cabra-garcía et al. - 2012 - cross-taxon congruence of α and β diversity among five leaf litter...
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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
e-mail: [email protected]
A. M. Osorio
e-mail: [email protected]
P. Chacon
e-mail: [email protected]
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
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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 Predatory ants Oribatid mites Spiders Other arachnids
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 Predatory ants Oribatid mites Spiders Other arachnids
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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