparing the observed correlation value to the randomly generated ones (Kessler et al.

2009). All Mantel tests were conducted with the XLSTAT program (Addinsoft 2008),

using 9,999 randomizations. Mantel analyses were also used to assess the relationship

between Da diversity and b diversity.

We calculated mean sampling completeness (i.e. the ratio between observed and mean

estimated richness) for each taxon. To assess the potential impact of mean sampling

completeness in correlation analyses, we correlated this variable with the correlation

coefficients obtained in each combination (e.g. predatory ants/spiders), using the lower of

the two values for mean sampling completeness (Kessler et al. 2009). Based on Leal et al.

(2010) a surrogate was defined as being reasonable if it explained[60% of the variation

in total species richness, good if it explained[70%, and excellent if it explained

[80%.

Results

A total of 6,765 individuals grouped into 290 morphospecies were collected (Supple-

mentary material 2). The most abundant taxa were ants and oribatid mites, which

accounted for 89.66% of all captures. The groups with the highest number of morpho-

species were ants and spiders with 54.13 and 22.41%, respectively, of the total registered

(Table 1). The regional mean sampling completeness ranged from 55% for other arachnids

to 87% for predatory ants (Table 1).

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Diversity patterns across vegetation types

In general richness patterns were consistent in all taxa; species richness tended to decrease

in highly intervened vegetation types (pastures and sugarcane crops) in relation to native

ones (forests) (Fig. 2). This trend was statistically significant in ants and other arachnids

(Fig. 2). All taxa evaluated showed the highest value of species richness in secondary

forest and the lowest value in sugarcane crops, except for other arachnids, which had the

lowest richness in pastures. The average observed similarity (bobs) between vegetation

types ranged from 13% (other arachnids) to 54% (ants); average estimated similarity (best)

ranged from 27% (other arachnids) to 94% (ants).

Correlation analysis

a Diversity

Correlation coefficients of aobs diversity varied considerably (Table 2). Four of the 10

pairwise comparisons were significant and all were positive, with ants and predatory ants

most strongly correlated (q = 0.65; P\0.0001). Similar results were obtained with Daobsdiversity although the number of significant correlations was higher in relation to

aobs (Table 3). Correlation coefficients for aest and Daest tended to decrease in relation

to aobs and Daobs (Fig. 3); likewise, the number of significant correlations decreased from 4to 2 (aobs vs. aest) and from 9 to 8 (Daobs vs. Daest) (Tables 2, 3).

No significant correlations were found between mean sampling completeness and

correlation coefficients in any diversity measure (aobs q = 0.25, P = 0.49; aest q = -0.25,

P = 0.48; Daobs q = 0.31, P = 0.37; Daest q = 0.16, P = 0.66). Geographical distance

between sampling patches was not correlated with any a diversity measure (Table 4).

b Diversity

Eight of the 10 pairwise comparisons ofbobs were significant, all of which were positive.Correlation coefficients ofbobs diversity ranged from 0.05 to 0.49 (Table 5), similar results

were obtained with best diversity although the correlation values were somewhat lower.

Geographical distance between sampling patches was correlated with beta diversity

measures across all taxa, except for predatory ants. All except one of the significant

correlations were negative (Table 4).

Table 1 Richness, abundance and mean sampling completeness of ants and arachnids in 39 samplingpatches of the upper Cauca River basin

Taxon Abundance aobs aest Regional MSC (%) RSC (%)

Ants 3,107 135 169.36 79.71 3389Predatory ants 569 22 25.31 86.92 42100

Oribatid mites 2,390 41 58.17 70.48 33100

Spiders 504 65 117.55 55.30 41100

Other arachnids 195 27 49.04 55.06 43100

MSC mean sampling completeness, RSC range of mean sampling completeness for individual sampling

patches

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No matter which diversity measure was used (a or b), no individual taxon reached any

surrogate threshold ([60,[70, 80%[of the variation explained). In general cross-taxon

a-diversity correlations were higher than cross-taxon b-diversity correlations (Fig. 3).

Fig. 2 Species richness (aobs) of taxa evaluated across vegetation types. The box plot shows median (blacksquare), 50% (box limits) and 95% of all values (brackets). Different letters denote significant differences

(P\0.05). Patterns of estimated richness (aest) show roughly similar patterns and are therefore not shown.SF secondary forest, BF giant bamboo forest, RF riparian forest, SC sugarcane crop, P pasture

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a Diversity versus b diversity

All comparisons of patterns of a and b diversity resulted in low correlation values,

ranging from q = -0.16 to q = 0.06, averaging q = -0.01 for Daobs versus bobs and from

q = -0.16 to q = 0.09, averaging q = -0.02 for Daest versus best.

Discussion

a Diversity

Contrary to the results reported by other authors (Oliver and Beattie 1996; Kotze and

Samways 1999), a diversity patterns across taxa were in general consistent (Fig. 2).

Vegetation types with canopy layer such as forests had the highest richness values in

relation to homogeneous and highly intervened vegetation types such as pastures and sugar

cane crops.

Variations in a diversity are primarily related to local environmental factors and

interactions between populations (Halffter and Moreno 2005). In this context the so-called

habitat heterogeneity hypothesis (Tews et al. 2004), becomes important in explaining

the diversity patterns observed in this study. This hypothesis assumes that the structural

complexity of habitats may provide more niches and diverse ways of exploiting the

environmental resources, thereby increasing species diversity (Tews et al. 2004). Thus

Table 2 Correlations (P values) ofa-diversity (species richness per sampling patch) among the five studygroups

Ants Predatory ants Oribatid mites Spiders Other arachnids

Ants 0.3 0.18 0.21 0.41*Predatory ants 0.65*** 0.25 -0.12 0.38*

Oribatid mites 0.41* 0.31 0.08 0.19

Spiders 0.28 -0.03 0.15 0.25

Other arachnids 0.58** 0.43* 0.13 0.18

Values above the diagonal were based on the estimated richness values (aest); values below, on the observedrichness values (aobs)

* P\0.05, ** P\0.001, *** P\0.0001

Table 3 Correlations (P values) ofDa-diversity (differences in species richness per sampling patch) amongthe five study groups


Ants 0.35** 0.16* 0.11* 0.31**

Predatory ants 0.68*** 0.22** -0.19* 0.30**

Oribatid mites 0.4** 0.25** 0.03 0.08

Spiders 0.25** -0.03 0.14* 0.12*

Other arachnids 0.47*** 0.4** 0.12* 0.10*

Values above the diagonal were based on the estimated richness values (Daest); values below, on theobserved richness values (Daobs)

* P\0.05, ** P\0.001, *** P\0.0001

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similarity in richness patterns (Fig. 2) may reflect a common trend of the evaluated taxa

against an increase in habitat heterogeneity, from the highly intervened vegetation types to

the native ones.

Vegetation of a given environment determines certain characteristics of the leaf litter

layer such as nutritional quality, depth and heterogeneity (Facelli and Pickett 1991; Cor-

nelissen et al. 1999, Koivula et al. 1999), which directly affect the epigeic arthropod

assemblages analyzed (Uetz 1979; Bultman and Uetz 1982; Bultman et al. 1982; Hansen

2000; McGlynn et al. 2009) by reducing or increasing factors such as competitive

exclusion between species that inhabit this microenvironment (Wagner et al. 2003; Achury

Fig. 3 Correlation (P) values of a diversity (the number of species per sampling patches), Da diversity

(differences in species numbers between sampling patches), and b diversity (similarities in the speciescomposition between sampling patches) of each of the five study groups relative to the other 4 groups. The

box plots show medians (black square), 50% (the box limits) and 95% of all values (brackets). A ants, PA

predatory ants, OM oribatid mites, S spiders, OA other arachnids

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et al. 2008). Thus, further analyses of these properties in the leaf litter are needed to

establish to what extent it contributes to the richness patterns of the groups evaluated.

In accordance with Kessler et al. (2009), patterns of species richness were fairly similar,

regardless of the measure used (aobs, aest, Daobs, Daest). Predatory ants and the rest of the

ant assemblage had the strongest significant correlations in almost all cases (Tables 4, 5).

Despite the variation of the species richness (aobs) of ants that can be explained by therichness of predatory ants is under our defined ranges for a diversity surrogate (\60%),

both taxa appear to respond similarly to the conditions of the landscape in terms of species

richness.

Two investigations evaluated the potential use of ants as biodiversity indicators in the

upper Cauca River basin: Armbrecht and Ulloa-Chacon (2003) reported the little fire ant

Wasmannia auropunctata (Roger 1863) as a negative indicator of ant diversity in 14 dry

forest fragments, and Chacon et al. (2008) suggested predatory ants as positive indicators

of ant diversity in 10 dry forest fragments. The latter authors suggest that congruence in

richness patterns of these taxa could be related to the fact that the two groups share similar

microhabitat requirements for nesting. Our study is the second investigation that reports asignificant and positive relationship between predatory ant species richness and ant species

richness in the basin; nevertheless the group did not reach the established surrogate

thresholds.

We found different degrees of correlations (Table 2), which might be associated with

some of the explanations suggested by Gaston (see Introduction section); however a

Table 4 Mantel correlations (P values) of diversity measures and geographical distance between samplingpatches

Taxon Daobs Daest bobs best

Ants-

0.056-

0.031-

0.118*-

0.09*Predatory ants -0.049 -0.044 0.004 0.005

Oribatid mites -0.061 -0.059 -0.09* -0.12*

Spiders -0.033 -0.026 -0.17* -0.17*

Other arachnids -0.005 -0.006 0.26** -0.13*

* P\0.05, ** P\0.001

Table 5 Mantel correlations (P values) of b-diversity (differences in species composition between sam-

pling patches) among the five study groups


Ants 0.37** 0.14* 0.18* 0.12*

Predatory ants 0.58** 0.25** 0.04 0.03

Oribatid mites 0.44** 0.28** 0.12* 0.02

Spiders 0.16* 0.06 0.10* 0.17*

Other arachnids 0.32** 0.25** 0.10* 0.05

Values above the diagonal were based on Chaos Srensen similarity estimator (best); values below, on

Srensens quantitative (BrayCurtis) similarity index (bobs)* P\0.05, ** P\0.001

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detailed assessment of environmental factors is necessary to explore mechanisms behind of

the congruence and/or inconsistencies between the patterns, and further research is

required on the natural history of the groups. First of all, the distance between sampling

patches had no significant effect on the variation in the richness of the taxa (Table 4) so the

spatial factor in terms of site and distance between sampling patches can be eliminated asan explanation for the observed patterns. Another factor that can contribute to consistency

in richness patterns is a similar response of each taxon to an increment in area (the species-

area relationship); nevertheless a preliminary exploration of this subject did not suggest a

linear relationship ofaobs with patch area (Bermudez-Rivas unpublished data).

In our comparisons, the range of the variation of species richness of a given group that

could be explained by the richness of another was 0.142%. These values are within the

range reported by Schulze et al. (2004) for five groups in Indonesia, Barlow et al. (2007)

for 15 groups in Brazilian Amazonia and Leal et al. (2010) for nine groups in Brazilian

Atlantic forest and Caatinga, and are higher than values reported in other studies (Lawton

et al. 1998; Kessler et al. 2009). Some factors that can influence the absence of consensus

in the assessment of surrogate taxa are variation in (1) area in which correlations are

assessed (Weaver 1995; Negi and Gadgil 2002; Sauberer et al. 2004; Wolters et al. 2006;

Hess et al. 2006), (2) sampling protocols (Sauberer et al. 2004; Leal et al. 2010) and (3)

measures for the consistency of diversity patterns (Su et al. 2004; Barlow et al. 2007;

Lovell et al. 2007; Basset et al. 2008a; Leal et al. 2010; Grantham et al. 2010).

It is interesting to note that the correlation coefficients obtained with aest tended to be

lower in relation to that ofaobs which is consistent with some of the comparisons reported

by Kessler et al. (2009). This fact has a close relationship with mean sampling com-

pleteness, because when we compare groups with distinct sampling completeness,Daobs

will be necessarily different in relation with Daest which changes correlation patterns.

b Diversity

Cross-taxon b-diversity correlations were lower than cross-taxon a-diversity correlations

(Fig. 3). All correlations were positive as occurred in earlier studies (Barlow et al. 2007;

Kessler et al. 2009). In our comparisons, only 0.2 (spiders vs. other arachnids)33% (ants

vs. predatory ants) of the variance of similarities in the species composition of a given

group could be explained by the similarity of another. These values are in the range

reported by Barlow et al. (2007) and Uehara-Prado et al. (2009). Kessler et al. (2009) statethat the b diversity of all taxa along an ecological gradient (land use, elevation, climate,

soil fertility, etc.) will tend to shift more strongly when the ecological conditions are more

divergent.

Nevertheless, the highly modified area (upper Cauca River basin) where we evaluated

correlations is a complex landscape with no clear regional ecological gradient. Each

sampling patch and its surrounding matrix are a complex and unique mosaic landscape

where interaction between species occurs. This could be a reason for the lower cross-taxon

correlations in b diversity, which is contrary to results in recent publications (Su et al.

2004; Kessler et al. 2009). A pattern that seems to be consistent across all taxa is thatb diversity contributes in a large proportion to gamma diversity (Bermudez-Rivas

unpublished data), a pattern that have been found for spiders and predatory ants (Arcila-

Cardona et al. 2008; Cabra-Garca et al. 2010). Our results suggest that distance between

sampling patches (Table 4) explain a very low percentage (0.0066.760%) of the variation

ofb diversity across the sampling patches.

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a versus b diversity

Our results suggest that, on average, only 0.015% ofb diversity variation of a given group

could be explained by the patterns ofa diversity of another group. This result is congruent

with that reported by Kessler et al. (2009). Contrary to recent findings (Barlow et al. 2007;Kessler et al. 2009; Uehara-Prado et al. 2009), cross-taxon a-diversity correlations were

higher than cross-taxon b-diversity correlations. As proposed by Leal et al. (2010), the fact

that the groups evaluated in this study were collected by the same method of capture could

promote congruence in a-diversity measures given that several studies using different

collection methods at different spatial scales tended not to detect correlations between

groups (Leal et al. 2010). It is likely that taxa living and operating in the same microhabitat

have more congruent diversity patterns than those from different microhabitats (Leal et al.

2010).

To our knowledge, this is the first approach in Colombia that aims to assess congruence

in a and b diversity patterns of different leaf litter arthropods (multi-taxa approach) in a

tropical dry forest landscape. Therefore this research can serve as a baseline for comparing

diversity patterns from other arthropod taxa in order to identify robust surrogates of

diversity across different spatial scales. Ideally, conservation planning would be based on

detailed surveys, including a thorough knowledge of the affected species life histories,

distributions and interactions with other species and the physical environment (Favreau

et al. 2006). In the Colombian context, however, detailed data are costly to accumulate and

cannot be obtained in the timeframe within which landscape-altering decisions are made.

For this reason assessment of diversity congruence indicators is a very important tool for

guiding conservation planning.

Conclusions

Although no group reached the surrogate thresholds, we found a significant and positive

relationship between predatory ants and ants species richness. Future research needs to

evaluate whether this pattern is consistent regardless of scale, habitat, sampling method

and diversity measures used. Our results suggest that conservation planning in the upper

Cauca River basin should not be based on only a single leaf litter arthropod taxon given

that each group appears to be affected by different factors to a different extent, which couldbe related to the lack of strong congruencies (Caro 2010).

Acknowledgments Biologists Angela Arcila, Nestor Zuniga, Paloma Vejarano, Pilar Lopez and Rafael

Achury participated in the fieldwork. Researchers Fernando Fernandez, Eduardo Florez, David Luna, Jairo

Moreno, Osvaldo Villareal, Lillan Sendales, Alexandra Sierra, Wojciech Niedbaa and Jari Niemela con-

tributed with taxonomic determination and provided literature. Three anonymous reviewers and the Asso-

ciate Editor Jari Niemela provided detailed comments and important suggestions on an earlier version of the

paper. The program Joven Investigadores e Innovadores Virginia Gutierrez de Pineda from Colciencias

and Universidad del Valle funded the participation of J. Cabra-Garca and A. M. Osorio. The Instituto de

Investigacion de Recursos Biologicos Alexander von Humboldt (IAvH) funded part of this project

(Agreement No. 05-01-24843-054CE).

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